جستجوی مقالات مرتبط با کلیدواژه « MEDALUS » در نشریات گروه « آب و خاک »

The drying of Hamoon international wetlands and dust storms caused by these wetlands bed in the past two decades have been considered as one of the main environmental concerns of the eastern part of Iran. The purpose of this study was to investigate the relationship between meteorological variables of temperature, rainfall and discharge of the entrance water of the Hirmand River with the amount of land degradation in the Hamoon in a 21-year (1996- 2016) interval. For this purpose, weather data of temperature and precipitation were obtained at three synoptic stations of Kandahar, Farah and Zabol, and TRMM rainfall data and ERA temperature data were obtained from the related website. Land degradation based on the MEDALUS model and five criteria of wind erosion, soil quality, climate quality, management quality and vegetation was evaluated in Hamoon basin. The correlation between temperature, precipitation and discharge data was determined to land degradation statue. Investigations showed that the inflow of Hirmand River inlet to the Hamoon bed has been decreasing during this period, and the land degradation class has increased very drastically in all working units from the middle class to the severe class. Also the correlation of temperature data with inlet water discharge and land degradation were -0.558 (moderate level) and 0.735 (strong level) respectively, while the correlation of discharge with precipitation was 0.666. Correlations between precipitation and discharge with land degradation were found to be strong at 0.901 and 0.843, respectively. The results showed that the land degradation in the bed of the Hamoon has a good correlation with temperature changes, precipitation and inflow discharge. This correlation is such that it shows the indirect relationship between the amount of land degradation with the amount of inflow discharges and recorded precipitation and the temperature is correlated with each other. Between 1996 and 2002, the rate of land degradation increased and reached a very severe level with increasing temperature, decreasing precipitation and consequently reducing the inflow rate of the Hirmand River to the Hamoon. In 2003, with temperature decrease and the increase in precipitation, the inflow rate of the Hirmand River increased and finally the intensity of land degradation was reduced in the medium to high intensity units. In 2004 to 2016, the amount of rainfall in the Hirmand basin declined, with the result that the amount of discharge to the Hamoon wetlands declines again and the intensity of land degradation in the work units is at a very high level.

In this study, to study the status of water resources degradation in Kashan region, Isfahan Province, eight indices including: drop in groundwater, water salinity, irrigation efficiency, Well-to-Qanat development ratio, the pumping time, shortage of water supplies for animals and humans and the water negative balance were selected according to previous studies conducted on desertification in Iran and the world. Existing evaluation models were determined. Desertification map of the study area was provided according to MEDALUS model and selected indices. The selected indices were weighted using a multi-criteria decision method and each index having weight more than 0.5 were selected as the most effective indices of desertification. Again, the desertification status map of the study area was prepared by the most effective indices. Finally, the two desertification maps were compared. The results showed that the drop in groundwater, water salinity, the pumping time and water negative balance have the most effect on water resources degradation among selected indices. The results of comparing two groundwater degradation maps showed that based on map provided with eight indices, 87.78 and 8.30 percent of the total area are classified in critical conditions c and b, respectively. While the map provided by the most effective indicators shows that 99.15% of the total area is classified in the critical condition "c" and just 0.849% is classified in the critical condition "b". It can be concluded that to assess desertification status, it is better to first determine the indicators by weighting and prioritizing methods. This will identify the indicators that have not had a significant effect on the desertification phenomenon in the area and prevent their impact on desertification classes and reduction of scores.

This paper aimed to assess the severity of desertification in Segzi plain located in the eastern part of Isfahan city, focusing on groundwater quality criteria used in MEDALUS model. Bayesian Belief networks (BBNs) were also used to convert MEDALUS model into a predictive, cause and effects model. Different techniques such as Kriging and IDW were applied to water quality data of 12 groundwater wells to map continuous variations of the CL, SAR, EC, TDS, pH and decline in water table indices in GIS environment. The effects of measured water quality indicators on desertification severity levels were assessed using sensitivity and scenario analysis in BBNs model. According to the results of the MEDALUS, the desertification of the study area was classified as severe class due to its low quality of groundwater. Sensitivity analysis by the both models showed that decline in waater table, water chloride content and electrical conductivity were the most important parameters responsible for desertification in the region from ground water condition standpoint. The determination coefficient between the outputs of the MEDALUS and BBNs models (R2>0.63) indicated that the results of both models were significantly correlated (α=5 %). These results indicate that the application of BBNs model in desertification assessment can appropriately accommodate the uncertainty of desertification methods and can help managers to make better decision for upcoming land management projects.

Appropriate criteria and methods are required to assess desertification potential in various ecosystems. This paper aimed to assess desertification levels in Segzi plain located in east part of Isfahan, with a focus on soil quality criteria used in MEDALUS model. Bayesian Belief Networks (BBNs) were also used to convert MEDALUS model into a predictive, cause and effects model. Soil samples were collected from 17 soil profiles in all land units and some of their characteristics such as texture, soluble sodium and chlorine, organic material, Sodium Absorption Ratio (SAR), Electrical Conductivity (EC) and CaSo4 of all soil samples were determined in soil laboratory. The effects of measured soil quality indicators on desertification intensity levels were assessed using sensitivity and scenario analysis in BBNs. Results showed that the used integrated method can appropriately accommodate uncertainty in the desertification assessments approaches created as a result of the influence of different soil characteristics on desertification. According to the results of MEDALUS model, 28.28 % and 71.72 % of the study area were classified as poor and moderate areas in terms of soil quality respectively. Sensitivity analysis by both models showed that soil organic matter, SAR and EC were identified as the most important edaphic variables responsible for desertification in the study area. Evaluating the effects of various management practices on these variables can assist managers to achieve sound management strategies for controlling desertification.

Nowadays, land degradation is a serious problem in many parts of the world. Land degradation occurs as a result of various factors including climatic change, improper land use and management in arid, semi-arid and dry sub-humid areas. It has been recognized as a major socioeconomic, social and environmental problem in many countries of the world. Various models are provided in order to assess desertification in the world. It seems that the MEDALUS model has apparent advantages compared to the other ones, such as easy style, data accessibility and taking geometric mean. The objectives of this study were to mapping and quantitative evaluation of land degradation in Siyahpoush catchment using MEDALUS and adjusted MEDALUS model.
In this study, MEDALUS and adjusted MEDALUS models were applied to desertification assessment and mapping in Siyahpoush catchment. For this purpose, four important criteria (soil quality, climate, vegetation cover, management and policy) which were effective on desertification have been selected. Indices for each criterion are defined in the MEDALUS model. Index layers for each criterion were prepared using GIS. These indices were ranked in accordance with MEDALUS model. The geometric mean was then calculated and map was produced for each criterion. Land degradation map of the study area was finally prepared using the geometric mean criteria.
The result showed that management quality and climate quality criteria with a geometric average of 1.91 and 1.62 have played the most important role in sensitivity of the area to desertification. Soil quality criterion with a geometric average of 1.39 and vegetation quality criterion with a geometric average of 1.41 were classified in moderate and high quality, respectively. Therefore, vegetation quality was determined as the most appropriate criterion. The ESAI index for MEDALUS and adjusted MEDALUS model ranged 1.38 to 1.79 and 1.37 to 1.93, respectively. This means that all area is located in critical class of desertification.
The management and climate quality were identified as the most inappropriate criteria and vegetation quality was found as the most appropriate criterion. According to the obtained results, the study area is classified as critical class by ESAs model, so that 90.1% and 99.2% of the study area is located in the severe critical sub-class (C3) whit MEDALUS and adjusted MEDALUS model, respectively. However, implementing management policies would help to restrain this phenomenon at field or regional level. In addition, monitoring of land degradation needs to be considered that have involved more effective indices in this region.

Desertification is known as a major crisis in arid regions of Isfahan province. This study aimed to assess the performance of three main desertification models including MEDALUS, MICD and FAO-UNEP for mapping desertification severity in the hotspot of Jarghuyeh region, eastern Isfahan. Different desertification indicators and their related indices were chosen based on the characteristics of the region and fieldwork, and spatially mapped in 27 geomorphologic facies. The desertification severity maps were classified based on the classification scheme for each model in ArcGIS 10 environment, and then comparison of the models and selection of the best one were achieved using IDRISI Tiga 16.03 software. The results of all three models showed that more than 95% of the region can be classified as severe desertification but due to the differences in the number of desertification classes and also indicators and indices only 45% of desertification severity was observed to be similar across the models. Results indicated that the MEDALUS model due to its flexibility to accept new indicators and indices, GIS-based characteristics, and use of geometric mean of indicators in desertification mapping seems to be a suitable model for studying desertification severity in the region. According to this model, 85% and 15% of the area are classified as very severe and severe class of desertification, respectively, which indicates that the rate of desertification is very high and immediate management programs are needed to slow down the desertification process in the region.

Various researches on assessing and mapping of desertification have been carried out which have lead in development of regional and local models. In this study the MEDALUS method have been applied to assess and map the current status of desertification in the Sofikam – Mangali plain, the northwest of the Golestan province, Iran. The criteria and indices model were re-defined before the model application, whereas in the revised model 5 criteria, 20 indices were used to assess the condition of the study area. The criteria included were water erosion, vegetation, climate, soil and management. Then several sub-indicators affecting the quality of each main criterion were identified. Similar to the original version of the MEDALUS method, each sub-indicator was quantified according to its quality. ArcGIS 9 software was used to analyze and prepare the layers of quality maps using the geometric mean to integrate the individual sub-indicator maps. In turn the geometric mean of all five criteria quality maps was used to generate a desertification map of the study area. The results showed that 54.12 percent of the area is classified as severe, 43.7122 percent, moderate and 2.17 percent as low affected by desertification process. Further analysis indicated that the soil and vegetation indicators were the most important factors affecting desertification process in the Sofikam – Mangali plain, the northwest of the Golestan province.