Search

Research on water cooperation in the Eastern Nile Basin has focused on expanding policy and diplomacy tools for a better allocation of transboundary water resources confined to the river. Regional cooperation on water and related sectors such as energy and land expands the bargaining and areas for mutual gain, and thus enhances cooperation perspectives. This paper looks at the contribution and the potential benefits of a regional cooperation approach to addressing the underlying challenges of water diplomacy, such as complexity and distrust. It also promotes the understanding of river basins as a “resource basin” of integrated and linked resource-use issues, not always related to the river flow. The paper provides an analysis of priority issues for water–energy–food nexus in regional cooperation in the Eastern Nile Basin. This basin represents an illustrative case for regional cooperation and increased integration due to multiple comparative advantages inherent in the uneven endowments of water, energy and arable land resources, and to varying levels of economic and technological advancement among the three riparian countries: Egypt, Sudan and Ethiopia. The paper also analyzes institutional arrangements on a regional scale, and elaborates on the inherent trade-offs associated with them. [ABSTRACT FROM AUTHOR]

Abstract The estuarine delta of the Yellow River is a region of strong land-ocean-human interactions that undergoes a unique evolutionary process. In this paper, we combined historical data and remote sensing images to better understand the evolution of the Yellow River delta. Changes in the Yellow River estuarine flow path from natural swing to artificial diversion were first studied to understand the rules and mechanism of the delta formation. The complex geomorphic structural system of the Yellow River delta is constituted by contemporary and modern deltas and their sub-deltas. Remote sensing images and measured data indicate that variations in runoff and sediment load in the Yellow River estuary will affect the deltaic erosion and siltation. The natural and artificial factors that cause runoff and sediment changes include climate change, soil erosion control in the middle reaches, building reservoirs along the Yellow River, which are used as water supply for local cities and farmland irrigation, as well as the water and sediment regulation experiment in the Xiaolangdi reservoir. Furthermore, artificial intervention of diversion channels has contributed to the maintained stability of the Yellow River estuary environment, so as to have regional development and prosperity of the Yellow River delta. Graphical abstract Image 1 Highlights • The Yellow River estuarine flow paths change from natural swing to artificial diversion, and the delta formation rule. • The variation of runoff and sediment load in the Yellow River affect the deltaic erosion and siltation. • Probe into the natural and artificial reasons of runoff and sediment changes and decrease. • The estuarine artificial control maintains relative stableenvironment and creates prosperity of the Yellow River delta. • This study reflects land-ocean-human interaction on estuarine coastal region. [ABSTRACT FROM AUTHOR]

• BMA improved estimation of prediction uncertainty for daily streamflow simulations. • Applying BMA provided a better understanding of SWAT-HS reliability and precision. • BMA models had similar estimations for model reliability, but different for precision. • BMA showed that MNSE had the highest predictive ability in simulating streamflow. In this paper, multiple objective functions were used to conduct uncertainty analysis on calibrated streamflow simulations of SWAT-hillslope model (SWAT-HS), which is a semi-distributed model suited for humid, mountainous regions. SWAT-HS was set up for six watersheds of NYC water supply system and streamflow was simulated at a daily time step. Each SWAT-HS model setup was then passed through a calibration process for parameter optimization. This process involved constraining the model using several alternative objective functions which produce statistically acceptable streamflow simulations, which served as an ensemble of predictions for uncertainty analysis. We hypothesize that the uncertainty introduced by selecting a single objective function can be large with each objective function being sensitive to a specific hydrologic signature. Using multiple objective functions result in a wider range in optimum parameter values and an ensemble of simulations based on different objective functions can capture the overall prediction uncertainty through differences in parameter estimates. The Bayesian Model Averaging (BMA) method was then applied to ensemble predictions to quantify overall prediction uncertainty. The uncertainty analysis showed the similarity of uncertainty interval characteristics for all BMA based predictions across all watersheds. More than 94–97% of the observations were covered by uncertainty intervals estimated using multiple objective functions when compared to 73–79% of the observations when using a single objective function. No significant differences were observed among the six watersheds, and the results of their uncertainty analysis were similar. We propose the use of multiple objective functions as an option in ensemble modeling of streamflow and uncertainty analysis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Wildfires are becoming more severe and frequent and their effects increasingly expose water resources to stress. • Climate, wildfire, streamflow records (1975 to 2018), topography, and landcover data from 92 catchments were combined to quantify the contribution of wildfire to streamflow variability across Australian temperate forests. • On average wildfire regimes relatively results in 8.8% increases in streamflow across Australian temperate forests. • Wildfire effects on regional streamflow varied spatially depending on hydroclimate factors, particularly precipitation. As wildfires become more frequent and severe, there are concerns regarding their impacts on water yield from forested catchments. While there are many studies in Australia about the effects of individual wildfires on streamflow at fine scales (<1 km2) in specific geographic settings, the effects of wildfire regimes on streamflow at broad spatial scales across temperate forests in Australia are not well understood. In this paper, we combined climate, wildfire, streamflow records (1975 to 2018), topographic, and landcover data from 92 catchments (74 – 4740 km2) in the Australian temperate zone to quantify the contribution of wildfire regimes over time to streamflow variability in different hydroclimatic settings (humid, dry sub-humid, and semi-arid) and geographic regions (Southeast Australia (SEA), Southwest Western Australia (SWWA), and Tasmania (TAS)). Wildfire regimes were represented by two metrics: the burnt area to drainage area (BDA) ratio for wildfire events in each year and a spatially averaged metric of Time Since Fire (TSF), which is a spatial average of time since the last wildfire in the catchment. By comparing prefire and postfire runoff ratios our study found that on average there was a short-term increase in runoff ratio (∼3% in year 1 and ∼6% in year 2 post-fire) after wildfires with BDA > 25%. No influence of fire was found in the long-term (15–20 years after the wildfire) runoff ratio. We found that wildfire regime, measured by TSF, explained ∼8.8% of the variation in annual streamflow across the Australian temperate zone, and that with decreasing TSF (i.e., increased wildfire impact), the average streamflow increased. Streamflow variation explained by wildfire regimes varied with hydroclimate. The explained variance of streamflow by wildfire regimes in semi-arid catchments (23%) and dry sub-humid catchments (13%) were higher than humid catchments (5%). Our results provide a broad-scale understanding of how wildfire regimes influence streamflow variability at broad temporal and spatial scales, and provided important context and baseline information for determining the implications of changes in climate and fire regimes for regional water availability. [ABSTRACT FROM AUTHOR]

Summary In recent years, the Poyang Lake basin is in a prolonged drought which has placed immense pressure on the water resources utilization. In this paper, we explore the spatial and temporal distributions of extreme droughts in the Poyang Lake basin by using the methods of SPI (Standardized Precipitation Index) and EOF (Empirical Orthogonal Function) for the period of 1956–2009, which are influenced by regional precipitation anomalies and river–lake interaction due to water impounding of the Three Gorges Dam (TGD). The results show that: (1) the Poyang Lake basin experienced six extreme droughts during the past 60 years, which lead to decreases in streamflow from five tributary rivers down to the Poyang Lake. The droughts in the 1960s and the 2000s were the most serious ones. However, there was an increasing trend of streamflow in the upper and middle Yangtze in the 1960s, and a decreasing trend appeared in the 2000s. The decline of streamflow in the upper Yangtze reaches has lowered the water level of lower Yangtze River which has caused more outflow from the Poyang Lake to the Yangtze River; (2) the operation of the Three Gorges Dam (TGD) has altered the seasonal pattern of flow regimes in the Poyang Lake and significantly reduced the water level in the lower Yangtze River during the TGD impounding period from late September to early November; and (3) the conjunction of extreme droughts in the Poyang Lake and the upper Yangtze reaches coincided with the impounding of the TGD is the main cause of the low water level in the Poyang Lake. Although the impact of the recent droughts in the Poyang Lake and upper Yangtze reaches has played a crucial role in the low water level of Poyang Lake, more attention should be paid to its sensitivity to the influence of the large dam-induced changes in the interaction between river and lake, particularly during impounding periods. [ABSTRACT FROM AUTHOR]

[Display omitted] • Landscape's hydric potential (LHP) could be used as indicator in water management. • LHP method refers to runoff reduction in ecosystems. • The LHP values are reflected in land cover changes. • Trends of flow discharges in rivers could be explained by LHP changes. This paper presents an approach for mitigating water-related problems, that relates the retention of precipitation and use of ecosystems, as a tool for improving the quality, quantity and availability of water resources throughout the region. One approach is the determination of the landscape's hydric potential (LHP). Land cover changes can influence ecosystems in different ways depending on crucial factors that depend on water resources. Thus-far, many studies describe the influence of land cover changes on individual features of catchments and hydrological regime, but few have made an attempt to analysis how changes in land cover can holistically influence processes in catchments. In this context the innovative aspect of this work presents the consequence of land cover changes on water retention expressed by LHP — a general descriptor that is linked with many composite influence factors on water retention. A study was carried out on 33 catchments located in central Europe. Results show increased forest cover having a positive trend in the context of LHP. Conversely, increased urban and industrial areas negatively impact LHP. The presented analysis reveals that a few land cover changes had direct and clearly positive effects on LHP. The LHP had decreased in 21 catchments and increased in 12 catchments. Decreased LHP was generally observed in catchments located on the left side of the Vistula basin where there are more advantageous conditions for agriculture, rising industry and urban areas. The study showed that during the analyzed period, obtained changes of LHP values did not strongly affect hydrological regimes in studied catchments. Our results show that LHP is a very good and useful descriptor that includes many characteristics of catchment and could be used for river catchment management purposes. The landscape's hydric potential can be used in any catchment in the world. [ABSTRACT FROM AUTHOR]

Summary: The Melen Watershed is located in Western Black Sea region of Turkey. Buyuk Melen and Kucuk Melen Rivers are located in this watershed. By 2010 more than 50% of Istanbul’s water demand is supplied from the Buyuk Melen River. This paper presents a new approach using an artificial neural network (ANN) technique to improve precipitation forecast performance. Missing value predictions and the future precipitation value estimations were researched throughout this study. A case study was performed in Bolu and Duzce provinces of Turkey that are located in Black Sea Region. The most crucial objective of this study was to estimate missing values and to generate quantitative forecasts for future precipitation data of Duzce. Monthly average daily precipitation data of Bolu and limited number of Duzce precipitation data were used for this purpose. Ultimately, monthly river flow rate from the Melen Watershed of Turkey was modeled and forecasted through the SWAT Model using the generated precipitation data and other required spatial and temporal data. Results show that there is a considerable relation between the simulated model and observed results. This study also shows that water supply for Istanbul can be managed based on precipitation forecast. [ABSTRACT FROM AUTHOR]

Summary: Forested riparian zones perform numerous ecosystem functions, including the following: storing and fixing carbon; serving as wildlife habitats and ecological corridors; stabilizing streambanks; providing shade, organic matter, and food for streams and their biota; retaining sediments and filtering chemicals applied on cultivated/agricultural sites on upslope regions of the catchments. In this paper, we report a synthesis of a different feature of this type of vegetation, which is its effect on water yield. By synthesizing results from studies that used (i) the nested catchment and (ii) the paired catchment approaches, we show that riparian forests decrease water yield on a daily to annual basis. In terms of the treated area increases on average were 1.32±0.85mmday−1 and 483±309mmyr−1, respectively; n =9. Similarly, riparian forest plantation or regeneration promoted reduced water yield (on average 1.25±0.34mmday−1 and 456±125mmyr−1 on daily and annual basis, respectively, when prorated to the catchment area subjected to treatment; n =5). Although there are substantially fewer paired catchment studies assessing the effect of this vegetation type compared to classical paired catchment studies that manipulate the entire vegetation of small catchments, our results indicate the same trend. Despite the occurrence of many current restoration programs, measurements of the effect on water yield under natural forest restoration conditions are still lacking. We hope that presenting these gaps will encourage the scientific community to enhance the number of observations in these situations as well as produce more data from tropical regions. [ABSTRACT FROM AUTHOR]

Abstract: Phase 2 of the Distributed Model Intercomparison Project (DMIP 2) was formulated primarily as a mechanism to help guide the US National Weather Service (NWS) as it expands its use of spatially distributed watershed models for operational river, flash flood, and water resources forecasting. The overall purpose of DMIP 2 was to test many distributed models with operational quality data with a view towards meeting NWS operational forecasting needs. At the same time, DMIP 2 was formulated as an experiment that could be leveraged by the broader scientific community as a platform for testing, evaluating, and improving the science of spatially distributed models. This paper presents the key results of the DMIP 2 experiments conducted for the Oklahoma region, which included comparison of lumped and distributed model simulations generated with uncalibrated and calibrated parameters, water balance tests, routing and soil moisture tests, and simulations at interior locations. Simulations from 14 independent groups and 16 models are analyzed. As in DMIP 1, the participant simulations were evaluated against observed hourly streamflow data and compared with simulations generated by the NWS operational lumped model. A wide range of statistical measures are used to evaluate model performance on both run-period and event basis. A noteworthy improvement in DMIP 2 was the combined use of two lumped models to form the benchmark for event improvement statistics, where improvement was measured in terms of runoff volume, peak flow, and peak timing for between 20 and 40 events in each basin. Results indicate that in general, those spatially distributed models that are calibrated to perform well for basin outlet simulations also, in general, perform well at interior points whose drainage areas cover a wide range of scales. Two of the models were able to provide reasonable estimates of soil moisture versus depth over a wide geographic domain and through a period containing two severe droughts. In several parent and interior basins, a few uncalibrated spatially distributed models were able to achieve better goodness-of-fit statistics than other calibrated distributed models, highlighting the strength of those model structures combined with their a priori parameters. In general, calibration solely at basin outlets alone was not able to greatly improve relative model performance beyond that established by using uncalibrated a priori parameters. Further, results from the experiment for returning DMIP 1 participants reinforce the need for stationary data for model calibration: in some cases, the improvements gained by distributed models compared to lumped were not realized when the models were calibrated using inconsistent precipitation data from DMIP 1. Event-average improvement of distributed models over the combined lumped benchmark was measured in terms of runoff volume, peak flow, and peak timing for between 20 and 40 events. The percentage of model-basin pairs having positive distributed model improvement at basin outlets and interior points was 18%, 24%, and 28% respectively, for these quantities. These values correspond to 14%, 33%, and 22% respectively, in DMIP 1. While there may not seem to be much gain compared to DMIP 1 results, the DMIP 2 values were based on more precipitation–runoff events, more model-basin combinations (148 versus 51), more interior ungauged points (9 versus 3), and a benchmark comprised of two lumped model simulations. In addition, we propose a set of statistical measures that can be used to guide the calibration of distributed and lumped models for operational forecasting. [Copyright &y& Elsevier]

Summary: Streamflow prediction has a great significance in hydrology, water resources planning and management studies. Either long term or short term predictions of streamflow are necessary to optimise the operation of water resources systems. An Artificial Neural Network (ANN) is a nonlinear black-box modelling approach which has the capability to model complex nonlinear hydrological processes without physical expression. It is an alternative modelling approach that is inspired by brain and nervous systems to conventional hydrological models. This paper describes implementation of an ANN to predict catchment flows in a snow dominated mountainous basin named Karasu Basin, which is in the headwater of the Euphrates Basin in Turkey. Due to the non-availability of accurate snow data, catchment flows were predicted using only basic meteorological data, and a best meteorological data set was investigated to achieve best performance of the model. The ANN model was calibrated with recorded runoff data available for a period of 12years. Calibrated model was further used for a period of another 10years. To achieve model accuracy, the model was simulated with both the whole-year (annual) data and part-year (seasonal) data. It was found that model accuracy increased significantly when it was used for part-year (seasonal) data. The model results are encouraging and model accuracy can be further increased when the simulations include snow depth data and/or snow water equivalent data. [Copyright &y& Elsevier]

Abstract: Long monthly streamflow series of three control hydrological stations of the Pearl River basin were analyzed by using the scanning t-test and the scanning F-test. Possible implications of the changing properties of streamflow variations for the water resource management of the Pearl River Delta are also discussed. The results indicated that: 1) more complicated changes were observed in terms of the second center moment when compared to the first original moment. More significant abrupt changes of the second center moment imply more sensitive response of streamflow stability to climate changes and human activities; 2) abrupt behaviors of the first (second) center moment of the streamflow variations tend to be more sensitive to climate changes and/or human activities in the larger river basin when compared to those in the smaller river basin. These phenomena are attributed to buffering functions of more storage space of longer river channel, and more complicated and longer runoff yield and concentration processes in the river basin of larger drainage area; 3) annual minimum streamflow of the Pearl River basin tends to be increasing. This will be helpful for better human mitigation of the salinity intrusion in dry seasons across the Pearl River Delta. Annual maximum streamflow, when compared to annual minimum streamflow, shows larger-magnitude variability reflected by larger standard deviation, implying unfavorable conditions for flood mitigation in the Pearl River Delta. The results of this paper are of scientific and practical merits for water resource management and sound human mitigation to water hazards across the Pearl River Delta, and also are a good case study for similar researches in other river deltas in the world under the changing environment. [ABSTRACT FROM AUTHOR]

Summary: Miyun Reservoir is the main raw water source for Beijing’s domestic water supply. Flow discharge to Miyun Reservoir decreased drastically over a 50-year period, from 1956 to 2005, and had seriously affected Beijing’s water supply. Climate variability and human activity had been identified as the two main reasons for the decrease in flow. Here, climate variability refers to changes in precipitation and temperature. Impact of human activity includes direct withdrawal of water (referred to as “direct abstraction” in this paper) from the river (primary) or groundwater and indirect impact due to man-made changes in land use and vegetation in the upstream of the reservoir. According to the historical record, “direct abstraction” from the upstream of the reservoir has increased significantly since 1984. The study period was split into two sub-periods, from 1956 to 1983 and from 1984 to 2005. Based on the historical record, annual runoff in the upstream catchment of Miyun Reservoir (i.e., inflow into the reservoir) had decreased from 90.3mm to 41.8mm for the two sub-periods, a decrease of 48.5mm. Over the same period, average annual “direct abstraction” increased from 2.2mm to 13.4mm, an increase of 11.2mm. The latter accounted for 23% (11.2mm/48.5mm) of the decrease in inflow into the reservoir. This study utilised: (1) a distributed hydrological model (geomorphology-based hydrological model, or GBHM) and (2) a climate elasticity model to conduct a quantitative assessment of the impact of climate variability and the indirect impact of human activity on the inflow into the reservoir. Simulation results of GBHM and the climate elasticity model showed that climate impact was accountable for about 55% and 51% of the decrease in reservoir inflow, respectively. The indirect impact of human activity (mainly man-made land use and vegetation changes) accounted for 18% of the decrease in reservoir inflow. [Copyright &y& Elsevier]

Summary: In recent years, climate change impacts on water resources sectors have been extensively documented. Anticipated changes range from more severe storms to more frequent floods and drought at regional scale. Pressure on water resources and hence on the environment will probably increase with the need of quality data for sustainable design of water resources projects. Therefore, for an optimal network design, hydrometric networks are to be reviewed periodically based on the information needs of the various end users and the perspective for future water resources development. This paper evaluates hydrometric networks to identify essential streamflow stations and critical areas (highly poor network density) within major watersheds across the different provinces of Canada using entropy theory. The method is applied to daily streamflow data and information coefficients such as marginal entropy, joint entropy and transinformation index are used for the identification of important stations as well as critical areas in the basin. The analysis results show that almost all Canadian main watersheds contain deficient hydrometric networks. The most deficient streamflow networks are identified in Alberta (North Saskatchewan, Oldman, and Red Deer basins), Northern Ontario (Hudson Bay basin), and the Northwest Territories. The information might prove to be helpful for decision makers to undertake cost-benefit analyses for hydrometric network updating in each region. [Copyright &y& Elsevier]

Abstract: This paper quantifies two important native forest ecosystem services in southern Chile: water supply and recreational fishing opportunities. We analyzed streamflow in relation to forest cover in six watersheds located in the Valdivian Coastal Range (39°50′–40°05′S), the effect of forest management on streamflow in two watersheds in the Valdivian Andes (600–650m of elevation; 39°37′S), and fish abundance as a function of forest cover in 17 watersheds located in the Coastal Range and the Central Depression (39°50′–42°30′S). We found that the annual direct runoff coefficient (quickflow/precipitation) and total streamflow/precipitation in the dry summer season were positively correlated with native forest cover in the watershed (R 2 =0.67 and 0.76; * P =0.045 and 0.027, respectively) during four years of observations. Conversely, a negative correlation was found between summer runoff coefficients (total streamflow/precipitation) and cover of Eucalyptus spp. and Pinus radiata plantations (R 2 =0.84; * P =0.010). We estimated a mean increase of 14.1% in total summer streamflow for every 10% increase in native forest cover in the watershed. The analysis of streamflow changes between two paired watersheds dominated by native secondary Nothofagus stands, one thinned with 35% of basal area removal and a control, showed that the former had a 40% increase during summer (four years of observations). The best correlation between fish abundance and forest cover was found between trout abundance (%) and secondary native forest area in 1000m×60m stream buffers (R 2 =0.65, *** P <0.0001). We estimated a 14.6% increase in trout abundance for every 10% increase of native forest cover in these buffers. Similar approaches to quantify forest ecosystem services could be used elsewhere and provide useful information for policy and decision-making regarding forest conservation and management. [Copyright &y& Elsevier]