behzad moteshaffeh

Conservation of water and soil resources is necessary and inevitable for sustainable development. Planning is necessary for achieving this development both now and in the future. In this regard, the human relationship as a beneficiary of the natural ecosystem should be at the top of policies and comprehensive management of water resources. Based on this, the requirement for successful management of water resources is to change the approach towards cooperative management. The success of watershed projects entirely depends on people's participation in the decision-making, implementation, and conservation of the projects. One of the main components in water resources management at the local level is the local stakeholders and their interactive relationship between them and the government institutions is necessary for forming a cooperative mechanism of water resources. In this regard, social networks can be effectively used in collaborative management. The purpose of this study is to analyze the social network of water and soil resources stakeholders in Khaeiz and Ghale Seyed Moghim villages and to determine the main strengths of the network in order to apply successful collaborative management of these resources.

In the current research, social network theory and its principles were used to investigate and analyze the pattern of relations between the stakeholders of water and soil resources in Ghale Seyed Moghim and Khaeiz villages. First, using a local survey and a questionnaire, trust, and participation data were collected based on the Likert scale (zero, very little, low, medium, high, and very high), and a matrix of trust and participation relationships was formed, and the matrix of trust and participation relations was formed. Then, different network indicators in macro (including density, concentration, and size of the network, degree of ambidexterity and transferability of links, average geodesic distance, and E-I index), meso (including indicators of peripheral center and density of subgroups) and micro (including input degree centralities, output and intermediate) levels were calculated and evaluated using UCINET software.

Based on the calculated indicators, the network of beneficiaries in both villages is stable and balanced. Therefore, it is possible to plan to preserve water and soil resources well. The network of the stakeholders in Ghale Seyed Moghim village is more cohesive, which will be more effective in cooperative activities in the matter of local sustainable development Instead, people in Seyed Moghim villages were able to connect with each other more quickly, and building trust as well as their collective activities takes place in less time. Also, key actors were identified in both networks and should be involved in the decision-making and participatory management of water and soil resources in the region.

Social network analysis provides managers with an effective tool to identify users and their relationships, making water resources management efficient. Considering the results of network cohesion in Khaeiz, non-key actors should be encouraged to create trust and partnership bonds. Also, through educational and promotional activities, the existing participation and trust in the networks should be maintained, and the opportunity to create new trust and participation of stakeholders should be provided.

Achieving basin runoff estimation requires a more realistic simulation of the precipitation process. Simulation closer to the reality of the process has always been the goal of the researchers. How the first starting point of runoff at the basin level is, leads to different patterns, therefore, is effective in the accuracy of the process simulation. The lagged pattern of flow formation in the catchment area, due to the assumption of the formation of the flow from the center of the surface, is closer to the current flow reality than the conventional pattern in simulation, such as HEC-HMS. The present study was designed to evaluate the latent pattern in the catchment area of the Roudzard River, comparing it with the conventional model in the HEC-HMS simulator. The results showed that the lagged pattern, in contrast to the conventional model, increased the number of parameters for the three rainfall events, the values of the Nash and PWRMS were 0.13, -37.0, -0.08 and 2.49, 8.35, 6.41 respectively Which had a lower accuracy in comparison with the values of them such as 0.57, 0.68, 0.43 and 1.03, 6.96, 3.87 in the conventional pattern. However, sensitivity analysis of the parameters indicated the type of pattern is different in the relative sensitivity of the parameters. As in the delay pattern, the K parameter is more sensitive than the conventional pattern compared to the CN parameter. Comparison of two selected patterns in estimating flood volume showed that the delay pattern has a better performance than conventional pattern.

Floods are one of the most important natural hazards that have caused economic and social damage in most areas. Numerous climatic, hydrological, geomorphological and geological factors are involved in the occurrence of floods. Flood analysis, management and control can be done by preparing flood potential maps. The purpose of this study is to map the flood potential of Maroon watershed using random forest and support vector machine machine learning methods. For this purpose, 16 effective parameters in flood occurrence including altitude, slope and aspect, curvature, geological formations, land use, curve number, rainfall, temperature, stream power index )SPI), topographic wetness index )TWI), distance From stream, stream density, road distance, road density and NDVI index were considered. The mentioned parameters were prepared in ArcGIS 10.8, ENVI 5.3 and SAGA GIS 7.2 software environments and then converted to readable format for R software environment in order to implement the support vector machine and random forest models. Finally, RF and SVM models were implemented using SDM packages and evaluated using receiver operating characteristic )ROC). The results showed that RF and SVM models correctly predicted the flooding map of Maroon Basin with 0.997 and 0.947 percent accuracy, respectively

Soil erosion is a natural and global threat to water and soil resources. One of the most important effective factors in increasing soil erosion is changes in land use due to human activities. In this study, the impact of land use change on soil erosion in the town of Behbahan was studied using the RUSLE model in the Geographic Information System (GIS). In order to extract the final soil erosion map, the parameters of the RUSLE model consisting of R, K, L, S, C and P were first prepared for the years 2000 and 2021. These parameters were then converted into GRID format and the soil erosion map was obtained at the pixel level in the area by several of the parameters. Results from the erosion map in 2000 and 2021 indicated that the extent of soil erosion has increased over time. In 2021, the highest amount of erosion using the RUSLE model prediction is more exclusive to streams and rivers, although there is erosion across the region in different forms. The largest area in the region is classified as low erosion risk, which should be considered in planning. Among the effective erosion factors, the rain-induced erosion factor was high in the northern parts of the upstream region. Land use maps also show reduced vegetation at the soil surface. It causes a change in the number of efficient parameters in the model and thereby affects the amount of erosion in the region. Vegetation cover decreased from 2000 to 2021. The area of residential and agricultural land has increased, resulting in a reduction in natural land surface cover, and as a consequence, soil erosion conditions due to the impact of raindrops are increasing.

As a dreadful natural disaster caused by a severe reduction in precipitation rate, drought brings about, compared with other natural disasters, far-reaching spatial and temporal consequences, incurring severe damages. On the other hand, in late the 20th century, drought monitoring approaches underwent a paradigm shift, and advances in remote sensing and earth observation technologies allowed observations and monitoring of key drought-related variables over larger temporal and spatial scales than what the then conventional methods had already made possible. There are different remote sensing indices used to assess drought, including the PDI index which has been developed based on the spectral patterns of soil moisture changes in the NIR-Red space using the red and near-infrared bands of the ETM+ sensor. Therefore, as Khuzestan province is suffering from drought consequences, including but not limited to dust storms and economic difficulties, this study sought to identify the spatial and temporal trends of drought in the center of Khuzestan province.

The study area is located in southwestern Iran and the center of Khuzestan province at 31° 0ʹ 17ʺ to 31° 43ʹ 69ʺ N latitudes and 48° 35ʹ 51ʺ to 49° 32ʹ 2ʺ E longitudes covering an area of 7635/36 km2. To conduct the study, some twenty ETM+ remote sensing images of level-1 data taken from 1999 to 2018, (path/row 168/35) were collected from the United States Geological Survey website.After gathering the required data, some 411 random points were selected on the collected images, the pixel values of red and near-infrared bands were extracted and plotted against each other, and the slope of the best-fitted line, known as the soil line, was obtained. Then, the PDI drought index values were calculated using the slope and the values of the aforementioned bands. Finally, by applying a natural break classification method, different degrees were separated, and the drought’s trend of spatial and temporal changes was identified using Mann-Kendall's seasonal trend test at different significance levels.

The results of the spatial trend analysis of drought suggested that the trend was significant only in low drought and non-drought conditions. For the non-drought conditions, the probability of spatial changes was lower than the confidence level at 5% and 10% significant levels, indicating the significance of the conditions at these two levels, and thus, rejecting the null hypothesis at merely the 1% level. On the other hand, as the low drought conditions showed significant spatial changes only at the 10% significant level, the null hypothesis is rejected at the 1% and 5% levels. However, moderate and severe drought conditions revealed no trends in terms of spatial changes due to the higher probability values ​​of 0.28 and 0.3, respectively, which were higher than the determined significance levels. Moreover, the results of temporal trend analysis indicated no trend for the non-drought conditions, considering the fact that the null hypothesis was rejected at all significant levels. On the contrary, in the moderate drought conditions, a temporal trend was confirmed at all significant levels with the probability rate of 0.006 which was lower than all the assigned levels. Also, a temporal trend was found at low and severe drought conditions at 5% and 10% significance levels with a probability rate of 0.023 and 0.014.

The spatial analysis of the drought trend suggested that only the area with non-drought conditions had a significant increasing trend, which could be justified by the increase in the area of ​​irrigated land around water bodies in the area, especially around the Karun River in the west of the study area. The reduction in the area of land in the northeast of the study area with the low-drought conditions could be attributed to the rangeland degradation containing low and moderately dense vegetation.Moreover, the status of drought conditions in some sandy areas has changed from low in 1999 to moderate in 2018 due to vegetation destruction. The decreasing and increasing trends in areas of land with moderate and severe drought conditions, respectively, indicated the worsening of the drought conditions in the study area. Taking the changes in the drought index into account, it could be said that merely the areas with non-drought conditions remained unaffected by any significant increase or decrease in drought conditions, considering the fact that such areas are mainly wetlands, irrigated farms, and fish farms (that are naturally wet).However, the trend of the drought index value was found to be (highly) significant for other drought conditions, especially for moderate-drought conditions, indicating an increase in the severity of the drought conditions during the studied years. The frequent occurrence of dust storms in Khuzestan in recent years suggests that the results of this study correspond to the current reality of the region. In fact, it could be argued that during the last decade, the exacerbation of climate change and drought conditions on the one hand, and the development of construction projects and excessive extraction of water resources, on the other hand, have led to the dryness of many wetlands and wet areas, thus creating small deserts which are regarded as the main sources of dust storms in Khuzestan province within the past few years. Moreover, according to the findings of recent studies, desertification and drought trends have been increasing in recent years, indicating a great increase in the significance level of desertification in number 3 and 4 desertification centers in the east and southeast of Ahwaz, and a significant increase in the severity of drought conditions. This study proved the efficacy and applicability of the PDI drought index in drought monitoring.