Improving the simulations of the hydrological model in the karst catchment by integrating the conceptual model with machine learning models

C Sezen, M Šraj - Science of the Total Environment, 2024‏ - Elsevier
Hydrological modelling can be complex in nonhomogeneous catchments with diverse
geological, climatic, and topographic conditions. In this study, an integrated conceptual …

[HTML][HTML] Advancing hydrology through machine learning: insights, challenges, and future directions using the CAMELS, caravan, GRDC, CHIRPS, PERSIANN, NLDAS …

F Hasan, P Medley, J Drake, G Chen - Water, 2024‏ - mdpi.com
Machine learning (ML) applications in hydrology are revolutionizing our understanding and
prediction of hydrological processes, driven by advancements in artificial intelligence and …

A critical review on multi-sensor and multi-platform remote sensing data fusion approaches: current status and prospects

F Samadzadegan, A Toosi… - International Journal of …, 2024‏ - Taylor & Francis
Numerous remote sensing (RS) systems currently collect data about Earth and its
environments. However, each system provides limited data in terms of spatial resolution …

Leveraging machine learning and open-source spatial datasets to enhance flood susceptibility map** in transboundary river basin

Y Bhattarai, S Duwal, S Sharma… - International Journal of …, 2024‏ - Taylor & Francis
Floods pose devastating effects on the resiliency of human and natural systems. flood risk
management challenges are typically complicated in the transboundary river basin due to …

GIS-based flood susceptibility map** using bivariate statistical model in Swat River Basin, Eastern Hindukush region, Pakistan

ZU Rahman, W Ullah, S Bai, S Ullah, MA Jan… - Frontiers in …, 2023‏ - frontiersin.org
Frequent flooding can greatly jeopardize local people's lives, properties, agriculture,
economy, etc. The Swat River Basin (SRB), in the eastern Hindukush region of Pakistan, is a …

[HTML][HTML] Flood susceptibility map** using SAR data and machine learning algorithms in a small watershed in northwestern Morocco

S Hitouri, M Mohajane, M Lahsaini, SA Ali, TA Setargie… - Remote Sensing, 2024‏ - mdpi.com
Flood susceptibility map** plays a crucial role in flood risk assessment and management.
Accurate identification of areas prone to flooding is essential for implementing effective …

A novel multi-strategy hydrological feature extraction (MHFE) method to improve urban waterlogging risk prediction, a case study of Fuzhou City in China

H Huang, X Lei, W Liao, X Zuo, H Wang - Science of The Total Environment, 2023‏ - Elsevier
Reliable hydrological data ensure the precision of the urban waterlogging simulation. To
reduce the simulation error caused by insufficient basic data, a multi-strategy method …

[HTML][HTML] Integration of watershed eco-physical health through algorithmic game theory and supervised machine learning

AN Khiavi, M Tavoosi, H Khodamoradi… - Groundwater for …, 2024‏ - Elsevier
The eco-physical health assessment of watersheds is crucial for sustainable water resource
management and ecosystem services. This study quantifies the eco-physical health of the …

[HTML][HTML] SHAP-powered insights into spatiotemporal effects: Unlocking explainable Bayesian-neural-network urban flood forecasting

W Chu, C Zhang, H Li, L Zhang, D Shen, R Li - International Journal of …, 2024‏ - Elsevier
Given the increased incidence of pluvial floods due to climate change and urbanization, the
demand for highly efficient and accurate modeling within urban drainage systems has …

Leveraging GIS-based AHP, remote sensing, and machine learning for susceptibility assessment of different flood types in peshawar, Pakistan

M Tayyab, M Hussain, J Zhang, S Ullah, Z Tong… - Journal of …, 2024‏ - Elsevier
Due to its diverse topography, Pakistan faces different types of floods each year, which
cause substantial physical, environmental, and socioeconomic damage. However, the …