نشریه مرتع و آبخیزداری
سال هفتاد و چهارم شماره 1 (بهار 1400)

The complexity of the urban environment makes it difficult to consider all the vulnerable components of the urban. Hence, decision-making in urban environments is one of the most important issues in modern management. As a result, the purpose of this study is to investigate the urban vulnerability of Azimiyeh in Karaj to flood based on multi-criteria decision-making method. The statistical population includes specialists who had sufficient knowledge and experience in the field of vulnerability management in urban areas. To this research, first, comprehensive knowledge of the factors affecting the urban vulnerability to floods was obtained using library studies, and then, the results of the Delphi technique, , was shown that among the primary indices, a total of 11 effective indicators were selected and a map of each of them was prepared using ArcGIS software. Then, the urban vulnerability to floods was calculated using the TOPSIS method. The study area was divided into 13 sub-areas based on runoff directional pattern and field observations, and then the decision matrix was made according to 13 sub-areas and 11 indicators. The results showed the vulnerability of this region to floods, which among the studied sub-areas, in sub-areas No. 1 and 2 observed the highest of flood vulnerability and the lowest of it observed in sub-area No. 13. Causes of flood vulnerability in the region include a direct connection to the upstream catchment that has lithology impermeable and geologically impermeable, high-density of building and population, and lack of proportionate open spaces.

Heavy metal pollution is one of the most serious environmental problems that is spreading around the world. The purpose of this study was to determine the rate of pollution and enrichment of heavy metals inside and around the industrial town of Shiraz. For this aim, 20 surface soil samples were gathered from a depth of 0 to 15 cm from inside and around Shiraz industrial town, and the concentrations of Pb, Cr, Al, Mn, Cu, Zn, St, V, N, Co, Sc, Fe As was evaluated using the ICP-method MS. The results showed that the average concentrations of Cu, Pb, Mn, Cr, Al, Zn, St, V, Ni, Co, Fe, As and Sc are 75, 87.9, 541.6, 143.3, 21804.8, 275.4, 439.9, 173.3, 55.4, 12.0, 50579.3, 4.8, and 4.7 mg / kg, respectively. The results showed that the average concentration of all elements except Al (21804.8 mg/kg) and Sc (4.7 mg/kg) is much higher than the concentration of these elements in global soils. In addition, Cu, Pb, Zn, V and Cr show much higher concentrations than standard Chinese and Canadian standards. Calculation of the enrichment coefficient of the mentioned elements in soil samples indicates high enrichment of Cu (8.32), Pb (5.42), Zn (7.04), St (5.15), V (5.04), and Cr (5.34). The results of the present study indicate that the soils of the region are contaminated with Cu, Pb, V, Mn and Zn. Therefore, it is suggested to reduce metals in the environment by different methods.

The purpose of this study was to compare machine learning models including Support Vector Machine, Classification and Regression Tree, Random Forest, and Multivariate Discriminate Analysis to prioritize susceptible areas to dust production. To determine the dust days, hourly meteorological data of Alborz and Qazvin provinces and satellite images of the same days for the period 2000 to 2019 were used. 420 dust collection points were identified and the map of their distribution was prepared. The maps of factors affecting the occurrence of dust, including landuse map, soil orders map, slope map, slope aspect map, elevation map, vegetation map, topographic surface moisture, topographic surface ratio, and geology mam were prepared. Using the mentioned models, the impact of each of the effective factors of dust was determined and prioritization maps of dust harvesting areas were prepared. Models were evaluated using the ROC curve. According to the results, the elevation factor is more important in all models than the other parameters used in the model. The modeling results also showed that the Random Forest )RF( and Multivariate Discriminate Analysis (MDA) models had the highest values of accuracy (0.96), precision (0.94), Probability of Detection (POD) (0.98), and False Alarm Ratio (FAR) (0.051) compared to the others. The performance of the RF and MDA models is better than the other models, followed by the Support Vector Machine (SVM) and Classification and Regression Tree (CART) models, respectively. Also, in evaluating the models using Receiver Operating Characteristic (ROC), the RF model was selected as the best model.

Water is a source of life, even when it is abundant. In the last few years, the unreal certainty of water services in Iran has caused institutional structures of water to be unsuitable and incompatible with environmental changes, and when water-related crises such as drought, flood occurrence and in the larger scale, climate change, are capable of flexibility and resilient in the face of these changes. In this regard, the recognition of the present governance system in the country is considered essential. Therefore, in this study, mode and regime of water governance were studied in one of the problem areas of water scarcity. In order to determine the mode of governance, questionnaires were used in two levels of the institution and local stakeholders. In order to determine the regime of governance, formal and informal institutional network analysis method was used in the Arsanjan, Neyriz, Kherameh and Estahban counties. The results of the governance mode showed that in ten sub-functions of governance under consideration, the more hierarchical mode has been observed. In addition, the results of the analysis of the institutional network also showed that the current governance regime in all four counties is a centralized (Rent-seeking) regime, which is considered a hierarchical governance mode feature. Finally, the combination of methods of governance and arrival to meta-governance is proposed.

In this study, water use efficiency index (WUE) was used to assessing the effect of drought on the carbon and water cycle. To calculate this index, we used the gross primary product (GPP) and evapotranspiration (ET) products obtained from the MODIS sensor, and the trend of their changes and reaction of this index to drought were calculated for the period 2017-2001 in Fars province. Finally, we assessed the land degradation and desertification in different land uses for study area. The results showed that the indices of evapotranspiration, GPP, water use efficiency, and drought increased by 75.25%, 29.9%, 78.51%, and 67.23%, respectively. The effects of drought on evapotranspiration in agricultural lands and grasslands showed more than 67% positive relationship and also, in these land uses, we observed a significant positive relationship (33.4% and 12.5% for the agricultural lands and grassland, respectively). However, in shrubs lands, and savannas, it is more than 66.6% and 87.5%. The effect of drought on water use efficiency in grassland showed that more than 87% of these areas have a positive relationship. The effectiveness of water use efficiency in plants shows a positive relationship in 40.9% in this area, of which only 0.9% has a significant positive relationship. The negative relationship of this land use is about 59.1% of it. Of this negative amount, only 1.6% of the area had a significant negative relationship. The study of this relationship in the use of savannas shows 75% of this area, which includes 1.5 square kilometers.

Rapid population growth and the need to provide the necessities of life has caused human beings to change land use widely. In many cases these changes have been accompanied by disruption of balance in nature and providing the possibility of soil erosion. This study was carried out to investigate the effect of land use changes on increasing the intensity of wind erosion. Landsat satellite imagery and implementation of supervised classification by using SVMs were used to prepare land use map. Ground surface temperature was calculated, as one of the effective factors in wind formation, with single channel and split window algorithms in different land uses. In order to make connections between land use changes and wind erosion, effective climatic parameters such as temperature, relative humidity and maximum wind speed were investigated. The highest surface temperature was observed in poor and non-vegetation areas, and the lowest temperature was estimated in highlands and rangelands. Results showed an increase in average temperature as well as maximum and minimum absolute temperature and decrease in relative humidity. Over the past decade, the maximum wind speed in the study area showed a significant increase, and it has increased from eight m/s in 1990 to more than 20 m/s in the last decade. This shows that land use change by removing vegetation cover, as well as the uncontrolled increase of human constructions and creating thermal islands in the last 30 years, has a significant impact on the emergence of climate change and increasing wind speed.

Soil organic carbon is one of the most important indicators of soil quality. The purpose of this study is to study the spectral and non-spectral behaviors of soil in order to estimate the organic carbon of topsoil using factor analysis and multiple regression methods in the semi-steppe rangelands of Asuran, Semnan province. Soil sampling was performed using stratified random sampling method. After creating a map of homogeneous units in the area, in each homogeneous unit according to its area, several sampling points were selected completely randomly. A total of 145 sampling points were collected. At each sampling point, a composite soil sample (a mixture of 9 observations) was taken. Soil organic carbon was measured using Valkyli-Block titration method. Data of 114 samples were used to calibrate the model and data of 31 samples were used to validate it. The results showed that the correlation of spectral variables obtained from Landsat OLI sensor with surface soil organic carbon is higher than non-spectral variables obtained from 1: 25000 topographic maps. Also, the results of factor analysis by principal component analysis with eigenvalues greater than one showed that the total cumulative variance explained by 14 variables was equal to 90.2%, which was explained by three factors. The regression equation generated by the three extracted factors had suitable potential for predicting surface soil organic carbon (R2 = 0.59). The root mean square error (RMSE) of the proposed model was calculated to be 0.3.

With rapid growth of urban construction and urbanism as well as creation and development of infrastructure, flooding in urban areas has become more controversial. Occurrence of urban flood hazards in human settlements causes irreparable damages to the citizens. Therefore, in order to decrease the psychological and social impacts of urban flooding, attention to resilience approach of urban flood is discussed. The study of literature shows that enhanced resiliency against natural disasters is affected by social, economic, physical and managerial factors. Accordingly, the main objective of this study is to investigate the mentioned structures on resiliency of Tehran metropolitan area against urban flood. The methodology of this study is practical and in terms of survey and descriptive - analytical. The results of the study showed that in terms of socio - cultural index, the most favorable areas were identified. In terms of economic index, according to the components of the relevant component, the study area is the most desirable areas in terms of economic resilience. Also, managerial - institutional resiliency has been the most suitable areas in terms of managerial - institutional resiliency. In the physical resilience, according to the structure of the region and using wlc and ahp methods, it was found that the strengths and weaknesses of the region have a good physical resilience.