Spatiotemporal characteristics of meteorological drought events in 34 major global river basins during 1901-2021.

Meteorological drought is a crucial driver of various types of droughts; thus, identifying the spatiotemporal characteristics of meteorological drought at the basin scale has implications for ecological and water resource security. However, differences in drought characteristics between river basins have not been clearly elucidated. In this study, we identify and compare meteorological drought events in 34 major river basins worldwide using a three-dimensional drought-clustering algorithm based on the standardised precipitation evapotranspiration index on a 12-month scale from 1901 to 2021. Despite synchronous increases in precipitation and potential evapotranspiration (PET), with precipitation increasing by more than three times the PET, 47 % (16/34) of the basins showed a tendency towards drought in over half their basin areas. Drought events occurred frequently, with more than half identified as short-term droughts (lasting less than or equal to three months). Small basins had a larger drought impact area, with major drought events often originating from the basin boundaries and migrating towards the basin centre. Meteorological droughts were driven by changes in sea surface temperature (SST), especially the El Niño Southern Oscillation (ENSO) or other climate indices. Anomalies in SST and atmospheric circulation caused by ENSO events may have led to altered climate patterns in different basins, resulting in drought events. These results provide important insights into the characteristics and mechanisms of meteorological droughts in different river basins worldwide.

Emerging trends and spatial shifts of drought potential across global river basins.

Droughts have devastating effects on various sectors and are difficult to quantify and track because of the invisible and slow but prevalent propagation. This dilemma is more significant in the case of the complex interactions between land and atmosphere mechanisms, which are inadequately considered in previous drought metrics. Here, we investigate the spatiotemporal variability of the recently devised metric called 'Drought Potential Index (DPI)', which incorporates the antecedent land water storage and current precipitation. Using the spatial weighted centroid method, we elucidate the emerging spatial movement of the DPI within 168 major global river basins and analyze its influential factors. Improved drought detection and performance disparity of DPI as compared with multi-scale (i.e., 1, 3, 6, 9, 12-month) Standardized Precipitation Index, ensemble soil moisture anomaly, and Total Storage Deficit Index corroborate the robustness and improved insights of DPI. Higher increasing trends in DPI are detected over dryland basins (0.39 ± 0.43 %/a) than in the humid zones (0.15 ± 0.34 %/a). Six hotspot basins, namely, Don, Yellow, Haihe, Rio Grande, Sao Francisco, and Ganges river basins, are identified with increasing (2.1-3.5%/a) DPI during 2003-2021. The interannual occurrence of the highest DPI, spatial shifts, and relative contribution of DPI's constituent variables correspond well to the climatic and anthropogenic changes in humid and dry land basins. The absolute latitudinal/longitudinal shifts of ∼2° (as high as ∼3.2/4.9°) in DPI in 30% (47 out of 168 basins) of the global basins highlight the need for analyzing the water scarcity problems from both the perspectives of long-term trends and spatial shifts. Our findings provide a global assessment of the spatiotemporal shifts of drought potential and will be beneficial to understanding the anthropogenic and climatic influences on water resource management under a changing environment.

[Relationship Between Precipitation, River Water, and Groundwater Conversion in the Upper Reaches of Xilin River During the Rainy Season].

To deeply understand the hydrological cycle process and the transformation mechanism of different water bodies in the grassland inland river basin, the atmospheric precipitation, river water, and groundwater in the Xilin River Basin were taken as the research objects, the hydrogen and oxygen stable isotopes were analyzed, and the multi-scale spatio-temporal characteristics were analyzed to explore the quantitative transformation relationship between different water bodies in the basin. The results showed that:① the Xilin River Basin had an obvious inland semi-arid climate, the atmospheric precipitation was the main source of recharge for the river water and groundwater, and the groundwater and river water experienced different degrees of non-equilibrium evaporation at the same time. ② The isotopic composition of the river water showed the characteristics of depletion in spring and autumn and enrichment in summer and showed a trend of increasing from upstream to downstream in space. The variation in δ18O in shallow and deep groundwater during the growing season was basically the same, and the main difference between the two occurred at the end of the growing season, that is, the former tended to be stable, whereas the latter showed an upward trend, which reflected that the deep groundwater had a lagged response to the infiltration and recharge of atmospheric precipitation and surface water, and both of them were depleted gradually from southeast to northwest in space. ③ Based on the estimation results of the endmember mixing model, the average recharge ratio of atmospheric precipitation and shallow groundwater to river water in summer was 52.69% and 47.31%, respectively, indicating that shallow groundwater was an important recharge source of river water in the inland river basin even during the rainy season. The results of this study provide theoretical guidance for water resource regulation and ecological environment protection in a typical semi-arid grassland inland river basin.

Interkingdom ecological networks between plants and fungi drive soil multifunctionality across arid inland river basin.

Despite the known collective contribution of above- (plants) and below-ground (soil fungi) biodiversity on multiple soil functions, how the associations among plant and fungal communities regulate soil multifunctionality (SMF) differentially remains unknown. Here, plant communities were investigated at 81 plots across a typical arid inland river basin, within which associated soil fungal communities and seven soil functions (nutrients storage and biological activity) were measured in surface (0-15 cm) and subsurface soil (15-30 cm). We evaluated the relative importance of species richness and biotic associations (reflected by network complexity) on SMF. Our results demonstrated that plant species richness and plant-fungus network complexity promoted SMF in surface and subsurface soil. SMF in two soil layers was mainly determined by plant-fungus network complexity, mean groundwater depth and soil variables, among which plant-fungus network complexity played a crucial role. Plant-fungus network complexity had stronger effects on SMF in surface soil than in subsurface soil. We present evidence that plant-fungus network complexity surpassed plant-fungal species richness in determining SMF in surface and subsurface soil. Moreover, plant-fungal species richness could not directly affect SMF. Greater plant-fungal species richness indirectly promoted SMF since they ensured greater plant-fungal associations. Collectively, we concluded that interkingdom networks between plants and fungi drive SMF even in different soil layers. Our findings enhanced our knowledge of the underlying mechanisms that above- and below-ground associations promote SMF in arid inland river basins. Future study should place more emphasis on the associations among plant and microbial communities in protecting soil functions under global changes.

Super ensemble based streamflow simulation using multi-source remote sensing and ground gauged rainfall data fusion.

Traditional data-driven streamflow predictions usually apply a single model with inconsistent performance in different variability conditions. These days model ensembles or merging the benefits of different models without losing the general character of the data are becoming a trend in hydrology. This study compared three super ensemble learners with eight base models. Twelve years of monthly rolled daily time series data in three river catchments of Ethiopia (Borkena watershed: Awash river basin), (Gummera watershed: Abay river basin), and (Sore watershed: Baro Akobo river basin) is used for single-step daily streamflow simulation using previous thirty-day input timesteps. Five input scenarios are applied: three vegetation indices, three remote sensing-based precipitation products, ground-gauged rainfall, all fused inputs, and selected inputs with the Recursive Feature Elimination (RFE) algorithm. The time series is then divided into training and testing datasets with a ratio of 80:20. The performance of the proposed models was evaluated using the Root Mean Squared Error (RMSE), coefficient of determination (R2), Mean Absolute Error (MAE), and Median Absolute Error (MEDAE). Finally, the result is presented with the corresponding five input scenarios. The catchment's and input scenario's average performance indicated that the three super ensemble learners outperformed the eight base models with relatively stable performance. The top-ranked WASE model exceeded the linear regression baseline by 13.3%. XGB, CNN-GRU, and LSTM proved the highest performance of the base models. This study also revealed that LSTM's key downside is its performance drop in the absence of feature selection criteria. In comparison, XGB showed its superior performance after controlling redundant inputs internally. Moreover, this study uniquely highlights the potential of remote sensing-based vegetation indices in the science of data-driven streamflow modelling for non-gauged catchments with no meteorological time series.

Impacts of climate change and anthropogenic stressors on runoff variations in major river basins in China since 1950.

Runoff is one of the main components of hydrological cycle and an important index for water resources evaluation, understanding the runoff change and their causes is vital to water resource management. In the study, we analyzed the runoff change and the impacts of climate change and land use alteration on runoff variation based on natural runoff and previous studies in China. The results showed that there was a significant increasing trend in the annual runoff during 1961-2018 (p < 0.05), with change rate of 0.4 mm/a and abrupt point at 1999 across China, climate change dominated the runoff variation with a contribution of 54 %. In previous studies, the runoff of the major basins in China had a downward trend on the whole (-0.99 mm/a) except Continental River Basin (CRB) showed an increasing trend (0.25 mm/a), the abrupt points were mainly concentrated in 1991-2000, and human activity was the leading factor of runoff change with the contribution of 54 % across China. Human activity was the dominant factor of runoff change in Songhua and Liao River Basin (SLRB), Yellow River Basin (YRB), Hai River Basin (HRB) and Pearl River Basin (PRB), the contribution was >56 %, while climate change was the dominant factor of runoff change in Huai River Basin (HuRB), CRB, and Yangtze River Basin (YZRB). Overall, there was a significant correlation between runoff and precipitation, unused land, urban and grassland in China. We concluded that runoff change and the contribution of climate change and human activities varies greatly among different basins. The findings in this work can shed light on the quantitative understanding of runoff changes in national scale and offer a scientific basis for sustainable water management.

Impact of COVID-19 lockdown on water quality in China during 2020 and 2022: two case surges.

The COVID-19 severely affected the world in 2020. Taking the two outbreaks in China in 2020 and 2022 as examples, the spatiotemporal changes in surface water quality levels and CODMn and NH3-N concentrations were analyzed, and the relationships between the variations in the two pollutants and environmental and social factors were evaluated. The results showed that during the two lockdowns, due to the total water consumption (including industrial, agricultural, and domestic water) decreased, the proportion of good water quality increased by 6.22% and 4.58%, and the proportion of polluted water decreased by 6.00% and 3.98%, the quality of water environment has been improved significantly. However, the proportion of excellent water quality decreased by 6.19% after entering the unlocking period. Before the second lockdown period, the average CODMn concentration exhibited a "falling, rising, and falling" trend, while the average NH3-N concentration changed in the opposite direction. The correlation analysis revealed that the increasing trend of pollutant concentrations was positively correlated with longitude and latitude, and weakly correlated with DEM and precipitation. A slight decrease trend in NH3-N concentration was negatively correlated with the population density variation and positively correlated with the temperature variation. The relationship between the change in the number of confirmed cases in provincial regions and the change in pollutant concentrations was uncertain, with positive and negative correlations. This study demonstrates the impact of lockdowns on water quality and the possibility of improving water quality through artificial regulation, which can provide a reference basis for water environmental management.

Oceanic and terrestrial origin of precipitation over 50 major world river basins: Implications for the occurrence of drought.

The terrestrial and oceanic origins of precipitation over 50 major river basins worldwide were investigated for the period 1980-2018. For this purpose, we used a Lagrangian approximation that calculates the humidity that results in precipitation from the entire ocean area (ocean component of the precipitation, PLO) and the entire land area (land component, PLT) as well as the sum of both components (Lagrangian precipitation, PL). PL and its components were highly correlated with precipitation over the basins, where PLT accounted for >50 % of the PL in most of them. This confirmed the importance assigned by previous studies to terrestrial recycling of precipitation and moisture transport within the continents. However, the amount of PLO in almost all North American river basins was highlighted. The assessment of drought conditions through the Standardized Precipitation Index (SPI) at a temporal scale of 1- and 3-months revealed the number of drought episodes that affected each river basin, especially the Amazon, Congo, and Nile, because of the lower number of episodes but higher average severity and duration. A direct relationship between the severity of drought episodes and the respective severity computed on the oceanic and terrestrial SPI series was also found for the majority of basins. This highlights the influence of the severity of the SPI of oceanic origin for most basins in North America. However, for certain basins, we found an inverse relationship between the severity of drought and the associated severity according to the SPI of oceanic or terrestrial origin, thus highlighting the principal drought attribution. Additionally, a copula analysis provided new information that illustrates the estimated conditional probability of drought for each river basin in relation to the occurrence of drought conditions of oceanic or terrestrial origin, which revealed the possible main driver of drought severity in each river basin.

Linking Land Use Land Cover change to global groundwater storage.

Groundwater storage is facing the constant threat of over-exploitation and irreversible depletion, often attributed to agricultural and industrial usage as well as human mismanagement. While several methodologies, varying from well logs to gravity recovery data, have been successfully adopted over the years to track and mitigate groundwater loss, Land Use and Land Cover (LULC) has never been quantified to evaluate groundwater storage and variability. LULC change alters the hydrological connectivity between the surface and subsurface water. Towards this, we employed a decision tree based Machine Learning model to (a) identify hydrological and terrestrial drivers affecting groundwater resources, (b) predict shallow and deep groundwater variability, (c) rank the drivers according to their impact on groundwater distribution, and (d) understand groundwater distribution as a function of LULC change. The model was developed globally, and then extended to basinal scale observations in the Indus, Ganga and Brahmaputra rivers of the Indian subcontinent. Model output has helped to (a) compute the 'infiltration index' associated with each Land Cover, (b) equate cropland expansion among the three basins with shallow and deep groundwater storage and (c) link LULC-groundwater change to crop yield. RCP 2.6 crop yield estimates for the 21st century proves detrimental to Indian food and freshwater security, given the strong coupling of groundwater-LULC among the three basins and how Land Cover change translates to groundwater storage.

Optimization of water quality monitoring programs by data mining.

Water quality monitoring programs are essential planning and management tools, but they face many challenges in the developing world. The scarcity of financial and human resources and the unavailability of infrastructure often make it impossible to meet the legal requirements of water monitoring. Many approaches to optimizing water quality monitoring programs have already been proposed. However, few investigations have developed and tested data mining for this purpose. This article has developed data-based models to reduce the number of water quality parameters of monitoring programs using data mining. The objective was to extract patterns from the database, expressed by association rules, which together with field parameters, measured with automatic probes, can estimate laboratory variables. This approach was applied in 35 monitoring stations along 27 river basins throughout Brazil. The data are from fifty years of monitoring (1971-2021), constituting 6328 observations of 60 water quality parameters investigated in different environmental contexts, water quality, and the structuring of monitoring programs. With the applied approach it was possible to estimate 56% of the laboratory parameters in the monitoring stations investigated. The influence of environmental characteristics on the optimization capacity of monitoring programs was evident. The methodology used was not influenced by different water quality levels and anthropogenic impacts. However, the number of parameters was the most influential element in optimization. Monitoring programs with 20 or more water quality variables have the highest potential (≥44%) of optimization by this methodology. Results demonstrate that this approach is a promising alternative that can reduce the frequency of analyses measured in the laboratory and increase the spatial and temporal coverage of water quality monitoring networks.

Root attributes dominate the community assembly of soil fungal functional guilds across arid inland river basin.

Plant attributes are increasingly acknowledged as key drivers shaping soil fungal communities, but considerable uncertainty exists over fungal community assembly mechanisms and their plant drivers based only on inferences from plant aboveground attributes. To date, empirical evidences of how root attributes are integrated into microbiome-plant linkages remain limited. Using 162 soil samples from a typical arid inland river basin in China, we assessed the drivers that regulate the distribution patterns and assembly processes of total, mycorrhizal, saprotrophic and pathotrophic fungi in surface (0-15 cm) and subsurface soils (15-30 cm). Total fungi and fungal functional guilds exhibited similar distribution patterns in arid inland river basins. Null-model and variance partitioning analysis revealed that the heterogeneous selection induced by root attributes, rather than dispersal limitation, predominated the fungal community assembly. Multiple regressions on matrices further demonstrated that specific root length were the most important predictors of fungal community assembly, which mediated the balance of assembly processes of soil fungal communities. Heterogeneous selection decreased for total, mycorrhizal and saprotrophic fungi, but increased for pathotrophic fungi with increasing specific root length. Additionally, fine-root biomass exerted important effects on fungal assembly processes in subsurface soil but not in surface soil, suggesting root attributes differently affected fungal community assembly between surface and subsurface soil. Collectively, our study highlights the importance of considering root attributes in differentiating the balance of stochastic and deterministic processes in microbial community assembly.

Evaluating stakeholder engagement in collaborative research: co-producing knowledge for climate resilience.

This study describes the development, implementation, and evaluation of an initial stakeholder engagement experience designed to facilitate knowledge co-production. The engagement experience is part of a collaborative research framework (CRF), which facilitates iterative interactions among diverse researchers and stakeholders around the topic of enhanced climate resilience. Here, we describe the: (1) need for and development of a CRF as it relates to stakeholder engagement and knowledge co-production; (2) implementation of the initial engagement experience, focused around individual semi-structured interviews, in the context of a snow-dependent, arid river basin where historical water over allocation, climate change, and diversified water uses challenge the basin's resilience; and (3) formative evaluation of the engagement experience using an online survey to inform the development of more effective engagement practices. Results of the evaluation indicate that, after participating, most stakeholders understand and recognize the importance of research goals, demonstrate positive attitudes toward collaborative research and researchers, view their contribution of knowledge and expertise as critical to research, and perceive researchers as eager to use their expertise. Moreover, stakeholders emphasized various context-specific goals for knowledge co-production, such as finding innovative ways to adapt to increased competition for diminishing water supplies. To achieve these goals, stakeholders suggested researchers learn about their basin, including its water allocation history and agricultural practices. These results highlight the importance of centering stakeholder engagement experiences within a broader CRF and formatively evaluating such experiences to adapt them to achieve research goals.

A disaggregated assessment of national water security: An application to the river basins in Thailand.

Achieving water security is a global concern in the age of changing climate, population increase, urbanization, intensive socio-economic development, and land-use change. Addressing water security challenges is most appropriate at the river basin scale since hydrological boundaries at which water flows differ from administrative boundaries, and it can provide policymakers and decision-makers key insights to better support water management practices. This study carries out a disaggregated assessment of national water security by applying an indicator-based framework to evaluate water security conditions in all twenty-five river basins of Thailand from 2007 to 2015. The framework comprises five broad dimensions and eleven indicators. The study results revealed that the overall water security condition in Thai river basins has improved during this period. However, a fine-grained analysis at the dimensions and indicator level of water security shows that water productivity and the watershed health dimension are of concern in most river basins. The agricultural water productivity and the wastewater treatment capacity have deteriorated over the years in most basins. Likewise, it emerged that basins need to enhance their water resource management plans to account for future water challenges. The water security assessment framework presented in this study links well to the plans, policies, visions, and strategies developed for water resource management in Thailand. Thus, it can act as a decision-support tool to monitor the effectiveness of these plans and policies developed and arrive at interventions to enhance Thailand's water security.

Freshwater discharge from the large and coastal peninsular rivers of India: A reassessment for sustainable water management.

This study offers an updated mean annual water discharge of 10 large and 11 coastal basins of the Indian Peninsula and looks into environmental parameters influencing the water flux and discharge trends. The mean annual discharge of large and coastal rivers is estimated to be 221 and 294 km3. Thus, despite draining 25% of the Indian Peninsula, coastal rivers deliver more than half of the annual flux, and west-flowing coastal rivers contribute 85% of it. This study demonstrates temporal changes in the water discharge of various river basins. The presence of dams regulates discharge regimes of large rivers. The construction of large dams resulted in a significant decline in the water discharge of the Krishna, Cauvery, and Narmada. Through this study, we demonstrate the role of rainfall, catchment size, water loss through evapotranspiration and infiltration, and societal use of water in determining the runoff of each basin. We recommend tapping the water resources of the west-flowing rivers for proper planning, development, and management to reduce the water stress in the peninsular region and promoting sustainable management.

Multi-scale analysis of the characteristics of the changing landscape of the typical mountainous region of Southwest China over the past 40 years.

CONTEXT: Yunnan Province is an important ecological security barrier in China. This study investigated the temporal and spatial changes to landscape ecology and is of great significance for guiding landscape protection and future socio-economic development. OBJECTIVES: To analyze the temporal and spatial changes of the landscape patterns at the county, river basin, and provincial levels, and clarify and describe the temporal and spatial differentiation characteristics of the landscape patterns in Yunnan Province. METHODS: Based on landscape ecology, GIS spatial analysis, and spatio-temporal change analysis, nine landscape pattern indices, and spatial autocorrelation for different years, were calculated. RESULTS: The landscape of Yunnan Province has evolved as a whole toward isolation. The indices of separation and fragmentation changed significantly from 2010 to 2015. From 2015 to 2018 the rate of fragmentation decreased. Fragmentation in the Nu Jiang and Irrawaddy River basins was less than in other basins. The landscape patterns of the Jinsha and Pearl River basins were relatively fragmented due to human activity, socioeconomic development, and utilization. The differences between the Lancang and Red River Basins were relatively small and at an intermediate level. CONCLUSIONS: Spatial autocorrelation analysis indicated that there are three areas with typical clusters, namely the Hengduan Mountains where the degree of fragmentation of the landscape was low, while landscape connectivity and aggregation were high. The subtropical region of Southern Yunnan displayed high landscape heterogeneity, a complex shape index, and high connectivity and sprawl. Central Yunnan exhibited a fragmented landscape with poor connectivity and aggregation. These three regions correspond with "the three screens and two belts" in the Main Functional Planning Area of Yunnan Province.

Carbon Storage Change Analysis and Emission Reduction Suggestions under Land Use Transition: A Case Study of Henan Province, China.

The significant spatial heterogeneity among river basin ecosystems makes it difficult for local governments to carry out comprehensive governance for different river basins in a special administrative region spanning multi-river basins. However, there are few studies on the construction of a comprehensive governance mechanism for multi-river basins at the provincial level. To fill this gap, this paper took Henan Province of China, which straddles four river basins, as the study region. The chord diagram, overlay analysis, and carbon emission models were applied to the remote sensing data of land use to analyze the temporal and spatial patterns of carbon storage caused by land-use changes in Henan Province from 1990 to 2018 to reflect the heterogeneity of the contribution of the four basins to human activities and economic development. The results revealed that food security land in the four basins decreased, while production and living land increased. Ecological conservation land was increased over time in the Yangtze River Basin. In addition, the conversion from food security land to production and living land was the common characteristic for the four basins. Carbon emission in Henan increased from 134.46 million tons in 1990 to 553.58 million tons in 2018, while its carbon absorption was relatively stable (1.67-1.69 million tons between 1990 and 2018). The carbon emitted in the Huai River Basin was the main contributor to Henan Province's total carbon emission. The carbon absorption in Yellow River Basin and Yangtze River Basin had an obvious spatial agglomeration effect. Finally, considering the current need of land spatial planning in China and the goal of carbon neutrality by 2060 set by the Chinese government, we suggested that carbon sequestration capacity should be further strengthened in Yellow River Basin and Yangtze River Basin based on their respective ecological resource advantages. For future development in Hai River Basin and Huai River Basin, coordinating the spatial allocation of urban scale and urban green space to build an ecological city is a key direction to embark upon.

Influences of Shifted Vegetation Phenology on Runoff Across a Hydroclimatic Gradient.

Climate warming has changed vegetation phenology, and the phenology-associated impacts on terrestrial water fluxes remain largely unquantified. The impacts are linked to plant adjustments and responses to climate change and can be different in different hydroclimatic regions. Based on remote sensing data and observed river runoff of hydrological station from six river basins across a hydroclimatic gradient from northeast to southwest in China, the relative contributions of the vegetation (including spring and autumn phenology, growing season length (GSL), and gross primary productivity) and climatic factors affecting the river runoffs over 1982-2015 were investigated by applying gray relational analysis (GRA). We found that the average GSLs in humid regions (190-241 days) were longer than that in semi-humid regions (186-192 days), and the average GSLs were consistently extended by 4.8-13.9 days in 1982-2015 period in six river basins. The extensions were mainly linked to the delayed autumn phenology in the humid regions and to advanced spring phenology in the semi-humid regions. Across all river basins, the GRA results showed that precipitation (r = 0.74) and soil moisture (r = 0.73) determine the river runoffs, and the vegetation factors (VFs) especially the vegetation phenology also affected the river runoffs (spring phenology: r = 0.66; GSL: r = 0.61; autumn phenology: r = 0.59), even larger than the contribution from temperature (r = 0.57), but its relative importance is climatic region-dependent. Interestingly, the spring phenology is the main VF in the humid region for runoffs reduction, while both spring and autumn growth phenology are the main VFs in the semi-humid region, because large autumn phenology delay and less water supply capacity in spring amplify the effect of advanced spring phenology. This article reveals diverse linkages between climatic and VFs, and runoff in different hydroclimatic regions, and provides insights that vegetation phenology influences the ecohydrology process largely depending on the local hydroclimatic conditions, which improve our understanding of terrestrial hydrological responses to climate change.

Analysis of variations and controls of evapotranspiration over major Indian River Basins (1982-2014).

This study analyses long-term (1982-2014) estimates of evapotranspiration (ET) over four major river basins of India with the primary objective of understanding the factors controlling its space-time variability. Here we utilize terrestrial water storage change (TWSC) estimates, computed from WaterGAP Global Hydrology Model (WGHM) simulations, in monthly water balance computations to obtain the best available estimates of long-term ET for the study region. Trend analysis shows significant increase in annual ET over Ganga (2.72 mm/year) and Krishna (3.90 mm/year) River Basins, while in Godavari and Mahanadi River Basins the observed trends are insignificant. The relative contribution of potential factors (represented by precipitation, soil moisture, temperature and Normalized Difference Vegetation Index (NDVI)) that affect the variability of monthly ET is assessed using Hierarchical Partitioning Analysis (HPA). Results reveal that ET variance is largely controlled by the availability of water (represented by precipitation and soil moisture) in all the river basins. Precipitation (soil moisture) accounts for 65% (16%), 70% (20%), 77% (15%) and 67% (18%) of the variability in monthly ET over the Ganga, Godavari, Krishna and Mahanadi River Basins, respectively. Similarly, highest contributions from precipitation are also observed in annual scale variations of ET in all the river basins. Multiple regression analysis performed to assess the overall influence of controlling variables demonstrate that precipitation, soil moisture, temperature and NDVI explain 84% (Ganga), 86% (Godavari), 91% (Krishna) and 82% (Mahanadi) of variations observed in monthly ET over the respective basins. Results presented in this study have major implications for the understanding of ET variability, appropriateness and discrepancies in different ET products and compliment the contemporary efforts of extending GRACE-based ET estimates in space and time.

Damn those damn dams: Fluvial longitudinal connectivity impairment for European diadromous fish throughout the 20th century.

River longitudinal connectivity is crucial for diadromous fish species to reproduce and grow, its fragmentation by large dams may prevent these species to complete their life cycle. This work aims to evaluate the impact of large dams on the structural longitudinal connectivity at the European scale, from a Diadromous fish species perspective, since the beginning of the 20th century until the early 21st century. Based on large dam locations and completion year, a multitude of river impairment metrics were calculated at three spatial scales for six European oceanic regions and 12 time periods. The number of basins affected by large dams is overall low (0.4%), but for large river basins, that cover 78% of Europe's area, 69.5% of all basins, 55.4% of the sub-basins and 68.4% of river length are impaired. River network connectivity impairment became increasingly significant during the second half of the 20th century and is nowadays spatially widespread across Europe. Except for the North Atlantic, all oceanic regions have over 50% of impacted river length. Considering large river basins, the Mediterranean (95.2%) and West Atlantic (84.6%) regions are the most affected, while the Black (92.1%) and Caspian (96.0%) regions stand out as those with most compromised river length. In 60 years, Europe has gone from reduced impairment to over two-thirds of its large rivers with structural connectivity problems due to large dams. The number of such barriers increased significantly in the second half of the 20th century, especially main stem dams with decreasing distance to the river mouth. Currently, the structural longitudinal connectivity of European river networks is severely impacted. This concerns all regions considered, and those in southern Europe will face even higher challenges, given that this will be a future hot spot for hydropower development and predictably more affected by climate change.

System Dynamics Model for Evaluating Socio-Economic Impacts of Different Water Diversion Quantity from Transboundary River Basins-A Case Study of Xinjiang.

With the rapid development of social economy and global climate warming, scarce transboundary water resources, as one of the basic resources for socio-economic development, have increasingly become the focus of basin countries. To investigate the socio-economic impacts of different water diversion quantity from transboundary river basins, we used a system dynamics (SD) model to reflect interactions between population, water resources, and socio-economic development, and applied it to a case study in Xinjiang to simulate its change tendency from 2011 to 2030 from the temporal dimension. Then, four water diversion quantity of transboundary river basins and four alternative socio-economic development patterns were designed to comprehensively evaluate these impacts of water diversion quantity change on the socio-economy of the region along the river under different socio-economic development patterns. The results indicate that (1) there was a positive correlation between water diversion quantity and the economic output value of the region along transboundary river basins, and the marginal benefit of transboundary water resources would decrease gradually; (2) considering the difficulty of water diversion from transboundary river basins and the protection of downstream water use and ecological health of transboundary river basins, we believe that increasing the transboundary water resources by 20% was more conducive to the sustainable development of Xinjiang's socio-economy; (3) through the comparison of dynamic evolutions of socio-economic development and water impacts under four socio-economic development patterns, it is best for Xinjiang to plan its future development in the coordinated development of economic-resource scenario. Following this scenario, not only would the total output value of the socio-economy be better than other scenarios, but this also helps to alleviate the contradiction between the water supply and demand, which expected there would be a water shortage of 1.04 billion m3 in 2029 under 20% increase in water diversion quantity. Therefore, appropriate water diversion quantity, reasonable adjustment of industrial production growth rate, reduction of water consumption quotas of different industries and domestic water quota, and improvement of collection and treatment rate for sewage should be given priority in water resources management decision-making in Xinjiang or other arid regions along transboundary river basins.