AIMC Topic: Water Resources

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A new strategy for groundwater level prediction using a hybrid deep learning model under Ecological Water Replenishment.

Environmental science and pollution research international
Accurate prediction of the groundwater level (GWL) is crucial for sustainable groundwater resource management. Ecological water replenishment (EWR) involves artificially diverting water to replenish the ecological flow and water resources of both sur...

Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

Environmental science and pollution research international
The breathtaking economic development put a heavy toll on ecology, especially on water pollution. Efficient water resource management has a long-term influence on the sustainable development of the economy and society. Economic development and ecolog...

Different policies constrained agricultural non-point pollutants emission trading management for water system under interval, fuzzy, and stochastic information.

Environmental research
Formulating suitable policies is essential for resources and environmental management. In this study, an agricultural pollutants emission trading management model driven by water resources and pollutants control is developed to search reasonable poli...

Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue.

Environmental science and pollution research international
While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS) have been frequently employed in the field of water resources, documents aimed to...

A comparative study of data-driven models for runoff, sediment, and nitrate forecasting.

Journal of environmental management
Effective prediction of qualitative and quantitative indicators for runoff is quite essential in water resources planning and management. However, although several data-driven and model-driven forecasting approaches have been employed in the literatu...

Daily reference evapotranspiration prediction for irrigation scheduling decisions based on the hybrid PSO-LSTM model.

PloS one
The shortage of available water resources and climate change are major factors affecting agricultural irrigation. In order to improve the irrigation water use efficiency, it is necessary to predict the water requirements for crops in advance. Referen...

Enhanced rainfall prediction performance via hybrid empirical-singular-wavelet-fuzzy approaches.

Environmental science and pollution research international
Rainfall is a vital process in the hydrological cycle of the globe. Accessing reliable and accurate rainfall data is crucial for water resources operation, flood control, drought warning, irrigation, and drainage. In the present study, the main objec...

Real-time streamflow forecasting in a reservoir-regulated river basin using explainable machine learning and conceptual reservoir module.

The Science of the total environment
Real-time streamflow forecasting is essential to manage water resources effectively in a reservoir-regulated basin. However, forecasting becomes challenging without weather and upstream reservoir outflows forecasts in real-time. In this context, a no...

Stepwise decomposition-integration-prediction framework for runoff forecasting considering boundary correction.

The Science of the total environment
Predicting river runoff accurately is of substantial significance for flood control, water resource allocation, and basin ecological dispatching. To explore the reasonable and effective application of time series decomposition in runoff forecasting, ...

Evaluating water resource carrying capacity using the deep learning method: a case study of Yunnan, Southwest China.

Environmental science and pollution research international
Water resource carrying capacity (WRCC) is an important index for measuring the relations between water resource systems and socio-economic-environmental development. In view of the difficulty in describing the complex and nonlinear relationships bet...