فصلنامه مطالعات جغرافیایی مناطق خشک
پیاپی 44 (تابستان 1400)

Droughts are extreme phenomena that are described based on the characteristics of continuity in time and according to their spatial effects and can occur in any climatic situation. Recognition and behavior of droughts, which are closely and directly related to water resources management, are of particular importance. The main purpose of this study is to assess the risk of drought using Copula functions in the bivariate analysis of drought in the east of the country. For this purpose, drought characteristics including intensity and duration were extracted using modify standardized precipitation index (SPImod). To assess the risk of drought and analyze its two variables, the performance of nine copula functions of Clayton, Ali-Michael-Haq, Farli-Gumble-Morgenstern, Frank, Gumble, Gumble-Hoggard, Plackett, Filip-Gumble and Joe fits the intensity data and Drought duration was tested. Akaike criteria, maximum likelihood, and Nash-Sutcliffe coefficient were used to identify the superior joint function. The results showed that gamma and exponential distribution functions were identified as superior margin distribution functions for the variables of intensity and duration of drought, respectively, and the Nash-Sutcliffe coefficient ranged from 0.76 to 0.99, and the mean square error ranged from 0.007 to0 034., to determine the superior copula function, it was obtained that the copula function of the superior function was known to create a bivariate distribution in the study area. Also, the results of drought risk assessment using the joint return period showed that the highest risk is related to Bojnourd, Sabzevar, Torbat Heydariyeh, and Mashhad stations, so that Sabzevar station was dry about 53% of the total months during the statistical period and for Bojnourd station is about 55%. The results of risk analysis based on return period and copula functions can provide useful information to planners of water resources, environmental issues, farmers.

Increasing the population of cities and the growth and development of urban planning on the one hand and climate change on the other hand has affected the thermal balance of cities and has created thermal islands, so attention to the impact of design on the thermal comfort of urban spaces has become important. The study of the thermal performance of yards as common spaces between urban scale and architecture has been evaluated differently, but relatively limited knowledge about the micro-climatic behavior of these spaces is available. This study seeks to assess the thermal comfort conditions of traditional houses of the Qajar period in Isfahan. Therefore, 10 houses of the Qajar period in the city of Isfahan have been selected and by the ENVI-met 4 software, which is designed to simulate and measure the micro-climatic conditions of the city, study the changes of climatic parameters and evaluation of thermal comfort conditions on the first day of July based on PET index. The results show that the temperature in the studied central yards compared to the neighboring open urban spaces decreased by an average of 0.7-1.7 ° C, the relative humidity increased by 1-1.8% and the wind speed decreased by 1.5-2 m / s. The average mean radiant temperature for the studied houses was between 35.7-55.7 and there is a high correlation between the average mean radiant temperature and PET index. Also, according to the PET index, the thermal comfort conditions of the studied houses are between moderate and strong heat stress.

The resiliency approach has the potential to pay attention to the sustainability paradigm in the area of planning in different dimensions and sectors as a new shadow approach to local policies with a global approach to regional development. However, the concept of resilience has emerged over the past years as an emerging approach to environmental planning and management literature. In this research, with the focus of planning in the explanation of the resilience, the main objective is to describe the spatial pattern of study region. Therefore, the eastern part of Lake Urmia (in the form of political districts of 8 counties) was selected as the study area. The research method is analytical and utilizes quantitative GIS-based methods and spatial analysis tools as well as geospatial techniques. After presenting regional resilience status in three dimensions of social resilience, infrastructures and building strength in rural areas, finally the overall regional resilience index (using 19 criteria) were presented.The findings of this study showed that the distribution pattern of the general resonance index using Moran statistics is a cluster pattern type. The value of the Moran index in this analysis is 282/0 and since its value is positive and close to one, it can be concluded that the data have spatially correlated self-correlation. Also, based on the high standard Z score and the very small amount of P-value, it is possible to reject the hypothesis of the lack of self-correlation between the distributions of vibration in the studied area.

Resiliency models emphasize on the capabilities and methods by which people and societies deal with crises and calamities. With the aim of explaining city resiliency, this study investigates suitable approaches used to combat biological disasters including Covid-19 pandemic. In terms of goal, this study is of applied type and in terms of type of research it is a descriptive- analytical study. By making use of questionnaire and interview, the data were identified and categorized. Finally, upon completion of theme analysis process using ground theory approach, 40 main themes were obtained. The researchers designated the themes with distinguished names in the form of 12 general concepts and 40 sub-sets and these indices were selected for factorial analysis: physical-environmental, health infrastructure, managerial, cultural & social conditions, institutional conditions, economic conditions, public knowledge, social value creation, preventive performance, social health enhancement and facilitation of health services. The relationships among variable used in the paradigm and conceptual model of this study are presented and the data were analyzed using SPSS 22 & LISREL software. Based on our findings, the relationship between cultural-social conditions and resiliency (0.88) imposes the highest impact and the less effective relationship relates to that between managerial index and cultural-social conditions (0.41). Given the output of LISREL, the value of X2 computed as 1105.34 and the low value of this index indicates the small difference between conceptual model and observed data of this study. The value of RMSEA equals 0.037 and it is below 0.08 that indicates the model’s mean squared error is of desired degree. Moreover, based on the study relationships, there is a positive and significant relationship among the variables of city resilience study and there is a significant relationship among the aspects of resilience pattern for combating Covid-19 pandemic.

The hydrographic specifications of the karstic spring and the recession coefficient can reflect the hydro-climatic fluctuations and physical and geological characteristics of the aquifer system recharging the spring. In this study, in order to identify the hydrological geological behavior of Khorramabad Motahhari karstic Springhead (Sarab) during hydro-climatic fluctuations, quantitative analysis of recession curve based on Maillet exponential equation and coefficient of recession curve during wet years in a 27-year period (from 1991-92 to 2017-18) was calculated. To investigate the effect of hydrological fluctuations on the recession coefficient of Motahhari spring hydrograph, the changes in the time series of discharge coefficient during the base flow was analyzed by SDI hydrological drought index. Then, the statistical correlation of this index with evapotranspiration deficit index (SEDI) was analyzed to investigate the hydrological relationship and affectivity of the spring recession coefficient from climate fluctuations and biological changes. The results showed that the recession coefficient of Motahhari spring during the statistical period has an upward linear trend and its value has changed from 0.0081 to 0.0574 during mild and severe droughts, respectively. Statistical comparison of the time series of the recession coefficient of the mentioned spring with the values of SDI index showed that there is a significant inverse correlation with a negative coefficient of 65%. This means that with increasing hydrological drought of Motahhari spring and decreasing SDI values, the discharge coefficient of the spring increases and drainage takes place faster. Part of these changes is due to climatic and biological fluctuations. These effects were confirmed by the correlation between SDI and SEDI indices at a time scale of 6 months based on spectral analysis and cross-correlation at 95% confidence intervals. In addition, the spring recession coefficient can be influenced by the characteristics of Sarvak carbonate formation with limestone lithology and to some extent its fine-grained material. So, during droughts, the baseflow is affected by the conduit-flow and water stored in the body of the karstic aquifer and or due to large karst conduit and faults of Sarvak Formation, cause quickflow. In wet years, in addition to the rapid conduction of water by karstic conduits and fractures, probably recharged water from the Sarvak anticline flows into grained material with smaller pores consisting of calcareous material with a combination of sand and marl. These can cause high dynamic storage and low baseflow changes with a low hydraulic slope in dry months. In general, the results of this study give a comprehensive approach to karst spring management by predicting droughts and analyzing their drought coefficient.

Rainfall is the main source of the available water for human. Predicting the amount of the future rainfall is useful for informed policies, planning and decision making that will help potentially make optimal and sustainable use of available water resources. The main aim of this study was to investigate the trend and forecast monthly rainfall of selected synoptic station in Ardabil province using the best models of stochastic time series models. In this study, monthly rainfall for the next 5 years (2020 to 2024 AD) in the study area was predicted using different models of ARIMA family time series. Non-parametric Kendall- test was used to ensure the existence of the trend and the correlation diagram (ACF) was used to ensure the existence of seasonal changes in the time series. The best precipitation forecasting model in each of the 5 methods used for stabilization, was selected based on the values ​​of the model parameters, AIC criteria and correlation coefficient. The best static method and the best predictor model were used to predicte the next 5 year monthly rainfall. The results of man -Kendal test showed that the monthly rainfall data of Ardabil Synoptic Station had a decreasing trend (Z = 0.6119), but this trend was not significant at 95% confidence level. Study of the monthly rainfall data showed that there was a significant correlation between 12, 24, 36 and 48 month delays. The results of the monthly rainfall forecasting for the next five years (2020 to 2024) using the best static method and the best time series model in Ardabil Synoptic Station showed that the annual rainfall should decrease in 4 years of the next 5 years compared to the average of the 20 past years by 3 to 17 percent, the biggest drop since 2022. Rainfall will increase by 0.3% only in 2023.