Evaluation of satellite-derived surface soil moisture products over agricultural regions of Canada
Citation
Oozeer, Y., Fletcher, C.G., Champagne, C. (2020). Evaluation of satellite-derived surface soil moisture products over agricultural regions of Canada. Remote Sensing, [online] 12(9), http://dx.doi.org/10.3390/RS12091455
Plain language summary
Soil moisture is an important variable for agriculture, but it is difficult to measure because it varies greatly in space and time and there are limited sensors in place in Canada to monitor it. There are a number of satellite based data sets that estimate soil moisture globally, but they vary in accuracy and the frequency that they are updated. This paper examined several data sets from the European Space Agency that use different models for estimating soil moisture. The satellite data sets were compared to in situ stations in Alberta, Manitoba and Ontario. The data sets from the Soil Moisture and Ocean Salinity (SMOS) sensors were more accurate compared to the ESA Climate Change Initiative (ESA-CCI) data set, but the ESA-CCI data set covers a longer time period so it may be useful for studying long term processes.
Abstract
Soil moisture is a critical indicator for climate change and agricultural drought, but its measurement is challenging due to large variability with land cover, soil type, time, space and depth. Satellite estimates of soil moisture are highly desirable and have become more widely available over the past decade. This study investigates and compares the performance of four surface soil moisture satellite datasets over Canada, namely, Soil Moisture and Ocean Salinity Level 3 (SMOS L3), versions 3.3 and 4.2 of European Space Agency Climate Change Initiative (ESA CCI) soil moisture product and a recent product called SMOS-INRA-CESBIO (SMOS-IC) that contains corrections designed to reduce several known sources of uncertainty in SMOS L3. These datasets were evaluated against in situ networks located in mostly agricultural regions of Canada for the period 2012 to 2014. Two statistical comparison methods were used, namely, metrics for mean soil moisture and median of metrics. The results suggest that, while both methods show similar comparisons for regional networks, over large networks, the median of metrics method is more representative of the overall correlation and variability and is therefore a more appropriate method for evaluating the performance of satellite products. Overall, the SMOS products have higher daily temporal correlations, but larger biases, against in situ soil moisture than the ESA CCI products, with SMOS-IC having higher correlations and smaller variability than SMOS L3. The SMOS products capture daily wetting and drying events better than the ESA CCI products, with the SMOS products capturing at least 75% of observed drying as compared to 55% for the ESA CCI products. Overall, for periods during which there are sufficient observations, both SMOS products are more suitable for agricultural applications over Canada than the ESA CCI products, even though SMOS-IC is able to capture soil moisture variability more accurately than SMOS L3.