Journal of Range and Watershed Managment

Abstract Ecotourism, as a side activity of rangeland, can be effective in improving the livelihood of rangers and will reduce the pressure on rangelands by economizing rangeland. In this study, with the aim of evaluating the potential rangelands of Dermian , for ecotourism use, based on environmental and ecological factors (climate, topography, soil, distance from water sources and vegetation attractions) and infrastructure (distance from the city and from roads), was done. From the combination of maps in the GIS environment and based on the FAO limiting factor approach,, the rangeland suitability was determined. Based on the results, 36.7% of rangelands are in the middle suitability category (S2), 46.5% in the low suitability category (S3) and 16.8% in the non-suitable category (N) in terms of ecotourism. In this regard, 61.5% of the rangelands for livestock grazing, have low suitability (S3) and 38.5%, unsuitable (N). The percentage of vegetation and,, the poor condition of soil erosion, are factors limiting the suitability for ecotourism and livestock grazing. , it is necessary to reduce the number of livestock and graze livestock in accordance with ecological principles; that used the rangeland of the region for ecotourism along with livestock. This, in addition to compensating for the economic problems, will also help restore vegetation. Due to the need to preserve rangeland,, forest parks can be created to accommodate tourists, up to a suitable radius of the desired rangelands, and by placing remote viewing platforms and sidewalks, from the amount of damage to vegetation and reduced soil degradation.

Abstract Cover-management factor (C) is one of the most important influential factor on soil erosion using the Revised Universal Soil Loss Equation (RUSLE) model. C-factor is challenging to determine based on the proposed procedures due to lack of accurate information. Vegetation cover map can be used to estimate C-factor, but preparing a suitable mapping of vegetation cover is challenging in many situations. Therefore, in this study vegetation cover map was prepared and compared using the k Nearest Neighbor (k-NN) algorithm, linear regression (LR) and linear stepwise regression (LSR) in the study area. In regression methods, 17 vegetation and environmental indices were prepared and their relationships were investigated. The results of comparing the three methods showed that the k-NN method has better results than other regression methods due to its highest overall accuracy (83.3%) and kappa coefficient (75.9%) therefore, it was used to produce C-factor map. Results showed that the k-NN was very promising for mapping vegetation canopy cover in the arid and semi-arid areas. The results showed that among vegetation indices NDVI had the highest correlation (0.82) with percentage vegetation cover. Also, in the k-NN method, the Euclidean distance metrics in k = 9 has better results than the other two Fuzzy and Mahalanobis distances and can be used to estimation of vegetation cover map.

Abstract Landslide susceptibility mapping is considered as the first important step in landslide risk assessment. The main purpose of this study is to compare the performance of a machine learning algorithm (a logistic model tree), and a statistical model (a logistic regression), for landslide susceptibility modeling in the Sarkhoon watershed, Chaharmahal and Bakhtiari province. For this purpose, at first, a landslide inventory map including a total of 98 landslide locations was constructed using historical landslides, and extensive field surveys. In addition, a total of 100 non-landslide locations were also identified to construct a database. The landslide and non-landslide locations were randomly selected and divided into two groups with a 70/30 ratio for modelling and validation processes. Twenty conditioning factors were selected based on literature review and geo-environmental properties in the study area. Subsequently, the logistic model tree (LMT) and the logistic regression (LR) models were applied to identify the influence of conditioning factors on landslide occurrence. Finally, the performance of the models in landslide susceptibility mapping was investigated using the area under the receiver operating characteristics curve (AUC). The results concluded that the LR model (AUC = 0.797) outperformed and outclassed the LMT (AUC = 0.740) model in the study area. Although both models were reliable tools for spatial prediction of landslide susceptibility; however, the LR model was more accurate that it can be proposed as an alternative tool for better management of areas prone to landslide in the study area.

Abstract Water quality is always one of the major challenges for managers and decision makers in water resource management. However, the problems of water quality are more important than quantity. One of the main ways in thorough review and assessment of water quality using multivariate statistical techniques are, the majority of changes to a system, in order to identify important factors that influence could explain. This study classified zone Groundwater Quality Mashhad plain terms of agricultural potential and its quality review process has been carried out in recent decades. Therefore, the quality of groundwater for agricultural use was studied and maps of quality classification for 2001-2011 years were prepared. Then, using geological map, the effect of geological formations on degradation of groundwater quality was assessed. For water quality analyses, 10 important water quality variables in 39 selected wells were measured and they were analyzed using multivariate statistical techniques. The statistical analyses which were used are: Factor analysis for determining the most important variables, cluster analysis for determination of variables homogenous groups and Pearson Correlation for investigation of relationships between variables. The results have shown the best relationship between geological formation and quality factors. Also, the results of Factor Analysis also showed that EC and TDS 71.02 of the total variance explained by factor loading 0.98 and pH 14.91 of the total variance explained by factor loading 0.93 are the most important variables affecting the quality of groundwater in the study area.

Abstract The excessive reducing capacity of natural resources is one of the most important challenges that human beings have faced it in the last century. Proper land use and land use management based on its ecological potential play an important role in achieving sustainable development. Hence, in order to achieve sustainable development and in order to use land appropriately, tendencies should be directed towards the planning and utilization of resources on the basis of their resources. Therefore, since agriculture has a great deal of environmental impact on urban areas, the evaluation of agricultural lands is necessary. The aim of this study is evaluation of ecological potential of land in Eshtehard in terms of agriculture and rangelands. For this purpose, the ecological potential of the lands of Eshtehard was evaluated using ecological criteria and using Fuzzy, Fuzzy AHP methods and Geographic Information System (GIS). The Fuzzy method was used to standardize the layers and also to assign weight to each of the indices used by Fuzzy AHP method. The results of this study showed that class 1 lands with 1.50% is the lowest and the class 4 lands with 25.36% of the total area of the study area has the biggest area. The results of the analysis in this study indicate the high efficiency of Fuzzy AHP method in assessing the ecological potential of the area and can be used with changes necessary for other areas and also other location actives.

Abstract Desertification refers to land degradation in arid, semi-arid, and dry sub-humid region. It is a global environmental problem with political and socio-economic consequences. Land degradation occurs as a result of impoverished vegetation cover that may lead to a progressive and irreversible reduction of the biological or economic productivity. Overgrazing may cause degradation of soil and vegetation. Degradation of vegetation and soil in dry lands, sometimes called desertification, is thought to be a serious threat to the sustainability of human habitation.  Therefore, the intensity of grazing can serve as an index of environmental pressure. The Miandehi region, located in the Northeast Iran, has been selected as a test area to assess livestock pressure. Present paper assessed the pressure of livestock within the studied area using GIS. FAO-UNEP model (1984) proposes the use of a ratio of potential carrying capacity to present livestock density as an estimate of pressure of livestock. This method has been adopted with some modifications for the present study. Therefore, maps of the hazard of pressure of livestock were prepared after overlying and calculating different parameters in GIS. According to the final map of pressure of livestock in Miandehi region, areas of no hazard, slight hazard, severe hazard and very severe hazard comprised respectively 21.3, 5.6, 9.8 and 63.3 % of the study area. Results showed that areas under very severe hazard dominate Miandehi (63.3 % of total land).

Abstract In order to prevent any damages which can be caused by flood at Haraz watershed in the Mazandaran province, it is essential to prepare a flood susceptibility map using logistic regression. About 211 flood locations and 211 non-flood locations were first recognized. Ten flood conditioning factors such as Slope, plan curvature, altitude, distance from river, topographic wetness index (TWI), stream power index (SPI), rainfall, landuse and normalized differences vegetative index (NDVI) were then identified. The maps of all affecting factors were prepared using ArcGIS10.1, ENVI 5.1 and SAGA GIS2 software and they were exported to raster formats. Flood locations were randomly divided into two groups: 70% (151 flood locations) and 30% (60 flood locations) for modeling and validation, respectively. Enter method was selected for weighing the 10 factors in SPSS.18. The factors with their corresponding weights were used in the ArcGIS software for generation of flood susceptibility map. The map was divided into 5 classes. ROC curve and area under curve (AUC) are used for the validation of derived map. The results indicated that for prediction rate, the AUC is 78.3%; thus, the logistic regression has a reasonable accuracy for flood susceptibility mapping. The findings of this research are useful and necessary for scholars, the Mazandaran Regional Water Authority (MRWA), Ministry of Energy, and other agriculture and natural resources-related organizations in order for mitigating losses and damages during flooding events.

Abstract Physical characteristics of drainage basins such
as geological materials, landuse type and vegetation cover, soil type, surface
permeability, depth of underground water table, topographical conditions and
drainage are important factors in flood occurrence which affect prevailing
equations on water movement in drainage and determine storage capacity of
drainage basins. Geology is one of the most important factors affecting flood
occurrence of drainage basin. In this study it is attempted to investigate the
effect of geology factor on flood occurrence in Joneghan drainage basin,
Shahr-e – Koord, using a new method. In this respect, after preparing base maps
consisting of slope amount , geology , landuse , erodibility of geological
material , soil depth and drainage pattern , studies were performed in two
stages as follows: In the first stage, flood occurrence of hill slopes of each
sub- catchment was investigated. For doing so, work unit map was prepared using
slope and infiltration maps. Then in each sub-catchment, land use, erodibility
of geological materials and soil depth were overlaid with work unit map one by
one and dually. In the second stage, flood occurrence of drainage was
investigated as follows: First, longitudinal profile of main drainage of each
subcatchment was prepared using GIS. For investigation of flood occurrence of
drainages, slope and permeability of geological units were used. The results of
the first stage showed that permeability, slope, erodibility of geological
materials and soil depth have the greatest effect on flood occurrence,
respectively. Also based on this four – factor method, subcatchments were
divided into five flood occurrence classes as follow: low, low to medium,
medium, relatively high, and high. The results of the second stage showed that
drainage flood occurrence belongs to two classes of low to medium and medium.
By combining slope and drainage flood occurrence, it can be concluded that the
third subcatchment with medium flood occurrence is more susceptible to flood
relative to other subcatchments. With regard to the results of the present
study, it can be concluded that geology has high impact on flood occurrence and
permeability of geological materials decrease flood occurrence in the basin.

Abstract Distinguishing the susceptible areas to landslide using different landslide susceptibility mapping (LSM) models is one of the primitive and basic works to reduce probable damages and reduce risk. The main purpose of this research is the efficiency evaluation of four methods including Information value (WINF), Valuing area accumulation (Wa), Analytical Hierarchy Process (AHP), Kopta-Joshi proposed method (LNRF) for LSM in Zangvan watershed, Ilam province. At first, all the effective factors in landslide occurrence were inspected. By analyzing the parameters, nine factors including slope, aspect, elevation, precipitation, distance from road, distance from fault, distance from drainage, land use and lithology were distinguished as the effective factors in landslides occurrence in the studied area. After preparing the information of these nine factors in GIS environment, the location of landslides were determined using areal photographs and satellite images and LSM performed by the above four methods. Finally, the landslide index was used for evaluation the ability of appropriate LSM model. Based on this Index, the information value method classified more 52 percent of occurred landslides in very high danger class. Therefore, this method is more efficient and proposed as the best LSM method in the Zangvan watershed because of compatibility of landslides with high danger classes and ability of differentiation of danger classes.

Abstract This research was conducted to recognize Sibak-Sardab watershed rangeland potentials, evaluate and determine of suitability classes for sheep grazing. In this research, we used the proposed method of FAO (1992) and for information layers crossing used in Geographical Information System (GIS). In this research, sensitivity to erosion, water resources and forage production are three basic components of this study. We used the MPSIAC model for the sensitivity to erosion. The model of water resource suitability consists of three parameters, quantity, quality and water resource's accessibility. In the forage production model, we estimated the ratio of available forage to the whole produced forage in each vegetation type. According to the result 96% of the rangeland was in low suitability class (S3) and only 4% were in medium suitability class (S2). The most important factors causing the decrease in suitability were lower rates of available forage for the livestock, low forage production of classes, I, II and low palatability percentage. According to Actual use (22170 animal units in season grazing); and grazing capacity (15989 animal units) and also according to the high destruction because of heavy grazing; using a management method that can help to improve the rangeland condition is suggestion.

Abstract Soil erosion is a serious environmental problem in Vazroud watershed, which is located in the centre of the Mazandaran Province, Iran. Unfortunately, Vazroud watershed like most Iran watersheds don’t have recorded data and erosion and sedimentation gages to research, monitor and model soil erosion at large watershed. In order to assess the soil erosion risk, soil erosion modeling at the watershed scale are urgently needed to be undertaken. This study integrated the Revised Universal Soil Loss Equation (RUSLE) with a Geographic Information System (GIS) to estimate soil loss and identify the risk erosion areas in the Vazroud watershed. Multi-source (map-, space- and ground-based) datasets were used to obtain factors of RUSLE, and an integrated analysis was carried out in raster format of GIS and it was classified into five categories ranging from minimal risk to extreme erosion risk. Extensive field observations verify soil erosion risk map and total accuracy (90%) obtained. The soil erosion map was linked to land use, elevation and slope maps to explore the relationship between soil erosion and environmental factors and identify the areas of soil erosion risk. The slopes between 25 to 45 degree, the altitudes between 1180 to 2180 from sea level and bare lands have the high and extreme erosion risk in this study area. The results allow decision makers to implement management strategies to prioritization area and soil erosion reduction in Vazroud watershed. The integrated approach presented is relatively easy, fast, and straightforward, showing good potential for successful application in other areas.

Abstract Nowadays, watershed management practices are undertaken based on selective criteria and/
or a specific purpose such as a decrease in flood risk, soil erosion and the like. In this respect,
fuzzy logic has the ability to manage a wide range of options for decision making. This research
aimed to use the fuzzy logic theory to priorities watershed management practices considering
time and budget constraints in catchments with high sediment production and flood risk. This
research was carried out in the Foorg watershed of Darmian town with an area of 11137 ha. All
parameters related to soil erosion and flood risk were determined using the standard methods.
Fuzzy score for each mentioned factor was then determined. Finally watershed management
practices using the fuzzy theory and GIS were prioritized.

Abstract The analysis of the relationship between spatial distribution of environmental factors and
vegetation types is crucial for understanding mountainous ecosystems. In this research a
GIS based approach was used to produce a vegetation map for Sabzkouh protected area in
the Chaharmahal-Va-Bakhtiari province. To identify environmental parameters affecting the
vegetation cover, 6 primary and secondary environmental parameters including hypsometric,
slope steepness, slope direction, annual precipitation, temperature and sun radiation maps were
derived from the study area DEM. To investigate the relationship between these factors and
the spatial distribution of vegetation cover, quantitative analyses using statistical techniques
like Principal Components Analysis(PCA) were undertaken. Then, the spatial distribution
of vegetation types was predicted using a multi-logistic regression. Results showed that
topographic variables derived from the DEM were very useful for indicating habitats of
range and forest types. Although lack of information on the anthropogenic effects led to some
uncertainties in the interpretation of spatial pattern of vegetation types, the topographic and
climatic variables, derived from the DEM, were considerably effective in modelling the spatial
distribution of vegetation types.

Abstract In western and southern watersheds of Isfahan province, combinations of natural and human factors have caused numerous landslides related damages. One of the main strategies for restricting the damage caused by the landslide is to avoid these regions. For this purpose, it is necessary to prepare precise landslide hazard zonation map for such areas. For this purpose, by aerial photos, satellite images, geological maps and field studies , landslide inventory map was prepared in of the upstream watersheds of Karoon Basin called Marber River Basin with an area of 800 square kilometers. Then, nine factors including lithology, slope, land use, rainfall, vegetation cover, aspect, and lineaments elements such as road, fault and drainages were studied as 54 parameters. To enhance accuracy, speed and ease of analysis, all spatial and descriptive data were interred into GIS and 27466 homogeneous units were obtained by overlapping of the mentioned map layers. Analytical Hierarchy Process (AHP) and Multivariate Regression (MR) were used for multi criteria decision analysis and the results showed that both methods have the same accuracy in the separation of zones (lines) with the specific index of landslide risk.. But AHP approach of regression data, based on total quality index as an indicator of the accuracy of the learning has higher acceptability. This is related to this fact that the method has considered all 54 effective parameters due to the inherent performance of natural phenomena and events involved with the landslide. Based on multivariate regression method, only 30 of 54 variables were significant at 95% and 99% levels and r coefficient of regression equation was 57% which is quite acceptable

Abstract The use of GIS tools is one of the newest methods for performance of different land evaluation and planning projects. This research with the purpose of determination of appropriate landuse to natural land potential and improvement of land management of catchments was executed using GIS-tools in Taleghan area. At first ecological and socio-economic resources determined, mapped and entered to GIS environment. Then by analysis of more than 15 information layers, homogeneous and ecological units determined. By the use of watershed management and combined land planning model and in accordance with natural and socio-economic characteristics of the watershed, suitable landuses were proposed. At last optimum landuse map and the existing state of landuse map were adapted in GIS space. The results showed that 17 percent of the watershed area has suitable landuses while 83 percent of the watershed area needs landuse change.

Abstract In this paper the utilization of GIS for the parameterization of rainfall- runoff process, physically based hydrological model components is described. The hytrogeneity of soil and vegetation in a catchment can be expressed with distribution functions of infiltration and soil storage capacities which derived efficiently by an overlay of a soil map with land use characteristics. These distribution functions are used to consider the non-linear distribution of actual saturation within a catchment with regard to their impacts on generation of excess rainfall and deep percolation during a storm event. The newly developed infiltration model components and its parametrization by GIS was successfully applied to Kechik catchment. To obtain the nesessory information a simple digital soil map of the catchment was constructed by discretizing the watershed into 1×1 km2 grid cells, and combined with the land use classification to estimate for each cell in a soil texture class the areal distribution function of infiltration model parameters consist of surface soil moisture content, maximum and minimum infiltration capacity rate (Sm, fo, fc), coefficients of model (K1, K2, K3 & K4) and excess rainfall. The results of the model application are shown that the rainfall-effective runoff relationships during storm events in catchment, by application of GIS technology, a new generation of hydrological model for micro and macro scale can be developed under consideration of catchment characteristics and their spatial heterogeneity.