r. mostafazadeh

Resolving social, economic and ecological challenges, analyzing the relationships between stakeholders and their surrounding environment is one of the requirements for empowering rangeland users. The interaction of humans and nature is defined as socio-ecological systems. Vulnerability, resilience and adaptive capacity have been identified as three characteristics related to the socio-ecological system. Therefore, the main aim of this research is to investigate the spatial changes of socio-ecological systems based on vulnerability, resilience and adaptation capacity criteria. Also, prioritization of the northern rural districts of Ardabil province using multi-criteria evaluation is another objective of the current study.
In this study, the research was conducted in the northern villages of Ardabil province. As per the Iranian Statistics Center's report from 2015, the northern region of Ardabil province comprises four cities: Meshginshahr, Germi, Bilasuvar, and Parsabad, along with 31 rural districts and 980 villages. The total population in this area is 237,907, residing in 61,412 households. The study focused on rural districts as the primary socio-ecological management units. These units encompass rural communities and rangeland ecosystems, each evaluated based on criteria such as resilience, vulnerability, and adaptive capacity. Based on the purpose of the research and different dimensions of socio-ecological systems, the research sub-criteria were selected. Data for the sub-criteria were gathered through mapping, climate data, and questionnaire analysis. To standardize the values across different rural districts, the maximum method was applied due to the varying nature of the criteria. Then, different weighting methods were then employed to evaluate and prioritize the rural districts accordingly.
The analysis results indicate that Shaban and Lahrud rural districts in Meshginshahr county have the highest vulnerability scores (0.871 and 0.867), while Aslandoz and North Qashlaq rural districts in Parsabad county have the lowest scores (0.448 and 0.483). This suggests that Shaban and Lahrud are in a more vulnerable situation compared to Aslandoz and North Qeshlaq. In terms of resilience, central Arshagh and West Qashlaq rural districts in Parsabad county have the lowest values (0.252 and 0.286), while the two western Meshgin and Meshginshahr Ghareso rural districts have the highest values (0.692 and 0.691) among all rural districts. Additionally, the adaptive capacity criterion shows that Dasht and Lahrud rural districts in Meshginshahr exhibit the highest favorability (0.797 and 0.864), whereas Angirlu and South Qeshlaq rural districts in Bilasuvar have lower favorability compared to other districts (0.111 and 0.145). Furthermore, the zoned maps of socio-ecological system index values revealed that when applying equal weighting or adjusting the weight of each criterion, there were no significant variations in the socio-ecological system index across rural districts. Notably, the analysis indicated that the southern rural districts in the research area exhibited more favorable socio-ecological conditions compared to other regions. Consequently, it is imperative to implement robust measures to conserve nature and the environment, provide support to rural communities, and align efforts with sustainable development objectives. This approach will facilitate informed decision-making and effective management of plans and projects aimed at enhancing social-ecological systems.
The results showed that the index of socio-ecological systems of Dasht, Lahrud, Qarasu, Western Meshgin and Eastern Meshgin rural districts in all four weighting approach conditions (with the same weighting, emphasis on vulnerability criteria, emphasis on resilience criteria and emphasis on adaptation capacity criteria) are more desirable compared to other rural districts. Overall, it is important to acknowledge that rural communities face greater challenges compared to urban areas in various aspects. When natural disasters strike, these communities are particularly vulnerable and have limited resources to recover. Therefore, it is crucial for management efforts to focus on maintaining favorable conditions and enhancing vulnerability, resilience, and adaptive capacity in lower prioritized regions. Based on the research results, it is recommended to prioritize intra-regional and inter-regional equity to establish sustainable development and service indicators effectively. Special attention should be given to the spatial and physical organization of rural villages.

The present study aimed to assess the spatio-temporal changes in the natural vegetation cover of Ahl Iman watershed, Ardabil province. For this purpose, land use maps of the three years (2000, 2010, and 2020) were extracted from Landsat satellite images. Then, seven landscape metrics (patch density, edge density, patch richness, splitting index, contagion index, Euclidean nearest neighbor distance, and mean perimeter–area ratio), Normalized Differential Vegetation Index (NDVI), and road density were calculated. Finally, the Disturbance Index (DI) was calculated by the sum of the values of the criteria multiplied by their weight in the 11 sub-watersheds. The disturbance index (DI) was classified into very low (0-87), low (88-163), medium (164-239), high (240-315), and very high (>316) categories. Results showed DI of 177.77, 95.17, and 135.07 for the three studied years (2000, 2010, and 2020), representing a moderate, low, and low disturbance respectively. There was no significant difference between the three years in terms of disturbance. Further, the eastern and northern parts had higher disturbance indices compared to the southern and central parts of the watershed.

Hot spots are often associated with places where an abnormal process has occurred. Accordingly, their identification can help experts and managers to scrutinize the state of health and sustainability, from an ecological point of view. The present study was therefore conducted to analyze the spatial autocorrelation and identify hot spots of 11 landscape metrics, the new Runoff Landscape Index (RLI), and its related factors in 28 watersheds of Ardabil province. The average positive values of the z score obtained from Moran's index indicate the presence of spatial correlation in the studied watersheds. In addition, the results of local Moran's showed that the landscape metrics have a structured spatial pattern and are not randomly distributed. A completely unipolar pattern was obtained for land cover factor (λC), soil factor (λK), and RLI. Furthermore, the negative values of the local Moran's index for the topographic factor (λS) proved the scattered pattern. Spatial distribution of hot and cold spots, using the Getis-Ord-Gi index, showed no significant pattern in the λC of Ahmadkandi, Akbardavod, Deru, Mashiran, Firozabad, Lai, Nir, and Hir watersheds. Cold spots were observed in the Eiril, Namin, and Nanehkaran watersheds at the 90% confidence level and the rest of watersheds had hot spots at a 95% confidence level. The RLIs of Ahmadkandi, Akbardavod, Deru, Mashiran, Firozabad, Lai, Nir, and Hir watersheds lack a significant pattern, and the rest of watersheds showed the hot spots at a 95% confidence level.

The aim of the study was to determine the most important environmental factors (topography, climate, and soil) affecting changes in production and canopy cover of plant variations and to prepare prediction maps, based on the most important factor, in semi-steppe rangelands of Hir-Baghrou, Ardabil province, Iran. First, by detecting the vegetation types and different classes of environmental factors, the production and canopy cover were estimated in 1-m2 plots at full flower stage of dominant species. Then, to determine the most important environmental factors, affecting the production and canopy cover changes, the principal component analysis (PCA) was used. For modeling, first, the correlation between the most effective environmental factors was obtained from the PCA. Then, the highly correlated factors were eliminated and the quadratic polynomial models were obtained. Finally, the obtained models were simulated in GIS. The results of the PCA showed that the first six components with 71.65% had the greatest effect on the production and canopy cover changes. Based on the root mean squared error (RMSE), simulating maps of production (RMSE=0.76) and canopy cover (RMSE=0.48) by effective factor (annual precipitation) showed the highest accuracy. The results of this study can be used to manage the rangelands of Ardabil province to create a balance between supply and demand of production and also to balance carbon.

Following the unbalanced development and overexploitation of the country's watersheds, land fragmentation has become a major concern for the conservation of ecosystem services and land health. For this purpose, the present study was planned to evaluate and compare the landscape connectivity indices of KoozehTopraghi Watershed as one of the ecologically susceptible watersheds located in Ardabil Province. To this end, the landscape connectivity was investigated according to both structural and functional viewpoints, based on the green patches (rangelands and orchard) distributed at 36 sub-watershed areas. The mentioned indices were first calculated using the Fragstats Software and graph theory at each sub-watershed; then, they were standardized according to interval standardization between zero and one in order to consider the scale effect and draw a comparison in the same variation range. Therefore, the landscape connectivity was calculated, classified and mapped for each studied  sub-watershed and the whole watershed. Structural connectivity results showed the high level of landscape connectivity between green patches in all studied sub-watersheds. In addition, the results showed that the landscape connectivity was obtained with the mean and standard deviation of 0.50 ± 0.52, being varied from 0.50 to 0.97. The results also proved that out of the 36 sub-watersheds located in the KoozehTopraghi, only 15 sub-watersheds had natural lands (orchard and rangelands). Also, the sub-watershed 27, with the highest value of landscape connectivity (0.97), had the highest priority.

Analysis of river flow master recession curve is a way to assess the occurrence of hydrological drought.The purpose of this study was to inverstigate the master recession curve preparation of daily flow discharge.The master recession curve represents the nature of flow discharge,flow contribution sources,flowrecission through the river. The shape of master recession curve used to analyse the hydrologic regime,watershed response,groundwater contribution in river flow discharge. The daily flow river of Nirchaiwatershed have been used in this study through a 36-year of recorded data. The MRCs in different regressionequations (Linear,Exponential,Logharithmic,and Multinominal types) were extracted using a Visual Basicprogram (Posacev 2006) in excel environment,The constant coefficients,curve slope were defined andthen,the coefficient of determination of different MRCs were calculated. Based on the results,the bestMRC regression were selected (R2,0.91). The curve slope,constant values were estimated to be -0.07and 0.443,respectively. These coefficients,indicates,its comparisons in different rivers can be usedto investigate the hydrologic regime of the watersheds in different conditions.

The aim of this study was investigating the impacts of Bukan's Dam construction on hydrological indices based on the Flow Duration Curves (FDCs) of the Zarrinehrood River during the pre (1955-1971) and post-dam (1972-2011) construction periods. For this aim, nineteen hydrologic indices were calculated in four groups of Peak Flow, Flow Duration, Low Flows and Flow Variability. In this regard, the Flow Duration Curves were plotted for both pre and post-dam construction periods. Based on the results, the values of 1-day maximum flow and the average of daily flow in the post-dam construction period decreased by 13% and 7.5%, respectively. However, the values of the index for 1-day minimum flow in the post-dam period increased by 4.7 percent. The results showed that at 50% of the flow duration time in post dam construction period the amount of discharge was increased 40%, which related to the impact of the dam on the flow of the Zarrinehrood River. The average magnitude of the rising rate relative to the average flow discharge in the pre and post periods of the dam were 97.71 and 79.18 cubic meters per second respectively, which indicated a 18% decrease in the flow of river flooding during the period after the dam construction. In the post-dam period, the average amount of discharge increased in summer season. In conclusion, the construction of the dam had reduced the flood variation related indices and increased the indices of the flow related to the duration components.

The aim of present research is landslide hazard zoning using Bayesian theory in a part of Golestan province. For this purpose, landslides inventory map was created by landslide locations of landslide database (392 landslide locations). Then, the maps of effective parameters in landslide such as slope degree, aspect, altitude, slope curvature, geology, land use, distance of drainage, distance of road, distance of fault, stream power index (SPI), sediment transport index (STI), and rainfall were prepared in GIS environment. Relationship between effective factors and landslide locations were considered using Bayesian probability theory. In the next step, parameters classes weights were found and the landslide susceptibility mapping was achieved by fourteen modeling approaches (using whole parameters and deleting parameters one by one). The verification results by ROC curve and 30% landslide locations showed that the Bayesian probability model has 71.37% accuracy for the second approach of modeling in the study area.

Development of surface water monitoring networks is a critical factor in the assessment and protection of water resources. This study focuses on evaluating the effectiveness of surface water quality monitoring network and identify monitoring stations and water quality parameters which are important in assessing annual variations of water quality in Gorgan-roud River, Golestan Province. Cluster Analysis (CA) was used to monitor station grouping and Principal component analysis (PCA) and principal factor analysis (PFA) techniques were used for Assessment of water quality monitoring stations. The analysis of water quality data from nineteen water quality monitoring stations over a 12-year time period indicated that three monitoring stations (Taghi-Abad, Shir-Abad, and Nodeh) were identified as less important in explaining the annual variance of the water quality parameters. Also results revealed that total hardness and EC are most important parameters at first component and in the second component, pH and HCO3 are appropriate for assessing variations of water quality parameters in the Gorgan-roud River.