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Summary: Human activities are directly related to fossil fuel consumption and cause global warming and climate change effects by emitting greenhouse gas into the lower atmosphere. To reduce and adapt to such effects, renewable energy sources such as surface dams, including hydroelectric energy (HE) generation units, are gaining importance. In the current literature, HE potential calculations are based on formulations that are quite simple, clear and do not distinguish between different situations. In this paper, two classification methodologies are proposed for better assessment of HE production. The first one is based on the concept of the hypsographic curve to distinguish different drainage basin features into "Young," "Mature" and "Old." The second classification takes into account the newly defined energy index (EI) principle, which helps to classify the HE generation capability of drainage basins into "Very low," "Low," "Normal," "High" and "Very high." The application of the proposed methodology is presented for three drainage basins from the upstream sub‐basins of the Tigris River in Turkey. A comparison of the results shows that the proposed methodologies not only give numerical values but also sets linguistically rational and logical rules for the HE potential of a drainage basin. In the upstream basin of the Tigris River, the EI values vary between 0.705 and 0.122, corresponding to the "High" and "Low" categories, respectively. It is recommended that these two classification procedures be considered before the construction of any dam for HE production. [ABSTRACT FROM AUTHOR]

Research on the combined impact of watershed attributes on streamflow is crucial in water resources planning and management, particularly due to the strong link between landscape modification and watershed attributes. However, identifying critical watershed attributes remains a challenge. This study focuses on investigating the impact of watershed attributes on streamflow in the Hare catchment of Ethiopia's rift valley lakes basin. The Soil and Water Assessment Tool (SWAT) rainfall–runoff model was used, calibrated, and validated against observed discharge data to identify remedial measures for streamflow generation. The model's performance was evaluated using criteria such as R2, NSE, PBIAS, and RSR, which yielded satisfactory values. The study found significant changes in land cover, with forest and shrub land declining and agricultural land expanding. Comparing mean annual streamflow between 1998, 2009, and 2021, streamflow at 2021 land use and land cover increased by 13.03% compared to 2009, which had already increased by 16.05% compared to 1998. The study also examined the impact of climate variations by manipulating meteorological data length and average slope. Overall, this study provides valuable insights into the relationship between watershed attributes and streamflow, emphasizing the importance of considering land cover changes and climate variations for effective water resource management in the Hare catchment. [ABSTRACT FROM AUTHOR]

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

In ecologically fragile areas with arid climate, such as the Heihe River Basin in northwestern China, sustainable social and economic development depends largely on the availability and sustainable uses of water resource. However, there is more and more serious water resource shortage and decrease of water productivity in Heihe River Basin under the influence of climate change and human activities. This paper attempts to identify the severe water scarcity under climate change and presents possible solutions for sustainable development in Heihe River Basin. Three problems that intervened land use changes, water resource, the relevant policies and institutions in Heihe River basin were identified, including (1) water scarcity along with serious contradiction between water supply and demand, (2) irrational water consumption structure along with low efficiency, and (3) deficient systems and institutions of water resource management along with unreasonable water allocation scheme. In this sense, we focused on reviewing the state of knowledge, institutions, and successful practices to cope with water scarcity at a regional extent. Possible solutions for dealing with water scarcity are explored and presented from three perspectives: (1) scientific researches needed by scientists, (2) management and institution formulation needed by governments, and (3) water resource optimal allocation by the manager at all administrative levels. [ABSTRACT FROM AUTHOR]

Hydropower is sustainable and environmentally friendly source of energy worldwide. Driven by streamflow, it is vulnerable to climate change and land use change. The hydropower production from the two existing run-of-river hydropower projects on the Sondu Miriu River is vulnerable to rainfall variability and requires strategies for building resilience for the local communities. The objective of this study was to identify appropriate and sustainable strategies for integrating climate change adaptation into hydropower development within the Sondu Miriu River Basin. The methodology involved review of existing climate change adaptation strategies to identify appropriate strategies for integrating climate change adaptation in hydropower developments within the Sondu Miriu River Basin. The results indicate that no clear climate change adaptation strategies are being implemented within the basin. A framework is needed to implement appropriate climate change adaptation strategies within the basin. Climate Change act of 2016 created linkage with other existing policies for effective support of integration of climate change adaptation into hydropower development in Sondu Miriu River Basin. Strengthening community resilience to climate change impacts is one of the benefits to be derived from the hydropower projects by supporting appropriate adaptation strategies. [ABSTRACT FROM AUTHOR]

Climate change has increasingly been considered responsible for irregular weather patterns leading to many environmental hazards and catastrophes. Coping with these conditions and providing effective solutions require monitoring and collecting data of various hydrological parameters and events in high spatial and temporal resolutions, which is generally limited by the cost and energy requirements of the monitoring devices. In this work, we push the limit of the current low-cost data acquisition capabilities by developing the HydroMon3: a hydrological monitoring platform that collects, stores, and transmits high temporal resolution data reliably and accurately, and capable of interfacing different types of sensors. The modular design is driven by utilizing the recent burst in commercially available IoT-related electronics modules to minimize the cost and maximize flexibility, while applying various hardware and software techniques to ensure reliability and energy performance. Stream stage and tipping bucket monitoring units based on the HydroMon3 platform were deployed to more than 20 locations in two different watersheds, and their performance over a 6-month season was evaluated. Collected data for a number of storms provided important insights for linking hydrological events and showed substantial variability in the monitored parameters both spatially and temporally, which were compared with local data records and confirmed that conventional hydrological data acquisition methods are under representative of the actual events. Field-proven results demonstrate the units' ability to maintain autonomous operation from several months for the stream stage monitors to years for the rainfall gauges using of-the-shelf AA batteries. [ABSTRACT FROM AUTHOR]

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners. [ABSTRACT FROM AUTHOR]

Climate extremes have attracted widespread attention for their threats to the natural environment and human society. Based on gauged daily precipitation from 1963 to 2016 in four subregions of the Jinsha River Basin (JRB), four extreme precipitation indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were employed to assess the spatiotemporal variations of extreme precipitation events. Results show the following: (1) Max one-day precipitation amount (RX1day), max consecutive five-day precipitation amount (RX5day), precipitation on very wet days (R95p), and number of heavy precipitation days (R10mm) showed increasing trends in four subregions except for the decline of R10mm in the southeastern and RX5day in the midsouthern. Extreme precipitation has become more intense and frequent in most parts of the JRB. (2) In space, the four extreme precipitation indices increased from the northwest to the southeast. Temporal trends of extreme precipitation showed great spatial variability. It is notable that extreme precipitation increased apparently in higher elevation areas. (3) The abrupt change of extreme precipitation in the northwestern, midsouthern, and southeastern mainly appeared in the late 1990s and the 2000s. For the midnorthern, abrupt change mainly occurred in the late 1980s. This study is meaningful for regional climate change acquaintance and disaster prevention in the JRB. [ABSTRACT FROM AUTHOR]

Global climate change is becoming an increasingly important issue that threatens the imperiled planet. Quantifying the impact of climate change on the streamflow has been an essential task for the proper management of water resources to mitigate this impact. This study aims to evaluate the skill of an artificial neural network (ANN) method in downscaling precipitation, maximum temperature, and minimum temperature and assess the potential impacts of climate change on the streamflow in the Wabash River Basin of the Midwestern United States (U.S.) using the Soil and Water Assessment Tool (SWAT). A statistical downscaling technique based on an ANN method was employed to estimate precipitation and temperature at a higher resolution. The downscaled climate projections from five general circulation models (GCMs) under the three representative concentration pathway (RCP) scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5) for the periods of 2026–2050 and 2075–2099 as well as the historical period were incorporated into the SWAT model to assess the potential impact of climate change on the Wabash River regime. Calibration and validation of the SWAT model indicated the streamflow simulations matched the observed results very well. The ANN method successfully reproduced the observed maximum/minimum temperature and precipitation; however, bias in precipitation was observed in regard to the frequency distribution. Compared with the simulated streamflow in the historical period, the predicted streamflow based on the RCP scenarios showed an obvious decreasing trend, where the annual streamflows will be decreased by 13.00%, 17.59%, and 6.91% in the midcentury periods and 25.29%, 27.61%, and 15.04% in the late-century periods under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Climate warming dominated the streamflow decrease under the RCP2.6 and RCP4.5 scenarios. By contrast, under RCP8.5, the streamflow was affected by the joint actions of changes in temperature and precipitation. [ABSTRACT FROM AUTHOR]

Based on the daily temperature data from 26 meteorological stations in the Minjiang River Basin, for 1961 to 2016, the temporal trend and spatial distribution of extreme temperature in this region were analyzed using 16 extreme temperature indices. The results show that in terms of time variation, determined using linear trend analysis and a Mann–Kendall trend test, the warm and day indices mainly show an upward trend while the cold and night indices mainly show a downward trend in the entire basin. Among them, FD0, TN10, and CSDI significantly decrease at −1.3, −2.9, and −1.1 d/10a, respectively. TN90, TX90, SU25, and TR20 significantly increase at 3.0, 2.6, 2.1, and 2.2 d/10a, respectively. The crop growth period in the basin showed a significant increasing trend at 1.4 days/decade, while the diurnal temperature range showed a nonsignificant increasing trend at 0.03 days/decade. On comparing the change range of each index, it was found that the change range of the warm index is greater than that of the cold index, while the change range of the day index is smaller than that of the night index; thus, the change trends of the maximum and minimum temperatures in the whole basin are not obvious. Analysis of the changing trend at each station showed that the relative index of the extreme temperature in the basin has good climatic consistency in terms of spatial distribution. The distributions of the absolute and extreme indices are not uniform, which is consistent with the change in elevation in the basin. Further, the diurnal temperature range in the upper reaches of the basin is greater than that in the middle and lower reaches. However, because of the more obvious upward trends of the day and warm indices in the middle and lower reaches, and the more obvious downward trends of the night and cold indices in the upper reaches, the daily temperature differences in the upper, middle, and lower reaches of the Minjiang River Basin tend to be consistent. Therefore, the precipitation in the Minjiang River Basin shows a significant decreasing trend; thus, the basin shows a trend of drying and warming. [ABSTRACT FROM AUTHOR]

The effect of climate variability on the rainfall pattern is canvassed on the Uma Oya river basin, Sri Lanka, consisting of 5 rainfall gauging stations. The Uma Oya basin (720 km2) is given utmost precedence due to environmental concerns seen in the ongoing Uma Oya multipurpose development project (529 million USD worth) which is expected to divert water to the southeast dry zone of the country while adding 231 GWh/year electricity to the national grid. The rainfall data for a period of 26 years (1992–2017) were analysed using Mann–Kendall's test and Sen's slope estimator test to identify the rainfall trends. Both of these trend analysis test results depict only one negative trend for Hilpankandura Estate for the month of June; however, the seasonal trend analysis and annual trend analysis do not support this observation. Nevertheless, Mann–Kendall's test showed potential positive trends for the 3 rainfall gauging stations Kirklees Estate, Ledgerwatte Estate, and Welimada Group only in the 1st intermediate period (March-April), and this is well supported by the monthly trend analysis. Other than these trends, the results do not show any significant negative trends in the Uma Oya catchment. Therefore, the results vividly explain that there is no threat of water scarcity to the catchment area being resistant to changing global climate for the past 26 years. [ABSTRACT FROM AUTHOR]

Watershed discharge (WD) in the alpine regions, such as the upper reach of Yarlung Zangbo River Basin (YZRB), China, could have changed severely in response to climate changes. Yet, how hydrometeorological variables varied at different time scales and how WD varied in response to hydrometeorological variables in the alpine regions remained questions to be answered. The ensemble empirical mode decomposition (EEMD) method was employed in this study to investigate the nonlinear climate change trends (averaged and extreme states) and the associated multiscale impacts on WD variations over the upper reach of the YZRB during 1961–2009. All investigated hydroclimatic variables, i.e., precipitation, temperature, and WD, were found to be varied nonlinearly with clear multiscale oscillations characterizing great differences in the oscillation periods, corresponding significance levels, and variance contribution rates, among which precipitation posed a weak impact on WD variations, while temperature played a significant role in WD fluctuations. Furthermore, among all temperature extremes, the dominant index affecting WD variations was TXm (annual mean of the daily maximum temperature) but not TXx (annual maximum of the daily maximum temperature) at both interannual and interdecadal scales, which might be caused by that TXx increased evapotranspiration and reduced WD. A significant correlation between temperature (both averaged and partial extreme states) and annual WD at both interannual and interdecadal scales indicated that a synchronous change existed between them. The present study provided first insight into how hydrometeorological variables varied at different time scales and how WD fluctuated in response to hydrometeorological variables over the upper reach of the YZRB, China. [ABSTRACT FROM AUTHOR]

The assimilation of satellite soil moisture (SM) products with coarse resolution is promising in improving rainfall-runoff modeling, but it is largely impacted by the data assimilation (DA) strategy. This study performs the assimilation of a satellite soil moisture product from the European Space Agency (ESA) Climate Change Initiative (CCI) in a physically based semidistributed hydrological model (SWAT) in the upper Huai River basin in China, with the objective to improve its rainfall-runoff simulation. In this assimilation, the ensemble Kalman filter (EnKF) is adopted with full consideration of the model and observation error, the rescaling technique for satellite SM, and the regional applicability of the hydrological model. The results show that the ESA CCI SM assimilation generally improves the streamflow simulation of the study catchment. It is more effective for low-flow simulation, while for very high-flow/large-flood modeling, the DA performance shows uncertainty. The less-effective performance on large-flood simulation lies in the relatively low dependence of rainfall-runoff generation on the antecedent SM as during which the SM is nearly saturated and the runoff is largely dominated by precipitation. Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. Overall, the ESA CCI SM assimilation improves the streamflow simulation of the SWAT model in particular for low flow. This study provides an encouragement for the application of the ESA CCI SM in water management, especially over low-flow periods. [ABSTRACT FROM AUTHOR]

The current study presents a method for automating the Köppen–Garcia climate classification using a GIS module. This method was then applied in a case study of the Lerma-Chapala-Santiago watershed to compare time series data on climate from 1960 to 1989, 1981 to 2010, and 1960 to 2010. The kappa statistic indicated that the climate classifications of the generated model had a perfect degree of agreement with those of a prior nonautomated study. The climate data from the period 1960 to 2010 were used to create a climate map for the watershed. Overall, the dominant climates were dry, semiarid, temperate, and semiwarm temperate with a summer rainfall pattern. A comparative analysis of climate behavior between 1960 and 1989 and between 1981 and 2010 showed changes in temperature and extreme temperatures over 13.6% and 9.9%, respectively, of the watershed; the presence or absence of mid-summer drought also changed over 0.8% of the watershed. The module developed herein can be used to classify climates across all of Mexico, and data of varying spatial resolution and coverage can be inputted to the module. Finally, this module can be used to automate the creation of climate maps or to update climate maps at diverse spatial-temporal scales. [ABSTRACT FROM AUTHOR]