عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Drought as a recurring extreme climate event, can be defined from various perspective including meteorological, hydrological, agricultural and socio-economical. Drought is a recent feature of Iran climate. Many areas of Iran experience drought from time to time. In western region of this country, the 1998-2001 drought was a notoriously high impact event. Impacts include crop failure and the vulnerability of approximately 37 million inhabitants (over half of the population of Iran) to food and water shortage (Raziei et al. 2009, UN, 2001, Barlow et al., 2001). By the year 2001, crop failure resulting in US$2.6 billion worth of losses (Shahabfar and Eitzinger 2008). During 2008 drought event, 4 million hectares of rainfed and 2.7 million hectares of irrigated areas had been completely destroyed, leaving many farmers in financial crisis (USDA, 2008).
Drought indices commonly used to monitor, quantify and compare drought severity, duration and spatial coverage over regions with different climatic and hydrologic regimes. Recently a new drought index, Reconnaissance Drought Index, has been formulated based on precipitation and Evapotranspiration. Since there are different ETo formulations, it is especially important to understand how sensitive this index is to choice of ETo method. Therefore, the objective of this paper is to assess the impact of some common ETo methods with minimum input requirements on estimation of RDI in different climatic zones of Iran.
Materials and Methods
1. Climate data
For our analysis, we selected 4 meteorological stations with diverse climates, varying from arid to very humid climate. These stations including Ahvaz, Keram, Shahrkord and Bandar Anzali. The data used for this study were obtained from I.R of Iran meteorological organization (IRIMO) including the long term monthly average values for precipitation (mm), maximum, minimum and mean air temperature (ᵒC), maximum and minimum relative humidity (%), sunshine duration (h), wind speed at 2 m (ms-1) which used to compute reference evapotranspiration by five selected ETo methods.
2. Drought severity assessment through RDI
The RDI is expressed in three forms: the initial value ( ), normalized RDI (RDIn), and standardized RDI (RDIst). The initial value ( ) of RDI is presented in an aggregated form using a monthly timestep and is usually calculated for i-th year in a time basis of k of consecutive months using following equation:
Where pij and EToij are precipitation and ETo of the j-th month of the i-th year and N is the total number of years of the available data. The normalized RDI (RDIn) is estimated as follows:
In which is the arithmetic mean of values. The probability function of gamma distribution is defined as:
Where is a shape factor, >0 is a scale factor, and is the gamma function. Parameters and of the gamma function are estimated for each time scale (k) and for each location. The estimated parameters are then used to find the cumulative probability of for a given year for the location under study.
3. Reference Evapotranspiration Equations
For purpose of this paper, we selected the most commonly used ETo methods including Blaney-Criddle (Blaney-Criddle, 1950), Thornthwaite (Thornthwaite, 1948), Hargreaves (Hargreaves & Samani, 1985), Penman-Montieth with Hargreaves radiation term (Allen et al., 1998) and FAO-56 Penman-Montieth (Allen et al., 1998). In this study, the latest method was used as the reference method.
4. Statistical indicators
For each station, Mean Bias Error (MBE) and Root Mean Square Error (RMSE) were calculated to compare the impact of the different ETo methods on RDI values. The smaller RMSE and MBE indicate the better model's performance.
The values of ETo estimations obtained with four methods were compared with those calculated by the FAO56 P-M equation. In Bandar Anzali, the ETo values estimated by Blaney-Criddle equation were the highest among selected methods with a rather significant difference of about 500 mm in mean values. In Sharekord and Kerman, the Thorentwaite equation estimated the lower values, wherease in Ahvaz the highest ones were estimated by this method.
In the next step, assuming k is equal to 12, the RDIst series were calculated using the ETo values estimated by the methods under study. The comparison over the 39 last years revealed that the RDIst values calculated by the ETo methods under study are very close to those estimated by ETo reference method. In the other hand, in the most cases, the differences between RDI values were relatively small and do not exceed any drought severity threshold.
Since 3, 6, 9, 12, 24 or 48 months are the typical time scales for precipitation deficits to affect the five type of usable water sources (soil moisture, ground water, snowpack, steamflow and reservoir storage),the impact of various ETo methods on the severity of drought calculated by RDIst for shorter time scale than a year were also discussed. The analysis and comparisons are performed for the 6-month and 3-month time scales. The results of the comparison of the RDIst values calculated by four ETo methods against those obtained using FAO56 P-M suggested that there are reasonably good agreements between the 6-monthly RDIst series in all stations. The RMSE values were less than 0.51 and MBE values which can be practically considered as zeros. In the case of the four 3-month time scale, the most accurate results in Kerman and Sharekourd stations are provided by PMT and HS equations in relation to the other models.
The RDI is an important and useful tool for indicating meteorological drought. However, prior to apply this index, its sensitivity to ETo methods must be identified. This paper concludes that the differences between RDIst calculated by the selected ETo equations and those computed by reference method have no effects on the characterizations of drought severity class through RDIst series.The PMT and HS equations performed relatively better than the other models in semi arid stations (Kerman and Sharekourd) Therefore even if minimum data are available (P, T), the severity of drought can be reliably assessed by this index. These results are similar to those reported by Vangelis et al. (2013) for two stations in Greece.