فهرست مطالب mohammad amin asadi

Drought monitoring using appropriate drought indices is of importance in water resources management, especially in arid and semi-arid regions. Therefore, choosing the suitable drought index and calculating the desired drought index appropriately is of considerable importance in the study of drought. This study is aimed to determine the appropriate statistical distribution to calculate RDI drought index in arid and semi-arid regions of Central Iran. For this purpose, 16 synoptic stations in Central Iran were selected. To calculate RDI, precipitation and potential evapotranspiration values are required. The FAO-Penman-Monteith method was used to calculate potential evapotranspiration. To select the most appropriate statistical distribution, 17 statistical distributions were used. RDI for each synoptic station was calculated annually by fitting to each of the 17 distributions, separately. Then, based on the AIC and BIC criteria, the best statistical distribution was selected to calculate RDI for each station. While based on the literature, it is recommended to calculate RDI by fitting the data to one of the Gamma or log Normal distributions, the results showed that in most of the studied stations, the log Normal and Gamma distributions are not the most appropriate distribution. However, according to the results, Gamma distribution was one of the top 6 distributions in all the studied stations. The results also showed that the difference of RDI values ​​calculated based on different distributions in dry and wet years are relatively significant, which shows the importance of choosing the appropriate statistical distribution. The fit of the studied distributions to the precipitation data at different stations showed that the Nakagami distribution presents the best performance. In case of potential evapotranspiration, different distributions provided the best fit at different stations.

Drought is a natural hazardous phenomenon occurring in all climate types. However, it affects arid and semiarid regions more intensely than other areas. It also severely affects both the quantity and quality of water resources in arid zones. Moreover, land-use changes and urban and agricultural development also adversely influence water resources in these regions, especially groundwater resources.The extraction of a significant portion of drinking and agricultural water from groundwater resources has led to a sharp decline in groundwater storage in Iranchr('39')s arid and semiarid regions. Furthermore, as mentioned before, frequent droughts and land-use changes have affected these resources. This study, therefore, sought to investigate the effects of meteorological drought and land-use changes on groundwater quantity and quality in Darab plain, Fars Province, Iran.

Darab Plain is located in the south of Iran. The water supply in this plain is highly dependent on groundwater. The mean annual rainfall is 275 mm, and the mean annual temperature is 22 0C. In this study, data regarding precipitation, groundwater level, and salinity were used to estimate SPI (Standardize Precipitation Index), GRI (Groundwater Resources Index), and SECI (Standardized Electrical Conductivity Index). SPI is considered as the indicator of meteorological droughts. GRI quantifies changes in groundwater levels as a standardized index. SECI is applied to estimate any potential shifts in groundwater quality. Land-use maps of the basin for 2001, 2009, and 2017 were prepared using satellite imagery. Moreover, Landsat TM, ETM+, and OLI sensors were used. It should also be noted that land-use maps were created using the Supervised Classification method (Maximum likelihood algorithm). The produced maps included five classes: urban area, farmlands, gardens, rangelands, and bare lands.

SPI results showed normal classes for most of the years throughout the study period (-0/99 to +0/99). However, the trend line indicated an apparent decreasing trend for SPI during the period. Therefore, it could be concluded that the region is experiencing more droughts. A study of groundwater level changes suggested a continuous reduction of 36 m for the entire study period. While the comparison of SPI and GRI showed a general decreasing trend for GRI, it could be seen clearly that SPI changes caused GRI shifts. Moreover, droughts accelerate GRI reduction, and SPI growth either reduces GRI decreases or increases it slightly.On the other hand, SECI results indicated the salinity growth and quality reduction in the region. During the study period, the plain experienced a 293.6 µmho/cm increase in salinity. Furthermore, the comparison of GRI and SECI showed that any reduction in groundwater level would result in more saline. The comparison of land-use maps during the three years (2001, 2009, and 2017) also proved that agricultural uses increased by only 0.26% in 2009 compared with 2001. However, in 2017 compared with 2009, such uses decreased by 1.62%.The relationships between SPI and land-use changes with GRI and SECI were also investigated, indicating that droughts and land-use changes directly affect the quantity and quality of groundwater in Darab Plain.

Climate change has affected many parts of the world, changing drought characteristics in many regions. Therefore, the subsequent changes in water resources could be considerable. Furthermore, water resources are under pressure for population growth and land-use change. In this study, the collected data was divided into three 8-years periods (1993-2001, 2002-2009, 2010-2017), and the averages of SPI, GRI, SECI, and land-use were calculated for the three periods. The results showed that the increase in the severity of drought and the rise of the agricultural lands in the second period compared to the first one caused a decrease in water quantity (GRI decrease) and quality (SECI increase). However, a decrease in the severity of drought and the fall of the agricultural land-use in the third period compared to the second one lowered the rate of groundwater level decline (compared to the rate of GRI decreasing in the second period). In the third period, SECI increased (less quality) in response to the GRI decrease. The results showed that groundwater resources in Darab Plain were strongly dependent on both drought and land-use changes. The groundwater quality in the region was also directly affected by changes in groundwater level.

In this research, water balance components in Mehrgerd watershed was simulated using the SWAT hydrological model. The main purpose of this research is the model efficiency test and its ability to use as a water balance simulator in the Mehrgerd watershed. For this purpose, the necessary data such as precipitation, minimum and maximum temperature, relative humidity, sunshine hours, daily wind speed, monthly discharge and as well as required maps including digital elevation model (DEM), land use and soil were provided. and entered to the SWAT model. A sensitivity analysis was done using the )OAT( method to determine the sensitive parameters. The calibration and validation of the model were done by Sufi-2 algorithm. The calibration process was conducted for the period 2004 to 2012 while the validation process was from 2013 to 2016. Monthly runoff simulation accuracy was calculated using the determination coefficient (R²) and Nash Sutcliffe (NSE) index for calibration and validation 0.73, 0.69 and 0.71, 0.58, respectively. The results showed that 64 % of precipitation enters the atmosphere through evapotranspiration. Approximately, 31% of it goes to the waterway as the surface runoff and lateral flow. Finally, from 6 % of water entered into the soil layers, close to 1 % of it joins to the underground water. The results of this research show the acceptable performance of the SWAT model to simulate the water balance in Mehrgerd watershed. Therefore, this model can be used for water resources planning in this study area.

In water systems, precipitation is considered as input and evaporation as the output of the system. Water availability can be estemated from the relationship between these two factors. Therefore, evapotranspiration is the most important factor after precipitation in hydrological cycle. Evapotranspiration is influenced by climatic parameters such as temperature, wind, humidity and sunshine hours. In this research, changes in PET and effective climatic parameters, influencing on PET changes including temperature, wind, humidity, and solar radiation were investigated. For this purpose, PET in 14 weather stations of Yazd province were calculated using the FAO-Penman-Monteith method. Due to the lack of sunshine hours data in some stations, regeneration of the incomplete data was done by using regression method. Due to the lack of wind speed data at some stations, their reconstruction by using data from other stations was done by applying three methods of Inverse Distance Weighted, Kriging and Cokriging. After calculating potential evapotranspiration, PET data were zoned and their monthly and annual trends tested by Mann-Kendall test. Despite occurrence of climate change and increasing of temperature in 13 stations out of the 14 stations, it is expected an increase in potential evapotranspiration in past few decades, while, there is a decreasing trend in PET. Investigating on the effective parameters in potential evapotranspiration showed that wind speed has declined in the last few decades, and despite of an increase in temperature, potential evapotranspiration rate reduces in 64.3% of the stations. General trend of evapotranspiration was -0.86 in this period, which indicates a decrease in evapotranspiration in the Yazd province.

Potential evapotranspiration (PET) is one of important hydrological cycle parameters which its prediction is useful for water resources planning in the future, changes in the crop water requirements, and drought forecasting. In the case of PET long term prediction, global climate models (GCMs) based on the emission scenarios and then downscaling the outputs are used. For short term forecasting, statistical models are suggested. PET is a nonlinear phenomenon which is affected by temperature, humidity, sunshine and wind speed. In this study, PET was calculated by FAO-Penman-Monteith model for Yazd synoptic satiation during 1965-2010. Recently, NARX has widely used to predict hydrological and climatic parameters. In this research, performance of NARX for PET forecasting was analyzed. NARX is a nonlinear model which in addition to the target parameter, takes exogenous variables that affect target variable into account. Different nonlinear functions can be selected. In this research, a feedforward neural network because of its high ability in nonlinear processes modeling was chosen. The network was trained by GDX algorithm. Then, PET was predicted using nonlinear autoregressive model (NAR) which its input is just PET. Next, the results of NARX and NAR were compared. The results showed adding exogenous variables increases the accuracy of PET prediction, remarkably. R2 correlation coefficient between one month observed and predicted PET by NAR and NARX for 2002 to 2010 was 0.72 and 0.92, respectively.