Enhancing runoff forecasting through the integration of satellite precipitation data and hydrological knowledge into machine learning models

P Muñoz, DF Muñoz, J Orellana-Alvear, R Célleri - Natural Hazards, 2024 - Springer
In this study, we use feature engineering (FE) strategies to enhance the performance of
machine learning (ML) models in forecasting runoff and peak runoff. We selected a 300-km …

[HTML][HTML] Towards a Modern and Sustainable Sediment Management Plan in Mountain Catchment

A Cislaghi, E Morlotti, VG Sacchetti, D Bellingeri… - GeoHazards, 2024 - mdpi.com
Sediment management is fundamental for managing mountain watercourses and their
upslope catchment. A multidisciplinary approach—not limited to the discipline of hydraulics …

Hydrogeological mapping of fracture networks using earth observation data to improve rainfall–runoff modeling in arid mountains, Saudi Arabia

A Chaabani, E Adem, A Elfeki, MM Farran… - Open …, 2024 - degruyter.com
Rainfall–runoff modeling is essential for the hydrological analysis of basins; however, the
traditional modeling approach does not incorporate geological features such as fractures …

Unleashing the power of AI: revolutionizing runoff prediction beyond NRCS-CN method

SB Tarate, SM Raut - Arabian Journal of Geosciences, 2024 - Springer
Predicting runoff is vital for effectively planning and managing water resources within a
watershed or river basin. This research aims to compare the effectiveness of two distinct …