leila jalali; J. Bazrafshan; A.R. Tavakoli
Abstract
Introduction: There have been several indices for agricultural drought monitoring such as Palmer Drought Severity Index (PDSI), Crop Moisture Index (CMI) and Reconnaissance Drought Index (RDI). These indices model the general conditions of soil moisture as a function of climatic parameters such as temperature ...
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Introduction: There have been several indices for agricultural drought monitoring such as Palmer Drought Severity Index (PDSI), Crop Moisture Index (CMI) and Reconnaissance Drought Index (RDI). These indices model the general conditions of soil moisture as a function of climatic parameters such as temperature and rainfall and they are not appropriate to any specific crop. Crop- Specific Drought Index (CSDI) is among few indices which directly take into account evapotranspiration for drought monitoring. This index is defined based on the ratio of actual evapotranspiration (ETa) to potential evapotranspiration (ETp). Literature review of agricultural drought monitoring in Iran reveals that was mainly used Reconnaissance Drought Index (RDI) and in some cases Drought Severity Index Palmer (PDSI) which have less associated with the growth or performance of the specific crop or not. In this paper, a Crop Specific Drought Index (CSDI) model was evaluated for rain-fed wheat in a cold-temperate climate. Then, it’s correlation with RDI was assessed.
Materials and Methods: In this study, using 9 years of data of meteorology, soil, and crop yield and phenology, a CSDI model has been calibrated and validated for rain-fed wheat. A two-layer model of daily soil water balance was used to CSDI calculation. The first layer is the current root growth zone which its depth increases with time. The second layer is between the first layer and maximum depth of root growth which its depth decreases by root growth and the thickness of this layer becomes zero when the root growth is Maximum. Actual daily Evapotranspiration (ETa) was calculated based on two-layer model of daily soil water balance. For this, we used the moisture content of the first layer (active), potential evapotranspiration and daily rainfall values. The statistical indices of error analysis like RMSE, MAE and Index of Agreement was used for assessment of CSDI model. Then, to investigate the correlation possibility of crop specific drought severity, Reconnaissance Drought Index (RDI) was used which is based on two variables of potential evapotranspiration and precipitation. In fact, RDI considers the precipitation as a factor of moisture input and the potential evapotranspiration as a factor of moisture exhaust.
Results Discussion: At Kermanshah station high coefficient of determination (0.95), relatively high index of agreement (0.747), and low error values (RMSE =0. 098 and MAE =0. 068) was obtained. Sensitivity coefficients during vegetative and productivity stages were obtained 1.31 and -0.0542, respectively. As a result, crop yield at vegetative stage severely affected by aridity stress while at productivity stage there was no sensitivity. In fact, water demand supply is vital at vegetative stage .Range of RDI at Kermanshah station was between 1.13 to -2.59. This threshold is the condition between "moderately wet" and "extreme drought". Correlation between the two index was started from March (R2 =0. 467) and persisted to September (R2 =0. 717). But the highest coefficients of determination were related to July to august (0. 738). Although CSDI didn’t affect by drought stress during October to February, it affected by moisture of March onward. RDI incorporating precipitation and potential evapotranspiration is one of the most recent developments for the assessment of drought severity through drought indices. That is why this index is chosen to investigate the relationship with CSDI. Actually, both indices get evapotranspiration factor in the agricultural drought monitoring. Based on the results, there is a good correlation between two indices. Since the CSDI is relay on ETa to ETp ratio and RDI is based on the P/ ETp ratio, it can be concluded that there is a possible to replacement of ETa with rainfall (R) in the CSDI equation.
Conclusion: Many indices and indicators are available to assist in the quantitative assessment of drought severity, and these should be evaluated carefully for their application to each region or location and sector. This paper presents a CSDI model which compared with RDI. Based on the results of this analysis, CSDI model was performed well in high values of coefficients of determination and Index of Agreement, and low values of errors. Therefore, the CSDI seems to be a reliable index to assess agricultural drought. Furthermore, it is observed a reliable relation between CSDI and RDI during crop growth period. Due to good correlation of CSDI and RDI, it can be proposed to replacement of rainfall (R) instead of ETp in the CSDI equation.
