Enhanced Soil Moisture Retrieval through Integrating Satellite Data with Pedotransfer Functions in a Complex Landscape of Ethiopia

Author:

Teferi Ermias12ORCID,O’Donnell Greg3,Kassawmar Tibebu2,Mersha Berihun D.4,Ayele Gebiaw T.5ORCID

Affiliation:

1. Center for Environment and Development Studies, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia

2. Water and Land Resource Center (WLRC), Addis Ababa University, Addis Ababa P.O. Box 3880, Ethiopia

3. School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK

4. Department of Hydraulic and Water Resources Engineering, Debre Tabor University, Debre Tabor P.O. Box 272, Ethiopia

5. Australia River Institute and School of Engineering, Griffith University, Brisbane QLD 4111, Australia

Abstract

Remotely sensed soil moisture products potentially provide a valuable resource for monitoring agricultural drought and assessing food security. The agriculture dominated countries of Eastern Africa experience high inter-annual variability of rainfall, but the monitoring and assessment of the predominantly rainfed agriculture systems is hindered by an absence of ground-based observations. This study evaluates the accuracy of three soil moisture products: ASCAT SWI 12.5 km, SMAP soil moisture data 9 km (SPL3SMP_E), and enhanced surface soil moisture map derived through integrating ASCAT SWI and Pedotransfer Functions (PTFs) (ASCAT_PTF_SM), in Ethiopia, through comparison with in situ-observed soil moisture datasets. Additionally, a new water retention PTF, developed for Ethiopian soils, is integrated with a high-resolution soil property dataset to enhance the spatial resolution of the soil moisture product. The results show that the new integrated dataset performs better in terms of unbiased root mean square error (ubRMSE = 0.0398 m3/m3) and bias (0.0222 m3/m3) in comparison with ASCAT SWI 12.5 km (ubRMSE = 0.0.0771 m3/m3, bias = 0.1065 m3/m3). SMAP is found to have limitations during the wet season, overestimating soil moisture. The finer spatial resolution of the data allows for a better depiction of heterogeneity of soil moisture across the landscape and can be used to identify water-related issues and improve hydrological models for agricultural water management.

Funder

UK Research and Innovation’s Global Challenges Research Fund

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

Reference59 articles.

1. Investigating soil moisture–climate interactions in a changing climate: A review;Seneviratne;Earth-Sci. Rev.,2010

2. Observed data-based assessment of relationships among soil moisture at various depths, precipitation, and temperature;Mahmood;Appl. Geogr.,2012

3. Responses of sensible and latent heat fluxes to soil moisture changes: Temporal stability analysis across different land surface types on the Tibetan Plateau;Wang;Atmosphere,2020

4. Influence of Soil Moisture Content on the Rainfall Redistribution into Surface Runoff and Infiltration;Mezentsev;Water,2021

5. The International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurements;Dorigo;Hydrol. Earth Syst. Sci.,2011

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