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Abstract
The main objective of this study is to analyze the potential use of L-band radar data for the estimation of soil moisture over tropical agricultural areas under dense vegetation cover conditions. Ten radar images were acquired using the Phased Array Synthetic Aperture Radar/Advanced Land Observing Satellite (PALSAR/ALOS)-2 sensor over the Berambadi watershed (south India), between June and October of 2018. Simultaneous ground measurements of soil moisture, soil roughness, and leaf area index (LAI) were also recorded. The sensitivity of PALSAR observations to variations in soil moisture has been reported by several authors, and is confirmed in the present study, even for the case of very dense crops. The radar signals are simulated using five different radar backscattering models (physical and semi-empirical), over bare soil, and over areas with various types of crop cover (turmeric, marigold, and sorghum). When the semi-empirical water cloud model (WCM) is parameterized as a function of the LAI, to account for the vegetation’s contribution to the backscattered signal, it can provide relatively accurate estimations of soil moisture in turmeric and marigold fields, but has certain limitations when applied to sorghum fields. Observed limitations highlight the need to expand the analysis beyond the LAI by including additional vegetation parameters in order to take into account volume scattering in the L-band backscattered radar signal for accurate soil moisture estimation.
Highlights
An accurate knowledge of soil moisture is important for the evaluation of several processes, such as evapotranspiration, infiltration, and runoff, and for the modeling of the soil–vegetation–atmosphere interface [1,2,3,4,5]
We present the performance of different models for the simulation of backscattering over bare and vegetation-covered soils and we discuss the potential of Water Cloud Model (WCM) inversion for soil moisture estimations
The sensitivity of L-band radar signals to the surface soil moisture is analyzed for HH and HV radar polarizations, and for different agricultural areas
Summary
An accurate knowledge of soil moisture is important for the evaluation of several processes, such as evapotranspiration, infiltration, and runoff, and for the modeling of the soil–vegetation–atmosphere interface [1,2,3,4,5]. Soil moisture measurements can contribute to the management of water resources [6,7]. Various global soil moisture products are available on an operational basis. These rely on microwave radiometric measurements (e.g., SMOS: Soil Moisture and Ocean Salinity, AMSR-E: Advanced Microwave Scanning Radiometer for EOS, SMAP: Soil Moisture Active and Passive mission) and/or scatterometer measurements (e.g., ASCAT: Advanced SCATterometer), and have a spatial resolution ranging between 10 and 40 km [12,13,14,15,16]. As agricultural farms are small in size (~ ha), these global soil moisture products alone are of little use for the evaluation of soil moisture at the scale of individual fields
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