فهرست مطالب ali reza nafarzadegan

Flooding is one of the environmental hazards that causes a lot of repeated damage to water and soil resources in different regions of Iran and around the world. Check dams as a mechanical practice have been built in many watershed areas of the country to control peak discharge and prevent soil erosion. Therefore, it is essential to examine the role of these mechanical practices in flood control at the level of watersheds. The current study aims to investigate the effect of the construction of three proposed structures (two masonry check dams and one embankment dam), with spillway heights of 9, 6, and 8 meters, on flood characteristics in Kander Abdolreza watershed, Fars province, Iran. In other words, this study examines whether the construction of these three consecutive structures fulfills the goal of the operation, which is flood control through a significant reduction in peak discharge and flood volume in the study area. Therefore, the most important variables in this study is the flood volume and the volume of reservoirs proposed for flood control. The amount of flood volume is extracted from the flood hydrograph, and the volume of reservoirs is obtained using a contour map and storage-height curves. It is obvious that if the volume of the reservoir is more than the volume of the flood, all the flood will be attenuated by the structure and the runoff would not pass through the spillway of the dam. 

In this study, the HEC-HMS model was used to simulate the rainfall-runoff process and the reservoir effect of each of the three proposed consecutive check dams on flood characteristics. The study area, Kander Abdul Reza watershed, is located about 27 kilometers southeast of Lamerd city, Fars province, Iran. According to the division of watersheds in the country, it is part of the Kol-Mehran basin which is a subbasin of the major basin of the Persian Gulf and Oman Sea. In this regard, after preparing the required data, including properties related to topography, rainfall, soil hydrologic group, and designed structures, the peak discharge and volume of flood under different return periods were estimated using the HEC-HMS model. Ghahreman-Abkhezr method was also used to estimate the intensity of rainstorms. The characteristics of the flood in the downstream were investigated in the absence of three proposed structures (two masonry check dams and one embankment dam) and in the next step, the effect of these reservoirs/dams on the hydrograph of the flood was analyzed. Due to the fact that the proposed structures are located upstream of the residential area and the highway, the basis of the design of the structures was the flood discharge with a return period of 100 years. Finally, using the obtained results, the percentage of reduction in the peak discharge of the flood under the influence of the construction of each of the reservoirs/dams was determined and compared.

The outcomes of SCS unit hydrograph for Kander Abdolreza watershed showed that the flood peak discharge in the return period of 2, 5, 10, 25, 50, and 100 years is equal to 7, 32, 46, 72, 91, and 116 m3.s-1, respectively; so that the time base of the hydrograph varies from 6.5 hours in the 2-year return period to nearly 9 hours in the 100-year return period. Meanwhile, the volume of runoff varies from 1.73 m3 in the return period of 2 years to 1053 m3 in the return period of 100 years. The results also showed that if the three proposed three consecutive structures were built, with a total reservoir volume of 614367 m3, the peak flood discharge would fall from 116 m3.s-1 to 32 m3.s-1 over a 100-year return period. In addition, the outcomes of the simulation of the rainfall-runoff process in the study watershed indicated that the reduction in the peak discharge and volume of the flood after the implementation of the proposed structural measures for the 50-year return period was 84% and 73%, respectively; and for the 100-year return period it was reduced by 72% and 57%, respectively. Thus, according to the results of the simulation of the effect of the designed structures, it can be claimed that the proposed structures for the study watershed would have the ability to mitigate and control floods.

The implementation of the proposed structural measures for the Kander Abdolreza watershed, including two masonry check dams and one embankment dam, in addition to reducing the peak discharge and the volume of flood flows, can stabilize the longitudinal profile of the stream channels, which is useful for the conservation of soil and water resources in the study area. At different return periods (2, 5, 10, 25, 50, and 100 years), the three proposed structures have the required capacity to store runoff and reduce the peak discharge in the study watershed; however, as the return period increases, the role of these reservoirs/dams in controlling the flood and reducing the peak flow decreases. Moreover, the effect of the proposed consecutive structures system on peak flow reduction is greater than the effect of these structures on flood volume reduction.In general, to increase the effectiveness of the watershed studies plans, it is recomended to include the study of the impact of the implementation of structural measures on the characteristics of flood flows in the service description worksheet of these projects so that the decision to carry out or not to carry out for structural operations in each basin or sub-basin is made based on the simulation results and with more detailed information. In addition, to better evaluate the proposed structural measures for flood control, it is suggested to prioritize the installation of hydrometric stations in ungauged watersheds that are prone to flood generation.

This study was carried out with the aim of determining weather parameters and air pollutants affecting seasonal changes of particulate matter of less than 10 microns (PM10) in Yazd city using Random Forest (RF) and extreme gradient boosting (Xgboost) models.

The required data was obtained from 2018 to 2022. Levene’s test was applied to investigate the significant difference in the variance of PM10 values in 4 different seasons, and Boruta algorithm was used to select the best predictive variables. RF and Xgboost models were trained using two-thirds of the input data and were tested using the remaining data set. Their performance was evaluated based on R2, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Nash–Sutcliffe Model Efficiency Coefficient (NSE).

The RF showed a higher performance in predicting PM10 in all the study seasons (R2  > 0.85; RMSE < 22). The contribution of dust concentration and relative humidity in spring PM10 changes was more than other variables. For summer, wind direction and ozone were identified as the most important variables affecting PM10 concentration. In the autumn and winter, air pollutants and dust concentration had the greatest effect on PM10, respectively.

RF model could explain more than 85% of PM10 seasonal variability in Yazd city. It is recommended to use the model to predict the changes of this air pollutant in other regions with similar climatic and environmental conditions. The results can also be useful for providing suitable solutions to reduce PM10 pollution hazards in Yazd city.

Vegetation is an important component of terrestrial ecosystems whose changes are controlled by climate changes and human activities. In order to detect the climate change impact on vegetation dynamics of Kermanshah province, Iran, this study was conducted using multi-time images of NDVI and EVI regarded as vegetation indices taken by MODIS sensors. Also, the trend of changes in climatic parameters such as temperature and precipitation were used by Mann-Kendall test over 15 years (2006 – 2020). Finally, the correlation between vegetation and climatic parameters was examined. The result of 15-year changes in vegetation using two indicators of NDVI and EVI showed that the trend of vegetation in more than 59% of Kermanshah province has been decreasing. The trend of precipitation in more than 88% had decreased and the trend of temperature in the 98% area had increased. The correlation between vegetation obtained from NDVI and EVI indices with the climatic parameter showed a positive correlation between precipitation and vegetation and a negative correlation between temperature and vegetation in more than 80% and 59% of this province, respectively. The results of the correlation analysis of different land-uses showed that in the barren lands and shrub lands, the positive correlations between precipitation and vegetation were stronger than the negative correlation between temperature and vegetation. In contrast, in grasslands and savannahs, the relationship between vegetation and temperature was stronger than that for precipitation. According to the results of this study, the climate changes and human activities are effective in controlling the trend of vegetation in different areas, which can be well demonstrated using the information obtained from remote sensing data.

The integration of inter-sectoral policies is necessary for natural resource management. This is due to the fact that the scope of current environmental and sustainability issues goes beyond traditional sectoral boundaries. The water resources in Iran are facing a problem due to the excessive exploitation of underground water resources. The lack of cooperation and communication among institutions responsible for managing underground water resources is the root of this problem. Numerous studies have examined the use of social network analysis and its effect on natural resource management, addressing the complexity and unpredictability of social-ecological systems. Some researchers have examined the impact of social networks on each other, society, and social processes, while other researchers have explored organizational arrangements for better management. The objective of this study is to identify institutions, categorize them, and analyze the pattern of communication and cooperation between them, to collaborate together in a synergistic manner for collective action in the field of cooperative aquifer management in the Isin Plain.

The social network analysis technique is employed in this study to determine the roles and positions of stakeholders, to establish a management system that is coherent and compatible to balance the Isin Plain Aquifer. The relationship between organizational activists involved in water was analyzed through a social network analysis questionnaire conducted after learning about them in a snowball way and completed by linking cooperative relations and information exchange through a complete network. In terms of water governance and their roles, organizations were classified into different groups. The ecological boundary of the current study of agricultural lands affected by the Isin Plain aquifer and its social boundary are 31 governmental and non-governmental organization related to the Isin Plain groundwater. For this purpose, the results of answering the questionnaires at the organization level were entered into Excel software in the form of a matrix. After adjusting the data,
the data was transformed from the Likert spectrum mode into binary format using the UCINET 6 software, and the desired indicators were calculated. At the macro level, the indices of density, reciprocity, transitivity, degree, and geodesic distance were computed and examined the index of internal and external links at the intermediate level, and the indices of degree centrality, betweenness centrality, and closeness centrality at the micro level of the network. The groundwater governance regime in the study area was investigated using two indicators of density and degree centrality at the macro level. Two indicators of density and internal and external links at the macro level were used to investigate common imaging to achieve water governance.

According to the results, the macro-level indicators in the studied network were not in a positive position, and the organization network of the studied region was found to have a low level of social capital. In addition, 38.71% of organizations related to the participatory governance of water resources were in the central subgroup, while 61.29% of the organizations were in the peripheral subgroup. Due to their role in providing services, government agencies have the greatest impact on water resources in the study area. Furthermore, there are no non-governmental organizations or production cooperatives in this area that play an active role in managing water resources. According to the E - I index, the exchange of information and cooperation in intermediary and protection subgroups is external, and intermediary institutions are willing to exchange information and cooperate with the actors of other subgroups to protect more natural areas. The results show that among the investigated actors, the Regional Water of Company Hormozgan and the police force are among the key political and organizational powers, as a center and source of advice and a communication bridge for other actors. These actors are instrumental in the process of information transfer and cooperation in the organizational network of the studied region. Thus, these two actors are considered flexible bodies that can be effective in the successful implementation of cooperative management of water resources to balance the aquifer of the Isin Plain with less time and cost. The social network analysis revealed that the actors have weak interactions for managing aquifers in the Isin Plain, and their influence and powers in the network are also different. The weak cooperation of different groups involved in the management of groundwater resources of the Isin Plain can reduce collaborative activities effectiveness, lead to conflicts in their actions, and prohibit the sustainable balancing of the aquifer. Non-governmental organizations and production cooperatives either do not exist or are not actively involved in aquifer management. In the implementation of participatory management programs, it is possible to utilize the capacity of influential and key actors to promote the integration of stakeholders and water policies. It increases their participation in relevant restoration and balancing projects, and improves the management of water resources. The governance system for managing groundwater resources is centralized and uncoordinated, depending on the network's centrality, which indicates low power distribution, coordination, and adaptive capacity. Furthermore, there is a lack of coherence in the structure of knowledge shared among stakeholders. The Isin Plain's water resources management depiction does not focus on negotiation, but rather on ambiguity. Therefore, it is necessary to achieve cooperative management of the aquifer in the studied area, increasing cooperation and two-way communication between organizations and more communication with less key actors, especially non-governmental organizations

IntroductionGroundwater is among the most precious natural resources for human health, economic development and environmental diversity. Since the measurement of groundwater parameters and water quality is difficult, costly and far from being available, interpolation techniques are an easy solution. At the same time, there is a strong correlation between groundwater quality and land use in areas with sensitive aquifers. Changes in land use caused by factors such as rapid growth and expansion of urban centers, rapid population growth, and the lack of land, the need for increased production and the evolution of technologies are important concerns. The literature review shows that the quantitative and qualitative decline in groundwater is a global crisis. As a result, the factors affecting the quantitative and qualitative decline in groundwater range from climate factors to socio-economic factors.In the current research, find an answer to the poor condition of the Isin Plain aquifer by looking at the relationship between some hydrological factors and changes in cultivation pattern of the region is the main goal. For this purpose, the water table and EC of groundwater were interpolated using geostatistical methods. Using satellite imagery, the trend of culture pattern changes over time was obtained. Finally, the relation between the factors on the Isin plain was established. Material and MethodsFor this purpose, the quantity and quality of groundwater in eastern and western Isin plains were interpolated using the Kriging and IDW methods, during the four statistical years of 2004, 2011, 2018, and 2021 and the time series of 2004-2021. The RMSE statistic was used to evaluate the performance of the methods.Then, satellite images and ground truth data was used for land use change classes to investigate the land use changes during the cropping season, along with the determination of changes in the quantity and quality of groundwater in the eastern and western Isin plains for the mentioned years. Satellite data including Landsat 5 multi-temporal satellite images in 2004, 2011, and 2018 and Landsat 8 and Sentinel 2 images for February 2021 were obtained from the USGS.Following preparation of the related images using the flash module, atmospheric and radiometric corrections were performed. Then, the corrections information was extracted into the text file appended to each image. With field survey, the coordinates of the representative pixels were determined and seven land use classes of gardens, vegetables, bare lands, residential and industrial areas, saline lands, and Prosopis Cineraria and Juliflora species were determined. The maximum likelihood classification method was used to separate seven main land use classes based on 127 training samples. For the purpose of assessing accuracy, an error matrix was created for the producer's accuracy, the user's accuracy, the overall accuracy, and the kappa coefficient calculation. Finally, to examine the relationship, the land use map and the groundwater and EC interpolation maps were overlapped into the Arc Map software environment. Results and DiscussionBy comparing the interpolation methods of IDW and Kriging with the RMSE validation technique, it was found that the best interpolation method for estimating water table and EC is Kriging, followed by the IDW method. A review of the land use maps of the Eastern and Western Plains of Isin showed the increase and decrease of different land use categories over the years under study. The overall accuracy and Kappa coefficient were over 82% and 0.79, indicating the acceptable accuracy of the classification and maps obtained. The results of overlapping land use maps and spatial changes in ground water indicate that the location of agricultural land, especially gardens in the eastern Isin plain and vegetables in the western Isin plain, is compatible with the areas of having low water table. The results of overlapping the land use map obtained from Landsat 8 data and EC spatial changes showed the highest amount of EC in can be observed in Prosopis Cineraria and Juliflora species and residential and industrial uses in eastern and western Isin plain. The results obtained from Sentinel2 indicate that the value of EC was significant in the bare lands of eastern Isin and in the saline lands of western Isin. However, the increase in agricultural use, especially for gardens and vegetables, and the pairing with areas with the lowest water table indicates an over-extraction of groundwater for agricultural purposes. On the other hand, the significant extent of bare lands and the upward trend of saline lands, residential and industrial areas, and matching with areas with high EC and the adaptation of maximum EC with Prosopis Cineraria and Juliflora species uses may be a warning for poor condition of the Isin plain aquifer.

The purpose of this study is to reveal the physical expansion and spatial changes of heat islands in Minab city during three time periods (1975-1988, 1988-2000, and 2000-2014). For this purpose, TM and OLI images of Landsat satellite were  used. The physical changes of the city were obtained by analyzing the values extracted from the two indices of normalized difference built (NDBI) and normalized difference vegetation (NDVI). To find heat islands of the city, single-channel and separate-window algorithms  and to investigate the contribution of population growth and urban horizontal growth on changes in heat islands, Shannon and Holdren entropy models were  used. The results showed that the maximum amount of physical expansion of the city happened 901.61 hectares, in the years 1988 to 2000 of which 55.6 percent was based on population growth and 44.4 percent was based on the incrae of land per capita. The area of the heat islands was estimated to be 112.96 hectares, indicating the north-south and east-west trend, which has grown more than 4 times compared to the previous period. The share of population factor in this growth was 62.8 hectares and the share of urban sprawl was 50.16 hectares. The Shannon’s entropy value was 0.3, indicating an unrestricted growth in the considered period. In general, in the 39-year period, a 5 fold increase in the size, a 6.34 fold increase in the population and a 5.7 fold increase in the heat islands area were observed in the Minab city. Since no documentary report has been presented regarding the investigation of heat islands in Minab city, the results of the present research can be used to manage the concentration of the city points.

In recent years, Minab plain, one of the most important agricultural plains in the south of the country, has experienced extensive land subsidence. Also, the study of the groundwater level of the Minab plain in a long-term periods showed that since 2001, the drop in the aquifer level has intensified and an average annual drop of 42 cm has been observed. Furthermore, previous geotechnical studies in the region have shown that besides the drop in groundwater level, the presence of swollen  and soluble sediments has increased the severity of subsidence in the Minab plain. According to the evidences of the previous studies and damages caused by land subsidence to infrastructure, buildings and agricultural lands, recognizing this phenomenon, identifying areas sensitive to it and investigating the factors affecting its occurrence can play an important and effective role in predicting land subsidence and preventing associated damages. In the current study, unlike other land subsidence studies, which emphasized the drop in groundwater level and the type of geological formations, the characteristics of soil and land surface in the explanation of subsidence phenomenon have been considered.

The study area of ​​Minab plain with an area of ​​653.6 square kilometers is located between the longitudes of 56° 49' to 57° l5' East and latitudes of 27° 1' to 27° 19' North. First, a time-series analysis of Sentinel-1 radar was performed to identify the land subsidence sites and calculate the displacement rate. After calculating the vertical displacement, for the spatial modeling and the preparation of land subsidence hazard map of Minab plain, data mining methods were employed with soil and land surface features. The investigated time period in the present study covers the years 2015, 2017 and 2019. Spatial variations of 12 variables including soil texture, vegetation, percentages of sand, silt and clay, land surface temperature, soil bulk density, land cover type and soil salinity were gathered and prepared using Google Earth Engine (GEE) and TerrSet software to be used as independent variables of the spatial model. Then, by using Naïve Bayes (NB), Decision Tree (DT) and k-Nearest Neighbor (kNN) data mining models in the RapidMiner software platform, the necessary information was extracted to map the potential land subsidence zones. It is noteworthy that in the constructed models, the land subsidence map for different years (resulting from Sentinel-1 radar image processing) was considered as a dependent variable and the maps accociated with 12 variables mentioned were considered as independent variables. Performance criteria such as classification error, kappa coefficient, absolute error, normalized absolute error, relative error, and root mean squared error were used to evaluate the resulting models with respect to spatial accuracy.

The amount of subsidence for 2015, 2017 and 2019 is computed 3.61, 0.92 and 5.69 cm, respectively. The results obtained by interferometry processes showed that the land subsidence progresses from the central parts of the plain to the edges of the plain and the eastern areas of Minab plain have less amount of land subsidence compared to other areas. Overlap of sinkhole points recorded in the field survey also showed good agreement with the results of radar image analysis. The highest rate of land subsidence, which was equal to 5.69 cm, occurred in 2019. This amount of land subsidence is certainly hazardous for agriculture, the environment and the facilities in the study region.

Among the independent variables, vegetation, heavy soil texture and soil salinity had a more meaningful effect on different land subsidence classes. Also, among the models used for land subsidence risk mapping, the performance of the decision tree method with an accuracy of 63.15, classification error of 36.85, kappa of 29.7, absolute error and relative error of 0.5, normalized absolute error of 0.45 and the sum of the squares error of 0.56 was better than the other two models. Findings of this study showed that soil and land surface characteristics have the ability to express 0.6 of the variance of land subsidence phenomenon in the region and for more accurate modeling, effective data such as changes in groundwater level and the geological material of aquifer can be used. Also, the findings of this study as well as the prepared map of potential land subsidence occurrence in different parts of the study area can play an important role in risk reduction, land use planning and water resources management in the region.

GGroundwater is considered as one of the most remarkable sources of fresh water. The aim of the current research is to apply four machine learning models of Random Forest (RF), Support Vector Machine (SVM), Bioclim, and Domain to groundwater potential mapping in Kahurestan watershed, Hormozgan province. The innovation of the research is to employ Bioclim and Domain algorithms to groundwater potential simulation, to compare them with the two techniques of RF and SVM and to combine these four models by an innovative and new equation. For this purpose, 11 criteria including slope percent, slope aspect, plan curvature, profile curvature, soil adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI), slope length and steepness factor (LS), stream power index (SPI), topographic wetness index (TWI), land use, and distance to streams were considered. Also, the data of 113 high-discharge wells were used for simulation (70%) and validation (30%)processes. The collinearity test was performed prior to modeling which indicated that there was no relationship between the variables. Evaluation of the modeling performance with the ROC curve showed that all four methods used had very good accuracies and AUC values higher than 90% for prediction. The survey on the weight of the criteria based on the RF method demonstrated that the land use/cover and distance to streams criteria has the highest weight. The final map revealed that 21.4% of the area under study has good groundwater potential.

Being located in an arid and semi-arid region, Iran has always faced with limited water resources. As groundwater extraction has now exceeded the permitted limits all over Iran and the country faces considerable constraints in developing groundwater resources, severe water crisis looms large in the horizon. In this regard, a quick solution should be considered to supply water from non-conventional water resources (brackish and saline waters, rainwater harvesting, cloud seeding, etc.). Therefore, this study sought to investigate the status of water in Fatuyeh-Todroyeh plain in Bastak city, Hormozgan province, and the possibility of supplying water from unconventional resources, especially the brackish and saline waters, for agricultural purposes.

In the first step, the required maps of the study area including the groundwater electrical conductivity (EC) map were prepared, using ArcGIS software. Then, chemical analysis of the Fatuyeh-Todroyeh aquifer’s water quality was performed by AqQA software on the data gathered through three rounds of sampling from the wells, followed by the calculation of water quality index (WQI). In the next step, the the study plain’s hydro-climatic balance was measured via Budyko conceptual model, taking changes in storage into account. Then, to investigate the economic justification of using inland water desalination plants in the region, the cost-benefit ratio of the cucumber greenhouse cultivation, and the investment’s return rate for the installation of water desalination plants and greenhouse sites were calculated. Finally, having decided on appropriate criteria and options, the hierarchical analysis method (AHP) was applied for comparing different management options and offering the best plan for supplying unconventional water resources for the agricultural, drinking, and industrial sectors of the study region, using Expert Choice software.

The results of water resources quality surveillance showed that the Fatuyeh-Todroyeh plain’s groundwater samples ranged from acceptable to completely unpleasant in terms of drinkability according to Schuler diagram, and that its dominant water type was something between chloride and sulfate according to Piper diagram. Moreover, based on Wilcox diagram, the suitability of groundwater resources for irrigation purposes ranged from doubtful to unsuitable. In other words, there were no groundwater resources in the plain with low and medium EC and low to high SAR risks. Furthermore, the highest coefficient of variation belonged to sodium ion which was equal to 0.67 over the study plain. In general, according to WQI quality index, 75% of the water in Fatuyeh-Todroyeh plain’s wells have very poor quality, being inappropriate for agriculture and drinking.
Calculations of the plain’s water balance indicated that the decline in storage changes was 2.4 million cubic meters annually, making the development and extraction of groundwater impossible. The results of the investigation of the economic justification revealed that according to the cost-benefit ratio which was found to be greater than one in all years of a five-year period and the investment’s return rate which was greater than the current bank interest rate, the construction of inland water desalination plant and the establishment of greenhouses in the study region is economically justified. The results of AHP calculations suggested that based on the criteria set for unconventional water management in the agricultural sector of the study area, implementing the optimal cultivation pattern was the best choice in this regard, followed by the option of constructing a desalination plant. As for drinking purposes, the highest score belonged to the option of constructing water desalination plants, and for the industrial purposes, the highest score related to the option of prohibiting wastewater discharge into the river protection area.

Conclusion

the study’s findings showed that there were no facilities for the development of groundwater extraction in the region. However, constructing a dam in a suitable place, controlling the rainwater runoff (which is of very poor quality), and desalinating the stored water by a desalination system could help use the plain water acquired for drinking and agricultural purposes in Fatuyeh-Todroyeh plain

Background and Objective:

The Middle East is one of the most important regions in the world for dust production. Iran, located in the Middle East, is exposed to numerous local and trans-regional dust systems due to its location in the arid and semi-arid regions of the world. Dust storms, in addition to covering arable land and plants with wind-blown materials, destroy fertile lands and reduce biological production and biodiversity, and severely affect the survival of residents. Dust storms are involved in the transmission of dangerous pathogens to humans, air pollution, and damage to respiratory function. Dust storms in Yazd province are relatively common and the average number of days with dust storms in the province reaches 43 days a year. This phenomenon has caused many problems for the people of the province. The main indicators of air quality are the concentration of suspended particles and the aerosol optical depth (AOD) following the occurrence of dust events. Numerous studies have been conducted in the world to identify the centers of dust collection and their origin. However, to the best of the authors’ knowledge, there is no study on the spatial zoning of dust conditions using three algorithms of CART, MARS and TreeNet algorithms as the predictive models. The purpose of this study is to forecast and zoning the potential of different areas for the production of dust aerosols using remote sensing data and data mining models as well as to specify the most important variables on this phenomenon in Yazd province.

Materials and Methods:

 The Yazd province lies in a dry region of Central Iran. The province experienced average annual rainfall of about 57 mm and an average annual temperature of about 20 ºC. The maximum temperature experienced in the warmest month of the province is close to 46 ºC. The maximum wind speed in this province is up to 120 kilometres per hour. The Google Earth Engine (GEE) interface (Javascript editor) was applied to collect remote sensing data in order to form three data sets that contain features related to topography, climate, and land surface conditions. These features were employed as the independent variables of the models, which is built by taking advantage of three data mining algorithms, classification and regression tree (CART), multivariate adaptive regression splines (MARS), and TreeNet, to specify the potential of areas for dust production. The dependent variable (target variable) of the models was the aerosol optical depth (AOD), which was acquired from MOD04 AOD retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite. The outcomes of the three models for classifying areas with different dust potentials were evaluated under performance criteria, such as R-squared, mean absolute deviation (MAD), the mean square error (MSE), the mean relative absolute deviation (MRAD), and the root means square error (RMSE).

Results and Discussion :

The results showed the variables mostly affecting the dependent variable (AOD) in the MARS model were actual evapotranspiration, soil moisture, and the Palmer drought severity index. The values of R2 and RMSE in the MARS model were equal to 0.72 and 0.02, respectively. Similarly, the features with the highest relative importance according to the TreeNet model were soil moisture, Palmer drought severity index, and actual evapotranspiration. The values of R2 and RMSE in the TreeNet model were equal to 0.75 and 0.019, respectively. The results revealed that the CART model with R2 =0.85, MAD = 0.011, MSE =0.002, MRAD =0.262, and RMSE =0.014 had the best performance compared with the other two data mining models. The soil moisture, elevation, reference and actual evapotranspiration, minimum and maximum temperature, Palmer drought severity index, downward shortwave solar radiation, and wind speed were the most important variables in forecasting the potential of areas for dust production, respectively. Also, the areas with very high, high, moderate, low and very low susceptibility were occupied about 16%, 19%, 26%, 20% and 20% of the Yazd province, respectively.

Conclusion :

All three models, which were based on three data mining algorithms, CART, MARS, and TreeNet, had a good agreement in specifying the most important variables affecting the optical depth of the dust aerosols in the study area. However, these models indicated different priority order for the identified variables in terms of relative importance; Besides, there was a difference in their performance criteria. As mentioned above, the CART model was the best-performing model, of the current study, for specifying the potential of areas for the generation of dust aerosols. According to this model, 25.8% of the province was classified as the moderate-risk of aerosol production, 18.6% of the province as the high-risk of aerosol production, and 16.0% of the study region as the very high-risk of dust aerosols. The high-risk areas are mostly spread in the western and southwestern regions of the Yazd province.
Palmer United States golfer (born in 1929) More (Definitions, Synonyms, Translation).

Dust phenomenon is one of the natural disasters that is considered as a serious environmental hazard, especially in arid and semi-arid regions due to the great damage it causes every year. The present study aimed to investigate the relationship between 14 climatic variables with the maximum monthly aerosol optical depth (AOD) due to the dust events in Hormozgan province. First, by coding in the Google Earth Engine (GEE) environment, a satellite image was retrieved from the MODIS aerosol products for each day, and while preparing the AOD time series, the average maximum monthly dust values for a 17-year period (2000-2017) was extracted. Also, monthly climate and water balance products of University of Idaho including actual and reference evapotranspiration, minimum and maximum temperature, precipitation accumulation, soil moisture, Palmer drought severity index, climate water deficit, downward surface shortwave radiation, vapor pressure, vapor pressure deficit, and wind speed, as well as land surface temperature (LST) and vegetation index (EVI) were extracted and, while sampling these images, the relationship between the average maximum monthly dust values with them were computed using the ordinary least squares (OLS) and geographic weighted regression (GWR) methods. Then, the global Moran's I statistics was employed to analyze the spatial autocorrelation and distribution of dust over the province. The results showed that the GWR model with the root mean square error of 0.14, the sum of residual squares of 11.3, the coefficient of determination of 0.82, and the corrected Akaike information criterion of -570.19, performed better than the OLS method. The evaluation of the coefficients of the GWR model showed that the variables of vegetation cover, soil moisture and precipitation had the greatest effect on the amount of dust, respectively. Also from the perspective of spatial autocorrelation, a cluster pattern was observed for dust distribution over the province.

The purpose of this study was to assess the impact of the land use changes in the Minab city on the variations in the urban heat islands (UHI), using the random forest classification method and spatial statistics on TM and OLI Landsat images in 1988, 1998, 2008 and 2018. First, land surface temperature (LST) was calculated using the split-window and the single-channel algorithms. Land use map was generated using supervised classification random forest method and its performance was assessed by two criteria of overall accuracy and kappa coefficient. In order to survey spatial autocorrelation and clustering, pattern of hot spots, the two statistics of Anselin Local Moran's I and Getis-Ord GI were applied. In 1988, land uses of vegetated, barren, and urban built-up lands were occupied 30.1, 32.53 and 37.37 percent of the city area, respectively; in 2018, the areas of these land uses were 16.36, 9.56 and 74.08 percents, respectively. A threefold and twice-fold decrease in the area was observed for barren and vegetated lands, respectively; while the area of urban built-up lands had more than doubled. The calculated values for urban-heat-island ratio index (URI) in 1988, 1998, 2008, and 2018 were 0.45, 0.34, 0.11, and 0.22, respectively. The outcomes of two considered spatial statistics indicated the clustering, pattern for UHI of the Minab city. In addition, there was a good agreement between the results of Getis-Ord GI statistic (hotspots spatial analysis) and the Local Moran's I statistic (spatial autocorrelation) on the spatial pattern of heat and cool clusters.

A multi-objective linear optimization model has been formulated, which is used for water and crop area allocation in two irrigation and drainage networks of Dorudzan and Karbal, including five farming regions. The developed model is based on four bankruptcy rules of proportional cutback (PC), constrained equal awards (CEL), constrained equal losses (CEL), and adjusted proportional (APR) in terms of the certainty and uncertainty in the water availability. The developed model has four objective functions to reflect the various agricultural and environmental consumptions and is solved for two dry and non-dry conditions using a fuzzy compromise approach. The outputs of the model showed that the regions with higher shares of water receives the most allocated water through the bankruptcy rules of the PC and CEL in dry and non-dry condition, respectively. On the other hand, the most allocated water for the regions with lower shares of water occurs through the bankruptcy rule of the CEA in both hydro climatic conditions. The outcome of the stability evaluation using the bankruptcy stability index (BASI) indicated that this criterion could not be used to evaluate stability under all bankruptcy situations; thus, one should take the necessary precaution for making a decision according to its output

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The flood is one of the most important natural disasters, which is causing significant damage to affected areas. In flood management process, the factors which effectively responsible in flood formation are identified, and then areas with high potential for flood occurrence are identified. Because of the vast extent of catchment areas and the limited economic and administrative resources, the implementation of flood control projects in all flood-producing areas is not feasible. Therefore, prioritizing sub-watersheds is one of the chief measures for sustainable management of watersheds, with the purpose of controlling the flood. Multi-criteria decision-making (MCDM) methods such as the analytic hierarchy process (AHP) method and the analytic network process (ANP) are the techniques for identifying the areas with high flood-producing potential.
Since soil properties, infiltration rate, and quantitative geomorphological characteristics determine the amount of excess rainfall and runoff production, thus, the simultaneous application of morphometric analysis method and decision making models is very useful in the areas with data scarcity. In morphometric analysis, the physiographic and morphological characteristics of the watershed are analyzed based on the digital elevation model and finally the sub-watersheds are prioritized. Dividing large areas into multiple sub-watersheds and prioritizing these sub-watersheds reduce the time and cost of running watershed operations as well as making watershed projects more efficient.
The purpose of this study was to determine the sub-watersheds with critical conditions in terms of flooding risk in Dehbar watershed, Khorasan-e Razavi Province, Iran to reduce the costs of carrying out the watershed management projects focusing on flood control. It is worth noting that due to the lack of required data, morphometric and hydrologic analysis methods were used. In order to prioritize the sub-watersheds of Dehbar watershed, multi-criteria decision-making methods including AHP, VIKOR, and Permutation were employed. Afterwards, the results of these models were compared and verified by regional flood analysis method.
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The study area was Dehbar watershed located in Torqabeh and Shandiz County, Khorasan-e Razavi Province, Iran. The area of the Dehbar watershed was estimated to be 115.73 km2. In order to better identify and evaluate runoff production capabilities, the watershed is divided into smaller hydrological units that have been separately investigated. This classification was made based on the location of the water resources, the location of the villages, the hydrographic network, the topographic contour lines, the satellite imagery, the field visit, and the integrative view in the GIS system, so that through the use of the ArcHydro extension in ArcMap, the Dehbar watershed was divided into 6 hydrologic and 4 non-hydrologic sub-watersheds.
The Dehbar watershed was divided into 10 sub-watersheds. In the current study, 13 evaluation criteria including area, compactness coefficient, drainage density, circularity factor, form factor, curve number, bifurcation ratio, main channel length, average slope, average height, time of concentration, rainfall and runoff coefficient were selected, and the amount of each for each sub-watershed was calculated. The weight of parameters was derived by the AHP technique. After determining the weights of the evaluation criteria and the preparation of decision matrix, VIKOR and Permutation models were employed for prioritization. After prioritizing, the regional flood analysis method (based on existing stations in the watershed) was used to compute maximum flood discharge in different return periods in order to evaluate and validate the considered models.
To this end, a homogeneous area with hydrometric stations was first identified based on geographical and climatic conditions within the region of the study area. The outliers were then eliminated and the frequency analysis was performed for each station individually and the best-fit statistical distribution was identified and selected. Finally, for regional flood analysis, a regression relation was acquired between peak discharges and contributing area in adjacent catchments; thus, it is possible to estimate peak discharge in the study area.
Finally, the outcomes of three employed multi- criteria decision making methods were combined using the average rating method.
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Pairwise comparisons between considered criteria were performed based on AHP method and the relative weight of each criterion was obtained. Runoff coefficient with the relative weight of 0.221 had the highest importance among the considered criteria. Subsequently, rainfall criterion, time of concentration criterion, and curve number criterion were in the following ranks with the relative weights of 0.148, 0.116 and 0.109, respectively. The criteria of average elevation and form factor also had the lowest relative weights. Meanwhile, the inconsistency rate in AHP method was 0.04, indicating that the decision making process is consistent.
After determining the relative weights of each criterion for each sub-watershed, the VIKOR model was applied. According to this method, sub-watershed No.1 ranked first with Q index of 0.9715, sub-watershed No.3 ranked second with Q index of 0.8739, and sub-watershed No. 2 ranked third with Q index of 0.6030. Therefore, these sub-watersheds should gain high priority in watershed and flood control operations. Meanwhile, sub-watershed No. 7 with Q index of 0.0312, sub-watershed No. 10 with Q index of 0.0950 and sub-watershed No. 9 with Q index of 0.3132 were in tenth, ninth and eighth priority, respectively. Thus, these sub-watersheds had the lowest priority for implementing watershed management activities.
In the next step, the Permutation model was employed. According to the results of this model, sub-watersheds No. 1, No. 3 and No. 2 were ranked first to third, respectively. This is due to the high amount of rainfall, runoff coefficient and curve number in these sub-watersheds. Meanwhile, sub-watersheds 5, 8 and 10 were in the lowest ranks.
In addition, the results of regional flood analysis showed that sub-watersheds 1, 3, 8 and 2 had higher flood peak discharge, respectively. Meanwhile, sub-watersheds 5, 10, 4 and 9 had lower flood peak discharge and were in the last priority in terms of potential for flood generation.
In the final step, in order to provide a proper ranking for sub-watersheds, we used the average rating method to combine the obtained priorities by three different applied techniques. The outcomes showed that sub-watersheds No. 1, No. 3, and No. 2 were in the first rank, and therefore, in terms of the need for watershed management measures were in the top priority.
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The results of this study showed that the derived priority of the sub-watersheds using morphometric and hydrological parameters as evaluation criteria to identify flood-producing areas is a suitable and appropriate method. Therefore, it is recommended that, in order to reduce costs and gain optimal outcomes, watershed management projects focusing on flood control should be implemented in the identified sub-watersheds which are in top priority in terms of generating flood discharge. The outcomes also showed that one or two factors alone could not determine the priority of flood-producing capability of sub-watersheds and a sub-watershed with a larger area does not necessarily have the higher potential for generating flood, but the interaction of different factors ultimately determines the priority of the sub-watershed in terms of flood-producing potential.

Soil salinity is considered as one of the potential environmental hazards. The purpose of this study was to find the best index and the most suitable relationship for estimating soil salinity and its mapping using remote sensing data. At the first step, random sampling was performed using fishnet method and surface soil electrical conductivity (EC) measurements. Then, the threshold levels (92%, 95%, and 98%) were applied to the output images of each indicator. The methodology included using the least squares fitting (LS-fit) technique and principal components analysis (PCA) for halite and gypsum minerals, determining the correlation between the output of indices and ground data, and performing clustering and factor analysis between EC and output images. In order to select the best model derived from Landsat-8 band combinations and the amount of salinity, collinearity test, Durbin-Watson test, and backward multivariate regression were employed. The Cohen‘s kappa coefficient was also applied to evaluate the multivariate regression formed by Landsat-8 bands. The performance of the indicators was evaluated based on four criteria of root mean square error (RMSE), mean bias error (MBE), mean absolute error (MAE) and R-squared (R2). The results of the factor analysis showed the smallest distance between the EC, salinity index (SI) and brightness index (BI). The SI with an amount of 0.89 had the highest Pearson correlation with EC. In the dendrogram diagram, SI index with EC was placed in a cluster, and the RMSE, MBE, MAE and R2 values of the SI index were estimated to be 0.16, 0.11, 0.12, and 0.76, respectively. Compared to the rest of the indicators and linear, multivariate regression (with Cohen‘s kappa coefficient of 60%,), the SI index has provided better outcomes.

The contradiction between increased demand for water and decreased water availability has led to excessive exploitation of water resources and, in some cases, encroachment on the share of water needed to preserve the natural environment. Today, managing water resources and finding optimum strategies for water allocation has attracted the attention of policy makers. Water scarcity, especially in arid and semi-arid areas, makes the situation dire and challenging for water allocation. Such physical restrictions cause competition for water among irrigation and drainage networks and the ecosystem. In order to achieve optimum sustainable strategies for allocation of water between multiple stakeholders, a set of conflicting (negatively or weakly correlated) and incommensurable objective functions should be addressed.
To reach optimum crop area and water allocation schemes, one can optimize the amount of water allocated to the plant by considering the crop response to water deficit. The incorporation of crop-water production function into the linear objective function for maximizing agricultural net benefit would transform it to a non-linear objective function. Therefore, the problem would become more complicated.
Regarding practical problems, the optimization of the ratios of variables and parameters would provide a deeper understanding for managers and decision makers than optimizing each of them in the form of a separate objective function. Thus, such formulation can be considered as a tool to assess the sustainability of agricultural ecosystems. Combining the objectives by taking advantage of ratios would facilitate the process of analysis of alternative solutions. One of the issues in dealing with multi-objective optimization problems is the choice of a solution from a usually large set of non-inferior alternative points that make up the optimal tradeoff (Pareto) curve. One can take advantage of social selection methods to resolve conflicts between the objectives of different stakeholders by identifying the best settlement solutions from among an optimal set of non-inferior alternative solutions.
The aim of the current study is to develop a non-linear multi-objective optimization model for water allocation which takes into account crop-water production function, reservoir continuity, and surface water balance. The developed multi-purpose framework is based on four sustainability indicators, two fractional functions and two simple functions.

2.1. Water bankruptcy: The two main components of a bankruptcy situation are the amount of resources available and the claimed amounts of the stakeholders. In most water allocation cases, the first component can be easily equated with the amount of water available for distribution between users at a specific time and place.
The proportional cutback rule is one of the long-established principles for bankruptcy situations. It is widely employed to manage water resources under water scarcity in different parts of the world. According to the proportional cutback rule, allocated water to each water claimant is according to a proportion of its claimed volume of water. This proportion is defined as the ratio of total available water to total water demands of water claimants.
2.2. Deficit irrigation: Deficit irrigation is an optimization policy in which plants are subjected to different levels of water shortages. In each condition, the desirable level of water shortage and the resultant crop yield are determined through an optimization process on the basis of crop-water production function. This function describes the relationship between the gained crop yield and the total amount of water consumed by the plant through evapotranspiration.
2.3. Social choice approaches: Social decision-making methods are procedures that take into account all individual preferences in order to reach a social preference. In the current study, social choice rules such as the plurality, Borda count, median voting, majoritarian compromise, pairwise comparison, and Condorcet choice have been employed to choose a compromise point among a set of non-inferior alternative solutions.
2.4. Proposed sustainability model for farming and the ecosystem: In this research, we developed an optimization model for multi-purpose agricultural and environmental sustainability. The main goal of the proposed model was to address the optimal allocation of water between farming and the ecosystem in the Dorudzan reservoir-river system. The developed model consists of four objective functions, two fractional functions and two simple functions.
The first objective is the maximum ratio of net income –in terms of deficit irrigation– to blue water utilization. In order to optimize the virtual water content in agricultural products, one can divide the crop water requirement into two parts, green and blue water, and attempt to improve the water use efficiency of irrigation water. The second objective is the maximum ratio of total crop yields to total blue water utilization or, in other words, the minimum total blue virtual water content.
The third objective is the maximum fairness in water allocation or minimum total difference between the amount of allocated water to each irrigation district and the water share, which is determined by the bankruptcy, proportional cutback, rule.
The fourth objective is the minimum shortage in meeting the water demand of the Bakhtegan Lake ecosystem.
The main constraints of the proposed model are reservoir continuity, surface water balance at the downstream of the dam, crops’ acreages, and water consumption in each irrigation district.

We computed the average values of the 12-month standardized runoff index (SRI) for the 7-year periods (33 periods) from 1976-2015. According to the outcomes, the period of 2007 to 2014 water years, with an annual average SRI value of -1.25, was selected as a period of water bankruptcy for implementation of a proposed simulation-optimization model for multipurpose sustainability of the Droudzan reservoir-river system.
By solving the developed model using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), we generated an optimal trade-off set that contained 637 management alternatives. Each generated alternative offered different values for the objective functions of the model.
There was no socially optimal management option based on the median voting and majoritarian compromise rules. This output revealed that none of the generated efficient management alternatives could obtain the approval of the majority of stakeholders, not only at first ranking level, but at all possible ranking levels (637 levels). Moreover, the compromise set derived by the Condorcet rule was an empty set. The latter output indicated that there was no management option in the generated optimal trade-off set, which agreed upon by all stakeholders through the pairwise comparison procedure.
The output of the plurality rule was a compromise set with four members given the fact that the voting took place between the four aspects of sustainability. Therefore, each of the four identified options by the plurality rule was the most desirable option based on one of the four aspects of sustainability in the system under consideration.
Among applied social choice techniques, only the Borda count and pairwise comparison approaches were able to identify a compromise set with a single member, Management Option No. 87, which could be recognized as the socially-optimal conflict-resolving alternative for the problem under investigation.
According to the conflict-resolving management alternative, the 7-year (the bankruptcy period) average of the cultivation areas allocated to wheat, barley and canola would be 16%, 24%, and 41%, respectively. This management option would supply 46% of the water demand of Bakhtegan Lake. In terms of relative satisfaction, this alternative has the second rank based on three sustainability indicators of the blue water productivity, allocating water for preserving the natural environment, and fair distribution of water among identified socially-optimal management options.

Given the nonlinear and multi-objective nature of the problem under investigation, the output of the developed model was an optimal set of non-inferior solutions that form the trade-off curve between four aspects of sustainability (objective functions) in the Dorudzan reservoir-river system. The current study also attempted to find a compromise solution among generated non-inferior alternative solutions by using social choice rules. Results of the proposed methodology provided valuable information on efficient water governance strategies and how to achieve multi-purpose agricultural and environmental sustainability in the study region.

One of the key issues in the practical planning for water resources is the existence of uncertain factors. One of the approaches for decision making under such circumstances is interval programming. The aim of the study is to develop an interactive optimization model for water and crop area allocation. The developed model comprises four objectives that take into account socio-economic factors, the virtual water content of crops, and meeting environmental water requirements. For solving the model, four crop area scenarios (assumptions) were considered. Results showed that by raising the level of satisfaction threshold on the constraints, the amount of water allocated to each water user is declined. So that from the satisfaction level of 0.65 to the level of complete satisfaction, the model allocates only the minimum amount of water (40 MCM) to meet the environmental water needs. Based on considered scenarios for solving the model, the largest cultivation areas are allocated to wheat and maize for autumn and spring cultivations, respectively. Solving the model in the absence of upper bound for crop areas revealed that the greatest difference between optimal crop area and the highest cultivation area happened was belong to rice with 2777 and 5821.6 hectares in Dorudzan and Korbal districts, respectively. The main advantage of the developed model in the present study is the linear formulation as well as its ability to deal with uncertain parameters. Outcomes of the model provide information required for the assessment of risk and reliability of planning options for water allocation.

Evapotranspiration is one of the most important components of the hydrological cycle which is directly influenced by atmospheric conditions. This study investigated annual and seasonal trends in reference evapotranspiration (ET0) and its key influencing climatic variables during 1966-2005 at 10 stations in southern Iran (with centrality of Fars province). First, multivariate regression analysis was performed to identify the major meteorological variables affecting ET0. Second, annual and seasonal trends in climatic variables as well as ET0 were assessed using the Mann-Kendall test, Spearman''s rho, the Pearson correlation and linear regression to evaluate their contribution to the temporal trend in ET0. Results suggested that the more effective variables for ET0 were wind speed (U2), relative humidity (RH) and sunshine hours (n). Also, the majority of trends in seasonal and annual ET0 were non-significant and after that decreasing and increasing trends had higher frequencies. In addition, distributions of relative frequencies of trend types at all considered time-scales were similar for both parametric and non-parametric techniques. Hence, the disagreement between parametric and non-parametric trend results did not depend on the degree of normality in the annual and seasonal ET0 distributions in the study area.