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Development of a spatially-varying Statistical Soil Moisture Profile model by coupling memory and forcing using hydrologic soil groups.

Authors :
Pal, Manali
Maity, Rajib
Source :
Journal of Hydrology. Mar2019, Vol. 570, p141-155. 15p.
Publication Year :
2019

Abstract

Highlights • Spatially varying Statistical Soil Moisture Profile (SSMP) model is developed. • SSMP considers Hydrologic Soil Groups (HSGs) to impart spatial transferability. • SSMP model is able to estimate soil moisture profile at ungauged locations. • Promising to assess vertical soil moisture profile over a large area. Abstract Information on vertical Soil Moisture Content (SMC) profile is important for several hydro-meteorological processes. This study borrows the idea of coupling the memory and forcing from a previous study and develops a spatially-varying Statistical Soil Moisture Profile (SSMP) model to estimate the vertical SMC profile. It uses only surface soil moisture (0–5 cm) values and Hydrological Soil Groups (HSGs) information of the location. The focus of the study is incorporation of the HSG information to ensure the spatial transferability of the proposed model by capturing the spatial variations of soil moisture profile with the change in soil hydraulic properties. The wide range of soil moisture data for model development as well as for spatial validation is obtained from 171 stations from different networks of International Soil Moisture Network (ISMN) at five different depths, i.e., 5, 10, 20, 51 and 102 cm. The HSG information at the locations are extracted from the Web Soil Survey (WSS) database. The potential of spatial transferability of the SSMP model is assessed by applying it to the new stations within the corresponding HSG. Model performances are promising for all four depth pairs (5–10, 10–20, 20–51 and 51–102 cm) of all four HSGs during both model development and spatial validation given the model complexity. Hence, the spatially-varying SSMP model is suitable at the ungauged locations by incorporating the HSG information. The potential application of the proposed model shows the future scope to assimilate the satellite based surface SMC data into the model to develop a vertical soil moisture profile map over a large area. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00221694
Volume :
570
Database :
Academic Search Index
Journal :
Journal of Hydrology
Publication Type :
Academic Journal
Accession number :
134744304
Full Text :
https://doi.org/10.1016/j.jhydrol.2018.12.042