Gully Erosion in I. R. Iran: Characteristics, Processes, Causes, and Land Use

Majid, Shahn; Bayat, Reza; Charkhabi, Amir Hossein

doi:10.1007/978-3-030-23243-6_23

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Rangelands cover around 84 billion ha, about 52% of Iran (Hosseininia, Azadi, Zarafshani, Samari, & Witlox, 2013; Mashayekhi, 1990), and support around 83 million domesticated grazers (Behmanesh, Abedi Sarvestani, Sharafatmandrad, & Hajili‐Davaji, 2016; Hosseininia et al, 2013). But development and land use changes in Iran are shrinking rangeland ecosystems (Beygi Heidarlou, Banj Shafiei, Erfanian, Tayyebi, & Alijanpour, 2019; Fathizad, Rostami, & Faramarzi, 2015; Ghaffari, Keesstra, Ghodousi, & Ahmadi, 2010; Yousefi, Moradi, Boll, & Schönbrodt‐Stitt, 2016; Yousefi, Pourghasemi, Hooke, Navratil, & Kidová, 2016) and over‐grazing is reducing the quality of the range (Behtari, Jafarian, & Alikhani, 2019; Soufi, Bayat, & Charkhabi, 2020).…”

Section: Introductionmentioning

confidence: 99%

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

et al. 2020

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Increased use and increasing demands pose serious threats to rangelands. In this study, we document a pronounced downward trend in rangeland quality in the Alborz Mountains in Firozkuh County, Iran using analysis of three machine‐learning models (MLMs). A total of 1,147 transects were established to evaluate the rangeland quality trends from field data collected over a 7‐year period. Twelve independent conditional factors were analyzed for their relationships to range quality through three MLMs—Random Forest (RF), classification and regression tree (CART), and support vector machine (SVM). Based on assessments of the trained and validated models, RF, with a ROC‐AUC = 0.96, was determined to be the most robust. The results show that about 20% of the rangeland in the study area is in a critically degraded condition. Distances from roads and livestock density are the two factors most strongly linked to degradation. These results, in combination with field observations, indicate that the rangelands of the study area face two major challenges (overgrazing and early grazing) that require new strategies to mitigate and prevent damages. This study may provide important guidance for evaluating rangeland conditions in other regions of the world.

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Section: Introductionmentioning

confidence: 99%

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

et al. 2020

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“…In Iran, gully erosion is one of the main environmental issues because, with an incremental pace, soil erosion is becoming a national threat (Zabihi et al 2018;. Approximately 1,500 tons/km 2 of soil per year are washed away, which results in 1 mm/yr reduction in soil thickness across the whole Iranian surface (Soufi et al 2020). Among different types of soil erosion including sheet, rill, splash, and a gully in Iran, the gully is the most significant type of erosion that is several times more damaging than other types of erosion, which leads to dams' sedimentation, destruction of transportation and energy transmission lines, decreasing and losing farmlands productivity, land degradation and long-term negative economic consequences (Zakerinejad and M€ arker 2014;Nazari Samani et al 2018;Zabihi et al 2018;Arabameri, Chen, et al 2019;Nhu et al 2020).…”

Section: Introductionmentioning

confidence: 99%