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The development of decision-making systems based on artificial intelligence can lead to achieving optimal solutions water-land-food nexus. In this paper, an extreme learning machine model was developed with the objective function of wheat production maximization. The constraints defined for this problem are divided into three categories: technical parameters of production in agriculture, climatic stress on water resources and land limits. The water, land and food nexus was simulated using 23 experimental farms in Henan province during the 2021-2022 cultivation year. Root-mean-square error was used as an error criterion, and Pearson's coefficient was incorporated into the decisionmaking system as a correlation index of variables. Harvest index, length of the growth period, cultivation costs and irrigation water were the criteria to evaluate the impact of the sustainable model. The harvest index and the length of the growth period showed the highest and lowest correlation with the production rate, respectively. Furthermore, the optimal management of irrigation water and cost had the most significant impact on increasing crop production. The method proposed in this paper can be a virtual cropping model by changing the area under cultivation of a crop in the different farms of a study area, which increases yield production. [ABSTRACT FROM AUTHOR]

Precipitation prediction is one of the important issues in meteorology and hydrology, and it is of great significance for water resources management, flood control, and disaster reduction. In this paper, a precipitation prediction model based on the empirical mode decomposition-variational mode decomposition-long short-term memory (EMD-VMD-LSTM) is proposed. This model is coupled with EMD, VMD, and LSTM to improve the accuracy and reliability of precipitation prediction by using the characteristics of EMD for noise removal, VMD for trend extraction, and LSTM for long-term memory. The monthly precipitation data from 2000 to 2019 in Luoyang City, Henan Province, China, are selected as the research object. This model is compared with the standalone LSTM model, EMD-LSTM coupled model, and VMD-LSTM coupled model. The research results show that the maximum relative error and minimum relative error of the precipitation prediction using the EMD-VMD-LSTM neural network coupled model are 9.64 and -7.52%, respectively, with a 100% prediction accuracy. This coupled model has better accuracy than the other three models in predicting precipitation in Luoyang City. In summary, the proposed EMD-VMD-LSTM precipitation prediction model combines the advantages of multiple methods and provides an effective way to predict precipitation. [ABSTRACT FROM AUTHOR]

Traditional studies on the carrying capacity of groundwater resources mainly focus on a comprehensive evaluation, and this paper provides quantitative prediction and early warning on the carrying capacity of groundwater resources, which is important for groundwater management and protection. This study constructed an early warning indicator system for the carrying capacity of groundwater resources, established an early warning method on the carrying capacity of groundwater resources, determined the early warning grades of Henan Province and various cities from 2023 to 2025, and analyzed the spatial distribution pattern. The results showed that the early warning grades of Henan Province from 2023 to 2025 were mild warnings. In the subsystems, the early warning grades of the groundwater resources and economic society systems were mild warnings, while the early warning grades of the ecological environment system were moderate warnings. The early warning grades of the carrying capacity of groundwater resources in all cities were basically mild or moderate warnings, showing a downward trend. This study establishes an early warning method on the carrying capacity of groundwater resources that includes the selection of early warning indicators, prediction of indicators, and determination of the early warning grades which can be a reference for other regions. [ABSTRACT FROM AUTHOR]

With the rapid advance of industrialization and urbanization and the intensified impact of global climate change, the contradiction between the global water shortage and economic growth has become prominent. This paper, taking Henan province as an example, analyzed the influence of water resource policy on regional economic growth through a calculable general equilibrium model and further discussed the relevant policy recommendations. The results showed that the improvement of water supply, water efficiency and water technology could promote the growth of the regional economy and result in a positive effect on regional GDP, employment and resident income. However, the rise of water price has a negative impact on regional economic development, mainly reflected in regional GDP, employment and household income. The improvement of water price, water efficiency and water conservancy technology would lead to a decrease in regional water consumption, while only the increase of the water supply would lead to an increase in water consumption. Accordingly, the paper puts forward policy suggestions, such as accelerating the improvement of water conservancy facilities, establishing a reasonable water price mechanism and actively exploring experience in water conservation and emission reduction. [ABSTRACT FROM AUTHOR]

Water used for production is the primary consumer of regional water. Water footprint reflects the actual water consumption of each product, which can reflect the intensity of water consumption of each production sector and the flow of water resources implied in the product trade. In this paper, the water footprint of each sector in Henan Province in 2017 was calculated using non-competitive input-output techniques. Furthermore, a dual-objective planning model that minimizes water resource export and maximizes labor compensation was established, based on which the export structure of the sector in the province was optimized. Research findings show that agriculture is the primary consuming sector of water resources from the direct water use perspective. In comparison, the food processing industry is the major consuming sector of water resources from the water footprint perspective. The difference in water resources consumed by sectors from the perspective of water footprint is smaller than that from the perspective of direct water use. Second, most water-intensive sectors have a relatively large water footprint of out-of-province use, which results in 52.75% of Henan Province's produced water being consumed outside the province. Third, the current export structure adjustment of sectors in Henan Province can achieve a Pareto improvement of water conservation and economic development. It is expected to save 14.65% of the province's export water resources and increase Henan Province's total exports by 170.61 billion (170.61 - 109) yuan and increase labor compensation by 39.76 billion yuan. This study can be used to optimize water allocation and improve sustainable water use in water-scarce regions. [ABSTRACT FROM AUTHOR]

The determination of the total amount of water pollutant emission in different regions is a difficult problem faced by managers and researchers. Previous studies mostly focused on operability and fairness with little attention paid to local water quality. In order to make total emission pollutant control (TEPC) truly serve the improvement of water quality, a water total emission pollutant allocation model was built based on water environmental carrying capacity (WECC) in this paper. This model was used to construct a water pollutant emission control allocation scheme for 28 cities in Henan Province, China. The results showed that the chemical oxygen demand (COD) reduction rates for these cities ranged from 16.8 to 38.6% and ammonia-nitrogen (NH3-N) reduction rates ranged from 5.7 to 43.5% in 2020, which were different from the previous targets for these cities without considering their current status of water quality. The largest COD reduction rates for different types of point sources (industrial, urban, and large-scale livestock sources) were 35.4%, 39.0%, and 38.0%, respectively, and the largest NH3-N reduction rates were 62.2%, 42.5%, and 43.5%, respectively. This study solves the problem of long-term disconnection between TEPC and water quality improvement in China. The results can also be applied to implement the TEPC to improve water quality in other regions with a similar problem. [ABSTRACT FROM AUTHOR]