Document Type : Research Paper
Authors
Abstract
Agricultural drought occurs when soil moisture is less than that required for the optimized production and damages crop yield. Drought indexes are used for monitoring purposes and in some of these indicators rainfall data are used. But, agricultural droughts indexes use soil moisture data. Among the most important drought indexes that use soil moisture as input parameter, soil moisture drought index (SMDI) can be noted. Generally, mathematical models are used for soil moisture estimation. The objective of this study was to estimate soil moisture using AquaCrop model and to calculate SMDI with this estimation and compare it with the rainfall-based drought indexes such as PNI, DI, SPI and CZI, using Qazvin synoptic station data of 1982-2008. The results of soil moisture estimation using AquaCrop showed that monthly changes in soil moisture at 5 cm depth were very strong. With increasing depth, soil moisture changes were less and remained constant after 40 cm of depth. Average values of SMDI, PNI, DI, SPI and CZI were, respectively, 0.41.2, 10026.2, 0.042.6, 0.01.0, and 0.01.0. Based on SMDI, the wettest year was 1994 while the driest years were 1997, 1999 and 2008. But, based on other indexes, the wettest and driest years were 1982 and 2008. The main point for SMDI is that, in addition to the current season soil moisture conditions, the index uses soil moisture conditions of the previous year to calculate SMDI. According to our results, SMDI had low coefficient of determination with the other drought indexes, rain, and evaporation.
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