As global water scarcity becomes increasingly acute, water demand forecasting has emerged as a critical component in water resource management and planning. This review aims to comprehensively survey and analyze the current state of research, existing issues, and development trends in the field of water demand forecasting. Presently, there are numerous studies on water demand forecasting; however, most of the forecasting results tend to be overestimated. On the mechanistic level, research has gradually shifted from considering single factors to accounting for the complex influences of multiple factors. This paper summarizes the mechanism of water demand from the three levels of agriculture, industry, and residential life. In terms of forecasting methods, various techniques have been explored and applied, particularly new methods based on artificial intelligence and machine learning, which have demonstrated significant advantages in improving forecasting accuracy and handling nonlinear relationships. Despite the notable progress and practical achievements in water demand forecasting, several challenges and issues remain. Future research should focus on diversifying methodologies, comprehensively considering multiple influencing factors, further refining forecasting models and technical systems, strengthening uncertainty and risk management, and emphasizing practical applications and policy guidance.

With the impact of climate change in recent years, the instability of precipitation and the increase of evaporation have made water resources in Shaanxi Province more and more stressed. How to maintain stable economic development while ensuring the sustainable development of agriculture within the limited water resources has become an important issue facing Shaanxi Province. This paper analyzes the temporal and spatial distribution characteristics of maize irrigation water requirement in Shaanxi Province based on meteorological data and obtains the ideal irrigation water requirement. However, considering the agricultural water scarcity issue in this region, this paper establishes different water scarcity scenarios, adopts the Jensen model to construct an objective function aimed at minimizing crop yield reduction, and solves it using a genetic algorithm to obtain the optimized maize irrigation scheduling under different water scarcity scenarios. The results analysis indicates the following: (1) The effective rainfall in Shaanxi Province from 1960 to 2019 shows a slight upward trend, while the maize water requirement and maize irrigation water requirement shows a downward trend. (2) The spatial distribution of maize irrigation water requirement in Shaanxi Province decreases gradually from north to south. High-value areas are mainly distributed in the northern regions of Yulin City and Yan’an City in Shanbei. Low-value areas are distributed in Ankang City in Shannan. (3) In the face of water scarcity, spring maize should ensure water use during the middle growth period, fast development period, and initial growth periods. Under the same water scarcity conditions, the yield reduction rate is the highest in Guanzhong, followed by the Shannan, and the lowest in Shanbei. This paper aims to provide a scientific and reasonable optimization plan for maize irrigation in Shaanxi Province by calculating and analyzing the maize irrigation water requirement in Shaanxi Province, combined with optimization tools such as genetic algorithms, to address the challenges brought by water resource constraints.

Urban expansion has reshaped land-use patterns, altered the provision of ecosystem services, and brought challenges to regional sustainable development. However, studies on urban agglomerations with uneven development remain insufficient. This study takes the core development area of the Central Plains Urban Agglomeration as the study area and explores changes in ecosystem services during multidimensional urbanization from 2000 to 2020. Using the CASA and InVEST models, three ecosystem services, namely net primary productivity (NPP), water yield (WY), and soil conservation (SC), were quantified. Spatial associations and local heterogeneity were analyzed using the bivariate Moran’s I. The results show that regional urbanization exhibited a Zhengzhou-centered monocentric pattern, with rapid growth in GDP density and significant expansion of urban land. The responses of ecosystem services to urbanization showed divergent trends, with NPP increasing slightly, while WY and SC decreased. NPP and SC showed a synergistic effect, whereas WY had trade-off relationships with both services. Due to uneven regional development, urbanization indicators and ecosystem services showed evident spatially heterogeneous relationships. This study provides evidence for ecological conservation, ecosystem-service management, and sustainable spatial governance in developing urban agglomerations where rapid growth and ecological constraints coexist.