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Water, Volume 7, Issue 6 (June 2015) – 34 articles , Pages 2542-3165

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2941 KiB  
Article
Flow Regime Classification and Hydrological Characterization: A Case Study of Ethiopian Rivers
by Belete Berhanu, Yilma Seleshi, Solomon S. Demisse and Assefa M. Melesse
Water 2015, 7(6), 3149-3165; https://doi.org/10.3390/w7063149 - 22 Jun 2015
Cited by 46 | Viewed by 11900
Abstract
The spatiotemporal variability of a stream flow due to the complex interaction of catchment attributes and rainfall induce complexity in hydrology. Researchers have been trying to address this complexity with a number of approaches; river flow regime is one of them. The flow [...] Read more.
The spatiotemporal variability of a stream flow due to the complex interaction of catchment attributes and rainfall induce complexity in hydrology. Researchers have been trying to address this complexity with a number of approaches; river flow regime is one of them. The flow regime can be quantified by means of hydrological indices characterizing five components: magnitude, frequency, duration, timing, and rate of change of flow. Similarly, this study aimed to understand the flow variability of Ethiopian Rivers using the observed daily flow data from 208 gauging stations in the country. With this process, the Hierarchical Ward Clustering method was implemented to group the streams into three flow regimes (1) ephemeral, (2) intermittent, and (3) perennial. Principal component analysis (PCA) is also applied as the second multivariate analysis tool to identify dominant hydrological indices that cause the variability in the streams. The mean flow per unit catchment area (QmAR) and Base flow index (BFI) show an incremental trend with ephemeral, intermittent and perennial streams. Whereas the number of mean zero flow days ratio (ZFI) and coefficient of variation (CV) show a decreasing trend with ephemeral to perennial flow regimes. Finally, the streams in the three flow regimes were characterized with the mean and standard deviation of the hydrological variables and the shape, slope, and scale of the flow duration curve. Results of this study are the basis for further understanding of the ecohydrological processes of the river basins in Ethiopia. Full article
(This article belongs to the Special Issue Hydrologic System Analysis, Patterns, and Predictions for Arid and Semi-arid Environment)
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Figure 1

Figure 1
<p>Summary statistics of catchment area, river length, and gauging stations used in this study.</p> Full article ">Figure 2
<p>Cluster dendrogram of flow regime classification.</p> Full article ">Figure 3
<p>Variable factor and individual factor map of Principal Component Analysis (PCA).</p> Full article ">Figure 4
<p>Flow duration curve (FDC) of streams for different flow regimes in Ethiopia. (<b>A</b>) Ephemeral streams; (B) Intermittent streams; (<b>C</b>) Perennial stream; (<b>D</b>) All in one view.</p> Full article ">Figure 4 Cont.
<p>Flow duration curve (FDC) of streams for different flow regimes in Ethiopia. (<b>A</b>) Ephemeral streams; (B) Intermittent streams; (<b>C</b>) Perennial stream; (<b>D</b>) All in one view.</p> Full article ">Figure 5
<p>Flow regimes of Ethiopian streams along with elevation variability.</p> Full article ">
3244 KiB  
Article
Controls on Suspended Sediment Concentrations and Turbidity within a Reforested, Southern Appalachian Headwater Basin
by Jerry R. Miller, Jacob T. Sinclair and Danvey Walsh
Water 2015, 7(6), 3123-3148; https://doi.org/10.3390/w7063123 - 19 Jun 2015
Cited by 11 | Viewed by 6854
Abstract
Water quality data collected between 2007 and 2014 within the Allen Creek Watershed were used to: (1) determine the factors controlling the temporal variations in turbidity and suspended sediment concentration (SSC) within a representative, high-gradient headwater basin in the Southern Appalachians; and (2) [...] Read more.
Water quality data collected between 2007 and 2014 within the Allen Creek Watershed were used to: (1) determine the factors controlling the temporal variations in turbidity and suspended sediment concentration (SSC) within a representative, high-gradient headwater basin in the Southern Appalachians; and (2) assess the recovery of water quality following extensive logging operations during the early to mid-1900s. Regression analysis suggests that suspended sediment is primarily derived from upland areas and variations in concentration reflect rainfall intensity and total event precipitation. Overall, SSC and turbidity were low in stream waters in comparison to both reference values for stable streams and more developed basins in the region. Some floods were characterized by high SSC values, but limited turbidity and vice versa. Differences in measured SSC and turbidity between storms reflect different controls on the two parameters, and the apparent influence of natural organic matter on turbidity during rainfall events that are incapable of transporting sediment to the channel via overland flow. Low SSC and turbidity values are presumably related to the reforestation of hillslopes and riparian buffers following the cessation of logging operations. They also are due to a historical reduction in the sedimentological connectivity of hillslopes and tributaries with the axial channel that occurred during logging operations. Full article
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<p>Map showing location of the upper Allen Creek basin (Waynesville Municipal Watershed) in North Carolina, and the location of the monitoring sites within the watershed: (1) Allen Creek #1; (2) Cherry Cove; (3) Old Bald Creek #1; (4) Old Bald Creek #2; (5) Old Bald Creek #3; (6) Lower Allen Creek #2.</p> Full article ">Figure 2
<p>Between site comparison of measured flow (discharge) (<b>a</b>); suspended sediment concentration (<b>b</b>); and turbidity (<b>c</b>, <b>d</b>). Box represents 25%–75% frequency interval, whereas whiskers repent maximum and minimum values for a, b, c. The 1%–99% range is shown by the whiskers in plot c. Discharge values for lower Allen Creek #2 site are currently unavailable.</p> Full article ">Figure 3
<p>(<b>a</b>) Number of rainfall events between March 2007 and July 2010 within the Allen Creek Watershed categorized by meteorological season. Includes a total of 69 events; (<b>b</b>) Average rainfall duration and the generated peak discharge associated with each precipitation event.</p> Full article ">Figure 4
<p>Suspended sediment concentrations measured during base flow conditions at the Allen Creek #1 monitoring station between March 2007 and September 2011. Nearly 85% of the samples exhibited concentrations &lt;5 mg/L; more than 99% exhibited concentration &lt;10 mg/L.</p> Full article ">Figure 5
<p>SSC plotted as a function of time following precipitation for the Allen Creek #1 monitoring site. Based on 69 events analyzed between March 2007 and July 2010.</p> Full article ">Figure 6
<p>Statistically significant relationships were identified between SSC and discharge during individual events at the monitoring sites, such as shown for the Allen Creek #1 during an event in March 2007 (<b>a</b>); and at the Cherry Cove site during an 3–13 April 2010 event (<b>b</b>); Similar relationships do not exist when data are combined for multiple events at a site as shown for Allen Creek #2 (<b>c</b>).</p> Full article ">Figure 7
<p>Examples of hysteresis loops observed for Allen Creek #1 (<b>a</b>,<b>b</b>) during the 4–5 March 2008 flood and Old Bald Creek #3 during the 28 April 2014 flood (<b>c</b>,<b>d</b>). Turbidity often exhibits a hysteretic loop that differs from that observed for SSC.</p> Full article ">Figure 8
<p>Photographs showing differences in channel stability between the Allen Creek #1 (<b>a</b>); Cherry Cove (<b>b</b>) and Old Bald Creek #1 (<b>c</b>) monitoring sites. Notice moss covered boulders at Cherry Cove and Old Bald Creek, indicating their recent lack of movement, and the eroding banks and bedrock knickpoint in Allen Creek photograph.</p> Full article ">Figure 9
<p>Average time turbidity was above a specified turbidity value at the Allen Creek #1 site between March 2007 and July 2010.</p> Full article ">Figure 10
<p>Variations in turbidity as a function of stream flow at the Allen Creek #1 (<b>a</b>); Cherry Cove (<b>c</b>); and Old Bald Creek #1 (<b>d</b>) monitoring stations; (<b>b</b>) variations in turbidity at the Allen Creek #1 site during the 15–16 March 2007 event only.</p> Full article ">Figure 11
<p>(<b>a</b>) Relationships between SSC and turbidity at the Old Bald #1 site (<span class="html-italic">n</span> = 511). Values are plotted in arithmetic scale to more effectively show that different relationships occur between events; (<b>b</b>) Peak SSC and turbidity values measured during 15 separate floods at the Allen Creek site between March 2008 and July 2010. Note that some precipitation events initiate a response in SSC, some a response in turbidity, and others a response in both.</p> Full article ">Figure 12
<p>(<b>a</b>) Time series showing the differences in the timing of peak SSC and turbidity values measured for a flood at the Old Bald Creek #3 site, 27–28 April 2014; Semi-systematic variations in SSC (<b>b</b>) and turbidity (<b>c</b>) occurred during the event. Differences in the timing of peak SSC and turbidity suggests changes in water clarity results from a factor(s) other than suspended sediment.</p> Full article ">
1013 KiB  
Article
Water Use Efficiency in Saline Soils under Cotton Cultivation in the Tarim River Basin
by Xiaoning Zhao, Hussein Othmanli, Theresa Schiller, Chengyi Zhao, Yu Sheng, Shamaila Zia, Joachim Müller and Karl Stahr
Water 2015, 7(6), 3103-3122; https://doi.org/10.3390/w7063103 - 19 Jun 2015
Cited by 37 | Viewed by 10206
Abstract
The Tarim River Basin, the largest area of Chinese cotton production, is receiving increased attention because of serious environmental problems. At two experimental stations (Korla and Aksu), we studied the influence of salinity on cotton yield. Soil chemical and physical properties, soil water [...] Read more.
The Tarim River Basin, the largest area of Chinese cotton production, is receiving increased attention because of serious environmental problems. At two experimental stations (Korla and Aksu), we studied the influence of salinity on cotton yield. Soil chemical and physical properties, soil water content, soil total suction and matric suction, cotton yield and water use efficiency under plastic mulched drip irrigation in different saline soils was measured during cotton growth season. The salinity (mS·cm−1) were 17–25 (low) at Aksu and Korla, 29–50 (middle) at Aksu and 52–62 (high) at Aksu for ECe (Electrical conductivity measured in saturation-paste extract of soil) over the 100 cm soil profile. The soil water characteristic curves in different saline soils showed that the soil water content (15%–23%) at top 40 cm soil, lower total suction power (below 3500 kPa) and lower matric suction (below 30 kPa) in low saline soil at Korla had the highest water use efficiency (10 kg·ha−1·mm−1) and highest irrigation water use efficiency (12 kg·ha−1·mm−1) and highest yield (6.64 t·ha−1). Higher water content below 30 cm in high saline soil increased the salinity risk and led to lower yield (2.39 t·ha−1). Compared to low saline soils at Aksu, the low saline soil at Korla saved 110 mm irrigation and 103 mm total water to reach 1 t·ha−1 yield and increased water use efficiency by 5 kg·ha−1·mm−1 and 7 kg·ha−1·mm−1 for water use efficiency (WUE) and irrigation water use efficiency (IWUE) respectively. Full article
(This article belongs to the Special Issue Sustainable Water Management and Decision Making under limited Data Availability)
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<p>The location of the Aksu (left arrow) and Korla (right arrow) experimental stations in Tarim River Basin.</p> Full article ">Figure 2
<p>Field experimental design in different saline soils during cotton season from May to September 2012 in Tarim River Basin (<b>a</b>) at Aksu station and (<b>b</b>) at Korla station.</p> Full article ">Figure 3
<p>The soil water content in different soil depths (0–80 cm) during cotton season from May to September 2012 in Tarim River Basin (<b>a</b>) in low saline soil at Korla; (<b>b</b>) in low saline soil at Aksu; (<b>c</b>) in middle saline soil at Aksu; and (<b>d</b>) in high saline soil at Aksu.</p> Full article ">Figure 4
<p>The soil matric suction in different soil depths (25 cm, 45, 65 cm) during cotton season from May to October 2012 in Tarim River Basin (<b>a</b>) in low saline soil at Korla; (<b>b</b>) in low saline soil at Aksu; (<b>c</b>) in middle saline soil at Aksu; and (<b>d</b>) in high saline soil at Aksu.</p> Full article ">Figure 5
<p>The soil water characteristic curves (matric and osmotic suction) in different saline (low at Korla, low, middle and high at Aksu) soils during cotton season from May to September 2012 in Tarim Basin (<b>a</b>) in 25 cm soil depth; (<b>b</b>) in 45 cm soil depth; and (<b>c</b>) in 65 cm soil depth.</p> Full article ">Figure 6
<p>The relationship between the simulated and the measured soil water content with modelling (Vol% = a0 + a1 × pF<sub>1</sub> + a2 × clay% + a3 × silt% + a4 × C<sub>org</sub> + a5 × N<sub>tot</sub> + a6 × pF<sub>2</sub>) (pF1: pF matric, pF2: pF osmetic, C<sub>org</sub>: (g/kg), N<sub>tot</sub>: (g/kg)) (<b>a</b>) in low saline soil; (<b>b</b>) in middle saline soil; and (<b>c</b>) in high saline soil.</p> Full article ">
2968 KiB  
Article
Spatial Downscaling of TRMM Precipitation Product Using a Combined Multifractal and Regression Approach: Demonstration for South China
by Guanghua Xu, Xianli Xu, Meixian Liu, Alexander Y. Sun and Kelin Wang
Water 2015, 7(6), 3083-3102; https://doi.org/10.3390/w7063083 - 19 Jun 2015
Cited by 29 | Viewed by 8253
Abstract
The lack of high spatial resolution precipitation data, which are crucial for the modeling and managing of hydrological systems, has triggered many attempts at spatial downscaling. The essence of downscaling lies in extracting extra information from a dataset through some scale-invariant characteristics related [...] Read more.
The lack of high spatial resolution precipitation data, which are crucial for the modeling and managing of hydrological systems, has triggered many attempts at spatial downscaling. The essence of downscaling lies in extracting extra information from a dataset through some scale-invariant characteristics related to the process of interest. While most studies utilize only one source of information, here we propose an approach that integrates two independent information sources, which are characterized by self-similar and relationship with other geo-referenced factors, respectively. This approach is applied to 16 years (1998–2013) of TRMM 3B43 monthly precipitation data in an orographic and monsoon influenced region in South China. Elevation, latitude, and longitude are used as predictive variables in the regression model, while self-similarity is characterized by multifractals and modeled by a log-normal multiplicative random cascade. The original 0.25° precipitation field was downscaled to the 0.01° scale. The result was validated with rain gauge data. Good consistency was achieved on coefficient of determination, bias, and root mean square error. This study contributes to the current precipitation downscaling methodology and is helpful for hydrology and water resources management, especially in areas with insufficient ground gauges. Full article
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<p>Study area and elevation.</p> Full article ">Figure 2
<p>Schematic overview of the downscaling approach.</p> Full article ">Figure 3
<p>Schematic of cascade for dimensional <span class="html-italic">d</span> = 1, branching number <span class="html-italic">b</span> = 2.</p> Full article ">Figure 4
<p>Regression results of TRMM 3B43 multi-year average with elevation, latitude, and longitude, showing the coefficient of determination (<span class="html-italic">R</span><sup>2</sup>).</p> Full article ">Figure 5
<p>Regression performance of the two approaches (stepwise multi-linear regression and ANN) on 0.25° (<b>a</b>); 0.5° (<b>b</b>); and 1.0° (<b>c</b>) scale, using elevation, longitude, and latitude as predictive variables. Shows the three indicators (<span class="html-italic">RMSE</span>, <span class="html-italic">R</span>, and <span class="html-italic">Bias</span>).</p> Full article ">Figure 6
<p><span class="html-italic">R</span><sup>2</sup> of the linear fitting between empirical moments and scales, for both original and detrended precipitation fields. The x-axis represents different orders of moment.</p> Full article ">Figure 7
<p>Multifractal analysis of filtered precipitation field for November 1998 (<b>a</b>,<b>b</b>) and June 2013 (<b>c</b>,<b>d</b>). Shows the linear relationship in log-log plot between empirical moment (τ(<span class="html-italic">q</span>)) and scale(λ) (a,c), and the curvature of the function τ(<span class="html-italic">q</span>) ~ <span class="html-italic">q</span> (b,d).</p> Full article ">Figure 8
<p>Relationship between averaged precipitation and the random cascade model parameter σ<sup>2</sup>.</p> Full article ">Figure 9
<p>Original and downscaled precipitation field, for the snapshot of November 1998 (<b>a</b>) and June 2013 (<b>b</b>).</p> Full article ">Figure 10
<p>Comparing downscaled precipitation field with rain gauge at specific locations. Shows the mean, 10 percentile, and 90 percentile of the corresponding downscaled ensemble fields of two gauge stations (106.46 E, 25.26 N (<b>a</b>); 108.15 E, 27.57 N (<b>b</b>)).</p> Full article ">Figure 11
<p>Comparing the three downscaled precipitation fields with all 72 rain gauges in the study area. “ANN” refers to the approach of downscaling the trend with ANN regression and the residual with interpolation; “MF” refers to the multifractal approach alone; “Combined” refers to the combined multifractal and regression approach.</p> Full article ">Figure 12
<p>Comparing of cumulative distribution function between station precipitation data and downscaled data. A wet month (<b>a</b>) June 1998 and a dry month (<b>b</b>) November 2013 are shown.</p> Full article ">
375 KiB  
Short Communication
River Flows in the Ebro Basin: A Century of Evolution, 1913–2013
by Julio Sánchez-Chóliz and Cristina Sarasa
Water 2015, 7(6), 3072-3082; https://doi.org/10.3390/w7063072 - 19 Jun 2015
Cited by 8 | Viewed by 4626
Abstract
The water forecast is a major uncertainty in the design of strategies to cope with potential restrictions and ensure the availability of water, even during extreme events such as drought. In this context, our study aimed to present and analyze an updated broad [...] Read more.
The water forecast is a major uncertainty in the design of strategies to cope with potential restrictions and ensure the availability of water, even during extreme events such as drought. In this context, our study aimed to present and analyze an updated broad temporal and geographical overview of the evolution of river flows for the most important river in Spain, the Ebro river, from 1913 to 2013. Our main findings indicate a decreasing trend in water resources from 1913 to the present, and a significant level of volatility that reveals a striking irregularity, with asymmetric cycles and dry years. These findings question the current irrigation policies and together with a need to rethink their implementation should drive further research. Full article
(This article belongs to the Special Issue Recent Advances in Riverflow Research)
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<p>Water flows in Tortosa (hm<sup>3</sup> per year) 1913–2013. Note: For example, <span class="html-italic">x</span> for 1943–1944 is equal to1943–1913, 1913 being the first year. Source: Own elaboration.</p> Full article ">Figure 2
<p>Water flows plus water consumption in Tortosa (hm<sup>3</sup> per year) 1913–2013. Note: <span class="html-italic">x</span> is obtained as in <a href="#water-07-03072-f001" class="html-fig">Figure 1</a>. Source: Own elaboration.</p> Full article ">Figure 3
<p>Water flows in Tortosa (hm<sup>3</sup> per year) 1913–2013 with trends and cycles. Source: Own elaboration. See also Supplementary Online Material of [<a href="#B4-water-07-03072" class="html-bibr">4</a>]. Note: <span class="html-italic">x</span> is obtained as in <a href="#water-07-03072-f001" class="html-fig">Figure 1</a> using for each cycle its initial year.</p> Full article ">
858 KiB  
Article
Removal of Metaldehyde from Water Using a Novel Coupled Adsorption and Electrochemical Destruction Technique
by Mohammed A. Nabeerasool, Andrew K. Campen, David A. Polya, Nigel W. Brown and Bart E. Van Dongen
Water 2015, 7(6), 3057-3071; https://doi.org/10.3390/w7063057 - 19 Jun 2015
Cited by 13 | Viewed by 8544
Abstract
Metaldehyde is a selective pesticide applied to control snails and slugs and which, particularly when application rates are high and during periods of high rainfall, may find its way into water courses, some of which may be used as drinking water supplies. Existing [...] Read more.
Metaldehyde is a selective pesticide applied to control snails and slugs and which, particularly when application rates are high and during periods of high rainfall, may find its way into water courses, some of which may be used as drinking water supplies. Existing water treatment processes have been inadequate for reducing metaldehyde residual levels (up to 8 µg/L) found in some waters to below the EU/UK statutory limit of 0.1 µg/L. Here a novel coupled adsorption and electrochemical regeneration technology is tested to determine if it is capable of effectively removing metaldehyde. We demonstrate that metaldehyde is not only adsorbed on the adsorbent used but is also destroyed during the regeneration stage, resulting in residual metaldehyde concentrations below the EU/UK regulatory limit for drinking water. No known harmful breakdown by-products were observed to be generated by the process. The effectiveness of the process seems unaffected by organic-rich peat water, indicating the potential for the treatment of drinking water much of which in the UK is derived from upland peaty catchments. Furthermore, successive spiking experiments showed that this technology has the potential to be applied as a continuous process without the generation of substantial waste products. Full article
(This article belongs to the Special Issue Water Quality Control and Management)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>(<b>A</b>) Kinetics of metaldehyde adsorption onto Nyex<sup>TM</sup> 1102. Metaldehyde remaining expressed as a percentage of the initial metaldehyde concentrations of 250, 2000 or 12,000 μg/L as indicated; (<b>B</b>) Adsorption isotherm of metaldehyde on Nyex<sup>TM</sup> 1102. Equilibration time 60 min; initial pH 6–7. Bars indicate the error; when they are not visible the error bar is smaller than the symbol used.</p> Full article ">Figure 2
<p>(<b>A</b>) Freundlich log-log plot of solid-phase concentration (q<sub>e</sub>) <span class="html-italic">versus</span> liquid-phase concentration (C<sub>e</sub>) at equilibrium. Dashed vertical line represent mean metaldehyde removed per treatment cycle as determined from <a href="#water-07-03057-f003" class="html-fig">Figure 3</a>A; (<b>B</b>) Langmuir plot for the metaldehyde/Nyex<sup>TM</sup> 1102 system, where q<sub>e</sub> and C<sub>e</sub> are in µg/g and µg/L, respectively. Bars indicate the error, when they are not visible the error bar is smaller than the symbol used.</p> Full article ">Figure 3
<p>Metaldehyde remaining (expressed as a percentage of initial concentration ~8000 µg/L) after successive treatment cycles (<b>A</b>) with and without regeneration (15 min; current 0.5 A) and mixing (15 min); under (<b>B</b>) varying mixing times at constant regeneration times of 15 min and current of 0.5 A; (<b>C</b>) varying regeneration times at constant mixing time of 15 min and current of 0.5 A; and (<b>D</b>) varying current at constant mixing time (15 min) and regeneration time (15 min; current 0.1 A, 0.25 A and 0.5 A). Dotted arrows indicate generalized trends, when there are multiple comparable trends only a single arrow is given. Bars indicate the error, when they are not visible the error bar is smaller than the symbol used.</p> Full article ">Figure 4
<p>Metaldehyde remaining of triplicate spikes (initial concentration 11 µg/L) after successive treatment cycles. Mixing times, 15 min; regeneration times, 15 min; current, 0.5 A. Bars indicate the error, when they are not visible the error bar is smaller than the symbol used. Metaldehyde concentrations in all the spikes were reduced to below the EU and UK regulatory limit of 0.1 μg/L [<a href="#B10-water-07-03057" class="html-bibr">10</a>] (dashed line) after seven treatment cycles.</p> Full article ">Figure 5
<p>Metaldehyde remaining (expressed as a percentage of the mean starting concentration of 8000 µg/L) after successive treatment cycles using the coupled adsorption and electrochemical regeneration technology (<b>A</b>) for different initial pHs and (<b>B</b>) in the presence and in the absence of other organics in peat water. Dotted arrows indicate generalised trends. Bars indicate the error; when they are not visible, the error bar is smaller than the symbol used. All experiments were carried out with mixing and regeneration times of 15 min and a current of 0.5 A.</p> Full article ">
4574 KiB  
Article
Effects of Land Use and Climate Change on Groundwater and Ecosystems at the Middle Reaches of the Tarim River Using the MIKE SHE Integrated Hydrological Model
by Patrick Keilholz, Markus Disse and Ümüt Halik
Water 2015, 7(6), 3040-3056; https://doi.org/10.3390/w7063040 - 19 Jun 2015
Cited by 46 | Viewed by 11267
Abstract
The Tarim basin is a unique ecosystem. The water from the Tarim River supports both wildlife and humans. To analyze the effects of both land use and climate changes on groundwater, a research site was established at Yingibazar, which is a river oasis [...] Read more.
The Tarim basin is a unique ecosystem. The water from the Tarim River supports both wildlife and humans. To analyze the effects of both land use and climate changes on groundwater, a research site was established at Yingibazar, which is a river oasis along the middle section of the Tarim River. A hydrological survey was performed to assess the general water cycle in this area with special emphasis on groundwater replenishment as well as the impact of agricultural irrigation on the riparian natural vegetation with respect to salt transport and depth of groundwater. Although high-resolution input data is scarce for this region, simulation of water cycle processes was performed using the hydrological model MIKE SHE (DHI). The results of the calibrated model show that natural flooding is the major contributor to groundwater recharge. There is also a close interaction between irrigated agricultural areas and the adjacent natural vegetation for groundwater levels and salinity up to 300 m away from the fields. Furthermore, the source of water used for irrigation (i.e., river and/or groundwater) has a high impact on groundwater levels and salt transportation efficiency. The ongoing expansion of agricultural areas is rapidly destroying natural vegetation, floodplains, and their natural flow paths. Our results show that more unstable annual Tarim floods will occur in the future under the background of climate change. Therefore, integrated hydrological simulations were also performed for 2050 and 2100 using MIKE SHE. The results confirm that after the glaciers melt in the Tian Shan Mountains, serious aquifer depletion and environmental degradation will occur in the area, causing great difficulties for the local people. Full article
(This article belongs to the Special Issue Sustainable Water Management and Decision Making under limited Data Availability)
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<p>Location of the research site at Yingibazar in the middle reaches of the Tarim River.</p> Full article ">Figure 2
<p>Schematic view of the MIKE SHE modules (DHI©, modified by Keilholz).</p> Full article ">Figure 3
<p>Comparison between the calibration (C), validation without land-use changes (V1), and validation with land-use changes (V2) for correlation (<b>a</b>); root mean square error (<b>b</b>) and mean error (<b>c</b>).</p> Full article ">Figure 4
<p>Groundwater recharge by the Tarim River (<b>a</b>) and floodplains (<b>b</b>) for the year 2012.</p> Full article ">Figure 5
<p>Changes in salt concentration and groundwater levels at transition zones when the irrigation water is used from local groundwater resources (<b>a</b>) or from the Tarim River (<b>b</b>).</p> Full article ">Figure 6
<p>Effects of land-use and climate change in the future (2050 and 2100) on flooding, distance to groundwater table in summer and winter, and water stress.</p> Full article ">Figure 7
<p>Changes in the vitality zones in future scenarios caused by (<b>a</b>) land-use changes and (<b>b</b>) land-use changes combined with climate change.</p> Full article ">
1289 KiB  
Article
Investigating Willingness to Pay to Improve Water Supply Services: Application of Contingent Valuation Method
by Kamshat Tussupova, Ronny Berndtsson, Torleif Bramryd and Raikhan Beisenova
Water 2015, 7(6), 3024-3039; https://doi.org/10.3390/w7063024 - 19 Jun 2015
Cited by 69 | Viewed by 11747
Abstract
Safe water supply is one of the important Millennium Goals. For development of market water supply services, the willingness of consumers to pay is essential. The consumers’ willingness to pay (WTP) for piped water supply using the contingent valuation (CV) method with different [...] Read more.
Safe water supply is one of the important Millennium Goals. For development of market water supply services, the willingness of consumers to pay is essential. The consumers’ willingness to pay (WTP) for piped water supply using the contingent valuation (CV) method with different starting point bids was investigated for the Pavlodar Region, Kazakhstan. The results showed that households with access to groundwater (well or borehole water users) perceived this as of good quality. Consumers without access to groundwater used open-source, standpipe or delivered water for which they had to travel and spend time or to pay. Open source water and standpipe water quality was perceived as bad or satisfactory. More than 90% of the consumers were willing to pay for better water quality and regular water supply. The mean WTP was estimated to be about 1120 in bids and about 1590 KZT per household per month in open-ended question format (150 KZT is ~1 USD as of January 2012). The results can be used to better identify the proper technological choice and the level of service to be provided making rural water projects both sustainable and replicable at a larger scale. Full article
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<p>Drinking water users’ perception of water quality.</p> Full article ">Figure 2
<p>Answer rate to open-ended and bids format questions for standpipe and private connection, respectively.</p> Full article ">Figure 3
<p>Boxplot of WTP for open-ended and bids answers both private connection and standpipe water (SD = standard deviation).</p> Full article ">Figure 4
<p>Cumulative distribution of maximum WTP (KZT) for standpipe (<b>a</b>) and private (<b>b</b>) connection.</p> Full article ">Figure 5
<p>(<b>a</b>) WTP bids distribution for private connection depending on water supply type (KZT); and (<b>b</b>) WTP bids distribution for standpipe water depending on water supply type (KZT).</p> Full article ">
2492 KiB  
Article
Analysis of Dry Spells in Southern Italy (Calabria)
by Tommaso Caloiero, Roberto Coscarelli, Ennio Ferrari and Beniamino Sirangelo
Water 2015, 7(6), 3009-3023; https://doi.org/10.3390/w7063009 - 17 Jun 2015
Cited by 37 | Viewed by 7991
Abstract
A deficit in precipitation may impact greatly on soil moisture, snowpack, stream flow, groundwater, and reservoir storage. Among the several approaches available to analyze this phenomenon, one of the most applied is the analysis of dry spells. In this paper, an investigation of [...] Read more.
A deficit in precipitation may impact greatly on soil moisture, snowpack, stream flow, groundwater, and reservoir storage. Among the several approaches available to analyze this phenomenon, one of the most applied is the analysis of dry spells. In this paper, an investigation of the spatial and temporal patterns of dry spells, in a region of southern Italy, has been carried out on a daily precipitation dataset. First, the frequency distributions of the sequences of dry days have been analyzed. Then, the regional areas most affected by dry events have been evaluated at annual and seasonal scale. Finally, the long-term trend of the dry spells has been estimated at annual and seasonal scale. Results show that the lower probabilities of long dry spells occur in the main reliefs of the region, while the highest values have been detected in the Ionian side. The spatial distribution of the mean and maximum length values of the dry spells evidenced a west–east gradient. The trend analysis mainly revealed a negative behavior in the duration of the dry spells at annual scale and a positive trend in the winter period. Full article
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<p>(<b>a</b>) Location of the selected stations on a Digital Elevation Model (DEM) of Calabria; (<b>b</b>) regional monthly precipitation distribution; and (<b>c</b>) regional seasonal precipitation distribution.</p> Full article ">Figure 2
<p>Spatial distributions of the (<b>a</b>) 90th; (<b>b</b>) 95th and (<b>c</b>) 99th percentiles of the dry spell durations.</p> Full article ">Figure 3
<p>(<b>a</b>) Yearly mean and (<b>b</b>) maximum length of the dry spells in the observation period.</p> Full article ">Figure 4
<p>Mean length of the dry spells on a seasonal basis, (<b>a</b>) winter; (<b>b</b>) spring; (<b>c</b>) summer and (<b>d</b>) autumn.</p> Full article ">Figure 5
<p>Maximum length of the dry spells on a seasonal basis: (<b>a</b>) winter; (<b>b</b>) spring; (<b>c</b>) summer and (<b>d</b>) autumn.</p> Full article ">Figure 6
<p>Summary and spatial distribution of the trend analysis on dry spell durations at (<b>a</b>) annual and seasonal scale: (<b>b</b>) winter; (<b>c</b>) spring; (<b>d</b>) summer and (<b>e</b>) autumn.</p> Full article ">
2171 KiB  
Article
Effects of Rainfall Intensity and Slope Gradient on Runoff and Soil Moisture Content on Different Growing Stages of Spring Maize
by Wenbin Mu, Fuliang Yu, Chuanzhe Li, Yuebo Xie, Jiyang Tian, Jia Liu and Nana Zhao
Water 2015, 7(6), 2990-3008; https://doi.org/10.3390/w7062990 - 17 Jun 2015
Cited by 101 | Viewed by 11088
Abstract
The rainfall-runoff process (RRP) is an important part of hydrologic process. There is an effective measure to study RRP through artificial rainfall simulation. This paper describes a study on three growing stages (jointing stage, tasseling stage, and mature stage) of spring maize in [...] Read more.
The rainfall-runoff process (RRP) is an important part of hydrologic process. There is an effective measure to study RRP through artificial rainfall simulation. This paper describes a study on three growing stages (jointing stage, tasseling stage, and mature stage) of spring maize in which simulated rainfall events were used to study the effects of various factors (rainfall intensity and slope gradient) on the RRP. The RRP was tested with three different rainfall intensities (0.67, 1.00, and 1.67 mm/min) and subjected to three different slopes (5°, 15°, and 20°) so as to study RRP characteristics in semiarid regions. Regression analysis was used to study the results of this test. The following key results were obtained: (1) With the increase in rainfall intensity and slope, the increasing relationship with rainfall duration, overland flow, and cumulative runoff, respectively, complied with logarithmic and quadratic functions before reaching stable runoff in each growing stage of spring maize; (2) The runoff coefficient increased with the increase in rainfall intensity and slope in each growing stages of spring maize. The relationship between runoff coefficient, slope, rainfall intensity, rainfall duration, antecedent soil moisture, and vegetation coverage was multivariate and nonlinear; (3) The runoff lag time decreased with the increase in rainfall intensity and slope within the same growing stage. In addition, the relationship between runoff lag time, slope, rainfall intensity, antecedent soil moisture, and vegetation coverage could also be expressed by a multivariate nonlinear equation; (4) The descent rate of soil infiltration rate curve increased with the increased rainfall intensity and slope in the same growing stage. Furthermore, by comparing the Kostiakov, Horton, and Philip models, it was found that the Horton infiltration model was the best for estimating soil infiltration rate and cumulative infiltration under the condition of test. Full article
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<p>The structure of the experimental plots and soil water measurement instruments [<a href="#B4-water-07-02990" class="html-bibr">4</a>].</p> Full article ">Figure 2
<p>RRP and cumulative runoff in growing stage with different rainfall intensities (<b>a</b>), (<b>c</b>) and (<b>e</b>) show the RRP of jointing stage, tasseling stage, and mature stage, respectively, with different rainfall intensities; (<b>b</b>), (<b>d</b>) and (<b>f</b>) show the cumulative runoff process of these three stages, respectively, with different rainfall intensities.</p> Full article ">Figure 3
<p>RRP and runoff accumulation process in growing stage with different slopes (<b>a</b>), (<b>c</b>) and (<b>e</b>) show the RRP of the jointing stage, tasseling stage, and mature stage, respectively, with different slopes; (<b>b</b>), (<b>d</b>) and (<b>f</b>) show the cumulative runoff process of these three stages, respectively, with different slopes).</p> Full article ">Figure 4
<p>Variation of runoff coefficient in each growing stage with different rainfall intensities at a slope of 10 degrees.</p> Full article ">Figure 5
<p>Variation of runoff coefficient in each growing stage with different slopes when the rainfall intensity is 0.5 mm/min.</p> Full article ">Figure 6
<p>Variation of runoff lag time in each growing stage of spring maize with different rainfall intensities at a slope of 10°.</p> Full article ">Figure 7
<p>Variation of runoff lag time in each growing stage of spring maize with different slopes when the rainfall intensity is 0.5 mm/min.</p> Full article ">Figure 8
<p>Curve of soil infiltration in growth period of spring maize: (<b>a</b>), (<b>b</b>) and (<b>c</b>) show the soil infiltration curves with different rainfall intensities in the jointing stage, tasseling stage, and mature stage, respectively; (<b>d</b>), (<b>e</b>) and (<b>f</b>) show the soil infiltration curves with different slopes in the three stages, respectively.</p> Full article ">
2151 KiB  
Article
Using Pressure and Alteration Indicators to Assess River Morphological Quality: Case Study of the Prahova River (Romania)
by Gabriela Ioana-Toroimac, Liliana Zaharia and Gabriel Minea
Water 2015, 7(6), 2971-2989; https://doi.org/10.3390/w7062971 - 17 Jun 2015
Cited by 11 | Viewed by 6562
Abstract
River morphological quality assessment, derived from quantification of human pressures as well as river channel alteration, is a demand of the Water Framework Directive (WFD) in terms of integrating hydromorphological elements in defining ecological status. Our study’s aim is to contribute to the [...] Read more.
River morphological quality assessment, derived from quantification of human pressures as well as river channel alteration, is a demand of the Water Framework Directive (WFD) in terms of integrating hydromorphological elements in defining ecological status. Our study’s aim is to contribute to the hydromorphological evaluation by proposing indicators and separating classes, based on a revisited Morphological Quality Index (rMQI) protocol. The rMQI is based on 12 indicators of human pressures, 10 indicators of channel form adjustments, and 11 indicators of functionality. The rMQI scoring system allows for the quantification of changes when compared to reference conditions, be they undisturbed or nearly undisturbed by human interventions, with absent channel adjustments and a functioning natural river style. We used the lower, meandering sector of the Prahova River to demonstrate our assessment methodology. The Lower Prahova River suffers from a minor local intervention and a diminishing intensity of fluvial processes specific to a meandering style. Meanders geometry was affected by significant changes that included a decrease in the radius of curvature, width and width–to–mean–depth ratio. We concluded that the Lower Prahova River has a good morphological quality, which is rated as second class on a scale of five levels, from natural to severely modified. We recommend an improvement in the hydromorphological evaluation protocol in Romania by additional indicators for morphological alterations specific to each channel pattern. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The study area and its features. (<b>a</b>) Location of the Prahova River basin in Romania; (<b>b</b>) Main morphometric characteristics of the Prahova River and basin [<a href="#B23-water-07-02971" class="html-bibr">23</a>]; (<b>c</b>) Location of the Lower Prahova River as studied river sector; (<b>d</b>) Land use in the Prahova River basin according to Corine Land Cover database [<a href="#B24-water-07-02971" class="html-bibr">24</a>].</p> Full article ">Figure 2
<p>Flowchart of a methodological protocol of the revisited Morphological Quality Index (rMQI); data and scoring for each indicator are in Supplementary File.</p> Full article ">Figure 3
<p>Results of Revisited Morphological Quality Index (rMQI) protocol for the Lower Prahova River; a list of acronyms for values are provided in Supplementary File.</p> Full article ">Figure 4
<p>Particularities of the Lower Prahova River. (<b>a</b>) Local human pressures; (<b>b</b>) Lateral dynamics of river channel during the 1954–2005 timeline.</p> Full article ">
5114 KiB  
Article
Comments on Uncertainty in Groundwater Governance in the Volcanic Canary Islands, Spain
by Emilio Custodio, María Del Carmen Cabrera, Roberto Poncela, Tatiana Cruz-Fuentes, Gema Naranjo and Luis Olavo Puga De Miguel
Water 2015, 7(6), 2952-2970; https://doi.org/10.3390/w7062952 - 17 Jun 2015
Cited by 9 | Viewed by 5918
Abstract
The uncertainty associated with natural magnitudes and processes is conspicuous in water resources and groundwater evaluation. This uncertainty has an essential component and a part that can be reduced to some extent by increasing knowledge, improving monitoring coverage, continuous elaboration of data and [...] Read more.
The uncertainty associated with natural magnitudes and processes is conspicuous in water resources and groundwater evaluation. This uncertainty has an essential component and a part that can be reduced to some extent by increasing knowledge, improving monitoring coverage, continuous elaboration of data and accuracy and addressing the related economic and social aspects involved. Reducing uncertainty has a cost that may not be justified by the improvement that is obtainable, but that has to be known to make the right decisions. With this idea, this paper contributes general comments on the evaluation of groundwater resources in the semiarid Canary Islands and on some of the main sources of uncertainty, but a full treatment is not attempted, nor how to reduce it. Although the point of view is local, these comments may help to address similar situations on other islands where similar problems appear. A consequence of physical and hydrological uncertainty is that different hydrogeological and water resource studies and evaluations may yield different results. Understanding and coarsely evaluating uncertainty helps in reducing administrative instability, poor decisions that may harm groundwater property rights, the rise of complaints and the sub-optimal use of the scarce water resources available in semiarid areas. Transparency and honesty are needed, but especially a clear understanding of what numbers mean and the uncertainty around them, to act soundly and avoid conflicting and damaging rigid attitudes. However, the different situations could condition that what may be good in a place, may not always be the case in other places. Full article
(This article belongs to the Special Issue Study, Development and Management of Water in Volcanic Areas)
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<p>Situation of the Canary Islands. The location of the example areas in Gran Canaria mentioned in the text are shown.</p> Full article ">Figure 2
<p>La Aldea area (NW of Gran Canaria). (<b>A</b>) Groundwater head contours (m asl) and flow paths corresponding to the 1991–1992 hydrologic year; (<b>B</b>) total recharge to the study area resulting from the hydrogeological model. Results depend highly on the variable yearly rainfall contribution, surface reservoir management, antecedent conditions and local decisions.</p> Full article ">Figure 3
<p>Preliminary recharge estimations in mm/year in the northeast of Gran Canaria Island, extending from the coast to the top [<a href="#B21-water-07-02952" class="html-bibr">21</a>]. Recharge ranges shows the uncertainty that can be expected in each area according to the two most sensible parameters: maximum soil water reserve (in italics) and threshold for runoff generation (underscored). The third figure in brackets refers to the estimated average ratio of yearly recharge to rainfall, as a fraction. N2, N3 and N4 refer to catchment areas of the Water Plan.</p> Full article ">
1887 KiB  
Article
Sensitivity and Interaction Analysis Based on Sobol’ Method and Its Application in a Distributed Flood Forecasting Model
by Hui Wan, Jun Xia, Liping Zhang, Dunxian She, Yang Xiao and Lei Zou
Water 2015, 7(6), 2924-2951; https://doi.org/10.3390/w7062924 - 17 Jun 2015
Cited by 26 | Viewed by 6946
Abstract
Sensitivity analysis is a fundamental approach to identify the most significant and sensitive parameters, helping us to understand complex hydrological models, particularly for time-consuming distributed flood forecasting models based on complicated theory with numerous parameters. Based on Sobol’ method, this study compared the [...] Read more.
Sensitivity analysis is a fundamental approach to identify the most significant and sensitive parameters, helping us to understand complex hydrological models, particularly for time-consuming distributed flood forecasting models based on complicated theory with numerous parameters. Based on Sobol’ method, this study compared the sensitivity and interactions of distributed flood forecasting model parameters with and without accounting for correlation. Four objective functions: (1) Nash–Sutcliffe efficiency (ENS); (2) water balance coefficient (WB); (3) peak discharge efficiency (EP); and (4) time to peak efficiency (ETP) were implemented to the Liuxihe model with hourly rainfall-runoff data collected in the Nanhua Creek catchment, Pearl River, China. Contrastive results for the sensitivity and interaction analysis were also illustrated among small, medium, and large flood magnitudes. Results demonstrated that the choice of objective functions had no effect on the sensitivity classification, while it had great influence on the sensitivity ranking for both uncorrelated and correlated cases. The Liuxihe model behaved and responded uniquely to various flood conditions. The results also indicated that the pairwise parameters interactions revealed a non-ignorable contribution to the model output variance. Parameters with high first or total order sensitivity indices presented a corresponding high second order sensitivity indices and correlation coefficients with other parameters. Without considering parameter correlations, the variance contributions of highly sensitive parameters might be underestimated and those of normally sensitive parameters might be overestimated. This research laid a basic foundation to improve the understanding of complex model behavior. Full article
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<p>The location, elevation, river networks, and distribution of rain gauge and hydrologic stations of the Nanhua Creek catchment.</p> Full article ">Figure 2
<p>Comparisons between the observed and the Liuxihe simulated hydrographs for the three representative storm floods. (<b>a</b>) 198106; (<b>b</b>) 198505; (<b>c</b>) 198005.</p> Full article ">Figure 3
<p>Scatter plots of the Morris screening results based on different objective functions measures under small, medium, and large flood magnitudes.</p> Full article ">Figure 4
<p>Comparisons between the first and total order sensitivity indices of seven parameters in the Liuxihe model with and without accounting for correlations based on different objective functions measures under three different flood magnitudes (UCS1 and UCST designated the uncorrelated first and total order sensitivity indices; CS1 and CST designated the correlated first and total order sensitivity indices).</p> Full article ">Figure 5
<p>Variations of the total order sensitivity indices along with increasing sample size. (<b>a</b>) For the least sensitive parameter <span class="html-italic">Ks</span>; (<b>b</b>) for the most sensitive parameter <span class="html-italic">FC</span>.</p> Full article ">Figure 6
<p>Second order sensitivity indices between 12 parameters based on different objective functions measures under three different flood magnitudes. Dark grey shadow denoted high parameter interactions. Light gray shadow denoted low parameter interactions.</p> Full article ">
273 KiB  
Article
Welfare Effects of Water Variability in Agriculture. Insights from a Multimarket Model
by Roberto Ponce, María Blanco and Carlo Giupponi
Water 2015, 7(6), 2908-2923; https://doi.org/10.3390/w7062908 - 16 Jun 2015
Cited by 6 | Viewed by 5541
Abstract
The purpose of this research is to assess the welfare effects of climate change on the Chilean agricultural sector, with special focus on changes in water availability. The productive impacts of climate change on the agricultural sector are well analyzed at both a [...] Read more.
The purpose of this research is to assess the welfare effects of climate change on the Chilean agricultural sector, with special focus on changes in water availability. The productive impacts of climate change on the agricultural sector are well analyzed at both a global and national level. There is, however, a lack of evidence about the aggregated impacts, considering both demand and supply. This study tries to fill this gap by using a multimarket model, specifically designed for the Chilean agricultural sector. According to our results, changes in water availability will have modest welfare impacts, with an average decrease of total surplus of 4.3%, minor price changes (around −1%), and no significant impacts on total agricultural land. Despite the small aggregated effects, it is expected that climate change will have uneven consequences across regions and activities. For instance, even though the southern zone (zone 3) shows the smallest income changes −14% (average), the impacts within the zone range from 1% to 52% decrease in agricultural net income. This situation suggests large distributional consequences of climate change for the Chilean agricultural sector. Full article
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<p>Cumulative Distribution Function: CPS (Million USD).</p> Full article ">
412 KiB  
Article
Contribution of Water Saving to a Stable Power Supply in Vietnam
by Takayuki Otani, Kanako Toyosada and Yasutoshi Shimizu
Water 2015, 7(6), 2900-2907; https://doi.org/10.3390/w7062900 - 15 Jun 2015
Cited by 4 | Viewed by 5607
Abstract
In Vietnam, the rapid expansion of cities is exceeding the supply capacity for water and electricity, and restrictions on water supply and blackouts occur on a daily basis. In this study, the authors examined whether water-saving equipment could solve these problems. This paper [...] Read more.
In Vietnam, the rapid expansion of cities is exceeding the supply capacity for water and electricity, and restrictions on water supply and blackouts occur on a daily basis. In this study, the authors examined whether water-saving equipment could solve these problems. This paper focused on toilet bowls that consumed a large amount of water, and on showers for which heat consumption was high. In Vietnam, the main heat source for showers is the electric water heater, typically having a power consumption of 2500–4500 W. Although the current diffusion rate of such water heaters is just 13%, their use will spread widely in the future. These heaters have already placed a peak load on electricity consumption in winter when a large amount of energy is consumed for heating water, and they will become a significant factor in blackout risks as their use becomes commonplace nationwide. It is clear that the introduction of water-saving showers will allow not only a more efficient use of water resources, but will also mitigate against the risk of blackouts. Full article
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<p>Power consumption forecast and power capacity in southern Vietnam (Vietnam Electricity Research 2012).</p> Full article ">Figure 2
<p>Conceptual diagram of water-saving project evaluation in developing countries.</p> Full article ">Figure 3
<p>Water and shower temperature in Hanoi and Ho Chi Minh City.</p> Full article ">Figure 4
<p>Effect of water saving on water and electric power supply in Vietnam. BaU: Completion of water infrastructure building; Project: Implementation of water-saving project.</p> Full article ">Figure 5
<p>Electricity consumption in Vietnam.</p> Full article ">
2858 KiB  
Article
Quantitative Impacts of Climate Change and Human Activities on Water-Surface Area Variations from the 1990s to 2013 in Honghu Lake, China
by Bianrong Chang, Rendong Li, Chuandong Zhu and Kequn Liu
Water 2015, 7(6), 2881-2899; https://doi.org/10.3390/w7062881 - 15 Jun 2015
Cited by 24 | Viewed by 6323
Abstract
The water-surface areas of the lakes in the mid-lower reaches of the Yangtze River, China, have undergone significant changes under the combined impacts of global climate change and local anthropogenic stress. As a typical lake in this region, the Honghu Lake features water-surface [...] Read more.
The water-surface areas of the lakes in the mid-lower reaches of the Yangtze River, China, have undergone significant changes under the combined impacts of global climate change and local anthropogenic stress. As a typical lake in this region, the Honghu Lake features water-surface area variations that are documented in this study based on high–resolution remote sensing images from the 1990s to 2013. The impact of human activities is analyzed by a novel method based on land use data. The relative impacts of each driving force are further distinguished by the statistical analysis method. Results show that the water-surface area has significant inter-annual and seasonal variabilities, and the minimum of which generally occurs in spring. The degree to which climate factors and land use structure affect the water-surface area varies between different stages. In the April-May period, the sum of the water demands of paddies and aquaculture has a negative effect that is greater than the positive effect of the difference between the monthly precipitation and monthly evaporation. In the June–October period, the precipitation features a positive impact that is greater than the negative effect of the water demand of agriculture. Meanwhile, climate factors and human activities have no influence on the lake area in the November–March period. With the land use being altered when annual precipitations are close in value, paddy field areas decrease, ponds areas increase, and the water demand of agriculture rises in both flood and drought years. These findings provide scientific foundation for understanding the causes of water-surface area variations and for effectively maintaining the stability of the Honghu Lake area through adjustments in land use structure. Full article
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<p>Location of Honghu Lake, Hubei Province, China.</p> Full article ">Figure 2
<p>Monthly minimum and maximum area distributions of the Honghu Lake from the 1990s to 2013.</p> Full article ">Figure 3
<p>Minimum and maximum area distributions of Honghu Lake each year from 1990s to 2013</p> Full article ">Figure 4
<p>Curve of water-surface area variations of the Honghu Lake from the 1990s to 2013.</p> Full article ">Figure 5
<p>Relationship between water area and climate factors in the (<b>a</b>) April–May and (<b>b</b>) June–October periods.</p> Full article ">Figure 6
<p>Water demands for three types of land use in the (<b>a</b>) April-May and (<b>b</b>) June-October periods of representative wet and dry years.</p> Full article ">
1569 KiB  
Article
A Multi-Criteria Model Selection Protocol for Practical Applications to Nutrient Transport at the Catchment Scale
by Ye Tuo, Gabriele Chiogna and Markus Disse
Water 2015, 7(6), 2851-2880; https://doi.org/10.3390/w7062851 - 15 Jun 2015
Cited by 18 | Viewed by 7107
Abstract
Process-based models are widely used to investigate nutrient dynamics for water management purposes. Simulating nutrient transport and transformation processes from agricultural land into water bodies at the catchment scale are particularly relevant and challenging tasks for water authorities. However, few practical methods guide [...] Read more.
Process-based models are widely used to investigate nutrient dynamics for water management purposes. Simulating nutrient transport and transformation processes from agricultural land into water bodies at the catchment scale are particularly relevant and challenging tasks for water authorities. However, few practical methods guide inexperienced modelers in the selection process of an appropriate model. In particular, data availability is a key aspect in a model selection protocol, since a large number of models contain the functionalities to predict nutrient fate and transport, yet a smaller number is applicable to specific datasets. In our work, we aim at providing a model selection protocol fit for practical application with particular emphasis on data availability, cost-benefit analysis and user’s objectives. We select for illustrative purposes five process-based models with different complexity as “candidates” models: SWAT (Soil and Water Assessment Tool), SWIM (Soil and Water Integrated Model), GWLF (Generalized Watershed Loading Function), AnnAGNPS (Annualized Agricultural Non-Point Source Pollution model) and HSPF (Hydrological simulation program-FORTRAN). The models are described in terms of hydrological and chemical output and input requirements. The model selection protocol considers data availability, model characteristics and user’s objectives and it is applied to hypothetical scenarios. This selection method is particularly formulated to choose process-based models for nutrient modeling, but it can be generalized for other applications which are characterized by a similar degree of complexity. Full article
(This article belongs to the Special Issue Sustainable Water Management and Decision Making under limited Data Availability)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Hydrology/hydrogeology processes considered by common process-based models.</p> Full article ">Figure 2
<p>Amounts of inputs for each category: (<b>a</b>) climate; (<b>b</b>) soil; (<b>c</b>) hydrology/hydrogeology; (<b>d</b>) land use and vegetation; (<b>e</b>) topography; and (<b>f</b>) separated system.</p> Full article ">Figure 2 Cont.
<p>Amounts of inputs for each category: (<b>a</b>) climate; (<b>b</b>) soil; (<b>c</b>) hydrology/hydrogeology; (<b>d</b>) land use and vegetation; (<b>e</b>) topography; and (<b>f</b>) separated system.</p> Full article ">Figure 3
<p>Numbers of nutrient inputs sources of the models: (<b>a</b>) N input sources; (<b>b</b>) P input sources.</p> Full article ">Figure 4
<p>Numbers of transport and transformation processes involved in the nutrient outputs: (<b>a</b>) N transport processes; (<b>b</b>) N transformation processes; (<b>c</b>) P transport processes; (<b>d</b>) P transformation processes.</p> Full article ">Figure 5
<p>Scheme of the model selection protocol.</p> Full article ">
483 KiB  
Article
Hydraulic Behavior and Chemical Characterization of Lapilli as Material for Natural Filtering of Slurry
by Nereida Falcón-Cardona, Vanessa Mendoza-Grimón, Juan Ramón Fernández-Vera, Idaira Hernández-Brito, Jose Manuel Hernández-Moreno, Sebastian O. Pérez Báez, Axel Ritter and María Del Pino Palacios-Díaz
Water 2015, 7(6), 2840-2850; https://doi.org/10.3390/w7062840 - 15 Jun 2015
Cited by 2 | Viewed by 4853
Abstract
Livestock effluents are a beneficial nutrient supply for crops, whereby their use is critical to ensure the sustainability of the farms global management. However, they can cause serious ecological problems if misused, polluting soils and groundwater. Combining “soft technology” and local materials is [...] Read more.
Livestock effluents are a beneficial nutrient supply for crops, whereby their use is critical to ensure the sustainability of the farms global management. However, they can cause serious ecological problems if misused, polluting soils and groundwater. Combining “soft technology” and local materials is a low cost solution in terms of finance and energy. The REAGUA project (REuso AGUA, Water reuse in Spanish) analyzes the possibility of using “picon” (lapilli) as a material for the treatment of liquid manure from ruminants, for later use in subsurface drip irrigation system to produce forage and biofuels, in which the soil acts as a subsequent advanced treatment. A three-phase system, in which the effluent was poured with a vertical subsurface flow in an unsaturated medium, is designed. In order to determine the management conditions that optimize the filter, it was necessary to characterize the hydraulic behavior of lapilli and its ability to remove substances. Using three lapilli-filled columns, unsaturated flux, and a ruminant effluent, the reduction of chemical oxygen demand (COD), biochemical oxygen demand after 5 days (BOD5) and ammonia, phosphorus and suspension solids (SS) obtained was over 80%, 90%, and 95% respectively, assumable values for irrigation. Full article
(This article belongs to the Special Issue Study, Development and Management of Water in Volcanic Areas)
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<p>Volumetric water content versus time in each of the columns.</p> Full article ">Figure 2
<p>Bromide tracer concentration (<b>a</b>) and phosphate (<b>b</b>) <span class="html-italic">versus</span> time of sampling.</p> Full article ">Figure 3
<p>Values of ammonium concentration (<b>a</b>) and phosphorus (<b>b</b>) over time at the three columns.</p> Full article ">
1832 KiB  
Article
Large-Scale Hydrological Modeling and Decision-Making for Agricultural Water Consumption and Allocation in the Main Stem Tarim River, China
by Yang Yu, Markus Disse, Ruide Yu, Guoan Yu, Lingxiao Sun, Philipp Huttner and Christian Rumbaur
Water 2015, 7(6), 2821-2839; https://doi.org/10.3390/w7062821 - 12 Jun 2015
Cited by 34 | Viewed by 9261
Abstract
A large-scale hydrological model (MIKE HYDRO) was established for the purpose of sustainable agricultural water management in the main stem Tarim River, located in northwest China. In this arid region, agricultural water consumption and allocation management are crucial to address the conflicts among [...] Read more.
A large-scale hydrological model (MIKE HYDRO) was established for the purpose of sustainable agricultural water management in the main stem Tarim River, located in northwest China. In this arid region, agricultural water consumption and allocation management are crucial to address the conflicts among irrigation water users from upstream to downstream. The results of model calibration indicated a close correlation between simulated and observed values. Scenarios with the change on irrigation strategies and land use distributions were investigated. Irrigation scenarios revealed that the available irrigation water has significant and varying effects on the yields of different crops. Irrigation water saving could reach up to 40% in the water-saving irrigation scenario. Land use scenarios illustrated that an increase of farmland area in the lower reach gravely aggravated the water deficit, while a decrease of farmland in the upper reaches resulted in considerable benefits for all sub-catchments. A substitution of crops was also investigated, which demonstrated the potential for saving considerable amounts of irrigation water in upper and middle reaches. Overall, the results of this study provide a scientific basis for decision-making on agricultural water consumption and allocation in the study area. Full article
(This article belongs to the Special Issue Sustainable Water Management and Decision Making under limited Data Availability)
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<p>Tarim River basin and main stem river gauging stations.</p> Full article ">Figure 2
<p>Annual discharge of the main stem Tarim River in the past six decades.</p> Full article ">Figure 3
<p>Sub-catchments in the main stem of Tarim River in MIKE HYDRO.</p> Full article ">Figure 4
<p>Observed and simulated discharge from three gauging stations: 2006–2008.</p> Full article ">Figure 5
<p>Actual crop evapotranspiration (<span class="html-italic">ET</span><sub>a</sub>) and deep percolation (DP) in sub-catchments A–D during the crop-growing season.</p> Full article ">Figure 6
<p>Irrigation scenarios based on fraction of total available water (TAW). Average yield performance of crops showing in the whole irrigation field within three-year simulation period.</p> Full article ">Figure 7
<p>Effects of land use scenarios LUD (land use decrease), LUI (land use increase) and CTC (crop type change), with irrigation water demand reduction and % irrigation water deficit reduction as indicators in sub-catchments A–D.</p> Full article ">
5791 KiB  
Article
Climate or Land Use?—Attribution of Changes in River Flooding in the Sahel Zone
by Valentin Aich, Stefan Liersch, Tobias Vetter, Jafet C. M. Andersson, Eva N. Müller and Fred F. Hattermann
Water 2015, 7(6), 2796-2820; https://doi.org/10.3390/w7062796 - 12 Jun 2015
Cited by 54 | Viewed by 9349
Abstract
This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the [...] Read more.
This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the observed trends to the postulated drivers. For this purpose, the ecohydrological model SWIM (Soil and Water Integrated Model) with a new, dynamic LULC module was set up for the Sahelian part of the Niger River until Niamey, including the main tributaries Sirba and Goroul. The model was driven with observed, reanalyzed climate and LULC data for the years 1950–2009. In order to quantify the shares of influence, one simulation was carried out with constant land cover as of 1950, and one including LULC. As quantitative measure, the gradients of the simulated trends were compared to the observed trend. The modeling studies showed that for the Sirba River only the simulation which included LULC was able to reproduce the observed trend. The simulation without LULC showed a positive trend for flood magnitudes, but underestimated the trend significantly. For the Goroul River and the local flood of the Niger River at Niamey, the simulations were only partly able to reproduce the observed trend. In conclusion, the new LULC module enabled some first quantitative insights into the relative influence of LULC and climatic changes. For the Sirba catchment, the results imply that LULC and climatic changes contribute in roughly equal shares to the observed increase in flooding. For the other parts of the subcatchment, the results are less clear but show, that climatic changes and LULC are drivers for the flood increase; however their shares cannot be quantified. Based on these modeling results, we argue for a two-pillar adaptation strategy to reduce current and future flood risk: Flood mitigation for reducing LULC-induced flood increase, and flood adaptation for a general reduction of flood vulnerability. Full article
(This article belongs to the Special Issue Hydro-Ecological Modeling)
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<p>Map of the research area in West Africa including land use classes used in the model as base map in the year 2000. The orange, green, and red outlines mark the watershed of the gauging stations Alcongui (Goroul River), Garbe-Kourou (Sirba River) and the watershed of Niamey (Niger River). The grey dots show the grid of the PGFv2 climate reanalysis data set. The red dots show the grid of the climate data used for the analysis. The hatched area marks the region which is used for the quantification of land use and land cover changes.</p> Full article ">Figure 2
<p>Land use and land cover changes between 1950 and 2005 for crop and pasture after Hurtt <span class="html-italic">et al.</span> (2011) [<a href="#B23-water-07-02796" class="html-bibr">23</a>].</p> Full article ">Figure 3
<p>Changes in the main land use classes of crop, savannah, and pasture from 1950 until 2005 for the watershed of the Niger River between Ansongo and Niamey, and the catchments of the Sirba and Goroul Rivers (see area in <a href="#water-07-02796-f001" class="html-fig">Figure 1</a>).</p> Full article ">Figure 4
<p>Comparison of precipitation from interpolated PGFv2 reanalysis data (red) with observations from six weather stations (black) in the research area. For each station, the annual precipitation (<b>left</b>) and the cumulative sum of the precipitation of the whole period (<b>right</b>) is depicted.</p> Full article ">Figure 5
<p>Comparison of mean annual temperature of interpolated PGFv2 reanalysis data (red) with observations from six weather stations (black) in the research area.</p> Full article ">Figure 6
<p>Exemplary process of how the information from the Land Use and Land Cover data of the Land-Use Harmonization project is used on the subbasin level to produce land cover maps for the different years which are then used by the land use change module. The whole square represents one exemplary subbasin, with small squares representing individual stable units (SU).</p> Full article ">Figure 7
<p>Comparison of discharges with four different land use coverages (100% crop, 100% pasture, 100% Savanna and land use as observed) for the Sirba and Goroul watersheds.</p> Full article ">Figure 8
<p>Validation and calibration of the SWIM model for the watersheds of Alcongui, Garbe-Kourou and Niamey for eight-year periods using PGFv2 reanalysis climate forcing. For Niamey, the measured discharge at the Diré gauge is additionally plotted, which is fed into the model.</p> Full article ">Figure 9
<p>Anomalies of annual maximum discharges for the gauging stations Alcongui (Goroul River), Garbe-Kourou (Sirba River) and differentiated between the Red and the Guinean Flood for Niamey (Niger River). On the top of each region, rainfall anomalies over the respective catchment are plotted. A LOESS curve with a minimum point is added as a dashed line and the Theil-Sen estimators for the discharge trends are plotted as bold lines, beginning at the minimum of the observed discharge points. Please note that, for the observed values of the Red Flood at Niamey, the time series is incomplete (see <a href="#sec2dot4dot2-water-07-02796" class="html-sec">Section 2.4.2</a>). Therefore, the LOESS curve is not plotted and the trends start at 1984 (see <a href="#sec2dot6-water-07-02796" class="html-sec">Section 2.6</a>). For the Guinean Flood at Niamey, all minima are on the same point and the circle is plotted in black.</p> Full article ">
1579 KiB  
Article
A Mix Inexact-Quadratic Fuzzy Water Resources Management Model of Floodplain (IQT-WMMF) for Regional Sustainable Development of Dahuangbaowa, China
by Xueting Zeng, Xiaoliu Yang, Liyang Yu and Huili Chen
Water 2015, 7(6), 2771-2795; https://doi.org/10.3390/w7062771 - 12 Jun 2015
Cited by 18 | Viewed by 5826
Abstract
In this study, a mix inexact-quadratic fuzzy water resources management model of floodplain (IQT-WMMF) has developed, through incorporating techniques of credibility-constrained programming (CP), two-stage programming (TP), interval-parameter programming (IPP) and quadratic programming (QP) within a general framework for limited data availability. The IQT-WMMF [...] Read more.
In this study, a mix inexact-quadratic fuzzy water resources management model of floodplain (IQT-WMMF) has developed, through incorporating techniques of credibility-constrained programming (CP), two-stage programming (TP), interval-parameter programming (IPP) and quadratic programming (QP) within a general framework for limited data availability. The IQT-WMMF can provide an effective linkage between system benefit and the associated economic penalty attributed to the violation of the pre-regulated water target under limited data availabilities expressed probabilistic distributions and interval values; meanwhile, imprecise and no-linear economic data would be resolved. The developed method is applied to a real case of planning water resources in the Dahuangbaowa floodplain, China, with the aim to develop a sustainable water resources management in the study region. A number of scenarios with wet land expansion strategies under various credibility levels are analyzed, implying that different policies can lead to varied water-allocation patterns, system benefits, and system-failure risks. The results discover that water deficits and flood damages have brought negative effects on economic development synchronously, which need to effective plans to reduce losses of shortages and floods for achieving higher system benefits. Tradeoffs between economic benefit and system-failure risk can support generating an increased robustness in risk control for water resources allocation under uncertainties, which is beneficial to adjust the current water-allocation sustainably. Full article
(This article belongs to the Special Issue Sustainable Water Management and Decision Making under limited Data Availability)
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<p>Study area.</p> Full article ">Figure 2
<p>Framework of IQT-WMMF application of Dahuangbaowa floodplain.</p> Full article ">Figure 3
<p>Optimized water targets under scenario 1 (λ = 0.6).</p> Full article ">Figure 4
<p>Water shortages and surplus under scenario 1 (λ = 0.6).</p> Full article ">Figure 5
<p>Water allocation under scenario 1 (λ = 0.6).</p> Full article ">Figure 6
<p>Water allocation of ecology under various λ-cut levels (scenario 1).</p> Full article ">Figure 7
<p>System benefits for scenarios 1–3.</p> Full article ">Figure 8
<p>Water shortages and surplus of ecology under scenarios 1 to 3 (λ = 0.6).</p> Full article ">Figure 9
<p>Water allocations under scenarios 1 to 3 (λ = 0.6).</p> Full article ">
2088 KiB  
Article
Discharge Alterations of the Mures River, Romania under Ensembles of Future Climate Projections and Sequential Threats to Aquatic Ecosystem by the End of the Century
by Anastasia Lobanova, Judith Stagl, Tobias Vetter and Fred Hattermann
Water 2015, 7(6), 2753-2770; https://doi.org/10.3390/w7062753 - 9 Jun 2015
Cited by 10 | Viewed by 6499
Abstract
This study aims to assess the potential alterations in the hydrological regime attributed to projected climate change in one of the largest rivers in the Carpathian Area, the Mures River, and to estimate associated threats to riverine ecosystem. The eco-hydrological model, Soil and [...] Read more.
This study aims to assess the potential alterations in the hydrological regime attributed to projected climate change in one of the largest rivers in the Carpathian Area, the Mures River, and to estimate associated threats to riverine ecosystem. The eco-hydrological model, Soil and Water Integrated Model (SWIM), was applied on the Mures River basin, calibrated and validated against records at a gauging station in Alba-Julia town. A set of nine future projections for climatic parameters under one emissions scenario A1B over the period 1971–2100 were fed into the SWIM model. To provide functional link between hydrological regimes and riverine ecosystems, each of the nine simulated discharge time series were introduced into the IHA (Indicators of Hydrological Alterations) tool. Triggered changes in hydrological patterns of the Mures River were assessed at the basin and sub-basin scales. The obtained results present a strong agreement through all nine climate projections; suggesting an increase in the discharge of Mures River for the winter season; a decrease in summer and prolongation of the low flow periods by the end of the century. Anticipated changes would pose threats to aquatic ecosystems; altering normal life-cycles; and depleting natural habitats of species. Full article
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<p>Mures River basin.</p> Full article ">Figure 2
<p>Diagram of the workflow process.</p> Full article ">Figure 3
<p>Calibration of Mures River model until Alba Julia gauge, over period from 1986 to 1994.</p> Full article ">Figure 4
<p>Validation of Mures River model until Alba Julia gauge, over period from 1996 to 2001.</p> Full article ">Figure 5
<p>Deviation in monthly median discharge of Mures River for 2021–2050 [<a href="#B42-water-07-02753" class="html-bibr">42</a>].</p> Full article ">Figure 6
<p>Deviation in monthly median discharge of Mures River for 2071–2100.</p> Full article ">Figure 7
<p>Duration of high flow event in days for reference and two future periods for all nine future projections, respectively.</p> Full article ">Figure 8
<p>Duration of low flow event in days for reference and two future periods for all nine future projections, respectively.</p> Full article ">Figure 9
<p>Mapping of percentage deviations in number of selected indicators on the sub-basin level: (<b>a</b>, <b>a'</b>), Percentage deviation in the duration low flow event for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>b</b>, <b>b'</b>) Percentage deviation in the duration low flow event for the second future period with respect to reference period and associated standard deviation for nine model runs; (<b>c</b>, <b>c'</b>) Percentage deviation in the monthly discharged during calendar winter; (<b>d</b>, <b>d'</b>) Percentage deviation in the monthly discharge during calendar winter months for the second future period with respect to reference period and associated standard deviation for nine model runs d' months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>e</b>, <b>e'</b>) Percentage deviation in the monthly discharge during calendar summer months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>f</b>, <b>f'</b>) Percentage deviation in the monthly discharge during calendar summer months for the second future period with respect to reference period and associated standard deviation for nine model runs; (<b>g</b>, <b>g'</b>) Percentage deviation in the monthly discharge during calendar autumn months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>h</b>, <b>h'</b>) Percentage deviation in the monthly discharge during calendar autumn months for the second future period with respect to reference period and associated standard deviation for nine model runs; (<b>i</b>, <b>i'</b>) Percentage deviation in the monthly discharge during calendar spring months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>j</b>, <b>j'</b>) Percentage deviation in the monthly discharge during calendar spring months for the second future period with respect to reference period and associated standard deviation for nine model runs.</p> Full article ">Figure 9 Cont.
<p>Mapping of percentage deviations in number of selected indicators on the sub-basin level: (<b>a</b>, <b>a'</b>), Percentage deviation in the duration low flow event for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>b</b>, <b>b'</b>) Percentage deviation in the duration low flow event for the second future period with respect to reference period and associated standard deviation for nine model runs; (<b>c</b>, <b>c'</b>) Percentage deviation in the monthly discharged during calendar winter; (<b>d</b>, <b>d'</b>) Percentage deviation in the monthly discharge during calendar winter months for the second future period with respect to reference period and associated standard deviation for nine model runs d' months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>e</b>, <b>e'</b>) Percentage deviation in the monthly discharge during calendar summer months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>f</b>, <b>f'</b>) Percentage deviation in the monthly discharge during calendar summer months for the second future period with respect to reference period and associated standard deviation for nine model runs; (<b>g</b>, <b>g'</b>) Percentage deviation in the monthly discharge during calendar autumn months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>h</b>, <b>h'</b>) Percentage deviation in the monthly discharge during calendar autumn months for the second future period with respect to reference period and associated standard deviation for nine model runs; (<b>i</b>, <b>i'</b>) Percentage deviation in the monthly discharge during calendar spring months for the first future period with respect to reference period and associated standard deviation for nine model runs; (<b>j</b>, <b>j'</b>) Percentage deviation in the monthly discharge during calendar spring months for the second future period with respect to reference period and associated standard deviation for nine model runs.</p> Full article ">
1625 KiB  
Article
The Costs of Benefit Sharing: Historical and Institutional Analysis of Shared Water Development in the Ferghana Valley, the Syr Darya Basin
by Ilkhom Soliev, Kai Wegerich and Jusipbek Kazbekov
Water 2015, 7(6), 2728-2752; https://doi.org/10.3390/w7062728 - 9 Jun 2015
Cited by 41 | Viewed by 11109
Abstract
Ongoing discussions on water-energy-food nexus generally lack a historical perspective and more rigorous institutional analysis. Scrutinizing a relatively mature benefit sharing approach in the context of transboundary water management, the study shows how such analysis can be implemented to facilitate understanding in an [...] Read more.
Ongoing discussions on water-energy-food nexus generally lack a historical perspective and more rigorous institutional analysis. Scrutinizing a relatively mature benefit sharing approach in the context of transboundary water management, the study shows how such analysis can be implemented to facilitate understanding in an environment of high institutional and resource complexity. Similar to system perspective within nexus, benefit sharing is viewed as a positive sum approach capable of facilitating cooperation among riparian parties by shifting the focus from the quantities of water to benefits derivable from its use and allocation. While shared benefits from use and allocation are logical corollary of the most fundamental principles of international water law, there are still many controversies as to the conditions under which benefit sharing could serve best as an approach. Recently, the approach has been receiving wider attention in the literature and is increasingly applied in various basins to enhance negotiations. However, relatively little attention has been paid to the costs associated with benefit sharing, particularly in the long run. The study provides a number of concerns that have been likely overlooked in the literature and examines the approach in the case of the Ferghana Valley shared by Kyrgyzstan, Tajikistan and Uzbekistan utilizing data for the period from 1917 to 2013. Institutional analysis traces back the origins of property rights of the transboundary infrastructure, shows cooperative activities and fierce negotiations on various governance levels. The research discusses implications of the findings for the nexus debate and unveils at least four types of costs associated with benefit sharing: (1) Costs related to equity of sharing (horizontal and vertical); (2) Costs to the environment; (3) Transaction costs and risks of losing water control; and (4) Costs as a result of likely misuse of issue linkages. Full article
(This article belongs to the Special Issue Water-Energy-Food Nexus in Large Asian River Basins)
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<p>Topography, transboundary water resources and infrastructure in the Ferghana Valley (map by Alexander Platonov, 2015; courtesy of the International Water Management Institute).</p> Full article ">
2699 KiB  
Article
Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models
by Sungwon Kim and Vijay P. Singh
Water 2015, 7(6), 2707-2727; https://doi.org/10.3390/w7062707 - 5 Jun 2015
Cited by 15 | Viewed by 7275
Abstract
The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP) representative catchment, in South Korea. [...] Read more.
The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP) representative catchment, in South Korea. A three-layer MLP model, using three training algorithms, was used to estimate areal rainfall. The Levenberg–Marquardt training algorithm was found to be more sensitive to the number of hidden nodes than were the conjugate gradient and quickprop training algorithms using the MLP model. Results showed that the networks structures of 11-5-1 (conjugate gradient and quickprop) and 11-3-1 (Levenberg-Marquardt) were the best for estimating areal rainfall using the MLP model. The networks structures of 1-5-11 (conjugate gradient and quickprop) and 1-3-11 (Levenberg–Marquardt), which are the inverse networks for estimating areal rainfall using the best MLP model, were identified for spatial disaggregation of areal rainfall using the MLP model. The KSOFM model was compared with the MLP model for spatial disaggregation of areal rainfall. The MLP and KSOFM models could disaggregate areal rainfall into individual point rainfall with spatial concepts. Full article
(This article belongs to the Special Issue Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling)
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<p>Schematic diagram of the Wi-stream catchment.</p> Full article ">Figure 2
<p>Influence of the number of hidden nodes for three training algorithms (test period). (<b>a</b>) NS; (<b>b</b>) MAF; (<b>c</b>) RMSE; (<b>d</b>) APE.</p> Full article ">Figure 2 Cont.
<p>Influence of the number of hidden nodes for three training algorithms (test period). (<b>a</b>) NS; (<b>b</b>) MAF; (<b>c</b>) RMSE; (<b>d</b>) APE.</p> Full article ">Figure 3
<p>Structure of MLP (11-5-1) developed for estimating areal rainfall.</p> Full article ">Figure 4
<p>Structure of MLP (1-5-11) developed for spatial disaggregation of areal rainfall.</p> Full article ">Figure 5
<p>Influence of individual rainfall stations for three training algorithms of MLP (test period). (<b>a</b>) NS; (<b>b</b>) MAF; (<b>c</b>) RMSE; (<b>d</b>) APE.</p> Full article ">Figure 6
<p>Structure of KSOFM (1-[5 X 5]-5-11) developed for spatial disaggregation of areal rainfall.</p> Full article ">Figure 7
<p>Influence of individual rainfall stations for three training algorithms of KSOFM1 (test period). (<b>a</b>) NS; (<b>b</b>) MAF; (<b>c</b>) RMSE; (<b>d</b>) APE.</p> Full article ">Figure 8
<p>Influence of individual rainfall stations for three training algorithms of KSOFM2 (test period). (<b>a</b>) NS; (<b>b</b>) MAF; (<b>c</b>) RMSE; (<b>d</b>) APE.</p> Full article ">Figure 8 Cont.
<p>Influence of individual rainfall stations for three training algorithms of KSOFM2 (test period). (<b>a</b>) NS; (<b>b</b>) MAF; (<b>c</b>) RMSE; (<b>d</b>) APE.</p> Full article ">Figure 9
<p>Rainfall box plots for Euiheung (No.8) station (test period). (<b>a</b>) Conjugate gradient; (<b>b</b>) Levenberg–Marquardt; (<b>c</b>) Quickprop.</p> Full article ">Figure 9 Cont.
<p>Rainfall box plots for Euiheung (No.8) station (test period). (<b>a</b>) Conjugate gradient; (<b>b</b>) Levenberg–Marquardt; (<b>c</b>) Quickprop.</p> Full article ">Figure 10
<p>Rainfall box plots for Hwasu (No.9) station (test period). (<b>a</b>) Conjugate gradient; (<b>b</b>) Levenberg–Marquardt; (<b>c</b>) Quickprop.</p> Full article ">Figure 10 Cont.
<p>Rainfall box plots for Hwasu (No.9) station (test period). (<b>a</b>) Conjugate gradient; (<b>b</b>) Levenberg–Marquardt; (<b>c</b>) Quickprop.</p> Full article ">
486 KiB  
Article
Subgrid Parameterization of the Soil Moisture Storage Capacity for a Distributed Rainfall-Runoff Model
by Weijian Guo, Chuanhai Wang, Xianmin Zeng, Tengfei Ma and Hai Yang
Water 2015, 7(6), 2691-2706; https://doi.org/10.3390/w7062691 - 29 May 2015
Cited by 8 | Viewed by 5852
Abstract
Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this [...] Read more.
Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM) resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin. Full article
(This article belongs to the Special Issue Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling)
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<p>Location and gauging stations of the study area.</p> Full article ">Figure 2
<p>Schematic representation of runoff generation within a grid.</p> Full article ">Figure 3
<p>An illustration of the model performance of the Grid-Xinanjiang model with the subgrid parameterization in the Yanduhe Basin in 1986. Red dot, observed discharge; black line, simulated discharge; blue bar, precipitation.</p> Full article ">Figure 4
<p>Effect of the grid resolution on the density function of the soil storage capacity.</p> Full article ">Figure 5
<p>The monthly precipitation, evapotranspiration, runoff and relative soil moisture processes.</p> Full article ">Figure 6
<p>Model performances with and without subgrid parameterization. The solid line represents the <span class="html-italic">NSC</span> from the Grid-Xinanjiang model with uniform grid, and the dash-dot line represents the <span class="html-italic">NSC</span> after incorporating the subgrid variability.</p> Full article ">Figure 7
<p>Discharge from the original Grid-Xinanjiang model (<span class="html-italic">Q<sub>uni</sub></span>) versus runoff after incorporating the subgrid variability (<span class="html-italic">Q<sub>non-uni</sub></span>).</p> Full article ">
2670 KiB  
Article
Tracing the Sources and Processes of Groundwater in an Alpine Glacierized Region in Southwest China: Evidence from Environmental Isotopes
by Yuchuan Meng, Guodong Liu and Mingxi Li
Water 2015, 7(6), 2673-2690; https://doi.org/10.3390/w7062673 - 29 May 2015
Cited by 22 | Viewed by 4919
Abstract
The melting of alpine snow and glaciers is an important hydrologic process on Mount Gongga, China. The relevance of ice-snow melt to the groundwater recharge in the glacierized Hailuogou watershed is so far not well known. To better understand the origin of groundwater [...] Read more.
The melting of alpine snow and glaciers is an important hydrologic process on Mount Gongga, China. The relevance of ice-snow melt to the groundwater recharge in the glacierized Hailuogou watershed is so far not well known. To better understand the origin of groundwater and the hydrological interactions between groundwater, meltwater, and precipitation in this region, 148 environmental isotopic data of water samples were analyzed for changes in isotopic composition. The results indicate that the groundwater contains a uniform isotopic signature, with δ18O values between −13.5‰ and −11.1‰ and δ2H values between −90‰ and −75‰. The mean stable isotopic composition of groundwater is heavier than that of ice-snow meltwater but lighter than that of precipitation. The effect of evaporation on the isotopic variation of groundwater is very limited and the seasonal isotope variations in precipitation are attenuated in groundwater. A model based on the δ18O results suggests that approximately 35% of the groundwater is derived from ice-snow meltwater sources. The study demonstrates that ice-snow meltwater is a substantial source of shallow groundwater in the alpine regions on the edge of the Tibetan Plateau. Full article
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<p>Map of the study region, with the meteorological station (3000 m a.s.l.) and hydrological station (2920 m a.s.l.).</p> Full article ">Figure 2
<p>Seasonal variation of groundwater depth (m), temperature (°C), precipitation (mm), and river runoff (m<sup>3</sup>/s) at the HLG hydrological station: (<b>a</b>) the mean monthly temperature from 1988 to 2009; (<b>b</b>) the mean monthly precipitation from 1988 to 2009; (<b>c</b>) the groundwater depth during the observation period; and (<b>d</b>) the mean monthly discharge of the HLG River from 1994 to 2009.</p> Full article ">Figure 2 Cont.
<p>Seasonal variation of groundwater depth (m), temperature (°C), precipitation (mm), and river runoff (m<sup>3</sup>/s) at the HLG hydrological station: (<b>a</b>) the mean monthly temperature from 1988 to 2009; (<b>b</b>) the mean monthly precipitation from 1988 to 2009; (<b>c</b>) the groundwater depth during the observation period; and (<b>d</b>) the mean monthly discharge of the HLG River from 1994 to 2009.</p> Full article ">Figure 3
<p>Temporal changes in δ<sup>18</sup>O (<b>a</b>); δ<sup>2</sup>H (<b>b</b>); and d-excess (<b>c</b>) of water samples in the study area.</p> Full article ">Figure 3 Cont.
<p>Temporal changes in δ<sup>18</sup>O (<b>a</b>); δ<sup>2</sup>H (<b>b</b>); and d-excess (<b>c</b>) of water samples in the study area.</p> Full article ">Figure 4
<p>Correlation between δ<sup>2</sup>H and δ<sup>18</sup>O values for water collected from May 2008 to December 2009. The LMWL is shown as a solid line. The GMWL (dashed line) is shown for reference.</p> Full article ">Figure 5
<p>Relationships of δ<sup>2</sup>H and δ<sup>18</sup>O in precipitation, groundwater, and ice-snow meltwater: (<b>a</b>) annual mean value; (<b>b</b>) mean value in wet season; and (<b>c</b>) mean value in dry season.</p> Full article ">Figure 6
<p>Calculated fractions of ice-snow meltwater and precipitation contributing to groundwater at sampling site I and site III: (<b>a</b>) site I, on the basis of δ<sup>18</sup>O; (<b>b</b>) site I, on the basis of δ<sup>2</sup>H; (<b>c</b>) site III, on the basis of δ<sup>18</sup>O; (<b>d</b>) site III, on the basis of δ<sup>2</sup>H.</p> Full article ">
69116 KiB  
Article
Areal Distribution of Ammonium Contamination of Soil-Water Environment in the Vicinity of Old Municipal Landfill Site with Vertical Barrier
by Eugeniusz Koda, Piotr Osinski, Anna Sieczka and Dorota Wychowaniak
Water 2015, 7(6), 2656-2672; https://doi.org/10.3390/w7062656 - 29 May 2015
Cited by 38 | Viewed by 7207
Abstract
The content of the paper is focused on determining the influence of an old municipal landfill site on the pollution of soil and groundwater by ammonium. The assessment of the influence was conducted on piezometric recording basis, laboratory tests and site investigation, which [...] Read more.
The content of the paper is focused on determining the influence of an old municipal landfill site on the pollution of soil and groundwater by ammonium. The assessment of the influence was conducted on piezometric recording basis, laboratory tests and site investigation, which gave information on contamination level and direction of pollutants migration. Based on the groundwater monitoring results, several maps of groundwater level changes were created. Moreover, mapping of ammonium distribution and migration paths within Lubna Landfill surroundings was also provided. The monitoring data show improvement of water quality in almost every piezometer after only a few years from when groundwater protection system was installed at the site. It indicates that reduction of ammonium within the vicinity of the landfill is continuously progressing in time. On the basis of the results obtained, the magnitude of variability in pollutant migration and changes in concentration, as well as efficiency of the vertical barrier were assessed. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Pattern of contamination zones migration within landfill’s subsoil.</p> Full article ">Figure 2
<p>Potential nitrogen transformation pathways/nitrogen cycle that may occur in landfill environment.</p> Full article ">Figure 3
<p>Groundwater monitoring for Lubna Landfill, with geological cross-section.</p> Full article ">Figure 4
<p>Geological cross-section of Lubna Landfill subsoil.</p> Full article ">Figure 5
<p>The groundwater depth contour map for Lubna Landfill surroundings (2014).</p> Full article ">Figure 6
<p>Experimental set-up to determine ammonium in groundwater samples.</p> Full article ">Figure 7
<p>Changes of NH<sub>4</sub><sup>+</sup> concentration on Lubna Landfill in piezometers 5A and 9A.</p> Full article ">Figure 8
<p>Distribution map of ammonium contamination within Lubna Landfill surroundings (1996), before vertical barrier construction.</p> Full article ">Figure 9
<p>Distribution map of ammonium contamination within Lubna Landfill surroundings (2003), five years after vertical barrier construction.</p> Full article ">Figure 10
<p>Distribution map of ammonium nitrogen contamination within Lubna Landfill surroundings (2014), 15 years after vertical barrier construction.</p> Full article ">
468 KiB  
Article
Water Institutions and Management in Cape Verde
by Miguel Suarez Bosa
Water 2015, 7(6), 2641-2655; https://doi.org/10.3390/w7062641 - 29 May 2015
Cited by 3 | Viewed by 6721
Abstract
The water-management model used in Cape Verde for irrigation water is a singular one involving both public and private institutions. The institutional framework adopted since independence (1975) includes influences of both Portuguese colonial occupation and African culture. Water is a common-pool resource, [...] Read more.
The water-management model used in Cape Verde for irrigation water is a singular one involving both public and private institutions. The institutional framework adopted since independence (1975) includes influences of both Portuguese colonial occupation and African culture. Water is a common-pool resource, which can take the form of communal, private or state property, or not be subject to any form of ownership. Thus, this case study enables us to compare theories about managing. From a neo-liberal point of view, the common administration of resources of this kind is inefficient, but for one school of the institutional theory, solutions can come “from within”; in other words, from user groups themselves, who can co-operate, once they have defined commitments. Research based on surveys and interviews with private sector administrators leads to the conclusion that user association management is successful, whereas, individual management can lead to squandering. Full article
(This article belongs to the Special Issue Study, Development and Management of Water in Volcanic Areas)
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<p>Situation of the Cape Verde Archipelago. Source: Adapted from Wikimedia Commons [<a href="#B19-water-07-02641" class="html-bibr">19</a>].</p> Full article ">Figure 2
<p>Institutionalization of water administration in Cape Verde. Source: Adapted from Borges [<a href="#B24-water-07-02641" class="html-bibr">24</a>]. Made on the premises.</p> Full article ">Figure 3
<p>Kind of calendar used for water distribution in Cape Verde. Source: Information provided by Paulina Costa Fortes and Manuel Baptista, Representative and Engineer from MRD/IHGRH, respectively in Porto Novo (Santo Antäo) and the interview occurred in Porto Novo on 4 December 2013.</p> Full article ">
3310 KiB  
Article
Evaluating the Effects of Mulch and Irrigation Amount on Soil Water Distribution and Root Zone Water Balance Using HYDRUS-2D
by Ming Han, Chengyi Zhao, Gary Feng, Yingyu Yan and Yu Sheng
Water 2015, 7(6), 2622-2640; https://doi.org/10.3390/w7062622 - 29 May 2015
Cited by 57 | Viewed by 10015
Abstract
Water scarcity is the most critical constraint for sustainable cotton production in Xinjiang Province, northwest China. Drip irrigation under mulch is a major water-saving irrigation method that has been widely practiced for cotton production in Xinjiang. The performance of such an irrigation system [...] Read more.
Water scarcity is the most critical constraint for sustainable cotton production in Xinjiang Province, northwest China. Drip irrigation under mulch is a major water-saving irrigation method that has been widely practiced for cotton production in Xinjiang. The performance of such an irrigation system should be evaluated for proper design and management. Therefore, a field experiment and a simulation study were conducted to (1) determine a modeling approach that can be applied to manage drip irrigation under mulch for cotton production in this region; and (2) examine the effects of irrigation amount and mulch on soil water distribution and root zone water balance components. In the experiment, four irrigation treatments were used: T1, 166.5 m3; T2, 140.4 m3; T3, 115.4 m3; and T4: 102.3 m3. The HYDRUS-2D model was calibrated, validated, and applied with the data obtained in this experiment. Soil water balance in the 0–70 cm soil profile was simulated. Results indicate that the observed soil water content and the simulated results obtained with HYDRUS-2D are in good agreement. The radius of the wetting pattern, root water uptake, and evaporation decreased as the amount of irrigation was reduced from T1 to T4, while a lot of stored soil water in the root zone was utilized and a huge amount of water was recharged from the layer below 70 cm to compensate for the decrease in irrigation amount. Mulch significantly reduced evaporation by 11.7 mm and increased root water uptake by 11.2 mm. Our simulation study suggests that this model can be applied to provide assistance in designing drip irrigation systems and developing irrigation strategies. Full article
(This article belongs to the Special Issue Sustainable Water Management and Decision Making under limited Data Availability)
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<p>Experiment region (<b>A</b>) and the domain geometry of the simulated region and the positions where soil water content was measured (<b>B</b>).</p> Full article ">Figure 2
<p>Positions of different boundary conditions.</p> Full article ">Figure 3
<p>(<b>A</b>) Reference evapotranspiration (<span class="html-italic">ET</span><sub>0</sub>) and cotton potential evapotranspiration (<span class="html-italic">ET</span><sub>c</sub>); (<b>B</b>) Crop coefficient (<span class="html-italic">K<sub>c</sub></span>), basal coefficient (<span class="html-italic">K</span><sub>cb</sub>), and evaporation coefficient (<span class="html-italic">K</span><sub>e</sub>) of the FAO-56 dual crop coefficient method.</p> Full article ">Figure 4
<p>Root water uptake distribution function, <span class="html-italic">i.e.</span>, <span class="html-italic">b</span>(<span class="html-italic">x</span>, <span class="html-italic">z</span>) of Equation (8).</p> Full article ">Figure 5
<p>Comparison of the simulated and observed soil water contents of the four treatments.</p> Full article ">Figure 6
<p>Simulated soil water contents (lines) and measurements (dots) at various depths in different observation locations for T2. The three columns of the plots represent the horizontal location: the left column of the plots for the observation point under drip line (<span class="html-italic">x</span> = 4.03 cm), the middle column of the plots for the observation point under mulch (<span class="html-italic">x</span> = 36.25 cm), and the right column of the plots for the observation point under exposed soil (<span class="html-italic">x</span> = 68.47 cm). The five rows represent the following depths from the soil surface: 10, 30, 50, 70, and 90 cm.</p> Full article ">Figure 7
<p>Simulated soil water contents of each treatment in 2D on 2 August 2007.</p> Full article ">Figure 8
<p>Average soil water contents simulated during the growing season under the two scenarios (<span class="html-italic">i.e.</span>, with/without mulch cover).</p> Full article ">
747 KiB  
Article
Improving Water Use in Fodder Production
by Vanessa Mendoza-Grimón, José Manuel Hernández-Moreno and María Del Pino Palacios-Díaz
Water 2015, 7(6), 2612-2621; https://doi.org/10.3390/w7062612 - 27 May 2015
Cited by 6 | Viewed by 5585
Abstract
Water deficit in semi-arid regions limits the future of the livestock sector. Also, its high price represents a percentage of the total cost of forage production. Non-conventional water resources applied by subsurface drip irrigation (SDI), in which the safe use lies in the [...] Read more.
Water deficit in semi-arid regions limits the future of the livestock sector. Also, its high price represents a percentage of the total cost of forage production. Non-conventional water resources applied by subsurface drip irrigation (SDI), in which the safe use lies in the management and not on the level of water treatment, would enhance the ruminant production sustainability. To obtain the optimal benefit, the transformation of water per kilogram of dry matter produced must have a high grade of effectiveness. Under this premise, a maralfalfa crop (Penissetum sp, hybridum) has been established with an SDI system and reclaimed water. Forage yield is analyzed with respect to a 40% irrigation reduction. This study shows that, with the use of these good irrigation management practices, it is possible to harvest an annual production of 90 to 72 t·ha−1 in the warmer regions of the Canary Islands. This implies water consumption between 13,200 and 8100 m3·ha−1. A water consumption of 21,000 m3·ha−1 per year for the same production, at a ratio of 230 L·t−1, can be estimated for the rest of the Canary Islands coastal regions. The use of the water management described in this paper can be profitable in the Canary Islands for fodder production. Full article
(This article belongs to the Special Issue Study, Development and Management of Water in Volcanic Areas)
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<p>Meteorological data during the experimental period: daily radiation (daily rad) expressed in MJ·m<sup>−2</sup>·day<sup>−1</sup>, mean temperature, expressed in day °C (Tmed) and monthly radiation (monthly rad) in MJ·m<sup>−2</sup>·month<sup>−1</sup>.</p> Full article ">Figure 2
<p>Nitrogen leaf content, expressed in %, for both treatments (trat 1: 100% and trat 2: 60% of the dose) for three harvests (represented by the date of cutting).</p> Full article ">Figure 3
<p>(<b>a</b>) Yield (kg·DM·m<sup>−2</sup>) and (<b>b</b>) water consumption per dry matter produced, water consumption coefficient (L·kg<sup>−1</sup> DM) for both treatments (trat 1: 100% and trat 2: 60% of the dose) and∙harvests.</p> Full article ">Figure 4
<p>(<b>a</b>) Yield (kg·m<sup>−2</sup> DM) and water consumption coefficient (L·kg<sup>−1</sup> MS) for both treatments (100% and 60% of the dose) and∙harvest; and (<b>b</b>) relationship between water use efficiency (WUE, in g·L<sup>−1</sup>) and crop yield (kg·m<sup>−2</sup> DM) obtained for the∙harvests and treatments (1 and 2).</p> Full article ">
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