Application of New Agricultural Drought Index Based on Soil Moisture and Modified Vegetation Index Using Remote Sensing Data of SMAP and TERRA

Subject Areas : Drought in meteorology and agriculture

Aliakbar  Karamvand ¹ (Ph.D. Student, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.)
Seyed Abbas  Hosseini ² (Assistant Professor, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran .)
Ahmad  Sharafati ³ (Assistant Professor, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran)

Received: 2022-04-27 Accepted : 2022-07-12 Published : 2022-12-22

Keywords: Remote sensing, Soil moisture, Vegetation Drought Index, Agricultural Drought Index, Drought,

Abstract :

Background and Aim: There are always challenges of spatial and temporal resolution in-situ measurement methods of factors affecting drought phenomena, and the presence of human operators is required. However, due to remote sensing's ability to measure data on the entire surface of the planet with an acceptable spatial and temporal resolution, its use in controlling and observing drought has grown more than ever, and it has become a powerful tool in the hands of experts. In this study, based on two components of surface soil moisture and modified vegetation index (EVI) by applying remote sensing data, a new agricultural drought index named (SMADIN) is proposed.Method: To achieve the goal of proposing a drought index based on soil moisture, surface soil moisture data from the SMAP satellite of 5 cm depth was used. These data were validated before use against daily field measurements provided by the Iranian Meteorological Organization over a 250-day period. Validation step error was evaluated using the root mean square error method between satellite data and field measurements. Furthermore, the EVI index was calculated using data from the TERRA satellite and the MODIS sensor. Eventually, an analytical method is used to propose a drought index based on soil moisture. In order to compare the performance of this index in different weather conditions, two regions were chosen, one representing a dry climate and the other a wet climate. Then, the correlation matrix was plotted by the Pearson method for SMADIN agricultural drought index versus vegetation health index (VHI) and the results were discussed.Results: Validation showed that field data measured in land use similar to remote sensing had an average root mean square error of 0.05 .The results indicate that the new agricultural drought index correlates up to 96% with VHI in the humid climate and 98% in arid regions. In addition, a 5-year comparison of the new SMADI and VHI time series in the study area demonstrates synchrony in peaks, minimums, increases, and decreases.Conclusion: An agricultural drought index based on soil moisture is proposed in this study. We believe that, in recent years, when the lifetime of the SMAP satellite data exceeds 7 years, it is possible to use this index in future studies. Considering the possible error of SMAP and TERRA data in providing drought index, it is suggested to use this index in future studies in dry regions such as the central and southern regions of Iran.