Exploring Spatio-Temporal Variations in Water and Land Resources and Their Driving Mechanism Based on the Coupling Coordination Model: A Case Study in Western Jilin Province, China

Agriculture, Journal Year: 2025, Volume and Issue: 15(1), P. 98 - 98

Published: Jan. 3, 2025

Water and land resources (WLR) are the most important basic for social economic development. The effective alignment of WLR is crucial maximizing resource utilization promoting sustainable regional This study focuses on Western Jilin Province (WJP), China, employing degree coupling coordination model, spatial autocorrelation, center gravity transfer model to assess characterize spatio-temporal differentiation patterns water matching from 2006 2020. Five indicators—annual average temperature (AAT), urbanization rate (UR), population density (PD), reclamation (RR), (WRUR)—were selected as influencing factors. A Tobit was constructed elucidate driving mechanisms behind evolution (CCD) in WJP. results indicate following: (1) From a temporal perspective, WJP has shown year-on-year increase 2020, transitioning moderate imbalance intermediate coordination, reflecting trend continuous improvement. (2) Regarding distribution, overall remained relatively stable between 2020; however, direction distribution gradually shifted northeast southwest then northwest southeast. (3) AAT, PD, RR 2020 were all statistically significant at p < 0.01. Notably, positively influences CCD WLR, whereas AAT PD exert negative impact. In contrast, UR WRUR do not significantly affect WLR.

Language: Английский

Research on Water Resource Carrying Capacity Assessment and Water Quality Forecasting Based on Feature Selection with CNN-BiLSTM-Attention Model of the Min River Basin

Water, Journal Year: 2025, Volume and Issue: 17(6), P. 824 - 824

Published: March 13, 2025

To achieve a more accurate assessment of water resource carrying capacity (WRCC), the indicators resources, social and ecological environment were selected to construct WRCC system on basis combinatorial assignment method with advantages. Moreover, incorporation key quality influences into predictions facilitated performance predictive models. Adaptive Lasso Regression was used select factors affecting quality, whereas CatBoost algorithm ranked importance by in prediction model. The Convolutional Neural Network-Bidirectional Long Short-Term Memory-Attention (CNN-BiLSTM-Attention) model forecast WQI. research results propose new evaluation method. show that average barrier levels for socio-economic development, 34.97%, 34.93%, 30.10%, respectively. Compared other layers WRCC, obstacle degree layer has always been lower. total sewage treatment, greening coverage built-up areas, per capita green space parks main within Min River Basin. Based factor screening, it can be seen dissolved oxygen is positively correlated watershed, while influencing are negatively Total nitrogen had greatest impact conditions regression coefficient −1.7532. From comparison results, known hybrid make MAE value 45% monitoring points reach minimum, RMSE 35% minimum. percentages remaining models reached lowest values 15% 20% 30%, models, MSE relatively small, which conducive predicting

Language: Английский

Evaluating the Impact of Transformation and Upgrading on the Green Efficiency of Industrial Water: Evidence from Sectoral Performance

Water Resources Management, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

Language: Английский