Location: Hydrology and Remote Sensing LaboratoryTitle: Evaluation of remotely-sensed and model-based soil moisture products according to different soil type, vegetation cover and climate regime using station-based observations over Turkey
|BULUT, B. - Middle East Technical University|
|TUGRUL, YILMAZ,M. - Middle East Technical University|
|AFSHAR, M.H. - Middle East Technical University|
|UNAL, SORMA,A. - Middle East Technical University|
|YUCEL, I. - Middle East Technical University|
|SIMEK, O. - Collaborator|
Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2019
Publication Date: 9/1/2019
Citation: Bulut, B., Tugrul, Y., Afshar, M., Unal, S., Yucel, I., Cosh, M.H., Simek, O. 2019. Evaluation of remotely-sensed and model-based soil moisture products according to different soil type, vegetation cover and climate regime using station-based observations over Turkey. Remote Sensing. 11(16):1875. https://doi.org/10.3390/rs11161875.
Interpretive Summary: Meso-scale soil moisture networks are useful for monitoring hydrologic concerns on a national scale. These networks in combination with remote sensing satellites can provide a detailed soil moisture record useful for many applications, but verification of remote sensing products is required. In Turkey, a national scale network is used to validate several soil moisture products for the first time in this unique landscape. There were high quality error statistics for most of the products, with the modeled products performing the best with a rescaling method. This is useful for meteorologists and hydrologists within the eastern Mediterranean region for understanding local weather patterns as well as water dynamics.
Technical Abstract: Soil moisture status in Turkey is a valuable variable for many hydrological applications, but in situ observations are only able to provide a small amount of information spatially. Remotely sensed- and model-based soil moisture products provide soil moisture status with larger area coverage on a continuing basis. This study evaluates the performance of remotely sensed- and model-based soil moisture products, including: the Advanced Scatterometer (ASCAT), Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E), the European Space Agency Climate Change Initiative (ESA-CCI), Antecedent precipitation index (API), and Global Land Data Assimilation System (GLDAS-NOAH). These soil moisture products are evaluated between 2008 and 2011 against the calibrated station-based soil moisture observations collected by the General Directorate of Meteorology of Turkey. The calibration of soil moisture observing sensors with respect to the soil type, correction of the soil moisture for the soil temperature, and the quality control of the collected measurements are performed prior to the evaluation of the products. Evaluation of remotely sensed- and model-based soil moisture products is performed considering different characteristics of the time series (i.e., seasonality and anomaly components) and the study region (i.e., soil type, vegetation cover, soil wetness and climate regime). The systematic bias between soil moisture products and in situ measurements is eliminated by using a linear rescaling method. Correlations between the soil moisture products and the in situ observations are varying between 0.57 and 0.87, while the unbiased root mean square errors of the products versus the in situ observations are varying between 0.028 and 0.043. Overall, results show that NOAH and ESA-CCI soil moisture products are performing better than other model- and remotely sensed- based soil moisture products, while these results are valid for the entire study period and the region under all soil types and climate regimes.