Evaluation and Improvement of SMOS and SMAP Soil Moisture Products for Soils with High Organic Matter over a Forested Area in Northeast China

Mengjie Jin,Xingming Zheng,Xiaofeng Li,Kai Zhao,Tao Jiang,Xiao-Jie Li

doi:10.3390/rs9040387

Abstract

Soil moisture (SM) retrieval from SMOS (the Soil Moisture and Ocean Salinity mission) and SMAP (the Soil Moisture Active/Passive mission) passive microwave data over forested areas with required accuracy is of great significance and poses some challenges. In this paper, we used Ground Wireless Sensor Network (GWSN) SM measurements from 9 September to 5 November 2015 to validate SMOS and SMAP Level 3 (L3) SM products over forested areas in northeastern China. Our results found that neither SMOS nor SMAP L3 SM products were ideal, with respective RMSE (root mean square error) values of 0.31 cm3/cm3 and 0.17 cm3/cm3. Nevertheless, some improvements in SM retrieval might be achievable through refinements of the soil dielectric model with respect to high percentage of soil organic matter (SOM) in the forested area. To that end, the potential of the semi-empirical soil dielectric model proposed by Jun Liu (Liu’s model) in improving SM retrieval results over forested areas was investigated. Introducing Liu’s model into the retrieval algorithms of both SMOS and SMAP missions produced promising results. For SMAP, the RMSE of L3 SM products improved from 0.16 cm3/cm3 to 0.07 cm3/cm3 for AM (local solar time around 06:00 am) data, and from 0.17 cm3/cm3 to 0.05 cm3/cm3 for PM (local solar time around 06:00 pm) data. For SMOS ascending orbit products, the accuracy was improved by 56%, while descending orbit products improved by 45%.

Highlights

Soil moisture (SM) is a vital variable in the global land surface water cycle and energy cycle.Accurate estimates of SM can be used to forecast and prevent floods and extreme drought events.In addition, SM estimation accuracy directly influences the reliability of numerical weather predictions and hydrological models
The Soil Moisture Active/Passive (SMAP) SM values were closer to the ground measurements than Soil Moisture and Ocean Salinity (SMOS), with a daily AM mean value of 0.28 cm3 /cm3 and PM
Due to the high content of soil organic matter (SOM) in the top soil layer of the forested study area, a new soil dielectric model (Liu’s model) that considers the impacts of SOM was introduced into the retrieval algorithms of both SMOS and SMAP

Summary

Introduction

Soil moisture (SM) is a vital variable in the global land surface water cycle and energy cycle.Accurate estimates of SM can be used to forecast and prevent floods and extreme drought events.In addition, SM estimation accuracy directly influences the reliability of numerical weather predictions and hydrological models. Several studies have reported that L-band passive microwave radiometry is the most promising technique for monitoring SM in vegetated areas, due to its ability to penetrate the canopy cover and sensitivity to SM in all weather conditions [1,2,3]. The most commonly used satellite-based sources of SM are the Soil Moisture and Ocean Salinity (SMOS) mission, launched in 2009, and the Soil Moisture Active/Passive (SMAP) mission, launched in 2015. Both SMOS and SMAP are equipped with L-band sensors and aim to provide global near-surface SM (0–5 cm depth) products with an accuracy level of 0.04 cm3 /cm

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