Abstract
The goal of this study was to validate soil moisture data from Soil Moisture Ocean Salinity (SMOS) using two in situ databases for Pernambuco State, located in Northeast Brazil. The validation process involved two approaches, pixel-station comparison and areal average, for three regions in Pernambuco with different climatic characteristics. After validation, the SMOS data were used for drought assessment by calculating soil moisture anomalies for the available period of data. Four statistical criteria were used to verify the quality of the satellite data: Pearson correlation coefficient, Willmott index of agreement, BIAS, and root mean squared difference (RMSD). The average RMSD calculated from the daily time series in the pixel and the areal assessment were 0.071 m3m−3 and 0.04 m3m−3, respectively. Those values are near to the expected 0.04 m3m−3 accuracy of the SMOS mission. The analysis of soil moisture anomalies enabled the assessment of the dry period between 2012 and 2017 and the identification of regions most impacted by the drought. The driest year for all regions was 2012, when the anomaly values achieved −50% in some regions. The use of SMOS data provided additional information that was used in conjunction with the precipitation data to assess drought periods. This may be particularly relevant for planning in agriculture and supporting decision makers and farmers.
Highlights
Soil moisture is an important parameter of the hydrologic cycle, which has hydrological, ecological, environmental, and agricultural impacts
The analysis was accomplished in the following three steps: (1) application of the criteria presented in the prior section to daily and eight-day time interval firstly for pixel assessment; (2) application of the assessment criteria using areal average for the three regions; and (3) after validation of the Soil Moisture Ocean Salinity (SMOS) data, using the soil moisture series to generate maps to evaluate the severity of the recent drought in terms of spatial and temporal dynamics
The statistical criteria values showed that SMOS data fit the in situ data well
Summary
Soil moisture is an important parameter of the hydrologic cycle, which has hydrological, ecological, environmental, and agricultural impacts. Soil moisture monitoring supplies fundamental information about interactions between soil, vegetation, and atmosphere to improve the accuracy of meteorological forecasting [3,4]. These data help improve agricultural productivity and flood and drought risk management, contributing to supporting actions that mitigate the effects of water scarcity [1,5,6]. Soil moisture has been applied for drought monitoring by the United States Drought Monitor, which uses data from the U.S National Weather
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
