Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data |
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| Institution: | 1. Centre for Carbon, Water and Food, University of Sydney, Camden, NSW, 2570, Australia;2. Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, 2751, Australia;3. Monash University, Melbourne, VIC, 3800, Australia;4. School of Life and Environmental Sciences, University of Sydney, NSW, 2006, Australia;5. Swinburne University of Technology, Hawthorn, VIC, 3122, Australia;1. Department of Environment Protection and Development, Environmental Engineering Faculty, Warsaw University of Technology, ul. Nowowiejska 20, Warsaw 00-653, Poland;2. Hydrological Forecasting Office, Institute of Meteorology and Water Management ? National Research Institute, ul. Piotra Borowego 14, Cracow 30-215, Poland;3. Department of Bioresource Engineering, McGill University, 21 111 Lakeshore Road, Sainte-Anne-de-Bellevue, QC H9x3V9, Canada,;1. Water Resources and Remote Sensing Laboratory, School of Civil, Architectural, and Environmental Engineering, Sungkyunkwan University, Suwon 440-746, Republic of Korea;2. Water Resources and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Sungkyunkwan University, Suwon 440-746, Republic of Korea;1. Western Australian Centre for Geodesy, The Institute for Geoscience Research, Curtin University, Perth, Australia;2. Civil and Environmental Engineering Department, University of California, Los Angeles, USA;3. Institute of Geodesy and Geoinformation (IGG), Bonn University, Bonn, Germany;4. Ethiopian Institute of Water Resources, Addis Ababa University, Ethiopia;5. Department of Natural Resources and the Environment, University of Connecticut, USA;6. School of Earth Sciences and Engineering, Hohai University, Nanjing, China;7. Department of Hydraulic and Water Resources Engineering, Arba Minch University, Arba Minch, Ethiopia |
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| Abstract: | Monitoring of temporal and spatial soil moisture variability is an important issue, both from practical and scientific point of view. It is well known that passive, L-band, radiometric measurements provide best soil moisture estimates. Unfortunately as it was observed during Soil Moisture and Ocean Salinity (SMOS) mission, which was specially dedicated to measure soil moisture, these measurements suffer significant data loss. It is caused mainly by radio frequency interference (RFI) which strongly contaminates Central Europe and even in particularly unfavorable conditions, might prevent these data from being used for regional or watershed scale analysis. Nevertheless, it is highly awaited by researchers to receive statistically significant information on soil moisture over the area of a big watershed. One of such watersheds, the Odra (Oder) river watershed, lies in three European countries – Poland, Germany and the Czech Republic. The area of the Odra river watershed is equal to 118,861 km2 making it the second most important river in Poland as well as one of the most significant one in Central Europe.This paper examines the SMOS soil moisture data in the Odra river watershed in the period from 2010 to 2012. This attempt was made to check the possibility of assessing, from the low spatial resolution observations of SMOS, useful information that could be exploited for practical aims in watershed scale, for example, in water storage models even while moderate RFI takes place. Such studies, performed over the area of a large watershed, were recommended by researchers in order to obtain statistically significant results. To meet these expectations, Centre Aval de Traitement des Donnes SMOS (CATDS), 3-days averaged data, together with Global Land Data Assimilation System (GLDAS) National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab (NOAH) model 0.25 soil moisture values were used for statistical analyses and mutual comparisons.The results obtained using various statistical tools unveil high scientific potential of CATDS SMOS data to study soil moisture over the Odra river watershed. This was also confirmed by reasonable agreement between results derived from CATDS SMOS Ascending and GLDAS data sets. This agreement was achieved mainly by using these data spatially averaged over the whole watershed area, and for observations performed in the period longer than three-day averaging time. Comparisons of separate three-day data in a given pixel position, or at smaller areas would be difficult because of data gaps. Hence, the results of the work suggest that despite of RFI interferences, SMOS observations can provide effective input for analysis of soil moisture at regional scales. Moreover, it was shown that CATDS SMOS soil moisture data are better correlated with rainfall rate than GLDAS ones. |
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| Keywords: | Soil moisture SMOS GLDAS CATDS The Odra watershed Regional studies |
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