Optimal Allocation Of Water Resources Research Articles

Study on the ecological water demand security assessment for the Panjin wetland based on landscape pattern

Abstract The model was used to predict and analyze the future changes in the total ecological water demand of the Panjin wetland, with a view to providing some scientific reference for the optimal allocation of regional water resources and the sustainable development of wetlands. The results showed that (1) the quality of the habitat environment in the Panjin wetland has a great influence on the change of the total water demand, and the total ecological water demand in the Panjin wetland will continue to decrease in the future. (2) There is a clear correlation between landscape pattern and ecological water demand. (3) The distribution characteristics of the landscape pattern are greatly influenced by political factors, thus affecting the total ecological water demand of the Panjin wetland.

High resolution annual irrigation water use maps in China based-on input variables selection and convolutional neural networks

Water use and available water resources are the prerequisites for optimal water resources allocation, which is an efficient way to alleviate water scarcity all over the world. However, the spatial scales of water use and available water resources are often not matched due to their different ways for data surveying or observing. The spatial distributed (grid-scale) water use map is one of the ways to convert the spatial scales of the water use and available water resources. As irrigation is essential to guarantee sustainable development of agriculture, food security and economy, and accounts for most water use in China. A framework to generate high resolution (1 km) annual irrigation water use maps has been proposed. An iterative input variables selection (IIS) algorithm is adopted to select the optimal input variables among candidate input variables. After determining the optimal input variables, the convolutional neural network (CNN) is built to establish the relationship between the selected input variables and the irrigation water use. The spatial distributed irrigation water use maps can be produced by the trained CNN with the selected input variables at grid scale. The spatial distributed annual irrigation water use maps in China is produced at 1 km resolution from 1998 to 2013, and the performance of the framework has been proven to be credible with three metrics (i.e., root mean squared error, Nash Sutcliffe efficiency coefficient and relative error). Based on the spatial distributed annual irrigation water use maps, the spatial autocorrelation of annual irrigation water use in China is weak and the clustered pattern is random with 99% confidence. The temporal changing pattern mainly depends on precipitation and soil moisture in most prefectures, and the change of the cultivated area can also lead to dramatic change of the annual irrigation water use in China. The proposed framework can generate high resolution spatial distributed annual irrigation water use maps at grid scale, and the maps can be applied to ensure the optimal water resources allocation to realize efficient utilization of water resources and the agricultural policy-making.

Optimization Model of Water Resources Allocation in Coal Mine Area Based on Ecological Environment Priority

It is of great practical significance to explore the efficient water resources allocation model based on ecological environment priority in coal mine areas. In this paper, an open-well coal mining area is selected as the study area. Firstly, the changing characteristics of water supply and demand balance in the study area during 2015–2020 are studied, and the defects of the existing water resources allocation mode are analyzed. Then, considering the economic, social, and ecological factors, a multi-objective model of optimal allocation of water resources was established. Finally, the optimal water resource allocation scheme was obtained by using a particle swarm optimization algorithm. The results indicate that both the water supply and consumption in the study area decreased from 2015 to 2020. The utilization rate of fresh water also has been declining year by year, and the water source structure tilted to the reclaimed water resources. Among water users, coal mining water consumption is the highest, while ecological water consumption is the lowest. There is still a large amount of recycled water that has not been reused, resulting in a waste of water resources. The optimal water resources allocation scheme shows that the allocation scheme meets the needs of each water user within the limits of the water supply source. The sewage reuse rate reached nearly 100%, which realized the maximum utilization efficiency of water resources. The utilization rate of fresh water was 29.94%, and the dependence on freshwater resources was reduced. Reclaimed water accounts for 77.8% of the total water consumption. The water source structure has been optimized to realize efficient use of water resources.

Distribution characteristics and influencing factors of water resources in Henan Province

Abstract A clear understanding of the spatial and temporal distribution characteristics of water resources is essential for the optimal allocation and sustainable utilization of water resources. In this paper, the spatial and temporal distribution characteristics of water resources in Henan Province were studied based on GIS, combining the Mann-Kendall (M-K) nonparametric test and rescaled range (R/S) analysis. In addition, SPSS software was used to analyze the influence of climate and land use type on water resources. The results indicated that (1) the hot spots of water resources were concentrated in the southwest, while the low values were concentrated in the northeast, and the distribution of water resources decreased from southwest to northeast. (2) In the past 21 years, spatiotemporal mutations in the water resource sequence occurred between 2010 and 2014. The Z-values of the M-K trend test were all less than 0, the H-values of groundwater resources (GWRs) were mostly greater than 0.5, and the h-values of surface water resources (SWRs) and total water resources (TWRs) were less than 0.5, showing an overall declining trend. However, this trend may change in the future. (3) From the correlation analysis, climate change had a greater impact on water resources than land use changes did.

Optimal Allocation of Water Resources Based on GWAS Model in Handan, China

Optimal allocation of water resources is an effective way to solve the supply and demand contradiction between water resources and water users. Recently, the rapid economic and social development of Handan has significantly increased water demand in various industries. Superimposed on the reduction of incoming water in upstream rivers and the limitation of the total amount of groundwater extraction, a large number of water sources such as South-to-North Water Diversion, Yellow River Water Diversion, and Weihe River Water Diversion are used to replace domestic and industrial water. In support of Handan’s dynamic supply and demand of water resources, the transported water was generalized as a virtual reservoir and introduced into the GWAS model. The allocation results show that the total water shortage volume and rate of Handan was 527.60 × 106 m3 and 17.92% in 2025 at a P = 50%, respectively. Water shortage was concentrated in the primary industry. The allocation results align with actual water use conditions. The allocation of transported water is more reasonable than the conventional allocation scheme, and the domestic water is completely replaced by the South-to-North Water Diversion in the eastern plain of Handan. These research results can provide a technical reference for water resource allocation in Handan.

Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests

In water resources management on a global scale, it is important to reconcile the conflicting interests of different regions and actors regarding water use. To solve this issue more effectively, an optimal allocation model of water resources that coordinates the interests of regional multi-level water resource managers and balances the benefits acquired by regional multi-level water resource managers was proposed. The model consisted of three components, including option generation, option selection, and fallback bargaining. The Hybrid Strategy Whale Optimization Algorithm (HSWOA) was created to generate the initial alternative set throughout the alternative generation process. In the alternative screening process, quick non-dominated sorting was used to choose Pareto alternatives from the initial alternative set. Through many rounds of negotiations, water resource managers at all levels reached a consensual water resource allocation plan during fallback bargaining. This model was used to reconcile the conflicting water interests of municipal and county water managers in Handan, China, in terms of economic, social, and ecological benefits. It was also compared with the Pareto solution set obtained from NSGA-III. In terms of convergence speed and accuracy, the results demonstrated that HSWOA outperformed the Whale Optimization Algorithm (WOA). The results show that several rounds of discussions between municipal and county water management eventually resulted in Nash equilibrium. In normal flow year, the recommended scheme could yield economic benefit of 315.08×108 Yuan, social benefit of 0.1700, and ecological benefit of 5.70 × 106 m3, whereas in low flow year, the recommended scheme could yield economic benefit of 354.85×108 Yuan, social benefit of 0.2103, and ecological benefit of 57.82 × 106 m3. Compared to existing studies, the recommended scheme has clear advantages in terms of social and ecological benefits. The proposed optimal water resource allocation was Pareto optimal. This paper presented a new way of thinking about reconciling the conflicting interests of different levels of water resource managers in the process of water allocation.

Based AHP Loss Function Model for Equilibrium Dam Water Use

The purpose of this paper is to establish a model to balance water for power generation and domestic use. Dams and reservoirs have been an important part of human production and life since ancient times. In order to make full use of water resources, we have modelled the distribution of water resources in Lake Powell and Lake Mead to help achieve optimal allocation of water resources. Several models are established, Model I: Multiobjective Optimization. Model II: Loss function model based on Analytic Hierarchy Process. The discussion of the above models covers a wealth of industry factors and emergencies, so our model has strong adaptability and flexibility. It can be used not only in the factor we are learning, but also in other factors. Finally, we conduct a sensitivity analysis for extreme climate events. The results show that the model is insensitive to changes in extreme climate events, which means it can deal with water allocation problems in extreme situations. The model can be considered stable.

Analysis of Virtual Water Flow Patterns and Their Drivers in the Yellow River Basin

Virtual water flows have a profound impact on the natural water system of a country or region, and they may help conserve local water resources or exacerbate water scarcity in some areas. However, current research has only focused on the measurement of virtual water flows, without analysis of the causes of virtual water flow patterns. This study first obtained virtual water flow patterns across provinces by constructing a multi-regional input–-output (MRIO) model of the Yellow River basin in 2012 and 2017, and then analyzed its driving factors by applying the extended STIRPAT model to provide directions for using virtual water trade to alleviate water shortages in water-scarce areas of the basin. We found the following: (1) The Yellow River basin as a whole had a net virtual water inflow in 2012 and 2017, and the net inflow has increased from 2.14 billion m3 to 33.67 billion m3. (2) Different provinces or regions assume different roles in the virtual water trade within the basin. (3) There is an obvious regional heterogeneity in the virtual water flows in different subsectors. (4) Per capita GDP, tertiary industry contribution rate, consumer price index, and water scarcity are the main positive drivers of virtual water inflow in the Yellow River Basin provinces, while primary industry contribution rate, per capita water resources, and water use per unit arable area promote virtual water outflow. The results of this paper present useful information for understanding the driving factors of virtual water flow, which could promote the optimal allocation of water resources in the Yellow River basin and achieve ecological protection and high-quality development in this area.

Impacts of Climate Change on Natural Runoff in the Yellow River Basin of China during 1961–2020

The change in natural runoff is highly relevant to total river flow dispatch and water resource utilization in the Yellow River Basin (YRB). Based on the annual mean temperature and total precipitation records from 70 meteorological stations from 1961–2020, the impact of climate change on the natural runoff of the YRB is investigated using the Mann-Kendall (M-K) test and Bivariate Wavelet analysis methods. Results show that the annual mean temperature over the YRB increased by 0.33 °C decade−1 during 1961–2020, with a warming rate of more than 0.40 °C decade−1 observed in its northern part. The annual total precipitation increases by 10–20 mm decade−1 in the northwest YRB, while it decreases by 20–30 mm decade−1 in the southeast YRB. The result of the M-K test shows abrupt variations in temperature and natural runoff, especially in the 1980s and 1990s. The decrease in natural runoff is closely tied to the increase (decrease) in temperature (precipitation), especially for the period 1993–2020. The bivariate wavelet coherence analysis further suggests that the decrease in the natural runoff, which has persisted over the past 60 years, is primarily driven by precipitation reduction rather than regional warming. In the stage of rapid warming, the inter-decadal influence of precipitation on natural runoff gradually changes to the influence of inter-annual fluctuation. The finding contributes to providing an important scientific basis for evaluating the optimal allocation of water resources in arid and semi-arid areas against the background of climate change.

Optimal allocation of agricultural water resources in Yanghe watershed considering blue water to green water ratio.

Yanghe Watershed has low annual rainfall, uneven spatial and temporal distribution, extreme shortage of water resources in some areas. The contradiction between supply and demand of water for agricultural production is prominent and the expected production value cannot be achieved. Therefore, it is necessary to investigate the supply and demand of agricultural water resources and the impact of green water on agricultural crops in Yanghe Watershed. This article proposes a new crop economic model for increasing the green-water footprint to blue-water footprint ratio (GWF:BWF) in accordance with the regional characteristics, alleviating agricultural water shortage in irrigation areas, optimizing water resource allocation, and achieving sustainable agricultural development. The proposition is based on a study of five crops in eight districts and counties in the Yanghe River watershed. By combining the economic model F with a crop water production function, we achieved 89.3%, 88.9%, 97.1%, 81.5%, and 87.0% of the optimal water demands of the five crops, respectively, and effectively improved the underground irrigation of crops and the water resource utilization efficiency. The GWF:BWF threshold interval was subsequently selected based on the temporal changes in the BWF and GWF in the study area. This enabled significant reduction of the planting area of blue-water crops and increase in the proportion of green-water crops, while also improving the agricultural economy of the Yanghe Watershed. The proposed model promises to afford enhanced management of agricultural irrigation areas that experience rainfall shortage. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Inter-basin water diversion homogenizes microbial communities mainly through stochastic assembly processes

Inter-basin water transfer is an effective manner to achieve the optimal allocation of water resources, while accompanied by some ecological effects. The responses of microorganisms to water diversion and the ecological processes in regulating the community assembly are still unclear. Taking the eastern route of South-to-North Water Diversion Project as the study area, we investigated the microbial community patterns and the underlying assemblage processes in habitats with different hydrological connectivity, including isolated lakes, connected lakes and man-made canal. The results showed that microbial communities in the canal had higher diversity, lower dissimilarity, weaker compositional variation, and stronger co-occurrence patterns compared with that in the connected and isolated lakes. These findings suggested that the increase of connectivity among natural aquatic habitats due to water diversion can homogenize microbial communities and reduce microbial heterogeneity. The neutral and null models demonstrated the importance of stochastic processes in shaping microbial community assembly. Dispersal limitation and variable selection were the predominant mechanisms structuring microbial communities in the isolated lakes. Due to the homogenized environmental condition and the enhanced hydrologic connectivity in the canal and the connected lakes, microbial communities had higher dispersal capability and ecological drift occurred more frequently in these lotic habitats. The variations in microbial community structure were mainly driven by biotic ecological succession than abiotic factors, with positive and negative cohesion explained 63% and 25% of variability, respectively. Six taxa were considered as the potential introduced microorganisms, which may favor the nutrient biogeochemical cycling and the organic matter degradation, but may also bring ecological risks. Overall, this study provides a deeper understanding of the ecological consequences of inter-basin water diversion, and helps the regulation and management of these projects.

Evaluation of metaheuristic optimization algorithms for optimal allocation of surface water and groundwater resources for crop production

Extensive variability in current climatic conditions necessitates the need for optimal planning of water resources to manage socio-economic and environmental requirements efficiently. The optimal allocation of surface water and groundwater is essential to maximize crop net return due to uncertainty in seasonal rainfall, groundwater, and surface water availability in each region. This study demonstrated a multi-objective model to maximize the crop net return and efficient management of water resources. The multi-objective model comprised three objective functions maximizing the crop net return, minimizing the water deficit, and maximizing the aquifer recharge. The model’s practicability was analyzed through the case study of the Pennar-Palar-Cauvery link canal command in India. Three meta-heuristic approaches, particle swarm optimization (PSO), genetic algorithm (GA), and marine predators algorithm (MPA), were employed to solve the presented model. And their performance was evaluated using hypervolume and coverage metrics, indicating MPA’s superiority in obtaining well-distributed Pareto-optimal solutions. Thus, decision-makers can choose the best feasible solution based on current resource availability and preferences. The model was executed considering different cropping area deviations (5–25%) in the existing cropping pattern and allowance of groundwater mining from 0% to 70%. The obtained cropping pattern utilizing MPA at 25% cropping deviation achieved an increased net return of 1327.05 million INR.

Research on the optimal allocation of agricultural water and soil resources in the Heihe River Basin based on SWAT and intelligent optimization

In the context of global climate change, changes in precipitation and temperature conditions, especially the increasing frequency of extreme climate events, have a severe impact on agricultural production. Predicting climate change and adjusting planting structures over time are critical to sustainable agricultural development. In this study, the Coupled Model Intercomparison Project Phase 6 (CMIP6) and Soil and Water Assessment Tool (SWAT) models were used to simulate the future climate and runoff in the middle reaches of the Heihe River Basin (MHR). Then, the MOPSO and NSGA-II were used to plan future planting structures. The results showed that the temperature and precipitation in the MHR showed an increasing trend. By the 2070 s, the temperature was projected to increase by more than 2 °C under SSP245, while that under SSP585 was more than 4 °C. The annual mean precipitation was projected to increase, but the distribution was uneven, and the increased precipitation was mainly concentrated in spring and autumn. Under the interaction of temperature and precipitation, the runoff of the Heihe River will increase in the future, especially under SSP585, and the runoff of the Heihe River is projected to reach 2.48 billion m³/a in the 2070 s. Crop water demand was projected to increase with temperature, and crop irrigation water demand would increase by 14.4 % in the 2070 s under SSP245. Planting vegetables helps to improve agricultural economic benefits and carbon sinks, but to control soil erosion, the area of vegetables is best kept at approximately 16 %. Fertilizers and agricultural films are the primary carbon sources in agricultural production activities in MHR, accounting for more than 60 % of the total carbon. This study suggests promoting sustainable agricultural development by improving irrigation efficiency, using low-carbon fertilizers, controlling soil erosion, and gradually expanding the vegetable planting area with a considered ecological environment.

Construction and application of a refined model for the optimal allocation of water resources — Taking Guantao County, China as an example

The traditional optimal allocation of water resources mostly focuses on the allocation of different water supply sources to various types of water users in life, production, and ecology, and cannot reflect the differences in time and space of a certain type of water users. Therefore, this paper constructs a refined model for the optimal allocation of water resources, and further explores the optimal allocation of water resources with multiple water sources, multiple users, and multiple objectives. The main steps of the model construction are: (1) Regional gridding. The planting structure map and land use type map of the same resolution in the study area are selected and superimposed on them, the application attributes of each cell can be directly obtained. (2) Water demand gridding. On the basis of gridding in the study area, according to the application attributes of each cell, the quota method is used to predict the water demand of each cell. Then the water demand forecast result for the entire research area is obtained. (3) Water supply gridding. It is possible to reflect the types of water supply sources that a certain or a certain type of cell can accept, as well as the types of water supply sources that can be supplied by a certain type of water supply sources, by determining the types of water supply sources in the research area. The supply ranges that various water supply sources can reach, followed by the completion of the water supply grid. (4) According to the results of water demand gridding and water supply gridding, the water demand of each cell and the corresponding water supply source and water supply topological relationship are established, and the objective function is to minimize water shortage and maximize economic benefits to build a refined model for the optimal allocation of water resources.(5) The particle swarm algorithm is introduced to solve it, and the Pareto optimal solutions is obtained to determine the optimal water distribution for each cell. (6) Taking Guantao County, China as an example, the model was applied. In terms of minimum water shortage, the total water demand in Guantao County is predicted to be 118.8719 million m3 in the planning year (P = 50 %), while the total water supply is 125.2818 million m3. The water supply can meet the demand for water. In terms of financial advantages, the planned level of water Annual economic benefits will amount to 4.0865 million yuan.

Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China

The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization.

Efficient Utilization and Optimal Allocation of Agricultural Water Resources in the Yellow River Basin

Efficient Utilization and Optimal Allocation of Agricultural Water Resources in the Yellow River Basin

Research on Optimal Allocation of Water Resources in Handan City Based on the Refined Water Resource Allocation Model

In order to realize the dynamic regulation and control of regional water resources and alleviate the imbalance between supply and demand of regional water resources, on the basis of the demand of refined management of water resources, the dynamic General Water Allocation and Simulation Model (GWAS) of Handan City was constructed. The research on the optimal allocation of water resources in different regions and counties under different normal and dry years in the planning years (2025 and 2035) was carried out. The results show that the allocated water volume in the normal and dry years of Handan in 2025 is 2.248 billion m3 and 2.150 billion m3, respectively, and the water shortage rate is 11.72% and 22.11%, respectively. The water shortage is mainly in agriculture. In 2035, the allocated water volumes in normal and dry years will be 2.504 billion m3 and 2.33 billion m3, respectively, and the water shortage rates will be 4.50% and 21.84%, respectively. After optimized allocation, the water supply structure was significantly improved. The proportion of groundwater supply will decrease at each planning level year, and the water supply of external water transfer and unconventional water will increase. This research can provide technical reference to the Handan development scheme depending on water resources in the future, as well as the optimal allocation of water resources in other cities in the Beijing–Tianjin–Hebei Region.

Simulation of daily maize evapotranspiration at different growth stages using four machine learning models in semi-humid regions of northwest China

The accurate estimation of crop evapotranspiration (ETc) is essential for precision irrigation, optimal allocation of regional water resources, and efficiency improvement of agricultural water resources. This study developed Random Forest (RF), Support Vector Machine (SVM), Artificial Neural Network (ANN) and Extreme Learning Machine (ELM) models for maize ETc estimation in northwest China. The meteorological data and crop data from 2011 to 2012 were used to train the RF, SVM, ANN and ELM. The models’ simulation accuracy was verified by using the data of 2013 under six different input combinations. The input combinations included daily data for crop coefficient (Kc), global solar radiation (Rs), wind speed (u2), maximum and minimum air temperatures (Tmax and Tmin), and maximum and minimum relative humidity (RHmax and RHmin). The results showed that the SVM model achieved the highest simulation accuracy at the seedling emergence to jointing stage and at the grouting to harvest stage of summer maize, with the coefficient of determination (R2) ranging 0.701–0.895 and 0.637–0.841, mean absolute error (MAE) ranging 0.310–0.654 and 0.468–0.743 mm/d, and mean square error (MSE) ranging 0.227–0.722 and 0.513–1.227 mm/d, respectively. The ELM model achieved the highest simulation accuracy at the booting to silking stage and during the whole growth period, the coefficient of determination (R2) ranging 0.601–0.828 and 0.891–0.954, mean absolute error (MAE) ranging 0.418–1.194 and 0.285–0.530 mm/d, and mean square error (MSE) ranging 0.887–2.515 and 0.182–0.587 mm/d, respectively. Considering the accessibility and simulation accuracy of input parameters, the SVMⅠ-2, ELMⅡ-5, SVMIII-4, and ELMIV-2 models were recommended for simulating ETc at the seedling emergence to jointing stage, at the booting to silking stage, at the grouting to harvest stage, and during the whole growth period, with the coefficient of determination (R2) of 0.796, 0.879, 0.800 and 0.896, mean absolute error (MAE) of 0.416, 0.418, 0.553 and 0.328 mm/d, and mean square error (MSE) of 0.327, 0.887, 0.655 and 0.190 mm/d, respectively. In conclusion, machine learning models can accurately simulate the daily evapotranspiration of maize in northwest China.

Coordinated optimal allocation of water resources and industrial structure in the Beijing–Tianjin–Hebei regions of China

Coordinated optimal allocation of water resources and industrial structure in the Beijing–Tianjin–Hebei regions of China

Study on Water Quantity Allocation Optimization for Single Main Canal in Large-Scale Irrigation Area Based on DP Method

The mathematical model of optimal water quantity allocation for a single main canal in a large-scale irrigation area was constructed that took the minimal sum of the squared deviation of water shortage for water receiving areas controlled by the single main canal in one given irrigation period as the study target, and the total irrigation quantity of the single main canal as a constraint condition. Taking the optimal allocation of water quantity of each branch canal as decision variables, and several branch canals under the irrigation sequence of the main canal as a state variable, this model was solved by the one-dimensional dynamic programming (DP) method, by which the minimal water shortage and corresponding optimal water quantity allocation of each branch canal was calculated. The proposed method could provide a decision-making reference for optimal water resources allocation of single main canal irrigation areas, and also provide the theoretical basis for optimal water quantity allocation of a main canal with rotation irrigation by strips or with segmented rotation irrigation mode in China’s large-scale irrigation areas. Taking Hengliu Main Canal of Zhouqiao Irrigation Area in Jiangsu Province as a study case, optimization results showed that in a medium drought year (p = 75%) and a special drought year (p = 95%), minimal water shortage for water receiving areas controlled by Hengliu Main Canal was respectively 2.57 × 104 m3 and 23.31 × 104 m3 during the ponding period of rice. The corresponding water quantity allocation for each branch canal has reflected a compellent model solution precision and efficiency.