Regional Water Resources Allocation Research Articles

Coordinated allocation of conventional and unconventional water resources considering uncertainty and different stakeholders

The optimal allocation of water resources is a critical means of resolving the supply–demand paradox. To optimize the allocation of regional water resources, an Interval Numeral-Hierarchical Planning Model (INHPM) was established to integrate unconventional water resources into the water resource allocation system while simultaneously considering the interests of decision makers at different levels and the uncertainty in a water resource allocation system. The INHPM directs conventional and unconventional water supply departments to achieve coordinated development through the objective function of the synergy degree. The theory of synergy and the theory of information entropy serve as the theoretical foundations for the objective function of the synergy degree. In addition, the interval number was introduced to allow the INHPM to address uncertainty in a water resource allocation system. The hierarchical planning model served as the primary framework for assisting decision makers in minimizing conflicts of interest among various stakeholders in a water allocation system. In this paper, the Interval Multi-Objective Genetic Algorithm (IMOGA) was established to solve the INHPM, as opposed to the previous method of transforming the uncertainty model into a certainty model and solving it (IMOGA-INHPM). Finally, using the optimal allocation of conventional and unconventional water resources in Ordos, Northwest China, as an example, the results and comparison analysis of a case study demonstrate the IMOGA-practicability INHPM's and efficiency.

Investigating a Water Resource Allocation Model by Using Interval Fuzzy Two-Stage Robust Planning for the Yinma River Basin, Jilin Province, China

This study introduces a fuzzy method to construct the interval fuzzy two-stage robust (ITSFR) water resource optimal allocation model based on the interval two-stage robust (ITSR) water resource optimal allocation model. Optimal economic benefit was considered the objective function, and the number of available water resources, sewage treatment capacity, reuse water treatment capacity, and total pollutant control were considered as the constraints. Under three five-year planning periods (2015–2020, 2020–2025, and 2025–2030) and according to the allocation levels of dry, flat, and abundant water periods (low, medium, and high discharge), the pollution absorption, upgrading projects, and water resource allocation schemes of various water sectors (industry, municipal life, ecological environment, and agricultural sector) in the Yinma River Basin were optimized. Water consumption quota is an interval value; high and low water consumption lead to a waste of water resources in the water consumption sector and restrict the development of the water consumption sector, respectively, which indicates that the water consumption quota has the characteristics of fuzzy uncertainty. Therefore, the optimization model was set as a fuzzy parameter in the solution process. The simulation results indicated that water quota can directly influence the income of water resource use, and thus, indirectly influence the economic benefit of the Yinma River Basin during the planning period. In the planning period of the Yinma River Basin, the economic benefit interval of dry, flat, and abundant water periods was reduced by 57%, 55%, and 48%, respectively, which provides a robust method with the advantages of a balanced economy, a stable system, reduced decision-making space, and significantly improved decision-making efficiency. Moreover, the emission ranges of typical pollution indicators (chemical oxygen demand (COD) and ammonia nitrogen) in the eight counties and urban areas of the Yinma River Basin were significantly reduced during the three planning periods (Dehui area had the highest overall reduction of ammonia nitrogen in the industrial sector during the second five-year planning period, up to 65%), which indicated a significant improvement in the decision-making efficiency. In addition to the Changchun City planning areas dominated by the agriculture production water sector, water resource allocation accounts for >80% of the regional water resource allocation; using the fuzzy optimization method after the Yinma River Basin water resource allocation model, the overall water deficit was significantly reduced; moreover, it was almost the same as in the first five-year period of Changchun City industry water deficit, which declined by up to 33%. The problem of resource waste caused by excessive water limiting in the water sector could be avoided because of the fuzzy water limit. To solve the prominent problem of water deficit in large- and medium-sized cities in the basin, industrial and ecological water sectors can implement measures such as water resource reuse. The total amount of water reuse in a medium year increases by up to 46% compared with that in the ITSR optimization model, which can be attributed to the reduced water consumption limit range of water consumption sectors after the fuzzy water consumption limit. This shows that more water can be allocated to meet the requirements of the water sector during decision-making. In conclusion, this study offers an effective scheme for decision makers to plan water resource allocation in the Yinma River Basin.

Optimal allocation of regional water resources under water saving management contract

Optimal allocation of regional water resources under water saving management contract

Forecast of regional water demand based on NSGAII-FORAGM

Abstract Regional water demand is an important basic data for regional engineering planning, design and management. Making full use of multi-source data and prior knowledge to quickly and economically obtain high-precision regional water demand is of great significance to the optimal allocation of regional water resources. In order to accurately predict the regional water demand, this study took Yulin City as a research area to predict the water demand of the city from 2017 to 2019. Aiming at the oscillating characteristics of the regional water demand sequence and the over-fitting problem of traditional prediction models, this study proposed the non-dominated sorting genetic algorithm II-fractional order reverse accumulative grey model (NSGAII-FORAGM). The regional water demand oscillation sequence was transformed into a monotonically decreasing non-negative sequence. Based on the transformation sequence, an optimization model was constructed according to the two objective functions of ‘maximum (or minimum) order’ and ‘best fit to historical data’, and the NSGAII method was adopted to solve the model. The three model structures of ‘fractional order’, ‘reverse accumulation’ and ‘obtaining order through multi-objective optimization model ‘ were tested based on the water use sequence of the three sectors (industry, tertiary industry and domestic) in Yulin City, and the performance of the method is compared with NSGAII-IORAGM, NSGAII-FOFAGM and SOGA-FORAGM. The results showed that the average relative error of the model established in this study for the simulation of industry, tertiary industry (the tertiary industry is a technical name for the service sector of the economy, which encompasses a wide range of businesses), and domestic was 15.54%, 11.20%, 9.98% respectively. The average relative error of the model established in this study for the prediction of industry, tertiary industry and domestic was 9.46%, 7.9%, and 1.8%, respectively. For the simulation of water demand sequences in three sections, the simulation average relative errors of the other three models were not absolutely dominant except for the SOGA-FORAGM model. The average relative predicted error by the model in this study was the smallest (the relative errors of the three sequence predictions for industry, tertiary industry and domestic were lower than the relative errors of the optimal results of the comparison model, which were 0.97%, 0.72% and 4.5%, respectively), indicating that the model had certain applicability for the water demand prediction of various sectors (industry, tertiary industry and domestic) in the region compared with other models, and can improve the accuracy of the prediction results.

Technical Points of Water-Draw and Discharge Impact Analysis in Guidelines for Water Resource Assessment of Coastal Nuclear Power Plants

Nowadays, cleaner production is getting more and more attention, and nuclear power has been widely used due to its low energy consumption and lower pollution. Most nuclear power plants in China, including those under construction and constructed ones, are coastal. For a nuclear power plant, however, its large amount of water consumption and high guarantee rate of water quality will have impacts on the regional water-resource allocation in the site area. During the water-discharge process, low-level radioactive wastewater and warm water will be discharged, while medium or even highly radioactive wastewater will be generated in an accident, both of which will affect the environment of the receiving water. In 2016, the Chinese government began to work on the Guidelines for Water Resources Assessment of Coastal Nuclear Power Plant Projects. The compilation work, led mainly by the Ministry of Water Resources, focused on analyzing key technical points of the impacts of water intake, wastewater discharge, and their reduction measures, as well as water-protection measures. In this study, the technical requirements for impact analysis of water-draw, wastewater discharge, and their remedial measures for coastal nuclear power construction projects in different periods were put forward. Lastly, the measures for water conservation, protection, and management were given. All the technical requirements and measures gave a research basis and technical support for the formulation of the guidelines.

An Interval Two‐Stage Classified‐Allocation Model for Regional Water Management under Nonstationary Condition

AbstractDue to climate change and human activities, the assumption of the stationarity of hydrologic features will no longer hold. Moreover, uncertainties, such as the apparent randomness of hydrologic elements, and complexities, such as the existence of various water users with different characteristics, also introduce huge challenges for water managers. To address nonstationarity, uncertainty, and complexity, a new approach is proposed for the optimal allocation of regional water resources. This objective was achieved via two steps: First, the generalized additive model was chosen to analyze the nonstationary probability distribution of the hydrologic dataset; then, an interval two‐stage classified‐allocation model is formulated by incorporating two‐stage stochastic programming, interval parameter programming and classification thought. The model can not only address uncertainties, which were expressed as interval parameters and probability distributions, but can also handle complexities by classifying the water users into agricultural and nonagricultural users. The approach was applied to the Zhanghe Irrigation District to optimize available water allocation for municipality, industry, hydropower, and agriculture in two planning years (namely 2010 and 2015). The annual inflow of the Zhanghe Reservoir is found to be nonstationary and can be well fitted by Gamma distribution with one location parameter based on a nonlinear function of time. Moreover, the difference in output between the two years with different inflow probability distributions indicates the need for nonstationary analysis. Comparison to the inexact two‐stage water management model that did not consider the variation of agricultural water requirement shows the meaning of classification. From the results, municipality and industry are more competitive than agriculture and then hydropower. For agriculture, winter rape and cotton have higher priority than rice. These solutions of the optimal targets and optimal water allocation for different water users can help managers to accurately develop allocation plans under uncertain and nonstationary conditions.

A novel approach to dynamically optimize the spatio-temporal distribution of crop water consumption

The finite water resources are the main factors limiting agricultural sustainable development in arid and semiarid zones. In these water-scarce areas, optimizing limited water resources is an important way to reduce water consumption, increase crop yields and improve regional economic benefits. In this study, a CA-Jensen optimization model integrating cellular automata method and crop water production function into multi-objective dynamic optimization was developed and applied to the middle reaches of the Heihe River basin in the Northwest China to adjust the spatial distribution of cropland and the spatiotemporal allocation of crop water consumption. The net economic benefits of unit water, the crop water productivity and the value of the terrestrial ecosystem services represented the economic, social and ecological benefits in the objective function of the optimization model respectively. Adaptive cellular genetic algorithm was utilized to search and solve the optimization model. The obtained optimization results of the base year (2015) showed that the net benefits of unit water increased by 4.5% and the crop water productivity increased by 28.6%. In addition, for the target year (2030), although the reduction of agricultural water and cultivated land by 12.95% and 18.63% respectively led to a decrease of total economic benefits by 15.72%, the net benefits of unit water and social benefits got increased by 15.71% and 20.52%, respectively. Therefore, the optimization model can provide decision makers with guidance on the rational allocation of regional agricultural water resources in the future.

Water resources allocation model based on ecological priority in the arid region

Based on the characteristics of arid regions in the central and southern Ningxia，firstly we constructed the theoretical framework about rational allocation of water resources based on ecological priority, which supplemented and improved the theoretical system on rational allocation of water resources for sustainable development. On the basis of theoretical research, depending on its characteristic of water resources：pumping water from Yellow River in the north, piloting water from Jing River in the south and regional water resources, which formed a mixing water supply pattern of “pumping, piloting, storage”. The theory of water resource allocation system was perfected. Then the mathematical model for the rational allocation of water resources was established on the basis of biggest benefit combined with economy, society and ecology. The model coincided the ecological water and domestic water benefit into the overall benefits, and provides them larger benefit coefficient and the priority order coefficient to realize the reasonable allocation of water resources on ecological priority mode. Finally, the results of allocation are analysed in detail, which provides constructive suggestions and guiding direction for the study of the rational allocation of regional water resources.

Applicability analysis of multiple precipitation products in the Qaidam Basin, Northwestern China.

In the Qaidam Basin, meteorological stations are sparsely distributed, and the observational precipitation data are therefore not comprehensive, which significantly hampers the accurate assessment and optimal allocation of regional water resources. This study aims to evaluate the accuracy of three precipitation products (MSWEP V2, GPM IMERG V6, and TRMM 3B43) against gauged-based precipitation data from nine meteorological stations and 12 hydrologic stations in the Qaidam Basin from 2001 to 2016. The results reveal the following: (1) At the annual and monthly scales, the MSWEP product has the highest accuracy, followed by the GPM product. However, the TRMM product only reveals a correlation at the monthly scale; (2) the MSWEP product performs better in the wet season than the dry season, and the TRMM product has an abnormally high value of precipitation in the wet season. Moreover, it was shown that the accuracy of the GPM product is superior to that of the TRMM product; however, it has a low detection capability in some mountainous areas; and (3) the average error of each precipitation product at the meteorological stations is smaller than that at the hydrological stations.

Uncertainty Analysis of SWAT Modeling in the Lancang River Basin Using Four Different Algorithms

The hydrological model is the primary tool for regional water resources management, allocation, and prediction. However, these models always suffer from large uncertainties from multiple sources. Therefore, it is necessary to conduct an uncertainty analysis before performing hydrological simulation. Sequential Uncertainty Fitting (SUFI-2), Parameter Solution (ParaSol), Generalized Likelihood Uncertainty Estimation (GLUE), and Particle Swarm Optimization (PSO) integrated with the SWAT-CUP software were used to calibrate the Soil and Water Assessment Tool (SWAT) model and quantify the parameter sensitivity and prediction uncertainty of the SWAT in the Lancang River (LR) Basin, which is located in the southwest of China. This model was calibrated and validated using the four algorithms both at the daily scale, and the optimal simulation results derived by the four methods showed that the SWAT model performed well over the Yunjinghong station with Nash–Sutcliffe efficiency coefficient (NSE) and coefficient of determination (R2) values greater than 0.8 both in the calibration (1975 to 1989) and validation (1990 to 2004) periods. Among the four algorithms, the ParaSol algorithm produced the best simulation result at the daily scale with NSE values of 0.89 and 0.90 for the calibration and validation periods, respectively. Furthermore, the ParaSol algorithm has the greatest proportion of simulations (94%) with an NSE greater than 0.5. Parameter sensitivity analysis results demonstrated that the four methods all can be used for parameter sensitivity analysis in streamflow simulation, and they all identified that the base flow factor for bank storage (ALPHA_BNK) and effective hydraulic conductivity in the main channel alluvium (CH_K2) were more sensitive. The uncertainty analysis of model parameters showed that the parameter 95PPU (95% prediction uncertainty) width yielded by the ParaSol algorithm was the smallest compared with that of the other methods, followed by PSO, SUFI-2, and GLUE. The uncertainty analysis of the model simulation indicated that the SUFI-2 and PSO methods can achieve satisfactory results (with P-factor > 0.7 and R-factor < 1.5) at the daily scale; among them, SUFI-2 (P-factor = 0.93, R-factor = 1.17) performed much better than PSO (P-factor = 0.78, R-factor = 1.14). In general, by comparing its evaluation criteria (NSE, R2, RE, P-factor, and R-factor) to other methods, ParaSol stood out as the most efficient tool for model calibration. However, SUFI-2 remains the most robust method to perform uncertainty analysis considering its uncertainties of model structure, model inputs, and parameters. This study provides insight into hydrological simulation of the LR Basin using the appropriate algorithm to calibrate the model and implement the uncertainty analysis.

Spatio-Temporal Variations of Crop Water Footprint and Its Influencing Factors in Xinjiang, China during 1988–2017

Scientifically determining agricultural water consumption is fundamental to the optimum allocation and regulation of regional water resources. However, traditional statistical methods used for determining agricultural water consumption in China do not reflect the actual use of water resources. This paper determined the variation in the crop water footprint (CWF) to reflect the actual agricultural water consumption in Xinjiang, China, during the past 30 years, and the data from 15 crops were included. In addition, the STIRPAT (stochastic impacts by regression on population, affluence and technology) model was used to determine the factors influencing the CWF. The results showed that the CWF in Xinjiang increased by 256% during the 30-year period. Factors such as population, agricultural added value, and effective irrigated area were correlated with an increase in the CWF. This study also showed that the implementation of national and regional policies significantly accelerated the expansion of agricultural production areas and increased the amount of agricultural water used. The objectives of this paper were to identify the factors influencing the CWF, give a new perspective for further analysis of the relationship between agricultural growth and water resources utilization, and provide a reference for local policy decision-makers in Xinjiang.

Optimal allocation of regional water resources based on multi-objective dynamic equilibrium strategy

Raising water demand, insufficient freshwater resources and uneven precipitation are the main causes of water conflicts in the river basin. The main challenges in water resources allocation are the following: first, the uncertainty of water supply caused by climate change; second, the dynamic allocation of water resources is not considered; third, there is a lack of equitable water allocation, which may lead to intensified conflicts among the water user sectors. Based on the above challenges, a multi-objective dynamic programming optimal water resources allocation model under uncertainties is established in this paper, which could be a resolution for water disputes as it addresses simultaneously economic, social and environmental benefits. The proposed model considers maximizing the minimum satisfaction degree of each water sector, maximizing the utilization efficiency of water resources in the basin, and maximizing economic benefits. Satisfaction degree function is introduced to optimize water allocation equality in water use sectors (agricultural, domestic, and industrial sectors), and economic efficiency loss acceptance is integrated into the model constraints to control the economic loss corresponding to variations in water availability. In addition, a case study demonstrated the practicality and rationality of the proposed model, and the model results proposed herein show significantly help for a single river basin. Most importantly, the results show that model with dynamic constraint ensures a greater overall economic return for the entire basin, and a larger variation in water resources of sub-area leads to a larger maximum economic efficiency loss. Moreover, the proposed model herein is flexible and can be used in other developing countries/regions only by modifying the parameters according to the actual situation.

Spatiotemporal Variations in Drought and Wetness from 1965 to 2017 in China

Drought and extreme precipitation events can have major environmental and socioeconomic impacts. Yet, how drought and wetness are changing in China in the context of climate change is still under debate. Here, the standardized precipitation evapotranspiration index (SPEI) was calculated based on high-quality and more densely distributed daily meteorological observation data from 655 stations across China during the period of 1965–2017. National and regional trends in drought and wetness and their various characteristics, including intensity, duration, frequency, and percentage of area affected, were investigated at multiple timescales. We found that (1) China as a whole has undergone a significant (p < 0.01, trend significant at the level of 0.01) wetting trend, with an annual SPEI increase of 0.5 per decade from 1965 to 2017. A seasonal wetting trend was also observed, with summer being particularly significant (p < 0.01). (2) Regionally, each subregion also showed a wetting trend during the study period except for southwest China, and these wetting trends were significant in the western region of northwest China (p < 0.05, trend significant at the level of 0.05), the Tibetan Plateau (p < 0.05), and eastern China (p = 0.06). (3) Decadal trends in drought and wetness intensity, frequency, duration, and affected areas indicated that the drought events also became more severe and more frequent in the last two decades, and the areas showing drying trends were mainly located in southwest China (especially for the autumn drought) and the southwestern parts of eastern northwest China (spring drought). Our results highlight the fact that although a wetting trend was observed in most regions of China, the frequent occurrence of severe drought in southwest China and the southwestern parts of eastern northwest China still present a considerable threat to both the environment and society. Therefore, how to effectively coordinate the allocation of regional water resources to cope with drought risk under future climate change will be particularly important.

Study on Coupling Mechanism of Carbon-Water Symbiosis System and Regulation and Control of Water Resources in the Context of Regional Collaborative Development

In the aspect of theoretical research, the regional carbon-water coupling mechanism has not yet formed a complete conceptual framework, so there is an urgent need to build an academic system of the carbon-water coupling under a unified physical device. Therefore, based on the overall identification of the coupling mechanism of the water cycle and carbon balance, this paper systematically analyses the characteristics of carbon capture and release in the process of water resources and energy development, puts forward the connotation, symptoms and overall tasks of water resources allocation based on low-carbon development model, and constructs a technical framework supported by regional carbon-water coupling simulation and water resources allocation. The critical technical issues such as water resources allocation, model construction process, countermeasures and safeguard measures based on the low-carbon model. The safety early warning model of water quality and quantity in regional carbon-water symbiosis system is put forward, which provides a method reference for the regulation and control of local water resources.

Estimation of summer maize evapotranspiration using MARS model in the semi-arid region of northwest China

Evapotranspiration (ET) is a crucial parameter of agricultural water management, and its accurate estimation is of great significance to implement precision irrigation and optimal allocation of regional water resources. This study investigated the efficiency of the multivariate adaptive regression splines (MARS) model for estimating daily ET of summer maize under twelve input combinations, including complete and incomplete meteorological factors and crop growth indicators for the period 2011–2013. The performance of the MARS model was compared with the empirical Priestley-Taylor (P-T), Shuttleworth-Wallace (S-W) and Two-Patch (T-P) models as well as the back-propagation neural networks (BPNN) model. The optimal MARS and BPNN models achieved better ET prediction than the optimal empirical models at each growth stage.The MARS model was superior to the BPNN model at all growth stages in terms of mean absolute error: seedling emergence to tasseling (0.8476 mm/d vs. 0.9833 mm/d), tasseling to grouting (0.6777 mm/d vs. 0.7162 mm/d), grouting to harvest (0.3342 mm/d vs. 0.4336 mm/d) and the entire growth period (0.8752 mm/d vs. 0.9577 mm/d). Generally, the MARS model outperformed the BPNN model and empirical models at all growth stages, indicating that the optimal MARS models accurately modeled the complex nonlinear relationships between ET and the meteorological factors and crop growth indicators. The MARS model is thus highly recommended for estimating ET during the entire growth period of summer maize in the semi-arid regions when lack of adequate meteorological factors or crop growth indicators.

Evaluating the value of ecological water considering water quality and quantity simultaneously

AbstractThis study applies a choice experiment to evaluate the value of ecological water and investigate public preferences in the Shiyang River Basin, which is an ecologically fragile region in China. The four ecological attributes were ecological water quantity in the upper sub‐basin, ecological water quantity in the middle sub‐basin, ecological water quantity in the lower sub‐basin, water quality in Hongyashan Reservoir. The results show that water quality was the most preferred attribute among all the chosen attributes, and public prefer the increase of the ecological water quantity in the lower sub‐basin. In addition, it was concluded that increases of 40 million m3 and 60 million m3 of the ecological water quantity in the middle and lower sub‐basins, respectively, with the ecological water quality improved from Class IV to III, would be worth 2.82 billion RMB. The research findings are expected to support strategies for regional water resources allocation as well as help to understand public support for the policy.

Prediction of Daily Water Consumption of Residential Communities Based on Correlation Analysis and BP Neural Network

In recent years, with the rapid development of cities, water resources are becoming increasingly scarce. Reasonable prediction of community water use is an important basis for regional water resources allocation, effective management of water resources and water conservation. The prediction model of BP neural network based on correlation analysis is established. Firstly, the influence factors of water consumption are analyzed by the correlation analysis theory, the influence size is sorted, and then the partial autocorrelation theory is used to analyze the daily water flow sequence, and the optimal delay time is determined, and then the input variables are determined. Then the BP neural network model is used to predict the water consumption of the community. Finally, the BP neural network model based on the correlation analysis is compared with the other models. The results show that the average error of forecasting model for residential community water consumption is 2.21% and the maximum relative error is 6.87%. Compared with the BP neural network model without correlation analysis and the least squares support vector machine model, the error is the smallest.

Research on the development and utilization mode of mine water resources

China’s mine water comprehensive utilization rate is low. The main reason for the increase in the utilization rate after 2015 is the reduction in coal production. The shutdown of a large number of coal mines by capacity has objectively led to a reduction in mine water volume. Based on the development and utilization of mine water, this paper clarifies the characteristics of mine water utilization mode, and discusses the classification of mine water utilization mode and suggestions for safeguard measures in terms of mine water utilization targets and treatment difficult. The research undertook in this paper will expand the utilization of mine water and improve the utilization rate of mine water. It will help enterprises realize the transformation of mine water into waste and realize the value-added effect of mine water. It is desirable for the unconventional water resources will be integrated into the water source. It can help ease the contradiction between water supply and demand in water shortage areas and improve the efficiency and utilization efficiency of regional water resources allocation.

Does Information Asymmetry Impact Sub-Regions' Cooperation of Regional Water Resource Allocation?

Water resources allocation is an urgent problem for basin authorities. In order to obtain greater economic benefits from limited water supplies, sub-regions must cooperate with each other. To study the influence of cooperation among sub-regions and the symmetry of cooperation information on the interests of the basin authority and each sub-region, this study proposes a regional water allocation model in three different situations: (1) non-cooperation; (2) cooperation and information symmetry; (3) cooperation and information asymmetry. The proposed model clearly reflects the Stackelberg game relationship between the basin authority and sub-regions. Finally, the model is applied to the Qujiang River Basin in China, and the decisions of the basin authority and sub-regional managers of the Qujiang River Basin under three different situations are discussed. The results show that regional cooperation benefits both the cooperative regions and the social welfare value of the entire river basin, when compared with non-cooperation.

Optimal allocation of water resources through artificial fish swarm algorithm: A case study in Haixing, China

North China is a typical developing region where the conflict between large water demand and little natural water resources exist. Thus, scientifically optimizing the allocation of regional water resources is particularly significant in this area. In this study, Haixing County, China was selected as the research region. Then, regional optimization model of water resource allocation was established, of which the objective function aims at the maximum integrated benefit of regional social and economy. In this model, two forbidden red lines of water use amount and water use efficiency were considered as the constraints, and Artificial Fish Swarm Algorithm was applied to calculate the optimization of water resource allocation. In 2020, the p = 50% total water shortage is forecast as 0.747 × 106 m3 or 2.1%. The results show that the efficiency and benefits have been improved, which illustrates that the optimization allocation of water resources through Artificial Fish Swarm Algorithm is reasonable. The research could provide a crucial technical support for regional water resource management.