دکتر رضا ذاکری نژاد

Soil erosion is often regarded as one of the main processes of desertification. Many parts of the world have been affected by soil erosion, resulting in major environmental problems and causing land degradation, loss of agricultural land, destroyed villages and infrastructure as well as historic places. Soil erosion particularly affects arid and semi-arid regions due to long dry periods and often-intensive precipitation events. The soil particles washed off by surface and subsurface runoff are the biggest pollution factor in terms of amount and volume. Our case study is located in the Southern Isfahan province, Central Iran. The area is severely affected by water erosion such as gullies, rills and badlands. The main aim of this study is to predict the spatial distribution of the different water related erosion types and their susceptibilities using a probabilistic Maximum Entropy Model approach based on the following environmental layers: lithology, soil textures, land use, precipitation, Normalized Difference Vegetation Index and topographic indices derived from an SRTM DEM with 30 m spatial resolution. An inventory of the erosion forms and features such as gully erosion, rill erosion and badland erosion was determined based on Google Earth images (GE), aerial photos and a field campaign conducted in 2018. In order to validate the stochastic modelling approach, we divided the entire sample in a train (70%) and test (30%) dataset. We validated the model performance using the Area Under Curve (AUC) value. The model yields good (rill and gully erosion) to excellent (badland) results for both train and test data. The spatial prediction of susceptibilities for rill, gully and badland erosion show that in total more than 40% of the study area is affected by water erosion processes (4.8% rill erosion; 23.4% gully erosion and 17.9% badland erosion). The knowledge of susceptible areas is crucial for a proper land management and related soil conservation measures to guarantee a sustainable land use. © 2021 Comitato Glaciologico Italiano. All rights reserved.

Watershed prioritization for the identification of spatial hotspots of flood risk using the combined TOPSIS-GIS based approach: A case study of the Jarahi-Zohre catchment in Southwest Iran

( Article . Gold )

Shirani, K., Zakerinejad, R.

Acta Universitatis Carolinae, Geographica (03005402)56(1)pp. 120-128

2020

A comparison of actual evapotranspiration estimates based on Remote Sensing approaches with a classical climate data driven method

( Article . Gold )

Tofigh, S., Rahimi, D., Zakerinejad, R.

Acta Universitatis Carolinae, Geographica (03005402)55(2)pp. 165-182

Water level instability analysis of Urmia Lake Basin in the northwest of Iran

( Article . )

Bashirian, F., Rahimi, D., Movahedi, S., Zakerinejad, R.

Arabian Journal of Geosciences (discontinued) (18667538)13(4)

2019

Quantitative mapping of desertification risk using the modified MEDALUS model: A case study in the Mazayejan Plain, Southwest Iran

( Article . Gold )

Zakerinejad, R., Masoudi, M.

Acta Universitatis Carolinae, Geographica (03005402)54(2)pp. 232-239

2018

Assessment of gully erosion in relation to lithology in the southwestern Zagros Mountains, Iran using ASTER data, GIS and stochastic modeling

( Article . )

Zakerinejad, R., Omran, A., Hochschild, V., Maerker, M.

Geografia Fisica e Dinamica Quaternaria (03919838)41(2)pp. 95-104

2017

A toolbox for sediment budget research in small catchments

( Article . Gold • Green )

Chalov, S., Golosov, V., Tsyplenkov, A., Theuring, P., Zakerinejad, R., Maerker, M., Samokhin, M.

Geography, Environment, Sustainability (25421565)10(4)pp. 43-68

2015

An integrated assessment of soil erosion dynamics with special emphasis on gully erosion in the Mazayjan basin, southwestern Iran

( Article . )

Zakerinejad, R., Maerker, M.

Natural Hazards (15730840)79pp. 25-50

2014

Prediction of gully erosion susceptibilities using detailed terrain analysis and maximum entropy modeling: A case study in the Mazayejan plain, southwest Iran

( Article . )

Zakerinejad, R., Maerker, M.

Geografia Fisica e Dinamica Quaternaria (03919838)37(1)pp. 67-76

Gully erosion is one of the most severe environmental problems in large areas of Iran. Land degradation and accelerated desertification are the consequence in susceptible areas. Gully erosion normally takes place when surface runoff is concentrated and thus, detach and transfer soil particles down the slopes into the drainage network. In traditional soil erosion studies these processes often have been neglected. In this study we investigate the spatial distribution of gully erosion processes with a quantitative method since in many national assessment approaches just qualitative models were applied. For this study we utilized a detailed terrain analysis and a stochastic modeling approach using mechanical statistics. Moreover we predict the potential spatial distribution of gullies in the Mazayejan plain of Fars province in southwestern Iran where gully erosion is the main environmental threat. Our methodological approach consists in the following steps: i) mapping of gully erosion phenomena in a test area based on Google Earth images; ii) development of a digital elevation model (DEM) with 10 meter resolution, iii) detailed terrain analysis deriving more than 20 terrain indices, iv) application of the Maxent model for the test area using the gully erosion forms as dependent variable and topographic indices as predictor variable and finally v) prediction of the spatial distribution of gully erosion potential for the entire study area. Model performance was evaluated by the Receiver Operating Characteristic (ROC). The results obtained show that the Maxent model perform very well and thus, it is suitable for the prediction of the gully erosion potential in the area. Among the terrain indices utilized in the prediction the most important ones are: convergence index, plan curvature, and slope. The proposed methodology allows conducting a proper gully erosion assessment in order to identify the priority areas for soil conservation and land use management.