Surface runoff response to climate change based on artificial neural network (ANN) models: a case study with Zagunao catchment in Upper Minjiang River, Southwest China | Citedby Results | Journal of Water and Climate Change | IWA Publishing

Skip to Main Content

Skip Nav Destination

Surface runoff response to climate change based on artificial neural network (ANN) models: a case study with Zagunao catchment in Upper Minjiang River, Southwest China

Journal of Water and Climate Change (2019) 10 (1): 158–166.

This article has been cited by the following articles in journals that are participating in CrossRef Cited-by Linking.

Quantification of the effects of conservation practices on surface runoff and soil erosion in croplands and their trade-off: A meta-analysis

Joy Rajbanshi
Sharmistha Das
Roni Paul

Science of The Total Environment (2023) 864: 161015.

Monthly Water Balance of Ungauged Watersheds Using Empirical and Conceptual Models: A Case Study of the Semiarid Mountainous Watersheds, Southwest of Saudi Arabia

Abdulnoor A. J. Ghanim

Sustainability (2023) 15 (11): 8728.

Optimization of agricultural soil and water resources under fuzzy and random uncertainties: Synergy and trade-off between equity-based economic benefits, nonpoint pollution and water use efficiency

Yingshan Chen
Qiang Fu
Vijay P. Singh
Yi Ji
Mo Li
Yijia Wang

Agricultural Water Management (2023) 281: 108264.

An artificial neural network‐hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal

Roshika Bhattarai
Utsav Bhattarai
Vishnu Prasad Pandey
Pawan Kumar Bhattarai

Journal of Flood Risk Management (2022) 15 (4)

Consumption of Atmospheric Carbon Dioxide through Weathering of Ultramafic Rocks in the Voltri Massif (Italy): Quantification of the Process and Global Implications

Francesco Frondini
Orlando Vaselli
Marino Vetuschi Zuccolini

Geosciences (2019) 9 (6): 258.