Evaluation of GPM precipitation products and mapping soil moisture using SMAP data in the northwest of Iran

Document Type : Research Article

Authors

1 , Institute of Geophysics, University of Tehran

2 Department of Space Physics, Institute of Geophysics, University of Tehran

Abstract

Soil moisture influences the partitioning of rainfall into evapotranspiration, infiltration and runoff, hence it is an important factor for determining the magnitude of flood events. The Soil Moisture Active and Passive (SMAP) mission is a microwave all-weather sensor with cloud penetration capability it can be harnessed for inundation mapping. On the other hand, Global Precipitation Measurement (GPM) is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. The Integrated Multi-satellitE Retrievals for GPM (IMERG) products, with 0.1° × 0.1° spatial resolution and 30 min temporal resolution, are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account.
In this study, daily rainfall estimates from IMERG Early, Late, and Final runs (IMERG-E, IMERG-L and IMERG-F) are compared with daily precipitation measured by 22 synoptic rain-gauges over the northwest and western regions of Iran. Assessment is implemented for a period from April 2016 to February 2017. The assessment technique is using a contingency table that reflects the frequency of “Yes” and “No” of the satellite estimation. We have used two threshold values of 0.1 mm/day to define rain/no rain and 5.0 mm/day as moderate or higher rainfall events. The scatter plots of daily precipitation values, IMERG-E, IMERG-L and IMERG-F data against rain-gauge observations, indicate underestimation according to Bias for moderate or higher rainfall; this is more so when the precipitation threshold is increased. However, the IMERG-F shows better performance (i.e., closer to one-to-one line) in estimating moderate or higher rain. For the first threshold, all the three runs show approximately same performances; but some differences are seen at the second threshold. At this threshold, POD for IMERG-F is about 0.27 and for the two other products is about 0.14, which means larger fraction of the observed “Yes” events was correctly estimated by IMERG-F than IMERG-E and IMERG-L.
At the second part of this work, the synergistic use of satellite-based precipitation and soil moisture observations was dedicated to mapping of flood monitoring in the northwest of Iran on 14 April 2017. In this study, a value-added product was used that over-samples the SMAP volumetric soil moisture data with a spatial resolution of 40 km and posts it on a 9 km grid, SPL2SMP_E. The SMAP data maps show a pattern that is consistent with the precipitation maps; i.e., following the rainfall on 14 April, there is an increase in the saturated area and after that it begins to decay.
So together, SMAP and GPM can provide information on the surface water fluxes, an important quantity for assessing and monitoring the Earth’s fresh water resources. Therefore, integrated GPM and SMAP data can serve as a key tool for application users and emergency management to assess the extent and potential impact of flooding events among other hydrometeorological phenomena.

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References

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Iranian Journal of Geophysics
Volume 12, Issue 3
December 2018
Pages 70-86

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