Allocation Of Water Resources Research Articles

Progress and future of China's aquatic ecological environment protection

AbstractSafeguarding water resources, aquatic habitats, and ecosystems is paramount for the well‐being of the populace, the future of the nation, and the sustainable development of China. With the relentless progression of ecological and environmental protection and the establishment of an ecological civilization, China's aquatic ecological environment protection has undergone five decades of exploration. The water environment protection paradigm has gradually transitioned from emphasizing pollutant emission concentration control and total pollutant emission control to prioritizing water environment quality improvement. Particularly in the past decade, regions nationwide have conducted proactive explorations and practices in source control, emission abatement, and quality enhancement. This paper systematically reviews the achievements in China's water environmental quality improvement and the characteristics of water environment management at various stages over the past half‐century. Considering the deployment of “three waters” coordination (water resources, water environment, and water ecology), green development, pollution, carbon reduction, and so forth, this paper analyzes the challenges confronted by China's aquatic ecological environment protection. Finally, future directions are prospected from six aspects: green development, climate change response, water resource allocation optimization, collaborative governance of multiple pollutants, aquatic ecological protection strengthening, and intelligent management improvement.

Establish an agricultural drought index that is independent of historical element probabilities

AbstractCurrently, there are three main shortcomings in meteorological drought indices: first, they rely on historical climate probability functions; second, the timescale used in calculations has a certain degree of subjectivity; third, the same index value may correspond to vastly different levels of actual drought in different climate types of regions. The purpose of this article is to establish a meteorological drought index that does not rely on historical meteorological element probability functions. Through theoretical derivation, four drought‐level maintenance lines are established on the cumulative precipitation‐cumulative water surface evaporation coordinate plane, and the coordinate quadrant is divided into five drought‐level areas. Through forward daily rolling accumulation, the maximum distance point is selected from the dynamically changing coordinate points to determine the corresponding cumulative precipitation and cumulative evaporation. The meteorological drought index is established by the distance from the selected coordinate point to each drought‐level maintenance line. Using daily precipitation and evaporation data from meteorological observation stations, the index is calculated based on the established meteorological drought index model, and compared with actual drought evolution and drought disaster records. The results show that the index can capture the development of drought well, and its changes are very consistent with drought disaster records. The index is of great significance for drought monitoring or assessment, and can provide guidance for water resource allocation, crop layout, and urban planning. Furthermore, it can also provide a way of thinking that does not rely on historical element probabilities for future drought research.

Construction and application of urban water resources spatial equilibrium model: A case study of Ulanqab City

ABSTRACT Evaluating the water resources spatial equilibrium (WRSE) is the foundation for scientifically planning the construction of an optimized water resource allocation system and achieving the high-standard development of the China Water Network Project. To elucidate the characteristics of WRSE variation in Ulanqab City, this study explored a novel WRSE assessment model based on connection number and the subtraction set pair potential method. The results indicate that: (1) there exists a mismatch between the distribution of water resources in Ulanqab City and its socio-economic development. In 2020, the Gini coefficients of water resources total quantity concerning resident population, gross domestic product (GDP), industrial output value, and irrigated land area were 0.48, 0.48, 0.51, and 0.28, respectively. (2) From 2011 to 2020, the overall WRSE level in Ulanqab City showed an increasing trend year by year. Among them, the WRSE levels in six counties improved, while Jining District consistently remained at a low equilibrium state due to the prominent contradiction between water supply and demand. (3) In the future, Ulanqab City can further enhance the WRSE level by promoting the reuse of recycled water, intensifying groundwater pollution control, and implementing a quota management system for agricultural water use.

Unravelling the potential of Big Data-driven decision-making in sustainable water irrigation: An AI perspective

Big Data-driven initiatives have transformed several industries by using large databases to extract vital information and enhance operations. In the field of sustainable water irrigation, Big Data enables intelligent water management, allowing for exact resource allocation, monitoring and analysis. This combination enables smart decision-making, increasing productivity in agriculture while reducing water consumption and environmental impacts. The revolutionary influence of data-driven approaches on managing water resources for sustainable and efficient irrigation practices has significant potential. The research highlights the importance of Big Data-driven approaches in water management by examining their applicability. It explores the artificial intelligence (AI) techniques for water irrigation that is sustainable and determines significant affecting factors efficient water management. The study encourages AI in intelligent water management systems and explains the application of big data in irrigation. It illustrates how smart water management which includes hydrated irrigation and predictive water infrastructure can contribute to AI-driven water management. To handle complicated water supply problems, the research presents an estimated water level model, highlighting the integration of AI and indicating the revolutionary potential of these techniques in attaining sustainable water irrigation. We highlight the novel possibilities of big data-driven methods for sustainable water irrigation, illustrating the essential part of AI techniques in effective water resource allocation.

Community participation and effective water management: A study on water user organizations (WUOs) in Thailand

This study examines the factors enhancing the effectiveness of Water User Organizations (WUOs) in Thailand, spotlighting the integration of geo-informatics and community involvement in water management. Employing a community-based participatory research approach, we assessed the impact of advanced technological tools and increased community engagement on WUOs' operations and sustainability. Our methodology included surveys, interviews, and an analysis of water management practices before and after geo-informatics implementation. Findings reveal a significant increase in community participation and an improvement in water management knowledge. The use of geo-informatics led to notable advancements in water allocation efficiency and conflict resolution, directly contributing to the financial sustainability of WUOs. Specifically, the application of geo-informatics facilitated more accurate and timely water resource allocation, evidenced by enhanced community engagement metrics and the resolution of longstanding conflicts. These results underscore the value of combining geo-informatics with community-driven approaches to water management, offering valuable insights for policymakers and practitioners. The study advocates for policies that support the adoption of technological innovations and promote community-centric governance, providing a scalable model for sustainable water resource management. This approach not only improves the functionality and sustainability of WUOs but also sets a precedent for holistic water governance practices globally.

Optimal Allocation of Water Resources in Canal Systems Based on the Improved Grey Wolf Algorithm

Xinjiang is located in the arid region of northwestern China, and agriculture accounts for an absolute share of total water use. Resource-based, engineering, structural, and managed water shortages coexist. Therefore, it is of great significance to vigorously develop water conservation technology and improve the efficiency of water transmission and distribution in canal systems. This research aims at addressing the problems of difficult manual regulation and the overall optimization of the final canal system, low-water-resource utilization efficiency, and management efficiency. Taking the branch-double two-stage canal system of Dongfeng branch canal in Mangxiang, Jinghe irrigation district, as a case study, and the rotation irrigation group and irrigation duration as decision variables, canal distribution is modeled with the goal of minimizing seepage losses. The improved grey wolf algorithm combined with particle swarm optimization is used for the first time and compared with the traditional grey wolf algorithm, genetic particle swarm optimization fusion algorithm, and northern goshawk algorithm. The results show that (1) on the basis of meeting the water discharge capacity and water demand requirements of the canal system, the diversion time of the water distribution scheme obtained by using the improved grey wolf algorithm is shortened from 11 d to 8.91 d compared with the traditional empirical water distribution scheme. (2) The improved grey wolf algorithm converges to the optimal value within 10 generations compared to the remaining methods, and the total water leakage is reduced from 16.15 × 104 m3 to 11.75 × 104 m3. (3) The number of gate adjustments is reduced, and the canal gates are opened and closed at the same time within each rotational irrigation group. The grey wolf algorithm improved by its combination with particle swarm has stronger optimization ability and convergence, which can better meet the requirements of efficient water resource allocation in irrigation canal systems, as well as a high application value.

Divergent patterns of rainfall regimes in dry and humid areas of China

Monitoring the long-term dynamics of the wet season is important for both the current operation and future management of water resource systems. Wet seasons in China are substantially influenced by monsoons with great variability but are unknown. We conducted a comprehensive assessment of rainfall regimes in China between 1982 and 2020 using a modified anomalous accumulation method at the pixel level. We observed divergent patterns of “wet areas becoming drier, and dry areas becoming wetter” with rainfall amount and rainy days increasing in dry regions, and decreasing in humid regions. Wet seasons extend to dry areas and shorten in wet areas, with trends related to dryness. Simultaneously, as the dryness increased, the length, number of dry spells, and consecutive dry days increased. Concurrent increases in rainy days and dry spells indicated a seasonal rainfall regime toward greater variations in drier areas, which was not entirely consistent with a global intensification pattern of “dry getting drier and wet getting wetter”, implying increased potential climatic risks in dry areas. For climate risk prediction, water resource allocation, and agricultural management, we advocate a finer and more precise dynamic assessment of the wetting–drying pattern.

Water resources management considering groundwater instability affected by climate change scenarios

In the present study, using GMS and MODFLOW code, a model of Khorramabad aquifer (Iran) was developed under unsteady conditions with considering the climate change (as a study innovation) in scenarios of RCP26 (optimistic) and RCP85 (pessimistic) based on results of CNRM-CM5 global climate model (Centre National de Recherches Me'te'orologiques—phase 5 of the Coupled Model). Using surface runoff data and computational level output from GMS, an integrated model was created in WEAP. According to scenarios of RCP26 and RCP85 for periods (2040–2069) and (2070–2099), the climate change effects on surface water and groundwater were evaluated. Results showed that water level calculated by GMS was obtained with high accuracy in calibration period (RMSR = 1.42 m, MSR = 0.85 m) and in verification period (MAE = 0.88, r = 0.98 and NSE = 0.97), which was in agreement with observed water levels of wells in region. The water level in RCP26 (2040–2069 and 2070–2099) compared to observed water level, on average, decreased by 0.154 m and 1.175 m, respectively, and in RCP85 for the same period, a decrease of 0.621 m and 0.753 m of calculated water level was observed compared to baseline. Then, allocation of surface water and groundwater resources to consumption sectors (agricultural, urban and industrial sectors) was analyzed using WEAP. Results showed that the lowest deficit of water resources in all sectors occurred in RCP26 (2040–2069) with a value of 7% and the highest deficit occurred in RCP85 (2070–2099) with a value of 180% compared to baseline.

Application of One-Dimensional Hydrodynamic Coupling Model in Complex River Channels: Taking the Yongding River as an Example

River conditions are complex and affected by human activities. Various hydraulic structures change the longitudinal slope and cross-sectional shape of the riverbed, which has a significant impact on the simulation of water-head evolution. With continuous population growth, the hydrological characteristics of the Yongding River Basin have undergone significant changes. Too little or too much water discharge may be insufficient to meet downstream ecological needs or lead to the wastage of water resources, respectively. It is necessary to consider whether the total flow in each key section can achieve the expected value under different discharge flows. Therefore, a reliable computer model is needed to simulate the evolution of the water head and changes in the water level and flow under different flow rates to achieve efficient water resource allocation. A one-dimensional hydrodynamic coupling model based on the Saint-Venant equations was established for the Yongding River Basin. Different coupling methods were employed to calibrate the coupling model parameters, using centralised water replenishment data for the autumn of 2022, and the simulation results were verified using centralised water replenishment data for the spring of 2023. The maximum error of the water-head arrival time between different river sections was 4 h, and the maximum error of the water-head arrival time from the Guanting Reservoir to each key cross-section was 6 h. The maximum flow error was less than 5 m3/s, and the changing trend of the flow over time was consistent with the measured data. The model effectively solved the problem of low accuracy of the water level and flow calculation results when using the traditional one-dimensional hydrodynamic model to simulate the flow movement of complex river channels in the Yongding River. The output results of the model include the time when the water head arrives at the key section, the change process of the water level and flow of each section, the change process of the water storage of lakes and gravel pits, and the change process of the total flow and water surface area of the key section. This paper reports data that support the development of an ecological water compensation scheme for the Yongding River.

Seasonal variation of water utilization sources and responses to precipitation in the dominant species of broad-leaved and needle-leaved mixed forests in Mount Lushan, China

Elucidating the seasonal patterns of water sources for dominant species in the sub-tropical humid mountainous forest, analyzing the eco-hydrological complementarity and competition mechanisms among coexisting species, investigating the responses of plant water utilization to precipitation, could provide a theoretical basis for vegetation restoration and management. Based on the stable hydrogen and oxygen isotope technique, we analyzed the δ2H and δ18O characteristics of precipitation, xylem water from Pinus massoniana and Quercus variabilis, and soil water from 0-100 cm depth in Mount Lushan, China. The MixSIAR model, Levins index, and PS index were used to calculate the relative contribution rate of each water source, the hydrological niche breadth, and niche overlap of P. massoniana and Q. variabilis. The results showed that, in the wet season (March to July), P. massoniana primarily utilized soil water from the 0-20 cm and 20-40 cm depths, while Q. variabilis primarily utilized that from the 20-40 cm and 40-60 cm depths. During the dry season (August to September), P. massoniana and Q. variabilis utilized 40-60 cm and 60-80 cm of soil water, respectively, resulting in an increase in the depth of water absorption. In the early growing season (March to April) and the late growing season (September), there was a high hydrological niche overlap between P. massoniana and Q. variabilis, resulting in intensitive water competition. In the middle of the growing season (May to August), the water source was adequately allocated, and the hydrolo-gical niche was segregated to meet the high transpiration demand. Q. variabilis primarily utilized soil water from a depth of 60-80 cm and 60-80 cm before a precipitation event, and from a depth of 0-20 cm and 20-40 cm after the event. In contrast, P. massoniana primarily utilized soil water from a depth of 0-20 cm and 20-40 cm both before and after a precipitation event. In conclusion, water utilization patterns of P. massoniana and Q. variabilis exhibited a seasonal trend, with shallow water uptake during the rainy season and deep water uptake during the dry season. These species are capable of efficiently allocating water resources during the peak growth season, and their root systems actively respond to change in soil moisture level. They have strong adaptability to extreme precipitation events and exhibit remarkable water conservation capabilities.

Construction of water resource allocation model based on green supply chain theory

Construction of water resource allocation model based on green supply chain theory

Using Copula functions to predict climatic change impacts on floods in river source regions

Flood frequency in river source regions is significantly affected by rainfall and snowmelt as part of climatic changes. A traditional univariate flood frequency analysis cannot reflect the complexity of floods, and when used in isolation, it can only underestimate flood risk. For effective flood prevention and mitigation, it is essential to consider the combined effects of precipitation and snowmelt. Copula functions can effectively quantify the joint distribution relationship between floods and their associated variables without restrictions on their distribution characteristics. This study uses copula functions to consider a multivariate probability distribution model of flood peak flow (Q) with cumulative snowmelt (CSm) and cumulative precipitation (CPr) for the Hutubi River basin located in northern Xinjiang, China. The joint frequencies of rainfall and snowmelt floods are predicted using copula models based on the Coupled Model Intercomparison Project Phase 6 data. The results show that Q has a significant positive correlation with 24-d CSm (r = 0.559, p = 0.002) and 23-d CPr (r = 0.965, p < 0.05). Flood frequency will increase in the future, and mid- (2050–2074) and long-term (2075–2099) floods will be more severe than those in the near-term (2025–2049). The probability of flood occurrence is higher under the SSP2-4.5 and SSP1-2.6 scenarios than under SSP5-8.5. Precipitation during the historical period (1990–2014) led to extreme floods, and increasing future precipitation trends are found to be insignificant. Snowmelt increases with rising temperatures and occurs earlier than estimated, leading to an earlier flood period in the basin and more frequent snowmelt floods. The Q under the joint return period is larger than that during the same univariate return period. This difference indicates that neglecting the interaction between precipitation and snowmelt for floods leads to an underestimation of the flood risk (with underestimations ranging from 0.3% to 22%). The underestimations decrease with an increase in the return period. The joint risks of rainfall or snowmelt according to various flood periods should be considered for rivers with multi-source runoff recharge in flood control design. This study reveals the joint impact of precipitation and snowmelt on extreme floods under climate change in river source regions. This study also provides a scientific basis for regional flood prevention and mitigation strategies, as well as for the rational allocation of water resources.

Crop coefficients of natural wetlands and riparian vegetation to compute ecosystem evapotranspiration and the water balance

AbstractWetlands, namely the riparian ones, play a major role in landscape and water resources functionalities and provide enormous opportunities for ecosystems services. However, their area at globe scale is continuously decreasing due to appropriation by the riverain communities or by allocation of water resources to other uses, namely irrigation, in prejudice of natural wetlands. Due to the high competition for water, namely for agricultural irrigation, the calculation of the vegetation evapotranspiration (ETc), i.e. the consumptive water use of the wetland ecosystems, is mandatory for determining water supply–demand balance at various scales. Providing for the basin and local levels the reason for this review study on ETc to be presented in an irrigation focused Journal. The review also aims to make available adequate Kc values relative to these ecosystems in an ongoing update of FAO guidelines on evapotranspiration. The review on ETc of natural wetlands focused on its computation adopting the classical FAO method, thus the product of the FAO-PM grass reference ETo by the vegetation specific Kc, i.e., ETc = Kc ETo. This approach is not only the most common in agriculture but is also well used in natural wetlands studies, with Kc values fully related with vegetation ecosystems characteristics. A distinction was made between riparian and non-riparian wetland ecosystems due to differences between main types of water sources and main vegetation types. The Kc values are tabulated through grouping wetlands according to the climate since the variability of Kc with vegetation, soil, and water availability would require data not commonly available from the selected studies. Tabulated values appear to be coherent and appropriate to support field estimation of Kc and ETc for use in wetlands water balance when not measured but weather data may be available to compute the grass reference ETo. ETc and the water balance could then be estimated since they are definitely required to further characterization and monitoring of wetlands, defining measures for their protection, and assessing ecosystems’ services.

Towards interpretability lightweight semantic segmentation model for waterbody extraction in large-scale high resolution remote sensing images

ABSTRACT In recent years, high resolution (HR) remote sensing images have brought significant changes to land cover monitoring. Monitoring water resources, a vital and scarce commodity for human survival, is a crucial aspect of land cover monitoring and forms the foundation for water resource allocation in regions facing shortages. Hence, a universal method is necessary to address this problem and handle large-scale water resources monitoring. We explore the network structure via improving the interpretability to reduce the network layers and propose a lightweight pixel-wise semantic segmentation model, which achieves waterbody extraction from GF-1 remote sensing images with high accuracy and high speed. The proposed model structure addresses both semantic segmentation for large and small waterbodies, extracting fine-grained edge and contour information from high-resolution feature maps. Additionally, it efficiently extracts multi-scale high-level semantic information using residual convolutional blocks and dilated convolutional blocks. The multi-scale feature maps are fused, and binary classification is predicted through Support Vector Machines (SVM). Furthermore, the paper introduces a model training method with an adaptive learning rate, reducing the overall training time. To validate the model’s performance, remote sensing images from GF-1 are utilized to construct a dataset. Experimental results, compared with five models, demonstrate that the proposed method achieves the highest accuracy and least training time.

Development of a new rotational irrigation model in an arid basin based on ecological zoning and sluice regulation

Precise and efficient allocation of existing water resources is of great significance to protect and restore desert riparian forests in inland river basins. However, the lack of detailed ecological zoning in most basins hinders the optimization of the current ecological sluice regulation scheme, leading to low effectiveness in vegetation restoration and water resources management. To address this problem, we proposed for the first time an ecological zoning method that integrates the vegetation gradient model and control of ecological sluices. Specifically, the mainstream of Tarim River basin (China) was classified into three types of ecological functional zones, i.e., key protection, key restoration, and ecologically sensitive zones, based on the kernel NDVI (kNDVI) gradient detection framework. On this basis, the basin was divided into 27 sluice group control areas determined by the control range of ecological sluices and the study area was further divided into five grades zones of ecological rotation irrigation. Based on the results of ecological zoning and the priorities of rotational irrigation, this study proposes a new rotational irrigation model in the basin to further promote vegetation recovery. The results showed that guarantee rate of ecological water supply to vegetation protection and restoration increased from 82.3% to 101.7% before and after rotational irrigation, respectively, indicating the effectiveness of this new method. The results of this study have a practical value and may significantly contribute to the optimal allocation and management of water resources in global arid basins.

Evolution of spatiotemporal pattern of virtual water in the Yangtze River economic belt

Cross-regional water allocation within the river basin, coupled with the development of specialized industries based on comparative advantages, can effectively mediate overall water use efficiency. The uneven distribution of water resources and structural contradictions in water usage hinder the sustainable development of water resources in the Yangtze River Economic Belt (YEB). This study aims to address these issues from the perspective of virtual water trade, to facilitate cross-regional water resource allocation and guide structural adjustments in industrial water use, ensuring water security. In this study, we developed a dynamic multi-regional input–output model (MRIO) to explore dynamic change of virtual water trade pattern in the YEB that evolves over time. This model sheds light on evolving virtual water transfer patterns and the nuances of water resource pressure transmission. Additionally, it quantifies sectoral water use variations, pinpointing the cornerstone industries across different regions. The findings are as follows: (1) The pattern of virtual water transfer predominantly towards the developed downstream regions remains unchanged, but regional disparities are gradually diminishing. (2) The upstream regions of the YEB transfer more water resource pressures externally, while the downstream regions do not experience excessive external transfers of water resource pressures. (3) The pattern of Agriculture-driven virtual water transfers is gradually being disrupted. While the upstream regions continue to rely on Agriculture as their pillar industries, the downstream regions are progressively shifting towards tertiary industries such as Service. These results indicate that economic development is the primary driver of changes in the the pattern of virtual water transfer, and economic disparities are a key factor in shaping the latest virtual water transfer. Based on existing policies, there is a need for comprehensive coordination of water resource allocation and strengthening of virtual water trade exchanges between regions to address the uneven distribution of water resources. Additionally, it is necessary to resolve structural water use conflicts by developing specialized economic strengths based on the main industries for virtual water in each region.

Research on optimal allocation of soil and water resources based on water–energy–food–carbon nexus

Current population growth and rapid urbanization in China have intensified the demand for water, energy, and food. This is threatening the intertwined global water, energy, and food security. Therefore, it is necessary to formulate interconnected and interdependent water, energy, food, and carbon policies. In this study, based on the theory of water–energy–food–carbon nexus, a soil and water resource optimization allocation model was developed by establishing an optimization modeling framework to achieve coordination between various sectors of water allocation. The model is an effective decision-making tool that fully considers the close relationship within the nexus system, and multiple uncertainty conditions. It was applied on the Fen River Basin in Shanxi Province as the study area, and a series of optimized allocation schemes were obtained. The results indicated that the current water allocation to each sector is meeting its minimum water demand. The planting structure optimization of two crops, wheat and corn, reduces the regional agricultural water consumption. For example, in dry years, the area of wheat cultivation (which needs more irrigation and has lower net economic benefits) is reduced and that of corn (which needs less irrigation and consumes less water) is increased in each subdistrict. The wheat plantation area in the midstream and downstream is decreased by 2.08% and 26.25%, respectively. The water use structure of crops indicated that precipitation and groundwater resources significantly contribute to the production of both crops throughout the entire growth process. This model can be applied in other regions; the model's economic and ecological benefits are combined so that decision makers can consider the stability of the water–energy–food–carbon system and provide optimal resource allocation under various scenarios, contributing to achieving the goal of sustainable development.

Prediction of Large-Scale Regional Evapotranspiration Based on Multi-Scale Feature Extraction and Multi-Headed Self-Attention

Accurately predicting actual evapotranspiration (ETa) at the regional scale is crucial for efficient water resource allocation and management. While previous studies mainly focused on predicting site-scale ETa, in-depth studies on regional-scale ETa are relatively scarce. This study aims to address this issue by proposing a MulSA-ConvLSTM model, which combines the multi-headed self-attention module with the Pyramidally Attended Feature Extraction (PAFE) method. By extracting feature information and spatial dependencies in various dimensions and scales, the model utilizes remote sensing data from ERA5-Land and TerraClimate to attain regional-scale ETa prediction in Shandong, China. The MulSA-ConvLSTM model enhances the efficiency of capturing the trend of ETa successfully, and the prediction results are more accurate than those of the other contrast models. The Pearson’s correlation coefficient between observed and predicted values reaches 0.908. The study has demonstrated that MulSA-ConvLSTM yields superior performance in forecasting various ETa scenarios and is more responsive to climatic changes than other contrast models. By using a convolutional network feature extraction method, the PAFE method extracts global features via various convolutional kernels. The customized MulSAM module allows the model to concentrate on data from distinct subspaces, focusing on feature changes in multiple directions. The block-based training method is employed for the large-scale regional ETa prediction, proving to be effective in mitigating the constraints posed by limited hardware resources. This research provides a novel and effective method for accurately predicting regional-scale ETa.

Assessment of natural resource endowment and urban-rural integration for sustainable development in Xinjiang, China

Water and land (W-L) resources become even more important in the context of urban-rural integration in China's arid northwest region in order to achieve sustainable development goals (SDGs). Our study used Gini coefficients to examine the relationship between natural resources and economic development in China's Xinjiang Uygur Autonomous Region. Cobb-Douglas (C-D) production functions were used to determine the economic impacts of W-L resources on rural-urban economic development. We also examined the spatiotemporal interaction characteristics of the growth drag effect of W-L resources. As a result of the decline in Gini coefficients between 2000 and 2020, Xinjiang experienced a decrease in water resources, land resources, and urban-rural GDP (gross domestic product). The output elasticities of urban-rural land and water resources were 0.3544 and 0.4790, respectively, whereas the output elasticities of urban-rural land resources were 0.1501 and 0.2185, respectively. As a result, water resources contribute to the growth of urban-rural GDP more than land resources, and W-L resources contribute to the economic development of rural areas more than it does to that of urban areas. Land resources were found to have a drag effect on urban and rural economies, respectively, in 7 and 56 counties, respectively, and water resources were found to have a drag effect on urban and rural economies, respectively, in 67 and 58 counties. In Xinjiang, water resources contributed more to economic growth than land resources. Even though W-L resources still have a drag effect on urban-rural economic growth, we can gain greater driving force by optimizing and improving resource use. However, this requires an optimal allocation and efficient use of water resources.

Evaluation of Carrying Capacity of Water Resource in the Heihe River Basin Based on Game Theory and Cloud Model

To optimize the allocation of water resources and ensure sustainable water resources management, we evaluated the carrying capacity of water resources in the Heihe River Basin. 16 evaluation indicators were selected from the social, economic, ecological, and water resource systems to construct an evaluation system of the carrying capacity. The combination weight and membership degree were determined using the game theory combined with the weighting method and normal cloud model. The water resource utilization efficiency during 21 years was estimated by analyzing influencing factors and development trends of carrying capacity of water resources. The water use rate was important in the carrying capacity, and indicators such as urbanization rate, per capita Gross Domestic Product (GDP), sewage discharge per 10000 yuan, and water consumption per 10000 yuan of industrial output value were important factors affecting the carrying capacity. The carrying capacity of the Heihe River Basin increased from a severe overload status (Level I) in 2000 to a good status (Level V) in 2021. In the other years, the status remained at Level IV. The carrying capacity was improved. The result of TOPSIS confirmed the consistency of the development trend of the carrying capacity and the appropriateness of the developed evaluation model in this study. The model based on the game theory and cloud model can be used to effectively guide the sustainable development of water resources and improve the carrying capacity of water resources of the Heihe River Basin. The results of this study serve as a reference for establishing policies to save water resources and evaluate the carrying capacity of water resources.