This research was carried out to determine whether the changes in precipitation and temperature trend in Iran are attributed to climate change or natural climate variability. The trend and its magnitude with the climatic extremes indices considered by Expert Team on Climate Change Detection and Indices were analysed based on the quality-controlled daily data of 37 meteorological stations by nonparametric Mann-Kendall test and Sen's slope method from 1966 to 2015. Results indicated that TXx, TNn, the average maximum, and minimum temperature indices have increased with a significant trend in most parts of Iran. The minimum temperatures (TNn and annual Tmin) were increased more rapidly than maximum temperatures (TXx and annual Tmax) and rising temperatures have occurred in northern latitude and western regions more than elsewhere. As a result, the temperature increase leads to changes in seasons and season length; and reduces the growing season of a
Drought is one of the most important threats for agricultural production in the world, espatially in Iran. This phenomenon has started with reduction of precipitations that lead to a decrease in soil moisture and an increase in soil surface temperature, which affect the vegetation growth. The purpose of this study was to investigate droughts in the Jaz_Murian basin by VHI, VCI, TCI and SPI indices using MODIS satellite imagery and meteorological data. For this purpose, the LST products (MOD11A1) and vegetation products (MOD13A1) were selected from 2000 to 2018 at the same time (the first week of March). The VHI and VCI maps were produced and the drought occurrences with critical and very severe classes were identified. Also, the SPI index was calculated using precipitation data in Kahnooj synoptic meteorological station. According to the VHI index, the results showed that over 75% of the study area was classified as the severe, very severe and extreme classes of drought and has suffered from
Recharge is considered a key parameter in groundwater models for sustainable management of aquifers, which is influenced by factors such as land use, soil, weather, etc. The present study was conducted to couple WetSpass-M and MODFLOW models for evaluating Neyshabour aquifer condition in steady and transient states. To this aim, the simulated recharge by the WetSpass-M model was applied as an input of MODFLOW to assess the groundwater balance. The hydrodynamic coefficients were determined by calibrating the model, evaluating and the model sensitivity to the hydraulic conductivity coefficient, specific yield (Sy), and recharge. The results indicated that the annual average of surface runoff, actual evapotranspiration, interception, and recharge during 1991–2017 equaled 18, 36, 7.6, and 42.6% of the average annual precipitation in the basin, respectively, with the simulated water balance error 4.2%. The average annual recharge of the basin varies between 0-257.41 mm with an average of 105.25 mm/y. Accordingly, the maximum and minimum average monthly recharge occurs during March and July, respectively. The appropriate matching of the simulated and observed water levels and obtaining the suitable values of RMSE, R2, ME, and MAE evaluation criteria in steady and transient states indicate the adequate accuracy of the WetSpass-M model in estimating the recharge and success of the couple two models. Based on the simulated groundwater balance, the aquifer faces a deficit of 421.3 MCM per year and 97.41 cm in the annual groundwater level. The model displayed more sensitivity to the hydraulic conductivity coefficient compared to other parameters.
The motivation of this research is the continuation and intensification of drought effects on various socio-economic sectors and the observation of few studies and no coordinated efforts to provide a compatible framework for drought risk management in different economic sectors and population groups of the study region. Present research was carried out to assess the vulnerability and population exposed to drought in Khorasan Razavi province. Meteorological data sets for the years 1950-2020, drought indices including Palmer self-calibration (scPDSI), standardized precipitation (SPI), standardized precipitation evapotranspiration (SPEI), population and livestock density indicators, agricultural lands, water stress, socio-economic and infrastructural factors have been used. Results indicate that dry and wet periods were estimated more intense by SPEI in all studied stations, also a significant difference was observed between the results of the SPI and SPEI indices in determining the long dry and wet periods. The highest variation between the occurrence of dry and wet periods was estimated using the SPEI, which could be related to seasonal fluctuations of temperature and computational evapotranspiration. Although no significant correlation was observed between used indices to identify the number of wet months, however, a significant positive correlation exists between the numbers of dry months estimated by those. Drought risk analysis demonstrated that the central and southern parts of the province are exposed to very severe drought, while the northern and northeastern parts of the area are more inclined to severe drought. The highest class of drought exposure is observed in the southern, central, and eastern regions of the province so they represent the high-risk category of drought.
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