A comprehensive evaluation of satellite-based and reanalysis soil moisture products over the upper Blue Nile Basin, Ethiopia

被引:3
作者
Alaminie, Addis A. [1 ]
Annys, Sofie [2 ]
Nyssen, Jan [2 ]
Jury, Mark R. [3 ]
Amarnath, Giriraj [4 ]
Mekonnen, Muluneh A. [5 ]
Tilahun, Seifu A. [1 ,6 ]
机构
[1] Bahir Dar Univ, Fac Civil & Water Resources Engn, Bahir Dar, Ethiopia
[2] Univ Ghent, Dept Geog, Ghent, Belgium
[3] Univ Puerto Rico Mayaguez, Phys Dept, Mayaguez, PR USA
[4] Int Water Management Inst, 127 Sunil Mawatha, Battaramulla, Sri Lanka
[5] Alberta Energy Regulator, Regulatory Applicat Branch, Environm Sci Applicat Team, Calgary, AB, Canada
[6] Int Water Management Inst, Accra, Ghana
来源
SCIENCE OF REMOTE SENSING | 2024年 / 10卷
关键词
Soil moisture evaluation; ESA-CCI; SMAP; SMOS; ERA5; CFSR; GLDAS; LIS; Gilgel Abay watershed; Ethiopia; SYNTHETIC-APERTURE RADAR; DATA ASSIMILATION; RETRIEVAL; TEMPERATURE; PERFORMANCE; VALIDATION; EROSION; ASCAT;
D O I
10.1016/j.srs.2024.100173
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil moisture data is crucial for enhancing drought monitoring, optimizing water management, refining irrigation schedules, forecasting floods, and understanding climate change impacts. Despite the existence of long-term global satellite and reanalysis products, the performance of global satellite products in Ethiopia is underexplored, highlighting a need for comprehensive assessments to effectively utilize these resources and address critical environmental challenges. This research evaluates various operational satellites and reanalysis soil moisture datasets over the Gilgel Abay watershed. The datasets include the European Space Agency's Climate Change Initiative Soil Moisture (ESA-CCI SM), Soil Moisture and Ocean Salinity (SMOS), NASA's Soil Moisture Active Passive mission (SMAP Enhanced), the European Centre for Medium-Range Weather Forecasts Fifth Generation Reanalysis (ECMWF ERA5), Climate Forecast System reanalysis (CFSRv2), NASA's Short-term Prediction Research and Transition Center - Land Information System (SPoRT-LIS), and NASA's Global Land Data Assimilation System (GLDAS). After applying bias correction, the Kolmogorov-Smirnov two-sample t-tests, Bonferroni correction, and statistical error metrics, the evaluation reveals that all products, except NASA-GLDAS, effectively capture soil moisture dynamics. SMAP shows superior temporal dynamics, followed by SMOS, ESA-CCI, CFSRv2, LIS and ERA5. Using Spearman's rank correlation coefficient (rs), SMAP (rs = 0.68) and SMOS (rs = 0.67) identified as the most accurate soil moisture products, with SMOS excelling in spatial representation and closely aligning with the Topographic Wetness Index (TWI). However, the lack of sufficient in situ monitoring networks limits the ability to perform a thorough evaluation. Establishing these networks is essential for improving satellite retrievals and modelling in the upper Blue Nile Basin, Ethiopia.
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页数:15
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