نشریه مدیریت جامع حوزه های آبخیز
سال دوم شماره 2 (پیاپی 4، تابستان 1401)

The increase in greenhouse gases in recent decades and the resulting increase in temperature have upset the balance of the Earth's climate system and caused widespread climate change in most parts of the world. According to the definition of the Intergovernmental Panel on Climate Change (IPCC) (2013), climate change is a change in the state of a climate in which its mean or changeable characteristics change for decades or longer. Therefore, forecasting climate variables in the future is necessary to consider measures to reduce the effects of climate change. Climate models are good tools for assessing the climate in the future. These models simulate climatic parameters in the future by different scenarios of radiation induction. Selecting an appropriate climate model is essential for predicting and simulating climate data in the future, as well as evaluating changes in climate parameters in the future. An overview of studies conducted on the application of climate change models in the country indicates that in most studies, the application of atmospheric circulation models has been studied and regional models have been evaluated less. Therefore, in this study, two models of general circulation of atmosphere and region in Isfahan province are compared.

Isfahan province, with an area of 107018 square kilometers, is located between 30 degrees and 43 minutes to 34 degrees and 37 minutes north latitude of the equator and 49 degrees and 38 minutes to 55 degrees and 32 minutes east longitude of the Greenwich meridian. The climate of Isfahan province is generally temperate and dry. In this research, daily observational data including rainfall, average temperature and average wind speed from the Meteorological Organization, data predicted by REMO model in the base period 1991-2005 and the future period 2020-2100 for the parameters of rainfall, average temperature and wind speed from the base CORDEX data and three types of inputs were used to model climate variables by CanESM2 model. These inputs include daily precipitation data, mean temperature and mean wind speed of the synoptic station, open atmosphere analysis data (NCEP) and CanESM2 model data. To evaluate the efficiency of the models in the study area, the observational data and the data predicted by the models in the common statistical period by the statistical criteria of Percentage coefficient (PBIAS), Nash-Sutcliffe coefficient (NSE), standard ratio root (RSR), explanation coefficient (R2) and square error (RMSE) were assessed. Also, in order to better evaluate the performance of the models, the data simulated by the models were compared with the observational data by months.

The results of this study for the REMO regional climate model showed that this model is not suitable for simulating the rainfall parameter in Isfahan, Airport, Kashan and Golpayegan stations, nor is it suitable for simulating the average temperature parameter in Isfahan, Golpayegan, Nain and Kashan stations. In these stations, on average, the values simulated by the model for the precipitation parameter are more than the observational values and for the average temperature parameter are less than the observational values. In other studied stations, the values simulated by the model for rainfall parameters and average temperature have an acceptable agreement with the observational data. Also, the correlation of the simulated values of the model with the observational data for the wind parameter indicates that this model is not suitable for predicting wind data in the study area and the values simulated by the model are on average higher than the observational data in the period. The results of the CanESM2 atmospheric circulation model showed that the SDSM model has a high efficiency for modeling and exponential microscale in the study area. The results also showed that this model has a high efficiency for simulating the parameters of average temperature and wind speed relative to rainfall in the study area, which can be due to the presence of zero values in the data series. The results of rainfall parameter statistical criteria showed that the CanESM2 model in Daran, Isfahan, Khor and Biabank, Nain and Natanz stations is suitable for simulating rainfall in the future. Also, the results of the statistical criteria and simulated data of the model in the joint period for temperature and wind parameters showed high agreement with the observational data.

Climate models are appropriate tools for assessing the climate in the future. In this study, the efficiency of REMO regional climate models and the general CanESM2 atmospheric model were investigated. The results showed that the REMO climate model does not have the appropriate efficiency to simulate rainfall, average and wind speed in the study area, but CanESM climate model has high efficiency to simulate average and wind speed in the region. It can therefore be used as a suitable model for forecasting future climate in the study area.

Due to the importance of conservation of natural resources, the development of strategies for the protection and exploitation of these resources is felt as a fundamental necessity more than ever. People's participation in any project guarantees the implementation and sustainability of that project. This issue is more important in the protection of natural resources, because issues related to the environment and natural resources are intertwined with the lives of communities, and the success of any program will require the participation of these communities, so the role of people in decision-making, Planning, implementing, monitoring and evaluating any conservation plan is of critical importance. Therefore, an appropriate management system to protect these areas should be according to the management which is based on the participation of local communities. In other words, the main strategy to implement sustainable development in the field of renewable natural resources is to emphasize the factors that call for the participation of local communities. Studies on the participation of watershed residents in watershed management projects show that if the executive activities are carried out without the presence of the people, they do not take responsibility for the maintenance of the projects and therefore do not make any effort to eliminate their defects. In other words, people greatly increase their efficiency by engaging in such plans and programs (watershed management). In general, the success or failure of watershed management projects should be sought in the presence or absence of people. However, paying attention to determining the factors affecting the participation of watershed residents in watershed management projects and analyzing their relationship is an inevitable necessity. Therefore, the general purpose of the present descriptive-correlational study is to determine the factors affecting the participation of watershed residents in watershed management plans and analyze their relationship in the watershed of the great river of Naein.

Naein Great River Basin with an area of about 130,000 hectares between 32 degrees and 45 minutes and 18 seconds to 33 degrees and 09 minutes and 20 seconds north latitude and 52 degrees and 29 minutes and 18 seconds to 53 degrees and 05 minutes and 41 seconds is east of the Greenwich meridian. The minimum height of this basin is 1552 meters and the maximum height is 3094 meters (Figure 1). This watershed is located in Naein city of Isfahan province in terms of country divisions and includes two villages of Koohestan and Baharestan and 41 inhabited villages with a population of about 2298 people. The questionnaire was the data collection tool of this research, the apparent validity of which was examined by a group of experts including professors of watershed science and engineering and experts of the Jihad-e-Agriculture and Natural Resources Department, after which the necessary corrections were made accordingly. Its reliability coefficient was obtained between SPSS software and Cronbach's alpha method between 0.866 and 0.920. The statistical population of the present study consisted of watershed inhabitants living in the Naein Great River Basin of Isfahan Province (N = 2298). Of these, 476 people were selected as a statistical sample using Cochran's formula by random sampling method. Finally, 476 complete questionnaires were submitted and analyzed.

The results of Pearson correlation test showed that there is a positive and significant relationship between economic factors and the willingness of watershed residents to participate in watershed management projects (direct-strong correlation). It seems that in this watershed, the financial conditions and economic power of watershed residents are somewhat equal and at a moderate level. In such circumstances, providing low-interest facilities and credits can greatly strengthen the incentive for watershed residents to participate in watershed management projects. The results of Spearman correlation test showed that there is a positive and significant relationship (direct-severe correlation) between communication factors and information sources with the desire of watershed residents to participate in watershed management projects. The results of Kendall Tao test of each of the items of communication factors and information sources with the willingness of watershed residents to participate in watershed management projects showed that there is a positive and significant relationship between all indicators with the willingness to participate in watershed management projects. In other words, the more communication factors and information resources such as training classes, local leaders, experts, visiting other projects, radio, television, etc. are used, the more watershed residents will participate in watershed management projects. Therefore, it can be said that by promoting mass and social media, holding training classes, visiting other successful projects, etc. the amount of participation in watershed management projects can be increased. Also, according to the findings of the present study, the most important social factors affecting the participation of watershed residents in the Naein River Basin include the motivation of watershed participants to participate in future projects, the ability of local councils, encouraging friends, acquaintances and experts, the impact of educational and extension services, the awareness of watershed residents, the tendency to work collectively, and the impact of work experience. Also, the most important individual factors influencing the participation of watershed residents in the Naein Great River Basin include gender, age, and education. Therefore, special attention should be paid to these factors in the agenda of natural resource planners and specialists. For example, local councils can be used to involve watershed residents in watershed management projects.

In general, the findings of this study on the effects of social factors, economic factors, communication factors, information resources and variables of individual factors and their characteristics (land size, capacity of local councils, impact of local knowledge use, visiting other projects, experts’ information dissemination, etc.) show that these factors influence the participation of watershed residents in watershed management projects, and since these factors and items have severe effects on the desire of watershed residents to participate in watershed management projects, paying attention to these cases can help us improve watershed management projects, which requires that experts and the government pay special attention to the watershed dwellers living in the basin.

Desertification is a natural disaster risk event. This phenomenon, along with the extent of degradation, various effects and complexity of the process, deals with qualitative and uncertain indicators and follows the behavior of fuzzy systems. Therefore, in evaluating combating desertification to achieve preferred and optimal strategies, the use of multi-criteria fuzzy decision-making methods seems necessary. Therefore, this study was conducted to determine the priority of strategies to combat desertification using hierarchical analytical models in a fuzzy environment in the Yazd-Khezrabad plain during 2019-2020 as a case study.

Fuzzy decision matrix was obtained from fuzzy Delphi method and within the framework of multi-criteria decision-making method. Using Expert Choice software and ELECTRE model, the initial priority of strategies was obtained. In order to estimate the final priority of strategies, TOPSIS method was used and the results were analyzed using GAIA diagram, Graphical Analysis for Interactive Assistance, in Visual PROMETHEE software environment.

The results show that the strategy of "adjustment in abstraction from groundwater resources" (A31) with a ratio of 56.59% is the most important strategy in controlling and reducing the effects of desertification and rehabilitation of degraded lands. The strategies of livestock grazing control (A20), irrigation pattern change and implementation of low water requirements (A33), vegetation development and restoration (A23) and prevention of improper conversion and change of land use (A18) with proximity ratios of 15.76 %, 13.53%, 11.34% and 2.78% were selected as the next priorities, respectively. Analyses performed in Visual PROMETHEE software environment also confirmed the results of the ranking. As the analysis showed, the strategy of "adjustment in abstraction of groundwater resources" (A31) with a pure out ranking progress of Phi = 0.3635 still remained the most preferred evaluation strategy and other strategies were ranked as before.

Overall, it is concluded that in line with the strategy of adjusting the abstraction of groundwater resources (A31), by implementing aquifer projects, improving irrigation methods, land improvement, controlling the growth of industries and aquaculture crops, the process of desertification can be slowed down and destroyed lands can be restored. It is suggested that in the plans to control and reduce the effects of desertification and rehabilitation of degraded lands, the obtained results and rankings should be considered.

The unavailability, inadequacy and low quality of Dubai observational data is one of the problems of water resources management, This factor has made water resources management projects difficult. Collecting information requires hydrometric stations, which are expensive to build, and take a long time to collect information. This requirement is therefore recognized by the International Hydrological Association. Prediction in watersheds without statistics has been adopted as a research agenda for the coming decades. In addition, many watersheds in the world have statistical shortcomings. Due to human intervention, it is very difficult to predict in these watersheds. To solve this problem, hydrologists use a tool called area analysis. Due to the complexities related to the emergence of flow continuity, one of the ways to study the variables that cause it, is using an artificial neural network. Most artificial neural network researchers believe that artificial neural networks perform well in investigating unknown and complex issues for two main reasons: First, they have a good relationship between input and output by having pattern recognition capabilities. Second, they are less sensitive to errors between data input and output than other models.

This study aims to evaluate the artificial neural networks in the analysis of the flow continuity curve region using two functions of sigmoid transfer and hyperbolic tangent in the hidden layer and linear transfer function in the output layer. For this purpose, 33 watersheds in the area of ​​Salt Lake Lake were selected according to the length of the statistical period and the minimum of human activities. Independent variables were considered. Using factor analysis, six factors of area, average height, length of main waterway, drainage density, percentage of permeable formations and percentage of rangeland lands were selected. In order to select suitable hydrometric stations, daily flow statistics of all hydrometric stations of the Salt Lake watershed were prepared by Iran Water Resources Research Company (Tamab). Then, the duration of daily discharge statistical period of all hydrometric stations was extracted. Suitable stations were selected according to the appropriate common statistical length and the absence of a diversion dam and upstream dam. Drought threshold discharge percentages were then extracted using daily discharge statistics by calculating the probability percentage through the Weibull relation in Excel 2010 software.

In this study, which was performed in a number of Salt Lake watersheds for regional analysis of the flow continuity curve, we compared the estimation of different flow rates of the flow continuity curve using artificial neural shock with two functions of sigmoid transfer and hypermolic tangent in the hidden layer and the linear function in the output layer. Using the results of factor analysis, six variables of area, average height, length of main waterway, drainage density, percentage of permeable formations and percentage of rangeland lands were selected. In the next step, by changing the type of transmission function in the hidden layer in the multilayer perceptron artificial neural network to analyze the region of the flow continuity curve, it was determined that the sigmoid transfer function is more efficient than the hyperbolic tangent transfer function in most flow continuity flows. Also, the artificial neural network has a high efficiency in estimating the flow continuity curve, the root index value of the mean square error is between 0.01 to 1.92 cubic meters per second and the Nash-Sutcliffe efficiency coefficient is between 0.40 and 0.97 in the discharges.

The results showed that in flows 2, 10, 20, 25, 33.3, 50, 75, 90 and 92% of sigmoid function in the hidden layer with coefficients of explanation 0.88, 0.55, 0.78, 0.60, respectively. , 0.80, 0.63, 0.58, 0.47 and 0.41; The root mean square error is 0.01, 1.92, 1.68, 1.11, 1.78, 0.98, 0.17, 0.21 and 0.21 cubic meters per second and the coefficient of instability is 0.89, 0.40, 0.97, 0.47, 0.84, 0.78, 0.70, 0.93 and 0.41 and in 15 and 30% discharges of hyperbolic tangent function in the hidden layer with coefficient of determination of 94.94, respectively. 0. and 0.80, the root mean square error of 0.40 and 1.16 cubic meters per second and the efficiency coefficients of 0.70 and 0.86 have higher accuracy In general the artificial neural network has a high efficiency in estimating the flow continuity curve.

The development of agricultural and urban areas and overexploitation of natural resources have caused significant changes in the hydrological regime of watersheds. Furthermore, population increase, unprincipled exploitations and climate changes have intensified this process. It is therefore necessary to know and study it continuously. The trend of hydrological series may also change due to climate change, land use and watershed management. Therefore, identifying the presence or absence of changes in time in rainfall and discharges of an area and presenting it in statistical analysis seems necessary. The Mann-Kendall test is one of the most widely used nonparametric methods for analyzing the flow of such data. Studying periods of rainfall and discharge as well as land use change can be useful in expressing the role of climatic and human factors. Therefore, the present study was conducted to investigate the trend of land use change and the role of each in the discharge trend of Kiar watershed. 

The present study was conducted in Kiar watershed located in Chaharmahal and Bakhtiari province as one of the northern sub-basins of Karun River. In order to conduct the current research and achieve the desired goals, after obtaining the information and data required for the research from the Chaharmahal and Bakhtiari Regional Water Organization, a joint statistical course of study stations was determined. Finally, the mentioned period was selected from 1363-1390. Then, Mann-Kendall non-parametric test was used to investigate the trend of changes in precipitation and discharge of stations in Kiar watershed. Then, land use changes in the study area in three time periods were extracted using the object-oriented classification method in IDRISI Taiga 16.03 software environment using Landsat's TM sensor images. Using the parameters of overall accuracy and kappa coefficient, the accuracy of the classification was calculated. Finally, the trend of land use change and its relationship with the trend of discharge were evaluated.

The results of trend analysis for the Dey River time series (on seasonal and annual scales) at the Burnt Mountain Station show that discharge has had a decreasing trend on both scales. The highest discharge trend in the seasonal series belongs to summer and the lowest discharge trend belongs to fall at the significant level of 1%. The study of trends in the rainfall time series of the region shows a different behavior. While the trend in Borujen station was upward, Shahrekord and Beheshtabad exhibited a downward trend, and no trend was found in Farsan station. The decreasing trend of discharge and precipitation in Kuh-e-Sokhteh hydrometric station and rain gauge stations in Shahrekord and Beheshtabad are on the same side, which can be attributed to the decrease in discharge due to the rainfall behavior of the region. The results of the trend of land use change showed that residential and agricultural lands have an increasing trend and rangeland and barren lands have a decreasing trend. Increasing the level of agriculture and residential areas can be a reason for reducing the trend in discharge.

Based on the results of the present study, the results of trend analysis for the time series of the river at the burnt mountain station showed that the discharge trend in seasonal and annual scales is Downward. The highest discharge trend in the seasonal series belongs to the summer season and the lowest discharge trend belongs to the autumn season. Also, the results of studying the trend in the time series of rainfall in the region showed different behaviors. While, the trend in Borujen station was upward, Shahrekord and Beheshtabad exhibited a downward trend, and no trend was found in Farsan station.

Paying attention to the impact of pollutants on human health is of particular importance. Air pollution is now one of the significant environmental and economic problems globally, and this crisis is more severe in large industrial cities. Air pollution has caused a sharp increase in various respiratory and skin diseases, congenital disabilities, physical weakness, and many other diseases. On the other hand, the costs to eliminate these pollutions are remarkable (Rouhi & Khezri, 2014). Finding the optimal emission limits has always been a challenging issue for economic planners and city managers for two reasons. First, there is a desire for the economic development of each city (and the country at higher levels). Second, the strength and resilience of the city towards the absorption of the pollutants is a limiting factor. Not paying attention to this principle and imposing more pollutants than the ability to absorb and purify the ecosystem cause severe air pollution with harmful effects on humans and the environment (Ghodsi Ma’ab, 2016). Considering that Arak city has been introduced as one of the most polluted cities in the world according to the statistics of the World Health Organization, especially in terms of particulate matter (Rezaei Vandchali et al., 2017), studies on the effects of air pollution on social resilience of this city can be useful for proper city management and community health.

The city of Arak is the capital of the Markazi province and is located in the southwest of Tehran province, at a distance of 288 km. Arak covers an area of 98.7178 km2, 4.24% of the total area of the province. The city of Arak is located on the orbit of 34° and 5ʹ and 30ʺ in the northern hemisphere of the equator and on the meridian 49° and 41ʹ and 30ʺ east longitude of the Greenwich meridian. The plateau of Arak has an area of 5400 km2, of which 2400 km2 includes the high plain of Arak, and the rest is the heights around Arak. This study aimed to investigate the effects of air pollution on the social resilience of residents in Arak in 2019. The method of research was descriptive in a causal-comparative form, using a questionnaire. The population included all Arak residents and 283 volunteer respondents (153 females and 125 males) filled in the questionnaire which was done by voluntary sampling method. The social resilience questionnaire included 50 questions representing 50 research variables in eleven aspects: social solidarity, awareness, resource diversity, flexibility, security, trust, communication, participation, social support, social solidarity, and air pollution (Table 3). The validity of the questionnaire was investigated by the experts in the field and was confirmed after reviewing the proposed amendments. Moreover, the reliability of the questionnaire was evaluated by calculating the Cronbach’s alpha method, and its value was 0.78. Therefore, the social resilience questionnaire could be implemented in the population. The questionnaire also gathered the respondents’ demographic information, including age, gender, residence history, education level, ownership status, and occupation.

Three hypotheses were proposed to investigate the effects of air pollution on the social resilience of citizens in various regions of Arak. To investigate the hypotheses, using the data of Environment Organization of Markazi Province, air quality indicators in 2019 were received from three active stations of Ostandari, Shariati, and Horiba. Three indicators of CO, NO2, and PM2.5 were selected as air quality indicators based on most of the daily data reported during the year. After selecting the social resilience variables and evaluating the questionnaire’s validity and reliability, first, three regions related to three active stations, and for comparison, three more regions in the study area, namely, Hepco, Mokhaberat, and Aqil-Abad, were considered during the investigations. The copies of the prepared questionnaire were distributed among the regions’ residents who volunteered to respond to the questions. It can be said that only the third hypothesis that there is a significant difference between the effect of air pollution indicators (CO, NO2 and PM2.5) on social resilience of residents in various regions of Arak was confirmed, which was in line with the results of Suarez et al. (2016), Johnson Jr (2004), Pluhar et al. (2009), Ghorbani et al. (2017) and Mehranpour & Ebrahimi Ghavamabadi. (2016). In explaining the result of the third hypothesis, we can refer to the living conditions of the citizens. As an industrial center of the country with a large number of factories and urban traffic, especially with outdated vehicles that have increased pollutants, Arak has faced warning conditions due to increasing pollutants with impacts on climate change, environment, and human health.