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Water, Volume 13, Issue 5 (March-1 2021) – 166 articles

Cover Story (view full-size image): Exemplary for Central Asian water management challenges, the data-scarce Ili-Balkhash basin shared between China and Kazakhstan is confronted with climate change and shifts in water demand as a result of land use changes under the Belt and Road Initiative. This study assesses reliability of environmental flows of the Ili river to Lake Balkhash using a scenario-based modeling approach. The results suggest that the basin is historically vulnerable to environmental shortages, and potentially growing competition for water resources between domestic and up- and downstream users may be exacerbated by climatic conditions. The modeling tool and outcomes support transboundary management and local decision making. View this paper
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26 pages, 4813 KiB  
Article
Distributed-Framework Basin Modeling System: II. Hydrologic Modeling System
by Gang Chen, Wenjuan Hua, Xing Fang, Chuanhai Wang and Xiaoning Li
Water 2021, 13(5), 744; https://doi.org/10.3390/w13050744 - 9 Mar 2021
Cited by 7 | Viewed by 3362
Abstract
A distributed-framework hydrologic modeling system (DF-HMS) is a primary and significant component of a distributed-framework basin modeling system (DFBMS), which simulates the hydrological processes and responses after rainfall at the basin scale, especially for non-homogenous basins. The DFBMS consists of 11 hydrological feature [...] Read more.
A distributed-framework hydrologic modeling system (DF-HMS) is a primary and significant component of a distributed-framework basin modeling system (DFBMS), which simulates the hydrological processes and responses after rainfall at the basin scale, especially for non-homogenous basins. The DFBMS consists of 11 hydrological feature units (HFUs) involving vertical and horizontal geographic areas in a basin. Appropriate hydrologic or hydraulic methods are adopted for different HFUs to simulate corresponding hydrological processes. The digital basin generation model is first developed to determine the essential information for hydrologic and hydraulic simulation. This paper mainly describes two significant HFUs contained in the DF-HMS for hydrologic modeling: Hilly sub-watershed and plain overland flow HFUs. A typical hilly area application case study in the Three Gorges area is introduced, which demonstrates DF-HMS’s good performance in comparison with the observed streamflow at catchment outlets. Full article
(This article belongs to the Special Issue Modelling Hydrologic Response of Non­-homogeneous Catchments)
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Figure 1

Figure 1
<p>Structure of distributed-framework basin modeling system including different hydrological feature units or hydrological feature units (HFUs) and hydrologic processes.</p> Full article ">Figure 2
<p>(<b>A</b>) Codes for runoff concentration directions. (<b>B</b>) Flowchart of area accumulation method for runoff concentration path generation. (<b>C</b>) Scheme of fastest runoff concentration path method involving with four cells (0–3) having 5 positive slopes (S<sub>01</sub>, S<sub>02</sub>, S<sub>03</sub>, S<sub>12</sub>, and S<sub>32</sub>).</p> Full article ">Figure 3
<p>Sub-watersheds generated by the digital basin generation model in the Three Gorges area.</p> Full article ">Figure 4
<p>(<b>a</b>) Land cover and (<b>b</b>) river network in the Taihu basin.</p> Full article ">Figure 5
<p>Logic structure diagram of construction land runoff generation model.</p> Full article ">Figure 6
<p>(<b>a</b>) Sketch map of division of overland area in plain area; (<b>b</b>) diagram of river-network polygon catchment areas of rivers.</p> Full article ">Figure 7
<p>(<b>a</b>) Location of the study area and (<b>b</b>) drainage map of Three Gorges area.</p> Full article ">Figure 8
<p>Generalized the main river network in the Three Gorges area.</p> Full article ">Figure 9
<p>The structure of the Xinanjiang model without the impermeable area (<b>a</b>) and the diagrammatic sketch of the saturation excess runoff generation mechanism based on soil water storage capacity curve (<b>b</b>).</p> Full article ">Figure 10
<p>Rainfall distribution and simulated and observed discharge timeseries at four representative hydrological stations in 2005.</p> Full article ">Figure 11
<p>Rainfall distribution and simulated and observed discharge timeseries at four representative hydrological stations in 2006.</p> Full article ">Figure 12
<p>Comparison of simulated and observed outflows (m<sup>3</sup>/s) from the Three Gorges Reservoir in 2007 and 2008.</p> Full article ">
21 pages, 4534 KiB  
Article
A Parametric Approach for Determining Fishway Attraction Flow at Hydropower Dams
by Patrick Heneka, Markus Zinkhahn, Cornelia Schütz and Roman B. Weichert
Water 2021, 13(5), 743; https://doi.org/10.3390/w13050743 - 9 Mar 2021
Cited by 7 | Viewed by 3739
Abstract
High discharges at hydropower plants (HPP) may mask fishway attraction flows and, thereby, prevent fishes from locating and using fishways critical for their access to upstream spawning and rearing habitats. Existing methods for determining attraction flows are either based on simple guidelines (e.g., [...] Read more.
High discharges at hydropower plants (HPP) may mask fishway attraction flows and, thereby, prevent fishes from locating and using fishways critical for their access to upstream spawning and rearing habitats. Existing methods for determining attraction flows are either based on simple guidelines (e.g., a proportion of HPP discharge) that cannot address the spatial and temporal complexity of tailrace flow patterns or complicated studies (e.g., combinations of detailed hydraulic and biological investigations) that are expensive and time-consuming. To bridge this gap, we present a new, intermediate approach to reliably determine attraction flows for technical fishways at small to medium-sized waterways (mean annual flow up to 400 m3/s). Fundamental to our approach is a design criterion that the attraction flow should maintain its integrity as it propagates downstream from the fishway entrance to beyond the highly turbulent zone characteristic of HPP tailraces to create a discernable migration corridor connecting the fishway entrance to the downstream river. To implement this criterion, we describe a set of equations to calculate the width of the entrance and the corresponding attraction discharge. Input data are usually easy to obtain and include geometrical and hydraulic parameters describing the target HPP and its tailrace. To confirm our approach, we compare model results to four sites at German waterways where the design of attraction flow was obtained by detailed experimental and numerical methods. The comparison shows good agreement supporting our approach as a useful, intermediate alternative for determining attraction flows that bridges the gap between simple guidelines and detailed hydraulic and biological investigations. Full article
(This article belongs to the Special Issue Fish Passage at Hydropower Dams)
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Figure 1

Figure 1
<p>(<b>a</b>) Typical scheme of a hydropower dam at federal waterways in Germany. (<b>b</b>) Photograph of turbine tailrace of Lauffen (Neckar River, Germany).</p> Full article ">Figure 2
<p>Scheme of fishway entrance at hydropower plant tailwater. Entrance bay and attraction flow are used to create a migration corridor where flow conditions meet hydraulic requirements such as directional flow and comparatively low turbulence; <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mrow> <mi>A</mi> <mi>F</mi> </mrow> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> length of a coherent attraction flow jet; <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mrow> <mi>T</mi> <mi>Z</mi> </mrow> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> length of the turbulent zone.</p> Full article ">Figure 3
<p>Schematic longitudinal section of the turbulent zone in a tailrace downstream of a vertically mounted Kaplan turbine with elbow draft tube; <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mrow> <mi>T</mi> <mi>Z</mi> </mrow> </msub> <mo>=</mo> </mrow> </semantics></math> length of the turbulent zone; <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mrow> <mi>v</mi> <mi>e</mi> <mi>r</mi> <mi>t</mi> <mi>i</mi> <mi>c</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math>= vertical velocity; <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>m</mi> </msub> <mo>=</mo> </mrow> </semantics></math> bulk mean velocity at draft tube exit section; tailwater levels <math display="inline"><semantics> <mrow> <mi>U</mi> <msub> <mi>W</mi> <mrow> <mn>30</mn> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>U</mi> <msub> <mi>W</mi> <mrow> <mn>330</mn> </mrow> </msub> </mrow> </semantics></math> with 30 and 330 days of nonexceedance and <math display="inline"><semantics> <mrow> <mi>U</mi> <msub> <mi>W</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> at design discharge of HPP; <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>D</mi> <mi>T</mi> </mrow> </msub> <mo>=</mo> </mrow> </semantics></math> water depth at draft tube exit section.</p> Full article ">Figure 4
<p>Normalized length of turbulent zone <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mrow> <mi>T</mi> <mi>Z</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>h</mi> <mrow> <mi>D</mi> <mi>T</mi> </mrow> </msub> </mrow> </semantics></math>, as recorded from site inspections, for various bulk velocities <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>m</mi> </msub> </mrow> </semantics></math> at the draft tube exit section for horizontally mounted turbines (HMT) and vertically mounted turbines (VMT). Linear fit from Equation (2) with <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mrow> <mi>v</mi> <mi>e</mi> <mi>r</mi> <mi>t</mi> <mi>i</mi> <mi>c</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mn>0.56</mn> <mo> </mo> <mi mathvariant="normal">m</mi> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math> for VMT and point estimate at <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>1.58</mn> <mo> </mo> <mi mathvariant="normal">m</mi> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math> with <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mrow> <mi>v</mi> <mi>e</mi> <mi>r</mi> <mi>t</mi> <mi>i</mi> <mi>c</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mn>0.7</mn> <mrow> <mo> </mo> <mi mathvariant="normal">m</mi> </mrow> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math> for HMT.</p> Full article ">Figure 5
<p>Normalized half-length <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mi>x</mi> </msub> <mo>/</mo> <mi>b</mi> </mrow> </semantics></math> of turbulent rectangular surface jet for aspect ratios <math display="inline"><semantics> <mrow> <mi>b</mi> <mo>/</mo> <mi>h</mi> </mrow> </semantics></math> from 0 to 2. Different markers refer to results of published investigations [<a href="#B32-water-13-00743" class="html-bibr">32</a>,<a href="#B39-water-13-00743" class="html-bibr">39</a>,<a href="#B40-water-13-00743" class="html-bibr">40</a>,<a href="#B41-water-13-00743" class="html-bibr">41</a>,<a href="#B42-water-13-00743" class="html-bibr">42</a>].</p> Full article ">Figure 6
<p>Schematic sketch to visualize the recirculation zone and reverse flow present in a fishway entrance bay; <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mi>r</mi> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> length of recirculation zone; <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>r</mi> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> reverse flow velocity; <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>a</mi> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> mean ambient velocity; <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>r</mi> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> lateral offset of fishway entrance bay.</p> Full article ">Figure 7
<p>Reduction of the normalized propagation length <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mrow> <mi>x</mi> <mo>,</mo> <mi>a</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>L</mi> <mi>x</mi> </msub> </mrow> </semantics></math> of turbulent jets in reverse flows for velocity ratios <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>r</mi> </msub> <mo>/</mo> <msub> <mi>v</mi> <mn>0</mn> </msub> </mrow> </semantics></math> as obtained from [<a href="#B32-water-13-00743" class="html-bibr">32</a>]. Normalization with propagation length <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mi>x</mi> </msub> </mrow> </semantics></math> without reverse flow. Approximation with an exponential fit (Equation (9)). Comparison with results from 3D-hydrodynamical simulations in the tailrace of Eddersheim Dam.</p> Full article ">Figure 8
<p>Attraction discharge <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mrow> <mi>A</mi> <mi>F</mi> </mrow> </msub> </mrow> </semantics></math> normalized by design discharge of the adjacent turbine <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mo>,</mo> <mi>T</mi> </mrow> </msub> </mrow> </semantics></math> at hydropower plant for a velocity at entrance slot <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mrow> <mi>E</mi> <mi>S</mi> </mrow> </msub> <mo> </mo> <mo>=</mo> <mo> </mo> <mn>1.5</mn> <mrow> <mo> </mo> <mi mathvariant="normal">m</mi> </mrow> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math> and a form factor <math display="inline"><semantics> <mrow> <mi>k</mi> <mo> </mo> <mo>=</mo> <mo> </mo> <mn>1</mn> </mrow> </semantics></math> determined using Equations (10)–(14) for hydraulic conditions at <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> (<b>a</b>) for vertically mounted Kaplan turbines and (<b>b</b>) for horizontally mounted Kaplan turbines;<math display="inline"><semantics> <mrow> <mo> </mo> <msub> <mi>v</mi> <mrow> <mi>a</mi> <mi>t</mi> <mi>t</mi> <mi>r</mi> <mi>a</mi> <mi>c</mi> <mi>t</mi> <mi>i</mi> <mi>o</mi> <mi>n</mi> </mrow> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> minimum attraction velocity; <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> = downstream water depth at the entrance slot; <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>D</mi> <mi>T</mi> </mrow> </msub> <mo> </mo> <mo>=</mo> </mrow> </semantics></math> water depth at draft tube exit section; <math display="inline"><semantics> <mrow> <msub> <mi>A</mi> <mrow> <mi>D</mi> <mi>T</mi> </mrow> </msub> </mrow> </semantics></math> = area of the draft tube exit section.</p> Full article ">Figure 9
<p>Comparison of the results of the present methods and case study results for (<b>a</b>) slot width <math display="inline"><semantics> <mi>b</mi> </semantics></math> and (<b>b</b>) attraction discharge <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mrow> <mi>A</mi> <mi>F</mi> </mrow> </msub> </mrow> </semantics></math>. Where available discharges are compared for three different hydraulic conditions as given in <a href="#water-13-00743-t003" class="html-table">Table 3</a>.</p> Full article ">Figure A1
<p>Top view of tailrace and entrance bay of the hydrodynamic-numerical model of the dam in Eddersheim (Main River); streamlines of the attraction flow (<math display="inline"><semantics> <mrow> <mi>v</mi> <mo> </mo> <mo>&gt;</mo> <mo> </mo> <mn>0.8</mn> <mo> </mo> <mi mathvariant="normal">m</mi> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>) and the mean flow field of the turbine are plotted for (<b>a</b>) turbine discharge = 0 m<sup>3</sup>/s, (<b>b</b>) turbine discharge = 70 m<sup>3</sup>/s.</p> Full article ">Figure A1 Cont.
<p>Top view of tailrace and entrance bay of the hydrodynamic-numerical model of the dam in Eddersheim (Main River); streamlines of the attraction flow (<math display="inline"><semantics> <mrow> <mi>v</mi> <mo> </mo> <mo>&gt;</mo> <mo> </mo> <mn>0.8</mn> <mo> </mo> <mi mathvariant="normal">m</mi> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>) and the mean flow field of the turbine are plotted for (<b>a</b>) turbine discharge = 0 m<sup>3</sup>/s, (<b>b</b>) turbine discharge = 70 m<sup>3</sup>/s.</p> Full article ">Figure A2
<p>Aerial photos of dams on the Neckar River at (<b>a</b>) Lauffen and (<b>b</b>) Kochendorf, the Moselle River at (<b>c</b>) Lehmen, and the Main River at (<b>d</b>) Wallstadt.</p> Full article ">
4 pages, 4213 KiB  
Editorial
Natural Radionuclides as Aquatic Tracers in the Terrestrial and the Coastal/Marine Environment
by Michael Schubert and Jan Scholten
Water 2021, 13(5), 742; https://doi.org/10.3390/w13050742 - 9 Mar 2021
Cited by 1 | Viewed by 2070
Abstract
Investigations in hydrology and hydrogeology are often hampered by a lack of parameters that permit direct observation or monitoring of the processes of interest [...] Full article
(This article belongs to the Special Issue Using Natural Radionuclides as Aquatic Tracers in the Terrestrial and the Coastal/Marine Environment)
►▼ Show Figures

Figure 1

Figure 1
<p>Decay and buildup of radionuclide activity concentrations as function of time.</p> Full article ">Figure 2
<p>Radionuclides suitable as age tracers versus approximately covered age ranges.</p> Full article ">
32 pages, 30439 KiB  
Article
Quaternary Evolution of the Lower Calore and Middle Volturno Valleys (Southern Italy)
by Francesca Filocamo, Natalia Leone, Carmen Maria Rosskopf, Vittoria Scorpio, Santiago Giralt and Pietro Patrizio Ciro Aucelli
Water 2021, 13(5), 741; https://doi.org/10.3390/w13050741 - 9 Mar 2021
Cited by 2 | Viewed by 3188
Abstract
The lower Calore and middle Volturno valleys preserve stratigraphical and morphological evidence and tephrostratigraphic markers particularly suitable for reconstructing the long-term geomorphological evolution of the central-southern Apennines. Aim of our study is to identify the main steps of the Quaternary landscape evolution of [...] Read more.
The lower Calore and middle Volturno valleys preserve stratigraphical and morphological evidence and tephrostratigraphic markers particularly suitable for reconstructing the long-term geomorphological evolution of the central-southern Apennines. Aim of our study is to identify the main steps of the Quaternary landscape evolution of these valley systems and to improve knowledge about the relationships between fluvial processes and tectonics, volcanic activity, climatic and human influences. To this purpose, we carried out an integrated geomorphological and chrono-stratigraphical analysis of identified fluvial landforms and related deposits, integrated by 230Th/234U datings on travertines from the Telese Plain area. The study highlighted in particular: (1) fluvial sedimentation started in the Middle Pleistocene (~650 ka) within valleys that originated in the lower Pleistocene under the control of high-angle faults; (2) extensional tectonics acted during the Middle and Upper Pleistocene, driving the formation of the oldest fluvial terraces and alluvial fans, and persisted beyond the emplacement of the Campanian Ignimbrite pyroclastic deposits (~39 ka); and (3) from the late Upper Pleistocene onwards (<15 ka), the role of tectonics appears negligible, while climatic changes played a key role in the formation of three orders of valley floor terraces and the youngest alluvial fans. Full article
(This article belongs to the Special Issue Fluvial Geomorphology and River Management)
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Figure 1

Figure 1
<p>(<b>a</b>) The Volturno River basin and the analyzed segments of the Volturno and Calore valleys; (<b>b</b>) geological sketch map of the sector of the southern Apennine chain including the middle Volturno and lower Calore valleys. For location and limits, see the white box in (<b>a</b>). In dashed black frames the three study sectors A, B, and C. Legend: (1) Alluvial and lacustrine deposits (Upper Pleistocene–Recent); (2) Volcanic deposits (Upper Pleistocene–Holocene); (3) Travertines (Upper Pleistocene–Holocene?); (4) Eluvial-colluvial, slope, and alluvial fan deposits (Middle Pleistocene–Holocene); (5) Alluvial deposits (Middle–Upper Pleistocene); (6) Slope breccias of Laiano Synthem (Lower Pleistocene); (7) Sands, clays and conglomerates of Ariano Unit (Pliocene); (8) Siliciclastic deposits of Molise and Caiazzo Flysch (Upper Miocene); (9) Varicoloured clays, limestones, marls, and arenites of Sannio Units (Upper Cretaceous–Miocene); (10) Limestones and dolostones of Carbonate Platform Units (Trias–Miocene).</p> Full article ">Figure 2
<p>Geomorphological sketch of sector A.</p> Full article ">Figure 3
<p>Stratigraphical logs of boreholes drilled through the AL deposits. For location, see <a href="#water-13-00741-f002" class="html-fig">Figure 2</a>.</p> Full article ">Figure 4
<p>(<b>a</b>) Schematic geological cross section through the Calore River valley in sector A. See <a href="#water-13-00741-f002" class="html-fig">Figure 2</a> for location; (<b>b</b>) detail of the geological cross section showing the relationships between the colluvial deposits containing reworked Neapolitan Yellow Tuff (NYT) deposits, the T1 and T2 alluvial deposits and the deposits of the third generation of AF along the right valley side.</p> Full article ">Figure 5
<p>(<b>a</b>) Typical outcrop of alluvial unit 1a and (<b>b</b>) detail of a sandy-silty layer in the lower part. The length of the scale is 60 cm; (<b>c</b>) the 648 ± 6 ka <sup>40</sup>Ar/<sup>39</sup>Ar dated Tephra layer (TL) interbedded in the alluvial unit 1a at Masseria Acquafredda.; (<b>d</b>) the Campanian Ignimbrite (CI) pyroclastic flow deposits cropping out in the V.ne Ariola stream valley; (<b>e</b>) massive coarse and medium, poorly rounded polygenic gravels in sandy–silty matrix, cropping out at the top of the oldest HFT remnants; (<b>f</b>) fault plane (FP) in the alluvial unit 1a; (<b>g</b>) decimetric offset in a sandy layer of alluvial unit 1a highlighting a NE–SW oriented fault; (<b>h</b>) dragged pebbles that highlight a NW–SE oriented fault.</p> Full article ">Figure 6
<p>Calore and Volturno rivers longitudinal profiles and reconstruction of valley floor terraces T1–T3.</p> Full article ">Figure 7
<p>Stratigraphical logs of boreholes drilled through the T1 and T2 VFT (For location seethe geomorphological sketches).</p> Full article ">Figure 8
<p>(<b>a</b>) NYT reworked tephra layer in the colluvial deposits covering the T1 terrace; (<b>b</b>) erosional contact (white dotted line) between the deposits of the third AF generation (III AF) and the fluvial deposits of T1 (T1 Fd); (<b>c</b>) heterometric, sub-angular to sub-rounded pebbles of the 3rd AF generation containing recent anthropic artifacts.</p> Full article ">Figure 9
<p>Geomorphological sketch of sector B.</p> Full article ">Figure 10
<p>Schematic geological cross section through the Calore River valley in sector B. For location, see <a href="#water-13-00741-f009" class="html-fig">Figure 9</a>.</p> Full article ">Figure 11
<p>Stratigraphic logs of boreholes drilled in the Telese Plain area on the CI and HFT terraces. For location of boreholes, see <a href="#water-13-00741-f009" class="html-fig">Figure 9</a>.</p> Full article ">Figure 12
<p>(<b>a</b>) One of the escarpment bordering the CI-T towards the Calore River valley floor, showing the contact between the pyroclastic deposits (CI) and the underlying alluvial unit 1a (AL); (<b>b</b>) the Amorosi travertines; (<b>c</b>) the Telese travertines.</p> Full article ">Figure 13
<p>Stratigraphical logs of boreholes drilled on the T-T. For location of boreholes, see <a href="#water-13-00741-f009" class="html-fig">Figure 9</a>.</p> Full article ">Figure 14
<p>Geomorphological sketch of sector C.</p> Full article ">Figure 15
<p>Schematic geological cross section through the Volturno River valley in sector C. For location, see <a href="#water-13-00741-f014" class="html-fig">Figure 14</a>.</p> Full article ">Figure 16
<p>(<b>a</b>) View of T2 and T3 terraces in the Volturno River valley; (<b>b</b>) T3 deposits exposed along the Volturno fluvial scarp; (<b>c</b>) detail of thinly laminated sandy-silty T3 deposits.</p> Full article ">Figure 17
<p>Schematic cross sections (not in scale) illustrating major morpho-evolutive steps (Stages A–G) of the Quaternary landscape evolution reconstructed for the middle Volturno and lower Calore valleys in sectors A, B, and C. The sections refer to the final phase of each stage. From Stage E to Stage G, the cross sections show a zoom of the valley floor areas.</p> Full article ">
13 pages, 1697 KiB  
Article
Nitrogen Leaching and Nitrogen Balance under Differing Nitrogen Fertilization for Sugarcane Cultivation on a Subtropical Island
by Ken Okamoto, Shinkichi Goto, Toshihiko Anzai and Shotaro Ando
Water 2021, 13(5), 740; https://doi.org/10.3390/w13050740 - 9 Mar 2021
Cited by 8 | Viewed by 2754
Abstract
Fertilizer application during sugarcane cultivation is a main source of nitrogen (N) loads to groundwater on small islands in southwestern Japan. The aim of this study was to quantify the effect of reducing the N fertilizer application rate on sugarcane yield, N leaching, [...] Read more.
Fertilizer application during sugarcane cultivation is a main source of nitrogen (N) loads to groundwater on small islands in southwestern Japan. The aim of this study was to quantify the effect of reducing the N fertilizer application rate on sugarcane yield, N leaching, and N balance. We conducted a sugarcane cultivation experiment with drainage lysimeters and different N application rates in three cropping seasons (three years). N loads were reduced by reducing the first N application rate in all cropping seasons. The sugarcane yields of the treatment to which the first N application was halved (T2 = 195 kg ha−1 N) were slightly lower than those of the conventional application (T1 = 230 kg ha−1 N) in the first and third seasons (T1 = 91 or 93 tons ha−1, T2 = 89 or 87 tons ha−1). N uptake in T1 and T2 was almost the same in seasons 1 (186–188 kg ha−1) and 3 (147–151 kg ha−1). Based on the responses of sugarcane yield and N uptake to fertilizer reduction in two of the three years, T2 is considered to represent a feasible fertilization practice for farmers. The reduction of the first N fertilizer application reduced the underground amounts of N loads (0–19 kg ha−1). However, application of 0 N in the first fertilization would lead to a substantial reduction in yield in all seasons. Reducing the amount of N in the first application (i.e., replacing T1 with T2) improved N recovery by 9.7–11.9% and reduced N leaching by 13 kg ha−1. These results suggest that halving the amount of N used in the first application can improve N fertilizer use efficiency and reduce N loss to groundwater. Full article
(This article belongs to the Section Water Quality and Contamination)
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<p>Average monthly climate data of the Japan International Research Center for Agricultural Sciences of Tropical Agricultural Research Front (JIRCAS–TARF) (2004–2019); rain, mean monthly rainfall (mm); radn, mean daily solar radiation (MJ m<sup>−2</sup>); Tmax, mean daily maximum temperature (°C); Tmin, mean daily minimum temperature (°C).</p> Full article ">Figure 2
<p>Layout of lysimeters with N treatments. Treatments (T1–T7) refer to the different N fertilizer application treatments shown in <a href="#water-13-00740-t002" class="html-table">Table 2</a>.</p> Full article ">Figure 3
<p>Outline of observations of soil moisture and drainage water.</p> Full article ">Figure 4
<p>Cumulative rainfall and deep drainage under different N treatments (T1–T7) in: (<b>a</b>) season 1; (<b>b</b>) season 2; and (<b>c</b>) season 3. Treatments refer to the different N application rates shown in <a href="#water-13-00740-t002" class="html-table">Table 2</a>.</p> Full article ">Figure 4 Cont.
<p>Cumulative rainfall and deep drainage under different N treatments (T1–T7) in: (<b>a</b>) season 1; (<b>b</b>) season 2; and (<b>c</b>) season 3. Treatments refer to the different N application rates shown in <a href="#water-13-00740-t002" class="html-table">Table 2</a>.</p> Full article ">Figure 5
<p>Mean monthly NO<sub>3–</sub>N concentrations in the drainage water of different treatments (T1–T7) and monthly rainfall. Treatments refer to the different N fertilizer application rates shown in <a href="#water-13-00740-t002" class="html-table">Table 2</a>.</p> Full article ">Figure 6
<p>Cumulative rainfall and N loads in deep drainage under different N treatments: (<b>a</b>) season 1; (<b>b</b>) season 2; and (<b>c</b>) season 3. Treatments (T1–T7) refer to the different N application rates shown in <a href="#water-13-00740-t002" class="html-table">Table 2</a>.</p> Full article ">
16 pages, 3136 KiB  
Article
Setting the Phosphorus Boundaries for Greek Natural Shallow and Deep Lakes for Water Framework Directive Compliance
by Ifigenia Kagalou, Chrysoula Ntislidou, Dionissis Latinopoulos, Dimitra Kemitzoglou, Vasiliki Tsiaoussi and Dimitra C. Bobori
Water 2021, 13(5), 739; https://doi.org/10.3390/w13050739 - 9 Mar 2021
Cited by 7 | Viewed by 2528
Abstract
Eutrophication caused by nutrient enrichment is a predominant stressor leading to lake degradation and, thus, the set-up of boundaries that support good ecological status, the Water Framework Directive’s main target, is a necessity. Greece is one of the Member States that have recorded [...] Read more.
Eutrophication caused by nutrient enrichment is a predominant stressor leading to lake degradation and, thus, the set-up of boundaries that support good ecological status, the Water Framework Directive’s main target, is a necessity. Greece is one of the Member States that have recorded delays in complying with the coherent management goals of European legislation. A wide range of different statistical approaches has been proposed in the Best Practice Guide for determining appropriate nutrient thresholds. To determine the nutrient thresholds supporting the good status of natural Greek lakes, the phytoplankton dataset gathered from the national monitoring programme (2015–2020) was used for shallow and deep natural lakes. The regression analyses were sufficient and robust in order to derive total phosphorus thresholds that ranged from 20 to 41 μg/L in shallow and 15–32 μg/L in deep natural lake types. Nutrient boundaries that encompass the stressors these lakes are subject to, are essential in proper lake management design. Full article
(This article belongs to the Special Issue The WFD 20 Years After—Ecological Status Assessment and Restoration of Aquatic Ecosystems)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Lake types of the Greek Monitoring Network. Greek Shallow Natural Lakes (GR-SNL): 1. Doirani, 2. Kastoria, 3. Lysimacheia, 4. Mikri Prespa, 5. Ozeros, 6. Pamvotida, 7. Paralimni, 8. Zazari; Greek Deep Natural Lakes (GR-DNL): 9. Amvrakia, 10. Kourna, 11. Megali Prespa, 12. Trichonida, 13. Vegoritida, 14. Volvi, 15. Yliki.</p> Full article ">Figure 2
<p>Scatter plot showing relationship between Ecological Quality Ratio (EQR) values of phytoplankton and Total Phosphorus (TP, μg/L) with fitted Generalized Additive Models (GAM) in (<b>a</b>) Greek Shallow Natural Lakes (GR-SNL) and; (<b>b</b>) Greek Deep Natural Lakes (GR-DNL). Open circles are outliers not used to fit model.</p> Full article ">Figure 3
<p>Box plots showing range of Total Phosphorus (TP, μg/L) concentrations by ecological classes (H: High, G: Good, M: Moderate, PB: Poor-Bad) in (<b>a</b>) Greek Shallow Natural Lakes (GR-SNL); (<b>b</b>) Greek Deep Natural Lakes (GR-DNL). The width of boxes is proportional to number of records in class. The <span class="html-italic">p</span>-values represent the significance of Wilcoxon test results.</p> Full article ">Figure 4
<p>Binary logistic regression (±95% confidence limits) between Total Phosphorus (μg/L) and the probability of phytoplankton being classified as: (<b>a</b>,<b>b</b>) moderate or worse; (<b>c</b>,<b>d</b>) good or worse in Greek Shallow Natural Lakes (GR-SNL) and Greek Deep Natural Lakes (GR-DNL), respectively. Lines show potential good-moderate and high-good thresholds at probabilities 0.25, 0.5 and 0.75, reflecting differing levels of precaution and intersections with fit ±95% confidence limits.</p> Full article ">Figure 5
<p>Percentage of water bodies where phytoplankton or Total Phosphorus (TP, μg/L) classifications for ecological status differ in comparison to the level used to set the threshold for (<b>a</b>,<b>b</b>) good-moderate or worse status; (<b>c</b>,<b>d</b>) high-good or worse status in Greek Shallow Natural Lakes (GR-SNL) and Greek Deep Natural Lakes (GR-DNL), respectively. Each line shows a sub-sample of data set selected randomly (loess models). Vertical lines mark the mean and range of intersections (minimum value, 1st quantile, median, mean, 3rd quantile, maximum value).</p> Full article ">Figure 6
<p>Classification decision trees of Total Phosphorus (TP, μg/L) on biological classes (High, Good, Moderate) based on phytoplankton in (<b>a</b>) Greek Shallow Natural Lakes (GR-SNL); (<b>b</b>) Greek Deep Natural Lakes (GR-DNL). Each node shows the predicted class, the predicted probability of each class and the percentage of observations in the node (High, Good, Moderate).</p> Full article ">Figure 7
<p>Cross-validation results of the decision tree for (<b>a</b>) Greek Shallow Natural Lakes (GR-SNL); (<b>b</b>) Greek Deep Natural Lakes (GR-DNL).</p> Full article ">
19 pages, 6860 KiB  
Article
Development of Fragility Curves for Piping and Slope Stability of River Levees
by Nicola Rossi, Mario Bačić, Meho Saša Kovačević and Lovorka Librić
Water 2021, 13(5), 738; https://doi.org/10.3390/w13050738 - 9 Mar 2021
Cited by 12 | Viewed by 3956
Abstract
The design code Eurocode 7 relies on semi-probabilistic calculation procedures, through utilization of the soil parameters obtained by in situ and laboratory tests, or by the means of transformation models. To reach a prescribed safety margin, the inherent soil parameter variability is accounted [...] Read more.
The design code Eurocode 7 relies on semi-probabilistic calculation procedures, through utilization of the soil parameters obtained by in situ and laboratory tests, or by the means of transformation models. To reach a prescribed safety margin, the inherent soil parameter variability is accounted for through the application of partial factors to either soil parameters directly or to the resistance. However, considering several sources of geotechnical uncertainty, including the inherent soil variability, measurement error and transformation uncertainty, full probabilistic analyses should be implemented to directly consider the site-specific variability. This paper presents the procedure of developing fragility curves for levee slope stability and piping as failure mechanisms that lead to larger breaches, where a direct influence of the flood event intensity on the probability of failure is calculated. A range of fragility curve sets is presented, considering the variability of levee material properties and varying durations of the flood event, thus providing crucial insight into the vulnerability of the levee exposed to rising water levels. The procedure is applied to the River Drava levee, a site which has shown a continuous trend of increased water levels in recent years. Full article
(This article belongs to the Special Issue Dam Safety. Overtopping and Geostructural Risks)
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<p>Levee failure mechanisms analysed in the study: slope instability (<b>a</b>) and internal erosion (<b>b</b>).</p> Full article ">Figure 2
<p>Workflow of probabilistic analysis of levee slope stability.</p> Full article ">Figure 3
<p>An overall layout of the Selnica–Dubovica levee with its distinctive segments.</p> Full article ">Figure 4
<p>A cross-section of the case study levee.</p> Full article ">Figure 5
<p>Flow regimes during overflow of a dam, redrawn from [<a href="#B65-water-13-00738" class="html-bibr">65</a>].</p> Full article ">Figure 6
<p>Numerical model for analyses of case study levee.</p> Full article ">Figure 7
<p>Fragility curves for landside slope stability with respect to varying hydraulic conductivities.</p> Full article ">Figure 8
<p>Fragility curves for transient seepage of 5-day duration.</p> Full article ">Figure 9
<p>Fragility curves for variability of reduced strength parameters.</p> Full article ">Figure 10
<p>Probabilities of failure and respective reliability indices for levee slope stability.</p> Full article ">Figure 11
<p>Probability of piping failure for piping design case 1 (PDC1).</p> Full article ">Figure 12
<p>Probability of piping failure for PDC2.</p> Full article ">Figure 13
<p>Mean curves for PDC1 and PDC2.</p> Full article ">
25 pages, 10113 KiB  
Article
Means and Extremes: Evaluation of a CMIP6 Multi-Model Ensemble in Reproducing Historical Climate Characteristics across Alberta, Canada
by Badrul Masud, Quan Cui, Mohamed E. Ammar, Barrie R. Bonsal, Zahidul Islam and Monireh Faramarzi
Water 2021, 13(5), 737; https://doi.org/10.3390/w13050737 - 9 Mar 2021
Cited by 24 | Viewed by 5239
Abstract
This study evaluates General Circulation Models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for their ability in simulating historical means and extremes of daily precipitation (P), and daily maximum (Tmax), and minimum temperature (Tmin). Models are evaluated against hybrid [...] Read more.
This study evaluates General Circulation Models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for their ability in simulating historical means and extremes of daily precipitation (P), and daily maximum (Tmax), and minimum temperature (Tmin). Models are evaluated against hybrid observations at 2255 sub-basins across Alberta, Canada using established statistical metrics for the 1983–2014 period. Three extreme indices including consecutive wet days (CWD), summer days (SD), and warm nights (WN) are defined based on the peak over the threshold approach and characterized by duration and frequency. The tail behaviour of extremes is evaluated using the Generalized Pareto Distribution. Regional evaluations are also conducted for four climate sub-regions across the study area. For both mean annual precipitation and mean annual daily temperature, most GCMs more accurately reproduce the observations in northern Alberta and follow a gradient toward the south having the poorest representation in the western mountainous area. Model simulations show statistically better performance in reproducing mean annual daily Tmax than Tmin, and in reproducing annual mean duration compared to the frequency of extreme indices across the province. The Kernel density curves of duration and frequency as simulated by GCMs show closer agreement to that of observations in the case of CWD. However, it is slightly (completely) overestimated (underestimated) by GCMs for warm nights (summer days). The tail behaviour of extremes indicates that GCMs may not incorporate some local processes such as the convective parameterization scheme in the simulation of daily precipitation. Model performances in each of the four sub-regions are quite similar to their performances at the provincial scale. Bias-corrected and downscaled GCM simulations using a hybrid approach show that the downscaled GCM simulations better represent the means and extremes of P characteristics compared to Tmax and Tmin. There is no clear indication of an improved tail behaviour of GPD based on downscaled simulations. Full article
(This article belongs to the Special Issue Past and Future Trends and Variability in Hydro-Climatic Processes)
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<p>Map of Alberta with its four extreme climate regions (R1; R2; R3; and R4) overlaid with grid locations of five GCMs selected for the study. The black dots indicate a centroid of 2255 sub-basins. The inset shows the location of Alberta in Canada and its topography.</p> Full article ">Figure 2
<p>A schematic diagram of the methodology adopted for this study using both downscaled and non-downscaled/raw data.</p> Full article ">Figure 3
<p>Observed mean annual precipitation (in mm) and mean annual daily temperature (maximum and minimum in °C) for the 1983–2014 period are shown in the first column in the left. Relative difference for precipitation (%) and only difference for temperature (°C) between the GCM simulated and observed data for the same period is shown in right four columns. A positive relative difference and delta temperature indicate an overestimation by GCMs.</p> Full article ">Figure 4
<p>The spatial pattern of verification metrics between GCM simulation and observed data for the period of 1983–2014. Here, the KS test is used for P and the <span class="html-italic">bR</span><sup>2</sup> and <span class="html-italic">NSE</span> are used for both Tmax and Tmin. Red and blue colour indicate poor and good performance of individual GCMs, respectively.</p> Full article ">Figure 5
<p>Spatial distribution of mean annual duration and frequency of CWD, SD, and WN for the 1983–2014 period for 2255 sub-basins. The first column in the left represents the magnitude of duration and frequency based on observed data and rest four columns indicate the difference between GCM simulations and observation (delta changes). A positive delta mean frequency and duration indicate an overestimation by GCMs.</p> Full article ">Figure 6
<p>Kernel density curves of mean duration and mean frequency of CWD, SD, and WN for the 1983–2014 period.</p> Full article ">Figure 7
<p>Spatial distribution of the tail index (shape parameter) of P, Tmax, and Tmin extremes for the 1983–2014 period for 2255 sub-basins. The first column in the left represents the magnitude of tail index based on observed data and the rest four columns indicate the difference (delta change) between GCM simulations and observation. A positive shape indicates an overestimation by GCMs.</p> Full article ">Figure 8
<p>Kernel density curves of the tail index (shape parameter) of P, Tmax, and Tmin extremes for the 1983–2014 period.</p> Full article ">Figure 9
<p>Kernel density curves of mean duration and mean frequency of CWD, SD, and WN corresponding to four climate regions in Alberta for the 1983–2014 period.</p> Full article ">Figure 10
<p>Kernel density curves of the tail index (shape parameter) of P, Tmax, and Tmin extremes corresponding to four climate regions in Alberta for the 1983–2014 period.</p> Full article ">Figure 11
<p>The verification metrics between GCM simulations (downscaled: DS and non-downscaled: NDS) and observed data for the period of 1983–2014. The x-axis represents the 2255 sub-basins in Alberta and y-axis represents the corresponding evaluation metric for daily P, Tmax, and Tmin. The negative values of NSE were ignored and the x-axis was set at 0.</p> Full article ">Figure 12
<p>Spatial distribution of delta (difference between downscaled GCM simulations and observation) mean annual duration and frequency of CWD, SD, and WN for the 1983–2014 period for 2255 sub-basins. A positive delta mean frequency and duration indicate an overestimation by downscaled GCMs.</p> Full article ">Figure 13
<p>Spatial distribution of the delta tail index (shape parameter) between downscaled GCM simulations and observations of P, Tmax, and Tmin extremes for the 1983–2014 period for 2255 sub-basins. A positive shape indicates an overestimation by downscaled GCMs.</p> Full article ">
11 pages, 1971 KiB  
Review
The Problem of Removing Seaweed from the Beaches: Review of Methods and Machines
by Łukasz Warguła, Bartosz Wieczorek, Mateusz Kukla, Piotr Krawiec and Jakub Wojciech Szewczyk
Water 2021, 13(5), 736; https://doi.org/10.3390/w13050736 - 8 Mar 2021
Cited by 9 | Viewed by 5921
Abstract
Beach cleaning and algae collection in the shoreline area are important for the tourism industry, mainly for aesthetic reasons, but also to protect human health. In addition, the collected material can be used in many industries such as energy, medicine, cosmetics or catering. [...] Read more.
Beach cleaning and algae collection in the shoreline area are important for the tourism industry, mainly for aesthetic reasons, but also to protect human health. In addition, the collected material can be used in many industries such as energy, medicine, cosmetics or catering. The problem of cleaning the shoreline area concerns the need to clear land, water and the strip of shore and land onto which water is thrown from falling waves. The vast majority of available cleaning methods are adapted to cleaning beaches or waters. There is a lack of solutions and machine designs suitable for cleaning the coastal strip, which includes: land, the area of land on which the wave is thrown, shoal and deep water. This area is particularly important for tourism as it is mainly used for water bathing. Pictures from tourist areas that are exposed to intensive water contamination show that measures taken to clear the shoreline area are not very effective, as seaweed in shallow water is thrown ashore with the waves. The paper presents a review of methods for cleaning coastal waters and beaches from contamination. It also shows the author’s conceptual design adapted to clear the shoreline area and sandy beaches. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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<p>Seaweed pollution on the coast of the Dominican Republic in the region of the city of Punta Cana.</p> Full article ">Figure 2
<p>Concept for cleaning the coastal and near-shore strip from algae in particular: 1—land vehicle, 2—motorboat and 3—cleaning device.</p> Full article ">Figure 3
<p>Cleaning device: 1—frame, 2—surface for mounting to a water unit, 3—surface for mounting to a land unit, 4—drive unit of the working element of the cleaning machine, 5—linkage gear, 6 and 8—bearing supports of the working shaft, 7—working shaft, 9—clutch and 10—reducer.</p> Full article ">Figure 4
<p>Working shaft of the cleaning machine: 1—torsion springs, 2—spring fixing screws, 3—mounting screws for spring mountings and 4—spring mounting.</p> Full article ">Figure 5
<p>Possible position of the water unit in relation to the land unit: (<b>a</b>) delayed water unit, (<b>b</b>) water unit in optimal position in relation to the land unit and (<b>c</b>) overtaking water unit, where: 1—land unit, 2—water unit and 3—cleaning device.</p> Full article ">Figure 6
<p>Concept of a system for positioning a water unit in relation to a land unit: 1—land unit, 2—water unit, 3—joint attached to the water unit, 4—joint attached to the land unit, 5—sensor module, 6—extreme position sensor overtaking the land unit, 7—idle position sensor of the water unit, 8—extreme position sensor of the delayed movement of the water unit and 9—sensor activation lever.</p> Full article ">
23 pages, 2282 KiB  
Article
Natural Background Levels of Potentially Toxic Elements in Groundwater from a Former Asbestos Mine in Serpentinite (Balangero, North Italy)
by Elisa Sacchi, Massimo Bergamini, Elisa Lazzari, Arianna Musacchio, Jordi-René Mor and Elisa Pugliaro
Water 2021, 13(5), 735; https://doi.org/10.3390/w13050735 - 8 Mar 2021
Cited by 13 | Viewed by 2550
Abstract
The definition of natural background levels (NBLs) for potentially toxic elements (PTEs) in groundwater from mining environments is a real challenge, as anthropogenic activities boost water–rock interactions, further increasing the naturally high concentrations. This study illustrates the procedure followed to derive PTE concentration [...] Read more.
The definition of natural background levels (NBLs) for potentially toxic elements (PTEs) in groundwater from mining environments is a real challenge, as anthropogenic activities boost water–rock interactions, further increasing the naturally high concentrations. This study illustrates the procedure followed to derive PTE concentration values that can be adopted as NBLs for the former Balangero asbestos mine, a “Contaminated Site of National Interest”. A full hydrogeochemical characterisation allowed for defining the dominant Mg-HCO3 facies, tending towards the Mg-SO4 facies with increasing mineralisation. PTE concentrations are high, and often exceed the groundwater quality thresholds for Cr VI, Ni, Mn and Fe (5, 20, 50 and 200 µg/L, respectively). The Italian guidelines for NBL assessment recommend using the median as a representative concentration for each monitoring station. However, this involves discarding half of the measurements and in particular the higher concentrations, thus resulting in too conservative estimates. Using instead all the available measurements and the recommended statistical evaluation, the derived NBLs were: Cr = 39.3, Cr VI = 38.1, Ni = 84, Mn = 71.36, Fe = 58.4, Zn = 232.2 µg/L. These values are compared to literature data from similar hydrogeochemical settings, to support the conclusion on their natural origin. Results highlight the need for a partial rethink of the guidelines for the assessment of NBLs in naturally enriched environmental settings. Full article
(This article belongs to the Special Issue Natural Background Levels in Groundwater)
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<p>Location of the investigated area. 1 = recent alluvial deposits; 2 = alluvial deposits of the Balangero Plain (Middle–Upper Pleistocene); 3 = fluvioglacial deposits (Middle Pleistocene); 4 = fluvial deposits (Lower Pleistocene); 5 = Sesia-Lanzo zone; 6 = Lanzo Massif serpentinite; 7 = mine pit lake; 8 = remediation site; 9 = tailing piles; 10 = waste sludge; 11 = rivers; 12 = piezometric map of the phreatic aquifer from water table levels measured on Nov. 10–11, 2008 (m a.s.l.) [<a href="#B26-water-13-00735" class="html-bibr">26</a>]; 13 = monitoring station.</p> Full article ">Figure 2
<p>Eh–pH diagrams: (<b>a</b>) full plot, where the blue lines indicate the stability field of liquid water; (<b>b</b>) an enlargement of the portion indicated in red.</p> Full article ">Figure 3
<p>Piper diagram.</p> Full article ">Figure 4
<p>Relationship between Cr and Cr VI: (<b>a</b>) in drinking waters from California [<a href="#B52-water-13-00735" class="html-bibr">52</a>]; (<b>b</b>) in waters from the Anthemountas Basin, Greece [<a href="#B9-water-13-00735" class="html-bibr">9</a>] and at our study site (regression calculated using the total number of PTE measurements, including ND).</p> Full article ">
27 pages, 2423 KiB  
Review
Finding Nano: Challenges Involved in Monitoring the Presence and Fate of Engineered Titanium Dioxide Nanoparticles in Aquatic Environments
by Simone Heilgeist, Ryo Sekine, Oz Sahin and Rodney A. Stewart
Water 2021, 13(5), 734; https://doi.org/10.3390/w13050734 - 8 Mar 2021
Cited by 23 | Viewed by 5723
Abstract
In recent years, titanium dioxide (TiO2) has increasingly been used as an inorganic ultraviolet (UV) filter for sun protection. However, nano-TiO2 may also pose risks to the health of humans and the environment. Thus, to adequately assess its potential adverse [...] Read more.
In recent years, titanium dioxide (TiO2) has increasingly been used as an inorganic ultraviolet (UV) filter for sun protection. However, nano-TiO2 may also pose risks to the health of humans and the environment. Thus, to adequately assess its potential adverse effects, a comprehensive understanding of the behaviour and fate of TiO2 in different environments is crucial. Advances in analytical and modelling methods continue to improve researchers’ ability to quantify and determine the state of nano-TiO2 in various environments. However, due to the complexity of environmental and nanoparticle factors and their interplay, this remains a challenging and poorly resolved feat. This paper aims to provide a focused summary of key particle and environmental characteristics that influence the behaviour and fate of sunscreen-derived TiO2 in swimming pool water and natural aquatic environments and to review the current state-of-the-art of single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) approaches to detect and characterise TiO2 nanoparticles in aqueous media. Furthermore, it critically analyses the capability of existing fate and transport models to predict environmental TiO2 levels. Four particle and environmental key factors that govern the fate and behaviour of TiO2 in aqueous environments are identified. A comparison of SP-ICP-MS studies reveals that it remains challenging to detect and characterise engineered TiO2 nanoparticles in various matrices and highlights the need for the development of new SP-ICP-MS pre-treatment and analysis approaches. This review shows that modelling studies are an essential addition to experimental studies, but they still lack in spatial and temporal resolution and mostly exclude surface transformation processes. Finally, this study identifies the use of Bayesian Network-based models as an underexplored but promising modelling tool to overcome data uncertainties and incorporates interconnected variables. Full article
(This article belongs to the Special Issue Emerging Contaminants (ECs) in Water)
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<p>Routes of entry of nano-TiO<sub>2</sub> contained in sunscreens into the environment; adopted from Musee [<a href="#B23-water-13-00734" class="html-bibr">23</a>]. The grey boxes represent the focus of this research.</p> Full article ">Figure 2
<p>Schematic view of potential transformation, transport, and bioaccumulation processes in an aqueous environment.</p> Full article ">
12 pages, 31035 KiB  
Article
An Assessment of Dam Operation Considering Flood and Low-Flow Control in the Han River Basin
by Jaewon Kwak
Water 2021, 13(5), 733; https://doi.org/10.3390/w13050733 - 8 Mar 2021
Cited by 2 | Viewed by 2564
Abstract
An assessment of dam operation is essential in dam management; however, there is a lack of a simple method that could be used in actual practice. This study aims for an actual dam operation evaluation method for flood and low-flow control of the [...] Read more.
An assessment of dam operation is essential in dam management; however, there is a lack of a simple method that could be used in actual practice. This study aims for an actual dam operation evaluation method for flood and low-flow control of the three multi-purpose dams of Soyanggang, Chungju, and Hoengseong in the Han River basin, South Korea. Frequency matching method was applied to make a pair of cumulative distribution function (CDF) using daily dam inflow and outflow records. Runoff increasing and flood reduction rates are derived using CDFs of total and annual records. As a result, the average flood mitigation rates of the Chungju dam is approximately 35% annually and is relatively disadvantaged than the Soyanggang dam, which is 67.7% annually, due to small flood control capacity. The Hoengseong dam appeared to have a small flood reduction rate, but its runoff increasing rate is 94.7% annually because of the 209 km2 upper basin area. The suggested method in this study could be used as a simple and intuitive field method to evaluate dam operations. Also, according to the annual evaluation, the Soyanggang and Chunju dam need more aggressive and anticipative operations for flood control such as pre-discharge before flooding or modify the Restricted Water Level (RWL) for flood seasons. On the other hand, Hoengseong dam need further data and studies. Full article
(This article belongs to the Section Hydrology)
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<p>Concept of frequency matching in the CN method.</p> Full article ">Figure 2
<p>Dam operation and its result in CDF; (<b>a</b>) concept of dam operation; (<b>b</b>) the change in CDF due to dam operation.</p> Full article ">Figure 3
<p>The basic concept of evaluation for dam operation; colored area indicates the range of each area of flood and low-flow.</p> Full article ">Figure 4
<p>Study Area and Dam; red circle indicate the location of each dams, and colored area indicate that the upper basin area of each dam.</p> Full article ">Figure 5
<p>Study Area and Dam; red dot indicate the location of each dams, and colored area indicate the upper basin area of each dam.</p> Full article ">Figure 6
<p>Scatter diagram of runoff increasing rate vs. dam inflow at low-flow level with 20-year return period; (<b>a</b>) Soyanggang dam; (<b>b</b>) Chungju dam; (<b>c</b>) Hoengseong dam; red circle indicate record’s year which are severe drought during last 30 years.</p> Full article ">Figure 7
<p>Scatter diagram of flood reduction rate vs. dam inflow at flood level with 200-year return period; (<b>a</b>) Soyanggang dam; (<b>b</b>) Chungju dam; (<b>c</b>) Hoengseong dam; red circle indicates the 2020 record which is one of the most severe flood events during the last 30 years.</p> Full article ">Figure 8
<p>CDF of each dam record using frequency matching; (<b>a</b>) Soyanggang dam for 1976 onwards; (<b>b</b>) Chungju dam for 1987 onwards; (<b>c</b>) Hoengseong dam for 2001 onwards; red box indicate calculated area based on truncation level for flood and low-flow.</p> Full article ">Figure 9
<p>Precipitation, storage amount, and inflow rates during 2020 monsoon season (15 July to 15 September).</p> Full article ">
17 pages, 6002 KiB  
Article
Developing Real-Time Nowcasting System for Regional Landslide Hazard Assessment under Extreme Rainfall Events
by Yuan-Chang Deng, Jin-Hung Hwang and Yu-Da Lyu
Water 2021, 13(5), 732; https://doi.org/10.3390/w13050732 - 8 Mar 2021
Cited by 8 | Viewed by 2633
Abstract
In this research, a real-time nowcasting system for regional landslide-hazard assessment under extreme-rainfall conditions was established by integrating a real-time rainfall data retrieving system, a landslide-susceptibility analysis program (TRISHAL), and a real-time display system to show the stability of regional slopes in real [...] Read more.
In this research, a real-time nowcasting system for regional landslide-hazard assessment under extreme-rainfall conditions was established by integrating a real-time rainfall data retrieving system, a landslide-susceptibility analysis program (TRISHAL), and a real-time display system to show the stability of regional slopes in real time and provide an alert index under rainstorm conditions for disaster prevention and mitigation. The regional hydrogeological parameters were calibrated using a reverse-optimization analysis based on an RGA (Real-coded Genetic Algorithm) of the optimization techniques and an improved version of the TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability) model. The 2009 landslide event in the Xiaolin area of Taiwan, associated with Typhoon Morakot, was used to test the real-time regional landslide-susceptibility system. The system-testing results showed that the system configuration was feasible for practical applications concerning disaster prevention and mitigation. Full article
(This article belongs to the Special Issue Rainfall-Induced Shallow Landslides Modeling and Warning)
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<p>The configuration of the real-time nowcasting system for regional landslide events.</p> Full article ">Figure 2
<p>Schematic diagram of the rainfall-event definition used in the system.</p> Full article ">Figure 3
<p>Typhoon Morakot landslide inventory for the Xiaolin area.</p> Full article ">Figure 4
<p>Geological map of the Xiaolin area.</p> Full article ">Figure 5
<p>Required fundamental parameter layers for the Transient Rainfall Infiltration and Grid-based Regional Slope-Stability (TRIGRS) model: (<b>a</b>) Slope gradient; (<b>b</b>) Soil thickness; (<b>c</b>) Saturated soil unit weight; (<b>d</b>) Initial steady surface flux.</p> Full article ">Figure 6
<p>The calibrated parameter layers produced by the optimization reverse analysis: (<b>a</b>) Saturated hydraulic conductivity; (<b>b</b>) Saturated hydraulic diffusivity; (<b>c</b>) Soil cohesion for effective stress; (<b>d</b>) Soil friction angle for effective stress.</p> Full article ">Figure 7
<p>The real-time regional landslide-susceptibility display during Typhoon Morakot. (<b>a</b>) 06:00 on 7 August 2009. (<b>b</b>) 12:00 on 7 August 2009. (<b>c</b>) 00:00 on 8 August 2009. (<b>d</b>) 00:00 on 10 August 2009.</p> Full article ">
17 pages, 9236 KiB  
Article
Stratigraphic Analysis of Firn Cores from an Antarctic Ice Shelf Firn Aquifer
by Shelley MacDonell, Francisco Fernandoy, Paula Villar and Arno Hammann
Water 2021, 13(5), 731; https://doi.org/10.3390/w13050731 - 8 Mar 2021
Cited by 7 | Viewed by 3751
Abstract
In recent decades, several large ice shelves in the Antarctic Peninsula region have experienced significant ice loss, likely driven by a combination of oceanic, atmospheric and hydrological processes. All three areas need further research, however, in the case of the role of liquid [...] Read more.
In recent decades, several large ice shelves in the Antarctic Peninsula region have experienced significant ice loss, likely driven by a combination of oceanic, atmospheric and hydrological processes. All three areas need further research, however, in the case of the role of liquid water the first concern is to address the paucity of field measurements. Despite this shortage of field observations, several authors have proposed the existence of firn aquifers on Antarctic ice shelves, however little is known about their distribution, formation, extension and role in ice shelf mechanics. In this study we present the discovery of saturated firn at three drill sites on the Müller Ice Shelf (67°14′ S; 66°52′ W), which leads us to conclude that either a large contiguous or several disconnected smaller firn aquifers exist on this ice shelf. From the stratigraphic analysis of three short firn cores extracted during February 2019 we describe a new classification system to identify the structures and morphological signatures of refrozen meltwater, identify evidence of superficial meltwater percolation, and use this information to propose a conceptual model of firn aquifer development on the Müller Ice Shelf. The detailed stratigraphic analysis of the sampled cores will provide an invaluable baseline for modelling studies. Full article
(This article belongs to the Special Issue Review and Progress in Hydrological and Meteorological Monitoring of Glaciers)
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<p>Map of the study area. (<b>a</b>) shows the position on the Antarctic Peninsula, (<b>b</b>) shows the wider Müller Ice Shelf region, and the red points correspond to the ice core extraction sites.</p> Full article ">Figure 2
<p>Photograph of core handling on the Müller Ice Shelf. Two team members operated the electric drill, whilst the other two members bagged and recorded the extracted cores.</p> Full article ">Figure 3
<p>Photograph of the constructed light box. The displayed core is approximately 90 cm in length.</p> Full article ">Figure 4
<p>Water being drained from the upper section of the drill after the extraction of the lower section of M3. In <a href="#app1-water-13-00731" class="html-app">Video S1</a>, a video of the extraction of the lower section of core is included.</p> Full article ">Figure 5
<p>Examples of the (<b>a</b>) fine (core reference: M2-4), (<b>b</b>) medium (core reference: M2-10), and (<b>c</b>) large grains (core reference: M2-11) found in the ice cores. NB: The measuring tape used for scale in each image is in cm units with mm subintervals.</p> Full article ">Figure 6
<p>Examples of paired upper and lower contact morphologies. (<b>a</b>) Diffuse (core reference: M2-13), (<b>b</b>) sinuous (core reference: M1-17), and (<b>c</b>) planar (core reference: M16) contacts found in the ice cores. NB: The measuring tape used for scale in each image is in cm units with mm subintervals.</p> Full article ">Figure 7
<p>Examples of ice layers found in the ice cores. (<b>a</b>) is ice core section M2-13. In this section an ice lens overlays a fine ice lens (8 mm thick). A thin black line has been added to indicate how contacts between layers were visualised. (<b>b</b>) corresponds to section M1-3, which includes planar contacts at the base, and diffuse upper contacts. (<b>c</b>) shows section M1-4 which includes an ice lens with a sinuous contact at the base, and a diffuse upper contact. (<b>d</b>) is section M2-5 which has planar upper and lower contacts. NB: The measuring tape used for scale in each image is in cm units with mm subintervals.</p> Full article ">Figure 8
<p>Examples of fine ice lenses identified in the ice cores. (<b>a</b>) corresponds to section M1-6. The stippled line indicates a fine scale ice lens with planar contacts. (<b>b</b>) is section M1-18 which contains several fine-scale ice lenses that have diffuse contacts. NB: The measuring tape used for scale in each image is in cm units with mm subintervals.</p> Full article ">Figure 9
<p>An example of interlayering in section M2-10. Both (<b>a</b>,<b>b</b>) show the same section, however in (<b>b</b>), the fine-scale ice lenses and conduits are outlined in black. NB: The measuring tape used for scale in each image is in cm units with mm subintervals.</p> Full article ">Figure 10
<p>Horizontal (continuous line) and vertical (dashed line) small scale conduits identified in section M2-3. (<b>a</b>) shows the core section without interpretation, and (<b>b</b>) with interpretation. NB: The measuring tape used for scale in each image is in cm units with mm subintervals.</p> Full article ">Figure 11
<p>The stratigraphy recorded from the Müller 1 core. Granulometry is divided into fine (<b>green</b>), medium (<b>orange</b>) and coarse (<b>red</b>) grain sizes and the ice severely impacted by post extraction refreezing is shown as a hashed box. Recrystalized structures are divided into ice lenses (<b>blue</b>), fine-scale ice lenses (<b>purple</b>) and interlaying of firn and ice). Ice conduits are not presented as these small-scale features where not continuous across the core. Additionally, relative humidity as observed in the field, and density as measured in the laboratory are presented.</p> Full article ">Figure 12
<p>The stratigraphy recorded from the Müller 2 core. Granulometry is divided into fine (<b>green</b>), medium (<b>orange</b>) and coarse (<b>red</b>) grain sizes and the ice severely impacted by post extraction refreezing is shown as a hashed box. Recrystalized structures are divided into ice lenses (<b>blue</b>), fine-scale ice lenses (<b>purple</b>) and interlaying of firn and ice). Ice conduits are not presented as these small-scale features where not continuous across the core. Additionally, relative humidity as observed in the field, and density as measured in the laboratory are presented.</p> Full article ">Figure 13
<p>The stratigraphy recorded from the Müller 3 core. Granulometry is divided into fine (<b>green</b>), medium (<b>orange</b>) and coarse (<b>red</b>) grain sizes and the ice severely impacted by post extraction refreezing is shown as a hashed box. Recrystalized structures are divided into ice lenses (<b>blue</b>), fine-scale ice lenses (<b>purple</b>) and interlaying of firn and ice). Ice conduits are not presented as these small-scale features where not continuous across the core. Additionally, relative humidity as observed in the field, and density as measured in the laboratory are presented.</p> Full article ">Figure 14
<p>Approximate correlation between cores based on grain size. Red indicates coarse grain size, orange medium grain size and green indicates fine grain size. Uncoloured areas indicate saturated firn that was too modified post extraction to analyse precisely. Dashed lines indicate interpreted similarities between cores. Indicated elevations were recorded using a Garmin eTrex 30x handheld unit, so should be treated as indicative only.</p> Full article ">Figure 15
<p>Indicative distribution of recrystalized structures in each core (recrystalised features are not to scale). Dark grey indicates ice lenses, purple indicates fine ice lenses and pink indicates interlayered firn and ice sections.</p> Full article ">
10 pages, 20397 KiB  
Communication
On the Power of Microwave Communication Data to Monitor Rain for Agricultural Needs in Africa
by Noam David, Yanyan Liu, Kingsley K. Kumah, Joost C. B. Hoedjes, Bob Z. Su and H. Oliver Gao
Water 2021, 13(5), 730; https://doi.org/10.3390/w13050730 - 8 Mar 2021
Cited by 10 | Viewed by 5431
Abstract
Over the last two decades, prevalent technologies and Internet of Things (IoT) systems have been found to have potential for carrying out environmental monitoring. The data generated from these infrastructures are readily available and have the potential to provide massive spatial coverage. The [...] Read more.
Over the last two decades, prevalent technologies and Internet of Things (IoT) systems have been found to have potential for carrying out environmental monitoring. The data generated from these infrastructures are readily available and have the potential to provide massive spatial coverage. The costs involved in using these data are minimal since the records are already generated for the original uses of these systems. Commercial microwave links, which provide the underlying framework for data transfer between cellular network base stations, are one example of such a system and have been found useful for monitoring rainfall. Wireless infrastructure of this kind is deployed widely by communication providers across Africa and can thus be used as a rainfall monitoring device to complement the sparse proprietary resources that currently exist or to substitute for them where alternatives do not exist. Here we focus this approach’s potential to acquire valuable information required for agricultural needs across Africa using Kenya as an example. Full article
(This article belongs to the Special Issue Hydrology, Water Resources Management and Protection of the Marine Environment-Selected Papers from the 16th International Conference on Environmental Science and Technology (CEST2019))
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<p>A microwave communication mast situated in the city of Njabini (in Nyandarua County, Kenya). (<b>a</b>) The white round apparatuses installed on the mast are the microwave communication antennas used for rainfall monitoring; (<b>b</b>) a closer look at the microwave antenna. (Photo credit: K. K. Kumah.).</p> Full article ">Figure 2
<p>Deployment of commercial microwave links in Kenya (by a single cellular network provider). The mapped links (indicated by straight lines) operate in the frequency range of 7–26 GHz, with a magnitude resolution of 0.1 dB. The location of the test site near the town of Kericho is noted by a red dot on the map. (Data source: Safaricom.).</p> Full article ">Figure 3
<p>The test site, showing the location of the commercial microwave links (indicated by straight lines with the term CML beside them) and the adjacent rain gauges (indicated by triangles). An additional rain gauge (not indicated here) is located near the town of Kericho, but its measurements were not available during the event discussed here. (Image source: Esri, Maxar, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User Community).</p> Full article ">Figure 4
<p>Commercial microwave links vs. rain gauge measurements (rain event of 10 May 2013). (<b>a</b>) The measurements of the four rain gauges; (<b>b</b>) the measurements of the CMLs, where the dashed line indicates the measurements of rain gauge 1 (G1). The arrows indicate periods when the spot rain gauge did not measure rainfall, while the links in its close vicinity did.</p> Full article ">
27 pages, 7155 KiB  
Article
Interdecadal Variability in Myanmar Rainfall in the Monsoon Season (May–October) Using Eigen Methods
by Zin Mie Mie Sein, Irfan Ullah, Farhan Saleem, Xiefei Zhi, Sidra Syed and Kamran Azam
Water 2021, 13(5), 729; https://doi.org/10.3390/w13050729 - 7 Mar 2021
Cited by 31 | Viewed by 5635
Abstract
In this study, we investigated the interdecadal variability in monsoon rainfall in the Myanmar region. The gauge-based gridded rainfall dataset of the Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit version TS4.0 (CRU TS4.0) were used (1950–2019) to investigate the interdecadal variability [...] Read more.
In this study, we investigated the interdecadal variability in monsoon rainfall in the Myanmar region. The gauge-based gridded rainfall dataset of the Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit version TS4.0 (CRU TS4.0) were used (1950–2019) to investigate the interdecadal variability in summer monsoon rainfall using empirical orthogonal function (EOF), singular value decomposition (SVD), and correlation approaches. The results reveal relatively negative rainfall anomalies during the 1980s, 1990s, and 2000s, whereas strong positive rainfall anomalies were identified for the 1970s and 2010s. The dominant spatial variability mode showed a dipole pattern with a total variance of 47%. The power spectra of the principal component (PC) from EOF revealed a significant peak during decadal timescales (20–30 years). The Myanmar summer monsoon rainfall positively correlated with Atlantic multidecadal oscillation (AMO) and negatively correlated with Pacific decadal oscillation (PDO). The results reveal that extreme monsoon rainfall (flood) events occurred during the negative phase of the PDO and below-average rainfall (drought) occurred during the positive phase of the PDO. The cold phase (warm phase) of AMO was generally associated with negative (positive) decadal monsoon rainfall. The first SVD mode indicated the Myanmar rainfall pattern associated with the cold and warm phase of the PDO and AMO, suggesting that enhanced rainfall for about 53% of the square covariance fraction was related to heavy rain over the study region except for the central and eastern parts. The second SVD mode demonstrated warm sea surface temperature (SST) in the eastern equatorial Pacific (El Niño pattern) and cold SST in the North Atlantic Ocean, implying a rainfall deficit of about 33% of the square covariance fraction, which could be associated with dry El Niño conditions (drought). The third SVD revealed that cold SSTs in the central and eastern equatorial Pacific (La Niña pattern) caused enhance rainfall with a 6.7% square covariance fraction related to flood conditions. Thus, the extra-subtropical phenomena may affect the average summer monsoon trends over Myanmar by enhancing the cross-equatorial moisture trajectories into the North Atlantic Ocean. Full article
(This article belongs to the Section Water Use and Scarcity)
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<p>Elevation map of the study area.</p> Full article ">Figure 2
<p>The annual cycle of mean rainfall from in situ observations (OBS), GPCC, and CRUTS4.0 over Myanmar (mm) (1950–2019). The error bars show the monthly standard deviation of the interannual variability within the periods. The horizontal solid lines shows the standard deviation of all datasets blue, grey, and orange bars.</p> Full article ">Figure 3
<p>Climatology of mean summer monsoon (May–October) rainfall (mm) over Myanmar (1950–2019) (<b>a</b>) in situ observation rainfall; (<b>b</b>) GPCC rainfall.</p> Full article ">Figure 4
<p>Decadal change in mean summer monsoon rainfall (mm) over Myanmar: (<b>a</b>) 1951–1960; (<b>b</b>) 1961–1970; (<b>c</b>) 1971–1980; (<b>d</b>) 1981–1990; (<b>e</b>) 1991–2000; (<b>f</b>) 2001–2010.</p> Full article ">Figure 5
<p>Black lines, homogeneous regions’ average summer monsoon rainfall time series (mm); red line, the corresponding 10 year running mean variations (mm): (<b>a</b>) north, (<b>b</b>) east, (<b>c</b>) central, (<b>d</b>) west, and (<b>e</b>) south regions in Myanmar.</p> Full article ">Figure 6
<p>Interdecadal variability estimated with a 10 year running mean of the standardized summer monsoon rainfall (mm) anomaly over Myanmar.</p> Full article ">Figure 7
<p>Abrupt change in summer monsoon rainfall derived from the sequential Mann–Kendall test statistic; U<span class="html-italic">(t)</span>, forward sequential statistic; U<span class="html-italic">’(t)</span>, backward sequential statistic; the upper and lower dashed lines represent significant at the 95% confidence level.</p> Full article ">Figure 8
<p>The first three empirical orthogonal functions (EOF_ (<b>top</b>) spatial modes and EOF (<b>bottom</b>) time series: (<b>a</b>) EOF-1, (<b>b</b>) EOF-2, and (<b>c</b>) EOF-3.</p> Full article ">Figure 9
<p>Power spectra: (<b>a</b>) principal component (PC)1, (<b>b</b>) PC2, and (<b>c</b>) PC3. The red line indicates the Markov red noise spectrum, the green dashed line represents the 90% significance, and the blue dashed line denotes the 10% significance boundary for the Markov analysis.</p> Full article ">Figure 10
<p>The mean summer monsoon season (May–October) wind anomalies (m/s) at 850 hPa for (<b>a</b>) wet years (1962–1967, 1998, and 2003–2004) and (<b>b</b>) dry years (1978–1986 and 1988–1990). The red (blue) color indicates the significant positive (negative) anomalies over the target region.</p> Full article ">Figure 11
<p>Pressure vertical velocity (ω) (×10<sup>−3</sup> Pa s<sup>−1</sup>) over Myanmar during wet years (1962–1967, 1998, and 2003–2004) and dry years (1978–1986 and 1988 –1990): (<b>a</b>) wet years at 15° N, (<b>b</b>) dry years at 15° N, (<b>c</b>) wet years at 20° N, (<b>d</b>) dry years at 20° N, (<b>e</b>) wet years at 25° N, and (<b>f</b>) dry years at 25° N. The red (blue) color indicates a positive (negative) significant anomaly. The dashed (solid) lines show ascending (descending) motion. Negative (positive) values indicate an upward (downward) motion.</p> Full article ">Figure 12
<p>Correlation map between the mean decadal May–October SST (over the Indian Ocean and Pacific Ocean) and mean decadal May–October rainfall over Myanmar. Hatched regions show a significant correlation at the 95% confidence level.</p> Full article ">Figure 13
<p>Interdecadal variability in average 10 year running mean summer monsoon rainfall anomaly based on standard deviation, Pacific decadal oscillation (PDO), and Atlantic multidecadal oscillation (AMO) indices.</p> Full article ">Figure 14
<p>Time series of the normalized summer monsoon rainfall in Myanmar (1950–2010). The blue bars indicate the multidecadal variability (MDV) in the PDO index obtained using the ensemble empirical mode decomposition (EEMD) method.</p> Full article ">Figure 15
<p>Heterogeneous correlations of the first three SVD modes among global SST and Myanmar rainfall: (<b>a</b>) SST mode 1, (<b>b</b>) rainfall mode 1, (<b>c</b>) SST mode 2, (<b>d</b>) rainfall mode 2, (<b>e</b>) SST mode 3, and (<b>f</b>) rainfall mode 3.</p> Full article ">Figure 16
<p>Normalized time series of the first three SVD modes: (<b>a</b>) mode 1, (<b>b</b>) mode 2, and (<b>c</b>) mode 3 SST (red bars) and rainfall (black bars).</p> Full article ">
16 pages, 3438 KiB  
Article
1,2-DCA Natural Attenuation Evaluation in Groundwater: Insight by Dual Isotope 13C/37Cl and Molecular Analysis Approach
by Giovanna Carpani, Massimo Marchesi, Ilaria Pietrini, Luca Alberti, Luciano Massimo Zaninetta, Orfan Shouakar-Stash and Francesca de Ferra
Water 2021, 13(5), 728; https://doi.org/10.3390/w13050728 - 7 Mar 2021
Cited by 3 | Viewed by 3340
Abstract
Natural attenuation (NA) processes represent a valuable option in groundwater remediation. At a heavily 1,2-dichloroethane (1,2-DCA) contaminated site, Compound-Specific Isotope Analysis (CSIA) in combination with Biological Molecular Tools (BMTs) were implemented as a rigorous characterization approach to evaluate the occurrence of Natural Attenuation [...] Read more.
Natural attenuation (NA) processes represent a valuable option in groundwater remediation. At a heavily 1,2-dichloroethane (1,2-DCA) contaminated site, Compound-Specific Isotope Analysis (CSIA) in combination with Biological Molecular Tools (BMTs) were implemented as a rigorous characterization approach to evaluate the occurrence of Natural Attenuation in the proximity of the source area. By the use of microcosm experiments, the potential for natural and enhanced biodegradation under anaerobic conditions was documented, following the dichloroelimination pathway. Enrichment factors of −9.1‰ and −11.3‰ were obtained for 13C while Geobacter spp. and reductive dehalogenase genes (rdhs) were identified as main site-specific biomarkers. At pilot scale, enrichments of 13.5‰ and 6.3‰ for δ13C and δ37Cl, respectively, high levels of reductive dehalogenase (rdh group VI) along with the dominance of Geobacter spp. indicated the occurrence of significant dichloroelimination processes in groundwater under anaerobic conditions. By using the site-specific enrichment factors, degradation extents over approximately 70–80% were estimated, highlighting the relevant potential of NA in 1,2-DCA degradation in the vicinity of the source area at the site. The proposed fine-tuned protocol, including CSIA and BMTs, is proven to be effective as a groundwater remediation strategy, properly assessing and monitoring NA at site scale. Full article
(This article belongs to the Special Issue Groundwater and Soil Remediation)
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<p>(<b>a</b>,<b>b</b>) Plan view of the site, with detail (<b>c</b>) of the pilot area including the monitoring well distribution: the monitoring wells P8 and P16 are in black while the monitoring wells for the detailed pilot area characterization of are in blue (red points indicate other wells not used for the purpose of this study); blue lines (<b>a</b>) are piezometric lines of the upper confined aquifer.</p> Full article ">Figure 2
<p>1,2-dichloroethane (1,2-DCA) and vinyl chloride (VC) concentrations during the monitoring period from 2004 to 2013 for P8 and P16 (<b>a</b>). The absence of VC formation confirms a dihaloelimination mechanism; map distribution of 1,2-DCA concentration (mg/L) during the sampling campaign in 2015 (<b>b</b>).</p> Full article ">Figure 3
<p>Microcosm experiments results: 1,2-DCA concentrations and δ<sup>13</sup>C results over time for enhanced natural attenuation (ENA) microcosm experiments; numbers 1–3 indicate experiment number) and natural attenuation (NA) (microcosm experiments; numbers 1–3 indicate experiment number) on the left; Ln (f) and Ln (Rt/R0) for enrichment factor estimation (on the right).</p> Full article ">Figure 4
<p>Quantitative PCR (qPCR) experiments results: determination of the reductive dehalogenase gene (<span class="html-italic">rdh</span>) and <span class="html-italic">Geobacter</span> spp. 16SrRNA copy number in subsequent enrichment cultures. NC is the non-enriched culture (that is, no refresh) microcosm at the beginning.</p> Full article ">Figure 5
<p>(<b>a</b>) Sequence of the area surrounding the <span class="html-italic">rdh</span> gene in an enrichment culture of <span class="html-italic">Geobacter</span> spp. and (<b>b</b>) characterization of the reductive dehalogenase operon.</p> Full article ">Figure 6
<p>δ<sup>13</sup>C and concentrations data from the pilot area.</p> Full article ">Figure 7
<p>Illumina sequencing results: composition and relative abundance of the species identified in five representative wells in the pilot test area. <span class="html-italic">Geobacter</span> spp. (light blue with white points) is the strain mainly represented.</p> Full article ">Figure 8
<p>Dual isotope approach reporting the variation of δ<sup>13</sup>C and δ<sup>37</sup>Cl for the pilot area; Λ values for oxidation, dichloroelimination and <span class="html-italic">Dehalococcoides</span> sp. are the values reported in Palau et al., 2017a.</p> Full article ">
22 pages, 3363 KiB  
Article
An Enhanced Innovative Triangular Trend Analysis of Rainfall Based on a Spectral Approach
by Bilel Zerouali, Nadhir Al-Ansari, Mohamed Chettih, Mesbah Mohamed, Zaki Abda, Celso Augusto Guimarães Santos, Bilal Zerouali and Ahmed Elbeltagi
Water 2021, 13(5), 727; https://doi.org/10.3390/w13050727 - 7 Mar 2021
Cited by 15 | Viewed by 3719
Abstract
The world is currently witnessing high rainfall variability at the spatiotemporal level. In this paper, data from three representative rain gauges in northern Algeria, from 1920 to 2011, at an annual scale, were used to assess a relatively new hybrid method, which combines [...] Read more.
The world is currently witnessing high rainfall variability at the spatiotemporal level. In this paper, data from three representative rain gauges in northern Algeria, from 1920 to 2011, at an annual scale, were used to assess a relatively new hybrid method, which combines the innovative triangular trend analysis (ITTA) with the orthogonal discrete wavelet transform (DWT) for partial trend identification. The analysis revealed that the period from 1950 to 1975 transported the wettest periods, followed by a long-term dry period beginning in 1973. The analysis also revealed a rainfall increase during the latter decade. The combined method (ITTA–DWT) showed a good efficiency for extreme rainfall event detection. In addition, the analysis indicated the inter- to multiannual phenomena that explained the short to medium processes that dominated the high rainfall variability, masking the partial trend components existing in the rainfall time series and making the identification of such trends a challenging task. The results indicate that the approaches—combining ITTA and selected input combination models resulting from the DWT—are auspicious compared to those found using the original rainfall observations. This analysis revealed that the ITTA–DWT method outperformed the ITTA method for partial trend identification, which proved DWT’s efficiency as a coupling method. Full article
(This article belongs to the Special Issue Advanced Research on Sustainable Water Resources Management and Planning under Climate Change)
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<p>Flowchart proposed for the analysis combining innovative triangular trend analysis (ITTA) with discrete wavelet transform (DWT) (ITTA–DWT: hybrid method).</p> Full article ">Figure 2
<p>Innovative trend methodology template (the black dots are data with no trends) [<a href="#B41-water-13-00727" class="html-bibr">41</a>].</p> Full article ">Figure 3
<p>Northern Algeria and selected rainfall series used in the analysis.</p> Full article ">Figure 4
<p>Triangular trend analysis methodology applied on rainfall series of Oued Taria.</p> Full article ">Figure 5
<p>Triangular trend analysis methodology applied on rainfall series of Azazga.</p> Full article ">Figure 6
<p>Triangular trend analysis methodology applied on rainfall series of Ain Beida.</p> Full article ">Figure 7
<p>Triangular trend analysis methodology applied on rainfall Model (M22) resulting from DWT (ITTM−DWT: hybrid method) of Oued Taria station.</p> Full article ">Figure 8
<p>Triangular trend analysis methodology applied on rainfall Model (M21) resulting from DWT (ITTM−DWT: hybrid method) of Azazga station (ITM applied on model 6).</p> Full article ">Figure 9
<p>Triangular trend analysis methodology applied on rainfall Model (M3) resulting from DWT (ITTM−DWT: hybrid method) of Ain Beida station.</p> Full article ">Figure 10
<p>Correlogram of (<b>a</b>) Oued Taria, (<b>b</b>) Azazga, (<b>c</b>) Ain Beida rainfall (blue) and DWT model (Red) and simple spectrum of (<b>d</b>) Oued Taria, (<b>e</b>) Azazga, (<b>f</b>) Ain Beida rainfall (blue) and DWT model (Red).</p> Full article ">
13 pages, 2054 KiB  
Article
Comparison between the Lagrangian and Eulerian Approach in Simulation of Free Surface Air-Core Vortices
by Maryam Azarpira, Amir Reza Zarrati and Pouya Farrokhzad
Water 2021, 13(5), 726; https://doi.org/10.3390/w13050726 - 7 Mar 2021
Cited by 8 | Viewed by 7807
Abstract
The problematic consequences regarding formation of air-core vortices at the intakes and the drastic necessity of a thorough investigation into the phenomenon has resulted in particular attention being placed on Computational Fluid Dynamics (CFD) as an economically viable method. Two main approaches could [...] Read more.
The problematic consequences regarding formation of air-core vortices at the intakes and the drastic necessity of a thorough investigation into the phenomenon has resulted in particular attention being placed on Computational Fluid Dynamics (CFD) as an economically viable method. Two main approaches could be taken using CFD, namely the Eulerian and Lagrangian methods each of which is characterized by specific advantages and disadvantages. Whereas many researchers have used the Eulerian approach for vortex simulation, the Lagrangian approach has not been found in the literature. The present study dealt with the comparison of the Lagrangian and Eulerian approaches in the simulation of vortex flow. Simulations based on both approaches were carried out by solving the Navier–Stokes equations accompanied by the LES turbulence model. The results of the numerical model were evaluated in accordance with a physical model for steady vortex flow using particle image velocimetry (PIV), revealing that both approaches are sufficiently capable of simulating the vortex flow but with the difference that the Lagrangian method has greater computational cost with less accuracy. Full article
(This article belongs to the Special Issue Computational Fluid Mechanics and Hydraulics)
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<p>The side view of the experimental setup.</p> Full article ">Figure 2
<p>Vortex flow: (<b>a</b>) The physical model; (<b>b</b>) The Eulerian model; (<b>c</b>) The Lagrangian model.</p> Full article ">Figure 3
<p>The tangential velocity distribution in the physical model, the Eulerian, and Lagrangian models: (<b>a</b>) test 1; (<b>b</b>) test 2; (<b>c</b>) test 3.</p> Full article ">Figure 4
<p>The radial velocity distribution in the physical model, the Eulerian, and Lagrangian models: (<b>a</b>) test 1; (<b>b</b>) test 2; (<b>c</b>) test 3.</p> Full article ">Figure 5
<p>The water surface profile corresponding to the physical, Eulerian, and Lagrangian models.</p> Full article ">Figure 6
<p>Sensitivity analysis (tangential velocity, test 2): (<b>a</b>) Eulerian model; (<b>b</b>) Lagrangian model.</p> Full article ">
22 pages, 4553 KiB  
Article
Nonlinear Water Quality Response to Numerical Simulation of In Situ Phosphorus Control Approaches
by Baichuan Zhang, Ningya Lin, Xi Chen, Qiaoming Fan, Xing Chen, Tingyu Ren, Rui Zou and Huaicheng Guo
Water 2021, 13(5), 725; https://doi.org/10.3390/w13050725 - 7 Mar 2021
Cited by 1 | Viewed by 2458
Abstract
The nonlinear and heterogeneous responses of nutrients to eutrophication control measures are a major challenge for in situ treatment engineering design, especially for large water bodies. Tackling the problem calls for a full understanding of potential water quality responses to various treatment schemes, [...] Read more.
The nonlinear and heterogeneous responses of nutrients to eutrophication control measures are a major challenge for in situ treatment engineering design, especially for large water bodies. Tackling the problem calls for a full understanding of potential water quality responses to various treatment schemes, which cannot be fulfilled by empirical-based methods or small-scale tests. This paper presents a methodology for Phoslock application based on the idea of object-oriented intelligent engineering design (OOID), which includes numerical simulation to explore the features of responses to numerous assumed schemes. A large plateau lake in Southwestern China was employed as a case study to illustrate the characteristics of the water quality response and demonstrate the applicability of this new approach. It was shown by the simulation and scenario analysis that the water quality response to Phoslock application always reflected nonlinearity and spatiotemporal heterogeneity, and always varied with objects, boundary conditions, and engineering design parameters. It was also found that some design parameters, like release position, had a significant impact on efficiency. Thus, a remarkable improvement could be obtained by cost-effective analysis based on scenarios using combinations of design parameters. Full article
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<p>Flowchart of object-oriented intelligent engineering design (OOID)-Phoslock framework.</p> Full article ">Figure 2
<p>Structure of the modeling system for predicting effects of Phoslock application.</p> Full article ">Figure 3
<p>Location of Xingyun Lake and watershed.</p> Full article ">Figure 4
<p>Optional positions for Phoslock release.</p> Full article ">Figure 5
<p>Model grid of Xingyun Lake.</p> Full article ">Figure 6
<p>Model validation: simulated water level and water quality vs. observed data at the gauging station and monitoring stations: (<b>a</b>) water level validation. (<b>b</b>–<b>d</b>) Total phosphorus (TP) concentration validation.</p> Full article ">Figure 7
<p>Time series graph of total phosphorus (TP) concentration for a typical scenario of Phoslock application (base0, T2, A0, 300 t/d).</p> Full article ">Figure 8
<p>Response curve for each season with other parameters equal (base0, A0, 300 t/d).</p> Full article ">Figure 9
<p>Spatial distribution of TP concentration at different moments during the Phoslock release cycle (base0-T1-A0-300t): (<b>a</b>) 1st day, (<b>b</b>) 5th day, (<b>c</b>) 15th day, and (<b>d</b>) 30th day.</p> Full article ">Figure 10
<p>Time series graph of TP concentration for different sets of release positions (base1, T2, and 300 t/d).</p> Full article ">Figure 11
<p>Response curves for the cross effect of a release position and dose (base0, T1).</p> Full article ">Figure 12
<p>Relationship between the release position and response (average for the simulation period, T1–T4, and base0–base2).</p> Full article ">Figure 13
<p>Response produced by Phoslock per weight for scenarios (average for simulation period, T1–T4, and base–base2).</p> Full article ">Figure 14
<p>Response and effective boundary for 1944 scenarios (average for simulation period and seasons).</p> Full article ">Figure 15
<p>Cumulative probability distribution of response for each dose level.</p> Full article ">
17 pages, 6352 KiB  
Article
Performance Assessment of Posidonia oceanica (L.) Delile Restoration Experiment on Dead matte Twelve Years after Planting—Structural and Functional Meadow Features
by Sebastiano Calvo, Roberta Calvo, Filippo Luzzu, Vincenzo Raimondi, Mauro Assenzo, Federica Paola Cassetti and Agostino Tomasello
Water 2021, 13(5), 724; https://doi.org/10.3390/w13050724 - 7 Mar 2021
Cited by 17 | Viewed by 4365
Abstract
Following the restoration of natural conditions by reducing human pressures, reforestation is currently considered a possible option to accelerate the recovery of seagrass habitats. Long-term monitoring programs theoretically represent an ideal solution to assess whether a reforestation plan has produced the desired results. [...] Read more.
Following the restoration of natural conditions by reducing human pressures, reforestation is currently considered a possible option to accelerate the recovery of seagrass habitats. Long-term monitoring programs theoretically represent an ideal solution to assess whether a reforestation plan has produced the desired results. Here, we report on the performance of a 20 m2 patch of Posidonia oceanica transplanted on dead matte twelve years after transplantation in the Gulf of Palermo, northwestern Sicily. Photo mosaic performed in the area allowed us to detect 23 transplanted patches of both regular and irregular shape, ranging from 0.1 to 2.7 m2 and an overall surface close to 19 m2. Meadow density was 331.6 ± 17.7 shoot m−2 (currently five times higher than the initial value of 66 shoots m−2), and it did not show statistical differences from a close by natural meadow (331.2 ± 14.9). Total primary production, estimated by lepidochronology, varied from 333.0 to 332.7 g dw m2/year, at the transplanted and natural stand, respectively. These results suggest that complete restoration of P. oceanica on dead matte is possible in a relatively short time (a decade), thus representing a good starting point for upscaling the recovery of the degraded meadows in the area. Full article
(This article belongs to the Special Issue Restore Degraded Marine Coastal Areas in the Mediterranean Sea)
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<p>Study area. In relief on the right dead matte structures surrounded by sandy bottoms (39), detected by Multibeam Echosounder MBES survey near “Bandita” (Gulf of Palermo), where the <span class="html-italic">P. oceanica</span> restoration site is located [<a href="#B11-water-13-00724" class="html-bibr">11</a>]. The black dot in the lower left corner identifies the location of the area covered by the MBSS survey.</p> Full article ">Figure 2
<p>Side Scan Sonar mosaic. There are sandy bottoms with different granulometry, ripple marks covering dead matte and dead matte outcrops where natural and transplanted <span class="html-italic">P. oceanica</span> patches are established (see <a href="#water-13-00724-f003" class="html-fig">Figure 3</a>).</p> Full article ">Figure 3
<p>Distribution map of <span class="html-italic">P. oceanica</span> meadows (natural and transplanted) on dead matte surrounded by sandy bottoms.</p> Full article ">Figure 4
<p>Photo mosaic of the reforestation pilot plant carried out on 11 May 2020 (on the right); black arrows indicate white 0.5 × 0.5 m squares. On the left, performance of the plant from 2008 to 2020. The below right photo shows the head of one of the several iron spikes in the foreground, used to anchor the metal grids in 2008 (above left photo), fully encrusted by biofouling. The 2010 photo highlights an additional source of disturbance (gear for octopus fishing trapped in the mesh of an implant grid) for pilot transplantation project [<a href="#B11-water-13-00724" class="html-bibr">11</a>].</p> Full article ">Figure 5
<p>Frequency histogram of <span class="html-italic">P. oceanica</span> patches in relation to the area covered in the transplanted area.</p> Full article ">Figure 6
<p>Mean values (SE) of meadow density (<b>a</b>), leaf length (<b>b</b>), shoot surface (<b>c</b>) and number of leaves produced (<b>d</b>) in transplanted and natural beds.</p> Full article ">Figure 7
<p>Mean values (SE) of speed of growth (<b>a</b>), primary production (<b>c</b>) across lepidochronological years and shoot age (<b>b</b>,<b>d</b>).</p> Full article ">Figure 8
<p>Frequency of shoot age histograms for both beds. The vertical line represents the general mean shoot age.</p> Full article ">Figure 9
<p>Growth performance measurements plotted on reference growth charts. The distribution of speed of growth of rhizomes (<b>a</b>), rhizome length (<b>b</b>), primary production (<b>c</b>) and weight (<b>d</b>) of the two beds are compared with the expected percentile curves at different ages.</p> Full article ">
19 pages, 1915 KiB  
Article
A New, Catchment-Scale Integrated Water Quality Model of Phosphorus, Dissolved Oxygen, Biochemical Oxygen Demand and Phytoplankton: INCA-Phosphorus Ecology (PEco)
by Jill Crossman, Gianbattista Bussi, Paul G. Whitehead, Daniel Butterfield, Emma Lannergård and Martyn N. Futter
Water 2021, 13(5), 723; https://doi.org/10.3390/w13050723 - 7 Mar 2021
Cited by 15 | Viewed by 4599
Abstract
Process-based models are commonly used to design management strategies to reduce excessive algal growth and subsequent hypoxia. However, management targets typically focus on phosphorus control, under the assumption that successful nutrient reduction will solve hypoxia issues. Algal responses to nutrient drivers are not [...] Read more.
Process-based models are commonly used to design management strategies to reduce excessive algal growth and subsequent hypoxia. However, management targets typically focus on phosphorus control, under the assumption that successful nutrient reduction will solve hypoxia issues. Algal responses to nutrient drivers are not linear and depend on additional biotic and abiotic controls. In order to generate a comprehensive assessment of the effectiveness of nutrient control strategies, independent nutrient, dissolved oxygen (DO), temperature and algal models must be coupled, which can increase overall uncertainty. Here, we extend an existing process-based phosphorus model (INtegrated CAtchment model of Phosphorus dynamics) to include biological oxygen demand (BOD), dissolved oxygen (DO) and algal growth and decay (INCA-PEco). We applied the resultant model in two eutrophied mesoscale catchments with continental and maritime climates. We assessed effects of regional differences in climate and land use on parameter importance during calibration using a generalised sensitivity analysis. We successfully reproduced in-stream total phosphorus (TP), suspended sediment, DO, BOD and chlorophyll-a (chl-a) concentrations across a range of temporal scales, land uses and climate regimes. While INCA-PEco is highly parameterized, model uncertainty can be significantly reduced by focusing calibration and monitoring efforts on just 18 of those parameters. Specifically, calibration time could be optimized by focusing on hydrological parameters (base flow, Manning’s n and river depth). In locations with significant inputs of diffuse nutrients, e.g., in agricultural catchments, detailed data on crop growth and nutrient uptake rates are also important. The remaining parameters provide flexibility to the user, broaden model applicability, and maximize its functionality under a changing climate. Full article
(This article belongs to the Special Issue Current Trends in Catchment Biogeochemical and Hydrological Modelling)
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<p>Conceptual diagram of the functionality of the INCA-PEco model (adapted from Jackson-Blake et al. (2016)). Boxes in red indicate new processes and variables added to INCA-P to create INCA-PEco.</p> Full article ">Figure 2
<p>Calibration results of (<b>A</b>) TP concentration (<b>B</b>) TDP concentration, (<b>C</b>) chl-a concentration and (<b>D</b>) DO concentration within the river mouth of the Beaver River catchment between 2015 and 2017.</p> Full article ">Figure 3
<p>Calibration results of (<b>A</b>) TP concentration (<b>B</b>) TDP concentration, (<b>C</b>) chl-a concentration and (<b>D</b>) DO concentration in the Trent River between 2010 and 2015.</p> Full article ">Figure 4
<p>A sensitivity heat map for the Beaver and Trent model applications, using Kolmogorov–Smirnov (KS) values to indicate sensitivity of model performance to parameter variance.</p> Full article ">
15 pages, 2846 KiB  
Article
Development of a New Testing Approach for Decentralised Technical Sustainable Drainage Systems
by Johannes Wolfgang Neupert, Philipp Lau, Daniel Venghaus and Matthias Barjenbruch
Water 2021, 13(5), 722; https://doi.org/10.3390/w13050722 - 6 Mar 2021
Cited by 7 | Viewed by 3509
Abstract
A part of the sustainable drainage systems (SuDS) are used to treat stormwater and must be tested for their hydraulic performance and the removal efficiency to assess serviceability and retention of the pollutants efficacy for in situ use. Current test procedures provide a [...] Read more.
A part of the sustainable drainage systems (SuDS) are used to treat stormwater and must be tested for their hydraulic performance and the removal efficiency to assess serviceability and retention of the pollutants efficacy for in situ use. Current test procedures provide a good basis for laboratory testing SuDS on the test stand. However, the evaluation is not sufficiently representative to compare different SuDS with each other or for in situ use. The individual steps and specifications of an applied test procedure in Germany were considered and evaluation and optimizations for the test substance and sampling methodology of SuDS on the test stand were proposed. A comparison of the particle size distribution of the test substance Millisil W4 currently in use and total suspended solids of real road runoff was made, which showed that the presented test substance of real road-deposited sediments (RDS) provides a better reference for the test conditions and they could be the basis for more representative test methods. A particle size distribution was proposed for this new test substance. Furthermore, two methods of sampling were compared, which showed that a full flow sampling is preferable to a discrete sample. At the same time, it was shown that a separation limit of 20 µm is sufficient for the determination of TSS63. Full article
(This article belongs to the Special Issue Rainwater Management in Urban Areas)
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<p>Particle size distributions of Millisil W4 [<a href="#B40-water-13-00722" class="html-bibr">40</a>], tyre and road wear particles (TRWP) [<a href="#B39-water-13-00722" class="html-bibr">39</a>], polycyclic aromatic hydrocarbons (PAH) [<a href="#B9-water-13-00722" class="html-bibr">9</a>], heavy metal [<a href="#B9-water-13-00722" class="html-bibr">9</a>] and road-deposited sediments (RDS) [<a href="#B9-water-13-00722" class="html-bibr">9</a>,<a href="#B30-water-13-00722" class="html-bibr">30</a>].</p> Full article ">Figure 2
<p>(<b>a</b>) RDS sample equipment (<b>b</b>) before/after close-up of a RDS sampling.</p> Full article ">Figure 3
<p>(<b>a</b>) Road runoff sampling basket (full flow sampling) and (<b>b</b>) in situ use.</p> Full article ">Figure 4
<p>Test stand of the Department of Urban Water Management at the TU of Berlin according to DIBt requirements.</p> Full article ">Figure 5
<p>Particle size distribution across a road. Total width: 11.8 m (area 1: 0.8 m; area 2–7: 1.6 m; area 8: 1.4 m).</p> Full article ">Figure 6
<p>The RSD (n = 39) in comparison to Millisil W4 [<a href="#B40-water-13-00722" class="html-bibr">40</a>], tyre and road wear particles (TRWP) [<a href="#B39-water-13-00722" class="html-bibr">39</a>], polycyclic aromatic hydrocarbons (PAH) [<a href="#B9-water-13-00722" class="html-bibr">9</a>], heavy metal [<a href="#B9-water-13-00722" class="html-bibr">9</a>] and road-deposited sediments (RDS) [<a href="#B9-water-13-00722" class="html-bibr">9</a>,<a href="#B30-water-13-00722" class="html-bibr">30</a>]. RDS graphs are normalised to 1 mm and larger particles are not considered.</p> Full article ">Figure 7
<p>Road runoff PSD (n = 6) in compare to RSD, Millisil W4 [<a href="#B40-water-13-00722" class="html-bibr">40</a>], tyre and road wear particles (TRWP) [<a href="#B39-water-13-00722" class="html-bibr">39</a>].</p> Full article ">Figure 8
<p>(<b>a</b>) Recovery of discrete sampling and full flow sampling (n = 8) (<b>b</b>) Road-deposited sediments (RDS) &lt;63 µm (n = 8).</p> Full article ">Figure 9
<p>Comparison of wet and dry sieving of RDS (n = 8).</p> Full article ">
12 pages, 5074 KiB  
Article
How Can Be Lotic Ecosystem Size More Precisely Estimated? Comparing Different Approximations in Pre-Pyrenean and Pyrenean Mountains
by Fernando Coello Sanz, Frederic Casals and Jorge Rubén Sánchez-González
Water 2021, 13(5), 721; https://doi.org/10.3390/w13050721 - 6 Mar 2021
Viewed by 3001
Abstract
Rivers are among the most biodiverse and endangered ecosystems on earth. In Europe, concern over their conservation promoted the development of legal instruments for habitat and species conservation, the Habitats Directive, and water resource management, the Water Framework Directive. This legal protection demanded [...] Read more.
Rivers are among the most biodiverse and endangered ecosystems on earth. In Europe, concern over their conservation promoted the development of legal instruments for habitat and species conservation, the Habitats Directive, and water resource management, the Water Framework Directive. This legal protection demanded the estimate of river ecosystem surface for different purposes. Different approaches allow river surface to be measured at a low cost. Some accurate techniques like satellite images or LiDAR (Light Detection and Ranging) do not always work at a large scale or for streams and small rivers. We discuss here the use of the traditional hydraulics relationship between drainage area and bankfull width as a good approach to river surface estimation. We confirm that the use of this cheap and simple method could be a good approach to estimate river surface. However, we also proved that the development of regional curves, i.e., to establish the empirical relationship based on study area data, constitutes an essential improvement to estimation. Full article
(This article belongs to the Section Water Quality and Contamination)
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<p>Study area. (<b>a</b>) Location of the analyzed rivers, Pre-Pyrenean and Pyrenean, in Europe. (<b>b</b>,<b>c</b>) Examples of sections, in red, of legal bankfull river boundaries according to national cartography [<a href="#B58-water-13-00721" class="html-bibr">58</a>]. (<b>d</b>) Locations of all Pre-Pyrenean and Pyrenean rivers are marked with dark blue, and the locations of all sections in red. Coordinates in meters, EPSG: 25831.</p> Full article ">Figure 2
<p>Relationship between the logarithm of the drainage area (<span class="html-italic">A</span>) in km<sup>2</sup> and the logarithm of the real bankfull width (<span class="html-italic">Wb</span>) in m at the 76 studied sections. The blue line shows linear regression (<span class="html-italic">F</span><sub>1,74</sub> = 62.73, <span class="html-italic">p</span> &lt; 0.005, <span class="html-italic">r</span><sup>2</sup><span class="html-italic"><sub>adjusted</sub></span> = 0.46) with 95% CI (grey).</p> Full article ">Figure 3
<p>(<b>a</b>) Relationship between the differences between <span class="html-italic">Sb</span> and <span class="html-italic">Sbe</span> in m<sup>2</sup> and the real bankfull width (<span class="html-italic">Wb</span>) in m at the 76 studied sections. The blue line shows linear regression (<span class="html-italic">F</span><sub>1,74</sub> = 158.4, <span class="html-italic">p</span> &lt; 0.005, <span class="html-italic">r</span><sup>2</sup><span class="html-italic"><sub>adjusted</sub></span> = 0.68) with 95% CI (grey). (<b>b</b>) Relationship between the differences between <span class="html-italic">Sb</span> and <span class="html-italic">Sbe</span> in m<sup>2</sup> and the sinuosity index (SI) in m at the 76 studied sections. The blue line shows linear regression (<span class="html-italic">F</span><sub>1,74</sub> = 1.52, <span class="html-italic">p</span> &gt; 0.05, <span class="html-italic">r</span><sup>2</sup><span class="html-italic"><sub>adjusted</sub></span> = 0.01) with 95% CI (grey).</p> Full article ">Figure 4
<p>Relationships between log<sub>10</sub> (<span class="html-italic">Sb</span>) and log<sub>10</sub> (<span class="html-italic">Sbe</span>) in m<sup>2</sup> at the 76 studied sections for the <span class="html-italic">Sbe</span> estimated by the different regional curves. The black line shows the linear regression where <span class="html-italic">Sbe</span> was estimated by our regional curve (<span class="html-italic">F</span><sub>1,74</sub> = 51.24, <span class="html-italic">p</span> &lt; 0.001, <span class="html-italic">r</span><sup>2</sup><span class="html-italic"><sub>adjusted</sub></span> = 0.40). The red line shows the linear regression considering the <span class="html-italic">Sb</span> values for <span class="html-italic">Sbe</span>. Grey lines show all the different relationships between <span class="html-italic">Sb</span> and the <span class="html-italic">Sbe</span> estimated for the different curves.</p> Full article ">
18 pages, 4720 KiB  
Article
Urban Groundwater Contamination by Non-Steroidal Anti-Inflammatory Drugs
by Anna Jurado, Enric Vázquez-Suñé and Estanislao Pujades
Water 2021, 13(5), 720; https://doi.org/10.3390/w13050720 - 6 Mar 2021
Cited by 27 | Viewed by 3768
Abstract
Pharmaceuticals, such as non-steroidal anti-inflammatory drugs (NSAIDs) and their metabolites, have become a major concern due to their increasing consumption and their widespread occurrence in the environment. In this paper, we investigate the occurrence of NSAIDs and their metabolites in an urban aquifer, [...] Read more.
Pharmaceuticals, such as non-steroidal anti-inflammatory drugs (NSAIDs) and their metabolites, have become a major concern due to their increasing consumption and their widespread occurrence in the environment. In this paper, we investigate the occurrence of NSAIDs and their metabolites in an urban aquifer, which may serve as a potential resource for drinking water, and propose a methodology to assess the removal of these substances in the river–groundwater interface. Then, risk quotients (RQs) are computed, in order to determine the risk posed by the single NSAIDs and their mixture to human health. To this end, six NSAIDs and two metabolites were collected from an urban aquifer located in the metropolitan area of Barcelona (NE, Spain), in which the major pollution source is a contaminated river. All of the target NSAIDs were detected in groundwater samples, where the concentrations in the aquifer were higher than those found in the river water (except for ibuprofen). Diclofenac, ketoprofen, propyphenazone and salicylic acid were detected at high mean concentrations (ranging from 91.8 ng/L to 225.2 ng/L) in the aquifer. In contrast, phenazone and mefenamic acid were found at low mean concentrations (i.e., lower than 25 ng/L) in the aquifer. According to the proposed approach, the mixing of river water recharge into the aquifer seemed to some extent to promote the removal of the NSAIDs under the sub-oxic to denitrifying conditions found in the groundwater. The NSAIDs that presented higher mean removal values were 4OH diclofenac (0.8), ibuprofen (0.78), salicylic acid (0.35) and diclofenac (0.28), which are likely to be naturally attenuated under the aforementioned redox conditions. Concerning human health risk assessment, the NSAIDs detected in groundwater and their mixture do not pose any risk for all age intervals considered, as the associated RQs were all less than 0.05. Nevertheless, this value must be taken with caution, as many pharmaceuticals might occur simultaneously in the groundwater. Full article
(This article belongs to the Special Issue Urban Groundwater)
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<p>(<b>a</b>) Location of the Besòs River Delta (Barcelona, NE Spain); (<b>b</b>) spatial distribution of groundwater sampling points in the Plaça de La Vila of Sant Adrià del Besòs; (<b>c</b>) Section A–A’ showing the screen depth of the sampling points and the major direction of groundwater flow; (<b>d</b>) piezometric surface at the surrounding of Plaça de la Vila; and (<b>e</b>) mean residence time (<b>d</b>) distribution from the river to the parking lot. Note that the piezometric level is in meters above sea level (m a.s.l.), the pumping wells are represented with green dots and the black line in <a href="#water-13-00720-f001" class="html-fig">Figure 1</a>b shows the schematic cross-section in Figure 4 (section A–A’). The Catalan Water Agency (ACA) measures the river flow at the Santa Coloma gauging station.</p> Full article ">Figure 2
<p>Boxplots showing the concentration of the NSAIDs and their metabolites (ng/L) in groundwater (GW, n = 13), including the non-detected values. The dots represent the outliers and the black crosses indicate the mean. There is one outlier not displayed, for SA (620 ng/L). Metabolites are highlighted in bold. DCF, diclofenac; 4OH DCF, 4OH diclofenac; IBU, ibuprofen; KET, ketoprofen; MEF, mefenamic acid; PPZ, propyphenazone; PZ, phenazone; SA, salicylic acid.</p> Full article ">Figure 3
<p>Boxplots showing the removal (<span class="html-italic">R<sub>abs</sub>,</span> Equation (1)) of the NSAIDs and their metabolites in groundwater (GW, n = 13). The dots represent the outliers; there are two outliers which are not displayed for SA (−6.04) and IBF (−3.01). DCF, diclofenac; 4OH DCF, 4OH diclofenac; IBU, ibuprofen; KET, ketoprofen; MEF, mefenamic acid; PPZ, propyphenazone; PZ, phenazone; SA, salicylic acid.</p> Full article ">Figure 4
<p>Spatial distribution of <span class="html-italic">R<sub>abs</sub></span> (Equation (1)) for three selected NSAIDs with (<b>a</b>) high (4OH diclofenac), (<b>b</b>) moderate (salicylic acid), and (<b>c</b>) poor (mefenamic acid) <span class="html-italic">R<sub>abs</sub></span>. The removal concentration (ng/L) of these NSAIDs is also shown (in red).</p> Full article ">Figure 5
<p>Graphical distribution of the R<sub>abs</sub> values for (<b>a</b>) 4OH diclofenac, (<b>b</b>) diclofenac and (<b>c</b>) phenazone from the river to the parking area. R<sub>abs</sub> was evaluated using the mean degradation velocity using the decrease in the concentrations between ADPW and SAP-2b and the mean residence time distribution shown in <a href="#water-13-00720-f001" class="html-fig">Figure 1</a>e. Note that, in the absence of representative river concentrations, it was assumed that R<sub>abs</sub> = 0 in the river.</p> Full article ">Figure 6
<p>Human health life-stage RQ profile for the target NSAIDs and their mixture (sum of the target NSAIDs) in the shallow aquifer of the Besòs River Delta. DCF, diclofenac; IBU, ibuprofen; KET, ketoprofen; MEF, mefenamic acid; PPZ, propyphenazone; PZ, phenazone; SA, salicylic acid.</p> Full article ">
18 pages, 5425 KiB  
Article
Towards a Correlation between Long-Term Seawater Intrusion Response and Water Level Fluctuations
by Antoifi Abdoulhalik, Ashraf A. Ahmed, Abdelrahman M. Abdelgawad and G. A. Hamill
Water 2021, 13(5), 719; https://doi.org/10.3390/w13050719 - 6 Mar 2021
Cited by 4 | Viewed by 3171
Abstract
Laboratory and numerical experiments were conducted to provide a quantitative steady-state analysis of the effect of incremental variations of water level on saltwater intrusion. The purpose was to seek mathematical correlations relating both the wedge toe length and the height along the coastline [...] Read more.
Laboratory and numerical experiments were conducted to provide a quantitative steady-state analysis of the effect of incremental variations of water level on saltwater intrusion. The purpose was to seek mathematical correlations relating both the wedge toe length and the height along the coastline to the boundary head difference. The laboratory experiments were completed in a 2D sand tank where both freshwater and seawater levels were varied. The experiments were conducted for two bead sizes having different hydraulic conductivities. The numerical model SEAWAT was used to validate the results and then to perform sensitivity analysis. The experimental results show that at steady-state conditions, the logarithmic toe length could be expressed as a linear function of the boundary head difference. The linear relationship was recorded in both advancing and receding wedge phases. The linearity of the correlation was also well demonstrated with analytical solutions. Similar relationships were also derived in the scenarios where the sea level fluctuated while the freshwater boundary head was constant. The height of the saltwater wedge along the coastline was also found to be a linear function of the boundary head difference. The sensitivity analysis shows that the regression coefficients were sensitive to the hydraulic conductivity, the dispersivity, and the saltwater density, while the porosity and the rate of boundary head change induced negligible effects. The existence of a linear relationship between the logarithmic toe length and the boundary head difference was also well evidenced in a field-scale aquifer model for all the different hydrogeological aquifer conditions tested. This study is the first attempt in identifying the underlying correlation between the boundary water level variations and the main seawater intrusion (SWI) external metrics under controlled laboratory conditions, which is of great relevance from a water resources management perspective. Full article
(This article belongs to the Special Issue Seawater Intrusion into Coastal Aquifers)
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<p>Simplified diagrams of a coastal unconfined aquifer showing the main seawater intrusion (SWI) metrics.</p> Full article ">Figure 2
<p>Schematic diagram of the laboratory tank (<b>top</b>). Photograph of the experimental setup (<b>bottom</b>). (1) Porous media chamber; (2) freshwater reservoir; (3) saltwater reservoir; (4) ultrasonic sensors; (5) high-speed camera; (6) LED lights.</p> Full article ">Figure 3
<p>Experimental concentration colour maps of the aquifer system for the various head differences (dh) in case FW 1325: dh = 6mm (<b>a</b>) followed by freshwater drop to 5.2 mm (<b>b</b>), 4.4 mm (<b>c</b>) and 3.6 mm (<b>d</b>). Only one case is shown (case 1325) for one scenario (FW) for the sake of brevity. (from Abdoulhalik and Ahmed [<a href="#B13-water-13-00719" class="html-bibr">13</a>]).</p> Full article ">Figure 4
<p>Steady-state to steady-state toe length data against the head difference dh in advancing condition for FW and SL scenarios; (<b>a</b>) case 1090 and (<b>b</b>) case 1325; (<b>c</b>) comparison with the analytical solution (for case 1090).</p> Full article ">Figure 5
<p>Transient experimental toe length data in a receding scenario in case 1325 (<b>top</b>) and case 1090 (<b>bottom</b>) for both FW and SL scenarios</p> Full article ">Figure 6
<p>Steady-state to steady-state toe length data against the head difference dh in seawater retreat (SWR) experiment in case 1090 (<b>top</b>) and case 1325 (<b>bottom</b>) for both FW and SL scenarios.</p> Full article ">Figure 7
<p>Steady-state to steady-state saltwater wedge height <span class="html-italic">H<sub>s</sub></span> against the head difference dh in case 1090 following fluctuations of the freshwater head boundary (<b>top</b>) and saltwater boundary (<b>bottom</b>). SWR refers to saltwater retreat, while SWI refers to saltwater intrusion.</p> Full article ">Figure 8
<p>Comparison between the numerical modelling results and the experimental data of the toe length in case 1090 FW.</p> Full article ">Figure 9
<p>Change of the logarithmic toe length with the head difference for different head change magnitude.</p> Full article ">Figure 10
<p>Change of the logarithmic toe length with the head difference for different hydraulic conductivity of the aquifer.</p> Full article ">Figure 11
<p>Change of the logarithmic toe length with the head difference for different dispersivity values over the range 0.001–0.2 cm.</p> Full article ">Figure 12
<p>Change of the logarithmic toe length with the head difference for different porosity values.</p> Full article ">Figure 13
<p>Change of the logarithmic toe length with the head difference for different saltwater density values.</p> Full article ">Figure 14
<p>Change of the logarithmic toe length with the head difference for different values of (<b>a</b>) hydraulic conductivity, (<b>b</b>) dispersivity, and (<b>c</b>) saltwater density.</p> Full article ">
22 pages, 3422 KiB  
Article
Construction of Critical Periods for Water Resources Management and Their Application in the FEW Nexus
by Val Z. Schull, Sushant Mehan, Margaret W. Gitau, David R. Johnson, Shweta Singh, Juan P. Sesmero and Dennis C. Flanagan
Water 2021, 13(5), 718; https://doi.org/10.3390/w13050718 - 6 Mar 2021
Cited by 3 | Viewed by 3664
Abstract
Amidst the growing population, urbanization, globalization, and economic growth, along with the impacts of climate change, decision-makers, stakeholders, and researchers need tools for better assessment and communication of the highly interconnected food–energy–water (FEW) nexus. This study aimed to identify critical periods for water [...] Read more.
Amidst the growing population, urbanization, globalization, and economic growth, along with the impacts of climate change, decision-makers, stakeholders, and researchers need tools for better assessment and communication of the highly interconnected food–energy–water (FEW) nexus. This study aimed to identify critical periods for water resources management for robust decision-making for water resources management at the nexus. Using a 4610 ha agricultural watershed as a pilot site, historical data (2006–2012), scientific literature values, and SWAT model simulations were utilized to map out critical periods throughout the growing season of corn and soybeans. The results indicate that soil water deficits are primarily seen in June and July, with average deficits and surpluses ranging from −134.7 to +145.3 mm during the study period. Corresponding water quality impacts include average monthly surface nitrate-N, subsurface nitrate-N, and soluble phosphorus losses of up to 0.026, 0.26, and 0.0013 kg/ha, respectively, over the growing season. Estimated fuel requirements for the agricultural practices ranged from 24.7 to 170.3 L/ha, while estimated carbon emissions ranged from 0.3 to 2.7 kg CO2/L. A composite look at all the FEW nexus elements showed that critical periods for water management in the study watershed occurred in the early and late season—primarily related to water quality—and mid-season, related to water quantity. This suggests the need to adapt agricultural and other management practices across the growing season in line with the respective water management needs. The FEW nexus assessment methodologies developed in this study provide a framework in which spatial, temporal, and literature data can be implemented for improved water resources management in other areas. Full article
(This article belongs to the Special Issue The Water-Energy-Food Nexus: Sustainable Development)
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<p>Topography, land cover (2011), and soil drainage classification of the Matson Ditch Watershed, Dekalb County, IN, USA.</p> Full article ">Figure 2
<p>Schematic showing system and boundaries of the FEW nexus framework for the Matson Ditch Watershed downscaled on a hectare scale. As the Matson Ditch Watershed is precipitation-fed, the water source comes only from precipitation (mm), with the nutrients of interest in this study being surface and subsurface nitrate (NO<sub>3</sub>-N, kg/ha) and soluble phosphorus (SOLP, kg/ha). The energy use of each component is represented by E<sub>component</sub> (e.g., E<sub>tillage</sub>) in MJ from fuel or electricity, with carbon emissions (CO<sub>2</sub>, t/ha) being an output. Food production is represented by crop yield (t/ha) along with associated revenues (USD/ha). Costs (USD/ha) include fertilizer and pesticide application, and general costs of farm management.</p> Full article ">Figure 3
<p>Hydrological system for the Matson Ditch Watershed.</p> Full article ">Figure 4
<p>(<b>a</b>) Average monthly deficits (−ve) and surpluses (+ve) for corn; (<b>b</b>) Average monthly deficits (−ve) and surpluses (+ve) for soybeans; (<b>c</b>) Average monthly precipitation, effective precipitation (black dotted line), and evapotranspiration (grey solid line) for corn; (<b>d</b>) Average monthly precipitation, effective precipitation (black dotted line), and evapotranspiration (grey solid line) for soybeans. Shaded region indicates the range of distribution of the monthly D<sub>S</sub> across all years.</p> Full article ">Figure 5
<p>(<b>a</b>) Average effective precipitation (P<sub>eff</sub>), evapotranspiration (ET), and deficit/surplus (D<sub>S</sub>) for corn; (<b>b</b>) Annual range in deficit/surplus for corn; (<b>c</b>) Average effective precipitation (P<sub>eff</sub>), evapotranspiration (ET), and deficit/surplus (D<sub>S</sub>) for soybeans; (<b>d</b>) Annual range in deficit/surplus for soybeans.</p> Full article ">Figure 6
<p>Monthly average nutrient losses from crops in the Matson Ditch Watershed for 2006–2012: (<b>a</b>) surface NO<sub>3</sub>-N for corn; (<b>b</b>) surface NO<sub>3</sub>-N for soybeans; (<b>c</b>) subsurface drainage NO<sub>3-</sub>N for corn; (<b>d</b>) subsurface drainage NO<sub>3</sub>-N for soybeans; (<b>e</b>) soluble P for corn; (<b>f</b>) soluble P for soybeans. Shaded regions indicate the range of distribution of the monthly nutrient load across all years.</p> Full article ">Figure 7
<p>Summary of monthly (May–October) patterns for corn and soybeans in the Matson Ditch Watershed across the various aspects of the FEW nexus during the 2006–2012 time period. The color-scales indicate low values with lighter colors and higher values with darker colors. For food: the crops continue to grow until at the end of the growing season, in this case, in October. For energy: fuel usage and carbon emissions for each year can be determined for the agronomic calendars for each crop, along with their associated carbon emissions. For water: water quality loads for various pollutants (surface nitrate, NO<sub>3</sub>-N (surf); subsurface nitrate, NO<sub>3</sub>-N (sub surf); and soluble phosphorus, SOLP) are mapped out across the growing season for each crop. For water quantity, deficits and surpluses (D<sub>S</sub>) are indicated for each month for each crop.</p> Full article ">Figure 8
<p>Scatter plots for the Matson Ditch Watershed (MDW) showing: (<b>a</b>) effective precipitation (P<sub>eff</sub>) for corn and soybeans vs. monthly average precipitation compared to the effective precipitation (P<sub>eff</sub>) vs. precipitation curve provided by the FAO [<a href="#B24-water-13-00718" class="html-bibr">24</a>]; and, (<b>b</b>) deficits or surpluses (D<sub>S</sub>) vs. monthly average effective precipitation.</p> Full article ">
15 pages, 661 KiB  
Article
Water Insecurity in Ontario First Nations: An Exploratory Study on Past Interventions and the Need for Indigenous Water Governance
by Rachel Arsenault
Water 2021, 13(5), 717; https://doi.org/10.3390/w13050717 - 6 Mar 2021
Cited by 15 | Viewed by 14792
Abstract
In 2018, I began an exploratory study involving fourteen Ontario First Nation participants that examined some First Nation water security challenges and opportunities. In acknowledgment that many of the government assessments, reports, and investments to date have failed, this study aims to determine [...] Read more.
In 2018, I began an exploratory study involving fourteen Ontario First Nation participants that examined some First Nation water security challenges and opportunities. In acknowledgment that many of the government assessments, reports, and investments to date have failed, this study aims to determine the causes of the water crisis as well as potential solutions by sharing Indigenous perspectives and recommendations on water governance and security. During the study, Indigenous participants were asked interview questions regarding their water and wastewater systems, their historical and current water security conditions, and if they had recommendations for achieving water security in First Nations. The analysis from these interviews demonstrated that there were ten different themes for water security and insecurity in First Nation communities as well as a set of four recommendations shared by the fourteen participants. The participant recommendations are: (1) that Traditional Knowledge (TK) and Indigenous laws be included in water security initiatives and water governance; (2) that provincial and federal governments work with Indigenous communities on their water security challenges and opportunities; (3) that First Nation leadership develops and implements community water protection plans; (4) that Indigenous communities establish an oversight committee or body for monitoring tourist ventures and extractive development projects such as mining on their territories. This paper will also discuss how an Indigenous research paradigm can be applied during the research process to ensure that the information is captured from the Indigenous perspectives of the participants. Full article
(This article belongs to the Special Issue Sustainable Water Governance through Indigenous Research Approaches)
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<p>Illustration of the participants’ First Nation communities in Ontario.</p> Full article ">
32 pages, 15381 KiB  
Article
Impact of Prospective Climate Change Scenarios upon Hydropower Potential of Ethiopia in GERD and GIBE Dams
by Giovanni Martino Bombelli, Stefano Tomiet, Alberto Bianchi and Daniele Bocchiola
Water 2021, 13(5), 716; https://doi.org/10.3390/w13050716 - 6 Mar 2021
Cited by 19 | Viewed by 4818
Abstract
Ethiopia is growing fast, and the country has a dire need of energy. To avoid environmental damages, however, Ethiopia is looking for green energy polices, including hydropower exploitation, with large water availability (i.e., the Blue Nile, the greatest tributary of Nile river). Besides [...] Read more.
Ethiopia is growing fast, and the country has a dire need of energy. To avoid environmental damages, however, Ethiopia is looking for green energy polices, including hydropower exploitation, with large water availability (i.e., the Blue Nile, the greatest tributary of Nile river). Besides other dams on the Omo river, the GIBE family, Ethiopia is now building the largest hydropower plant of Africa, the GERD (Grand Ethiopian Renaissance Dam), on the Blue Nile river, leading to tensions between Ethiopia, and Egypt, due to potentially conflictive water management. In addition, present and prospective climate change may affect reservoirs’ operation, and this thereby is relevant for downstream water users, population, and environment. Here, we evaluated water management for the GERD, and GIBE III dams, under present, and future hydrological conditions until 2100. We used two models, namely, Poli-Hydro and Poli-Power, to describe (i) hydrological budget, and flow routing and (ii) optimal/maximum hydropower production from the two dams, under unconstrained (i.e., no release downstream besides MIF) and constrained (i.e., with fair release downstream) simulation. We then used climate change scenarios from the reports CMIP5/6 of the Intergovernmental Panel on Climate Change (IPCC) until 2100, to assess future hydropower production. Our results demonstrate that the filling phase of the GERD, particularly critical, have optimal filling time of 5 years or so. Stream flows at GERD could be greater than the present ones (control run CR) at half century (2050–2059), but there could be large decrease at the end of century (2090–2099). Energy production at half century may increase, and then decrease until the end of century. In GIBE III discharges would increase both at half century, and at the end of century, and so would energy production. Constrained, and unconstrained simulation provide in practice similar results, suggesting potential for shared water management in both plants. Full article
(This article belongs to the Special Issue Impact of River Hydrology on Hydraulic Engineering and Hydropower)
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<p>Regions of study in Ethiopia. DEM (Digital Elevation Model) of Blue Nile and Omo catchments closed at dam sites. We also report the stream flow and meteorological stations used in the study.</p> Full article ">Figure 2
<p>Hypsographic curve at dam sites. (<b>a</b>) Grand Ethiopian Renaissance Dam (GERD) and (<b>b</b>) GIBE.</p> Full article ">Figure 2 Cont.
<p>Hypsographic curve at dam sites. (<b>a</b>) Grand Ethiopian Renaissance Dam (GERD) and (<b>b</b>) GIBE.</p> Full article ">Figure 3
<p>Monthly flows during the calibration period (1965–1988), at dam sites and river discharge stations. (<b>a</b>) Blue Nile basin, GERD. (<b>b</b>) Omo basin, GIBE. We also report flow components (surface/subsurface).</p> Full article ">Figure 3 Cont.
<p>Monthly flows during the calibration period (1965–1988), at dam sites and river discharge stations. (<b>a</b>) Blue Nile basin, GERD. (<b>b</b>) Omo basin, GIBE. We also report flow components (surface/subsurface).</p> Full article ">Figure 4
<p>Mean monthly potential hydropower productions, discharge release, and water volumes stored in the reservoir during CR (2010–2019), with No Release (S1, solid lines), and Environmental Release (S2, dotted lines). (<b>a</b>) GERD and (<b>b</b>) GIBE.</p> Full article ">Figure 4 Cont.
<p>Mean monthly potential hydropower productions, discharge release, and water volumes stored in the reservoir during CR (2010–2019), with No Release (S1, solid lines), and Environmental Release (S2, dotted lines). (<b>a</b>) GERD and (<b>b</b>) GIBE.</p> Full article ">Figure 5
<p>MIF loss, and energy loss for the GERD dam, depending upon of different duration of the filling period, from 1 to 10 years. Simulation during 2010–2019.</p> Full article ">Figure 6
<p>Average yearly temperature variations. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 7
<p>Average yearly precipitation variations. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 8
<p>Yearly stream flow changes in GERD and GIBE III. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 9
<p>GERD. Average estimated monthly hydropower production. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 9 Cont.
<p>GERD. Average estimated monthly hydropower production. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 10
<p>GIBE III. Average estimated monthly hydropower production. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 10 Cont.
<p>GIBE III. Average estimated monthly hydropower production. (<b>a</b>) Mid Century P1. (<b>b</b>) End of Century P2.</p> Full article ">Figure 11
<p>Energy production changes ΔE, against precipitation changes ΔP: (<b>a</b>) GERD and (<b>b</b>) GIBE III.</p> Full article ">
28 pages, 47792 KiB  
Article
Alkylphenols and Chlorophenols Remediation in Vertical Flow Constructed Wetlands: Removal Efficiency and Microbial Community Response
by Inês P. F. M. Montenegro, Ana P. Mucha, Maria Paola Tomasino, Carlos Rocha Gomes and Cristina Marisa R. Almeida
Water 2021, 13(5), 715; https://doi.org/10.3390/w13050715 - 6 Mar 2021
Cited by 9 | Viewed by 3149
Abstract
This study aims to investigate the effect of two different groups of phenolic compounds (the alkylphenols nonylphenol (NP) and octylphenol (OP), and the chlorophenol pentachlorophenol (PCP)) on constructed wetlands (CWs) performance, including on organic matter, nutrients and contaminants removal efficiency, and on microbial [...] Read more.
This study aims to investigate the effect of two different groups of phenolic compounds (the alkylphenols nonylphenol (NP) and octylphenol (OP), and the chlorophenol pentachlorophenol (PCP)) on constructed wetlands (CWs) performance, including on organic matter, nutrients and contaminants removal efficiency, and on microbial community structure in the plant bed substrate. CWs were assembled at lab scale simulating a vertical flow configuration and irrigated along eight weeks with Ribeira de Joane (an urban stream) water not doped (control) or doped with a mixture of NP and OP or with PCP (at a 100 μg·L−1 concentration each). The presence of the phenolic contaminants did not interfere in the removal of organic matter or nutrients in CWs in the long term. Removals of NP and OP were >99%, whereas PCP removals varied between 87% and 98%, mainly due to biodegradation. Microbial richness, diversity and dominance in CWs substrate were generally not affected by phenolic compounds, with only PCP decreasing diversity. Microbial community structure, however, showed that there was an adaptation of the microbial community to the presence of each contaminant, with several specialist genera being enriched following exposure. The three more abundant specialist genera were Methylotenera and Methylophilus (methylophilaceae family) and Hyphomicrobium (hyphomicrobiaceae family) when the systems were exposed to a mixture of NP and OP. When exposed to PCP, the three more abundant genera were Denitromonas (Rhodocyclaceae family), Xenococcus_PCC_7305 (Xenococcaceae family) and Rhodocyclaceae_uncultured (Rhodocyclaceae family). To increase CWs efficiency in the elimination of phenolic compounds, namely PCP which was not totally removed, strategies to stimulate (namely biostimulation) or increase (namely bioaugmentation) the presence of these bacteria should be explore. This study clearly shows the potential of vertical flow CWs for the removal of phenolic compounds, a still little explored subject, contributing to promote the use of CWs as nature-based solutions to remediate water contaminated with different families of persistent and/or emergent contaminants. Full article
(This article belongs to the Special Issue Nature-Based Solutions for the Mitigation of Persistent and Emerging Contaminants)
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<p>Removal percentage (%, mean and standard deviation, <span class="html-italic">n</span> = 3) of ammonia (NH<sub>4</sub><sup>+</sup>), nitrite (NO<sub>2</sub><sup>−</sup>), nitrate (NO<sub>3</sub><sup>−</sup>) and phosphate (PO<sub>4</sub><sup>3−</sup>) ions in CWs irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with NP and OP. * In week seven of control treatment there was no PO<sub>4</sub><sup>3−</sup> ions removal.</p> Full article ">Figure 2
<p>Removal percentage (%, mean and standard deviation, <span class="html-italic">n</span> = 3) of PCP in CWs, irrigated for eight weeks with Ribeira de Joane water doped with 100 μg·L<sup>−1</sup> of PCP per week.</p> Full article ">Figure 3
<p>Removal percentage (%, mean and standard deviation, <span class="html-italic">n</span> = 3) of ammonia (NH<sub>4</sub><sup>+</sup>), nitrite (NO<sub>2</sub><sup>−</sup>) and nitrate (NO<sub>3</sub><sup>−</sup>) ions in CWs, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with PCP. <b>*</b> no NO<sub>3</sub><sup>−</sup> removal in CWs.</p> Full article ">Figure 4
<p>Alfa diversity index of the microbial community in the different CWs systems, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with NP and OP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). (<b>a</b>) Richness (number of observed OTUs); (<b>b</b>) dominance (Berger–Parker index); (<b>c</b>) diversity (Shannon diversity index).</p> Full article ">Figure 5
<p>(<b>a</b>) Cluster dendrogram analysis of Hellinger transformation using the Bray–Curtis dissimilarity matrix and (<b>b</b>) Nonmetric Multidimensional Scaling (NMDS) analysis of data transformed by “phyloseq” function and based on Bray–Curtis dissimilarity matrix to ordinate microbial community composition of the different CWs systems, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with NP and OP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). The Kruskal–Wallis test was conducted to examine the difference between microbial communities of each sample.</p> Full article ">Figure 6
<p>(<b>a</b>) Abundance of the major phyla, (<b>b</b>) classes with abundance &gt; 1% and (<b>c</b>) genera more abundant of bacteria across the different CWs systems substrates, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with NP and OP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). &lt;1% abund.: groups the phyla with abundance lower than 1%; “No_Relative_NA” groups the phyla without any close relatives.</p> Full article ">Figure 6 Cont.
<p>(<b>a</b>) Abundance of the major phyla, (<b>b</b>) classes with abundance &gt; 1% and (<b>c</b>) genera more abundant of bacteria across the different CWs systems substrates, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with NP and OP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). &lt;1% abund.: groups the phyla with abundance lower than 1%; “No_Relative_NA” groups the phyla without any close relatives.</p> Full article ">Figure 7
<p>Relative abundance of the specialist genera in plant root bed substrate samples: (<b>a</b>) in control CWs and (<b>b</b>) in doped CWs collected at the end of the experiment (after 8 weeks). Systems irrigated along eight weeks with Ribeira de Joane water not doped (control) or doped with NP and OP. Only genera with abundance &gt; 1% are shown.</p> Full article ">Figure 8
<p>Alfa diversity index of the microbial community in the different CWs systems, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with PCP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). (<b>a</b>) Richness (number of observed OTUs); (<b>b</b>) dominance (Berger–Parker index); (<b>c</b>) diversity (Shannon diversity index).</p> Full article ">Figure 9
<p>(<b>a</b>) Cluster dendrogram analysis of Hellinger transformation using the Bray–Curtis dissimilarity matrix and (<b>b</b>) NMDS analysis of data transformed by “phyloseq” function and based on the Bray–Curtis dissimilarity matrix to ordinate microbial community composition of the different CWs systems, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with PCP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). The Kruskal–Wallis test was conducted to examine the difference between microbial communities of each sample.</p> Full article ">Figure 10
<p>(<b>a</b>) Abundance of the major phyla, (<b>b</b>) classes with abundance &gt; 1% and (<b>c</b>) genera more abundant of bacteria across the different CWs systems substrates, irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with PCP. Samples collected at the beginning (T0) and at the end of the experiment (T8) (<span class="html-italic">n</span> = 3). &lt;1% abund. groups the phyla with abundance lower than 1%; and “No_Relative_NA” groups the phyla without any close relatives.</p> Full article ">Figure 11
<p>Relative abundance of the specialist genera of bacteria in plant roots bed substrate samples, (<b>a</b>) in control CWs and (<b>b</b>) in doped CWs collected at the end of the experiment (after 8 weeks). Systems irrigated for eight weeks with Ribeira de Joane water not doped (control) or doped with PCP. Only genera with abundance &gt; 1% are shown.</p> Full article ">
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