Review of GPM IMERG performance: A global perspective

RK Pradhan, Y Markonis, MRV Godoy… - Remote Sensing of …, 2022‏ - Elsevier
Accurate, reliable, and high spatio-temporal resolution precipitation data are vital for many
applications, including the study of extreme events, hydrological modeling, water resource …

[HTML][HTML] Satellite remote sensing of precipitation and the terrestrial water cycle in a changing climate

V Levizzani, E Cattani - Remote sensing, 2019‏ - mdpi.com
The water cycle is the most essential supporting physical mechanism ensuring the existence
of life on Earth. Its components encompass the atmosphere, land, and oceans. The cycle is …

Suitability of 17 rainfall and temperature gridded datasets for largescale hydrological modelling in West Africa

M Dembélé, B Schaefli… - Hydrology and Earth …, 2020‏ - hess.copernicus.org
This study evaluates the ability of different gridded rainfall datasets to plausibly represent the
spatiotemporal patterns of multiple hydrological processes (ie streamflow, actual …

Model estimates of China's terrestrial water storage variation due to reservoir operation

N Dong, J Wei, M Yang, D Yan, C Yang… - Water Resources …, 2022‏ - Wiley Online Library
Understanding the role of reservoirs in the terrestrial water cycle is critical to support the
sustainable management of water resources especially for China where reservoirs have …

Machine learning–based blending of satellite and reanalysis precipitation datasets: A multiregional tropical complex terrain evaluation

MA Ehsan Bhuiyan, EI Nikolopoulos… - Journal of …, 2019‏ - journals.ametsoc.org
This study evaluates a machine learning–based precipitation ensemble technique (MLPET)
over three mountainous tropical regions. The technique, based on quantile regression …

[HTML][HTML] Machine learning-based error modeling to improve GPM IMERG precipitation product over the brahmaputra river basin

MAE Bhuiyan, F Yang, NK Biswas, SH Rahat… - Forecasting, 2020‏ - mdpi.com
The Integrated Multisatellite Retrievals for Global Precipitation Measurement (GPM)(IMERG)
Level 3 estimates rainfall from passive microwave sensors onboard satellites that are …

Toward an improved ensemble of multi-source daily precipitation via joint machine learning classification and regression

H Chen, T Wang, C Montzka, H Gao, N Guo… - Atmospheric …, 2024‏ - Elsevier
Accurate estimation of precipitation at local to global scales can considerably enhance our
understanding of climate system dynamics. While numerous precipitation products are …

[HTML][HTML] Attribution analysis of seasonal runoff in the source region of the yellow river using seasonal Budyko hypothesis

G Ji, L Wu, L Wang, D Yan, Z Lai - Land, 2021‏ - mdpi.com
Previous studies mainly focused on quantifying the contribution rate of different factors on
annual runoff variation in the source region of the Yellow River (SRYR), while there are few …

[HTML][HTML] Artificial intelligence-based techniques for rainfall estimation integrating multisource precipitation datasets

RS Khan, MAE Bhuiyan - Atmosphere, 2021‏ - mdpi.com
This study presents a comprehensive investigation of multiple Artificial Intelligence (AI)
techniques—decision tree, random forest, gradient boosting, and neural network—to …

Groundwater modeling in data scarce aquifers: the case of Gilgel-Abay, Upper Blue Nile, Ethiopia

FK Khadim, Z Dokou, R Lazin, S Moges… - Journal of …, 2020‏ - Elsevier
Groundwater (GW) is the main source of domestic water supply in Ethiopia (85%), however,
despite widespread acknowledgement of its potential for resource-based development and …