No abstract

Soil is a living, dynamic and non-renewable source in lifetime which is vital for food production and the global balance of ecosystems. Every year more than 75 billion tons of soil erodes from the surface of earth. Taking care for this, appropriate methods needed to prevent erosion and sediment movement, which in its turn requires the presence of information about erosion intensity in the basin. Lack of statistical data and information on soil erosion and sediment production in Zemkan basin located in the West of Kermanshah Province, is an issue that paved the way to carry out this study with the aim of identification of erosion rate and sedimentation production and exploring sensitive areas of erosion. To achieve the above-mentioned aim, there was used the erosion potential method (EPM) using of geographical information system (GIS) to reduce errors and increase the relative accuracy in the analysis of the model. Required data in this study were prepared through field observations, existing maps, statistics of meteorological and hydrometric stations and library resources. After inputting maps into the ArcGIS software environment and geo-referencing them, required layer was digitized and there created database for them. Finally, using standard tables provided in the EPM model, accordant values for the basin extracted and incorporated into the layers according to the relations given in EPM model, map of erosion intensity zoning, erosion and sediment ratio calculated for the basin. Results showed that the rates of especial erosion (WSP) and especial sediment are (GSP), 2742.02 and 1005.55 m3/Km2/y respectively. Class and intensity of erodibility of basin were also identified as very intensive (V). Therefore, different policies of erosion control in the basin are necessary.

Although Zagros forests in western Iran lack industrial timber value due to the severe climate and socioeconomics problems, non-timber products are of great value and importance due to their high economic potential and also their potential to improve the welfare of forestdwelling and forest-fringe villagers. This study was done in the forests of the Zemkan basin, an important part of central Zagros forests, Iran, to recognize the non-timber forest products (NTFP S), investigate their potential economic value and role in people's livelihood. Data, collected using forest cruising, participatory observations, interviews with indigenous and local persons and experts, identified wild pistachio resin, wild pistachio fruit, oak fruit and oak syrup (Shokeh manna) among the non-timber products in this basin with total potential harvestable NTFPs of 77.16, 771.602, 13248.68, and 1324.868 tons per year, respectively. The economic rent from NTFPs is 33 US$/ha/ year and its total expected values with consideration of real interest rate when the exploiter invests the capital in the bank (6.4 %) and when money is borrowed from the bank to execute the incorporated projects (8.4 %) are $516/ha and $393/ha, respectively. Furthermore, families' economic share from potential profit of NTFPs is annually $601 per household. In addition wild pistachio resin has the highest share of the total potential profit of NTFPs and its equal to 51 % of the total of potential profit of NTFPs. Therefore, it is suggested that decisions be made to increase the infrastructure and strengthen the local selling market to enhance the cash income from NTFPs. Forest participatory management practices are suggested to organize and improve traditional use of the forests.

This study aimed to identify and select areas suitable for ecotourism. In this research, to assess the potential of ecotourism of Masal district, Fuzzy Analytical Hierarchy Process (FAHP) and GIS were used. For this purpose, appropriate evaluation criteria and sub-criteria were identified for determining recreational potential. Then, using AHP fuzzy, criteria and sub-criteria to determine the importance of assessing the potential recreational area prepared questionnaires and, were distributed among clinicians. Weighted criteria and sub-criteria in each questionnaire were calculated and by averaging the weights, final weight was calculated using the model. The required maps for evaluating of the recreational potential were generated by using GIS software and then these data layers were standardized using pertained function in IDRISI. Finally, the final map of recreational potential was prepared. The results of the final map of ecotourism potential showed that 89.97, 8.61 and 1.42 percent of the total area have very high, low and no potential for ecotourism activities, respectively. Areas with a high density of vegetation and water resources with suitable climatic conditions have the greatest potential for ecotourism activities in the study area. Area with low and poor ecotourism potential are central and eastern parts of the region, and there are low density of ecotourism activities and facilities in this area.

The construction of new breakwaters in Anzali port has had a significant impact on the water body of the Anzali international lagoon. The Anzali wetland is under threat from sediment influx from mountainous regions, and the study used satellite image processing to demonstrate how the construction of new breakwaters impedes the natural transfer of sediment from the lagoon to the sea. The methodology employed a hybrid approach combining two methods: normal water index (MNDWI) and supervised classification (SVM) to detect sediment accumulation in the wetland water zone. Following the construction of new breakwaters in 2009, an island formed and expanded exponentially in parts of Sorkhankol Wildlife Sanctuary's water body. This phenomenon is attributed to decreased water flow caused by increased cross-section current and volume of water, creating a dam-like function against channel flow leading to the sea. Consequently, sediments and suspended loads settle in Sorkhankol's water zone, leading to an increase in island area from 0.39 hectares to over 26 hectares during the studied period. Result showed Kappa coefficients by SVM algorithm for years 2002, 2010, 2012 and 2017 which were found to be 0.76, 0.62, 0.71 and 0.86 respectively indicating that SVM outperforms MNDWI in effectively monitoring landform changes.