Allocation Of Water Resources Research Articles

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.

Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering

The study of the expansion potential of artificial oases based on remote sensing data is of great significance for the rational allocation of water resources and urban planning in arid areas. Based on the spatio-temporal relationship between morphogenetic landform types and the development of artificial oases in Xinjiang, this study explored the development pattern of artificial oases in the past 30 years by using trend analysis and centroid migration analysis, constructing a series of landform–artificial oasis change indices, and investigating the suitability of different landforms for the development of artificial oases based on geomorphological location by adopting a hierarchical clustering method. The following conclusions are drawn: (1) From 1990 to 2020, the area of artificial oases in the whole territory continued to increase, with significant expansion to the south from 2005 to 2010. (2) Six categories of landform types for artificial oasis development were created based on the clustering results. Of these, 7.39% and 6.15% of the area’s geomorphological types belonged to the first and second suitability classes, respectively. (3) The optimal scale for analyzing the suitability of landforms for the development of artificial oases over the past 30 years in the whole area was 8 km, which could explain more than 96% of the changes in the growth of artificial oases. The distribution of landforms of first- and second-class suitability within the 8 km buffer zone of an artificial oasis in the year 2020 was 10.55% and 9.90%, respectively, and landforms of first-class suitability were mainly concentrated in the near plain side of the urban agglomerations located on the northern and southern slopes of the Tianshan Mountains, and the urban agglomerations at the southern edge of Altai Mountains. This study quantified the potential of different geomorphological types for the development of artificial oases and provided a basis for site selection in future artificial oasis planning and urban construction.

Changes in the Water Area of an Inland River Terminal Lake (Taitma Lake) Driven by Climate Change and Human Activities, 2017–2022

Constructed from a dataset capturing the seasonal and annual water body distribution of the lower Qarqan River in the Taitma Lake area from 2017 to 2022, and combined with the meteorological and hydraulic engineering data, the spatial and temporal change patterns of the Taitma Lake watershed area were determined. Analyses were conducted using Planetscope (PS) satellite images and a deep learning model. The results revealed the following: ① Deep learning-based water body extraction provides significantly greater accuracy than the conventional water body index approach. With an impressive accuracy of up to 96.0%, UPerNet was found to provide the most effective extraction results among the three convolutional neural networks (U-Net, DeeplabV3+, and UPerNet) used for semantic segmentation; ② Between 2017 and 2022, Taitma Lake’s water area experienced a rapid decrease, with the distribution of water predominantly shifting towards the east–west direction more than the north–south. The shifts between 2017 and 2020 and between 2020 and 2022 were clearly discernible, with the latter stage (2020–2022) being more significant than the former (2017–2020); ③ According to observations, Taitma Lake’s changing water area has been primarily influenced by human activity over the last six years. Based on the research findings of this paper, it was observed that this study provides a valuable scientific basis for water resource allocation aiming to balance the development of water resources in the middle and upper reaches of the Tarim and Qarqan Rivers, as well as for the ecological protection of the downstream Taitma Lake.

Significant contribution of the Tianshan lakes to their water storage and water resources

Study regionThe Tianshan region Study focusThe Tianshan region possesses a complex landscape with lakes, and changes in the water storage of these lakes serve as a crucial indicator of climate change. They also represent a significant water resource for the local area, profoundly impacting water resource allocation and playing a pivotal role in understanding the mass balance in the Tianshan region. Nevertheless, there is still a lack of systematic research on the Tianshan lake group. New hydrological insights for the regionThe results reveal that the total lake water storage is exhibiting an increasing trend (0.73±0.10 Gt/a). The Tianshan region experienced two periods of mass anomalies in 2010 and 2016, which were reflected not only in the changes of lake water storage but also in soil moisture, snow water, and even Global Navigation Satellite System (GNSS) displacement fields. These two mass anomalies were closely related to abnormal precipitation resulting from El Niño events (r=0.55, p<0.01). During these two mass anomaly periods, the regional total mass increased by 65.73 Gt and 67.35 Gt. Compared with their contributions to the mass (22% and 14%), the variations in lake area were remarkably slight (0.01% and 0.014%). This study contributes to understanding the sensitivity of lakes to climate responses and underscores the necessity of lake research for water resource management in complex surface environments.

Study on the Application of Water Resource Management Based on GF-7 Stereo Mapping Satellite

Abstract. GF-7 satellite was successfully launched on 3 Nov 2019. The two-line stereo camera can effectively obtain 20 km-width panchromatic stereo images with resolution better than 0.8m and 3.2m-resolution multispectral images. Through the composite mapping mode of stereo camera and laser altimeter, the satellite realizes 1:10,000-scale stereo mapping. This article selected the Qiafuqihai Reservoir and its upstream of the Yili River Basin as the study area. Hydrological landforms and vegetation coverage were monitored and three-dimensional dynamic simulation software was developed to verify the potential application of GF-7 stereo mapping satellite data in supporting drainage basin water resource allocation and management in future scenarios. 3 meters DSM derived from GF-7 surveying and mapping satellite finely portrayed the characteristics of hydroponic landforms of small watersheds. The upstream of Qiafuqihai was divided into eleven small watersheds. The water density was 8.5 times more than which was produced from STRM 90m. The elevation of the water-level fluctuation zone of the Qiafuqihai Reservoir ranged from 970 to 998 meters with the water area changed from 28.3 to 57.6 square kilometres. The terrain in the northwest and northeast was flat, with the main vegetation types being natural grasslands (64.9%) and arid lands (5.03%). The three-dimensional dynamic visualization software was developed and demonstrated hydrology information, vegetation coverage information and dynamic changes in the landform of the basin in three-dimensional environment. GF-7, the stereo surveying and mapping satellite, could be perfectly able to support the application of water resources deployment and management in the future.

Sustainable management of land use patterns and water allocation for coordinated multidimensional development

The sustainable and integrated management of resources is a crucial approach to achieving sustainable regional development in the face of limited land and increasingly scarce water resources. This paper proposes a multidimensional optimization model to jointly optimize land use patterns and water resource allocation under the conditions of maximizing economic benefits and minimizing social differences, ecological loads, environmental pollution, and carbon emissions. The optimization model is solved using the affiliation function method and then combined with random forest (RF) and cellular automata (CA) models to further obtain the optimal spatial layout of land use. This paper takes the Mid-Yangtze River City Cluster as an example and optimizes the land use pattern and water allocation in the region in 2020 and 2030. The results of the study show that the optimized water and land resource allocation scheme performs better than the status quo in all dimensions. The optimized economic benefits, social effects, ecological effects, environmental effects, and overall sustainability in 2020 are increased by 45.97%, 22.89%, 10.07%, 24.65%, and 42.73%, respectively. By 2030, overall sustainability reaches 0.69. The developed modeling framework helps to elucidate the internal linkages between land use and water allocation, and it provides decision-makers with diversified approaches to land and water resource management and adjustment for different cities in different periods, which promotes the sustainable development of urban agglomerations.

Equal allocation, demand priority or negotiated allocation? How to allocate water resources in the Tigris and Euphrates River Basin efficiently

The Tigris and Euphrates River Basin is an important water supply, but it suffers from water scarcity. It is necessary to carry out reasonable allocation of water resources in this region. Since water resources issues in this region are of multinational interest, international cooperative distribution efforts are needed. Common water resources allocation modes include equal allocation, demand priority or negotiation allocation. In order to derive the applicable range of various water resources allocation modes, this article constructs three differential game models and compares and analyzes the equilibrium results obtained by the models. Finally, the study shows that when the cost of developing water resources is small and the revenue obtained from developing water resources is large, the water-scarce region can obtain the maximum benefit by adopting the demand priority mode. Otherwise, the water-scarce region can obtain the maximum benefit by adopting the negotiation allocation mode. This study can inform the allocation, strategic interaction and cooperation of dynamic water resources in the two river basins.

Water use characteristics of coexisting sand‐binding vegetation in two typical soil habitats in the desert steppe of China

AbstractUnderstanding the water use characteristics and water relationship of coexisting vegetation in a mixed‐species plantation of trees and shrubs is crucial for the sustainable restoration of degraded arid areas. This study investigated the water use characteristic of coexisting sand‐binding vegetation combinations in the sierozem habitat (Populus przewalskii Maxim namely Populus‐S and Caragana liouana) and aeolian sandy soil habitats (Populus przewalskii Maxim namely Populus‐A and Salix psammophila) of the desert steppe. By analysing the δ2H and δ18O isotopes in xylem, soil water, groundwater and precipitation, a Bayesian MixSIAR model was employed to quantitatively assess the water utilization characteristics of plants. Throughout the growing season, in the sierozem habitat, C. liouana exhibits the highest efficiency in utilizing soil moisture above 60 cm (53.45%) and displays adaptable water use strategies. In contrast, Populus‐A predominantly relies on deep soil moisture below 60 cm plus groundwater (63.89%). In the aeolian sandy soil habitat, both Populus‐A and S. psammophila similarly favour deep soil moisture below the 60 cm soil plus groundwater (66.77% and 67.60%, respectively). During the transition period from the dry to the wet seasons, although both Populus‐A and S. psammophila in the aeolian sandy soil habitat shifted their water sources from deeper to shallower ones, there was considerable overlap in the water sources used by Populus‐A and S. psammophila. This overlap led to competition for water resources and exacerbated the depletion of deep soil moisture in both seasons. Conversely, in the sierozem habitat, the partitioning of water sources between Populus‐S and C. liouana facilitated the allocation and utilization of water resources between the two species. The findings highlight the need for species‐specific consideration in water resource allocation within mixed‐species plantations of trees and shrubs, which is crucial for sustainable vegetation restoration in sand‐binding ecosystems.

Evolution of an arid social-ecosystem with different water utilization spanning 12,000 years

Understanding the regime shifts of social-ecological systems (SES) and their local and spillover effects over time is crucial for ensuring future sustainability. However, limited research has focused on regime changes in SES under different modes of water resource utilization. In this study, we employ a concise theoretical framework to analyze regime shifts in the arid Tarim River Basin, considering changes in SES components. Additionally, we explore the drivers and local and regional effects of these shifts. The regime shifts in SES are categorized into four evolutionary phases: "Low productivity," "Slow population expansion," "Rapid environmental destruction," and "Ecological restoration and improvement" over the past 12,000 years. The reciprocal coupling of SES components plays a vital role in determining the regime of SES, which is heavily influenced by the utilization of water resources and the degradation of the environment. While increasing water consumption is a core factor leading to environmental destruction, it also drives socioeconomic growth. During the process of SES shift, the rational allocation and use of water resources can shape an ideal regime that promotes regional ecosystem restoration. The empirical connections between the different phases of SES in the regime shift, their drivers, and their adverse or beneficial impacts provide valuable insights for sustainable SES management. Lessons from basin management that solely pursues single goals and focuses on local aspects, without considering these connections, have significant implications for long-term planning and policy formulation in arid basins worldwide.

Optimal allocation of water resources in the middle route of south-to-north water diversion project based on multi-regional input-output model

Long-distance water diversion, as an essential degree to alleviate the imbalance of regional water resource distribution, has become a crucial part of the global efforts of water conservancy and water ecology. However, the way to ensure green use of water resources while adequately diverting water is an urgent hassle to be solved. Based on relevant data from 11 cities in the water receiving areas along the Middle Route of the South-to-North Water Diversion Project and Markowitz's portfolio model, this study selects nine independent and representative indicators from the economic, social, and ecological aspects. Using the benefits of these nine indicators in 2015–2021 as a basis, the water diversion allocation portfolio with the greatest comprehensive benefits under normal operation of the Middle Route of the South-to-North Water Diversion Project was calculated and evaluated, and the benefits were measured and verified using the input–output model. The results demonstrate that, taking Beijing as an example, the comprehensive benefits will reach the maximum when the water supplied for economic, social, and ecological aspects is 15.16%, 56.35%, and 28.49%, respectively. At this time, economic benefits scored 9.50, which provide the greatest impetus to promote ecological and social development in water-affected areas along the route. While ecological and social benefits, which aim to protect the ecosystem and improve livelihoods, have a lower ability to promote development in water-affected areas.

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, 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.

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.

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.

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

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

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.