Results 71 to 80 of about 576 (159)

A Machine Learning Approach for Improving the Accuracy of Gridded Precipitation With Uncertainty Quantification

International Journal of Climatology, Volume 46, Issue 1, January 2026.
A novel machine learning (ML) approach combining extreme gradient boosting with quantile regression is used to create Vietnam Precipitation with Uncertainty (VNpu). Our VNpu dataset outperforms individual input products, benchmark interpolation methods and an existing gauge‐based product, particularly for heavy and extreme rainfall events. ABSTRACT The
Vinh Ngoc Tran, Manh‐Hung Le, Tam V. Nguyen, Trong Dieu Hien Le, Hung T. T. Nguyen, Hong Xuan Do, Binh Quang Nguyen, Doan Van Binh, Tu Hoang Le, Hung Thanh Pham, Hoang Tran, Thanh Duc Dang, John D. Bolten, Tan Phan‐Van, Thanh Ngo‐Duc, Venkataraman Lakshmi   +15 more
wiley   +1 more source

Evaluation of Satellite Precipitation Products and Their Potential Influence on Hydrological Modeling over the Ganzi River Basin of the Tibetan Plateau

Advances in Meteorology, 2017
In the last few years, satellite-based precipitation datasets are believed to be a potential source for forcing inputs in driving hydrological models, which are important especially in complex terrain areas or ungauged basins where ground gauges are ...
Alaa Alden Alazzy, Haishen Lü, Rensheng Chen, Abubaker B. Ali, Yonghua Zhu, Jianbin Su   +5 more
doaj   +1 more source

Evaluation of satellite rainfall estimates over Ethiopian river basins [PDF]

Hydrology and Earth System Sciences, 2011
High resolution satellite-based rainfall estimates (SREs) have enormous potential for use in hydrological applications, particularly in the developing world as an alternative to conventional rain gauges which are typically sparse.
T. G. Romilly, M. Gebremichael
doaj   +1 more source

SMAP Satellite Microwave Radiometry to Monitor River Flow and Lake Level in the Lower Mekong Basin

Earth and Space Science, Volume 13, Issue 1, January 2026.
Abstract The NASA Soil Moisture Active Passive Mission (SMAP) satellite passive microwave radiometry (PMR) capability is demonstrated for measurements of river stage, river discharge, and lake level with in situ gauging data in the Lower Mekong Basin (LMB).
A. Podkowa, S. V. Nghiem, Z. Kugler, G. R. Brakenridge   +3 more
wiley   +1 more source

Comparative Evaluation of Gridded Precipitation Datasets in Capturing Hydrological Extremes in a Mesoscale Heterogeneous Catchment in Austria

Hydrological Processes, Volume 39, Issue 12, December 2025.
Although all precipitation products performed relatively poor in representing extreme precipitation events, their performance varied across elevations. Furthermore, SPARTACUS v2.1 and IMERG‐F v07 generated streamflow simulations that broadly align with observations. However, CHIRPS v2.0 and ERA5‐Land underperformed.
Zryab Babker, Mohammed Basheer, Tim G. Reichenau, Jürgen Komma, Oscar M. Baez‐Villanueva, Morteza Zargar, Karl Schneider   +6 more
wiley   +1 more source

Impacts of Spatial and Temporal Station Availability on Gridded Precipitation Products in Central America

Earth and Space Science, Volume 12, Issue 12, December 2025.
Abstract Gridded precipitation data sets have become essential for understanding climate variability and long‐term trends; however, their accuracy and reliability strongly depend on the availability and the spatial and temporal distribution of in situ meteorological observations. Here, we evaluate the performance of four gridded precipitation products:
Isabel González‐Méndez, Diego Pons, Talia G. Anderson, Irma Ayes Rivera, Kevin J. Anchukaitis   +4 more
wiley   +1 more source

Long‐Term Precipitation Estimates Generated by a Downscaling‐Calibration Procedure Over the Tibetan Plateau From 1983 to 2015

Earth and Space Science, 2019
The World Meteorological Organization stipulates a minimum of 30 years of historical data is needed to obtain meaningful results in climatological research.
Z. Q. Ma, D. Ghent, X. Tan, K. He, H. Y. Li, X. Z. Han, Q. T. Huang, J. Peng   +7 more
doaj   +1 more source

Towards Accurate Flood Forecasting: Integrating Satellite Data, Hydrological Modeling, and Deep Learning

Journal of Flood Risk Management, Volume 18, Issue 4, December 2025.
ABSTRACT In hydrologic modeling, forecasting peak floods is a complex and high‐priority task, particularly in regions with limited in situ observations. This research investigates the potential of utilizing satellite‐based precipitation products with near real‐time updates (NRT‐SbPP), together with deep learning, to improve peak flow estimation and ...
Saeideh Pourentezari, Hossein Salehi, Alireza Razeghi Haghighi, Mojtaba Sadeghi, Alireza Faridhosseini   +4 more
wiley   +1 more source

Assessing the Efficacy of High-Resolution Satellite-Based PERSIANN-CDR Precipitation Product in Simulating Streamflow

Journal of Hydrometeorology, 2016
AbstractThis study aims to investigate the performance of Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) in a rainfall–runoff modeling application over the past three decades.
Hamed Ashouri, Phu Nguyen, Andrea Thorstensen, Kuo-lin Hsu, Soroosh Sorooshian, Dan Braithwaite   +5 more
openaire   +1 more source

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Remote Sensing, 2015
Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an ...
Shimelis B. Gebere, Tena Alamirew, Broder J. Merkel, Assefa M. Melesse   +3 more
doaj   +1 more source