Mehdi Ghorbani; Seyed Amirhossein Garakani; Mina Hamidi; Sajad Amiri; Majid Rahimi
Abstract
Social capital is defined as a set of relationships, networks, trust, needs, and participatory systems within a society that enables it to confront challenges and improve the living conditions of its members. This study was conducted to analyze the intra-group social capital in three villages: Eskelabad, ...
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Social capital is defined as a set of relationships, networks, trust, needs, and participatory systems within a society that enables it to confront challenges and improve the living conditions of its members. This study was conducted to analyze the intra-group social capital in three villages: Eskelabad, Eslamabad Kalleh-ye Espid, and Chah-e Ahmad in Tafatan city. Given the importance of participatory management and strengthening social capital, analyzing the link between trust and participation among individuals in these villages is essential. The network analysis method was used to examine the links of trust and participation among individuals and villages of interest. The results before the project implementation showed low levels of trust, participation, cohesion, and social capital. However, after the project implementation, these indicators improved, and trust, participation, and the speed of interaction among individuals increased. The project implementation has led to increased unity and cohesion among village residents, increasing the intra-group social capital. In other words, improved communications have led to increased social welfare and the expansion of trust and participation among the residents.
Elham Mehrabi Gohari; Roghaye Shahriyaripour; Ahmad Tajabadipoor; Seyed Roohollah Mousavi
Abstract
This study aims to evaluate and compare the efficiency of Artificial Neural Network (ANN), Regression Tree (RT) and Neuro-Fuzzy (ANFIS) models using a digital soil mapping framework to predict soil texture in a part of Sirjan province. Sampling was carried out at 84 observation points with a regular ...
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This study aims to evaluate and compare the efficiency of Artificial Neural Network (ANN), Regression Tree (RT) and Neuro-Fuzzy (ANFIS) models using a digital soil mapping framework to predict soil texture in a part of Sirjan province. Sampling was carried out at 84 observation points with a regular grid of 2x2 km, and soil texture components were determined from the soil surface depth of 0 to 30 cm. Auxiliary variables included primary and secondary derivatives of the digital elevation model (DEM), a geomorphological map and remote sensing (RS) spectral indices. The appropriate variables selected using the Principal Component Analysis (PCA) feature selection method. Based on PCA, eight topographic variables and six vegetation indices and spectra from RS selected to predict soil texture components (sand, silt and clay). The efficiency of the models was evaluated using coefficient of determination (R2), mean error (ME), root mean square error (RMSE) and normalised root mean square error (nRMSE). The RMSE values in the neuro-fuzzy model compared with the regression tree model. The results of the neuro-fuzzy model were 1.43% for clay, 1.98% for sand and 2.1% for silt, which were 4.32%, 5% and 4.54% lower respectively compared to the regression tree model. The results of this study showed that the ANFIS model was more accurate in predicting clay, silt and sand compared to ANN and RT. Also, the geomorphology map, topographic wetness index, multi-resolution valley bottumn flatness index and Landsat 8 bands 5 and 6 had the highest relative importance in predicting soil texture components.
Leila Biabani; Hassan Khosravi; Gholamreza Zehtabian; Esmaeil Heydari Alamdarloo; Behzad Raygani
Abstract
Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. Wind erosion is a significant cause of ...
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Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. Wind erosion is a significant cause of land degradation and desertification, negatively impacting the economy, society, and environment, particularly in arid and semi-arid regions. To control and reduce the effects of wind erosion, the first step is to identify sensitive areas. The aim of this research is to identify areas susceptible to wind erosion using the ILSWE model in the watershed regions of the Dar Anjir-Saghand Desert, Namak Lake, and Sefidrud. This model has been calculated by combining five erosion indices, including climate erosivity, soil erodibility, surface crust, vegetation cover, and surface roughness. The model's results indicate that climatic factors, such as precipitation, evaporation, and wind, vary across these regions. These factors play a significant role in determining areas that are susceptible to wind erosion. It is noted that other factors, including differences in vegetation cover, soil characteristics, topographic conditions, and the extent of bare lands, salt marshes, sandy dunes, low-density pastures, and rainfed agricultural lands, have also influenced the results of this. In general, this study presents a new method for identifying wind erosion-sensitive areas in various climates. This method can prioritize regions that require further research and corrective measures.
Mohammad Gholami; majid kazemzadeh
Abstract
The inappropriate utilization of water resources has led to water shortages and numerous challenges for humanity. Assessing water scarcity can significantly contribute to sustainable water resource management. The Water Poverty Index (WPI), as a composite tool, assesses the factors affecting the water ...
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The inappropriate utilization of water resources has led to water shortages and numerous challenges for humanity. Assessing water scarcity can significantly contribute to sustainable water resource management. The Water Poverty Index (WPI), as a composite tool, assesses the factors affecting the water condition in a specific area using five critical criteria: Resources, Access, Capacity, Use, and Environment. in the present study, Razavi Khorasan province was divided into 22 study areas, then the water poverty index was used to assess the water scarcity in each of them. WPI results revealed that the Darghz study area scored 50.63, indicating the best water condition, while the Kashmir study area, Red Mountain, and Khalilabad had the worst water conditions, scoring 20/20 compared to other regions. The average of WPI for the entire province was 34.41, indicating an unfavorable state of water scarcity in this region. The average values for the five criteria—resources, access, capacity, consumption, and environment—across the entire province were 19.41, 36.35, 31.23, 38.06, and 47.05, respectively, that according to Use and Resource criteria, water utilization in this province exceeds available water resources by a factor of 1.96. According to this, overexploitation of water resources, particularly in the agricultural sector, and neglecting sustainable development and resilience thresholds of natural ecosystems were identified as significant management strategic mistakes contributing to water scarcity in this province. Therefore, make a balance between water utilization and available resources, allocating a portion of water for the natural ecosystems requirements, and reducing economic reliance on agriculture, can serves as a roadmap for water resources management to effective water resource management and prevent further deterioration of the current situation.
Zainab Afzali; Somayeh Amirtaimoori; Mohammad Reza Zare Mehrjerdi
Abstract
Rangelands play an important role in the sustainability of the ecosystem and providing financial support to many people in the world. Rangelands destruction has caused many concerns at the global level. The results of the studies show that the level of rangelands, rangeland productions and the satisfaction ...
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Rangelands play an important role in the sustainability of the ecosystem and providing financial support to many people in the world. Rangelands destruction has caused many concerns at the global level. The results of the studies show that the level of rangelands, rangeland productions and the satisfaction of rangeland users have decreased in Iran. Therefore, the purpose of this research is the pathology and complications of range management policies in Iran towards sustainable exploitation of rangelands. This research is applicable in terms of nature and purpose and mixed (qualitative-quantitative) in terms of research strategy. In the qualitative part, using the meta-synthesis method, the complications of pasture policy towards their sustainable use was determined, and then based on that, a research questionnaire was made and then based on the Delphi method, relying on the opinions of academic experts, for The significance of revealed complications was used. Also, in the qualitative part, articles related to the research topic in the last 15 years (2008-2023) were used, and the criteria for selecting sources was based on the theoretical saturation of the data. The statistical population of quantitative part was academic experts familiar with the subject and interested in cooperation, who formed the Delphi panel. In order to achieve the goal of the research, the opinions of 9 experts were used, and their selection was based on non-probability snowball sampling. The findings of the research indicate that 12 complications can be introduced as the main complications of range management policies in Iran.
Farzaneh Parsaie; Ahmad Farrokhian Firouzi; Masoud Davari; Ruhollah Taghizadeh-Mehrjardi
Abstract
Mechanical properties of soil, such as shear strength and penetration resistance, play a crucial role in optimizing crop productivity and proper soil management. The objective of the research was to produce digital map of soil shear strength and penetration resistance in Kielaneh watershed, located in ...
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Mechanical properties of soil, such as shear strength and penetration resistance, play a crucial role in optimizing crop productivity and proper soil management. The objective of the research was to produce digital map of soil shear strength and penetration resistance in Kielaneh watershed, located in Kurdistan Province, covering an area of 12,000 hectares using Gradient Boosted Decision Trees (XGBoost), Random Forest (RF), and k-Nearest Neighbors (KNN). Soil penetration resistance and shear strength were measured using handheld penetrometers and vane shear devices at 150 observation points from the surface soil layer (0 to 10 centimeters). Spectral data and auxiliary variables derived from the Digital Elevation Model and Sentinel-2 satellite images were used to predict soil shear strength and penetration resistance. These variables include CHND, VD, RSP, CHNBL, Brightness, WE, NDVI, Band12, Greenness, PLC, as well as soil parameters such as organic matter, calcium carbonate, bulk density, geometric mean particle size, soil texture (percentages of clay, sand, silt), and visible near-infrared spectral data as latent variable (LT), representing soil formation factors. The results showed that the XGBoost had higher accuracy compared to other models for predicting shear strength in surface soil layer with an (R2) of 0.61 and an nRMSE of 0.16, as well as for predicting penetration resistance in the surface soil layer with an (R2) of 0.60 and an nRMSE of 0.11. In conclusion, the XGBoost model, using spectral data along with topographic variables and soil parameters, was able to estimate the spatial variability of soil mechanical properties with acceptable accuracy in the study area. The generated maps can be used to make necessary management decisions regarding of the region.
Mohammad Reza Sayadi; Mehdi Ghorbani; Mohammad Jafari; Hamidreza Keshtkar; Leila Avazpour
Abstract
The objective of this paper is to identify the factors affecting the medicinal plant supply chain in the Nadushan region using a Glaser approach. The research method is applied in terms of purpose and qualitative in terms of method based on grounded theory and Glaser approach (emerging approach); and ...
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The objective of this paper is to identify the factors affecting the medicinal plant supply chain in the Nadushan region using a Glaser approach. The research method is applied in terms of purpose and qualitative in terms of method based on grounded theory and Glaser approach (emerging approach); and it is exploratory based on the nature of the data and the use of inductive philosophy. The study population consisted of experienced local people and managers and experts in the field of the medicinal plant supply chain with more than five years of experience. Participants were selected using purposeful sampling and theoretical judgment. The data collection method was fieldwork, and the data collection tool was in-depth and structured interviews with 30 participants, including native farmers (15), researchers and experts (10), and intermediaries (5) in the field. The grounded theory approach was used to analyze the data and identify the key factors affecting the supply chain. The results identified 9 selective codes and 41 core codes. The factors affecting the supply chain include climate and weather, the region's high potential for medicinal plant cultivation, initial budget and capital, storage conditions, institutional support, policy, medicinal plant production and harvesting management, medicinal plant processing management, and the use of healthy practices in productivity. Therefore, ensuring a sustainable and efficient supply chain is crucial for maintaining the quality, availability, and affordability of medicinal plants.
soroush namjoofar; Ahmad Nohegar; Zeinab Sazvar
Abstract
Horul Azim Wetland is located in the southwestern Iran in Khuzestan Province, has 1180 km2. About 70% of the wetland is located in Iraq, which has faced the challenges of drought and oil drilling, and many of its southern lands have dried up and become dust center. The present study was conducted with ...
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Horul Azim Wetland is located in the southwestern Iran in Khuzestan Province, has 1180 km2. About 70% of the wetland is located in Iraq, which has faced the challenges of drought and oil drilling, and many of its southern lands have dried up and become dust center. The present study was conducted with the aim of assessing the levels of heavy metal pollution in the dried part of this wetland. At first, 15 stations were identified on the LANDSAT image and the dried soil of the wetland was sampled by quadrat and the Cd, Cu, Pb, Fe, Mn and Ni were measured by ICP-MS device. To assess the pollution levels, Igeo, ER, PLI, RI, CSI and mCd were used. The results showed that the concentration of Cd, Cu, Ni and Pb is higher than the shale standard. According to the Igeo, Cd pollution is high (moderate to severe). According to the PI, Cd and Pb pollution are high and moderate, respectively. The ER shows that the ecological pollution of Cd is significant, but other metals don't have ecological risk. The average of the cumulative indices ER and PLI were 193 and 9.7, respectively, indicating a possible ecological risk for all points. The CSI pollution safety for Cd, Cu, Ni and Pb was 0.52, 0.25, 4.02 and 0.34, and the mCd index was 0.27, 10.4, 13.9 and 8.9, respectively, indicating a very high severity of pollution safety for Ni and Cd.
Behnaz Attaeian; Ali Badrestani; Saeid Khosrobeigi Bozchelui; Mohammad Mehdi Artimani
Abstract
Soil organic carbon as a key factor in soil stability and fertility is considered as one of the important environmental challenges in the context of climate change. The aim of this study was to determine soil organic carbon zonation in Gonbad paired-watershed, Hamedan province. In this research, the ...
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Soil organic carbon as a key factor in soil stability and fertility is considered as one of the important environmental challenges in the context of climate change. The aim of this study was to determine soil organic carbon zonation in Gonbad paired-watershed, Hamedan province. In this research, the information of meteorology, soil science and erosion and sedimentation study of Gombad watershed was used, including the information of 49 profiles in the 0-15 cm soil layer. After collecting data, tests of normality (Shapiro-Wilkα test <0.05), homogeneity of variance, and then the relationship between independent variables and organic carbon were performed using Pearson's linear correlation in SAS software. Also, determining the most effective independent variable using multivariate analysis, PCA factor analysis was used in XlStat 2.1 software. In order to determine the distribution and amount of soil organic carbon in the Gonbad representative watershed, modeling using SVM support vector machine learning algorithms and RF random forest was used in R software.The results showed that 78.18% of soil organic carbon changes depend on four components. Clay and nitrogen percentage were selected as the most effective variables on soil organic carbon content, so that the first component of clay content explained 34% and the second component nitrogen explained 18% of variations. According to the results of the implementation of the SVM and RF Models, the SVM model with a CE factor of 0.86 and RMSE of 0.05 in the test stage is a more accurate model in this study.
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