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• Probability of slight drought was higher than moderate drought. • Range of single probability of slight drought was 26.15 to 41.06% • Range of joint probability of droughts in moderately was 3.76 to 31.32% Documenting the joint probability of meteorological-hydrological, meteorological-agricultural, and hydrological-agricultural drought can be invaluable for understanding drought evolution under climate change in a high-diversity watershed of south China. Through constructing the edge and joint distribution functions of multi drought indices (SPEI, SPI, SSI, and SWI) based on SWAT and copula methods, we explored the evolution of multi droughts under climate change in the East River basin. During 1997–2017 and 2023–2099, we used logistic, generalized pareto, and normal distributions to construct edge distribution functions of SPEI, SPI, SWI, and SSI. For the four indices, the probability of slight drought increased with rcp2.6, 4.5, 6.0, and 8.5, and it was higher than moderate drought. Also, Clayton, Frank, Gumbel, and Gaussian copula functions were used to construct joint distribution functions of SPEI and SSI, SPEI and SWI, SSI and SWI to quantify their interactions. During 1997–2017, the probability of slight drought was 26.15 to 41.06 %, and the return period changed from 3.8 to 2.4 years. The joint probability of meteorological-hydrological, meteorological-agricultural, and hydrological-agricultural drought in slightly was 24.4 to 31.32 %, 14.95 to 22.63 %, and 6.18 to 22.05 %, respectively. During 2023–2099, the joint probability of droughts in moderately was 3.76 to 14.19 %, and the return period was 7 to 26.6 years. Our results provide a quantitative assessment of single and joint probability of meteorological, hydrological and agricultural drought, which could be used to support watershed water resource management. [ABSTRACT FROM AUTHOR]

Understanding the changes in hydrological process is a key subject for water resource management of a high-diversity watershed. In this paper, through an establishment of a SWAT-based model, the effects of climate change and its induced vegetation change on hydrological process were analyzed in the East River Basin. The model could well simulate the hydrological processes of the basin including surface runoff (SURQ), groundwater (GWQ), lateral flow (LATQ), total water yield (WYLD), actual evapotranspiration (ET), and groundwater recharge (PERC). Under the vegetation change induced by temperature increase, the effects of the vegetation change on hydrological process were larger than that of the temperature change. Under the vegetation change caused by the increase of temperature and precipitation, the vegetation change enhanced the effects of climate change on annual SURQ, LATQ, GWQ, WYLD, and PERC of the basin. Under spatial scale, when the temperature and precipitation changed simultaneously, the increase of precipitation could promote the increase of annual ET in sub-watersheds. Also, the annual SURQ, WYLD, GWQ and ET in western sub-watersheds were more sensitive to the cumulative changes of vegetation and climate. This work can provide useful information to decision makers in water resource management of watersheds. • A SWAT-based model was established for a multi-level simulation. • Response of hydrological process to a climate-driven vegetation change was explored. • Effect of climate and vegetation changes on hydrological process was quantified. [ABSTRACT FROM AUTHOR]

Traditional blue water resources assessment and management may not meet the needs of sustainable water resource utilization; ignoring the number of green water resources will underestimate the availability of water resources. To rationally allocate and scientifically manage the limited water resources, it is necessary to divide the rich and poor flow situation of blue water and green water. The MIKE SHE-MIKE HYDRO integrated coupled model was selected and used in the Yalong River basin to ascertain the blue and green water in the hydrological cycle. The model was calibrated by matching simulated discharge against observed streamflow discharge at the Tongziling Station. At the same time, the research analyzed the component of green water and the total amount of blue water or green water on a temporal scale. The set pair analysis (SPA) was introduced to classify blue water and green water, which can not only understand the amount and distribution characteristics of water resources in the Yalong River Basin but also rationally allocate the total of water resources in the basin from the perspective of the regional water cycle. Furthermore, according to the situation of blue water and green water in the basin, the related policies are formulated to realize the efficient utilization of water resources in the Yalong River basin. • A high-resolution hydrological model of the Yalong river basin is bulit. • The MIKE SHE system as the modeling platform is used to obtain the variation of Bluewater and Greenwater. • The set pair analysis (SPA) was introduced to study the variation of rich and poor Bluewater and Greenwater. • Table Captions. [ABSTRACT FROM AUTHOR]

In the upper reach of the Yangtze River Basin in China, changes of the runoff and sediment yield in the middle reach of the Jinsha River Basin have been given close attentions because of their declination trends over recent years. Then, the impact factors for the variations of runoff and sediment yield were urgent need to be investigated through a distributed hydrological modelling under multi spatiotemporal scales. The results showed that climate change had a significant impact on runoff and sediment yield of the basin before the operation of cascade reservoirs. The contribution rate of the reservoirs operation to the reduction of the annual runoff and sediment yield in the watershed was 48.90% and 28.75% respectively. The Ludila reservoir played an important role in reducing annual runoff and sediment yield of the basin. The location of reservoirs with the sequence of Ludila, Longkaikou, Jin'anqiao, and Ahai from upstream to downstream had the greatest effect on the annual sediment yield of the basin. The function of multiple reservoirs on the monthly runoff and sediment yield of the basin was not the superposition of a single one. Under the simultaneous change of temperature and precipitation, the precipitation had a greater impact on runoff and sediment yield of the basin than temperature. Spatially, the annual runoff and sediment yield in the middle and upper reaches of the basin were sensitive to changes of temperature and precipitation. This research provides scientific support for management of water and sediment resources in watersheds with cascade reservoirs. • The response of runoff and sediment yield (RSY) was assessed under multi scales. • The impact of reservoir scale on RSY was not superimposed. • The impact of temperature and precipitation on annual RSY was spatially different. [ABSTRACT FROM AUTHOR]

To facilitate regional water resources allocation, an integrated bi-level multi-objective programming (IBMP) model with dual random fuzzy variables was developed in this research The proposed model was derived through incorporating dual random fuzzy variables, multi-objective programming, and interval parameter programming within a bi-level optimization framework. This approach improved upon the previous bi-level programming methods and had two advantages. Firstly, it was capable of reflecting tradeoffs among multiple conflict preferences for water related bi-level hierarchical decision-making processes. Secondly, random fuzzy variables were used to tackle the dual uncertainties in both sides of the constraints, which were characterize as probability density functions and discrete intervals. Then, a real-world water resources planning problem was employed for illustrating feasibility of the application of IBMP model in Dongjiang river watershed of south China. Results reflected the alternative decisions for water allocation schemes under a set of probability levels and fuzzy α - cut levels, which can support in-depth analysis of tradeoffs among multiple levels and objective values. Moreover, modeling comparison analysis was undertaken to illustrate the performances of the proposed model. [Display omitted] • Dual-randomness bi-level interval multi-objective programming was developed; • Multi-objective, chance-constrained, and interval parameter programming approaches were used; • Interactions between multiple decision-makers can be addressed through hierarchical strategies; • Uncertain information can be expressed as interval and probability density functions; • Water allocation schemes under multiple constraint-violated levels can be handled. [ABSTRACT FROM AUTHOR]

An integrated simulation-optimization modeling system (ISOMS) approach was developed for assessing adaptive strategies in response to coupled impacts of climate and landuse variations. The ISOMS can not only reflect future hydrological trends under changing environment, but also provide water-allocation plans under various uncertainties expressed as random or fuzzy feature systematically. A case study of Anning River Basin with dry and warm characteristics in the upper Yangtze River was applied to inspect the model's applicability. A range of alternatives to adaptive strategies were generated under combinations of climate and landuse scenarios with different satisfaction levels. Results reveal that: (i) there exist increasing trend of temperature and precipitation in future period (2021–2050); (ii) the streamflow variation is more sensitive to climate change than landuse change; (iii) the hydrologic system uncertainties would lead to changes in water resources allocation; (iv) a low level of uncertainty satisfaction or a high level of violation risk would reduce the system reliability for the water resources system. The ISOMS approach has tremendous significance for evaluating hydrologic variations with complicated uncertainties, and providing optimal water allocation schemes responding to the coupled impacts of climate and landuse variations among society, economy and environment. • An integrated simulation-based optimization modeling on MIKE SHE and MFSCP method. • A set of 31 GCMs and three CA-Markov modules for climate and land use projections. • Hydrological process and water availability vary under changing conditions. • Adaptive strategies for water resources generated under multiple scenarios. [ABSTRACT FROM AUTHOR]

In this research, a dual-randomness bi-level interval multi-objective programming (DR-BIMP) model was developed for supporting water resources management among multiple water sectors under complexities and uncertainties. Techniques of bi-level multi-objective programming (BMOP), double-sided stochastic chance-constrained programming (DSCCP), and interval parameter programming (IPP) were incorporated into an integrated modeling framework to achieve comprehensive consideration of the complexities and uncertainties of water resources management systems. The DR-BIMP model can not only effectively deal with the interactive effects between multiple decision-makers in complex water management systems through the bi-level hierarchical strategies, but also can characterize the multiple uncertainties information expressed as interval format and probability density functions. It could thus improve upon the existing bi-level multi-objective programming through addressing discrete interval parameters and dual-randomness problems in optimization processes simultaneously. Then, the developed model was applied to a real-world case to optimally allocate water resources among three different water sectors in five sub-regions in the Dongjiang River basin, south China. The results of the model include determining values, interval values, and stochastic distribution information, which can assist bi-level decision-makers to plan future resources effectively to some extent. After comparing the variations of results, it is found that an increasing probability level can lead to higher system benefits, which is increased from [20,786.00, 26,425.92] × 108 CNY to [22,290.84, 27,492.57] × 108 CNY, while the Gini value is reduced from [0.365, 0.446] to [0.345, 0.405]. A set of increased probability levels gives rise to the lower-level objectives. Furthermore, the advantages of the DR-BIMP model were highlighted by comparing with the other models originated from the developed model. The comparison results indicated that the DR-BIMP model was a valuable tool for generating a range of decision alternatives and thus assists the bi-level decision-makers to identify the desired water resources allocation schemes under multiple scenarios. [Display omitted] • A dual-randomness bi-level interval multi-objective programming model was developed; • Interactions between multiple decision-makers can be addressed through bi-level hierarchical strategies; • Uncertain information associated with water can be expressed as interval and probability density functions; • Water resource allocation schemes under multiple constraint violated probability levels can be handled. [ABSTRACT FROM AUTHOR]

• We calculate the effect of an impounded reservoir in China on evapotranspiration and the evaporative ratio. • The dam has increased evapotranspiration and the evaporative ratio in the smallest subbasin holding the reservoir. • This increase cannot be explained by other changes in land use or vegetation. • Our hydrological basin-constrained approach estimates the water footprint of the hydroelectric project to be 16.5 m3/GJ. Water management by the impoundment of reservoirs has been found to influence evapotranspiration not only locally but also at the basin scale. Highly regulated hydrological basins generally show the effect of a net increase in evapotranspiration accompanying the successive impoundment of reservoirs. However, understanding and isolating the effect from a particular single impounded reservoir remains a challenge due to the lack of long-term observation data required and the existence of many other drivers present at the basin scale. Focusing on the hydrological basin having the largest hydropower potential in China, we isolated in time and space and quantified the effects of a single impounded reservoir on evapotranspiration and the evaporative ratio (i.e., the ratio of actual evapotranspiration to precipitation) before and after the construction of the Ertan Dam in 1998. We find that the dam has increased evapotranspiration in the smallest subbasin by 46±15 mm/yr and the evaporative ratio by 0.05±0.015, from the period before impoundment (1983-1997) to that after impoundment (2000-2012). This increase is found only within the smallest differential subbasin holding the impounded reservoir and cannot be explained by other changes in land use or vegetation. We use this result from our hydrological basin-constrained approach to calculate the water footprint of the hydroelectric project as 16.5 m3/GJ, which accounts for additional hydroclimatic effects of the impoundment of the reservoir beyond the water surface. Hence, this study finds that when runoff data is available, the water consumption and the water footprint of hydropower projects can be calculated by water mass balance at the scale of their hydrological basins. [ABSTRACT FROM AUTHOR]

Water quality data represent a critical resource for evaluation of the well-being of aquatic ecosystems and assurance of clean water sources for human populations. While the availability of water quality datasets is growing, the absence of a publicly accessible national water quality dataset for both inland and the ocean in China has been notable. To address this issue, we utilized R and Python programming languages to collect, tidy, reorganize, curate, and compile three publicly available datasets, thereby creating an extensive spatiotemporal repository of surface water quality data for China. Distinguished as the most expansive, clean, and easily accessible water quality dataset in China to date, this repository comprised over 330 000 observations encompassing daily (3588), weekly (217 751), and monthly (114 954) records of surface water quality covering the period from 1980 to 2022. It spanned 18 distinct indicators, meticulously gathered at 2384 monitoring sites, which were further categorized as daily (244 sites), weekly (149 sites), and monthly (1991 sites), ranging from inland locations to coastal and oceanic areas. This dataset will support studies relevant to the assessment, modeling, and projection of water quality, ocean biomass, and biodiversity in China, and therefore make substantial contributions to both national and global water resources management. This water quality dataset and supplementary metadata are available for download from the figshare repository at 10.6084/m9.figshare.22584742 (Lin et al., 2023b). [ABSTRACT FROM AUTHOR]

[Display omitted] • An integrated connectivity diagnostics and dependency analysis framework was proposed. • Variation characteristics of hydrological connectivity were accurately diagnosed. • The relationships between hydrological connectivity and water level were revealed. • The optimal ecological water level was determined for water replenishment management. An in-depth investigation on hydrological connectivity and its relationships with water level are fundamental for regional water replenishment management. In this research, an integrated connectivity diagnostics and dependency analysis framework (ICDDAF) was developed for determining the optimal ecological water level in Baiyangdian Wetland, North China. It consisted of two core modules: hydrological connectivity diagnostics (HCD) and hydrological connectivity–water level coexistence analysis (HC–WLCA). The results were as follows. 1) In the HCD module, remote sensing coupling geostatistical connectivity function methods can accurately evaluate the hydrological connectivity considering the directional difference and the validity of distance range. For intra–annual variations, the hydrological connectivity was relatively good in March at the monthly scale, spring at the seasonal scale and the west–east direction, while relatively weak in September and summer, which were related to the periodic characteristics of vegetation growth, overall terrain and flow direction. For inter–annual variations, it was generally weak and showed a downwards, then upwards and finally downwards trend. 2) In the HC–WLCA module, Multivariate Copula Analysis Toolbox was innovatively adopted to describe the coexistence relationships of hydrological connectivity and water level. Beta and generalized Pareto distributions were selected as the optimal marginal distributions for hydrological connectivity and water level indicators respectively, and Frank copula was determined as the optimal joint distribution function; the modelling uncertainty in the coexistence relationships was focused. 3) The water level of 7 m was determined as the optimal ecological water level for maintaining good hydrological connectivity and restoring ecological environment. Considering the coexistence relationships of hydrological connectivity and water level, such an ICDDAF can provide a new perspective for efficient adjustments of water levels based on hydrological connectivity pattern variations under different water replenishment schemes, aiming to achieve ecological restoration of wetlands. [ABSTRACT FROM AUTHOR]

• The distribution of green water resource was more homogeneous. • The annual average blue water was higher accounting for 65.1% of the total water flow. • The blue water has no significant variability in most river basins in 1992–2010. • The change of green water resource is caused mainly by green water flow. Poyang Lake basin has drought-prone pattern and floods in recent decades, posing a serious threat to water security and human life. In this research, the Soil and Water Assessment Tool (SWAT) was applied to investigate hydrological parameters characteristics, simulating uncertainties as well as spatial and temporal patterns of both blue and green water resources for the whole basin. The results revealed a strong correlation between the observed and simulated streamflow at six hydrological stations. The overall hydrological water balance analysis showed that 58.1 % of annual water yield is contributed by surface runoff, while groundwater flow contributes 38.8 % of annual water yield. The annual average blue water resource was higher accounting for 65.1 % of the total water resources. Green water coefficient was 34.9 % for the entire basin, varying from 26 % to 50 %. The spatial distribution of blue water resource was uneven in the basin with higher value in parts of the Ganjiang, Xinjiang and Raohe subbasins. While distribution of green water resource was more homogeneous. Blue water resource decreased significantly in Raohe subbasin with −37.1 mm/a whereas having no significant variability in other river basins from 1992 to 2010. The change of green water resource is caused mainly by the increase of green water flow in most subbasins. The results provide insights into prediction uncertainty reduction of simulation as well as green and blue water endowments. This research is of great significance to improve water resources management in Poyang Lake basin. [ABSTRACT FROM AUTHOR]

Formulating suitable policies is essential for resources and environmental management. In this study, an agricultural pollutants emission trading management model driven by water resources and pollutants control is developed to search reasonable policies for agricultural water resources allocation under multiple uncertainties. Random-fuzzy and interval information in water resources system that have directly impact on the effectiveness of management schemes is reflected through interval two-stage stochastic fuzzy-probability programming. The model was root from regional agricultural water resources system in Jining City, China under considering the relationship among effective precipitation, crop water demand, and pollutants emission. Two types policies (water consumption-control and pollutants emission-control) are designed for searching the related interaction on water resources management and water quality improvement. The results indicated that water resources policies would be of water and environmental double benefits, and a large rainfall would reduce irrigation amount from water sources and lead to a larger pollutants emission trading. The results will help for defining scientific and effective water resources protection and management policies and analyzing the related interacted effects on water consumption, pollutants control and system benefit. [ABSTRACT FROM AUTHOR]

Water production, utilization and recycle in urban system associated with a large amount of energy consumption and carbon emission that has increasingly international attention under sustainable development goals. In this study, a comprehensive urban water resources system management model is proposed under water-energy-carbon nexus and multiple uncertainties. The water-energy-carbon nexus was reflected in the processes of water extraction, water production and sewage treatment, and two objectives of maximizing the system benefit and minimizing carbon emission is transformed into two linear programming problem through the dual-objective interval fractional programming. Considering the interaction among water supply/demand, pollutants discharge control, energy consumption and self-energy utilization, indirect carbon emission as the main constraints, the developed model is applied to a typical water and energy sources shortage area of Qingdao city in north China. Multiple scenarios related to energy consumption and carbon emission control are designed to search the relationship among energy consumption, carbon emission and water resources allocation schemes. The results indicated that water demand as the main driving factor of energy consumption and carbon emission in urban water system cannot be directly limited through water supply structure adjustment. Through introducing self-energy supply (sludge utilization) and energy consumption control, water resources allocation schemes and water supply structure would be changed to improve energy saving potential with an obvious decrease trend of carbon emission intensity from 0.7921 tCO 2 /MWh to 0.5544 tCO 2 /MWh. The model could effectively provide reasonable urban water system management strategies under different water allocation demands and carbon emission challenges scenarios and deal with multiple uncertainties in decision-making process. [Display omitted] • Urban water resources system brings ecological environment issues. • A comprehensive urban water resources system management model is proposed. • Maximizing the economic benefits of per carbon emission to obtain the scheme. • Sludge utilization and energy consumption control can reduce carbon emission. • The model provides experiences for water-scarce regions around the world. [ABSTRACT FROM AUTHOR]

The problem of fresh water scarcity is one of the major constraints for regional development. Rapid urbanization and rising economic prosperity has further exacerbated problems with not only water quantity, but also water quality. Hence, sustainable utilization of water resources should be a priority, especially in water stressed areas. However, most current studies on optimal water allocation models are based on physical water, which cannot fully reveal the water flows embedded in imported and exported raw materials and products throughout all production processes. Thus, they fail to achieve sustainability goals. Therefore, the objective of this study was to set up an optimal water allocation model for industrial sectors based on water footprint accounting. In this paper, first the internal and external blue and gray water footprints were evaluated. The results indicated that the external water footprint was the major contributor to Dalian's water footprint, which shared around 72.58% of the total. Among all the industrial sectors, the chemical industry and chemical production sector had the highest total WF. Second, analyses of water productivity intensity of the WF and physical water for the industrial sectors were conducted. The comparison of the results revealed that physical water productivity intensity failed to explain the embedded water inflows in the production processes among the regions and sectors. Third, an optimization model based on the water footprint accounting results was thus set up. The optimal consequences indicated that a water allocation plan could meet both the water requirements for the blue and gray water footprints of the industrial sectors, and their target output goals as well. Therefore, this optimal allocation model is both rational and applicable for sustainable water utilization in future water management strategy formulations. [ABSTRACT FROM AUTHOR]

Problems with water resources restrict the sustainable development of a city with water shortages. Based on system dynamics (SD) theory, a model of sustainable utilization of water resources using the STELLA software has been established. This model consists of four subsystems: population system, economic system, water supply system and water demand system. The boundaries of the four subsystems are vague, but they are closely related and interdependent. The model is applied to Zhengzhou City, China, which has a serious water shortage. The difference between the water supply and demand is very prominent in Zhengzhou City. The model was verified with data from 2009 to 2013. The results show that water demand of Zhengzhou City will reach 2.57 billion m 3 in 2020. A water resources optimization model is developed based on interval-parameter two-stage stochastic programming. The objective of the model is to allocate water resources to each water sector and make the lowest cost under the minimum water demand. Using the simulation results, decision makers can easily weigh the costs of the system, the water allocation objectives, and the system risk. The hybrid system dynamics method and optimization model is a rational try to support water resources management in many cities, particularly for cities with potential water shortage and it is solidly supported with previous studies and collected data. [ABSTRACT FROM AUTHOR]

In this study, an integrated framework is proposed for agricultural water and land resources management under uncertain circumstances and energy-water nexus. The framework has two components: the optimized interval solutions generation of unknown market quotation and environment situation through the novel interval fuzzy-expectation programming, and the post-optimization decision-making of the tradeoff between system risk and return through risk-explicit interval programming. An optimization model based on the framework was developed from a real description for agricultural water resources system of Guangdong province under considering various crop, multiple water sources, and the related energy consumption in irrigation and drainage. The impact of energy consumption and risk level control on water resources allocation among different crops and system benefits were analyzed. The results indicated that the preference for surface water resources as the main water sources can effectively reduce regional irrigation energy consumption, and the planting area of each crop would have different variations duo to resources endowment constraints. Risk tradeoff-based results can provide valuable information and additional concern for developing low carbon-oriented agricultural water resources management schemes. [Display omitted] • An integrated framework for agricultural water resources management under uncertainty. • Influence of energy consumption on agricultural water resources allocation are explored. • Risk tradeoff-based results are obtained from risk explicit-interval fuzzy-expectation programming. [ABSTRACT FROM AUTHOR]