فصلنامه جغرافیای طبیعی
پیاپی 55 (بهار 1401)

In recent decades, climatic variables have become more pronounced, making the flow rate sensitive to these changes. This study used climatic data of 39 synoptic stations and nine hydrometric stations in the statistical period of 1994-2015 and prospective data of 2021-2080. Maan Kendall test in MATLAB environment has been used to detect annual changes. Maan Kendall statistics, Sen's slope estimates, and coefficient variation have been used from the relevant formulas in the Excel environment. The results show that the trend of precipitation in region 1, temperature in region 7, and evapotranspiration in basin eight are increasing, and the most changes in flow sensitivity analysis to precipitation changes in region 8, the temperature in regions 3 and 8, and the results of sensitivity analysis to evapotranspiration parameter It is different. The temperature in the three scenarios studied had a significant upward trend, and the changes in precipitation were different in different regions, and the most changes in the decrease in precipitation were in regions 1 and 4.

Drought is one of the climatic hazards that is of special importance. One of the problems of drought studies is the over-normal rainfall along with a relatively long period of drought. This divert SPI index; To the extent that sometimes, despite the occurrence of drought, the index incorrectly shows that period as normal or even wet and leads to incorrect decisions in drought management plans. In this study, SPI drought index in 8 provinces with 27 synoptic stations located in the center, south and east of Iran with De Martonne hyper-arid climate in a period of 34 years (1985-2019) for a period of twelve months was calculated and analyzed. In this study, for the first time, the EP-SPI hybrid index is presented in which effective precipitation data was used as program input. Thus, the effect of older rainfall is reduced and the index provides a better estimate of drought. The results of statistical analysis of EP-SPI versus SPI values show a significant correlation at the level of 5%. 83% of the events with a difference of more than one in October to March and the highest difference between the two methods is equivalent to four levels of drought index displacement from wet Severe to moderate drought. In this study, it was found that 9.3% of the events of the 12-month drought remained hidden from the SPI index. Therefore, it can be said that the efficiency of EP-SPI method for detecting latent droughts in a period of twelve months is confirmed.

Decreasing of precipitation and Increasing of temperature, leads to extreme climate events such as drought which drastically impact on agricultural. Knowledge about the timing, severity and extent of drought can aid planning and decision-making. Drought indices derived from in-situ meteorological data have coarse spatial and temporal resolutions. Thus, obtaining a real-time drought condition over a large area is difficult. Therefore, drought indices which is derived from remote-sensing data, has been widely used for drought monitoring..In this study, Vegetation Drought Index (VDI) was evaluated in Sistan & Balouchestan Province To do this, Terra Moderate Resolution Imaging Spectroradiometer MODIS (MOD02HKM and MOD11A1 ), Standard Precipitation Index (SPI) and monthly precipitation data GLDAS from 2000 to 2018 were utilized to evaluate VDI.Accuracy of the Drought spatial distribution maps based on Pearson correlation coefficient was used data. Results indicate high significant correlation rate in the study area. Thus VDI, has the potential to monitor agricultural drought in the case of study and the drought indices based on remote sensing data could well use in drought early warning systems.

The knowledge about spatial relationships of vegetation with sediment yield (S.Y) in watersheds is essential for optimal controlling and managing of water and soil resources. The purpose of this study was to recognize and determine the relationship between vegetation cover and annual S.Y of Sabalan catchments, N.W Iran. In this regard, the possibility of presentation of regional S.Y estimation models based on correlation and regression analysis were considered. Independent variables include average, minimum and maximum NDVI (Normalized Differential Vegetation Index), extracted through the processing of Landsa.t 8 satellite imagery in the ENVI environment. The dependent variable, which was the annual S.Y, was obtained through calculations on sediment load data of 10 sample hydrometric stations. Results of correlation test showed that there was a strong and significant relationship between the average NDVI and the annual S.Y in the catchments (r = -0/758). This inverse relationship emphasizes the importance and apparent role of vegetation in reducing sediment production and transporting in the region. Moreover, the results of regression tests showed that is possible to present the regional estimation models regards to annual S.Y by fitting linear, quadratic and power functions. In this regard, the quadratic model has the highest performance and explain 75% of the annual S.Y variance. The linear relationship was also able to explain 57% of the annual sedimentary variance.

Future research involves a set of endeavors that visualize potential futures and plan for them by searching for resources, patterns, and factors of change or stability. Future research reflects how the reality of "tomorrow" is born from the change (or stability) of "today." The increasing trend of floods in recent years indicates that most parts of the country are exposed to destructive floods and the extent of flood damage and loss of life and property has increased. The purpose of this study was to predict the future of floods in Tehran using the svm vector support machine algorithm. The research method is spatial analysis. The data used were prepared in the form of information layers. The criteria used were altitude, slope, direction of slope, land use, distance from the road, distance from the waterway, geology. The IGR index was obtained for 7 effective factors selected for the occurrence of surface floods in the study area to evaluate the predictive ability of the model. The results showed that the weight of geological factors, altitude, land use, slope, slope direction, distance from the road, distance from the river were 0.029, 0.026, 0.025, 0.019, 0.015, 0.009, 0.008, respectively, with the highest values. 0.029 was assigned to the geological factor and 0.008 to the distance from the river. The final zoning map showed that the high susceptibility class to flooding was in the range of 40.63% and the very low sensitivity class was 3.55% in the lowest area.

In this study, in order to identify the most important evidence of climate change in the southern coast of the Caspian Sea, temperature and precipitation changes were studied using 20 indices during 1968-2017. The results showed that the intensity of precipitation significantly increased, but the number of days with precipitation significantly decreased. Despite the increase in rainfall intensity, the total annual rainfall has decreased, because of the number of rainy days and length of wet periods significantly decreased. Seasonally, spring rainfall decreased and summer rainfall increased. All the extreme temperature indices showed significant trends. On average, the increasing trends of the minimum annual temperatures and maximum annual temperature were 0.51 ° C and 0.31 ° C in per decade, respectively. The frequency of hot days and hot nights significantly increase with an increase rate of 1.5% and 2.7% per decade, respectively. Also, the frequency of cold days and cold nights significantly fell with a decrease rate of 1.1% and 1.3% per decades, respectively. In general, the heating trend of the nights was stronger than during the days. The warm spell duration index showed a clear increase, with a rate of 2.6 d per decade. Comparison of the results of this study with the findings of global studies showed that the increasing trend of temperature in the southern Caspian coast is in line with the trends observed in global studies, but the decreasing trend of precipitation in the Caspian region is opposite to the increasing trend of global precipitation.

Precipitation is important climatic varibles which is directly involved the hydrological cycle. Iran is considered the most arid and semi – arid regions of the world due to lack rainfall and their inappropriate distribution, which has always faced water shortage important limitations of natural resources.Therefore, the present study was conducted with the aim of extracting scale behavior and identifying (long – term and short – term) precipitation memory of two Karkheh and Dez catchment. For this purpose, Precipitation data of two Karkheh and Dez catchment were used over a period of 60 years (1959 – 2019). The results showed that the stations both areas have 2 rainfall regimes. In the study precipitation regimes all stations, two basins were identified. The small – scale precipitation regime has a long – term memory and a stable time series. However the large – scale precipitation regimes has a short – term memory and its time series is static except Doab and Darreh Takht station. both precipitation regimes show completely different scale behavior. the relationship between precipitation scale behavior and topography of the study area was calculated using pearson correlation test. The results show that there is no significant relationship between Karkheh basin both precipitation regimes. but in Dez basin, there is a significant correlation the small – scale precipitation regime, but there is no significant correlation the large – scale precipitation regime. This can be due to the conflicting and heterogeneous topographic situation in different parts of the region in Karkheh

Climate change is one of the greatest challenges facing humanity in the 21st century. Therefore, prediction of climate change is very important to predict the future situation and to consider the necessary measures to adjust and adapt to climate change. Therefore, in this study, climate change was predicted in the Dez watershed. For this purpose, the data of two global models HadGEM2 and CanESM2 were used under three scenarios RCP2.6, RCP4.5 and RCP8.5 and the application of two downscaling models of LARS-WG and SDSM and the climate changes in the next three periods compared to the base period (1989-2018) were examined. The results showed that both downscaling models have good accuracy in simulating climate change in the study watershed. The results of prediction the studied models also showed that in the future periods the amount of precipitation in the watershed will change between -6.3 to 15.7% compared to the base period. The most decreasing and increasing changes will be related to the eastern and southwestern areas of the watershed, respectively. Also, the maximum temperature of the watershed will fluctuate between 1.3 to 3.9 oC and the minimum temperature will fluctuate between 1.5 to 3.5 oC. The highest and lowest changes will be related to the southeastern and northwestern areas of the watershed, respectively. Therefore, due to the increase in temperature and precipitation, as well as the mountainous nature of the watershed under study, it is necessary to consider flood control and containment and management strategies.