Search

Climate change and its impact on surface runoff in the upper Blue Nile basin and sub-basins have been widely studied in future climate projections. However, the impact on extreme flow events of rivers is barely investigated discretely. In this paper, the change in temperature and rainfall under the Representative Concentration Pathway (RCP) highest emission scenario (RCP 8.5) and its impact on the high flow and low flow simulated by the Soil and Water Assessment Tool (SWAT 2012) in major watersheds of the Lake Tana Basin has been evaluated by comparing the baseline period (1971–2000) with the 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100). The high flows of watersheds were selected by the Annual Maximum Series (AMS) model, whereas the low-flow watersheds were selected by the 7-day sustained mean annual minimum flow method. The result showed that the highest change in maximum temperature ranged from 2.93 °C to 5.17 °C in monthly time scales in the 2080s. The increment in minimum temperature is also more prominent in the 2080s and it is expected to rise by 4.75 °C. Inter-annual variability of the change in rainfall has shown increasing and decreasing patterns. The highest increments are expected by 22.37%, 25.58%, and 29.75% in the 2020s, 2050s, and 2080s, respectively, whereas the projected highest decrease in rainfall dictates the decrease of 6.42%, 7.11%, and 9.26% in 2020s, 2050s, and 2080s, respectively. Due to changes in temperature and rainfall, the low flow is likely to decrease by 8.39%, 8.33%, 6.21%, and 5.02% in Ribb, Gumara, Megech, and Gilgel Abay watersheds, respectively, whereas the high flow of Gilgel Abay, Megech, Gumara, and Ribb watersheds are expected to increase by 13.94%, 12.16%, 10.90%, and 10.24%, respectively, every 30 years. [ABSTRACT FROM AUTHOR]

Climate change plays a vital role in the hydrology of any river basin, which may have multidimensional consequences. There is a need to conduct climate change impact assessment studies with updated models and scenarios. This study aimed to assess the impact of climate change on the streamflow and hydropower in Pakistan's Kunhar River basin. Three general circulation models (GCMs), under two Shared Socioeconomic Pathway scenarios (SSPs 2–45 and 5–85), the Soil and Water Assessment Tool, and the flow duration curve were used to project the change in climatic parameters, streamflow, and hydropower potential, respectively. The findings indicated that in the 2080s, the precipitation, maximum, and minimum temperatures are projected to increase by 10%, 2.0 °C, and 3.0 °C under the SSP 2–45 scenario and are projected to increase by 8%, 3.7 °C, and 4.4 °C under the SSP 5–85 scenario, respectively. The annual streamflow may increase by 15 to 11%, and the seasonal fluctuations are more likely to be dominant compared with the annual fluctuations. The hydropower potential will probably increase by 24 to 16% under the SSP 2–45 and 5–85 scenarios in the 2080s. However, seasonal changes in streamflow and hydropower may impact the hydropower plant operation in the basin. The Kunhar River's hydrology may change from snow-fed to a rainfall–runoff river. [ABSTRACT FROM AUTHOR]

Changes in land area features, such as vegetation type and soil conditions, have an impact on carbon sources and sinks and support food production; this is critical in addressing global sustainability challenges such as climate change, biodiversity loss, and food security. The study's major goal was to determine how LULC changes in the past and future might affect streamflow in the Upper Gilgel Abay watershed. The modeling was conducted using the MOLUSCE Quantum GIS plugins cellular automata simulation method and streamflow modeled using SWAT. Landsat 5 TM (1995), Landsat 7 ETM + (2007), and Landsat 8 imaging (2018) satellites were used to collect the images, which were then categorized using ERDAS 2014 software, and the kappa coefficient becomes 84.04%, 82.37%, and 85.54% for 1995, 2007, and 2018 LULC, respectively. SWAT model better performed the simulation which is R2 of 0.77 for calibration and 0.68 for validation and ENS becomes 0.71 and 0.62 for calibration and validation, respectively. The output change in streamflow due to past and future LULC maps shows an increase in LULC in cultivated areas and resulted in 39%, 46.81%, and 52.45% in each of the years 1995, 2007, and 2018, respectively. The three LULC modifications in the land cover maps from 1995, 2007, and 2018 had simulated mean monthly peak discharges of 62.20 m3/s, 66.51 m3/s, and 72.10 m3/s, respectively. The projected LULC 2027 also shows a similar increase in the study area, and dominantly cultivated land illustrates the highest change at around 53.77% but the highest change occurs on grassland during (2018–2027) land use at around 12.29%. And the highest streamflow was found around a monthly average of 1400 m3/s. The study primarily provides insight into how LULC fluctuation affects streamflow, and it is crucial for water planners and natural resource professionals whose focus is on the Upper Gilgel Abay basin. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Land use/cover (LULC) and climate change are two main factors affecting watershed hydrology. In this paper, individual and combined impacts of LULC and climate change on hydrologic processes were analysed applying the model Soil and Water Assessment Tool in a coastal Alabama watershed in USA. Temporally and spatially downscaled Global Circulation Model outputs predict a slight increase in precipitation in the study area, which is also projected to experience substantial urban growth in the future. Changes in flow frequency and volume in the 2030s (2016-2040) compared to a baseline period (1984-2008) at daily, monthly and annual time scales were explored. A redistribution of daily streamflow is projected when either climate or LULC change was considered. High flows are predicted to increase, while low flows are expected to decrease. Combined change effect results in a more noticeable and uneven distribution of daily streamflow. Monthly average streamflow and surface runoff are projected to increase in spring and winter, but especially in fall. LULC change does not have a significant effect on monthly average streamflow, but the change affects partitioning of streamflow, causing higher surface runoff and lower baseflow. The combined effect leads to a dramatic increase in monthly average streamflow with a stronger increasing trend in surface runoff and decreasing trend in baseflow. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Climate-induced changes in precipitation and temperature can have a profound impact on watershed hydrological regimes, ultimately affecting agricultural yields and the quantity and quality of surface water systems. In India, the majority of the watersheds are facing water quality and quantity issues due to changes in the precipitation and temperature, which requires assessment and adaptive measures. This study seeks to evaluate the effects of climate change on the water quality and quantity at a regional scale in the Nagavali and Vamsadhara watersheds of eastern India. The impact rainfall variations in the study watersheds were modeled using the Soil and Water Assessment Tool (SWAT) with bias-corrected, statistically downscaled models from Coupled Model Intercomparison Project-6 (CMIP-6) data for historical (1975–2014), near future (2022–2060), and far future (2061–2100) timeframes using three Shared Socioeconomic Pathways (SSP) scenarios. The range of projected changes in percentage of mean annual precipitation and mean temperature varies from 0 to 41.7% and 0.7 °C to 2.7 °C in the future climate, which indicates a warmer and wetter climate in the Nagavali and Vamsadhara watersheds. Under SSP245, the average monthly changes in precipitation range from a decrease of 4.6% to an increase of 25.5%, while the corresponding changes in streamflow and sediment yield range from −11.2% to 41.2% and −15.6% to 44.9%, respectively. Similarly, under SSP370, the average monthly change in precipitation ranges from −3.6% to 36.4%, while the corresponding changes in streamflow and sediment yield range from −21.53% to 77.71% and −28.6% to 129.8%. Under SSP585, the average monthly change in precipitation ranges from −2.5% to 60.5%, while the corresponding changes in streamflow and sediment yield range from −15.8% to 134.4% and −21% to 166.5%. In the Nagavali and Vamsadhara watersheds, historical simulations indicate that 2438 and 5120 sq. km of basin areas, respectively, were subjected to high soil erosion. In contrast, under the far future Cold-Wet SSP585 scenario, 7468 and 9426 sq. km of basin areas in the Nagavali and Vamsadhara watersheds, respectively, are projected to experience high soil erosion. These results indicate that increased rainfall in the future (compared to the present) will lead to higher streamflow and sediment yield in both watersheds. This could have negative impacts on soil properties, agricultural lands, and reservoir capacity. Therefore, it is important to implement soil and water management practices in these river basins to reduce sediment loadings and mitigate these negative impacts. [ABSTRACT FROM AUTHOR]

Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management. [ABSTRACT FROM AUTHOR]

Climate change (precipitation and temperature) has significantly affected the hydrological regimes and future climate projection. Integration of climate model with physical based model is crucial for quantitative measurement of changes in surface water regime. For accurate estimation, modelling framework need finer scale resolution of climate model output. In this study, we examined the bias corrected, statistically downscale models drawn from the NASA, Earth Exchange Global Daily Downscaled Projections–Coupled Model Intercomparison Project Phase 5 (NEX-GDDP-CMIP5) over the study region. The rainfall and temperature projection output from the INMCM-4, MRI-CGCM3 and their ensemble mean performed well over the Mahi River basin (MRB), India. In this study, the climate data integrated with the SWAT model to analyse the potential impact of climate change on the discharge of MRB. The finding indicates that in the near future (2011–2040) projection of annual average streamflow increases by 76.74% based on the INMCM-4 outputs, 25% based on the MRI-CGCM3 outputs, and 24.53% based on the ensemble mean in comparison to the baseline period (1981–2010). Further, the modelling results of mean monthly streamflow in rainy season indicated that the lowest and highest streamflow changes will be ranging from about 631.07–2718.42 m3/s as observed by INMCM-4, 491.71–2938 m3/s observed by MRI-CGCM3, 513.02–2270.18 m3/s observed by ensemble mean, in the near future. Similarly, in the summer season, the lowest level of stream flow is found to be 158.27 m3/s observed by MRI-CGCM3, 193.38 m3/s (ensemble mean) and 258.53 m3/s (INMCM-4), respectively. Additionally, the streamflow trend was assessed by Mann–Kendall and Sen's slope method at the monthly, seasonal and annual scales. The future streamflow projection represented the ascending trend observed in south west and winter monsoon, while the descending trend was observed in pre-monsoon and post-monsoon under the INMCM-4, MRI-CGCM3, and ensemble mean. Results on projected precipitation, temperature and streamflow accretion would help to develop effective adaptation measures for reducing the impacts of climate change and to work out long-term water resource management plans in the river basin. [ABSTRACT FROM AUTHOR]

Global climate change has led to an increase in both the frequency and magnitude of extreme events around the world, the risk of which is especially imminent in tropical regions. Developing hydrological models with better capabilities to simulate streamflow, especially peak flow, is urgently needed to facilitate water resource planning and management as well as climate change mitigation efforts in the tropics. In view of the need, this paper explores the feasibility of improving streamflow simulation performance in the tropical Kelantan River Basin (KRB) of Peninsular Malaysia through coupling a conceptual process-based hydrological model − Soil and Water Assessment Tool (SWAT) with a deep learning model − Bidirectional Long Short-Term Memory (Bi-LSTM) in two ways. All SWAT parameters were set as their default values in one hybrid model (SWAT-D-LSTM), whereas three most sensitive SWAT parameters were calibrated in the other hybrid model (SWAT-T-LSTM). Comparison of daily streamflow simulation results have shown that SWAT-T-LSTM consistently performs better than SWAT-D-LSTM as well as the stand-alone SWAT and Bi-LSTM model throughout the simulation period. Particularly, SWAT-T-LSTM performs considerably better than the other three models in simulating daily peak flow. Based on the latest projection results of five GCMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) under three emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), the best-performed SWAT-T-LSTM was run to assess the potential impacts of climate change on streamflow in the KRB. Ensemble assessment results have concluded that both average and extreme streamflow is much likely to increase considerably in the already wet northeast monsoon season from November to January, which has surely raised the alarm for more frequent flood occurrence in the KRB. • Couple SWAT with Bi-LSTM to simulate daily streamflow in a tropical river basin. • Coupled model simulates streamflow much better than stand-alone SWAT and Bi-LSTM. • Use coupled model to assess impacts of climate change under multiple scenarios. • Both average and extreme streamflow is much likely to increase in monsoon season. [ABSTRACT FROM AUTHOR]

Human activities and climate change are recognized as two of the most important drivers of hydrologic variability and have attracted the interest of researchers over the past decade. Changes in land use, dam construction, agricultural development, and global warming are forces that directly or indirectly impact the global and local hydrologic regime. This study examines the effects of these drivers on streamflow and sediment transport in the Gorganroud watershed, located in the north of Iran. In addition, the most sensitive land use patterns are detected using statistical approaches and a hydrologic model. The current study's principal argument is based on the variability of land use patterns during the modeling procedure (2007–2019). The Soil and Water Assessment Tool (SWAT) model is used to consider the land use dynamics during the simulation period based on the hydrological regime of the reference period. The Simple Differential Method (SDM) and Climate Elasticity Method (CEM) are utilized to estimate the contribution rates of land use and climate change in streamflow and sediment transport changes. The results indicate that changes in land use have contributed more than 60% to streamflow and sediment regime changes in all subbasins. A sensitivity analysis of land uses and the spatial distribution of the Human Contribution Rate (HCR) over the study area reveal that an increase in orchard land use (8.7% during the computational period) is primarily responsible for these significant changes. [ABSTRACT FROM AUTHOR]

The assessment of the hydrological response to projected changes in climatic variables is imperative for water resources management, especially in watersheds where snowmelt represents a significant source of runoff. In this study, we modify the source code of the snow accumulation and melting algorithm of the Soil and Water Assessment Tool (SWAT) model to improve runoff simulations in snow dominated basins. A sinusoidal snowmelt function under the degree-day factor method was adopted with its parameters calibrated based on historical data. River flow simulations were compared to measured data under the modified and unmodified SWAT models. Model differences in future predictions of river flows (2032- RCP 4.5) were also assessed. The results showed that the modifications improved runoff simulations by better capturing flow dynamics as represented by daily flows and corresponding variability during the snowmelt period. The modified model increased the Nash–Sutcliffe Efficiency (from 0.64 to 0.79; 0.60 to 0.80; 0.70 to 0.75) and the coefficient of determination (from 48 to 67%, 48 to 69%, 58 to 70%) at three gauging stations. While both models predicted a decrease of water availability in the basin, future simulations with the modified snowmelt algorithm predicted that the drop in water availability as compared to baseline year (2008) will be less dramatic (24%) compared to predictions from the unmodified SWAT (31%). We argue that the proposed source code modifications to the snowmelt algorithm of SWAT provide better insights about future water availability in snow-dominated watersheds. [ABSTRACT FROM AUTHOR]

Quantification of the changes of water balance components is significant for water resource assessment and management. This paper employed the Soil and Water Assessment Tool (SWAT) model to estimate the water balance in a mountainous watershed in northwest China at different spatial scales over the past half century. The results showed that both Nash-Sutcliffe efficiency (NSE) and determination coefficient (R2) were over 0.90 for the calibration and validation periods. The water balance components presented rising trends at the watershed scale, and the total runoff increased by 30.5% during 1964 to 2013 period. Rising surface runoff and rising groundwater flow contributed 42.7% and 57.3% of the total rising runoff, respectively. The runoff coefficient was sensitive to increasing precipitation and was not significant to the increase of temperature. The alpine meadow was the main landscape which occupied 51.1% of the watershed and contributed 55.5% of the total runoff. Grass land, forest land, bare land, and glacier covered 14.2%, 18.8%, 15.4%, and 0.5% of the watershed and contributed 8.5%, 16.9%, 15.9%, and 3.2% of the total runoff, respectively. The elevation zone from 3500 to 4500 m occupied 66.5% of the watershed area, and contributed the majority of the total runoff (70.7%). The runoff coefficients in the elevation zone from 1637 to 2800 m, 2800 to 3500 m, 3500 to 4000 m, 4000 to 4500 m, and 4500 to 5062 m were 0.20, 0.27, 0.32, 0.43, and 0.78, respectively, which tend to be larger along with the elevation increase. The quantities and change trends of the water balance components at the watershed scale were calculated by the results of the sub-watersheds. Furthermore, we characterized the spatial distribution of quantities and changes in trends of water balance components at the sub-watershed scale analysis. This study provides some references for water resource management and planning in inland river basins. [ABSTRACT FROM AUTHOR]

Both climate and land use changes can influence water quality and quantity in different ways. Thus, for predicting future water quality and quantity trends, simulations should ideally account for both projected climate and land use changes. In this paper, land use projections and climate change scenarios were integrated with a hydrological model to estimate the relative impact of climate and land use projections on a suite of water quality and quantity endpoints for a Canadian watershed. Climatic time series representing SRES change scenario A2 were generated by downscaling the outputs of the Canadian Regional Climate Model (version 4.1.1) using a combination of quantile–quantile transformation and nearest neighbor search. The SWAT (Soil and Water Assessment Tool) model was used to simulate streamflow, nitrogen and phosphorus loading under different climate and land use scenarios. Results showed that a) climate change will drive up maximum monthly streamflow, nitrate loads, and organic phosphorus loads, while decreasing organic nitrogen and nitrite loads; and b) land use changes were found to drive the same water quality/quantity variables in the same direction as climate change, except for organic nitrogen loads, for which the effects of the two stressors had a reverse impact on loading. [ABSTRACT FROM AUTHOR]

Summary: In this paper we proposed: (1) an algorithm of glacier melt, sublimation/evaporation, accumulation, mass balance and retreat; (2) a dynamic Hydrological Response Unit approach for incorporating the algorithm into the Soil and Water Assessment Tool (SWAT) model; and (3) simulated the transient glacier retreat and its impacts on streamflow at basin scale. Application of the enhanced SWAT model in the Manas River Basin (MRB) in the Tianshan Mountains in northwest China, shows that the approach is viable as evidenced by a Nash–Sutcliff efficiency of 0.65 and a percent bias of −3.7% for daily streamflow and water balance, respectively. The results indicate that the glacier area decreased by 11% during the simulation period from 1961 to 1999, which is within the range of records from other glaciers. On average, glacier melt contributed 25% to streamflow, although glacier area accounts for only 14% of the catchment drainage area in the MRB. Glacier melt was positively correlated to temperature change (R 2 =0.70, statistical significance P <0.001) and negatively correlated to precipitation (R 2 =0.20, statistical significance P <0.005). The results indicate that glacier melt was more sensitive to temperature change than to precipitation change, implying that modeling the effects of climate change with increasing temperatures and decreasing precipitation should be further studied. [ABSTRACT FROM AUTHOR]

The Gulf Coast watersheds in the United States contain some of the highest levels of biodiversity of all freshwater systems in North America. Developing environmental management policies to protect and preserve these ecosystems makes the study of the impacts of projected climate change on the future hydrologic cycle crucial. We used the Soil and Water Assessment Tool (SWAT) to estimate the potential hydrologic changes for the mid‐21st century (2050s) and the late 21st century (2080s) in the Mobile River, Apalachicola River, and Suwannee River watersheds in the Gulf Coast region of the United States. These estimates are based on downscaled future climate projections from 20 global circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). SWAT models were calibrated and validated using the multi‐algorithm, genetically adaptive multi‐objective (AMALGAM) technique in a high‐performance computing (HPC) cluster. For the Gulf Coast watersheds, the climate is projected to be warmer and wetter. Projected changes in climatic variables are likely to bring large changes in both annual and seasonal hydrologic processes within these watersheds. We found substantial decreases in mean annual streamflow under RCP8.5 during the 2080s, with up to a 13.0% decrease projected for the Suwannee River watershed compared to the present day. Summer streamflow is projected to be substantially lower during the 2080s, with up to a 25.1% decrease projected for the Suwannee River watershed, during a time of high demand of water resources for agricultural, industrial, and ecosystem services. These hydrologic projections are expected to help in making better‐informed decisions for future water resources and ecosystem management in the Gulf Coast region. Future climate of the U.S. Gulf Coast region is projected to be warmer and wetter than in the present. Substantial hydrologic alterations are projected for the Gulf Coast watersheds. More importantly, summer streamflow is projected to decrease during the 2080s when there will be a high demand of water resources for agricultural, industrial, and ecosystem services. [ABSTRACT FROM AUTHOR]

Land use is the main factor that influences catchment hydrologic processes, and a better understanding of its effect is important for future land use planning and water resource management. By applying the Soil and Water Assessment Tool (SWAT), we assessed the effects of land use changes on major hydrologic processes (evapotranspiration (ET), discharge, river) on a large plain irrigation district, the Hetao Irrigation District (HID), China. The results indicated that SWAT was a useful tool for simulating the effects of land use changes on regional hydrologic processes. Human activities were the main factors that directly influenced land use in the HID. Land use changes had important impacts on the hydrologic processes of the HID. During 1995-2010, the land use changed greatly in the HID, leading to the changes in ET and discharge. The peak value of ET coincided with the exuberant crop growth period in the maximized sown crop area. In 1995s, wheat maximized the sown area and ET peaked in June; when sunflower and corn maximized the sown area in 2010s, ET peaked in July and August. The increased ET reduced discharge in the same period in the HID. Land use change affected the period and quantity of water diversion in the irrigation district. The quantity of water diverted in 1995 was greater than that in 2010, indicating that land use change significantly impacted the water quantity of the river, which was the water source of the irrigation district. This study will be a reference for future land use planning and water resource management in the irrigation district. [ABSTRACT FROM AUTHOR]

Streamflow alteration is one of the most noticeable effects of climate change. This study explored the effects of climate change on streamflow in the Bheri River using the Soil and Water Assessment Tool (SWAT) model. Three General Circulation Models (GCMs) under two Representative Concentration Pathways (RCPs; 4.5 and 8.5) for the periods of 2020-2044, 2045-2069, and 2070-2099 were used to investigate the impact of climate change. Based on the ensemble of the three models, we observed an increasing trend in maximum and minimumtemperatures at the rate of 0.025 °C/year and 0.033 °C/year, respectively, under RCP 4.5, and 0.065 °C/year and 0.071 °C/year under RCP 8.5 in the future. Similarly, annual rainfall will increase by 6.8-15.2% in the three future periods. The consequences of the increment in rainfall and temperature are reflected in the annual streamflow that is projected to increase by 6-12.5% when compared to the historical data of 1975-2005. However, on a monthly scale, runoff will decrease in July and August by up to 20% and increase in the dry period by up to 70%, which is favorable for water users. [ABSTRACT FROM AUTHOR]

Six global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 under three Respectively Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) were used to assess the impact of climate change on streamflow for the Huangnizhuang catchment (HNZ) in China. Change factor method was used for bias correction between GCM outputs and observations and the SWAT model was used to simulate the hydrological processes. The results indicated that the SWAT model performed well in the study catchment with a monthly Nash-Sutcliffe efficiency (NS) of 0.93 and 0.91 and daily NS of 0.63 and 0.68 for calibration and validation periods respectively. Their corresponding relative errors were −2.2 and 8.9, and −2.6 and 8.5 % respectively. The ensemble of multi-GCMs projected an increase of precipitation in the middle and end of twenty-first century over the HNZ, ranging from −2.4 to 9 %. However, streamflow is likely to decline in the future, ranging −6.9 to 0.8 %, mainly due to an increase of evapotranspiration in a warming world, as air temperature shows steadily increases for all the GCMs and RCPs. Average monthly streamflow from six GCMs are likely to increase in August and September but decline from October to June. The associated uncertainties of the reported results were also discussed. It includes, but is not limit to, different GCMs, emissions scenarios, downscaling techniques as well as hydrological simulations. The results of this study can inform planning of long-term basin water management strategies taking into account global change scenarios. [ABSTRACT FROM AUTHOR]

This study investigated land-use and land-cover change (LUCC) and hydrological responses under consistent climate change scenarios (A1B and B1) in the Heihe River Basin (HRB), a typical arid inland river basin in northwest China. LUCC was first projected using the Dynamic Conversion of Land-Use and its Effects (Dyna-CLUE) model. Two cases (Case 1 and Case 2) were then established to quantify the hydrological responses to single climate change and the combined responses to climate change and LUCC with the Soil and Water Assessment Tool (SWAT). The results of LUCC modeling under the A1B and B1 scenarios present distinct regional characteristics and also indicate that the projected future land-use patterns are not appreciably different than the actual map for the year 2000. In Case 1, which only considers the impacts of single climate change, overall, the streamflow at the outlet of the upper HRB is projected to decline, whereas at the outlet of the middle HRB to increase, under both climate change scenarios. Meanwhile, the frequency of occurrence of hydrological extremes is expect to increase under both scenarios. In Case 2, which considers the combined impacts of climate change and LUCC, the changes in streamflow and frequency of hydrological extremes are found to be remarkably consistent with those in Case 1. The results imply that climate change rather than LUCC are primarily responsible for the hydrological variations. The role of LUCC varies with regions in the context of climate change dominated hydrological responses. [ABSTRACT FROM AUTHOR]

Probable impacts of climate change on water resources are a great concern for hydrologists, water managers and policy makers. Global warming and climate change is expected to change the water availability. Using physically based hydrological model Soil and Water Assessment Tool (SWAT), this study assessed the sensitivity of streamflow to individual and combined changes in temperature and rainfall for the Yass River catchment of south eastern Australia. This study also predicted the change in streamflow based on three climate scenarios (B1, A1B, A2) of Intergovernmental Panel on Climate Change Special Report on Emission Scenarios and average of four general circulation models (CNRM-CM3, CSIRO-MK3.5, ECHam5 and MIROC3.2) for three future periods (2030, 2050 and 2090). Streamflow of the Yass River was found to be highly sensitive to both temperature and rainfall changes where 1 % change in rainfall might cause 3-5 % change in streamflow and flow might be reduced up to 16 % for 1 °C rise in temperature. Simulation results based on General Circulation Models (GCM) outputs predicted that the Yass River will likely experience huge change in streamflow due to the impact of climate change. However, due to associated uncertainties regarding climate change scenarios and climate models outputs, the results need to be evaluated carefully before making decisions in future water management and planning. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents a study on the assessment of stream flow sensitivity and the effects of long-term climate change on water resources particularly at Upper Pearl River Watershed (UPRW) in Mississippi. The study employs the Soil and Water Assessment Tool (UPRW ) simulation model which was calibrated using the monthly stream flow data. The results show that UPRW hydrology is sensitive to climate change which could stimulate stream flow generation in watersheds.

Climate change plays a pivotal role in the hydrological dynamics of tributaries in the upper Blue Nile basin. The understanding of the change in climate and its impact on water resource is of paramount importance to sustainable water resources management. This study was designed to reveal the extent to which the climate is being changed and its impacts on stream flow of the Gumara watershed under the Representative Concentration Pathway (RCP) climate change scenarios. The study considered the RCP 2.6, RCP 4.5, and RCP 8.5 scenarios using the second-generation Canadian Earth System Model (CanESM2). The Statistical Downscaling Model (SDSM) was used for calibration and projection of future climatic data of the study area. Soil and Water Assessment Tool (SWAT) model was used for simulation of the future stream flow of the watershed. Results showed that the average temperature will be increasing by 0.84 °C, 2.6 °C, and 4.1 °C in the end of this century under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively. The change in monthly rainfall amount showed a fluctuating trend in all scenarios but the overall annual rainfall amount is projected to increase by 8.6%, 5.2%, and 7.3% in RCP 2.6, RCP 4.5, and RCP 8.5, respectively. The change in stream flow of Gumara watershed under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios showed increasing trend in monthly average values in some months and years, but a decreasing trend was also observed in some years of the studied period. Overall, this study revealed that, due to climate change, the stream flow of the watershed is found to be increasing by 4.06%, 3.26%, and 3.67%under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter drought regimes across North America throughout the twenty-first century, and, consequently, future drought risk may not resemble the past. To explore the implications of nonstationary drought risk, this study combined a calibrated, regional-scale hydrological model with statistically downscaled climate projections and standardized drought indices to identify intra-annual patterns in the response of meteorological, soil moisture, and hydrological drought to climate change. We focus on a historically water-rich, highly agricultural watershed in the US Midwest—the Wabash River Basin. The results show likely increases in the frequency of soil moisture and hydrological drought, despite minimal changes in the frequency of meteorological drought. We use multiple linear regression models to interpret these results in the context of climate warming and show that increasing temperatures amplify soil moisture and hydrological drought, with the same amount of precipitation yielding significantly lower soil moisture and significantly lower runoff in the future than in the past. The novel methodology presented in this study can be transferred to other regions and used to understand how the relationship between meteorological drought and soil moisture/hydrological drought will change under continued climate warming. [ABSTRACT FROM AUTHOR]

Non-point source (NPS) pollution is a primary cause of water pollution in the Saemangeum watershed in South Korea. The changes in NPS pollutant loads in the Saemangeum watershed for an 81-year period (2019–2099) were simulated and analyzed by applying the soil and water assessment tool. Six climate model (BCC-CSM1–1, CanESM2, GFDL-ESM2G, HadGEM2-CC, INM-CM4, and MIROC-ESM) outputs using representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) were obtained from the South Korean Asia-Pacific Economic Cooperation (APEC) Climate Center. Simulated streamflow and water quality were evaluated using the Nash–Sutcliffe efficiency (NSE) index and coefficient of determination (R2). The model satisfactorily simulated streamflow with positive NSE values and R2 > 0.5. Based on two climate change scenarios (RCP 4.5 and RCP 8.5), gradual increases of 70.9 to 233.8 mm and 1.7 to 5.7 °C in annual precipitation and temperature, respectively, are likely for two time periods (2019–2059 and 2060–2099). Additionally, the expected future average annual and monthly streamflow, sediment, and total phosphorus showed changes of 5% to 43%, 3% to 40%, and −55% to 15%, respectively, whereas the expected future average annual and monthly total nitrogen showed decreases of −5% to −27%. Future NPS pollutant loads in the Saemangeum watershed should be managed according to different climate change scenarios. [ABSTRACT FROM AUTHOR]

The soil and water assessment tool (SWAT) model was applied for the first time in Cuba to assess the potential impacts of climate change on water availability in the Cauto River basin. The model was calibrated (and validated) for the 2001–2006 (2007–2010) period at a monthly timescale in two subbasins La Fuente and Las Coloradas, representative of middle and upper sections of the Cauto basin; the calibrated models showed good performance. The output available for the regional climate Model RegCM4.3 was used to force the calibrated SWAT models to simulate a baseline (1970–2000) period and near-future (2015–2039) hydrologic regimes under the representative concentration pathway (RCP) 8.5 emission scenario. The future projections suggest regional increases of 1.5 °C in mean annual temperature and a 38% decrease in mean annual precipitation in the subbasins. These changes translate to possible reductions in the annual streamflow of up to 61% with respect to the baseline period, whereas the aquifer recharge in the basin is expected to decrease up to 58%, with a consequent reduction of groundwater flow, especially during the boreal summer wet season. These projection scenarios should be of interest to water resources managers in tropical regions. [ABSTRACT FROM AUTHOR]