Water Allocation Strategies Research Articles

Prediction of Sediment Transport and Deposition in the Stone Buddha Temple Reservoir Based on HD and ST Bidirectional Coupling Model

Reservoirs deliver vital ecological services, including water storage and drainage. However, these functions are increasingly compromised by the dual pressures of climate change and human activities. Among the most pressing concerns is reservoir sedimentation, highlighting the urgency of investigating hydrodynamic sediment scouring. This study focuses on the plain reservoirs of Liaoning Province, using the Shifo Temple Reservoir as a case study. An optimized sediment scouring scheme was developed based on the reservoir’s hydrodynamic characteristics to improve water and sediment management. A coupled hydrodynamic and sediment transport (ST) model was constructed to simulate runoff dynamics and sediment distribution within the Liao he River Basin, while the MIKE21 model was applied to simulate the interaction between the hydrodynamics and sediment transport. The study analyzed groundwater dynamics across different runoff scenarios, seasons, and representative years, offering a scientific foundation for optimizing water and sediment allocation strategies. The results demonstrated a strong correlation between simulated and observed data during validation, confirming the accuracy of the hydrodynamic simulations. Utilizing the coupled HD and ST modules, the study proposed a sediment transfer scheme. The analysis revealed that flow rates between 165 and 190 m3/s significantly enhance sediment scouring in the long term (2029–2039) compared to the short term (2024–2029), effectively reducing sedimentation, minimizing deposition length, and lowering silt removal costs. The findings offer critical insights for predicting reservoir evolution and conducting risk assessments, thereby contributing to the sustainable management and ecological restoration of water systems in Liaoning Province.

A distributed simulation-optimization framework for many-objective water resources allocation in canal-well combined irrigation district under diverse supply and demand scenarios

To address the issues of both water resources allocation and sustainable management in agriculture areas with rising food demand, a simulation-optimization framework based on Flopy and Pymoo was proposed and developed for canal-well combined irrigation districts. The proposed framework first solved the many-objective water resources allocation problem which integrates groundwater simulation, crop production, and farmer income modules to quantitatively reveal the various trade-offs and synergies by using NSGA-III algorithm. The Entropy-TOPSIS method was then applied to recommend proper water allocation schemes. The proposed framework was further tested in Baojixia irrigation district considering various water supply and crop demand scenarios based on Copula-based uncertainty analysis. The Key findings are as follows: (1) the proposed framework could effectively optimize conjunctive water resources allocation problems of both surface water and groundwater; (2) low supply combined with high demand (p=0.17) is more likely to occur than high supply with high demand (p=0.02); (3) increased crop demand and restricted surface water negatively impact both water productivity and groundwater sustainability; and (4) the cumulative groundwater drawdown of recommend schemes is 36.9 % and 6.5 % higher under low to medium supply scenarios, while water productivity of recommend schemes decreases 28.2 % and 9.7 % with high and medium demand. This framework could provide useful insights for sustainable agricultural water management in canal-well combined irrigation district with various uncertainties in supply and demand scenarios.

Interannual moisture variability on the Qinghai Plateau: Trends, patterns, and implications

Investigating surface dry-wet patterns on the Qinghai Plateau (QP) is crucial for water allocation, ecological sustainability, and climate variability adaptation strategies. Existing discrepancies in the QP dry-wet trends and distribution characteristics underscored the need for a more refined analysis. This study utilized the Thornthwaite Moisture Index (IM) to quantify changes in surface dryness and wetness under prevailing climatic conditions. Linear trend regression and ensemble empirical mode decomposition (EEMD) were applied to study the dynamic and periodic characteristics of the QP from 1980 to 2018.Our findings revealed a decrease from southeast to northwest in IM, with the semi-arid and sub-humid transition line aligning closely with the 400 mm isohyet. The dry-wet transition line exhibited a northwestward trend over the past four decades. Possibly influenced by monsoon circulation and El Niño-Southern Oscillation (ENSO), the annual IM displayed a quasi-cycle of 3 to 5 years, manifested by a dry period (1990–2004) and a wet period (2005–2012). However, spatial differences existed, challenging the universality of the “Dry gets Drier and Wet gets Wetter (DDWW)” pattern. Precipitation (PRCP) changes could predict over 90 % of IM spatiotemporal variations. Additionally, the IM response to Average Temperature (TAVG) exhibited an inverted U-shaped curve, with a boundary (−3.8 °C) below which cooler regions became wetter and above which they became drier. The observed warming and precipitation shifts suggested that continued warming could lead to warmer and wetter climates, potentially causing ecological and environmental problems. Therefore, examining the surface moisture budget is of critical scientific and practical significance, in order to provide a decision-making basis for mitigating and adapting to climate change.

Water–Ecological Health Assessment Considering Water Supply–Demand Balance and Water Supply Security: A Case Study in Xinjiang

Water scarcity and ecological degradation in arid zones present significant challenges to regional ecological health. Despite this, integrating the water supply–demand balance and water supply security (SEC) into ecological health assessments—particularly through composite indicators—remains underexplored in arid regions. In this study, we assessed the ecological health changes in Xinjiang by utilizing multivariate remote sensing data, focusing on the balance between water supply and demand, the degree of SEC, and ecosystem resilience (ER). Our results indicate that while water supply and demand remained relatively stable in northern Xinjiang between 2000 and 2020, the conflict between supply and demand intensified in the southern and eastern agricultural regions. SEC evaluations revealed that 73.3% of the region experienced varying degrees of decline over the 20-year period. Additionally, ER assessments showed that 7.12% of the region exhibited a significant decline, with 78.6% experiencing overall reductions in ecological health. The indicators’ response to drought demonstrated that improvements in ecological health during wet conditions were less pronounced than declines during droughts. This study underscores the necessity of prioritizing areas with lower ecological health in future water allocation strategies to optimize water resource utilization.

Assessing Water Demands and Allocation Strategies Using the Water Evaluation and Planning System—A Case Study of the Ghrib Basin, Algeria

The Ghrib Basin is currently encountering water-related challenges due to population growth and growing competition among water users. Therefore, assessing the current water situation is essential for the anticipation of future needs in the region. This paper assesses water demand and allocation strategies in the Ghrib Basin, Algeria, using the Water Evaluation and Planning (WEAP) system. The simulation is based on five scenarios: “Increase in population and agricultural activity”, “Improving agricultural activity”, “Minimum domestic consumption”, “Enhancing Water Resources”, and “Best practice”, (which is a combination of two scenarios, i.e., “Improving agricultural activity” and ”Minimum domestic consumption”). The simulation outcomes indicate that the “Best practice” scenario represents the most advantageous and beneficial scenario by which the problem of the unmet demand can be solved. The resulting simulations indicated the need for the employment of water-efficient irrigation systems as well as the encouragement of sustainable water use, such as drip irrigation, which necessitates coordinated efforts and particular infrastructural investments. The derived outcomes are highly convincing and have the potential to serve as a decision support system for the effective governance of water resources in the Ghrib Basin. The methodology utilized in this study has the potential to be implemented in any basin across the globe.

Multi-objective optimal allocation of water resources in Shule River Basin of Northwest China based on climate change scenarios

The optimal allocation of water resources is crucial for addressing regional water scarcity, adapting to climate change, and promoting sustainable development. This study focused on the Shule River Basin and considered three climate scenarios (SSP1–2.6, SSP2–4.5, SSP5–8.5), which is combinations of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). A water resources optimal allocation model including water supply and demand prediction, multi-objective optimization, decision-making and analysis on optimal water allocation schemes was constructed. This model aims to analyze the optimal allocation of water resources in the Shule River Basin over three planning years (2025, 2030, 2035), considering guarantee rates of 50 % and 75 % under various climate scenarios. The obtained results indicate that: (1) An increasing trend in water demand in the planning year. For instance, under the SSP1–2.6 scenario, the basin's water demand is projected to reach 1.920×10^9 m3, 2.037×10^9 m3, and 2.103×10^9 m3 in 2025, 2030, and 2035, respectively. (2) The total water supply with a guarantee rate of 50 % (75 %) in the planning years is projected to be 1.939 (1.483)×10^9, 1.957(1.502) ×10^9, and 1.974 (1.519) ×10^9 m3, respectively. (3) In the three scenarios of SSP1–2.6, SSP2–4.5, and SSP5–8.5, the water demand for domestic and ecology is met in each planning year. There is a slight water shortage in the industrial sector, with a shortage rate ranging from 0 % to 13.41 %. The agricultural sector experiences the highest water shortage, with a rate of 1.93–44.77 %. (4) The water supply structure of each optimal allocation scheme of water resources was optimized. The economic benefits mainly depend on the industrial and ecological sectors. These findings offer valuable insights for optimizing the distribution of regional water resources in response to changing climatic conditions.

Quantifying water evaporation from large reservoirs: Implications for water management in water-stressed regions

Dam reservoirs are at the core of local water storage and supply, especially in water-stressed regions of the world with acute water shortage problems. However, evaporative losses from these reservoirs and their storage efficiency are often overlooked in water budgeting. We offer a mechanistic approach that combines physically-based modeling with remote sensing information of reservoir characteristics to reliably predict evaporative losses from dam reservoirs. The developed framework is used to predict evaporative water losses from potential dam reservoirs in different basins worldwide. We apply this framework to 10 of the largest dam reservoirs in the world's water-stressed regions to quantify evaporative water losses. Our analysis, spanning from 2000 to 2020, reveals considerable variations in annual evaporation rates in the reservoirs located in water-deprived regions exceeding 3200 mm/year during the study period with the total evaporative loss reaching 26.5 km3/year. The evaporative water loss accounts up to 15.8% of the storage capacity in one of the dam reservoirs, posing significant challenges for water allocation and conservation strategies, with notable economic and environmental consequences in regions already suffering from water scarcity.

Joint optimal allocation of regional water and land resources considering their mutual feed relationship

Water and land resources are indispensable prerequisites for the sustenance and advancement of human civilization. In recent decades, China has faced significant challenges in managing its water and land resources due to the intensifying competition resulting from rapid urbanization, industrialization, and population growth. The joint optimal allocation of water and land resources can effectively address these issues. However, there have been limited accomplishments in investigating the integrated water and land resources allocation system’s interaction with social, economic, and environmental development. This paper develops a novel joint optimal allocation model of regional water and land resources (JOAMRWLS). The model integrates water and land resources for integrated allocation, taking into account the mutual feed relationship between them, and thereby achieving comprehensive utilization and coordination of water and land resources within the region. Then a two-layer nesting algorithm based on successive approximation and nonlinear programming (SA-NLP) is proposed to solve the model, obtaining the regional optimal land use pattern and optimal water allocation scheme. Subsequently, this paper uses Luoyang City in Henan Province, China, as a case study to verify the proposed JOAMRWLS. The results indicate that the water volume and area of each land use type tend to stabilize after the fifth iteration of the calculation with a consistent water volume of 18.65 × 108 m3. Compared with the conventional optimization model of water resources (COMWR), the JOAMRWLS encompasses five cities experiencing water scarcity, whereas the latter includes twelve such cities. Furthermore, the economic benefit of the JOAMRWLS is 2.65 × 1011 CNY, surpassing that of the former at 2.56 × 1011 CNY, highlighting its superiority.

Construction of the water balance model for the Bontanga irrigation dam in Northern Ghana

ABSTRACT Freshwater resources are essential for the sustenance of all living things, for crop production and socio-economic activities. The objective of this study was to construct a water balance model aimed at optimizing reservoir management by analyzing variations in water availability in the reservoir. This model will help dam operators to adopt water allocation strategies, timing of water releases and storage decisions. An echo sounder was used to measure the depth of water. Crop water requirements were computed using FAO CROPWAT 8 software, and the InVEST-SDR model was used to estimate sediments exported downstream of the watershed. Model construction utilized multiple linear regression, and the results were tested at a level of significance α = 0.05. Model performance was evaluated using a coefficient of determination (R2) and the ratio of the root mean square error to the standard deviation of measured data (RSR). The results revealed a coefficient of determination (R2) of 0.743 and a ratio of the root mean square error to the standard deviation of measured data (RSR) of 0.67. The constructed model will provide essential information to stakeholders on drought preparedness and mitigation, including water conservation measures and the management of water releases during critical periods.

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.

Research on the connectivity of urban river network-wetland and water quality simulation.

The connectivity of urban river networks plays an important role in cities in many aspects, such as urban water safety, water quality (WQ), and aquatic ecological balance. This study focuses on the river network and the Majiawan Wetland in the Chaoyang District of Beijing by establishing a two-dimensional hydrological WQ model employing various water allocation schemes between the river network and the wetland. Water circulation and WQ are the main indexes, and the effects of different scenarios on improving water circulation and WQ are simulated and compared. This study demonstrates that the addition of water replenishment at the intersection of river network and internal slow-water zones of the wetland (Scheme 2) has greater effectiveness in improving both hydrology and WQ compared to two other schemes. The water area of the Majiawan Wetland has expanded, and water velocity has increased. Using chemical oxygen demand, total nitrogen, and total phosphorus as the index values for determining the water class, the WQ of about 20% of the wetland area was reached Water Class II (domestic drinking water), with Water Class III (general industrial water) accounting for the other 80%. This study provides valuable evaluation and reference for similar areas of urban river network connectivity.

Dynamic multiobjective two-stage fuzzy stochastic strategy for optimal water allocation in inter-basin water division under changing environment: A case study of Hanjiang-to-Weihe water division in Shaanxi Province, China

Extensive environmental changes increase the complex uncertainty surrounding water allocation systems, and irrational water allocation further exacerbates competition among users, posing formidable challenges to achieving dynamic and sustainable water resource management in inter-basin water diversion (IBWD) projects. This study established a dynamic multi-objective water allocation framework to address environmental change, uncertainty of water systems, and coordination between water allocation and deficit risk. The proposed framework focuses on water allocation as a continuous, multi-period decision-making process and considers reasonable water allocation from the individual to the overall multidimensionality. The feasibility and practicality of the framework were verified by long-term water allocation planning of the Hanjiang-to-Weihe IBWD in Shaanxi Province, China. The framework integrates the Soil and Water Assessment Tool model, three classical scenarios of the Coupled Model Intercomparison Project Phase 6, and optimization models to realize future sustainable water allocation optimal planning. The study found that the framework enables sustainable water allocation management and provides decisions for decision-makers under different water deficit conditions. Global optimal water allocation and the maximization of system benefits were achieved using multi-objective dynamic modeling. The average satisfaction level exceeded 0.9, and the Gini coefficient was below 0.05, both of which have a synergistic effect, with the former enhancing satisfaction within each subarea, and the latter ensuring equity among the subareas. The proposed framework aims to manage water resources of IBWD sustainably and provide optimal water allocation schemes to decision-makers under changing environments, which will alleviate water scarcity and interregional competition to promote regional sustainable development.

Surface Water Resource Accessibility Assessment of Rural Settlements in the Yellow River Basin

Analyzing the spatial relationship between humans and water is crucial for regional development and water allocation schemes, particularly in the face of extreme water scarcity in the Yellow River Basin. A quantitative evaluation model of surface water resource accessibility (SWRA) has been developed, with rural settlements serving as the research unit. This model is built upon three key dimensions: topography, distance, and surface water resources within the Yellow River Basin. The results show that: (1) The SWRA range spans from 0.13 to 0.88, with an average value of 0.47 and a standard deviation of 0.05. Higher SWRA values are concentrated in the eastern and western regions, while lower values are predominantly found in the central area. (2) The gradient of SWRA across the 12 catchments, from low to high, is as follows: Sanmenxia station, Lanzhou station, Shizuishan station, Longmen station, Tongguan station, Toudaoguai station, Xiaolangdi station, Huayuankou station, Lijin station, Gaocun station, Ai Shan station, and Tangnaihai station. (3) At the city scale, the SWRA values are generally higher in the eastern areas of 10 cities, with one exception being higher in the west. Conversely, in the western areas of nine cities, the SWRA values are lower. The remaining cities exhibit SWRA values at a medium level. The correlation coefficient between primary industry gross domestic product (GDP) and SWRA is 0.271 (N = 56, Sig = 0.043, in 0.05 level, the correlation is significant), which confirms that SWRA serves as a factor influencing GDP and is appropriately designed for assessing water accessibility. Consequently, managers can utilize SWRA results to make informed decisions regarding regional development and water allocation.

Quantifying the effects of institutional shifts on water governance in the Yellow River Basin: A social-ecological system perspective

Water governance in river basins worldwide faces challenges due to complex socio-economic and environmental factors. In the Yellow River Basin (YRB), two major institutional shifts, the 1987 Water Allocation Scheme (87-WAS) and the 1998 Unified Basin Regulation (98-UBR), aimed to address water allocation and usage issues. This study quantifies the net effects of these institutional shifts on water use within the YRB and analyzes the underlying reasons for their success or failure. We employ a Differenced Synthetic Control method to assess the impacts of the institutional shifts. Our analysis suggests that the 87-WAS unexpectedly increased water use by 5.75%, while the 98-UBR successfully reduced water use as anticipated. Our research highlights the role of institutional structures in governance policies, demonstrating that the mismatched structure of the 87-WAS led to increased competition and exploitation of water resources, while the 98-UBR, basin-wide authority and stronger connections between stakeholders, resulted in improved water governance. Our study underscores the importance of designing institutions that are consistent with the scale of the ecological system, promote cooperation among stakeholders, and adapt to changing social-ecological system (SES) contexts. As outdated and inflexible water quotas may no longer meet the demands of sustainable development in the YRB, policymakers must consider the potential consequences of institutional shifts and their impact on water use and sustainability.

Optimal water resource allocation considering virtual water trade in the Yellow River Basin

Water can be redistributed physically and virtually. We explored water allocation optimization to mitigate water stresses by constructing a physical–virtual dual water system and optimizing the 1987 Yellow River water allocation scheme. We calculated the virtual water volume, identified the virtual in-basin, out-of-basin, and export water volumes, and compared the total regional water demand (i.e., combined physical and virtual water volumes) with regional water planetary boundaries to optimize basin water allocation schemes. Virtual water accounted for > 90% of the total regional demands, whereas physical flows did not significantly impact them. Moreover, allocation quotas for Qinghai and Inner Mongolia should be reduced by 0.113 and 1.005 billion m3, respectively, for sustainability. Furthermore, improving the efficiency of water-intensive sectors and limiting virtual water outflows from heavy industry to out-of-basin sectors are vital to water intensification. Increased attention should be directed toward physical–virtual water demands than the current focus on supply-oriented water allocation.

Improving efficiency and sustainability of water-agriculture-energy nexus in a transboundary river basin under climate change: A double-sided stochastic factional optimization method

In this study, a double-sided stochastic fractional programming (DSFP) method is developed for identifying optimal water-allocation schemes of water-agriculture-energy nexus (WAEN) system under considering climate change impact. The advantages of DSFP are (i) handling complex uncertainty of double-sided randomness, (ii) addressing conflicting objectives with optimal system efficiency, and (iii) achieving trade-off between marginal benefit and system risk. Then, a DSFP-based water-agriculture-energy nexus (DSFP-WAEN) model is formulated for water resources allocation in a transboundary river basin of Central Asia, where 48 scenarios are designed to examine the impacts of climate change, irrigation efficiency, and system risk over a long-term planning horizon (2026–2050). Results reveal that: (i) among all agricultural activities, cash crop cultivation shows the greatest change in adaption to climate change, with the share of cash crop cultivation increasing to 70.7% by 2050 under RCP4.5; (ii) Kazakhstan, which has the largest irrigation needs and is the county most sensitive to water supply risk, should be the first to be constrained in the case of severe water shortages and poor delivery levels; (iii) the improvement of irrigation efficiency can increase the inflow to the Aral Sea by 2.7%, and reduce water loss of infield irrigation by 11.3% even under severe water shortage (i.e. p = 0.01). Compared with the models based on the traditional stochastic programming and single-objective methods, DSFP-WAEN has advantages in optimizing water-use efficiency and reflecting system complexity with flexible solutions. To coordinate transboundary water conflicts, strategies from both demand and supply sides related to quota management and water-saving techniques are suggested for the Syr Darya River basin, such as clean energy transition, drip irrigation promotion and canal system improvement. From a long-term planning perspective, WAEN schemes should be adapted to risk attitude and climate change, which can help address water scarcity and achieve future sustainability.

Dynamic multi-period sustainable water resources optimal allocation strategies: A case study of China

Global climate change and escalating water demand are exacerbating the burden on watershed management. In pursuit of a resilient water management framework, supportive of local economic growth and social stability, it is prudent for watershed management authorities to sequentially address the intricacies. The foremost step involves resolving supply–demand conflicts stemming from the seasonal ebb and flow before embarking on the development of an optimal dynamic allocation strategy. Therefore, this study has crafted a dynamic, seasonally responsive, multi-objective, multi-period water allocation system that harmonizes three pivotal objectives: economic efficiency, equity, and utilization efficiency. Then, to effectively mitigate the economic risks associated with uncertainty, the dynamic allocation framework incorporates the VaR and accounts for uncertainties in available surface water resources. Employing the improved adaptive self-constrained NSGA-III algorithm, we endeavored to simulate the optimal equilibrium solution in the face of various risks and facilitate a tradeoff between these objectives through a multi-period interaction mechanism. This iterative process displayed convergence within the range of 1.75 × 104 and 2.45 × 104 iterations. The proposed model was implemented to address the pressing issue of unsustainable water allocation within the MRB system in western China. Its validity and practicability were confirmed, and water allocation strategies were simulated across three distinct risk scenarios: high, medium, and low. Significantly, these findings have highlighted Chengdu as the focal area for considerable water apportionment. In light of this revelation, an emergency cooperation system has been established to address water shortages and uncertainties. Furthermore, some policy recommendations designed to guide watershed managers in the effective allocation of water resources.

Water allocation sustainability assessment in climate change: a modeling approach using water footprint and just policy

Abstract Climate change has challenged water allocation for food production in water-scarce areas. This fact calls for water reallocation (RA) strategies in basins with dominant agriculture. This study develops a framework combining the SWAT model and water footprint (WF) to evaluate water resource sustainability and improve its indices by fair RA from agriculture. The Karkheh River Basin in Iran was chosen as a study area for verification. Deficit irrigation (DI) was a farm strategy to promote basin sustainability and maintain food security. DI was distributed according to the equality of resources, proposed by Ronald Dworkin, as a just allocation principle. It means irrigated water would be allocated based on an equal water ratio per hectare. Results showed that the basin is currently unsustainable regarding the groundwater (BkWS) and surface flow (BuWS). According to the SSP5-8.5 scenario, the BuWS in the basin increases from 1.12 to 1.22 (9%), and BkWS increases from 2 to 2.15 (7.5%), while GnWS remains relatively constant at 0.99. By Dworkin's principle, DI caused 21-48% reduction in water allocation among five provinces. RA improved the BuWS, GnWS, and BkWS and ensured environmental flow. Climate change reduces 3.5% of food production, with an extra 9% by RA. These reductions would not endanger food security.

An improved bi-level programming model for water resources allocation under multiple uncertainties

Nowadays, with the scarcity of water resources, competition for water resources among different levels and water sectors is growing increasingly fierce. Furthermore, uncertainties are unavoidable in the water resources system. To address the aforementioned issues, a fuzzy max-min decision bi-level multi-objective interval programming model was proposed, which can not only focus on water conflicts at the same level or between different levels, but also pay attention to optimal allocation of water resources under uncertainty. The developed model was then applied to a case study in Wuwei City, Gansu Province, China, which selected fairness of water distribution and agricultural economic benefits as planning objectives. Based on the developed model, different water resources optimal allocation schemes under different representative hydrological years were provided. From the result, as representative hydrological years changed from wet (P = 25%) to dry (P = 75%), agricultural economic benefit and Gini coefficient of agriculture would vary from [35.19, 37.78] × 108 yuan to [31.12, 31.99] × 108 yuan and from [0.468, 0.429] to [0.505, 0.503], which indicates that as available water resources decrease, agricultural economic benefit would decrease and fairness of water distribution would also decrease. And the water distribution fairness of the upper bound water allocation scheme is higher than that of the lower bound water allocation scheme when in the same representative hydrological year. In addition, no matter what representative hydrological year, the results of the established bi-level programming model are always in the middle of the results of the upper and lower level individual objective, which means that the developed bi-level programming model has great advantage to deal with water competing conflict among different levels. Furthermore, based on the results of developed model, the reasonable water resources optimization schemes can be determined by the decision-makers when faced with multi-objective, bi-level and multiple uncertainties problems.

WHCrop: A novel water-heat driven crop model for estimating the spatiotemporal dynamics of crop growth for arid region

Crop models are widely used to assist in agricultural management decision-making and water productivity optimization. However, traditional crop models often depend on artificial and specific field management inputs, posing challenges in maintaining crops within a desired stress range. Consequently, the derived optimization schemes from these models become highly uncertain. Moreover, the complexity of the mechanisms involved and the multitude of parameters make it challenging to apply traditional crop models uniformly across various crops and regions. In this study, we have developed a novel crop model called WHCrop (Water-Heat Driven Crop model) that effectively captures, reflects, and controls the impact of various environmental factors (meteorology, topography, soil, and management) on crop growth process. The WHCrop model combines the simulation principles of biomass and yield from the CERES module in the DSSAT model, along with the soil water balance from the AquaCrop model, to estimate the dynamics of crop growth and production processes. Results indicated that WHCrop-based simulations, including canopy cover (CC), daily evapotranspiration (ET), and yield, matched well with ground-based measurements, and were better than the traditional crop model (DSSAT and AquaCrop) at both field and regional scales, especially under deficient irrigation conditions. Besides capturing the key variables associated with crop growth, WHCrop model could reproduce the adaptive response of these various to regional-scale temperature changes. Notably, the WHCrop model could effectively minimize uncertainties resulting from individual environmental change, thanks its incorporation of dynamic response mechanisms for crop growth under stress factors. Overall, the novel and informative WHCrop model offers some advantages over traditional crop models since it allows for optimal decision making to be derived from the randomly different inputs. As a result, the WHCrop model proves instrumental in assisting decision-makers in formulating critical water allocation strategies and developing effective management recommendations to enhance regional agricultural water productivity.