Estimation of Soil Moisture Index Using Multi-Temporal Sentinel-1 Images over Poyang Lake Ungauged Zone

Yufang Zhang,Xiaoling Chen,Jianmin Yin,Kun Sun,Jianya Gong

doi:10.3390/rs10010012

Abstract

The C-band radar instruments onboard the two-satellite GMES Sentinel-1 constellation provide global measurements with short revisit time (about six days) and medium spatial resolution (5 × 20 m), which are appropriate for watershed scale hydrological applications. This paper aims to explore the potential of Sentinel-1 for estimating surface soil moisture using a multi-temporal approach. To this end, a linear mixed effects (LME) model was developed over Poyang Lake ungauged zone, using time series Sentinel 1A and 1B images and soil moisture ground measurements from 15 automatic observation sites. The model assumed a linear relationship that varied with both time and space between soil moisture and backscattering coefficient (SM- σ 0 ). Results showed that three LME models developed with different polarized σ 0 images all meet the European Space Agency (ESA) accuracy requirement for GMES soil moisture product (≤5% in volume), with the vertical transmit and vertical receive (VV) polarized model achieving the best performance. However, the SM- σ 0 relationship was found to depend strongly on space, making it difficult to predict absolute soil moisture for each grid. Therefore, a relative soil moisture index was then proposed to correct for site effect. When compared with those of the linear fixed effects model, the soil moisture indices predicted by the LME model captured the temporal dynamics of measured soil moisture better, with the overall R2 and cross-validated R2 being 0.68 and 0.64, respectively. These results indicate that the LME model can be effectively applied to estimate soil moisture from multi-temporal Sentinel-1 images, which is useful for monitoring flood and drought disasters, and for improving stream flow prediction over ungauged zones.

Highlights

As an “Essential Climate Variable”, as identified by the Global Climate Observing System, soil moisture plays a critical role in the water and energy balance at the soil-atmosphere boundary, which has a large effect on climate [1,2]
Model, the performance of the vertical receive (VV) + VH polarized model is slightly worse than the single polarized models, obtaining the lowest R2 and the largest root-mean-square error (RMSE) and mean prediction error (MPE)
The linear mixed effects (LME) model that is developed in this study shows a better and more robust performance when compared with the linear fixed effects model (Figure 5)

Summary

Introduction

As an “Essential Climate Variable”, as identified by the Global Climate Observing System, soil moisture plays a critical role in the water and energy balance at the soil-atmosphere boundary, which has a large effect on climate [1,2]. The ungauged zone of Poyang Lake, which lacks hydrological observations, generally refers to the large alluvial plain stretching from seven stream flow gauging stations to the lake boundary. This region covers a majority of the Poyang Lake eco-economic zone, which is occupied by intensive rice agriculture, supporting the high-density local population. The significant seasonal fluctuations of Poyang Lake water levels and the associated inundation areas create extensive wetland ecosystems in this region [9]

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Conclusion