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Optimizing reservoir drawdown operations holds significant implications for hydropower generation, water supply, and drought mitigation strategies. However, achieving multi-objective optimization in reservoir drawdown operations poses fundamental challenges, particularly considering emergency storage capacity and seasonal drought patterns. This study introduces a novel multi-objective optimization framework tailored for a mega reservoir, focusing on drawdown operations to enhance hydropower generation and water supply reliability. A drawdown operation model leveraging a multi-objective ant lion optimizer is developed to simultaneously maximize reservoir hydropower output and minimize water shortage rates. China's Three Gorges Reservoir (TGR), situated over the upper reaches of the Yangtze River, constitutes the case study, with the standard operation policy (SOP) serving as a benchmark. Results showcase the efficacy of the proposed method, with substantial improvements observed: a 10.6% increase in hydropower output, a 6.0% reduction in water shortage days, and a 9.5% decrease in minimal reservoir water release compared to SOP. This study provides robust technical and scientific bolster to optimize reservoir ESC and enhance the synergy between hydropower generation, water supply, and drought resilience. Additionally, it offers decision-makers actionable strategies that account for emergency water supply capacities. These strategies aim to support mega reservoir's resilience against extreme drought events facilitating the collaboration between modelers and policy-makers, by means of intelligent optimization and decision-making technologies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Water resources sustainability in High Mountain Asia (HMA) surrounding the Tibetan Plateau (TP)-known as Asia's water tower-has triggered widespread concerns because HMA protects millions of people against water stress 1,2 . However, the mechanisms behind the heterogeneous trends observed in terrestrial water storage (TWS) over the TP remain poorly understood. Here we use a Lagrangian particle dispersion model and satellite observations to attribute about 1 Gt of monthly TWS decline in the southern TP during 2003-2016 to westerlies-carried deficit in precipitation minus evaporation (PME) from the southeast North Atlantic. We further show that HMA blocks the propagation of PME deficit into the central TP, causing a monthly TWS increase by about 0.5 Gt. Furthermore, warming-induced snow and glacial melt as well as drying-induced TWS depletion in HMA weaken the blocking of HMA's mountains, causing persistent northward expansion of the TP's TWS deficit since 2009. Future projections under two emissions scenarios verified by satellite observations during 2020-2021 indicate that, by the end of the twenty-first century, up to 84% (for scenario SSP245) and 97% (for scenario SSP585) of the TP could be afflicted by TWS deficits. Our findings indicate a trajectory towards unsustainable water systems in HMA that could exacerbate downstream water stress., (© 2023. The Author(s).)

Intensifying droughts under climatic warming are of widespread concern owing to their devastating impacts on water resources, societies and ecosystems. However, the effects of exogeneous drivers on regional droughts remain poorly understood. Using the Lagrangian method, atmospheric reanalysis data and climate projections from the Coupled Model Inter-comparison Project phase 6 (CMIP6), we show how exogenous precipitation minus evaporation (PME) deficit drives droughts across China. More specifically, we demonstrate that four distinct trajectories of such exogenous PME deficit fuel regional droughts. Three of these trajectories relate to oceanic PME deficit originating from the North Atlantic, eastern Bering Sea and Indian Ocean, and one trajectory characterizes exogenous terrestrial PME deficit from the Siberian Plateau. We show that during 1980–2020, droughts induced by exogenous PME deficit account for 45% of all droughts that occurred in China's coastal region, and for 7% of all droughts in the northwestern regions. Under climate scenario SSP245 (SSP585), limiting warming to 1.5 °C compared to 2 °C above pre-industrial levels could avoid 60% (84%) of exogenous drought exposure. This would in turn reduce population exposure by 40% (49%), and economic exposure by 73% (66%). Our study unravels how exogenous PME deficit drives droughts in China, underscoring the role that external drivers have on regional droughts and associated future prediction. [ABSTRACT FROM AUTHOR]

Whether or not large-scale vegetation restoration will lead to a decrease in regional terrestrial water storage is a controversial topic. This study employed the Geodetector model, in conjunction with observed and satellite hydro-meteorological data, to detect the changes in terrestrial water storage anomaly (TWSA) and to identify the contributions of climate change and vegetation greening across China during the years 1982–2019. The results revealed that: (1) during the period of 1982–2019, TWSA showed a downward trend in about two thirds of the country, with significant declines in North China, southeast Tibet, and northwest Xinjiang, and an upward trend in the remaining third of the country, with significant increases mainly in the Qaidam Basin, the Yangtze River, and the Songhua River; (2) the positive correlation between normalized vegetation index (NDVI) and TWSA accounts for 48.64% of the total vegetation area across China. In addition, the response of vegetation greenness lags behind the TWSA and precipitation, and the lag time was shorter in arid and semi-arid regions dominated by grasslands, and longer in relatively humid regions dominated by forests and savannas; (3) furthermore, TWSAs decreased with the increase in NDVI and evapotranspiration (ET) in arid and semi-arid areas, and increased with the rise in NDVI and ET in the humid regions. The Geodetector model was used to detect the effects of climate, vegetation, and human factors on TWSA. It is worth mentioning that NDVI, precipitation, and ET were some of the main factors affecting TWSA. Therefore, it is essential to implement rational ecological engineering to mitigate climate change's negative effects and maintain water resources' sustainability in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Documenting year-to-year variations in carbon storage potential in terrestrial ecosystems is crucial for the determination of carbon dioxide (CO 2) emissions. However, the magnitude, pattern, and inner biomass partitioning of carbon storage potential and the effect of the changes in climate and CO 2 on inner carbon stocks remain poorly quantified. Herein, we use a spatially explicit individual-based dynamic global vegetation model to investigate the influences of the changes in climate and CO 2 on the enhanced carbon storage potential of vegetation. The modelling included a series of factorial simulations using the Climatic Research Unit (CRU) dataset from 1916 to 2015. The results show that CO 2 predominantly leads to a persistent and widespread increase in light-gathering vegetation biomass carbon stocks (LVBC) and water-gathering vegetation biomass carbon stocks (WVBC). Climate change appears to play a secondary role in carbon storage potential. Importantly, with the intensification of water stress, the magnitude of the light- and water-gathering responses in vegetation carbon stocks gradually decreases. Plants adjust carbon allocation to decrease the ratio between LVBC and WVBC for capturing more water. Changes in the pattern of vegetation carbon storage were linked to zonal limitations in water, which directly weaken and indirectly regulate the response of potential vegetation carbon stocks to a changing environment. Our findings differ from previous modelling evaluations of vegetation that ignored inner carbon dynamics and demonstrate that the long-term trend in increased vegetation biomass carbon stocks is driven by CO 2 fertilization and temperature effects that are controlled by water limitations. [ABSTRACT FROM AUTHOR]

Reliable precipitation is crucial for hydrological studies over Tibetan Plateau (TP) basins with sparsely distributed rainfall gauges. In this study, four widely used precipitation products, including the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of the water resources (APHRODITE), the High Asia Reanalysis (HAR), and the satellite-based precipitation estimates from Global Precipitation Measurement (GPM) and Tropical Rainfall Measurement Mission (TRMM), were comprehensively evaluated by combining statistical analysis and hydrological simulation over the Upper Brahmaputra (UB) River Basin of TP during 2001–2013. In respect to the statistical assessment, the overall performances of GPM and HAR are comparable to each other, and both are superior to the other two datasets. For hydrological assessment, both daily and monthly GPM-based streamflow simulations perform the best not only at the UB outlet with very good results, but they also illustrate satisfactory results at Yangcun and Lhasa hydrological stations within the UB. Runoff simulation using HAR only performs well at the UB outlet, whereas it shows poor results at both Yangcun and Lhasa stations. The simulated results based on APHRODITE and TRMM show poor performances at UB. Generally, the GPM shows an encouraging potential for hydro-meteorological investigation over UB, although with some bias in flood simulation. [ABSTRACT FROM AUTHOR]

Documenting year-to-year variations in carbon-sequestration potential in terrestrial ecosystems is crucial for the determination of carbon dioxide (CO2) emissions. However, the magnitude, pattern and inner biomass partitioning of carbon-sequestration potential, and the effect of the changes in climate and CO2 on inner carbon stocks, remain poorly quantified. Herein, we use a spatially explicit individual based-dynamic global vegetation model to investigate the influences of the changes in climate and CO2 on the enhanced carbon-sequestration potential of vegetation. The modelling included a series of factorial simulations using the CRU dataset from 1916 to 2015. The results show that CO2 predominantly leads to a persistent and widespread increase in above-ground vegetation biomass carbon-stocks (AVBC) and below-ground vegetation biomass carbon-stocks (BVBC). Climate change appears to play a secondary role in carbon-sequestration potential. Importantly, with the mitigation of water stress, the magnitude of the above- and below-ground responses in vegetation carbon-stocks gradually increases, and the ratio between AVBC and BVBC increases to capture CO2 and sunlight. Changes in the pattern of vegetation carbon storage was linked to regional limitations in water, which directly weakens and indirectly regulates the response of potential vegetation carbon-stocks to a changing environment. Our findings differ from previous modelling evaluations of vegetation that ignored inner carbon dynamics and demonstrates that the long-term trend in increased vegetation biomass carbon-stocks is driven by CO2 fertilization and temperature effects that are controlled by water limitations. [ABSTRACT FROM AUTHOR]

Groundwater storage (GS) is the major water resource for vegetation in drylands. Thus, positive relationships between vegetative growth condition (VGC) and GS are expected in drylands. Since mining‐induced dewatering tends to deplete GS surrounding mine sites, VGC should become less favorable due to a shortage of accessible water. However, quantitative analysis repealed the opposite. We found that global annual mineral production in drylands increased by 24%, while GS decreased by 22% but the VGC improved by 37% (2002–2010). And negative relationships between VGC and GS were detected in 84.7% of global dryland mine sites. We concluded that irrigation supported by mining‐induced dewatering promoted the vegetation growth surrounding mine sites. However, since the GS is limited, irrigation‐supported vegetation growth is unsustainable. This study elucidates the reason behind these abnormal negative relationships and highlights the potential risk of vegetation degradation induced by unsustainable groundwater depletion in global dryland mine sites. Plain Language Summary: The impacts of mining activities on the relationships between dryland vegetation growth condition (VGC) and groundwater storage (GS) have been quantitatively evaluated based on the remote sensing observations. Our results indicate that increasing mineral production depletes GS but improves VGC in drylands. And the abnormal negative relationships between GS and VGC occurs in 84.7% of global dryland mine sites. We conclude that irrigation water sourced from mining‐induced dewatering drives an increase in vegetation growth. However, since the GS is limited, irrigation‐supported vegetation growth is unsustainable. These results elucidate the unsustainable impacts of mining activities on the transformation of the relationships between GS and VGC in global dryland mine sites. Key Points: Increasing mineral production depletes groundwater storage (GS) but promotes vegetation growth in drylandsMining‐induced dewatering reversed normal positive relationships between vegetation growth conditions and GSUnsustainable irrigation bonuses mask the potential risk of long‐term vegetation degradation in drylands [ABSTRACT FROM AUTHOR]

Large dams and reservoirs alter not only the natural flow regimes of streams and rivers but also their flooding cycles and flood magnitudes. Although the effect of dams and reservoirs has been reported for some vulnerable locations, the understanding of the inner‐basin variation with respect to the effects remains limited. In this study, we analyse the Three Gorges Dam (TGD) built on the Changjiang mainstream (Yangtze River) to investigate the dam effect variations in the system of interconnected water bodies located downstream. We investigated the effect of flow alterations along the downstream river network using discharge time series at different gauging stations. The river–lake interactions (referring to the interactions between the Changjiang mainstream and its tributary lakes i.e. the Dongting and Poyang lakes) and their roles in modifying the TGD effect intensity were also investigated in the large‐scale river–lake system. The results show that the water storage of the tributary lakes decreased after the activation of the TGD. Severe droughts occurred in the lakes, weakening their ability to recharge the Changjiang mainstream. As a consequence, the effect of the TGD on the Changjiang flow increase during the dry season diminished quickly downstream of the dam, whereas its impact on the flow decrease during the wet season gradually exacerbated along the mainstream, especially at sites located downstream of the lake outlets. Therefore, when assessing dam‐induced hydrological changes, special attention should be paid to the changes in the storage of tributary lakes and the associated effects in the mainstream. This is of high importance for managing the water resource trade‐offs between different water bodies in dam‐affected riverine systems. [ABSTRACT FROM AUTHOR]

Glaciers are important freshwater storage systems in the Tianshan Mountains. Under the context of climate change, quantifying changes in glacier mass balance, the melt-season (June–September) runoff and its key runoff component (glacier runoff) is of importance for understanding the discharge composition and ensuring adequate management of water resources. In this study, the modified HBV-D (Hydrologiska Byrans Vattenbalansavdelning-D) hydrological model was used to simulate hydrological processes for a data-sparse glacierized watershed, the headwater catchment of Manas River basin (MRB) in the Tianshan Mountains. Meanwhile, the roles of three modified elements of HBV-D in simulating glacier dynamics are identified. Sequently, the glacier mass balance and runoff during 1984–2006 are reconstructed and their responses to climate change are investigated. The analysis showed (1) the snow/glacier melt method makes more contribution to improving the performance of HBV-D model in simulating historical change of glacier volume, followed by the glacier dynamic method. (2) The reconstructed mass balance follows a decreased trend in the MRB. The maximum accumulation of glacier mass balance occurs in June. Snowmelt over the surface of glacier and glacier melt reach peak in June and August, respectively. Furthermore, sensitivity experiments showed increased mass balance induced by a 10% increase in precipitation cannot compensate for the decreased mass balance due to a 1 °C temperature rise. (3) Significant contribution (about 41.5%) of runoff in glacierized area to the melt-season total runoff of the catchment is identified. Both the glacier runoff and its contribution to melt-season total runoff show increased trends during the simulation period. Compared with the melt-season mean temperature and annual precipitation over glaciers, the melt-season positive accumulated temperature over glaciers played the most important role in influencing changes in glacier runoff in MRB. The findings in this study are beneficial for implementing adaptive countermeasures for water resources management in the data-scarce glaciated high-mountainous region. [ABSTRACT FROM AUTHOR]

As a large open lake that connects to the lower Yangtze River, the Poyang Lake, China, has persisted dramatic water level decline since 2003. For better management of lake water resources and ecosystem, this study quantitatively examined the contributions and spatiotemporal differences of compounding influencing factors to this hydrological change. Attempts were achieved through the reconstruction of lake water level series by two combined neural network models. The results indicate that with reference to the period 1980–1999, the average contributions to lake decline during 2003–2014 of lake-bottom topography change, the operation of the Three Gorges Dam (TGD), and climate change and other human activities over the Yangtze River basin were 50%, 18%, and 32%, respectively. The response of the lake water level to the three factors shows obvious spatiotemporal differences due to different influencing mechanisms. It is worth noting that the effect of lake-bottom topography change is still increasing across the lake. In addition, the reduction of precipitation in the Yangtze River basin should be highly correlated to the water level decline of the lake. From the perspective of maintaining a certain water level of the lake and preventing continuous decline and shrinkage, constructing the proposed water control structure would be an effective solution. [ABSTRACT FROM AUTHOR]

Meteorological Ensemble Streamflow Prediction (ESP), which uses Ensemble Weather forecasts (EWFs) to drive hydrological models, is a useful methodology for extending forecast periods and to provide valuable uncertainty information to improve the operation of future water resources. However, raw EWFs are usually biased and under-dispersive and so cannot be directly used in ESP, leading to the development of several post-processing methods. The performance of these methods needs to be evaluated/compared in building ESP based on deterministic and probabilistic criteria. In addition, likely influencing factors also need to be identified. This study evaluated the performance of four state-of-the-art methods: the Generator-based Post-Processing (GPP) method, Extended Logistic Regression (ExLR), Bayesian Model Averaging (BMA) and Affine Kernel Dressing (AKD), using a simple bias correction (BC) method as a benchmark. The evaluation was carried out over four watersheds with different basin areas in the humid region of central-south China based on the weather reforecasts from the Global Ensemble Forecasting System (GEFS). The results show that the performance of the post-processing methods varies with the forecast variable (precipitation, or air temperature or streamflow), but all of them outperform the BC and GEFS. For the four post-processing methods, the advantage of the generator-based methods (GPP and ExLR) lies in their probabilistic performance, which outperforms the distribution-based methods (BMA and AKD) by about 10% in precipitation forecasts and about 20% in streamflow forecasts, while the distribution-based methods (BMA and AKD) are better at their deterministic performance for precipitation forecasts, with a benefit of about 15%. Meanwhile, the post-processing methods generally perform better for precipitation and streamflow forecasts, but worse for air temperature forecasts for a bigger basin compared to the distribution-based methods. The results of this study emphasize the importance of considering the uncertainty of post-processing methods in ESP. [ABSTRACT FROM AUTHOR]

The Himalayan Mountains are the source region of one of the world's largest supplies of freshwater. The changes in glacier melt may lead to droughts as well as floods in the Himalayan basins, which are vulnerable to hydrological changes. This study used an integrated glacio-hydrological model, the Glacier and Snow Melt – WASMOD model (GSM-WASMOD), for hydrological projections under 21st century climate change by two ensembles of four global climate models (GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) and two bias-correction methods (i.e., the daily bias correction (DBC) and the local intensity scaling (LOCI)) in order to assess the future hydrological changes in the Himalayan Beas basin up to Pandoh Dam (upper Beas basin). Besides, the glacier extent loss during the 21st century was also investigated as part of the glacio-hydrological modeling as an ensemble simulation. In addition, a high-resolution WRF precipitation dataset suggested much heavier winter precipitation over the high-altitude ungauged area, which was used for precipitation correction in the study. The glacio-hydrological modeling shows that the glacier ablation accounted for about 5 % of the annual total runoff during 1986–2004 in this area. Under climate change, the temperature will increase by 1.8–2.8 ∘ C at the middle of the century (2046–2065), and by 2.3–5.4 ∘ C until the end of the century (2080–2099). It is very likely that the upper Beas basin will get warmer and wetter compared to the historical period. In this study, the glacier extent in the upper Beas basin is projected to decrease over the range of 63 %–87 % by the middle of the century and 89 %–100 % at the end of the century compared to the glacier extent in 2005. This loss in glacier area will in general result in a reduction in glacier discharge in the future, while the future streamflow is most likely to have a slight increase because of the increase in both precipitation and temperature under all the scenarios. However, there is widespread uncertainty regarding the changes in total discharge in the future, including the seasonality and magnitude. In general, the largest increase in river total discharge also has the largest spread. The uncertainty in future hydrological change is not only from GCMs, but also from the bias-correction methods and hydrological modeling. A decrease in discharge is found in July from DBC, while it is opposite for LOCI. Besides, there is a decrease in evaporation in September from DBC, which cannot be seen from LOCI. The study helps to understand the hydrological impacts of climate change in northern India and contributes to stakeholder and policymaker engagement in the management of future water resources in northern India. [ABSTRACT FROM AUTHOR]

In recent years, dramatic decline in China’s largest freshwater lake, Poyang Lake, has raised wide concerns about water supply and ecological crises in the middle–lower Yangtze River reaches. To assist in resolving the debates regarding the low water regime of the lake, the current study quantitatively assessed the enhanced water level decline from the changing underlying surface in the Poyang Lake region. It is the first time that the magnitude, temporal–spatial difference, trend development and background mechanism of lake water level variation and its causes are studied comprehensively. The results revealed that the changing underlying surface in the lake region has caused an average decline of annual water level of 0.26 m ~ 0.75 m across the lake during 2000–2014, which shows great seasonal and spatial differences. The enlarged outflow cross–section due to extensive sand mining was the major reason for the effect on water level decline in the northern lake. While, increased water surface gradient should be attributed to water level decline in the southern lake. The long–term increasing trend of annual lake water level decline reflects the cumulative effects of lake bottom topography change caused by the continuous south movement of sand mining activities. [ABSTRACT FROM AUTHOR]

Climate change has significant implications for glaciers and water resources in the Himalayan region. There is an urgent need to improve our current knowledge and methods in quantifying changes in water resources in this region. This study uses an integrated approach that couples a hydrological model and a glacier retreat model to assess the future water resources for two Himalayan basins. They are the Chamkhar Chhu basin in Bhutan (Eastern Himalayas) and the Beas basin in India (Western Himalayas). The future climate is simulated by two Regional Climate Models (RCMs) for south Asia under three Representative Concentration Pathways (Rcp2.6, Rcp4.5 and Rcp8.5). The six climate projections for the period 2010-2100 indicate significant warming effects; however, projected changes in precipitation are not consistent. Discrepancies in precipitation are noteworthy between the RCMs and greenhouse gases emissions scenarios. The glaciers in the Chamkhar Chhu basin are predicted to disappear or reduce to a small size before the 2050s, whereas the glaciers in the Beas basin are expected to lose mass before the 2060s, and afterwards to gain mass under Rcp2.6 and Rcp4.5, or to melt at a high rate under Rcp8.5. The available water resources per capita of two basins are projected to decrease in the period 2010-2050. The decreasing water resources are jointly induced by climate change and population growth. The latter is responsible for roughly 40 % of the water declines. Both basins are facing water shortages at present and the water shortages will intensify in the future. [ABSTRACT FROM AUTHOR]

Global warming has brought great pressure on the environment and livelihood conditions in Sudan and South Sudan. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Sudan and South Sudan and use it to predict future changes of precipitation; Tmin and Tmax for nine stations in Sudan and South Sudan are based on the SRA2 scenario of seven General Circulation Models (GCMs) outputs for the periods of 2011-2030, 2046-2065, and 2080-2099. The results showed that (1) the LARS-WG model produces good performance in downscaling daily precipitation and excellent performance in downscaling Tmax and Tmin in the study region; (2) downscaled precipitation from the prediction of seven GCMs showed great inconsistency in these two regions, which illustrates the great uncertainty in GCMs' results in the regions; (3) predicted precipitation in rainy season JJA (June, July, and August) based on the ensemble mean of seven GCMs showed a decreasing trend in the periods of 2011-2030, 2046-2065, and 2080-2099 in Sudan; however, an increasing trend can be found in SON (September, October, and November) in the future; (4) precipitation in South Sudan has an increasing trend in most seasons in the future except in MAM (March, April, and May) season in 2011-2030; and (5) predictions from seven GCMs showed a similar and continuous increasing trend for Tmax and Tmin in all three future periods, which will bring severe negative influence on improving livelihoods and reducing poverty in Sudan and South Sudan. [ABSTRACT FROM AUTHOR]

• A method to assess water stress is proposed based on scarcity-variability concept. • This is a first national evaluation of water transfer and storage strategies. • Reservoir operation plays a primary role in alleviating water stress in China. Water transfer and storage are two effective anthropogenic management strategies to alleviate the contradictions between water supply and demand. However, the trade-off and synergistic impacts of management strategies in alleviating water stress remain unclear at the national level. Therefore, this study proposes a framework that integrates the fraction of runoff being withdrawn (scarcity coefficient) and the variation of runoff weighted by reservoir (variability coefficient) to evaluate the multifaceted impacts of management strategies on water stress mitigation. The proposed framework evaluates the changes in both the water supply–demand balance and the historical variability of runoff by considering physical water transfers, virtual water flows, and reservoir operations. This study applied the framework to evaluate the spatiotemporal patterns of water stress and used principal component analysis to estimate the relative contributions of management strategies across ten first-order basins in China for the period of 2014–2018. Results show that water-resource scarcity coefficient varied between −37.15% and 13.28% at the basin scale (the national average varied −5%) and water-resource variability coefficient varied between −100% and −19.26% at the basin scale (the national average varied −61.11%). Management strategies, incorporating water transfer and storage strategies, shifted the distribution patterns of national water stress. The attribution analysis revealed that reservoir storage capacity was the largest contributor to the first principal component representing infrastructure element, whereas the second component representing economic element was affected by the net virtual water inflows. Overall, through exploring the outcomes of combined effects among management strategies, this proposed framework provides a comprehensive perspective for investigating how human activity alleviates regional water stress. [ABSTRACT FROM AUTHOR]

Characterized by increasing surface air temperature, global warming has altered the hydrological cycle at global and regional scales. In order to adapt water resources management under the context of global warming, attribution analysis on regional differentiation of water resources in the Yangtze River basin (YRB) was conducted in this study. Meteoro-hydrological variations across the basin were examined for the period 1960–2013, and then a statistic-based method was applied in quantifying the contributions of climate variability and human activities on annual runoff variations in different tributary sub-basins in the YRB. Our observation indicates that both the annual increasing rate and the inter-annual fluctuations of temperature in China and in the YRB were higher than that of the global average since the turn of the century. Climate change analysis indicates that the YRB experienced a hot-wet period during 1994–2002 and a hot-dry period during 2003–2013, since the step change of temperature in 1993. Contributions of climate change and human activities on runoff variations varied spatially in the basin. With reference to the baseline period of 1960–1993, the contribution of climate change played a dominant role in most regions of the basin, especially in those upstream sub-basins. The effect of human activities in the basin was quite complicated, not only its regional differentiation, but also its contribution were opposite during the hot-wet period and the hot-dry period in some sub-basins. The result of this study is helpful in understanding the impacts of climate change and human activities on water resources variation in both temporal and spatial scales. [ABSTRACT FROM AUTHOR]

Global climate change not only affects the processes within the water cycle but also leads to the frequent occurrences of local and regional extreme drought events. In China, spatial and temporal characterizations of drought events and their future changing trends are of great importance in water resources planning and management. In this study, we employed self-calibrating Palmer drought severity index (SC-PDSI), cluster algorithm, and severity-area-duration (SAD) methods to identify drought events and analyze the spatial and temporal distributions of various drought characteristics in China using observed data and CMIP5 model outputs. Results showed that during the historical period (1961–2000), the drought event of September 1965 was the most severe, affecting 47.07% of the entire land area of China, and shorter duration drought centers (lasting less than 6 months) were distributed all over the country. In the future (2021–2060), under both representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios, drought is projected to occur less frequently, but the duration of the most severe drought event is expected to be longer than that in the historical period. Furthermore, drought centers with shorter duration are expected to occur throughout China, but the long-duration drought centers (lasting more than 24 months) are expected to mostly occur in the west of the arid region and in the northeast of the semi-arid region. [ABSTRACT FROM AUTHOR]

Although landslide early warning and post-assessment is of great interest for mitigating hazards, emergency disposal solutions for properly handling the landslide and dammed lake within a few hours or days to mitigate flood risk are fundamentally challenging. In this study, we report a general strategy to effectively tackle the dangerous situation created by a giant dammed lake with 770 million cubic meters of water volume and formulate an emergency disposal solution for the 25 million cubic meters of debris, composed of engineering measures of floodgate excavation and non-engineering measures of reservoirs/hydropower stations operation. Such a disposal solution can not only reduce a large-scale flood (10,000-year return period, 0.01%) into a small-scale flood (10-year return period, 10%) but minimize the flood risk as well, guaranteeing no death raised by the giant landslide. [ABSTRACT FROM AUTHOR]

Affected by intensive human activities, basin hydrologic systems show characteristics of a dualistic structure. Thus, simulation of hydrological processes needs to consider the social water cycle system to obtain a more accurate result. This study uses a dualistic water cycle simulation system to simulate the hydrological processes affected by intensive human activities, which comprises the natural water cycle system and social water cycle system. The social water cycle system includes the agricultural water cycle system, industrial water cycle system, domestic water cycle system, and cross-regional allocation system. As part of the dualistic water cycle simulation system, an integrated dualistic hydrological model is developed which couples a distributed hydrological simulation module with a water resource allocation module. The integrated modeling approach is applied to the Haihe River basin. The results show that the model performance can be improved when considering coupled simulation of natural and social water cycle systems. This model can also be used to investigate the evolutionary relationships among the natural and social water cycle systems in the study region, and to assess the regional water resources in other basins affected by intensive human activities. [ABSTRACT FROM AUTHOR]

Identifying the links between variations in large-scale climate patterns and precipitation is of tremendous assistance in characterizing surplus or deficit of precipitation, which is especially important for evaluation of local water resources and ecosystems in semi-humid and semi-arid regions. Restricted by current limited knowledge on underlying mechanisms, statistical correlation methods are often used rather than physical based model to characterize the connections. Nevertheless, available correlation methods are generally unable to reveal the interactions among a wide range of climate oscillations and associated effects on precipitation, especially on extreme precipitation. In this work, a probabilistic analysis approach by means of a state-of-the-art Copula-based joint probability distribution is developed to characterize the aggregated behaviors for large-scale climate patterns and their connections to precipitation. This method is employed to identify the complex connections between climate patterns (Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)) and seasonal precipitation over a typical semi-humid and semi-arid region, the Haihe River Basin in China. Results show that the interactions among multiple climate oscillations are non-uniform in most seasons and phases. Certain joint extreme phases can significantly trigger extreme precipitation (flood and drought) owing to the amplification effect among climate oscillations. [ABSTRACT FROM AUTHOR]

Summary Reservoirs are one of the most efficient infrastructures for integrated water resources development and management; and play a more and more important role in flood control and conservation. Optimal refill operation before the end of flood season is a valuable and effective approach to compromise the flood control, hydropower generation and comprehensive utilization of water resources of river basins. An integrated model consisting of a flood control risk analysis module, a utilization benefits analysis module and a multi-objective evaluation module was proposed in this study to derive joint optimal refill rules for cascade reservoirs. The Jinsha River and Three Gorges cascade reservoirs in the Changjiang River basin of China are selected for a case study. Sixty-one years of observed daily runoff data from 1950 to 2010 have been used to test the model. The results indicate that the proposed model can make an effective tradeoff between flood control and utilization benefits. Joint optimal synchronous and asynchronous refill rules can generate 3.25% and 2.78% more annual average hydropower, respectively and improve the fullness storage rate without increasing flood control risk comparing with the original designed operating rules. [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]

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]

In this study, a spatiotemporal estimation method based on Funk singular value decomposition (F-SVD) that considers the spatiotemporal correlation of rainfall is proposed to improve estimations from gauge observations. Hourly rainfall data of several flood events are selected to verify the proposed method by comparing with Inverse Distance Weighting (IDW) and Ordinary Kriging (OK) in Hanjiang basin, China. The results show that (1) F-SVD has the best performance in rainfall estimation, the larger the amount of rainfall event, the greater the improvement of F-SVD method as compared to OK and IDW; (2) through the combination/integration with F-SVD, the accuracy of IDW and OK can be greatly improved. Therefore, F-SVD can be employed as a practical method to estimate rainfall spatial distribution, which is essential data for regional hydrological modelling and water resource analysis. • A spatiotemporal estimation method based on F-SVD is proposed to estimate rainfall using gauge observation. • F-SVD is utilized to decompose the spatiotemporal matrix consisted of rainfall data. • F-SVD has higher accuracy and lower uncertainty compared to OK and IDW. • Through combination with F-SVD, the accuracy of IDW and OK can be greatly improved. • It is a practical method to process data for regional hydrological modelling. [ABSTRACT FROM AUTHOR]

Summary: Large differences in future climatic scenarios found when different global circulation models (GCMs) are employed have been extensively discussed in the scientific literature. However, differences in hydrological responses to the climatic scenarios resulting from the use of different hydrological models have received much less attention. Therefore, comparing and quantifying such differences are of particular importance for the water resources management of a catchment, a region, a continent, or even the globe. This study investigates potential impacts of human-induced climate change on the water availability in the Dongjiang basin, South China, using six monthly water balance models, namely the Thornthwaite–Mather (TM), Vrije Universitet Brussel (VUB), Xinanjiang (XAJ), Guo (GM), WatBal (WM), and Schaake (SM) models. The study utilizes 29-year long records of monthly streamflow and climate in the Dongjiang basin. The capability of the six models in simulating the present climate water balance components is first evaluated and the results of the models in simulating the impact of the postulated climate change are then analyzed and compared. The results of analysis reveal that (1) all six conceptual models have similar capabilities in reproducing historical water balance components; (2) greater differences in the model results occur when the models are used to simulate the hydrological impact of the postulated climate changes; and (3) a model without a threshold in soil moisture simulation results in greater changes in model-predicted soil moisture with respect to alternative climates than the models with a threshold soil moisture. The study provides insights into the plausible changes in basin hydrology due to climate change, that is, it shows that there can be significant implications for the investigation of response strategies for water supply and flood control due to climate change. [Copyright &y& Elsevier]

Conventional frequency analyses are premised on time-invariance (or stationarity) in the parameters of the underlying probability distribution functions (pdfs). With evidence of hydrological impacts of climatic change, low frequency climate variability (e.g. El Nino and Southern Oscillation-ENSO) and other human related stressors such as land use changes, frequency analysis is now a key challenge as it has to incorporate (non-stationarity) or time-variation of the underlying distribution parameters. In this study, frequency analysis of extreme levels of Lake Malawi in Southern Malawi is performed incorporating non-stationarity. The lake is a critical transboundary water resource between Malawi, Mozambique, and Tanzania. The lakeshore areas are prone to extreme lake level variations which affects both infrastructure and life. With the lake undergoing considerable recession since 1980, there is a need to update the design extreme lake levels by incorporating non-stationarity. The study used observed mean lake levels from 1899 to 2017 from which annual maximum (AM) lake levels and partial duration series (PDS) were extracted. In the frequency analysis, the data area were firstly subjected to conventional analyses for evidence of non-stationarity using the Mann-Kendall (MK) test, Kwiatkowski–Phillips–Schmidt–Shin (KPSS) and the Augmented Dickey-Fuller Test (ADF). This was followed by the application of various routines in R software incorporating both stationary and non-stationary frequency analysis approaches such as the generalised additive model for location, scale and shape (GAMLSS) and Maximum likelihoods (ML). Goodness of fit was tested using the Akaike Information Criteria (AIC). The results are very critical in flood zoning especially with various planned infrastructural developments around the lakeshore. [ABSTRACT FROM AUTHOR]

Highlights • Propose successive approximation to solve curse of dimensionality raised in NSGA-II. • NSGA-II with successive approximation optimizes 21 mega-reservoirs’ joint operation. • Lift synergy of hydropower output, flood control, water supply and CO 2 mitigation. Abstract The high complexity of multi-objective joint reservoir operation imposes challenging barriers to the pursuit of optimal hydroelectricity output. Inasmuch as multi-objective evolution optimization algorithms, including the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), are trapped in the curse of dimensionality which could not be effectively solved the multi-objective operation of more than ten reservoirs. This study proposes a methodology that integrate the NSGA-II with a successive approximation approach to optimize the hydropower output for conquering the curse of dimensionality under the joint operation of 21 mega cascade reservoirs located in the Upper Yangtze River Basin of China. The successive approximation approach could effectively decompose the mutually related M-dimensional problem into M individual one-dimensional problems, which ingeniously overcomes the curse of dimensionality. The proposed model is anchored with strategies of advancing impoundment timings and raising water levels of cascade reservoirs. We show that our methodology, without adding or upgrading hydraulic infrastructures, empowers the joint operation to reach 110.79 billion kW·h/year (9.8% improvement) in hydropower output, which could reduce 86.97 billion kg/year in CO 2 emission, and to provide 44.97 billion m3/year in water supply with flood risk less than 0.016. The results suggest that our methodology can spur hydroelectricity output to support China’s tactics in fulfilling the pledge of carbon emission reduction and non-fossil energy expansion to 20% by 2030. [ABSTRACT FROM AUTHOR]

• The path analysis method is proposed to explain the interplay of drivers in soil moisture drought. • Precipitation deficits dominates the interannual variation of soil moisture drought while potential evapotranspiration impacts are magnified by drought deterioration. • Atmospheric movement and temperate indirectly affects soil moisture drought through precipitation and potential evapotranspiration. • Proportion of drought explanation decreased with increasing soil depth. Soil moisture drought, as one of the most important drought categories, is determined by both water supply (e.g., precipitation) and demand (e.g., potential evapotranspiration). To shed light on the underlying mechanisms driving soil moisture drought, the statistical multiple linear regression, machine learning, and modeling experiments methods have been pervasively used in early studies. However, these methods neglect the collinearity and interactions of climate variables, and thus cannot reflect the direct and indirect interaction of factors leading to soil moisture drought. To reveal the synergistic effects of water supply and demand on soil moisture drought, this study quantified the contributions of key drivers to the change of soil moisture drought by a path analysis method to exhibit the relationships between atmospheric movement state and soil moisture drought. Prior to applying the systematic path analysis model, we identified the spatial patterns of soil moisture droughts at different depths by using a state-of-art three-dimensional drought recognition method in China. Our results showed that precipitation deficits dominated the interannual variation of soil moisture drought while increasing potential evapotranspiration only had marginal intensification in drought. The response of soil moisture drought to potential evapotranspiration was magnified by drought deterioration, especially in basically severe drought conditions. The total column water vapor and the horizontal divergence of the vapor flux, as well as temperature, directly affected precipitation and potential evapotranspiration and led to soil moisture drought through various direct and indirect processes. This study highlighted that the interactions among precipitation, potential evapotranspiration, and atmospheric vapor movement state in space and time were important for understanding the drought development mechanisms. [ABSTRACT FROM AUTHOR]

• A novel Encoder-Decoder with an Exogenous input (EDE) structure is proposed. • Four models are evaluated and compared from different perspectives. • The EDE structure is more suitable for long lead-time flood forecasting. • The LSTM-EDE model improves the multi-step-ahead flood forecasting accuracy. Accurate and reliable multi-step-ahead flood forecasting is beneficial for reservoir operation and water resources management. The Encoder-Decoder (ED) that can tackle sequence-to-sequence problems is suitable for multi-step-ahead flood forecasting. This study proposes a novel ED with an exogenous input (EDE) structure for multi-step-ahead flood forecasting. The exogenous input can be the outputs of process-based hydrological models. This study constructs four multi-step-ahead flood forecasting approaches, including the Xinanjiang (XAJ) hydrological model, the single-output long short-term memory (LSTM) neural network with recursive strategies, the recursive ED combined with the LSTM neural network (LSTM-RED), and the LSTM-EDE models. The performance of these four models is evaluated and compared by the long-term 3 h hydrologic data series of the Lushui and Jianxi basins in China. The results show that the LSTM-RED model that integrates recursive strategies into the training process of neural networks is more advantageous than the LSTM model. The proposed LSTM-EDE model can overcome the exposure bias problem, simplify its model structure, increase the computational efficiency in the validation process, and improve the multi-step-ahead flood forecasting accuracy, as compared to the LSTM-RED model. [ABSTRACT FROM AUTHOR]

Summary Changes in lake hydrological regimes and the associated impacts on water supplies and ecosystems are internationally recognized issues. During the past decade, the persistent dryness of Poyang Lake (the largest freshwater lake in China) has caused water supply and irrigation crises for the 12.4 million inhabitants of the region. There is conjecture as to whether this dryness is caused by climate variability and/or human activities. This study examines long-term datasets of catchment inflow and Lake outflow, and employs a physically-based hydrodynamic model to explore catchment and Yangtze River controls on the Lake’s hydrology. Lake water levels fell to their lowest during 2001–2010 relative to previous decades. The average Lake size and volume reduced by 154 km 2 and 11 × 10 8 m 3 during the same period, compared to those for the preceding period (1970–2000). Model simulations demonstrated that the drainage effect of the Yangtze River was the primary causal factor. Modeling also revealed that, compared to climate variability impacts on the Lake catchment, modifications to Yangtze River flows from the Three Gorges Dam have had a much greater impact on the seasonal (September–October) dryness of the Lake. Yangtze River effects are attenuated in the Lake with distance from the River, but nonetheless propagate some 100 km to the Lake’s upstream limit. Proposals to build additional dams in the upper Yangtze River and its tributaries are expected to impose significant challenges for the management of Poyang Lake. Hydraulic engineering to modify the flow regime between the Lake and the Yangtze River would somewhat resolve the seasonal dryness of the Lake, but will likely introduce other issues in terms of water quality and aquatic ecosystem health, requiring considerable further research. [ABSTRACT FROM AUTHOR]

• An improved Budyko framework was proposed to evaluate basin hydrologic resilience to adverse climate change; • All the16 basins except two on the Tibetan plateau have low hydrologic resilience; • Vegetation structure plays an important role in regulating the hydrologic resilience. Climate change has a significant impact on the runoff of basins in cold, dry areas. The quantification of regional ecohydrological responses to climate change such as warming and drought is essential for establishing proper water resource management schemes. We propose a simple and novel method based on the Budyko framework to evaluate the hydrologic resilience of 16 basins that conform the Asian Water Tower in the Tibetan Plateau (TP). Our method defines two metrics within the Budyko domain – tolerance (ψ) and plasticity (φ) – that characterize the hydrologic resilience of a basin. Based on an ecohydrological point of view, a basin is considered hydrologically resilient if ψ and φ are both greater than 1 or its φ is negative and ψ is greater than 1. Our results show that ψ varies between 0.27 and 0.74, with an average value of 0.45 and φ varies between 2 and 16.33, with an average value of 6.90, for 14 out of the 16 basins. Only two basins – Taohe and Datonghe – had negative φ (-11.67 and -8.11, respectively) and ψ greater than 1 (2.26 and 19.58, respectively), suggesting that these two are the only basins with a hydrologic resilience to climatic warming/drying in the TP. Within the non-resilient basins, we found vegetation to play a key role in the level of tolerance and plasticity indicating that basins with a larger vegetation cover display a lower capability to adapt to adverse climatic changes. Following these results, we call for afforestation efforts to be carefully considered in cold, dry areas. The proposed method and conclusions drawn by this study may help predict the hydrologic responses to future adverse climatic conditions. [ABSTRACT FROM AUTHOR]

• Propose a multi-objective method to raise mutual benefits of water-food-energy nexus. • Floating photovoltaic deployment on ponds drives up renewable energy output. • Hybrid hydro-floating photovoltaic power generation raises energy efficiency. • Energy-driven solutions improve water-food-energy nexus management. Hybrid hydropower and floating photovoltaic power generation has far-reaching effects on the intertwined water, food and energy (WFE) nexus, but the complementary operation is fundamentally challenging especially under high uncertainties of hydro-meteorological conditions. This study proposed an artificial intelligence-based WFE system-overarching solution driven by hybrid hydro-floating photovoltaic power generation for promoting nexus synergies. A multi-objective optimization model grounded upon the Grasshopper Optimization Algorithm was developed to simultaneously maximize hydro-floating photovoltaic power output, the ratio of water storage to reservoir capacity, and the ratio of water supply to water demand. The Shihmen Reservoir watershed and its WFE system in northern Taiwan constituted the case study. The results demonstrated that the proposed optimization model could significantly improve synergistic benefits of the WFE nexus by reaching 13%, 13.3% and 15.1% in water storage, food production and hydro-floating photovoltaic power output, respectively. The optimal tilt angles of floating photovoltaic installation would vary between −11.9° (Summer) and 44.3° (Winter). This study opens up new perspectives on green energy production expansion while stimulating WFE nexus synergies in support of policy-makers with feasible schemes on floating photovoltaic deployment in the interest of social sustainability. In consequence, new niches are exploited for floating photovoltaic deployment and give rise to impact mitigation concerning hydro-meteorological uncertainties on WFE nexus management. [ABSTRACT FROM AUTHOR]

Global hydrological models (GHMs) have been developed to calculate the water balance on global or continental scales which is essential for water resources management. The hydrological processes are complex, heterogeneous, and hardly characterized by laboratory and field measurements, especially for the evapotranspiration (ET) rate because of the difficulties of directly measuring atmospheric vapor flux. As a result, practical theories of potential ET (PET) and their impact on runoff generation remain elusive. PET/ET methods in GHM can behave differently because of different assumptions and input requirements. In this study, we assess the variations of the water balance components in Europe based on six PET methods, i.e., Penman-Monteith (PM), radiation-based Priestley-Taylor (PT), radiation-based Turc, temperature-based Hargreaves, an empirical temperature-based (empirical-T) method, and a PET product of Global Land Evaporation Amsterdam Model (GLEAM). Besides, a global Macro-scale Water and Snow Balance Modeling System (WASMOD-M) is calibrated at daily time step based on 66 gauged watersheds in Europe and applied with two regionalization methods (i.e., the Global mean method and the Koppen method) at the 0.5°×0.5° grid scale for the 1997-2008 period. Results show that (1) the Turc and empirical-T methods derive similar results of water balance with that of GLEAM while largely different from that of PT and PM; (2) the empirical-T and Turc methods show a slight decrease, while others show a slightly increase trend in Europe on average; as for the seasonal PET, all methods show a slight increase in spring and autumn and a slight decrease in winter; (3) all methods indicate that the increase of PET and Actual ET (AET) in central Europe is more obvious than other parts of Europe; and (4) different methods derive a similar spatial distribution of PET and runoff in Europe although they vary considerably in the quantity. Further study is in progress to characterize surface processes and to investigate the differences of water balance component regarding the assumptions of PET methods. [ABSTRACT FROM AUTHOR]