Optimal Allocation Of Water Resources Research Articles

Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China

The reasonable allocation of water resources using different optimization technologies has received extensive attention. However, not all optimization algorithms are suitable for solving this problem because of its complexity. In this study, we applied an ameliorative multi-objective gray wolf optimizer (AMOGWO) to the problem. For AMOGWO, which is based on the multi-objective gray wolf optimizer, we improved the distance control parameter calculation method, added crowding degree for the archive, and optimized the selection mechanism for leader wolves. Subsequently, AMOGWO was used to solve the multi-objective optimal allocation of water resources in Handan, China, for 2035, with the maximum economic benefit and minimum social water shortage used as objective functions. The optimal results obtained indicate a total water demand in Handan of 2740.43 × 106 m3, total water distribution of 2442.23 × 106 m3, and water shortage of 298.20 × 106 m3, which is consistent with the principles of water resource utilization in Handan. Furthermore, comparison results indicate that AMOGWO has substantially enhanced convergence rates and precision compared to the non-dominated sorting genetic algorithm II and the multi-objective particle swarm optimization algorithm, demonstrating relatively high reliability and applicability. This study thus provides a new method for solving the multi-objective optimal allocation of water resources.

Sustainable Management of the Electrical-Energy–Water–Food Nexus Using Robust Optimization

The significance of the security of electrical energy, water, and food resources in the future, which are inextricably connected, has led to increasing attention to this important issue in studies. This is an issue inattention to which can have irreparable consequences in the future. One of the sectors where electrical energy, water, and food are very closely associated is agriculture. Undoubtedly, the ability to properly manage electrical energy, hydropower, and food resources that have many uncertainties brings about the development of agriculture on the one hand and the optimal allocation of electrical energy, water, and land resources on the other. Thus, while reaching the highest economic profit, the greenhouse gas emissions reach the minimum possible value too. In this study, via robust optimization and by precisely considering the existing uncertainties, a model was developed for the optimal allocation of electrical energy, water, and land resources for a region in the north of China. In addition to acknowledging the close relationship between electrical energy, water, and food sources, the results show the method’s effectiveness for sustainable management in agriculture.

Optimal Allocation of Water Resources and Eco-Compensation Mechanism Model Based on the Interval-Fuzzy Two-Stage Stochastic Programming Method for Tingjiang River.

In this work, based on the upper line of water resources utilization and the bottom line of water environmental quality of “Three Lines, Single Project”, a fuzzy optimization method was introduced into the Tingjiang River water resources optimal allocation and eco-compensation mechanism model, which is based on the interval two-stage (ITS) stochastic programming method. In addition, a Tingjiang River water resources allocation and eco-compensation mechanism model based on the interval fuzzy two-stage (IFTS) optimization method was also constructed. The objective functions of both models were to maximize the economic benefits of the Tingjiang River. The available water resources in the basin, the water environmental quality requirements, and regional development requirements were used as constraints, and under the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance, the water resources allocation plan of various sectors (industry, municipal, agriculture, and ecology) in the Tingjiang River was optimized, and an eco-compensation mechanism was developed. In this work, the uncertainty of the maximum available water resources in each region and the whole basin was considered. If the maximum available water resources were too high, it would lead to a large waste of water resources, whereas if the maximum available water resources were too low, regional economic development would be limited. Therefore, the above two parameters were set as fuzzy parameters in the optimization model construction in this work. The simulation results from the IFTS model showed that the amount of water available in the river basin directly affects the water usage by various departments, thereby affecting the economic benefits of the river basin and the amount of eco-compensation paid by the downstream areas. The average economic benefit of the Tingjiang River after the optimization of the IFTS model simulation was [3868.51, 5748.99] × 108 CNY, which is an increase of [1.67%, 51.9%] compared to the economic benefit of the basin announced by the government in 2018. Compared to the ITS model, the economic benefit interval of the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance was reduced by 28.54%, 44.9%, 31.49%, 40.37%, and 36.43%, respectively, which can improve the economic benefits of the basin and provide more accurate decision-making schemes. In addition, the IFTS simulation showed that the eco-compensation quota paid by downstream Guangdong Province to upstream Fujian Province is [28,116.4, 30,738.6] × 104 CNY, which is a reduction of [8461.404, 110,836] × 104 CNY compared to the 2018 compensation scheme of the government. Compared to the ITS model, the range of eco-compensation values was observed to increase by 9.94%, 54.81%, 15.85%, 50.31%, and 82.90%, respectively, under the five hydrological scenarios, which reduces the burden of ecological expenditure downstream and provides a broader decision-making space for decision-makers and thus enables improved decision-making efficiency. At the same time, after the optimization of the IFTS model, the additional water consumption of the second stage of the Tingjiang River during the extremely dry year decreased by 62.11% compared to the results of the ITS model. The additional water consumption of the industrial sector decreased by 68.39%, the municipal sector decreased by 59.27%, and in the first phase of water resources allocation for 14 districts and counties in the Tingjiang River, industrial and municipal sectors are the main two sectors. After introducing the fuzzy method into the IFTS model, the difference in the water consumption by these two sectors in the basin under different hydrological scenarios can be alleviated, and the waste of water resources caused by too low water allocation or excessive water allocation can be avoided. The national and local (the downstream region) eco-compensation quotas can be indirectly reduced, and the risk of water resources allocation and eco-compensation decision-making in the basin can be effectively reduced.

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.

Towards sustainable circular agriculture: An integrated optimization framework for crop-livestock-biogas-crop recycling system management under uncertainty

ContextGrowing socio-economic development and population poses unprecedented challenges for agriculture in meeting increasing demand of food, water, and energy. Rethinking the future agricultural production to simultaneously safeguard resources security and regulate environmental pollution is essential. Circular agriculture opens up a new path for the high-efficiency and environmental-friendly production. An integrated energy-water-food nexus optimization approach for managing agricultural resources and wastes in line with the principles of sustainable circular agriculture management is lacking. ObjectiveThis study therefore proposes an integrated uncertain optimization model to manage agricultural crop-livestock-biogas-crop recycling systems from a cross-sectoral energy-water-food nexus perspective in the changing environment. The aims are to: (1) balance objectives of input reduction, output promotion, ensuring equity, and global warming mitigation; (2) generate sustainable resources allocation strategies based on efficiency and recycling; (3) assess the global warming mitigation potential of the recycling systems from a life cycle perspective; and (4) deal with interactions, complexities, uncertainties, and risks existed in the recycling systems. MethodsThe proposed model framework is based on a stochastic multi-objective programming, while triangular fuzzy numbers, fuzzy credibility constrained programming, Stewart model, analytic hierarchy process, and opportunity carbon footprint are integrated to enhance its practicability and feasibility. The model is verified through a real-world case study in the Zhanghe Irrigation District, Hubei province, China. Results and conclusionsResults show that optimal water and land resources allocation solutions are more efficient than current strategies, with water consumption per unit area decreasing by 13.63% and rice production per unit area improving by 22.06%. Paddy field and biogas leakage are two of the largest sources of GHG emission, calling for agronomic and engineering measures to improve farmland management and biogas generation technology. Livestock breeding contributes 10% of the total GHG emission, along with generating 76% of the total biogas, indicating the great significance of manure recycle. Overall, 4.26 × 108 kg CO2 is reduced in the recycling system, contributed by chemical fertilizer reduction, agricultural wastes recycle, and non-renewable energy replacement. SignificanceThe study offers a potential nexus optimization approach for sustainable management of agricultural recycling systems from a holistic perspective. It can be used as a general model to extend to other agricultural systems suffering from similar resources and environmental crisis.

Flow reduction effect on fish habitat below water diversion—A case study of the Central Yunnan Water Diversion Project

With the implementation of large-scale water diversion projects, the reduction of river flow in water diversion areas may impact the ecological environment of the river. In this study, we used integrated hydrodynamic, habitat, and risk modeling methods to produce an ecological risk time series based on the consequences of departures from the optimum environmental flow range of a river, quantifying the extent to which flow regulation affects fish habitats. Taking the water diversion project in central Yunnan as an example, we used this method to produce a risk time series of fish habitats. This time series shows that the ecological risk increases when the river flow deviates from the optimal range of environmental flow. The degree of risk is different in different periods: in wet years, the risk is negligible; in normal years, the risk is between acceptable and critical, and in dry years, the risk is above critical. The research results can provide a basis for the optimal allocation of water resources to meet environmental flow requirements.

Multi-Objective Optimal Allocation of River Basin Water Resources under Full Probability Scenarios Considering Wet-Dry Encounters: A Case Study of Yellow River Basin.

Wet–dry encounters between basins and regions have an important impact on the allocation of water resources. This study proposes a multi-objective allocation model for basin water resources under full probability scenarios considering wet–dry encounters (FPS-MOWAM) to solve the problem of basin water resource allocation. In the FPS-MOWAM model, the sub-regions were merged by precipitation correlation analysis. Next, the joint probability distribution of basin runoff and region precipitation was constructed using copula functions. The possible wet–dry encounter scenarios and their probabilities were then acquired. Finally, the multi-objective allocation model of water resources was constructed using the full probability scenario for wet–dry encounters in each region. The FPS-MOWAM is calculated by the NSGA-II algorithm and the optimal water resource allocation scheme was selected using the fuzzy comprehensive evaluation method. Using the Yellow River Basin as an example, the following conclusions were obtained: (1) the Yellow River Basin can be divided into four sub-regions based on precipitation correlations: Qh-Sc (Qinghai, Sichuan), Sg-Nx-Nmg (Gansu, Ningxia, Inner Mongolia), Sxq-Sxj (Shaanxi, Shanxi), and Hn-Sd (Henan, Shandong), (2) the inconsistencies in synchronous–asynchronous encounter probabilities in the Yellow River Basin were significant (the asynchronous probabilities were 0.763), whereas the asynchronous probabilities among the four regions were 0.632, 0.932, and 0.763 under the high, medium, and low flow conditions in the Yellow River Basin respectively, and (3) the allocation of water resources tends to increase with time, allocating the most during dry years. In 2035, the expected economic benefits are between 11,982.7 billion CNY and 12,499.6 billion CNY, while the expected water shortage rate is between 2.02% and 3.43%. In 2050, the expected economic benefits are between 21,291.4 billion CNY and 21,781.3 billion CNY, while the expected water shortage rate is between 1.28% and 6.05%.

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

The optimal allocation of water resources oriented to prioritizing ecological needs using multiple schemes in the Shaying River Basin (Henan Section), China

Abstract China is actively exploring water resources management considering ecological priorities. The Shaying River Basin (Henan Section) serves as an important grain production base in China. However, conflicts for water between humans and the environment are becoming increasingly prominent. The present study analyzed the optimal allocation of water while considering ecological priorities in the Shaying River Basin (Henan Section). The ecological water demand was calculated by the Tennant and the representative station methods; then, based on the predicted water supply and demand in 2030, an optimal allocation model was established, giving priority to meeting ecological objectives while including social and comprehensive economic benefit objectives. After solving the model, the optimal results of three established schemes were obtained. This revealed that scheme 1 and scheme 2 failed to satisfy the water demand of the study area in 2030 by only the current conditions and strengthening water conservation, respectively. Scheme 3 was the best scheme, which could balance the water supply and demand by adding new water supply based on strengthening water conservation and maximizing the benefits. Therefore, the actual water allocation in 2030 is forecast to be 7.514 billion (7.514 × 109) m3. This study could help basin water management departments deal with water use and supply.

A New Multi-Objective Optimization Model of Water Resources Considering Fairness and Water Shortage Risk

Assessing the fairness of water resource allocation and structural water shortage risks is an urgent problem that needs to be solved for the optimal allocation of water resources. In this study, we established a new multi-objective optimization model of water resources based on structural water shortage risks and fairness. We propose an improved NSGA-III based on the reference point selection strategy (ARNSGA-III) to solve the optimization model. The superiority of this method was proven by comparing it with three other methods, namely, NSGA-III, MOSPO, and MOEA/D. The model was applied to optimize the allocation of water resources in Wusu City in China. The results show that the new multi-objective optimization model provides reasonable and feasible solutions for solving water conflicts. The convergence and stability of ARNSGA-III are better than those of the other three algorithms. Allocation schemes of water resources for Wusu City in normal years, dry years, and extremely dry years are proposed. In normal years, the structural water shortage risk index is reduced by 50.1%, economic benefits increased by 0.2%, and fairness is reduced by 60.5%. This study can provide new ideas for solving the multi-objective optimization of regional water resources.

Dynamic Evaluation of Water Utilization Efficiency in Large Coal Mining Area Based on Life Cycle Sustainability Assessment Theory

Coal mining enterprises have a variety of water sources, complex drainage structures, long production chain, and many links, which lead to uncoordinated water utilization and low water efficiency. Taking a large coal mining area of China as an example, a dynamic model was established to evaluate the water utilization efficiency based on the Life Cycle Sustainability Assessment (LCSA) theory. In the model, the influence of five aspects (including resources, economy, technology, society, and environment) and 19 factors was considered. The game theory method was adopted to calculate the fusion weights of the 19 factors according to the analytic hierarchy process and CRITIC method. The CW-VIKOR method was used to explain the dynamic evaluation results of water efficiency in the coal mining area. The results show that the environmental impacts of the mining system mainly come from three aspects: regional drainage, domestic sludge landfill and disposal, and water system electricity consumption. Electricity consumption in water systems has the greatest environmental impact, accounting for about 73%, regional drainage for about 26%, and domestic sludge landfill and disposal for about 1%.The CW-VIKOR approach can harmonize the interrelationships among resources, economy, technology, society, and environment. It is an effective method for LCSA of water resource in the coal mining area. The reliability of the evaluation results is high and close to the actual situation. The dynamic model established in this paper is also applicable to other coal mine areas, and only the factor weights need to be modified according to the specific characteristics of each coal mine. The model can provide guidance for optimal exploitation and allocation of coal mine water resources.

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.

Adjustable Robust Optimization for Multi-Period Water Allocation in Droughts Under Uncertainty

Optimal water resource allocation can go some way to overcoming water deficiencies; however, its achievement is complex due to conflicting hierarchies and uncertainties, such as water availability (WA) and water demand (WD). This study develops a robust water withdrawal scheme for drought regions that can balance the trade-offs between the sub-areas and water use participants, ensure sustainable regional system development, and guarantee robust solutions for future uncertainties. A bi-level affinely adjustable robust counterpart (AARC) programming framework was developed in which the regional authority as the leader allocates water to the sub-areas to maximize the intra- and intergenerational equity, and the sub-areas as the followers allocate water to their respective water departments to maximize their economic benefits and minimize water shortages. A case study from Neijiang, China, is given to illustrate the applicability and feasibility of this framework. The novelty of this study is to propose a sustainable bi-level AARC regional water allocation framework which integrates intra- and inter-generational equity of regional water use and priority rules reflected by goal preference programming between water departments under uncertainties of WA and WD simultaneously in water deficient regions.

Study of spatial distribution characteristics of river eco-environmental values based on emergy-GeoDa method

River eco-environmental value assessment is indispensable for the optimal allocation of watershed water resources. In this study, river eco-environmental values were divided into the values inside and outside the river based on the energy transfer and transformation of the water cycle. Their spatial distribution characteristics (spatial distribution map, spatial autocorrelation, and spatial aggregation) of 67 regions (states, leagues, and cities) in the Yellow River Basin (YRB) were analysed by combining emergy theory and GeoDa 1.14 software (emergy-GeoDa), and the significance of the results was tested. The results showed that: (1) the eco-environmental values inside the river were higher than those outside in the YRB, proving that eco-environmental water inside the river should be guaranteed and water consumption outside the river should not occupy water inside the river from the perspective of value; (2) the spatial distributions of eco-environmental values inside and outside the river were uneven, but obvious spatial aggregations were observed; (3) high- and low-value aggregations of eco-environmental values were observed inside the river in the lower and upper reaches of the YRB, respectively; (4) high- and low-value aggregations of eco-environmental values were observed outside the river in the middle and upper reaches of the YRB, respectively. It was suggested that ecological conservation and high-quality development should be considered as the goals for consolidating the river eco-environmental values in high-value areas and promoting in low-value areas, and low-value areas should be improved by high-value areas while allocating water resources in the YRB. These results provide suggestions for the sustainable development of river eco-environmental system in the YRB from a spatial perspective. In addition, the analysis method is also applicable for studying the spatial distribution characteristics of the values generated by the water and energy cycles of other regions.

Optimal Multi-Sectoral Water Resources Allocation Based on Economic Evaluation Considering the Environmental Flow Requirements: A Case Study of Yellow River Basin

Competitions and disputes between various human water sectors and environmental flow of the river are exacerbated due to the rapid growth of the economy in Yellow River basin as well as the limited supply of available water resources in recent decades. It is necessary to implement rational and effective management and allocation to alleviate the pressure of water shortage. In order to promote economic development and maintain the ecological balance of the river, both the water allocation to the river environmental system and different human needs should be of concern when making the allocation polices. This study developed a water allocation model based on Nash–Harsanyi bargaining game theory for optimal water resources allocation among agricultural, industrial, domestic, public, and urban ecological water (watering for urban green space) sectors while ensuring the environmental flow requirements of lower reaches. A comprehensive economic evaluation framework is built to assess the economic benefits of different water uses that were taken as the basis of water allocation model. The annual environmental base flow is 7.50 billion m3 in the lower reaches of Yellow River. Moreover, the optimal annual allocations for agricultural, industrial, domestic, public, and urban ecological water use sectors are estimated as 33.7, 6.42, 3.96, 1.75 and 2.68 billion m3, respectively.

Multi-objective game theory optimization for balancing economic, social and ecological benefits in the Three Gorges Reservoir operation

Reservoir operation is an important and effective measure for realizing optimal allocation of water resources. It can effectively alleviate regional scarcity of water resources, flood disasters and other social problems, and plays an important role in supporting sustainable strategic development of water resources. Coordinating the stakeholders is key to the smooth operation of a multifunctional reservoir. This research examines the competition among stakeholders of a multi-objective ecological reservoir operation aiming to provide for economic, social and ecological demands. A multi-objective game theory model (MOGM) specified 10-day water discharge to meet the triple water demands (power generation, socio-economic consumption and environment) for multi-purpose reservoir operation. The optimal operation of the Three Gorges Reservoir (TGR), with the ecological objective of providing comprehensive ecological flow demanded for some key ecological problems that may occur in the middle and lower reaches of the Yangtze River, was chosen as a case study. Discharged water calculated by the MOGM and a conventional multi-objective evolutionary algorithm/decomposition with a differential evolution operator was then allocated to different demands. The results illustrate the applicability and efficiency of the MOGM in balancing transboundary water conflicts in multi-objective reservoir operation that can provide guidance for the operation of the TGR.

Application of edge computing and GIS in ecological water requirement prediction and optimal allocation of water resources in irrigation area.

The purposes are to use water resources efficiently and ensure the sustainable development of social water resources. The edge computing technology and GIS (Geographic Information Science) image data are combined from the perspective of sustainable development. A prediction model for the water resources in the irrigation area is constructed. With the goal of maximizing comprehensive benefits, the optimal allocation of water quality and quantity of water resources is determined. Finally, the actual effect of the model is verified through specific instance data in a province. Results demonstrate that the proposed irrigation area ecological prediction model based on edge computing and GIS images can provide better performance than other state of the art models on water resources prediction. Specifically, the accuracy can remain above 90%. The proposed model for ecological water demand prediction in the irrigation area and optimal allocation of water resources is based on the principle of quality water supply. The optimal allocation of water resources reveals the sustainable development ideas and the requirements of the optimal allocation model, which is very reasonable. The improvement of the system is effective and feasible, and the optimal allocation results are reasonable. This allocation model aims at the water quality and quantity conditions, water conservancy project conditions, and specific water demand requirements in the study area. The calculation results have great practicability and a strong guiding significance for the sustainable utilization and management of the irrigation area.

RETRACTED ARTICLE: Forest rainfall characteristics based on heterogeneous computing and influencing factors of athletes’ physical supplement

The advent of the era of big data greatly stimulates the research and application of heterogeneous algorithms. Firstly, based on the characteristics of heterogeneous FPGA computing platform, this paper develops kb-knn heterogeneous algorithm based on KNN. In order to make full use of the heterogeneous platform, this paper classifies the unclassified data and adopts the parallel implementation scheme of flow between devices, so that the master and slave devices in the heterogeneous system can participate in the calculation cycle of global hydrology and material energy. This paper explains the importance of forest rainfall distribution for regional social and economic development and agricultural production, ecological balance, optimal allocation of water resources, and environmental protection. Due to the limited availability of data from multiple sources, there are few studies to analyze the precipitation changes of different time scales in mountainous areas. The forest precipitation data used in this paper usually have low temporal and spatial resolution, and cannot describe the spatiotemporal heterogeneity of precipitation in mountainous areas. In addition, the physical fitness of athletes mainly includes strength training and speed training. The combination of recovery and nutrition is the basic knowledge that coaches must have. The rehabilitation of athletes mainly depends on the amount of exercise, physical therapy, and massage adjustment. Reasonable nutrition is one of the most important factors for athletes to win and ensure their health and sports ability. Heterogeneous computing platform provides a new solution to accelerate the implementation of such algorithms. In the heterogeneous computing platform, this paper discusses the nutrition of athletes’ physical supplement and describes the characteristics of forest rainfall.

Optimal water allocation method based on the genetic algorithm for a system of a reservoir and two pumping stations

Abstract The subtropical monsoon climate zone features abundant water resources but with uneven temporal and spatial distribution, so seasonal water shortages are frequent. In order to reduce the water shortage and water spill in this region, a nonlinear optimization model for the joint operation of a system of a reservoir and two pumping stations is developed in this paper. In this model, the water supply of the reservoir and pumping volume of the pumping stations in each period are two types of decision variables, which are subjected to the annual available water in the reservoir, water rights of the two pumping stations and the operation rule of the reservoir. However, modern intelligent algorithms may fail in dealing with constraints of if-statements like the operation rule of the reservoir in this model. In light of the shortcoming of the classical genetic algorithm, a modified genetic algorithm is proposed by comparing the different methods for dealing with constraints. The modified algorithm shows a better adaptability to the operation rule. The modified genetic algorithm may provide a reference for similar modern intelligent algorithms to solve optimal water resources allocation for systems of multiple reservoirs and multiple pumping stations.