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Water, Volume 9, Issue 4 (April 2017) – 69 articles

Cover Story (view full-size image): Analytical channel design tools have not advanced appreciably in the last decades, and continue to produce designs based upon a single representative discharge that may not lead to overall sediment continuity. It is beneficial for designers to know when a simplified design may be problematic and to efficiently produce alternative designs. We investigate eighteen sand-bed rivers in a comparison of designs based on the Capacity-Supply Ratio approach and five single discharge metrics...View Full-Text.
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955 KiB  
Article
The Paradox of Water Management Projects in Central Asia: An Institutionalist Perspective
by Lioudmila Chatalova, Nodir Djanibekov, Taras Gagalyuk and Vladislav Valentinov
Water 2017, 9(4), 300; https://doi.org/10.3390/w9040300 - 24 Apr 2017
Cited by 19 | Viewed by 6607
Abstract
After the disintegration of the Soviet Union, the Central Asian countries have been faced with numerous development challenges in agriculture, especially those related to water use. Well-intentioned foreign donors and development agencies have stepped in to support local farmers, research centers, and public [...] Read more.
After the disintegration of the Soviet Union, the Central Asian countries have been faced with numerous development challenges in agriculture, especially those related to water use. Well-intentioned foreign donors and development agencies have stepped in to support local farmers, research centers, and public authorities in devising innovative solutions. Yet, development aid projects have borne fruit only partially. Paradoxically, innovative and apparently useful technologies proposed by foreign donors have rarely and only partially succeeded in taking root in the local institutional contexts. To explain this paradox, this paper draws on the institutional approach which shows the possibility of technological innovations being encapsulated by dysfunctional institutions. Reviewing recent studies of water-related projects in Central Asia, the paper shows this encapsulation to be at the core of the development project failures pervasive both in the Soviet period and today. If the concept of encapsulation is valid, then the current development efforts can be made more effective by detecting and counteracting the structures of vested interest on the part of all the actors involved, such as foreign donors, public authorities, research centers and local farmers. Full article
(This article belongs to the Special Issue The Future of Water Management in Central Asia)
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<p>Models of innovation projects.</p>
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2450 KiB  
Article
Understanding and Control of Biopolymer Fouling in Ultrafiltration of Different Water Types
by Xing Zheng, Frederik Zietzschmann, Stephan Plume, Hendrik Paar, Mathias Ernst, Zi Wang and Martin Jekel
Water 2017, 9(4), 298; https://doi.org/10.3390/w9040298 - 23 Apr 2017
Cited by 18 | Viewed by 5868
Abstract
The present work focuses on understanding and control of biopolymer fouling in ultrafiltration of a typical surface water and nearby secondary effluent for direct and indirect portable use. Characterization results show that both kinds of biopolymers are of similar molecular weight. Longer than [...] Read more.
The present work focuses on understanding and control of biopolymer fouling in ultrafiltration of a typical surface water and nearby secondary effluent for direct and indirect portable use. Characterization results show that both kinds of biopolymers are of similar molecular weight. Longer than one year water quality monitoring results show that the C/N ratio in the secondary effluent biopolymers was relatively constant at around 4.8, while that in the surface water macromolecules fluctuated at around 6.9. Under a similar mass load, the investigated secondary effluent biopolymers lead to hydraulic resistance slightly higher than that caused by filtering surface water macromolecules; however, the correspondingly formed fouling is significantly less reversible by hydraulic backwashing. The quantity of the nitrogenous biopolymers in the secondary effluent demonstrated a strong correlation with the extent of the irreversible fouling in ultrafiltration (UF), while that from the surface water did not. In membrane fouling cleaning tests, certain detergent demonstrated high efficiency in removing the irreversible fouling after UF of the secondary effluent, but presented no effect in eliminating fouling caused by the surface water foulants. In-line coagulation using FeCl3 prior to UF was shown as an effective fouling control method, but the effect depends heavily on the type of feed water. Full article
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<p>Fluorescence excitation emission matrix (F-EEM) of secondary effluent and surface water.</p>
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<p>Liquid chromatography with online organic carbon (LC-OCD) chromatograms of secondary effluent and surface water.</p>
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<p>Variation of biopolymer concentration in secondary effluent and surface water (no SW sample was analyzed from October 2009 to April 2010, but the drop of biopolymer concentration from September 2009 to April 2010 implies the process took place in real time).</p>
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<p>C/N ratio within biopolymers in secondary effluent and surface water.</p>
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<p>Hydraulic resistance filtering secondary effluent and surface water under 500 mL permeate volume (<span class="html-italic">n</span> = 13).</p>
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<p>Relationship between irreversible resistance and: (<b>a</b>) organic carbon content of biopolymer in ultrafiltration (UF) of secondary effluent (SE); (<b>b</b>) organic nitrogen content of biopolymer in UF of SE; (<b>c</b>) organic carbon content of biopolymer in UF of surface water (SW); and (<b>d</b>) organic nitrogen content of biopolymer in UF of SW.</p>
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<p>Cleaning effect of UF membrane fouled during filtering secondary effluent and surface water.</p>
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<p>In-line coagulation effect (mmol Fe<sup>3+</sup>/L using FeCl<sub>3</sub>) in UF of secondary effluent and surface water.</p>
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582 KiB  
Article
Re-Staging La Rasgioni: Lessons Learned from Transforming a Traditional Form of Conflict Resolution to Engage Stakeholders in Agricultural Water Governance
by Maria Laura Ruiu, Sante Maurizi, Simone Sassu, Giovanna Seddaiu, Olga Zuin, Chris Blackmore and Pier Paolo Roggero
Water 2017, 9(4), 297; https://doi.org/10.3390/w9040297 - 22 Apr 2017
Cited by 8 | Viewed by 6052
Abstract
This paper presents an informal process inspired by a public practice of conflict mediation used until a few decades ago in Gallura (NE Sardinia, Italy), named La Rasgioni (The Reason). The aim is twofold: (i) to introduce an innovative method that translates the [...] Read more.
This paper presents an informal process inspired by a public practice of conflict mediation used until a few decades ago in Gallura (NE Sardinia, Italy), named La Rasgioni (The Reason). The aim is twofold: (i) to introduce an innovative method that translates the complexity of water-related conflicts into a “dialogical tool”, aimed at enhancing social learning by adopting theatrical techniques; and (ii) to report the outcomes that emerged from the application of this method in Arborea, the main dairy cattle district and the only nitrate-vulnerable zone in Sardinia, to mediate contrasting positions between local entrepreneurs and representatives of the relevant institutions. We discuss our results in the light of four pillars, adopted as research lenses in the International research Project CADWAGO (Climate Change Adaptation and Water Governance), which consider the specific “social–ecological” components of the Arborea system, climate change adaptability in water governance institutions and organizations, systemic governance (relational) practices, and governance learning. The combination of the four CADWAGO pillars and La Rasgioni created an innovative dialogical space that enabled stakeholders and researchers to collectively identify barriers and opportunities for effective governance practices. Potential wider implications and applications of La Rasgioni process are also discussed in the paper. Full article
3338 KiB  
Article
Pluvial Flooding in European Cities—A Continental Approach to Urban Flood Modelling
by Selma B. Guerreiro, Vassilis Glenis, Richard J. Dawson and Chris Kilsby
Water 2017, 9(4), 296; https://doi.org/10.3390/w9040296 - 22 Apr 2017
Cited by 40 | Viewed by 10437
Abstract
Pluvial flooding is caused by localized intense rainfall and the flood models used to assess it are normally applied on a city (or part of a city) scale using local rainfall records and a high resolution digital elevation model (DEM). Here, we attempt [...] Read more.
Pluvial flooding is caused by localized intense rainfall and the flood models used to assess it are normally applied on a city (or part of a city) scale using local rainfall records and a high resolution digital elevation model (DEM). Here, we attempt to model pluvial flooding on a continental scale and calculate the percentage of area flooded for all European cities for a 10-year return period for hourly rainfall (RP10). Difficulties in obtaining hourly rainfall records compromise the estimation of each city RP10 and the Europe-wide DEM spatial resolution is low relative to those typically used for individual case-studies. Nevertheless, the modelling capabilities and necessary computing power make this type of continental study now possible. This is a first attempt at continental city flooding modelling and our methodology was designed so that our results can easily be updated as better/more data becomes available. The results for each city depend on the interplay of rainfall intensity, the elevation map of the city and the flow paths that are created. In general, cities with lower percentage of city flooded are in the north and west coastal areas of Europe, while the higher percentages are seen in continental and Mediterranean areas. Full article
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Graphical abstract
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<p>Map of Europe with the cities from Urban Audit that were studied.</p>
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<p>Methodology flowchart.</p>
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<p>Map of Europe with the hourly rainfall for a 10-year return period for all available gauges. Return periods were calculated assuming a GEV (Generalized Extreme Value) distribution for all gauges. The number of years available for each gauge varied between 6 and 63 (median = 17 years).</p>
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<p>Maps of Europe showing the residuals of the linear regressions used to estimate the hourly rainfall for a 10-year return period. (<b>a</b>) Shows absolute residuals (in millimetres) while (<b>b</b>) shows relative residuals (calculated as a percentage of the observed rainfall level for a 10-year return period).</p>
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<p>Observed Vs estimated hourly rainfall for a 10-year return period for all gauges. When possible, the observed values are shown with their respective 0.05 confidence interval (horizontal lines). For four gauges (Athens, Barcelona, Firenze and Málaga) confidence intervals are not available because the time-series for these gauges were not available and their 10-year return period rainfall was retrieved from the literature (published intensity–duration–frequency (IDF) curves). Predictive intervals (0.95 level) are also shown (vertical lines). The diagonal dotted line shows the 1:1 line.</p>
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<p>CityCat (City Catchment Analysis Tool) flood maps for Vienna using a 70-mm/h storm (base map: Map data—Google, DigitalGlobe).</p>
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<p>Map of Europe showing the estimates from the regression model for hourly rainfall for a 10-year return period. The locations of the gauges used are shown as black dots.</p>
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<p>Example of events curves for four cities: BG007C—Vidin (Bulgaria), ES003C—Valencia (Spain), GR006C—Volos (Greece), and UK017C—Cambridge (UK) calculated from the CityCat results. The red vertical dashed line shows the RP10 (hourly rainfall for a 10-year return period) and the dotted blue line shows the corresponding percentage of city flooded.</p>
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<p>Percentage of city flooded for historical hourly rainfall for a 10-year return period. These percentages are based on the rainfall event and the elevation map used for each city and do not have in consideration adaptation measures already implemented in these cities (like sewer systems) which will be different in different cities.</p>
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<p>Map of northern Italy with location of cities (<b>a</b>); flood maps of IT510C—Monza (<b>b</b>) and IT511C—Bergamo (<b>c</b>) and the cities’ pluvial flood impact functions—percentage of city flooded (meaning a height of water above 5 cm) per rainfall event (<b>d</b>). These two cities were chosen to exemplify how very similar RP10s can result in considerably different percentages of flooding.</p>
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1315 KiB  
Article
Performance and Yeast Tracking in A Full-Scale Oil-Containing Paromomycin Production Wastewater Treatment System Using Yeast
by Chunyan Wang, Ran Ding, Yingxin Gao, Min Yang and Yu Zhang
Water 2017, 9(4), 295; https://doi.org/10.3390/w9040295 - 22 Apr 2017
Cited by 4 | Viewed by 6170
Abstract
High residual oil content in antibiotic production waste mother liquor makes solid–liquid separation of fermentation residue and wastewater difficult. A yeast-based pretreatment process was established for the removal of oil and promotion of solid–liquid separation in antibiotic production wastewater treatment systems. Six yeast [...] Read more.
High residual oil content in antibiotic production waste mother liquor makes solid–liquid separation of fermentation residue and wastewater difficult. A yeast-based pretreatment process was established for the removal of oil and promotion of solid–liquid separation in antibiotic production wastewater treatment systems. Six yeast strains acquired from different sources were inoculated into sequencing batch reactors (SBR) in pilot and full-scale wastewater treatment plants. Oil removal rates were 85.0%–92.0% and 61.4%–74.2%, and sludge settling velocities (SV) were 16.6%–21.3% and 22.6%–32.0% for the pilot and full-scale operations, respectively. 18S rRNA gene clone libraries were established to track the fates of the inoculated yeasts, which showed that Candida tropicalis was dominant in the full-scale plant. The fungi and bacteria gene copy ratio determined by quantitative polymerase chain reaction was 14.87 during stable field operation, indicating that yeast successfully colonized. Both the pilot and full-scale studies proved that yeast can be used to promote solid–liquid separation, and yeast systems are a stable and effective method for oil-containing fermentation antibiotic production wastewater pretreatment. Full article
(This article belongs to the Special Issue Oily Water Treatment)
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<p>Full-scale fermentative antibiotic production wastewater treatment system.</p>
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<p>Performance of pilot-scale yeast sequencing batch reactor. SV of influent and effluent and oil removal rates were detected for 45 days (9 hydraulic retention times). Daily removal rate of SCOD and sludge settling velocity were detected for the aeration period.</p>
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<p>Performance of full-scale yeast pretreatment system. SV of influent and effluent and oil and SCOD removal rates were detected for 15 days successively during stable field operation.</p>
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1154 KiB  
Article
Numerical Simulation of Soil Evaporation with Sand Mulching and Inclusion
by Wenju Zhao, Ping Yu, Xiaoyi Ma, Jie Sheng and Changquan Zhou
Water 2017, 9(4), 294; https://doi.org/10.3390/w9040294 - 22 Apr 2017
Cited by 8 | Viewed by 5390
Abstract
A model of unsaturated soil-water movement using a prediction model of basic physical soil properties for calculating correlation functions was developed using VADOSE/W. The reliability of the model was assessed by comparing the results with those of a soil-column test. Coefficients of determination, [...] Read more.
A model of unsaturated soil-water movement using a prediction model of basic physical soil properties for calculating correlation functions was developed using VADOSE/W. The reliability of the model was assessed by comparing the results with those of a soil-column test. Coefficients of determination, R2, between the simulated and the measured daily evaporation for sand-mulch thicknesses of 0 (control, CK), 1.7, 3.6 and 5.7 cm were 0.8270, 0.8214, 0.8589 and 0.9851, respectively. R2, between the simulated and measured cumulative evaporation for mulch thicknesses of 0, 1.7, 3.6 and 5.7 cm were 0.9755, 0.9994, 0.9997 and 0.9983, respectively. The fits were, thus, good, verifying the reliability of the model. The program accurately predicted the distribution of cumulative evaporation and volumetric water content during evaporation from a soil column with mulch thicknesses of 1, 1.3, 1.5, 1.7, 2, 3, 5 cm and depths of sand inclusion thick of 0, 5, 10 and 15 cm for 20 days. Cumulative evaporation of sand inclusion was lower than in CK. Cumulative evaporation was independent of the mulch thickness and depended only on the depth of the inclusion: the deeper the inclusion, the higher the evaporation. The best mulch thickness was 5 cm, and the best inclusion depth was 5 cm. This study offers a new method to study the evaporation process with sand mulching and inclusion, which can provide guidance for improving the utilization efficiency of soil water. Full article
(This article belongs to the Special Issue Modeling of Water Systems)
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<p>Geometric model. (<b>a</b>) The model control column (CK); (<b>b</b>) The model of sand-mulched column with sand thicknesses of 1.7 cm; (<b>c</b>) The model of sand-mulched column with sand thicknesses of 3.6 cm; (<b>d</b>) The model of sand-mulched column with sand thicknesses of 5.7 cm.</p>
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<p>Comparison of measured and simulated values of daily evaporation and cumulative evaporation of soil column under different sand mulching thicknesses. (<b>a</b>) The comparison of the simulated values and measured values of daily evaporation between different sand mulching thicknesses; (<b>b</b>) The comparison of simulated values and measured values of cumulative evaporation between different sand mulching thicknesses.</p>
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<p>Cumulative evaporation of sand horizons in different thicknesses and horizons. (<b>a</b>) Cumulative evaporation of different layers with 1 cm thick sand. (<b>b</b>) Cumulative evaporation of different layers with 2 cm thick sand. (<b>c</b>) Cumulative evaporation of different layers with 3 cm thick sand. (<b>d</b>) Cumulative evaporation of different layers with 5 cm thick sand.</p>
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<p>Volumetric water content of sand horizons in different thicknesses and horizons at the end of evaporation. (<b>a</b>) Volumetric water content of different layers with 1 cm thick sand; (<b>b</b>) Volumetric water content of different layers with 2 cm thick sand; (<b>c</b>) Volumetric water content of different layers with 3 cm thick sand; (<b>d</b>) Volumetric water content of different layers with 5 cm thick sand.</p>
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3779 KiB  
Article
Adaptation of Cascade Hydropower Station Scheduling on A Headwater Stream of the Yangtze River under Changing Climate Conditions
by Ming Yang Zhai, Qian Guo Lin, Guo He Huang, Le Zhu, Kai An, Gong Chen Li and Yue Fei Huang
Water 2017, 9(4), 293; https://doi.org/10.3390/w9040293 - 22 Apr 2017
Cited by 12 | Viewed by 5477
Abstract
Cascade hydropower stations are effective in water resource utilization, regional water allocation, and flood risk management. Under changing climate conditions, water resources would experience complex temporal and spatial changes, which may lead to various issues relating to flood control and water resource management, [...] Read more.
Cascade hydropower stations are effective in water resource utilization, regional water allocation, and flood risk management. Under changing climate conditions, water resources would experience complex temporal and spatial changes, which may lead to various issues relating to flood control and water resource management, and challenge the existing optimal scheduling of cascade hydropower stations. It is thus important to conduct a study on cascade hydropower station scheduling under changing climate conditions. In this study, the Jinsha River rainfall–discharge statistical model is developed based on the statistical relationship between meteorological and runoff indicators. Validation results indicate that the developed model is capable of generating satisfactory simulation results and thus can be used for future Jinsha River runoff projection under climate change. Meanwhile, the Providing Regional Climates for Impacts Studies (PRECIS) is run to project future rainfall in the Jinsha River basin under two General Circulation Models (ECHAM5 and HadAM3P), two scenarios (A1B and B2), and four periods (1961–1990, 1991–2020, 2021–2050, and 2051–2099). The regional climate modeling data are analyzed and then fed into the Jinsha hydrological model to analyze the trends of future discharge at Xiangjiaba Hydro Station. Adaptive scheduling strategies for cascade hydropower stations are discussed based on the future inflow trend analysis and current flood scheduling mode. It is suggested that cascade hydropower stations could be operated at flood limited water level (FLWL) during 2021–2099. In addition, the impoundment of cascade hydropower stations should be properly delayed during the post-flood season in response to the possible occurrence of increased and extended inflow in wet seasons. Full article
(This article belongs to the Special Issue Adaptation Strategies to Climate Change Impacts on Water Resources)
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<p>Selected meteorological and hydrological stations on the Jinsha River.</p>
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<p>Simulated and observed results of average daily Jinsha River discharge during flood season in 2015.</p>
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<p>Simulated and observed results of average daily Jinsha River discharge during flood season in 2016.</p>
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<p>Rainfall distribution over the Jinsha River basin under A1B from May to July in different periods: (<b>a</b>) 2010–2040 rainfall compared with 1960–1990; (<b>b</b>) 2040–2070 rainfall compared with 1960–1990; (<b>c</b>) 2070–2099 rainfall compared with 1960–1990; (<b>d</b>) 2010–2040 rainfall compared with 1980–2010; (<b>e</b>) 2040–2070 rainfall compared with 1960–1990; (<b>f</b>) 2070–2099 rainfall compared with 1980–2010.</p>
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<p>Rainfall distribution over Jinsha River basin under A1B from August to October during different periods: (<b>a</b>) 2010–2040 rainfall compared with 1960–1990; (<b>b</b>) 2040–2070 rainfall compared with 1960–1990; (<b>c</b>) 2070–2099 rainfall compared with 1980–2010; (<b>d</b>) 2010–2040 rainfall compared with 1980–2010; (<b>e</b>) 2040–2070 rainfall compared with 1960–1990; (<b>f</b>) 2070–2099 rainfall compared with 1980–2010.</p>
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<p>Rainfall distribution over Jinsha River basin under B2 from May to October in different periods: (<b>a</b>) 2070–2099 rainfall compared with 1960–1990; (<b>b</b>) 2070–2099 rainfall compared with 1980–2010.</p>
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<p>Simulation of discharge for Jinsha River from May to October (1961–2099) under scenario A1B.</p>
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<p>Simulation results of Jinsha River discharge from May to October in 1961–2099 under scenario B2.</p>
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12919 KiB  
Article
Comparison of IMERG Level-3 and TMPA 3B42V7 in Estimating Typhoon-Related Heavy Rain
by Ren Wang, Jianyao Chen and Xianwei Wang
Water 2017, 9(4), 276; https://doi.org/10.3390/w9040276 - 22 Apr 2017
Cited by 32 | Viewed by 5652
Abstract
Typhoon-related heavy rain has unique structures in both time and space, and use of satellite-retrieved products to delineate the structure of heavy rain is especially meaningful for early warning systems and disaster management. This study compares two newly-released satellite products from the Integrated [...] Read more.
Typhoon-related heavy rain has unique structures in both time and space, and use of satellite-retrieved products to delineate the structure of heavy rain is especially meaningful for early warning systems and disaster management. This study compares two newly-released satellite products from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG final run) and the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA 3B42V7) with daily rainfall observed by ground rain gauges. The comparison is implemented for eight typhoons over the coastal region of China for a two-year period from 2014 to 2015. The results show that all correlation coefficients (CCs) of both IMERG and TMPA for the investigated typhoon events are significant at the 0.01 level, but they tend to underestimate the heavy rainfall, especially around the storm center. The IMERG final run exhibits an overall better performance than TMPA 3B42V7. It is also shown that both products have a better applicability (i.e., a smaller absolute relative bias) when rain intensities are within 20–40 and 80–100 mm/day than those of 40–80 mm/day and larger than 100 mm/day. In space, they generally have the best applicability within the range of 50–100 km away from typhoon tracks, and have the worst applicability beyond the 300-km range. The results are beneficial to understand the errors of satellite data in operational applications, such as storm monitoring and hydrological modeling. Full article
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<p>Study area and the spatial distribution of rain gauges.</p>
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<p>Statistical metrics (<span class="html-italic">ME</span>, <span class="html-italic">MAE</span>, RSME, and <span class="html-italic">CC</span>) of (<b>a1</b>–<b>a8</b>) the IMERG final run and (<b>b1</b>–<b>b8</b>) TMPA 3B42V7 against gauge observations for each typhoon event over the coastal region of China. The units of <span class="html-italic">ME</span>, <span class="html-italic">MAE</span>, and RSME is mm/day, and the range of <span class="html-italic">CC</span> is −1 to 1. ** The correlation is significant at the 0.01 level.</p>
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<p>Spatial distribution of total rainfall plotted for (<b>a</b>) gauge observations, (<b>b</b>) the IMERG final run, and (<b>c</b>) TMPA 3B42V7 for typhoon Matmo during the period of 23–25 July 2014.</p>
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<p>Spatial distribution of total rainfall (<b>a1</b>–<b>a4</b>), <span class="html-italic">RB</span> (%) in (<b>b1</b>–<b>b4</b>) IMERG and (<b>c1</b>–<b>c4</b>) TMPA for the typhoon events of Group I (Rammasun, Kalmaegi, Linfa, and Mujigae). Dots are scaled according to the magnitude of the overestimation or underestimation. The arrowed lines represent typhoon tracks.</p>
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<p>Spatial distribution of total rainfall (<b>a1</b>–<b>a4</b>), <span class="html-italic">RB</span> (%) in (<b>b1</b>–<b>b4</b>) IMERG and (<b>c1</b>–<b>c4</b>) TMPA for the typhoons of Group II (Chon-hom, Matmo, Soudelor, and Dujuan). Dots are scaled according to the magnitude of the overestimation or underestimation. The arrowed lines represent typhoon tracks.</p>
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<p>Scatter diagram and fitted curve of the rain intensity and <span class="html-italic">RB</span> in (<b>a</b>) IMERG final run and (<b>b</b>) TMPA 3B42V7 for the eight investigated typhoon events. The colors of the dots represent different magnitudes of <span class="html-italic">RB</span>.</p>
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<p>Variations of mean <span class="html-italic">RB</span> (%) and mean rain intensity (mm/day) within different buffer ranges (km) away from typhoon tracks during the period of (<b>a</b>) Rammasun, (<b>b</b>) Mujigae, (<b>c</b>) Kalmaegi, (<b>d</b>) Linfa, (<b>e</b>) Chon-hom, (<b>f</b>) Matmo, (<b>g</b>) Soudelor, and (<b>h</b>) Dujuan. The yellow histograms represent IMERG’s mean <span class="html-italic">RBs</span>, and the blue histograms represent TMPA’s mean <span class="html-italic">RBs</span>. The red polylines are the changes of mean rain intensity.</p>
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5000 KiB  
Article
Assessment of Social Vulnerability to Flood in Urban Côte d’Ivoire Using the MOVE Framework
by Malan Ketcha Armand Kablan, Kouassi Dongo and Mamadou Coulibaly
Water 2017, 9(4), 292; https://doi.org/10.3390/w9040292 - 21 Apr 2017
Cited by 64 | Viewed by 10820
Abstract
Coupled with poor urban development, the increasing urban population of many Sub-Saharan African countries is subject to recurrent severe flooding episodes. In response to these flood events, while the focus is often put on slums and precarious urban settings, the social implications of [...] Read more.
Coupled with poor urban development, the increasing urban population of many Sub-Saharan African countries is subject to recurrent severe flooding episodes. In response to these flood events, while the focus is often put on slums and precarious urban settings, the social implications of these floods affect a variety of social classes. Presenting a case study of Cocody, a district of Abidjan, Côte d’Ivoire, known to have the country’s highest number of flood-impacted people, this paper evaluates the social vulnerability of urban Côte d’Ivoire to flooding using the MOVE framework. The MOVE framework (Method for the Improvement of Vulnerability Assessment in Europe) has successfully been used in European contexts to assess social vulnerability of urban areas to geo-environmental disasters such floods. It helped assess the major factors involved in the social vulnerability to urban flooding and to have a good appreciation of the spatial distribution of areas that are vulnerable to urban flood. By taking this framework to the local context, relevant indicators were developed and GIS applications were used to assess spatially the relative social vulnerability of Cocody sub-districts to urban flooding. The results revealed that many sub-districts of Cocody are highly vulnerable to urban floods. Exposure and susceptibility are components that are found to have high influence on vulnerability to flood hazard in the district of Cocody. Their respective indicators need to be addressed properly in order to increase residents’ resilience to urban flooding. The MOVE theoretical framework can be applied in Africa by contextualizing the vulnerability by using local indicators. Full article
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<p>Localization of the district of Cocody.</p>
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<p>MOVE framework (source: [<a href="#B40-water-09-00292" class="html-bibr">40</a>]).</p>
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<p>Exposure to flood: (<b>a</b>) Population density map; (<b>b</b>) Flooded area map; (<b>c</b>) Elevation map; (<b>d</b>) Exposure map.</p>
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<p>Susceptibility to flood: (<b>a</b>) Vegetation cover map; (<b>b</b>) Percentage of elderly map; (<b>c</b>) Percentage of women map; (<b>d</b>) Percentage of children under five map; (<b>e</b>) Daily waste collection frequency map; (<b>f</b>) Unplanned waste deposit map; (<b>g</b>) Susceptibility map.</p>
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<p>Lack of resilience to flood: (<b>a</b>) Unemployment rate map; (<b>b</b>) Literacy rate map; (<b>c</b>) Insured people map; (<b>d</b>) Lack of resilience map.</p>
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<p>Map of vulnerability to flood.</p>
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1322 KiB  
Article
A Multi-Criteria Decision Analysis System for Prioritizing Sites and Types of Low Impact Development Practices: Case of Korea
by Jae Yeol Song and Eun-Sung Chung
Water 2017, 9(4), 291; https://doi.org/10.3390/w9040291 - 21 Apr 2017
Cited by 40 | Viewed by 7578
Abstract
This study developed a multi-criteria decision analysis (MCDA) framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM). Using TOPSIS method, which is a type [...] Read more.
This study developed a multi-criteria decision analysis (MCDA) framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM). Using TOPSIS method, which is a type of MCDA method, multiple types and sites of designated LID practices are prioritized. This system is named the Water Management Prioritization Module (WMPM). WMPM can simultaneously determine the priority of multiple LID types and sites. In this study, an infiltration trench and permeable pavement were considered for multiple sub-catchments in South Korea to demonstrate the WMPM procedures. The TOPSIS method was manually incorporated to select the vulnerable target sub-catchments and to prioritize the LID planning scenarios for multiple types and sites considering social, hydrologic and physical-geometric factors. In this application, the Delphi method and entropy theory were used to determine the subjective and objective weights, respectively. Full article
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<p>Detail procedure of Water Management Prioritization Module (WMPM).</p>
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<p>Model map of study region using the EPA’s SWMM.</p>
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<p>Screenshot of the 6th step of WMPM: generation and simulation of scenarios.</p>
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<p>Comparison of peak and total runoff using WMPM.</p>
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<p>Derived rankings of each alternative.</p>
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2204 KiB  
Article
Modeling Coupled Water and Heat Transport in the Root Zone of Winter Wheat under Non-Isothermal Conditions
by Rong Ren, Juanjuan Ma, Qiyun Cheng, Lijian Zheng, Xianghong Guo and Xihuan Sun
Water 2017, 9(4), 290; https://doi.org/10.3390/w9040290 - 21 Apr 2017
Cited by 6 | Viewed by 4875
Abstract
Temperature is an integral part of soil quality in terms of moisture content; coupling between water and heat can render a soil fertile, and plays a role in water conservation. Although it is widely recognized that both water and heat transport are fundamental [...] Read more.
Temperature is an integral part of soil quality in terms of moisture content; coupling between water and heat can render a soil fertile, and plays a role in water conservation. Although it is widely recognized that both water and heat transport are fundamental factors in the quantification of soil mass and energy balance, their computation is still limited in most models or practical applications in the root zone under non-isothermal conditions. This research was conducted to: (a) implement a fully coupled mathematical model that contains the full coupled process of soil water and heat transport with plants focused on the influence of temperature gradient on soil water redistribution and on the influence of change in soil water movement on soil heat flux transport; (b) verify the mathematical model with detailed field monitoring data; and (c) analyze the accuracy of the model. Results show the high accuracy of the model in predicting the actual changes in soil water content and temperature as a function of time and soil depth. Moreover, the model can accurately reflect changes in soil moisture and heat transfer in different periods. With only a few empirical parameters, the proposed model will serve as guide in the field of surface irrigation. Full article
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<p>Location of study sites.</p>
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<p>Test equipment.</p>
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<p>Precipitation and irrigation during the growth period of winter wheat.</p>
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<p>Comparison between simulated and observed values for soil water content in different stages of wheat growth.</p>
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<p>Comparison between simulated and observed values for soil temperature in different stages of wheat growth.</p>
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<p>Comparison between simulated and observed values for soil water content with time at different soil depths under conditions one and two.</p>
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<p>Comparison between simulated and observed values for soil temperature with time at different soil depths under conditions one and two.</p>
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<p>Comparison between simulated and observed values for soil water content with time at different soil depths under conditions one and three.</p>
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<p>Comparison between simulated and observed values for soil temperature with time at different soil depths under conditions one and three.</p>
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8803 KiB  
Article
Unsteady State Water Level Analysis for Discharge Hydrograph Estimation in Rivers with Torrential Regime: The Case Study of the February 2016 Flood Event in the Crati River, South Italy
by Eleonora Spada, Marco Sinagra, Tullio Tucciarelli and Daniela Biondi
Water 2017, 9(4), 288; https://doi.org/10.3390/w9040288 - 21 Apr 2017
Cited by 6 | Viewed by 5866
Abstract
Discharge hydrograph estimation during floods, in rivers with torrential regime, is often based on the use of rating curves extrapolated from very low stage–discharge measurements. To get a more reliable estimation, a reverse flow routing problem is solved using water level data measured [...] Read more.
Discharge hydrograph estimation during floods, in rivers with torrential regime, is often based on the use of rating curves extrapolated from very low stage–discharge measurements. To get a more reliable estimation, a reverse flow routing problem is solved using water level data measured in two gauged stations several kilometers from each other. Validation of the previous analysis carried out on the flood event of February 2016 at the Europa Bridge and Castiglione Scalo sections of the Crati River (Cosenza, Italy) is based on the use of ‘soft’ discharge measurement data and the comparison of the water level data computed in the downstream gauged section by three different hydraulic models with the ‘hard’ available water level measures. Results confirm that the 1D diffusive model provides more reliable results than the 1D complete one and no significant improvement is gained by the use of a more computationally demanding 2D model. Full article
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<p>Location of the investigated reach of the Crati River (Europa bridge–Castiglione Scalo) and of the river gauging stations.</p>
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<p>Streamflow time series for a typical year (2001) at Castiglione Scalo.</p>
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<p>Morphology of the Crati River basin with the location of the hydrometric gauged sections.</p>
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<p>Estimated discharge hydrographs at the monitoring sites of Busento and Crati river gauged sections and at Europa Bridge.</p>
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<p>Crati River, February 2016 flood: comparison between observed and computed stage hydrographs at Castiglione Scalo site (‘hard’ data).</p>
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<p>Castiglione Scalo section, 1D diffusive model: Nash Sutcliffe, NSh, versus: (<b>a</b>) <span class="html-italic">C</span><sub>1</sub> and <span class="html-italic">n</span> parameters for fixed optimum <span class="html-italic">C</span><sub>2</sub> parameter; (<b>b</b>) <span class="html-italic">C</span><sub>2</sub> and <span class="html-italic">n</span> parameters for fixed optimum <span class="html-italic">C</span><sub>1</sub> parameter; (<b>c</b>) <span class="html-italic">C</span><sub>1</sub> and <span class="html-italic">C</span><sub>2</sub> parameters for fixed optimum n parameter.</p>
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<p>Inundated area computed by the 2D model (<b>a</b>) at Europa bridge site and (<b>b</b>) at Castiglione Cosentino site.</p>
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<p>Comparison between observed and computed discharge hydrographs at Europa Bridge site for the 1D models and the 2D model (‘soft’ data).</p>
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<p>Comparison between observed and computed discharge hydrographs at Castiglione Scalo site for the 1D models and the 2D model (‘soft’ data).</p>
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<p>Comparison between the computed tributaries discharge hydrographs (Campagnano and Surdo) for the 1D models: (<b>a</b>) Campagnano; (<b>b</b>) Surdo.</p>
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9327 KiB  
Article
Possibilities of Using Low Quality Digital Elevation Models of Floodplains in Hydraulic Numerical Models
by Ireneusz Laks, Mariusz Sojka, Zbigniew Walczak and Rafał Wróżyński
Water 2017, 9(4), 283; https://doi.org/10.3390/w9040283 - 21 Apr 2017
Cited by 30 | Viewed by 5699
Abstract
The paper presents a method for the correction of low quality DEMs, based on aerial photographs, for use in 2D flood modeling. The proposed method was developed and tested on the example of the floodplain of the Warta River, which is the third [...] Read more.
The paper presents a method for the correction of low quality DEMs, based on aerial photographs, for use in 2D flood modeling. The proposed method was developed and tested on the example of the floodplain of the Warta River, which is the third biggest river in Poland. The correction of DEM is based on a series of a small number of measurements using GPS-RTK, which enable calculations of the global statistics like mean error (ME), root mean square error (RMSE) and standard deviation (SD). The impact of DEM accuracy was estimated by using a 2D numerical model. The calculated values of flow velocities, inundation area and volume of floodplain for each tested DEM were compared. The analyses indicate that, after the correction procedure, the predictions of corrected DEM based on poor quality data is in good quantitative and qualitative agreement with the referenced LIDAR DEM. The proposed method may be applied in the areas for which high resolution DEMs based on LIDAR data are not available. Full article
(This article belongs to the Special Issue Modeling of Water Systems)
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<p>Flowchart for data preparation for 2D hydraulic modeling.</p>
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<p>Study site location.</p>
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<p>DEM with the river bathymetry and assignment of the elevation values interpolated from DEM to the nodes of the FEM mesh. (<b>a</b>) Original DEM; (<b>b</b>) main channel river bathymetry interpolation; (<b>c</b>) DEM supplemented with river bathymetry (<b>d</b>) FEM mesh with the elevation interpolated from DEM supplemented with river bathymetry.</p>
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<p>(<b>a</b>) The calculated and measured water level hydrographs for the flood of 2010 in the section 352.170; and (<b>b</b>) relationship between the water level and flow rate on the basis of the results obtained from the 1D model for the cross-section 351.82.</p>
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<p>Histogram of the errors ∆<span class="html-italic">h</span> in meters (<b>a</b>); and the normal Q-Q plot for the distribution of errors (<b>b</b>).</p>
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<p>(<b>a</b>) Differences between the reference DEM based on LIDAR data and the original DEM and corrected DEM; (<b>b</b>) distribution of differences between the models.</p>
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<p>Relationship between the elevation according to the reference DEM vs. original DEM (<b>a</b>); and from the reference DEM vs. corrected DEM (<b>b</b>).</p>
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<p>Comparison of the measured elevation at a selected cross-section with elevation points derived from the original, corrected and referenced DEMs.</p>
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<p>Comparison of the curves describing the relationship of the elevation of the water table at the cross-section 351.820 and the volume of accumulated water, calculated on the basis of the results of the 2D model.</p>
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<p>Comparison of the flooded area and inundation depth values for the flow rate equal to 279.1 m<sup>3</sup>·s<sup>−1</sup>: (<b>a</b>) original DEM; (<b>b</b>) corrected DEM; and (<b>c</b>) reference DEM.</p>
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<p>Comparison of the velocity distributions obtained from the 2D model for the flow rate equal to 279.1 m<sup>3</sup>·s<sup>−1</sup>: (<b>a</b>) DEM with the comparison area marked as the red rectangle; (<b>b</b>) original DEM; (<b>c</b>) corrected DEM; and (<b>d</b>) reference DEM.</p>
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<p>Relations between the velocity values obtained from the 2D model for the reference DEM and (<b>a</b>) corrected DEM and (<b>b</b>) original DEM. Variants for the flow rate equal to 279.1 m<sup>3</sup>·s<sup>−1</sup>.</p>
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<p>Distribution of vertical averaged velocity obtained from the 2D model and measured during the flood in year 2010 at the cross-section 352.398.</p>
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2474 KiB  
Article
Evaluation of the Water Cycle in the European COSMO-REA6 Reanalysis Using GRACE
by Anne Springer, Annette Eicker, Anika Bettge, Jürgen Kusche and Andreas Hense
Water 2017, 9(4), 289; https://doi.org/10.3390/w9040289 - 20 Apr 2017
Cited by 14 | Viewed by 8674
Abstract
Precipitation and evapotranspiration, and in particular the precipitation minus evapotranspiration deficit ( P E ), are climate variables that may be better represented in reanalyses based on numerical weather prediction (NWP) models than in other datasets. P E provides essential information [...] Read more.
Precipitation and evapotranspiration, and in particular the precipitation minus evapotranspiration deficit ( P E ), are climate variables that may be better represented in reanalyses based on numerical weather prediction (NWP) models than in other datasets. P E provides essential information on the interaction of the atmosphere with the land surface, which is of fundamental importance for understanding climate change in response to anthropogenic impacts. However, the skill of models in closing the atmospheric-terrestrial water budget is limited. Here, total water storage estimates from the Gravity Recovery and Climate Experiment (GRACE) mission are used in combination with discharge data for assessing the closure of the water budget in the recent high-resolution Consortium for Small-Scale Modelling 6-km Reanalysis (COSMO-REA6) while comparing to global reanalyses (Interim ECMWF Reanalysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)) and observation-based datasets (Global Precipitation Climatology Centre (GPCC), Global Land Evaporation Amsterdam Model (GLEAM)). All 26 major European river basins are included in this study and aggregated to 17 catchments. Discharge data are obtained from the Global Runoff Data Centre (GRDC), and insufficiently long time series are extended by calibrating the monthly Génie Rural rainfall-runoff model (GR2M) against the existing discharge observations, subsequently generating consistent model discharge time series for the GRACE period. We find that for most catchments, COSMO-REA6 closes the water budget within the error estimates. In contrast, the global reanalyses underestimate P E with up to 20 mm/month. For all models and catchments, short-term (below the seasonal timescale) variability of atmospheric terrestrial flux agrees well with GRACE and discharge data with correlations of about 0.6. Our large study area allows identifying regional patterns like negative trends of P E in eastern Europe and positive trends in northwestern Europe. Full article
(This article belongs to the Special Issue The Use of Remote Sensing in Hydrology)
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<p>Study area: 26 European river basins, which are aggregated to 17 catchments as indicated by the different colors.</p>
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<p>Discharge available from the Global Runoff Data Centre (GRDC) for the most downstream gauging stations of the rivers in our study region. The monthly Génie Rural rainfall-runoff model with snow extension (GR2M-snow) is calibrated against the 10 most recent continuous years of each basin (marked by light blue). In red, the Gravity Recovery and Climate Experiment (GRACE) time span is indicated.</p>
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<p>Discharge <span class="html-italic">R</span> for the Rhine from Global Runoff Data Centre (GRDC) (blue) and simulated from Génie Rural rainfall-runoff model (GR2M)-snow (red) including the standard deviation (grey).</p>
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<p>Total water storage (TWS) change <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Δ</mi> <mi>S</mi> </mrow> </semantics> </math> (red) and its standard deviation (grey) for two selected river basins.</p>
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<p>Monthly total precipitation <span class="html-italic">P</span> from different models and simulated discharge <span class="html-italic">R</span> (black dashed) for selected catchments of the study area.</p>
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<p>Monthly total evapotranspiration <span class="html-italic">E</span> from different models for selected catchments of the study area.</p>
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<p>The closure of the water budget equation <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Δ</mi> <mi>S</mi> <mo>+</mo> <mi>R</mi> <mo>=</mo> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> is assessed for selected river basins. The left side of the equation is represented by the red line and includes propagated standard deviations (black). All time series are smoothed with a three-month moving average filter to facilitate interpretation.</p>
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<p>De-seasoned and de-trended time series of <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Δ</mi> <mi>S</mi> <mo>+</mo> <mi>R</mi> </mrow> </semantics> </math> (red) for selected river basins.</p>
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<p>Correlation of <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Δ</mi> <mi>S</mi> <mo>+</mo> <mi>R</mi> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> from COSMO-REA6 Reanalysis for (<b>a</b>) the original time series, as shown in <a href="#water-09-00289-f007" class="html-fig">Figure 7</a>, and (<b>b</b>) de-trended and de-seasoned time series, as shown in <a href="#water-09-00289-f008" class="html-fig">Figure 8</a>.</p>
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<p>(<b>a</b>–<b>d</b>) Bias of the water budget equation given in equivalent water height (EWH): red color means that <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> is underestimated, and blue color means that <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> is overestimated. (<b>e</b>) provides as a reference the propagated error of the left side of the water budget equation.</p>
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<p>Amplitudes of <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Δ</mi> <mi>S</mi> <mo>+</mo> <mi>R</mi> </mrow> </semantics> </math> given in equivalent water height (EWH).</p>
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<p>Trend of <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>−</mo> <mi>E</mi> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Δ</mi> <mi>S</mi> <mo>+</mo> <mi>R</mi> </mrow> </semantics> </math> given in equivalent water height (EWH).</p>
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254 KiB  
Article
Hydropower Royalties: A Comparative Analysis of Major Producing Countries (China, Brazil, Canada and the United States)
by Pierre-Olivier Pineau, Lucile Tranchecoste and Yenny Vega-Cárdenas
Water 2017, 9(4), 287; https://doi.org/10.3390/w9040287 - 20 Apr 2017
Cited by 15 | Viewed by 10002
Abstract
Hydropower is the leading renewable source of electricity generation and a low emission energy source. In order to be developed sustainably, it is important that its costs and benefits are adequately set and distributed. Different mechanisms, such as royalties, can be used for [...] Read more.
Hydropower is the leading renewable source of electricity generation and a low emission energy source. In order to be developed sustainably, it is important that its costs and benefits are adequately set and distributed. Different mechanisms, such as royalties, can be used for this purpose. Governments have usually kept hydropower royalty rates low, without internalizing negative externalities. This strategy is inefficient because it leads to larger electricity production and consumption, and hence exacerbates environmental impacts. This paper reviews the criteria proposed and used to set hydropower royalties. It also compares practices of the four main hydropower producers in the world: China, Brazil, Canada and the United States. Results show that royalty rates and distribution policies are determined in an arbitrary and unsystematic manner, but also that water use is usually undervalued. In order to encourage the development of this key renewable resource, in a sustainable and responsible way, national and international efforts should be made to rationalize and harmonize hydropower royalty rates. Full article
(This article belongs to the Special Issue Water Economics and Policy)
1569 KiB  
Article
Can Water Abundance Compensate for Weak Water Governance? Determining and Comparing Dimensions of Irrigation Water Security in Tajikistan
by Frederike Klümper, Thomas Herzfeld and Insa Theesfeld
Water 2017, 9(4), 286; https://doi.org/10.3390/w9040286 - 19 Apr 2017
Cited by 15 | Viewed by 6983
Abstract
In this paper we consider both hydrology and governance as critical dimensions for irrigation water security. We scale down the overall water security concept to the agricultural sector, suggest an index of irrigation water security faced by farmers, and provide an empirical illustration [...] Read more.
In this paper we consider both hydrology and governance as critical dimensions for irrigation water security. We scale down the overall water security concept to the agricultural sector, suggest an index of irrigation water security faced by farmers, and provide an empirical illustration in the case of Tajikistan. Irrigation water security is investigated by three different dimensions: (a) a hydrology dimension, expressing a lack of water availability; (b) a governance dimension, the perceived difficulty in accessing water; and (c) a hybrid dimension of governance and hydrology. We developed an irrigation water security index, which we empirically tested using farm household survey data (N = 399). This index provides evidence that different farm types, e.g., small versus large, perceive different water security threats. Further, we found that if one dimension is less distinctive, the complementary dimension occurs as a coping mechanism. Thus, we conclude that diversified support mechanisms for infrastructure and management are needed to reach a higher level of water security. Full article
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<p>Three dimensions to design the irrigation water security index. Source: Own Figure.</p>
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<p>Topographic map of Tajikistan indicating the case study regions. Source: Figure prepared by Neumann and Klümper based on Global Administrative Areas (GADM), version 1 and Data from the Consultative Group in International Agricultural Research—Shuttle Radar Topography Mission (CGIAR SRTM); <a href="http://srtm.csi.cgiar.org/" target="_blank">http://srtm.csi.cgiar.org/</a>.</p>
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<p>Distribution (k-density plots) of the three dimensions of irrigation water security. Source: Survey data 2013; Note: Scale from 1 = insecure to 5 = secure.</p>
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<p>Boxplot of hydrology and governance dimensions across farm types. Source: Survey Data 2013.</p>
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1204 KiB  
Review
Urban Water Cycle Simulation/Management Models: A Review
by Carlos Andrés Peña-Guzmán, Joaquín Melgarejo, Daniel Prats, Andrés Torres and Sandra Martínez
Water 2017, 9(4), 285; https://doi.org/10.3390/w9040285 - 19 Apr 2017
Cited by 28 | Viewed by 14974
Abstract
Urban water management is increasingly important given the need to maintain water resources that comply with global and local standards of quantity and quality. The effective management of water resources requires the optimization of financial resources without forsaking social requirements. A number of [...] Read more.
Urban water management is increasingly important given the need to maintain water resources that comply with global and local standards of quantity and quality. The effective management of water resources requires the optimization of financial resources without forsaking social requirements. A number of mathematical models have been developed for this task; such models account for all components of the Urban Water Cycle (UWC) and their interactions. The wide range of models entails the need to understand their differences in an effort to identify their applicability, so academic, state, and private sectors can employ them for environmental, economic, and social ends. This article presents a description of the UWC and relevant components, a literature review of different models developed between 1990 and 2015, and an analysis of several case studies (applications). It was found that most applications are focused on new supply sources, mainly rainwater. In brief, this article provides an overview of each model’s use (primarily within academia) and potential use as a decision-making tool. Full article
(This article belongs to the Special Issue Synergies in Urban Water Infrastructure Modeling)
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<p>Urban Water Cycle (UWC). Adapted from [<a href="#B58-water-09-00285" class="html-bibr">58</a>].</p>
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<p>Experiments reported by country.</p>
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1669 KiB  
Article
Temporal Distribution Characteristics of Alpine Precipitation and Their Vertical Differentiation: A Case Study from the Upper Shule River
by Qingfeng Li and Guojing Yang
Water 2017, 9(4), 284; https://doi.org/10.3390/w9040284 - 19 Apr 2017
Cited by 8 | Viewed by 5091
Abstract
Alpine precipitation is an important component of the mountain hydrological cycle and may also be a determinant of water resources in inland river basins. In this study, based on field observation data of the upper Shule River and daily precipitation records of the [...] Read more.
Alpine precipitation is an important component of the mountain hydrological cycle and may also be a determinant of water resources in inland river basins. In this study, based on field observation data of the upper Shule River and daily precipitation records of the Tuole weather station during 2009–2015, temporal distribution characteristics of alpine precipitation and their vertical differentiation were evaluated mainly using percentages of precipitation anomalies (Pa), coefficient of variation (Cv), precipitation concentration degree (PCD) and concentration period (PCP). The results indicated that the inter-annual variability of annual precipitation was generally small, with a Pa that was only somewhat larger in low altitude zones for individual years; the inter-annual fluctuation of monthly precipitation increased noticeably, but the Cv and precipitation can be described as a power function. Annual distribution was basically consistent; more than 85.6% of precipitation was concentrated during the period from May to September; PCD ranged between 0.71 and 0.83 while the PCP was located within the 37th–41st pentads. Diurnal variation of precipitation was defined, mainly occurring from 1500 to 0100 Local Standard Time, and displayed a vertical change that was dominated by precipitation intensity or precipitation frequency. The temporal distribution of alpine precipitation has a noticeable vertical differentiation, and this is likely to originate from the diversity of precipitation mechanisms in mountainous terrain areas. Full article
(This article belongs to the Special Issue Sustainable Water Management within Inland River Watershed)
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<p>Precipitation observing sites in the upper reaches of the Shule River.</p>
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<p><span class="html-italic">Pa</span> of annual precipitation from 2009 to 2015.</p>
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<p>Correlation between Cv and average monthly precipitation during 2009–2015. The trend line was derived from data from all four sites, whereas that of the single site is not shown. The superscript ‘**’ indicates statistical significance at the 99% confidence level.</p>
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<p>Distribution of average monthly precipitation during 2009–2015. Error bars represent one standard deviation.</p>
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<p>Diurnal variation of precipitation in the rainy season of 2013.</p>
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7333 KiB  
Article
Large Differences between Glaciers 3D Surface Extents and 2D Planar Areas in Central Tianshan
by Xianwei Wang, Huijiao Chen and Yaning Chen
Water 2017, 9(4), 282; https://doi.org/10.3390/w9040282 - 17 Apr 2017
Cited by 5 | Viewed by 5926
Abstract
Most glaciers in China lie in high mountainous environments and have relatively large surface slopes. Common analyses consider glaciers’ projected areas (2D Area) in a two-dimensional plane, which are much smaller than glacier’s topographic surface extents (3D Area). The areal difference between 2D [...] Read more.
Most glaciers in China lie in high mountainous environments and have relatively large surface slopes. Common analyses consider glaciers’ projected areas (2D Area) in a two-dimensional plane, which are much smaller than glacier’s topographic surface extents (3D Area). The areal difference between 2D planar areas and 3D surface extents exceeds −5% when the glacier’s surface slope is larger than 18°. In this study, we establish a 3D model in the Muzart Glacier catchment using ASTER GDEM data. This model is used to quantify the areal difference between glaciers’ 2D planar areas and their 3D surface extents in various slope zones and elevation bands by using the second Chinese Glacier Inventory (CGI2). Finally, we analyze the 2D and 3D area shrinking rate between 2007 and 2013 in Central Tianshan using glaciers derived from Landsat images by an object-based classification approach. This approach shows an accuracy of 89% when it validates by comparison of glaciers derived from Landsat and high spatial resolution GeoEye images. The extracted glaciers in 2007 also have an agreement of 89% with CGI2 data in the Muzart Glacier catchment. The glaciers’ 3D area is 34.2% larger than their 2D area from CGI2 in the Muzart Glacier catchment and by 27.9% in the entire Central Tianshan. Most underestimation occurs in the elevation bands of 4000–5000 m above sea level (a.s.l.). The 3D glacier areas reduced by 30 and 115 km2 between 2007 and 2013 in the Muzart Glacier catchment and Central Tianshan, being 37.0% and 27.6% larger than their 2D areas reduction, respectively. The shrinking rates decrease with elevation increase. Full article
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<p>Schematic diagram of the definitions of glacier’s area (A) and thickness (T) in a longitudinal glacier profile.</p>
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<p>Study area in Central Tianshan Mountain and the Muzart Glacier catchment (yellow line) of the upper Muzart River Basin, China. The analyzing areas are constrained by the 2500 m elevation contour (dark blue line).</p>
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<p>Flowcharts of glacier outline delineation using object-based image classification.</p>
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<p>Glacier outlines derived from Landsat images (yellow polygons) and GeoEye images (blue polygon and background images) using object-based classification in the upper sub-catchment of the Muzart Glacier catchment on 20 April 2015.</p>
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<p>Comparison of glacier outlines of CGI2 (blue polygon) and those derived from Landsat images (yellow polygons and background images) in this study using object-based classification in the Muzart Glacier catchment on 24 August 2007.</p>
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<p>Histogram of glacier 2D and 3D areas within different slope zones based on the second Chinese Glacier Inventory (CGI2) data (<b>a</b>) and glaciers classified from Landsat images (<b>b</b>) on 24 August 2007 in the Muzart Glacier catchment. The numbers above the columns are the frequency percentages of glacier areas in each slope zones against total 2D and 3D areas, respectively.</p>
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<p>Histogram of Glacier 2D and 3D areas within different elevation bands in 2007 in the Muzart Glacier catchment (<b>a</b>) and Central Tianshan (<b>b</b>). The numbers above the columns are the frequency percentages of glacier areas in each elevation bands against the total 2D and 3D areas, respectively.</p>
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<p>Histogram of Glacier 2D and 3D area difference between 2007 and 2013 (2013–2007) in different elevation bands in the Muzart Glacier catchment (<b>a</b>) and Central Tianshan (<b>b</b>). The numbers above columns are the area shrinking rates ((2013–2007)/2007) in each elevation bands.</p>
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<p>Comparison of 3D (<b>a</b>) and 2D (<b>b</b>) glacier outlines in 2007 (green lines) and 2013 (white lines) in a glacier sub-catchment of the Muzart Glacier catchment (mid-west). The background image is the Landsat 8 on 10 September 2013.</p>
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175 KiB  
Editorial
Water Resources Management: Innovation and Challenges in a Changing World
by Ashantha Goonetilleke and Meththika Vithanage
Water 2017, 9(4), 281; https://doi.org/10.3390/w9040281 - 17 Apr 2017
Cited by 34 | Viewed by 9378
Abstract
The prudent management of water resources is essential for human and ecosystem well-being. As a result of ever escalating and competing demands, compounded by pollution and climate change-driven impacts, available freshwater resources are becoming increasingly stressed. This is further compounded by poor management [...] Read more.
The prudent management of water resources is essential for human and ecosystem well-being. As a result of ever escalating and competing demands, compounded by pollution and climate change-driven impacts, available freshwater resources are becoming increasingly stressed. This is further compounded by poor management practices and the unsustainable extraction of water. Consequently, many parts of the world, particularly urban areas, are facing water shortages. Therefore, water resources management requires a clear understanding of the ongoing challenges and innovative approaches. This Special Issue provides the platform for the dissemination of knowledge and best practices to strengthen the management of our precious water resources into the future. Full article
7219 KiB  
Article
Optimal Operation Research of Flood Retarding in Plain River Network Region
by Zhenye Zhu, Zengchuan Dong, Wanhong Yang, Jie Zhou, Dayong Li, Xiaohua Fu and Wei Xu
Water 2017, 9(4), 280; https://doi.org/10.3390/w9040280 - 17 Apr 2017
Cited by 6 | Viewed by 5005
Abstract
The operation of flood retarding areas does not attract much attention, although they are important components of flood control systems. Poor operation of such areas restricts not only the socio-economic development of the flood retarding area, but also limits scientific flood control options. [...] Read more.
The operation of flood retarding areas does not attract much attention, although they are important components of flood control systems. Poor operation of such areas restricts not only the socio-economic development of the flood retarding area, but also limits scientific flood control options. As the second-largest flood retarding area in China, with more than 2000 km2 and 300 polders, the Hongze Lake vicinity was taken as a case study of graded flood retarding. A one and two-dimensional coupled hydrodynamic model was established to simulate flood routing in the Hongze Lake area. Fifteen different schemes involving different flood magnitudes and flood retarding operations were simulated. The results show that (1) having a flood retarding area is essential; and (2) the “graded flood retarding” scheme is superior to “no grading flood retarding” scheme; and (3) a “two-grade flood retarding” scheme is recommended. Full article
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Figure 1

Figure 1
<p>Location of Hongze Lake area.</p>
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<p>Land use in the vicinity of Hongze Lake.</p>
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<p>Roads in the vicinity of Hongze Lake.</p>
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<p>Diagram of the model coupling.</p>
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<p>Distribution of gross domestic product (GDP) and population.</p>
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<p>Treatment of cross sections beside the “Three beaches” area: (<b>a</b>) Original measured cross-section; and (<b>b</b>) Processed cross-section.</p>
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<p>“Narrow Slit” method: (<b>a</b>) Original measured cross-section; and (<b>b</b>) Processed cross-section.</p>
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<p>Different grid sizes for Hongze Lake and the flood retarding area.</p>
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<p>Distribution of polders of four flood retarding schemes. (<b>a</b>) no grading scheme; (<b>b</b>) graded Scheme 1; (<b>c</b>) graded Scheme 2; (<b>d</b>) graded Scheme 3.</p>
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<p>Simulated and observed water levels at five gauging stations in 2003 and 2007: (<b>a</b>) Location of the five gauging stations; (<b>b</b>) Jiangba station; (<b>c</b>) Laozishan station; (<b>d</b>) Linhuaitou station; (<b>e</b>) Xiangchengzhuang station; and (<b>f</b>) Shangzui station.</p>
Full article ">Figure 10 Cont.
<p>Simulated and observed water levels at five gauging stations in 2003 and 2007: (<b>a</b>) Location of the five gauging stations; (<b>b</b>) Jiangba station; (<b>c</b>) Laozishan station; (<b>d</b>) Linhuaitou station; (<b>e</b>) Xiangchengzhuang station; and (<b>f</b>) Shangzui station.</p>
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<p>Water level of Hongze Lake: (<b>a</b>) flood event <span class="html-italic">p</span> = 1%; (<b>b</b>) flood event <span class="html-italic">p</span> = 0.33%; and (<b>c</b>) flood event <span class="html-italic">p</span> = 0.05%.</p>
Full article ">Figure 11 Cont.
<p>Water level of Hongze Lake: (<b>a</b>) flood event <span class="html-italic">p</span> = 1%; (<b>b</b>) flood event <span class="html-italic">p</span> = 0.33%; and (<b>c</b>) flood event <span class="html-italic">p</span> = 0.05%.</p>
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<p>Maximum flood inundation maps. (<b>a</b>) <span class="html-italic">p</span> = 1% no grading; (<b>b</b>) <span class="html-italic">p</span> = 1% graded 1; (<b>c</b>) <span class="html-italic">p</span> = 1% graded 2; (<b>d</b>) <span class="html-italic">p</span> = 1% graded 3; (<b>e</b>) <span class="html-italic">p</span> = 0.33% no grading; (<b>f</b>) <span class="html-italic">p</span> = 0.05% no grading.</p>
Full article ">Figure 12 Cont.
<p>Maximum flood inundation maps. (<b>a</b>) <span class="html-italic">p</span> = 1% no grading; (<b>b</b>) <span class="html-italic">p</span> = 1% graded 1; (<b>c</b>) <span class="html-italic">p</span> = 1% graded 2; (<b>d</b>) <span class="html-italic">p</span> = 1% graded 3; (<b>e</b>) <span class="html-italic">p</span> = 0.33% no grading; (<b>f</b>) <span class="html-italic">p</span> = 0.05% no grading.</p>
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338 KiB  
Article
Daily Based Morgan–Morgan–Finney (DMMF) Model: A Spatially Distributed Conceptual Soil Erosion Model to Simulate Complex Soil Surface Configurations
by Kwanghun Choi, Sebastian Arnhold, Bernd Huwe and Björn Reineking
Water 2017, 9(4), 278; https://doi.org/10.3390/w9040278 - 17 Apr 2017
Cited by 16 | Viewed by 11456
Abstract
In this paper, we present the Daily based Morgan–Morgan–Finney model. The main processes in this model are based on the Morgan–Morgan–Finney soil erosion model, and it is suitable for estimating surface runoff and sediment redistribution patterns in seasonal climate regions with complex surface [...] Read more.
In this paper, we present the Daily based Morgan–Morgan–Finney model. The main processes in this model are based on the Morgan–Morgan–Finney soil erosion model, and it is suitable for estimating surface runoff and sediment redistribution patterns in seasonal climate regions with complex surface configurations. We achieved temporal flexibility by utilizing daily time steps, which is suitable for regions with concentrated seasonal rainfall. We introduce the proportion of impervious surface cover as a parameter to reflect its impacts on soil erosion through blocking water infiltration and protecting the soil from detachment. Also, several equations and sequences of sub-processes are modified from the previous model to better represent physical processes. From the sensitivity analysis using the Sobol’ method, the DMMF model shows the rational response to the input parameters which is consistent with the result from the previous versions. To evaluate the model performance, we applied the model to two potato fields in South Korea that had complex surface configurations using plastic covered ridges at various temporal periods during the monsoon season. Our new model shows acceptable performance for runoff and the sediment loss estimation ( NSE 0.63 , | PBIAS | 17.00 , and RSR 0.57 ). Our findings demonstrate that the DMMF model is able to predict the surface runoff and sediment redistribution patterns for cropland with complex surface configurations. Full article
(This article belongs to the Special Issue Soil Erosion by Water)
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Figure 1

Figure 1
<p>Schematic hydrological processes within an element. The hydrological phase estimates the amount of surface runoff (<span class="html-italic">Q</span>; mm) and subsurface interflow (<math display="inline"> <semantics> <mrow> <mi>I</mi> <msub> <mi>F</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics> </math>; <math display="inline"> <semantics> <mi mathvariant="normal">L</mi> </semantics> </math>) generated from an element. Assuming that the surface area of an element is <span class="html-italic">A</span> (<math display="inline"> <semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mrow> <mn>2</mn> </mrow> </msup> </mrow> </semantics> </math>), surface water inputs of an element is the effective rainfall (<math display="inline"> <semantics> <msub> <mi>R</mi> <mrow> <mi>e</mi> <mi>f</mi> <mi>f</mi> </mrow> </msub> </semantics> </math>; mm) and surface water contribution from upslope elements (<math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Σ</mi> <mrow> <mo>(</mo> <msub> <mi>Q</mi> <mrow> <mi>i</mi> <mi>n</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>/</mo> <mi>A</mi> </mrow> </semantics> </math>; mm). Surface runoff occurs when surface water inputs exceed surface water infiltration capacity, (<math display="inline"> <semantics> <mrow> <mi>S</mi> <msub> <mi>W</mi> <mi>c</mi> </msub> </mrow> </semantics> </math>; mm) which depends on available soil pore space left for surface water infiltration and the proportion of the impervious surface area (<math display="inline"> <semantics> <mrow> <mi>I</mi> <mi>M</mi> <mi>P</mi> </mrow> </semantics> </math>). The subsurface interflow occurs when the soil water budget (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>W</mi> </mrow> </semantics> </math>; mm) exceeds the soil water at field capacity (<math display="inline"> <semantics> <mrow> <mi>S</mi> <msub> <mi>W</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> </mrow> </semantics> </math>; mm). In this condition, a part of the excess soil water outflows from an element as an interflow, and the surface runoff and subsurface interflow generated in an element are discharged to downslope elements.</p>
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<p>Conceptual representation of the effective rainfall (<math display="inline"> <semantics> <msub> <mi>R</mi> <mrow> <mi>e</mi> <mi>f</mi> <mi>f</mi> </mrow> </msub> </semantics> </math>) on a slope element without permanent interception of rainfall (modified from Figure 1 of Choi et al. [<a href="#B39-water-09-00278" class="html-bibr">39</a>]). Given rainfall with a total volume of <span class="html-italic">P</span>, the amount of rainfall per unit area for both <span class="html-italic">A</span> (<math display="inline"> <semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mrow> <mn>2</mn> </mrow> </msup> </mrow> </semantics> </math>) and <math display="inline"> <semantics> <msup> <mi>A</mi> <mo>′</mo> </msup> </semantics> </math> (<math display="inline"> <semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mrow> <mn>2</mn> </mrow> </msup> </mrow> </semantics> </math>) is <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>/</mo> <mi>A</mi> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>/</mo> <msup> <mi>A</mi> <mo>′</mo> </msup> </mrow> </semantics> </math> which is equal to <span class="html-italic">R</span>. From the trigonometric rule, <span class="html-italic">A</span>, the projected area of <math display="inline"> <semantics> <msup> <mi>A</mi> <mo>′</mo> </msup> </semantics> </math> on the slope, is described as <math display="inline"> <semantics> <mrow> <msup> <mi>A</mi> <mo>′</mo> </msup> <mo>/</mo> <mi>cos</mi> <mrow> <mo>(</mo> <mi>S</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>. Therefore, the rainfall per unit surface area of the element (i.e., the effective rainfall) should be <math display="inline"> <semantics> <mrow> <mi>R</mi> <mo>·</mo> <mi>cos</mi> <mo>(</mo> <mi>S</mi> <mo>)</mo> </mrow> </semantics> </math>.</p>
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<p>Conceptual representation of interflow in an element (modified from Figure 3 of Choi et al. [<a href="#B39-water-09-00278" class="html-bibr">39</a>]). Let’s assume that there is an element with the width of <span class="html-italic">w</span>, the length of <span class="html-italic">l</span> and slope of <span class="html-italic">S</span>. Then, given transferable soil water for interflow (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>W</mi> <mo>−</mo> <mi>S</mi> <msub> <mi>W</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> </mrow> </semantics> </math>) and saturated soil lateral hydraulic conductivity (<span class="html-italic">K</span>), the volume of interflow from the element (<math display="inline"> <semantics> <mrow> <mi>I</mi> <msub> <mi>F</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics> </math>) can be represented as <math display="inline"> <semantics> <mrow> <mi>K</mi> <mo>·</mo> <mi>sin</mi> <mrow> <mo>(</mo> <mi>S</mi> <mo>)</mo> </mrow> <mo>·</mo> <mrow> <mo>(</mo> <mi>S</mi> <mi>W</mi> <mo>−</mo> <mi>S</mi> <msub> <mi>W</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>·</mo> <mi>w</mi> </mrow> </semantics> </math>, and cannot exceed the volume of the transferable soil water of the element (<math display="inline"> <semantics> <mrow> <mo>(</mo> <mi>S</mi> <mi>W</mi> <mo>−</mo> <mi>S</mi> <msub> <mi>W</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> <mo>)</mo> <mo>·</mo> <mi>A</mi> </mrow> </semantics> </math>).</p>
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<p>Schematic sediment phase of an element. The model estimates the amount of sediment loss from an element through three steps. In the first step, detached soil particles from an element (by raindrop (<span class="html-italic">F</span>) and runoff (<span class="html-italic">H</span>)) and sediment inputs from upslope elements (<math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Σ</mi> <mo>(</mo> <mi>S</mi> <msub> <mi>L</mi> <mrow> <mi>i</mi> <mi>n</mi> </mrow> </msub> <mo>)</mo> <mo>/</mo> <mi>A</mi> </mrow> </semantics> </math>) are delivered to the surface water of an element. Second, some of the suspended sediments (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>S</mi> </mrow> </semantics> </math>) delivered in the runoff settle down due to gravity at the deposition rate of the suspended sediments in the runoff (<math display="inline"> <semantics> <mrow> <mi>D</mi> <mi>E</mi> <mi>P</mi> </mrow> </semantics> </math>). Third, the model estimates the amount of sediment loss from an element by comparing the transport capacity of the runoff (<math display="inline"> <semantics> <mrow> <mi>T</mi> <mi>C</mi> </mrow> </semantics> </math>) and sediments available for transport (<span class="html-italic">G</span>), which are the remaining suspended sediments after gravitational deposition process. If <math display="inline"> <semantics> <mrow> <mi>T</mi> <mi>C</mi> </mrow> </semantics> </math> is larger than <span class="html-italic">G</span>, all the remaining sediments in the water (i.e., <span class="html-italic">G</span>) are washed away from an element. Otherwise, the amount of sediments equal to <math display="inline"> <semantics> <mrow> <mi>T</mi> <mi>C</mi> </mrow> </semantics> </math> is carried out by the surface runoff to downslope elements.</p>
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<p>Sobol’ total indices of model input parameters for a single element. The bars indicate the Sobol’ total indices and the error bars indicate the 95% confidence intervals of the indices from bootstrapping.</p>
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<p>Sobol’ total indices for runoff (<span class="html-italic">Q</span>) and sediment loss (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>L</mi> </mrow> </semantics> </math>) of the two field sites. Bars indicate the Sobol’ total indices and the error bars indicate the 95% confidence intervals of the indices from bootstrapping. We checked the sensitivity of the model to the parameters with high uncertainty due to absence of field data, such as parameters related to soil detachability (i.e., <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>K</mi> <mi>c</mi> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>K</mi> <mi>z</mi> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>K</mi> <mi>s</mi> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>R</mi> <mi>c</mi> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>R</mi> <mi>z</mi> </msub> </mrow> </semantics> </math>, and <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>R</mi> <mi>s</mi> </msub> </mrow> </semantics> </math>), soil hydraulic parameters (i.e., <span class="html-italic">K</span>, <math display="inline"> <semantics> <msub> <mi>θ</mi> <mrow> <mi>s</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics> </math>, and <math display="inline"> <semantics> <msub> <mi>θ</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> </semantics> </math>), vegetation structural parameters (i.e., <math display="inline"> <semantics> <mrow> <mi>G</mi> <mi>C</mi> </mrow> </semantics> </math>, <span class="html-italic">D</span>, <math display="inline"> <semantics> <mrow> <mi>N</mi> <mi>V</mi> </mrow> </semantics> </math>), the permanent interception (<math display="inline"> <semantics> <mrow> <mi>P</mi> <mi>I</mi> </mrow> </semantics> </math>), and the rill depth (<span class="html-italic">d</span>). <span class="html-italic">K</span>, <math display="inline"> <semantics> <msub> <mi>θ</mi> <mrow> <mi>s</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics> </math> and <math display="inline"> <semantics> <msub> <mi>θ</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> </semantics> </math> showed relatively high impacts on the runoff (<span class="html-italic">Q</span>) and the sediment loss (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>L</mi> </mrow> </semantics> </math>). The sediment loss (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>L</mi> </mrow> </semantics> </math>) also showed high sensitivity to <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>R</mi> <mi>c</mi> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>R</mi> <mi>z</mi> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>D</mi> <msub> <mi>R</mi> <mi>s</mi> </msub> </mrow> </semantics> </math> and <span class="html-italic">d</span>.</p>
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<p>Comparison between simulated and observed runoff (<span class="html-italic">Q</span>) and sediment loss (<math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>L</mi> </mrow> </semantics> </math>) for field 1 and field 2. We tested the model performance for both fields with optimized parameters (<a href="#water-09-00278-t003" class="html-table">Table 3</a>). Model performance was evaluated using the Nash-Sutcliffe efficiency coefficient (NSE), percent bias (PBIAS), and RMSE-observation standard deviation ratio (RSR) with the observed data from Arnhold et al. [<a href="#B37-water-09-00278" class="html-bibr">37</a>]. To make all overlapping points with values close to zero visible, we slightly jitterred the points.</p>
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2699 KiB  
Article
Characterization of Dissolved Organic Matter in Deep Geothermal Water from Different Burial Depths Based on Three-Dimensional Fluorescence Spectra
by Weifang Qiao, Xinyi Wang, Xiaoman Liu, Xiaoge Zhen, Jianwei Guo, Shidong Wang, Fang Yang, Guosheng Chen and Bo Zhang
Water 2017, 9(4), 266; https://doi.org/10.3390/w9040266 - 17 Apr 2017
Cited by 5 | Viewed by 5945
Abstract
Dissolved organic matter (DOM) plays an important role in the chemical evolution of groundwater. Thus, in order to understand the composition and characteristics of DOM in groundwater, analyzed 31geothermal water samples from five aquifers (i.e., between 600 m and 1600 m) in the [...] Read more.
Dissolved organic matter (DOM) plays an important role in the chemical evolution of groundwater. Thus, in order to understand the composition and characteristics of DOM in groundwater, analyzed 31geothermal water samples from five aquifers (i.e., between 600 m and 1600 m) in the city of Kaifeng were analyzed and the results were compared in order to clarify their spatial distribution, characteristics, sources, and environmental influences. Results show that as the depth of a thermal reservoir increases, the ultraviolet absorption (UV254) of geothermal water does not change significantly, the concentration of dissolved organic carbon (DOC) gradually increases with depth, and the fluorescence intensity of DOM remains weak. Some differences are also evident with regard to the location and intensity of geothermal water sample DOM fluorescence peaks depending on thermal reservoir. The results of this study show that the main source of DOM in geothermal water is endogenous, derived from high stability organic matter derived from sedimentary processes and associated microbial activity. Within the three geothermal reservoir depth ranges, 600 m to 800 m, 800 m to 1000 m, and 1000 m to 1200 m, DOM components were mainly protein-like as well as soluble microbial metabolites. However, at deeper depths, within the 1200 m to 1400 m and 1400 m to 1600 m thermal reservoirs, the proportion of protein-like components in DOM decreased, while the ratio fulvic-like and humic-like components increased, leading to changes in the positions of fluorescence peaks. Finally, our results demonstrate a close relationship between the intensity of fluorescence peaks, suggesting that a number of fluorescent components may share a common source. Full article
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Figure 1

Figure 1
<p>Location of geothermal well in study area.</p>
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<p>Changes of several parameters with well depth. (<b>a</b>) Changes of temperature with well depth; (<b>b</b>) Changes of pH value with well depth; (<b>c</b>) Changes of electrical conductivity (EC) with well depth; (<b>d</b>) Changes of total dissolved solids (TDS) with well depth; (<b>e</b>) Changes of specific UV absorbance (SUVA) with well depth; (<b>f</b>) Changes of dissolved organic carbon (DOC) with well depth.</p>
Full article ">Figure 3
<p>Three-dimensional excitation-emission matrix (EX, EM) fluorescence spectroscopy of dissolved organic matter (DOM) in typical water samples from each geothermal reservoir in Kaifeng. (<b>a</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 600 m and 800 m; (<b>b</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 800 m and 1000 m; (<b>c</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 1000 m and 1200 m; (<b>d</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 1200 m and 1400 m; (<b>e</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 1400 m and 1600 m.</p>
Full article ">Figure 3 Cont.
<p>Three-dimensional excitation-emission matrix (EX, EM) fluorescence spectroscopy of dissolved organic matter (DOM) in typical water samples from each geothermal reservoir in Kaifeng. (<b>a</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 600 m and 800 m; (<b>b</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 800 m and 1000 m; (<b>c</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 1000 m and 1200 m; (<b>d</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 1200 m and 1400 m; (<b>e</b>) Three-dimensional excitation-emission matrix fluorescence spectroscopy of DOM in water samples from depths between 1400 m and 1600 m.</p>
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<p>The distribution of fluorescence intensity in different thermal reservoirs.</p>
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2977 KiB  
Article
Effects of Local Weather Variation on Water-Column Stratification and Hypoxia in the Western, Sandusky, and Central Basins of Lake Erie
by Melanie M. Perello, Douglas D. Kane, Phoenix Golnick, Maya C. Hughes, Matt A. Thomas and Joseph D. Conroy
Water 2017, 9(4), 279; https://doi.org/10.3390/w9040279 - 16 Apr 2017
Cited by 14 | Viewed by 6279
Abstract
Hypoxia, low dissolved oxygen (DO) concentrations (<2 mg/L), has been a major issue in Lake Erie for decades. While much emphasis has been placed on biological factors, particularly algal blooms, contributing to hypolimnetic oxygen depletion, there has been little focus on the role [...] Read more.
Hypoxia, low dissolved oxygen (DO) concentrations (<2 mg/L), has been a major issue in Lake Erie for decades. While much emphasis has been placed on biological factors, particularly algal blooms, contributing to hypolimnetic oxygen depletion, there has been little focus on the role of weather. For this study, we monitored water temperature and DO concentrations at sites in the western, central, and Sandusky basins in Lake Erie during June and July 2010–2012. We then compared trends in stratification and DO concentrations to weather patterns during that period. We found that during those three years, there was significant variation in weather patterns, particularly decreased ice coverage and increased storm events in 2012. These weather patterns corresponded to 2012 having the warmest water temperatures, some of the lowest DO concentrations, and a deeper and thinner hypolimnion (especially in the central basin) than the previous years. We found a relationship between weather and hypoxia, providing further evidence for why these basins are susceptible to low DO conditions during summer months. The role of weather in hypoxia is another indication that the lake is vulnerable to effects of climate change and should be considered in management strategies. Full article
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<p>Location of the six monitoring stations in Lake Erie. Ballast Island Deep (BID) and Kelley’s Island Deep (KID) are both located in the western basin. Sandusky Subbasin Offshore (SOFF) and East Sandusky Subbasin (East) are in the Sandusky Subbasin. Lorain and Avon Point (AP) are both in the central basin. Bathymetric contours represent 1 m intervals. Basemap was provided by the Ohio Department of Natural Resources.</p>
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<p>Mean daily surface water temperature (°C) (+SD) for March through June of 2010 through 2012. Note that no data were available for March 2011 or for June 2012. Weather data is from the NOAA GLERL Real-Time Meteorological Network [<a href="#B18-water-09-00279" class="html-bibr">18</a>].</p>
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<p>Total accumulated ice coverage (Ice Cover/Total Area) for Lake Erie for 2010 through 2012 compared to thermocline depth (m) from the basins of our study. Weather data is from Environment Canada [<a href="#B20-water-09-00279" class="html-bibr">20</a>].</p>
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<p>Number of monthly storm events for the years 2010 through 2012. Data were not available for March 2011. A storm event is defined as having wind speeds greater than 7 m/s for three or more hours [<a href="#B22-water-09-00279" class="html-bibr">22</a>].</p>
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<p>Dissolved oxygen (mg/L) and temperature (°C) with depth for Ballast Island Deep (<b>A</b>), Kelley Island’s Deep (<b>B</b>), Sandusky Subbasin Offshore (<b>C</b>), East (<b>D</b>), Lorain (<b>E</b>), and Avon Point (<b>F</b>) sites from 2010 to 2012 during the first week (late June/early July) of the study each year.</p>
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<p>Dissolved oxygen (mg/L) and temperature (°C) with depth for Kelley’s Island Deep (<b>A</b>), Sandusky Subbasin Offshore (<b>B</b>), and East (<b>C</b>) from 2010 to 2012 during the second week (early-July) of the study each year. Note that only sites that were typically stratified are shown.</p>
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<p>Dissolved oxygen (mg/L) and temperature (°C) with depth for Ballast Island Deep (<b>A</b>), Kelley’s Island Deep (<b>B</b>), Sandusky Subbasin Offshore (<b>C</b>), East (<b>D</b>), Lorain (<b>E</b>), and Avon Point (<b>F</b>) sites in the western, central, and Sandusky basins of Lake Erie 2010–2012 during the third week (mid-July) of the study each year.</p>
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10786 KiB  
Article
Development of an Integrated Water Quality and Macroalgae Simulation Model for Tidal Marsh Eutrophication Control Decision Support
by Yan Chen, Rui Zou, Su Han, Sen Bai, Mustafa Faizullabhoy, Yueying Wu and Huaicheng Guo
Water 2017, 9(4), 277; https://doi.org/10.3390/w9040277 - 15 Apr 2017
Cited by 9 | Viewed by 4890
Abstract
Numerical modeling is an efficient and useful method for understanding the hydrodynamics and water quality responses to nutrient loading changes and other management in estuarine and coastal systems. In this study, the Environmental Fluid Dynamic Code (EFDC) was applied in the Famosa Slough, [...] Read more.
Numerical modeling is an efficient and useful method for understanding the hydrodynamics and water quality responses to nutrient loading changes and other management in estuarine and coastal systems. In this study, the Environmental Fluid Dynamic Code (EFDC) was applied in the Famosa Slough, a small tidal marsh system in urban San Diego County, California, to analyze multiple management scenarios focusing on different aspects of controlling processes: watershed load reduction, macroalgae harvesting, dredging, and the combination of different options. In order to evaluate these management scenarios, a previous EFDC model was enhanced through modifying the model code to allow simulations of both benthic and floating macroalgae as separate state variables, and configuring a sediment diagenesis model to predictively represent the dynamic interactions between the watershed load and benthic nutrient flux. The model was calibrated and verified by comparing model predictions with the observed data of hydrodynamic and water quality parameters throughout 2008. The calibrated model was then applied to simulate the water quality response to various management scenarios. The simulated results showed that combining watershed nutrient load reductions and harvesting floating macroalgae can produce significant water quality benefits. The results provide useful information for hydrological ecosystem protection and can be used for determining cost-effective implementation actions in the future. Full article
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<p>Environmental Fluid Dynamic Code (EFDC) Grid, sampling point, and watershed outline for the Famosa Slough, Famosa Channel, and the San Diego River.</p>
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<p>The following subset of the state variables available within the EFDC Comparison of observed and simulated water level variations for water surface elevations (<b>a</b>), salinity (<b>b</b>), and water temperature (<b>c</b>) at the Famosa Channel outlet.</p>
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<p>The following subset of the state variables available within the EFDC Comparison of observed and simulated water level variations for water surface elevations (<b>a</b>), salinity (<b>b</b>), and water temperature (<b>c</b>) at the Famosa Channel outlet.</p>
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<p>Comparison of observed vs. simulated Chlorophyll-a variations at the outlet of the Famosa Channel.</p>
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<p>Simulated macroalgae at the monitored transect.</p>
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<p>Comparison of observed vs. simulated DO (Dissolved Oxygen) variations at the outlet of the Famosa Channel.</p>
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<p>Comparison of Observed vs. Simulated Variations for PO<sub>4</sub><sup>3−</sup>-P (<b>a</b>), TP (<b>b</b>), NH<sub>4</sub><sup>+</sup>-N (<b>c</b>), NO<sub>3</sub><sup>−</sup>-N (<b>d</b>), and TN (<b>e</b>) at the Famosa Channel outlet.</p>
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<p>Comparison of Observed vs. Simulated Variations for PO<sub>4</sub><sup>3−</sup>-P (<b>a</b>), TP (<b>b</b>), NH<sub>4</sub><sup>+</sup>-N (<b>c</b>), NO<sub>3</sub><sup>−</sup>-N (<b>d</b>), and TN (<b>e</b>) at the Famosa Channel outlet.</p>
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<p>Spatially and temporal average water quality in the Famosa Slough for all Scenarios.</p>
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<p>Average water quality in the Famosa Slough under Scenario 7.</p>
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2972 KiB  
Article
Dynamic Assessment of Comprehensive Water Quality Considering the Release of Sediment Pollution
by Tianxiang Wang, Shiguo Xu and Jianwei Liu
Water 2017, 9(4), 275; https://doi.org/10.3390/w9040275 - 15 Apr 2017
Cited by 15 | Viewed by 5255
Abstract
Comprehensive assessment of water quality is an important technological measure for water environmental management and protection. Previous assessment methods tend to ignore the influences of sediment pollutant release and dynamic change of the water boundary. In view of this, this paper explores a [...] Read more.
Comprehensive assessment of water quality is an important technological measure for water environmental management and protection. Previous assessment methods tend to ignore the influences of sediment pollutant release and dynamic change of the water boundary. In view of this, this paper explores a new method for comprehensive water quality assessment. Laboratory simulation experiments are conducted to analyze the influences of sediment pollutant release on water quality, and the results are taken as increments, coupled with original samples, to constitute a new set of evaluation samples. Dynamic and comprehensive water quality assessment methods are created based on a principal component analysis (PCA)/analytic hierarchy process (AHP)–variable fuzzy pattern recognition (VFPR) model and adopted to evaluate water quality. A geographic information system (GIS) is applied to visually display the results of water quality assessment and the change of the water boundary. This study takes Biliuhe Reservoir as an engineering example. The results show the change process of the water boundary, during which the water level is reduced from 63.10 m to 54.15 m. The reservoir water quality is fine, of which the water quality level (GB3838-2002) is between level 2 and level 3, and closer to level 2 taking no account of sediment pollutant release. The water quality of Biliuhe Reservoir, overall, is worse in summer and better in winter during the monitoring period. Meanwhile, the water quality shows the tendency of being better from upstream to downstream, and the water quality in the surface layer is better than that in the bottom layer. However, water quality is much closer, or even inferior, to level 3 when considering the release of nitrogen and phosphorus in sediments, and up to 42.7% of the original assessment results of the samples undergo changes. It is concluded that the proposed method is comparatively reasonable as it avoids neglecting sediment pollutant release in the water quality assessment, and the presentation of the evaluation results and change of the water boundary is intuitive with the application of GIS. Full article
(This article belongs to the Special Issue Water Quality and Health)
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<p>The horizontal sampling point map of Biliuhe Reservoir.</p>
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<p>The vertical sampling points map in Biliuhe reservoir.</p>
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<p>The vertical change of water quality of Biliuhe Reservoir.</p>
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<p>The vertical change of comprehensive water quality considering sediment release of Biliuhe Reservoir.</p>
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3539 KiB  
Article
Experimental Investigation on Air-Water Interaction in a Hydropower Station Combining a Diversion Tunnel with a Tailrace Tunnel
by Wen Zhang, Fulin Cai, Jianxu Zhou and Yulong Hua
Water 2017, 9(4), 274; https://doi.org/10.3390/w9040274 - 13 Apr 2017
Cited by 12 | Viewed by 4606
Abstract
Diversion tunnels are often used as tailrace tunnels in underground hydropower stations. The special layout results in complex flow regimes, including air-water two-phase flow. A set of experiments is conducted based on the model of a hydropower station which combines partial diversion tunnels [...] Read more.
Diversion tunnels are often used as tailrace tunnels in underground hydropower stations. The special layout results in complex flow regimes, including air-water two-phase flow. A set of experiments is conducted based on the model of a hydropower station which combines partial diversion tunnels with tailrace tunnels to investigate the interactions between the air and water phases in the combined diversion tunnels. Interactions between the air and water phases observed in the combined diversion tunnel significantly alter flow dynamics, and are classified into four types according to the initial tail water level. There is a range of initial tail water levels in which the interaction between the air and water phases cannot be neglected, and the range becomes greater when the change in flow rate increases. Such interactions may cause a pressure surge and the pressure surge reaches the maximum when the initial tail water level is approximately equal to the crown of the tunnel. The surge pressures do harm to the safety and stability of hydropower stations, so the condition should be considered and controlled. Full article
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<p>Arrangement of the experimental model: (<b>a</b>) plan view and (<b>b</b>) longitudinal section along the center line of the second hydraulic unit.</p>
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<p>The critical relative tail water depth: (<b>a</b>) the intake critical relative tail water depth <span class="html-italic">y</span><sub>1</sub>*; (<b>b</b>) the single air pocket critical relative tail water depth <span class="html-italic">y</span><sub>2</sub>*; and (<b>c</b>) the interface instability critical relative tail water depth <span class="html-italic">y</span><sub>3</sub>*.</p>
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<p>Pressure oscillation over time at P3 and P6: (<b>a</b>) when <span class="html-italic">y</span>* = 1.086, for group 2; (<b>b</b>) when <span class="html-italic">y</span>* = 1.073, for group 2; and (<b>c</b>) when <span class="html-italic">y</span>* = 1.073, for group 4.</p>
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<p>Pressure oscillation over time for group 2, when <span class="html-italic">y</span>* = 1.047: (<b>a</b>) at P3 and P4, near the ventilation shaft, and (<b>b</b>) at P10 and P11, near the third gate shaft.</p>
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<p>Pressure oscillation over time for group 2, when <span class="html-italic">y</span>* = 0.963: (<b>a</b>) at P3 and P4, near the ventilation shaft; and (<b>b</b>) at P10 and P11, near the third gate shaft.</p>
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<p>Pressure oscillation over time for group 2, when <span class="html-italic">y</span>*=0.868: (<b>a</b>) at P3 and P4, near the ventilation shaft; and (<b>b</b>) at P10 and P11, near the third gate shaft.</p>
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<p>The relative maximum pressures of measuring points located on the crown for group 2: (<b>a</b>) at P3; (<b>b</b>) at P5; (<b>c</b>) at P6; (<b>d</b>) at P8; (<b>e</b>) at P9; and (<b>f</b>) at P10.</p>
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13921 KiB  
Article
The Impact of Integrated Aquifer Storage and Recovery and Brackish Water Reverse Osmosis (ASRRO) on a Coastal Groundwater System
by Steven Eugenius Marijnus Ros and Koen Gerardus Zuurbier
Water 2017, 9(4), 273; https://doi.org/10.3390/w9040273 - 12 Apr 2017
Cited by 9 | Viewed by 9663
Abstract
Aquifer storage and recovery (ASR) of local, freshwater surpluses is a potential solution for freshwater supply in coastal areas, as is brackish water reverse osmosis (BWRO) of relatively shallow groundwater in combination with deeper membrane concentrate disposal. A more sustainable and reliable freshwater [...] Read more.
Aquifer storage and recovery (ASR) of local, freshwater surpluses is a potential solution for freshwater supply in coastal areas, as is brackish water reverse osmosis (BWRO) of relatively shallow groundwater in combination with deeper membrane concentrate disposal. A more sustainable and reliable freshwater supply may be achieved by combining both techniques in one ASRRO system using multiple partially penetrating wells (MPPW). The impact of widespread use of ASRRO on a coastal groundwater system was limited based on regional groundwater modelling but it was shown that ASRRO decreased the average chloride concentration with respect to the autonomous scenario and the use of BWRO. ASRRO was successful in mitigating the local negative impact (saltwater plume formation) caused by the deep disposal of membrane concentrate during BWRO. The positive impacts of ASRRO with respect to BWRO were observed in the aquifer targeted for ASR and brackish water abstraction (Aquifer 1), but foremost in the deeper aquifer targeted for membrane concentrate disposal (Aquifer 2). The formation of a horizontal freshwater barrier was found at the top of both aquifers, reducing saline seepage. The disposal of relatively fresh concentrate in Aquifer 2 led to brackish water outflow towards the sea. The net abstraction in Aquifer 1 enforced saltwater intrusion, especially when BWRO was applied. The conclusion of this study is that ASRRO can provide a sustainable alternative for BWRO. Full article
(This article belongs to the Special Issue Water Quality Considerations for Managed Aquifer Recharge Systems)
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<p>The principle of aquifer storage and recovery and reverse osmosis (ASRRO) for storage and recovery of freshwater in brackish-saline aquifers.</p>
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<p>Location of the Westland study area and the regional hydraulic heads, groundwater salinity, location of greenhouse horticulture, and boundaries of the groundwater models.</p>
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<p>Top: Top view of the Local Model grid. Bottom: Cross-sectional view (West-East) showing the hydraulic heads (h) and the expected flow pattern through the various geological layers for the autonomous situation. The 27-ha subsection (area of the greenhouses connected to the ASRRO system) of the model is located within the marked box. The vertical exaggeration is 10:1.</p>
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<p>Average chloride concentration (g/L) throughout the 27-ha model subsection for: the total groundwater system (<b>a</b>), the Clay cap (<b>b</b>), Aquifer 1 (<b>c</b>), Aquitard 1 (<b>d</b>), and Aquifer 2 (<b>e</b>).</p>
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<p>Chloride concentrations along the mirror plane (W- &gt; E) of Local Model where the MC disposal wells are situated (scenario ASRRO; <span class="html-italic">t</span> = 30 year, end of summer). The 27-ha model subsection includes the part shown between the vertical dotted lines (<span class="html-italic">x</span> = 70; <span class="html-italic">x</span> = 160).</p>
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<p>Chloride concentrations along the mirror plane (W- &gt; E) of the Local Model where the MC disposal wells are situated (scenario BWRO; <span class="html-italic">t</span> = 30 year, end of summer). The 27-ha model subsection includes the part shown between the vertical dotted lines (<span class="html-italic">x</span> = 70; <span class="html-italic">x</span> = 160).</p>
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<p>Range of MC concentrations with time of water injected by MC disposal well 1 and MC disposal well 2, for ASRRO and BWRO; and the yearly averaged MC concentration of each MC disposal well for both scenarios.</p>
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<p>Distribution of local chloride concentrations in the 50 m × 50 m model cells of the MPPWs (Aquifer 1) of each individual BWRO and ASRRO system (average during the final year (year 30)).</p>
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<p>Distribution of local chloride concentrations in the 50 m × 50 m model cells of the MC disposal wells (Aquifer 2) of each individual BWRO and ASRRO system (average during the final year (year 30)).</p>
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<p>Relative chloride concentration changes (g/L) between ASRRO and Autonomous and between BWRO and Autonomous after 30 years in Aquifer 1 (<b>a</b>,<b>b</b>) and Aquifer 2 (<b>c</b>,<b>d</b>).</p>
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<p>Distribution of the 30-year averaged MC chloride concentration by the 616 MC disposal wells.</p>
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<p>Overview of the integral impacts of ASRRO (and BWRO) on the regional salinity distribution in the Westland study area in a west-east cross-section. Local impact include salinization (BWRO) and stratification (ASRRO), while regionally saltwater intrusion (Aquifer 1) and brackish water outflow are the main phenomena, having the most negative impact in the BWRO scenario.</p>
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<p>Maximum depth of occurrence (m below surface level) and total thickness (m) of Aquifer 2 (<b>top</b>), Aquitard 2 (<b>middle</b>), and Aquifer 3 (<b>bottom</b>).</p>
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<p>Topographic map (top) showing the outline of the regions wherein the Holocene clay cap is either 1, 2 or 3 model layers thick. The latter is presented in the bottom figure. The clay cap occurs in L2, (L3, L4), and is at most 15 m thick. The clay layer occurrence has been obtained from the PZH-Westland data [<a href="#B18-water-09-00273" class="html-bibr">18</a>].</p>
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<p>Horizontal conductivities (m/day) in the Regional Model for the Phreatic layer, and Aquifers 1 and 2. The North Sea is located northwest of the model domain.</p>
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<p>Vertical conductivities (m/day) in the Regional Model for the Phreatic layer, and Aquifers 1 and 2. The North Sea is located northwest of the model domain.</p>
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<p>Horizontal conductivities (m/day) in the Regional Model for the Clay cap and Aquitard 1. The North Sea is located northwest of the model domain.</p>
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<p>iBounds (−1, 0, 1) used in the Regional Model. The values are set to “−1” along the vertical boundary planes surrounding the active grid cells and in the top layer.</p>
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<p>Starting concentrations (g/L) in the Regional Model for the Phreatic layer, and Aquifers 1 and 2. The North Sea is located northwest of the model domain.</p>
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<p>Point water heads (m) in the Regional Model for the Phreatic layer, and Aquifers 1 and 2. The North Sea is located northwest of the model domain.</p>
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<p>Chloride concentration (g/L) after 30 years of practice of ASRRO and BWRO in Aquifer 1 (<b>a</b>,<b>b</b>) and Aquifer 2 (<b>c</b>,<b>d</b>).</p>
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4260 KiB  
Article
Comparative Analysis of HRU and Grid-Based SWAT Models
by Garett Pignotti, Hendrik Rathjens, Raj Cibin, Indrajeet Chaubey and Melba Crawford
Water 2017, 9(4), 272; https://doi.org/10.3390/w9040272 - 12 Apr 2017
Cited by 46 | Viewed by 13640
Abstract
A grid-based version of the Soil and Water Assessment Tool (SWAT) model, SWATgrid, was developed to perform simulations on a regularized grid with a modified routing algorithm to allow interaction between grid cells. However, SWATgrid remains largely untested with little understanding of the [...] Read more.
A grid-based version of the Soil and Water Assessment Tool (SWAT) model, SWATgrid, was developed to perform simulations on a regularized grid with a modified routing algorithm to allow interaction between grid cells. However, SWATgrid remains largely untested with little understanding of the impact of user-defined grid cell size. Moreover, increases in computation time effectively preclude direct calibration of SWATgrid. To gain insight into defining appropriate strategies for future development and application of SWATgrid, this research considers the simulated differences between commonly-employed hydrologic response unit (HRU)-based and grid-based SWAT models and the implications of resolution on their simulation and calibrated parameter values for a Midwestern, agricultural watershed. Results indicate that: (1) the gridded approach underpredicted simulated streamflow between 5% and 50% relative to the baseline model, depending upon the input spatial resolution and routing algorithm implemented; (2) gridded models generally underpredicted total phosphorous and sediment loads while overpredicting nitrate load; and (3) ranges of values of optimized model parameters remained similar up to 90 m. Results from this analysis should help in defining future applications of the SWATgrid model and the effects of differing spatial resolution of the model input data. Full article
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<p>Cedar Creek Watershed characteristics: (<b>a</b>) elevation (National Elevation Data (NED) 30 m) with the stream and precipitation gauging stations shown; (<b>b</b>) soil hydrologic group (State Soil Geographic (STATSGO) 250 m); and (<b>c</b>) land use (reclassified from NASS 2010 Crop Data Layer (CDL) 30 m).</p>
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<p>Comparison of observed and simulated monthly flow at the watershed outlet for the baseline 30-m Cedar Creek HRU model. Calibration period is 1994 to 2003, and the validation is 2004 to 2010.</p>
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<p>Hydrologic simulations for 90-m resolution models’ (<b>a</b>) monthly hydrographs and (<b>b</b>) average monthly absolute flow difference relative to the HRU model.</p>
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<p>Average relative model error as compared to the 30-m Cedar Creek HRU model.</p>
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<p>Effect of area on average annual total stream flow for each model approach.</p>
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<p>Frequency plots of normalized flow separation indices by resolution.</p>
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<p>Spatial output for selected annual average surface runoff (SURQ), lateral flow (LATQ) and groundwater flow (GWQ) for all model types at 90-m resolution. Values plotted at the unit of transport (i.e., subbasins and grid cells) at the scale maximize visual contrast. STD, standard.</p>
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<p>Calibrated parameter ranges by resolution for: (<b>a</b>) snowfall temperature (SFTMP); (<b>b</b>) snow melt temperature (SMTMP); (<b>c</b>) snow minimum melt factor (SMFMN); (<b>d</b>) snow maximum melt factor (SMFMX); (<b>e</b>) snow pack temperature lag factor (TIMP); and (<b>f</b>) surface runoff lag coefficient (SURLAG).</p>
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2420 KiB  
Article
Full Spectrum Analytical Channel Design with the Capacity/Supply Ratio (CSR)
by Travis R. Stroth, Brian P. Bledsoe and Peter A. Nelson
Water 2017, 9(4), 271; https://doi.org/10.3390/w9040271 - 12 Apr 2017
Cited by 6 | Viewed by 5701
Abstract
Analytical channel design tools have not advanced appreciably in the last decades, and continue to produce designs based upon a single representative discharge that may not lead to overall sediment continuity. It is beneficial for designers to know when a simplified design may [...] Read more.
Analytical channel design tools have not advanced appreciably in the last decades, and continue to produce designs based upon a single representative discharge that may not lead to overall sediment continuity. It is beneficial for designers to know when a simplified design may be problematic and to efficiently produce alternative designs that approximate sediment balance over the entire flow regime. The Capacity/Supply Ratio (CSR) approach—an extension of the Copeland method of analytical channel design for sand channels—balances the sediment transport capacity of a design reach with the sediment supply of a stable upstream reach over the entire flow duration curve (FDC) rather than just a single discharge. Although CSR has a stronger physical basis than previous analytical channel design approaches, it has not been adopted in practice because it can be a cumbersome and time-consuming iterative analysis without the use of software. We investigate eighteen sand-bed rivers in a comparison of designs based on the CSR approach and five single-discharge metrics: the effective discharge (Qeff) or discharge that transports the most sediment over time; the 1.5-year recurrence interval discharge (Q1.5); the bankfull discharge (Qbf); and the discharges associated with 50th (Qs50) and 75th (Qs75) percentiles of the cumulative sediment yield curve. To facilitate this analysis, we developed a novel design tool using the Visual Basic for Applications (VBA) programming language in Excel® to produce stable channel slope/width combinations based on the CSR methodology for both sand- and gravel-bed streams. The CSR Stable Channel Design Tool’s (CSR Tool) code structure was based on Copeland’s method in SAM and HEC-RAS (Hydrologic Engineering Center’s River Analysis System) and was tested with a single discharge to verify outputs. The Qs50 and Qs75 single-discharge designs match the CSR output most closely, followed by the Qbf, Qeff, and Q1.5. The Qeff proved to be the most inconsistent design metric because it can be highly dependent on the binning procedure used in the effectiveness analysis. Furthermore, we found that the more rigorous physical basis of the CSR analysis is potentially most important in designing “labile” channels with highly erodible substrate, high perennial flow “flashiness”, low width-to-depth ratio, and high incoming sediment load. The CSR Tool provides a resource for river restoration practitioners to efficiently utilize design techniques that can promote sediment balance in dynamic fluvial systems. Full article
(This article belongs to the Special Issue Stream Channel Stability, Assessment, Modeling, and Mitigation)
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<p>Visual representation of CSR analysis for simplified trapezoidal channel geometry.</p>
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<p>Family of width and slope combinations which provide continuity of water and sediment with solutions in section A: low width, high slope (generally too high velocity and stream power); section B: realistic range for single thread; and section C: high width (tendency toward braiding/habitat considerations).</p>
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<p>Sensitivity of departures between field-identified bankfull discharge versus <span class="html-italic">Q<sub>eff</sub></span>, <span class="html-italic">Q</span><sub>1.5</sub>, <span class="html-italic">Q<sub>s</sub></span><sub>50</sub>, and <span class="html-italic">Q<sub>s</sub></span><sub>75</sub> with changes in the R-B Index.</p>
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<p>Total average percent difference in sediment yield computed from single-discharge designs to those computed with CSR designs for all eighteen sites with changes in (<b>a</b>) the R-B Index and (<b>b</b>) the width-to-depth ratio. R-B Index relationship with <span class="html-italic">Q</span><sub>1.5</sub> is significant at <span class="html-italic">p</span> &lt; 0.05, all others have <span class="html-italic">p</span> &gt; 0.10. Width–depth ratio relationship with <span class="html-italic">Q</span><sub>1.5</sub> and <span class="html-italic">Q<sub>bf</sub></span> is significant at <span class="html-italic">p</span> &lt; 0.10, all others have <span class="html-italic">p</span> &gt; 0.10.</p>
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<p>Total average percent difference in sediment yield computed from single-discharge designs to those computed with CSR designs for all eighteen sites with changes in (<b>a</b>) the R-B Index and (<b>b</b>) the width-to-depth ratio. R-B Index relationship with <span class="html-italic">Q</span><sub>1.5</sub> is significant at <span class="html-italic">p</span> &lt; 0.05, all others have <span class="html-italic">p</span> &gt; 0.10. Width–depth ratio relationship with <span class="html-italic">Q</span><sub>1.5</sub> and <span class="html-italic">Q<sub>bf</sub></span> is significant at <span class="html-italic">p</span> &lt; 0.10, all others have <span class="html-italic">p</span> &gt; 0.10.</p>
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