Assessment of desertification status in Sefiddasht-Boroujen (Chaharmahal and Bakhtiari province) watershed using MEDALUS model
Subject Areas : Agriculture, rangeland, watershed and forestryFatemeh Nafar 1 , Ataollah Ebrahimi 2 , Ali Asghar Naghipour 3
1 - MSc. of Combating Desertification, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran
2 - Associate Professor, Department of Range and Watershed Management, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran
3 - Assistant Professor, Department of Range and Watershed Management, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran
Keywords: central Zagros, Environmental crisis, Vegetation, Critical plain, Desertification, climate,
Abstract :
Background and Objective The degradation of resources in many parts of the world is a serious threat to humanity due to its growing trend. Desertification, which is one of the manifestations of this degradation, has affected most countries and has been introduced as the third challenge of the 21st century after the two challenges of climate change and freshwater scarcity. Desertification is the degradation of land in arid, semi-arid, and semi-humid areas. This situation is caused by a series of important processes, the most important of which are the two factors of human activity and climate change. Several methods have been developed to determine the process of desertification, one of which is widely used, the Medalus method. Assessing the status of desertification processes (land degradation) in a village, region or country is important because it provides the opportunity to make informed decisions about the financial dimension and the amount of investment needed to control it. Considering the development of the desertification phenomenon in the Sefiddasht-Borujen region and the need to pay attention to the importance of the results of this destructive phenomenon in the future. The purpose of this study is to evaluate desertification using the Madalus model in the Sefiddasht-Borujen watershed with an area of 92565 hectares, located in Chaharmahal and Bakhtiari province.Materials and Methods Land use changes were investigated and detected using the distance measurement model. For this purpose, the images of 1998, 2009, and 2018 were used. The amount of changes during this period was determined, and the points where the most changes occurred were selected. Then using these points, in the Medalus model, the factors affecting desertification and its current situation were considered. Then, the effective parameters in desertification were studied in these points separately and the Medalus model was implemented in them. According to the Medalus method, effective factors in the desertification of the region were identified and each factor including climate, vegetation, soil, groundwater, and management and policy was considered as a criterion. Then, the characteristics of the mentioned criteria that were effective in the desertification of this region were considered as indicators. After each indicator received weight in relation to its impact on desertification and by evaluating them, their impact of them on the desertification process was determined. Finally, using the indicators of these criteria, the criteria map and finally, the desertification map were obtained from their geometric mean n order to study the climate criteria, three indices of rainfall, direction, and drought index were considered. The study of the climate was evaluated from 3 sample points in the meteorological and water weight stations of the province, which are harvested as points. To evaluate the soil condition, some physical and chemical properties such as soil texture, acidity, electrical conductivity, and the amount of organic matter were selected. To determine the soil properties, the first 170 sampling points were identified in the study area, and from 0 to 20 cm soil level, sampling was performed and transferred to the laboratory.Results and Discussion The results showed a score of climatic criteria calculated at 1.80 was determined in two classes and had the most role in desertification in the region. The score of management and policy, vegetation, and soil criteria respectively were calculated at 1.76, 1.71, and 1.55 and was determined into two classes severe and very severe. Also, water criteria were calculated at 1.33 and were determined in the middle class. Based on the Medalus model, the current desertification score was estimated to be 1.63. According to this map, the desertification situation of the region was divided into two classes, severe and very severe. Finally, it was calculated that 56% of this area is faced with severe and 44% of it very severe desertification. The result showed that the northern part of the study area is highly vulnerable, while the southern part of the region is less vulnerable to desertification. However, this region has high desertification intensity. The foretold sensitivity of this region to the phenomenon of desertification was consistent. In this model, climate, soil, vegetation, groundwater, management, and policy criteria were selected. According to the results, climate, management, policy, vegetation, soil, and groundwater criteria, respectively, had the greatest impact on desertification of this region due to the low precipitation, drought in recent years, illegal excavation of wells, and uncontrolled extractions more than the capacity of groundwater aquifers in Sefiddasht has caused the drying of most wells in this area. Also, the drying of Dehno Wetland is another reason for the intensity of desertification in the study area.Conclusion According to the obtained results, the phenomenon of desertification in this region is accelerating and would cause a destructive consequence. The study area, according to the proposed definition of desertification, has both natural and human desertification conditions. Natural factors such as unfavorable climatic conditions such as lack of rainfall, successive droughts, limited water resources, on the one hand, and destructive human factors such as traditional agricultural system, overgrazing, overexploitation of groundwater, conversion of pastures to land Agriculture, industries, mines and facilities, destruction of vegetation and shrubs, on the other hand, have led to the destruction of pastures and natural resources and accelerated desertification in the region. Evidence shows that in this region water table is lower than in other areas and as a consequence desertification is accelerated. Among the ways to deal with desertification in the region, it is possible to use the pastures and pastures in principle, according to their capacity at the right time, to permanently enclose the region under biological and mechanical desertification activities, proper exploitation of groundwater and prevents land use change.
Abbasi AP, Amani H, Zareian M. 2014. Quantitative assessment of desertification status using MEDALUS model and GIS (Case study: Shamil plain - Hormozgan province). Journal of RS and GIS for Natural Resources, 5(1): 87-97. (In Persian).
Ahmadi H. 2006. Applied Geomorphology, Wind Erosion. Tehran University Press, pp. 592. (In Persian).
Ait Lamqadem A, Pradhan B, Saber H, Rahimi A. 2018. Desertification sensitivity analysis using MEDALUS model and GIS: a case study of the Oases of Middle Draa Valley, Morocco. Sensors, 18(7): 2230. doi:https://doi.org/10.3390/s18072230
Arab Ameri AR, Ramesht MH, Rezaei K, Sohrabi M. 2019. Quantitative assessment of desertification risk using modified MEDALUS model, Case study: Shahroud Bastam Basin. Watershed Engineering and Management, 11(2): 508-522. (In Persian).
Arya AS, Dhinwa PS, Pathan SK, Raj KG .2009. Desertification land degradation status mapping of India. Current Science, 97(10): 1478-1483.
Bakr N, Weindorf DC, Bahnassy MH, Marei SM, El-Badawi MM. 2010. Monitoring land cover changes in a newly reclaimed area of Egypt using multi-temporal Landsat data. Applied Geography 30(4),592-605.
Boudjemline F, Semar A. 2018. Assessment and mapping of desertification sensitivity with MEDALUS model and GIS–Case study: basin of Hodna, Algeria. Journal of water and land development, 36(1): 17-26. doi:https://doi.org/10.2478/jwld-2018-0002
Contador JFL, Schnabel S, Gutiérrez AG, Fernandez MP. 2009. Mapping sensitivity to land degradation in Extremadura. SW Spain. Land Degradation & Development, 20(2): 129-144. doi:https://doi.org/10.1002/ldr.884
D’Odorico P, Bhattachan A, Davis k, Ravi S, Runyan C. 2013. Global desertification: Drivers and feedbacks. Advances in Water Resources, 51: 326–344. doi:https://doi.org/10.1016/j.advwatres.2012.01.013
Dutta S, Chaudhuri G. 2015. Evaluating environmental sensitivity of arid and semiarid regions in northeastern Rajasthan, India. Geographical Review, 105(4): 441-461. doi:https://doi.org/10.1111/j.1931-0846.2015.12093.x
Hadeel AS, Mushtak T, Jabbar MT, Chen X. 2010. Application of remote sensing and GIS in the study of environmental sensitivity to desertification: a case study in Basrah Province, southern part of Iraq. Applied Geomatics, 2(3): 101-112. doi:https://doi.org/10.1007/s12518-010-0024-y
Kadović R, Ali Mansour Y. Bohajar V, Perović S, Belanović Simić M, Todosijević S, Tošić M, Anđelić D, Mlađan, Dovezenski U. 2016. Land sensitivity analysis of degradation using MEDALUS model, case study: Deliblato Sands, Serbia. Archives of Environmental Protection, 42(4): 114-124.
Khosravi A, Mirabbasi R, Samadi H, Ghasemi DA. 2019. Monitoring and forecasting of groundwater Drought Using Groundwater Resource Index (GRI) and First to Third-Order Markov Chain Models (Case study: Boroujen Plain). Journal of Water and Soil conservation, 26(2): 117-136. (In Persian).
Lahlaoi H, Rhinane H, Hilali A, Lahssini S, Moukrim S. 2017. Desertification assessment using MEDALUS model in watershed Oued El Maleh, Morocco. Geosciences, 7(50): 1-16. doi:https://doi.org/10.3390/geosciences7030050
Lee EJ, Piao D, Song C, Kim J, Lim H, Kim E, Moon J, Kafatos M, Lamchin M, Jeon SW, Lee W.2019. Assessing environmentally sensitive land to desertification using MEDALUS method in Mongolia. Forest Science and Technology, 15(4): 210-220
Rezaipoor Baghedar AH, Bahrami H, Rafee Sharifabad J, Khosravi H. 2015. An evaluation on the intensity of desertification by using IMDPA model (Case study: Baghedar region, Yazd). Arid Regions Geographic Studies, 5(19): 42-54.
Schulz JJ, Cayuela L, Echeverria C, Salas J, Benayas JMR. 2010. Monitoring land cover change of the dryland forest landscape ofCentral Chile (1975–2008). AppliedGeography, 30(3): 436-447.
Taghipour S, Fazeli A, Kazemi B. 2016. A case study of desertification hazard mapping using the MEDALUS (ESAs) methodology in southwest Iran. Journal of Natural Resources and Development, 6: 1–8. (In Persian).
UNEP, 1992, World Atlas of Desertification, Edward Arnold, London.
Veron SR, Paruelo JM and Oesterheld M. 2006. Assessing desertification, Journal of Arid Environments, 66: 751-763.
Wijitkosum S. 2020. Reducing vulnerability to desertification by using the spatial measures in a degraded area in Thailand. Land, 9(2): 49. doi:https://doi.org/10.3390/land9020049
Xu D, Ding X. 2018. Assessing the impact of desertification dynamics on regional ecosystem service value in North China from 1981 to 2010. Ecosystem Services, 30: 172-180. doi:https://doi.org/10.1016/j.ecoser.2018.03.002
Xu D, Song A, Li D, Ding X, Wang Z. 2019. Assessing the relative role of climate change and human activities in desertification of North China from 1981 to 2010. Frontiers of Earth Science, 13(1): 43-54. doi:https://doi.org/10.1007/s11707-018-0706-z
Xu D, You X, Xia C. 2019. Assessing the spatial-temporal pattern and evolution of areas sensitive to land desertification in North China. Ecological Indicators, 97: 150-158. doi:https://doi.org/10.1016/j.ecolind.2018.10.005
Zhang C, Wang X, Li J, Hua T. 2020. Identifying the effect of climate change on desertification in northern China via trend analysis of potential evapotranspiration and precipitation. Ecological Indicators, 112: 106141. doi:https://doi.org/10.1016/j.ecolind.2020.106141
_||_Abbasi AP, Amani H, Zareian M. 2014. Quantitative assessment of desertification status using MEDALUS model and GIS (Case study: Shamil plain - Hormozgan province). Journal of RS and GIS for Natural Resources, 5(1): 87-97. (In Persian).
Ahmadi H. 2006. Applied Geomorphology, Wind Erosion. Tehran University Press, pp. 592. (In Persian).
Ait Lamqadem A, Pradhan B, Saber H, Rahimi A. 2018. Desertification sensitivity analysis using MEDALUS model and GIS: a case study of the Oases of Middle Draa Valley, Morocco. Sensors, 18(7): 2230. doi:https://doi.org/10.3390/s18072230
Arab Ameri AR, Ramesht MH, Rezaei K, Sohrabi M. 2019. Quantitative assessment of desertification risk using modified MEDALUS model, Case study: Shahroud Bastam Basin. Watershed Engineering and Management, 11(2): 508-522. (In Persian).
Arya AS, Dhinwa PS, Pathan SK, Raj KG .2009. Desertification land degradation status mapping of India. Current Science, 97(10): 1478-1483.
Bakr N, Weindorf DC, Bahnassy MH, Marei SM, El-Badawi MM. 2010. Monitoring land cover changes in a newly reclaimed area of Egypt using multi-temporal Landsat data. Applied Geography 30(4),592-605.
Boudjemline F, Semar A. 2018. Assessment and mapping of desertification sensitivity with MEDALUS model and GIS–Case study: basin of Hodna, Algeria. Journal of water and land development, 36(1): 17-26. doi:https://doi.org/10.2478/jwld-2018-0002
Contador JFL, Schnabel S, Gutiérrez AG, Fernandez MP. 2009. Mapping sensitivity to land degradation in Extremadura. SW Spain. Land Degradation & Development, 20(2): 129-144. doi:https://doi.org/10.1002/ldr.884
D’Odorico P, Bhattachan A, Davis k, Ravi S, Runyan C. 2013. Global desertification: Drivers and feedbacks. Advances in Water Resources, 51: 326–344. doi:https://doi.org/10.1016/j.advwatres.2012.01.013
Dutta S, Chaudhuri G. 2015. Evaluating environmental sensitivity of arid and semiarid regions in northeastern Rajasthan, India. Geographical Review, 105(4): 441-461. doi:https://doi.org/10.1111/j.1931-0846.2015.12093.x
Hadeel AS, Mushtak T, Jabbar MT, Chen X. 2010. Application of remote sensing and GIS in the study of environmental sensitivity to desertification: a case study in Basrah Province, southern part of Iraq. Applied Geomatics, 2(3): 101-112. doi:https://doi.org/10.1007/s12518-010-0024-y
Kadović R, Ali Mansour Y. Bohajar V, Perović S, Belanović Simić M, Todosijević S, Tošić M, Anđelić D, Mlađan, Dovezenski U. 2016. Land sensitivity analysis of degradation using MEDALUS model, case study: Deliblato Sands, Serbia. Archives of Environmental Protection, 42(4): 114-124.
Khosravi A, Mirabbasi R, Samadi H, Ghasemi DA. 2019. Monitoring and forecasting of groundwater Drought Using Groundwater Resource Index (GRI) and First to Third-Order Markov Chain Models (Case study: Boroujen Plain). Journal of Water and Soil conservation, 26(2): 117-136. (In Persian).
Lahlaoi H, Rhinane H, Hilali A, Lahssini S, Moukrim S. 2017. Desertification assessment using MEDALUS model in watershed Oued El Maleh, Morocco. Geosciences, 7(50): 1-16. doi:https://doi.org/10.3390/geosciences7030050
Lee EJ, Piao D, Song C, Kim J, Lim H, Kim E, Moon J, Kafatos M, Lamchin M, Jeon SW, Lee W.2019. Assessing environmentally sensitive land to desertification using MEDALUS method in Mongolia. Forest Science and Technology, 15(4): 210-220
Rezaipoor Baghedar AH, Bahrami H, Rafee Sharifabad J, Khosravi H. 2015. An evaluation on the intensity of desertification by using IMDPA model (Case study: Baghedar region, Yazd). Arid Regions Geographic Studies, 5(19): 42-54.
Schulz JJ, Cayuela L, Echeverria C, Salas J, Benayas JMR. 2010. Monitoring land cover change of the dryland forest landscape ofCentral Chile (1975–2008). AppliedGeography, 30(3): 436-447.
Taghipour S, Fazeli A, Kazemi B. 2016. A case study of desertification hazard mapping using the MEDALUS (ESAs) methodology in southwest Iran. Journal of Natural Resources and Development, 6: 1–8. (In Persian).
UNEP, 1992, World Atlas of Desertification, Edward Arnold, London.
Veron SR, Paruelo JM and Oesterheld M. 2006. Assessing desertification, Journal of Arid Environments, 66: 751-763.
Wijitkosum S. 2020. Reducing vulnerability to desertification by using the spatial measures in a degraded area in Thailand. Land, 9(2): 49. doi:https://doi.org/10.3390/land9020049
Xu D, Ding X. 2018. Assessing the impact of desertification dynamics on regional ecosystem service value in North China from 1981 to 2010. Ecosystem Services, 30: 172-180. doi:https://doi.org/10.1016/j.ecoser.2018.03.002
Xu D, Song A, Li D, Ding X, Wang Z. 2019. Assessing the relative role of climate change and human activities in desertification of North China from 1981 to 2010. Frontiers of Earth Science, 13(1): 43-54. doi:https://doi.org/10.1007/s11707-018-0706-z
Xu D, You X, Xia C. 2019. Assessing the spatial-temporal pattern and evolution of areas sensitive to land desertification in North China. Ecological Indicators, 97: 150-158. doi:https://doi.org/10.1016/j.ecolind.2018.10.005
Zhang C, Wang X, Li J, Hua T. 2020. Identifying the effect of climate change on desertification in northern China via trend analysis of potential evapotranspiration and precipitation. Ecological Indicators, 112: 106141. doi:https://doi.org/10.1016/j.ecolind.2020.106141