Showing 39 results for Gis
H.r. Pourghasemi, H.r. Moradi, S.m. Fatemi Aghda,
Volume 18, Issue 70 (3-2015)
Abstract
The objective of the current research was to prioritize effective factors in landslide occurrence and its susceptibility zonation using Shannon’s entropy index in North of Tehran metropolitan. To this end, 528 landslide locations were identified using satellite images such as Geoeye (2011-2012), SPOT-5 (2010), and field surveys, and then landslide inventory map was created for the study area in ArcGIS environment. Data layers such as slope degree, slope aspect, plan curvature, altitude, lithology, land use, distance of road, distance of fault, distance of drainage, drainage density, road density, sediment transport index (STI), stream power index (SPI), topographic wetness index (TWI), normalized difference vegetation index (NDVI), surface area ratio (SAR) and topographic position index (TPI) were created and the mentioned maps were digitized in GIS environment. Prioritization of effective factors by Shannon’s entropy index showed that the layers such as land use, lithology, slope degree, stream power index, and NDVI had the most effect on landslide occurrence. However, factors of topographic position index and plan curvature had the least effect. Also, landslide susceptibility zoning by the mentioned model and its accuracy assessment using relative operating characteristics (ROC) curve and 30 percent of landslide locations showed an accuracy of 82.83% with a standard error of 0.0233 in the study area.
K. Shirani, A. R. Arabameri,
Volume 19, Issue 72 (8-2015)
Abstract
This research was conducted to prepare landslide susceptibility zonation (LSZ) map for the Dez-e-Ouliabasin using logistic regression model. For this purpose, at first, the most important factors affecting land sliding including slope, aspect, elevation, precipitation, the distance from road, the distance from fault, the distance from drainage, land use, and lithology were determined. Then, thelandslide inventory mapwas preparedby using field digital checks, GPS and satellite images. In the next step, the landslide susceptibility zonation mapwas preparedby usinglogistic regression method. According to the obtained coefficients for LSZ maps, the most important factor in the study area was elevation layer. The Receiver Operating Curve (ROC) index value was calculated (0.92), which indicates a very high level and suggests thatthe observed mass movements have a strong relationship with the logistic regression model.
H. Beigi Harchegani, S. S. Heshmati,
Volume 19, Issue 72 (8-2015)
Abstract
The aim of this paper is to adapt a water quality index for individual samples and to compare the results with that of the original GIS-based approach. Thirteen water quality parameters observed in 97 wells from the Shahrekord aquifer were used. In GIS-based method, quality parameters maps are difference-normalized, ranked and GWQI map is drawn. In derived method, observations from individual wells were separately and similarly treated to obtain WQI for each well. Both GWQI maps displayed similar trends and were highly correlated (R=0.91). While the minimum and mean GWQI for both methods were identical (respectively 81 and 84) the derived method estimated the maximum GWQI slightly lower (7%) and showed up to 6% difference in water quality class coverage. Overall, the derived method GWQI is more correlated with observations and performs better than the GIS-based method, and therefore, can be used for determining the overall quality of individual water samples and without the requirement of samples being spatially distributed.
M. Erfanian, H. Farajollahi, M. Souri, A. Shirzadi,
Volume 20, Issue 75 (5-2016)
Abstract
The aim of this study is to prepare the groundwater spring potential map using Weight of Evidence, logistic regression, and frequency ratio methods and comparing their efficiency in Chehlgazi watershed, province of Kurdistan. At first, 17 effective factors in springs occurrence including geology, distance to fault, fault density, elevation, relative permeability of lithological units, slope steepness, slope aspect, plan curvature, profile curvature, precipitation, distance to Stream, drainage Stream density, Sediment Transport Capacity Index (STCI), Stream Power Index, topographic wetness index (TWI) and land use/land cover (LU/LC) were selected. The validation processes of methods were conducted by relative performance characteristic curve (ROC). The area under an ROC curve (AUC) for the weight of evidence, logistic regression and frequency ratio was 85/8%, 79% and 89%, respectively. The results showed that all methods are suitable estimator for mapping the groundwater spring potential in the study area. But the frequency ratio method with the most amounts is the best method to produce and map the groundwater spring potential. Also, validation of the mappings based on the percentage of pilot springs, training springs and all springs showed that the logistic regression, WoE and frequency ratio, with 45, 56 and 45 percent of spring occurrence on the high potential classes respectively, had the highest validation.
A. Holisaz, B. Ahadi Dos, M. Kamangar, A.n Ameli1,
Volume 20, Issue 76 (8-2016)
Abstract
The last two decades have seen increasing applications of digital terrain modeling in hydrological, geomorphological, pedagogical, and biological research, aided by rapid advancement of geographic information system (GIS). Hydrologic models are sensitive to change in the input values to the model, so the change of pixel size input data affects the output values of the model and produces different significant results. In this study, using topographic maps 1:25000 and 1:50000 and choosing ten pixel sizes (10, 15, 20, 25, 30, 50, 75, 80, 100, and 200) and software Arc GIS and HEC-HMS, output values of HEC-HMS model have been studied. Results of this study indicate that accuracy of peak discharge calculated by HEC-HMS model in the spatial scale map 1:50000 is more than the peak discharge calculated by HEC-HMS model in the spatial scale map 1:25000. Also accuracy of the calculated peak flows in a smaller pixel sizes (20 to 50) is more than the larger pixel sizes.
Z. Feyzi, A.r. Keshtkar, A. Malekian, H. Ghasemieh,
Volume 20, Issue 76 (8-2016)
Abstract
Shortage of rainfall and also relatively high intensity precipitations in short-term are characteristics of arid regions of the world, such as central of Iran. Studies have indicated that massive flooding causes great loss of life and properties every year. Also, Water scarcity in arid and semiarid regions of the world will cause fragile living conditions in these areas. Therefore, it is needed to reduce runoff rates using actions such as dam construction or artificial recharge techniques. In this study, seven factors were applied such as the slope, surface permeability, transmissibility in alluvium, alluvial quality, land use, runoff volume and thickness of the unsaturated layer to determine suitable areas and site selection for flood spreading and artificial recharge in south of Kashan plain. After preparing the digital layers, criteria weights were determined using Fuzzy AHP. The weighted maps were acquired and merged together. Results indicated that land use criterion with the greatest weight (0.22) was determined as the first priority in the site selection for flood speading. The parameters of runoff volume, permeability, slope, depth of the unsaturated layer, alluvial quality, and transfer coefficient were accounted as the second to seventh priorities.
M. Fallah Sourki, A. Kavian, E. Omidvar,
Volume 20, Issue 77 (11-2016)
Abstract
Prioritization of sub-watersheds is very important and necessary in order to implement soil and water conservation practices. This study has prioritized 13 sub-watersheds based on morphometric and land use characteristics using RS and GIS techniques in Haraz watershed to identify erosion-prone sub-watersheds. Morphometric characteristics including bifurcation ratio, drainage density, stream frequency, drainage texture, form factor, basin circularity, compactness coefficient, elongation ratio, length of overland flow, shape index, and basin relief were considered in morphometric analysis. Land use map was classified into seven classes of forest, water-body, irrigated farming, bare land, rangeland, orchard and residential area. Finally, sub-watersheds were classified into four categories as very high, high, medium and low in terms of priority for soil conservation. On the basis of morphometric analysis sub-watershed WS-4 was considered as high priority, whereas according to land use analysis, sub-watersheds WS-6, WS-8, WS-12 were in class of high priority. Sub-watershed WS-4 was categorized as a very high priority class based on the integration of morphometric and land use analysis. This region was identified as critical region therefore should be considered as priority class for implementation of soil and water conservation practices.
F. Abbaszadeh Afshar, ِ S. Ayoubi, A. Jafari,
Volume 21, Issue 1 (6-2017)
Abstract
Mapping the spatial distribution of soil taxonomic classes is important for useful and effective use of soil and management decisions. Digital soil mapping (DSM) may have advantages over conventional soil mapping approaches as it may better capture observed spatial variability and reduce the need to aggregate soil types. A key component of any DSM activity is the method used to define the relationship between soil observations and environmental covariates. This study aims to compare multiple logistic regression models and covariate sets for predicting soil taxonomic classes in Bam district, Kerman province. The environmental covariates derived from digital elevation models, Landsat imagery, geomorphology map and soil unit map that were divided into two different sets: (1) variables derived from digital elevation models, remote sensing and geomorphology map, (2) variables derived from digital elevation model, remote sensing, geomorphology map and the soil map. Stratified sampling schemes were defined in 100000 hectares, and 126 soil profiles were excavated and described. The results of accuracy model showed that data set 2 increased accuracy of model including overall accuracy, kappa index, user accuracy and reliability of the producer. The results showed that the multiple logistic regression model can promote traditional soil mapping and it can be used to large group of other scientific fields.
A. Haghizadeh, H. Yousefi, P. Nourmohammadi, Y. Yarahmadi,
Volume 22, Issue 3 (11-2018)
Abstract
To determine the potential for groundwater contamination, vulnerability should be evaluated in different areas susceptible to contamination should be investigated. Aquifer (carbonate) karst or part of it is karst aquifer in the western region of Iran; due to the natural conditions of the region and human activities, they are susceptible to contamination by carbonate aquifer through holes devourer and feeding point leading to pollution. The aim of this study was to analyze aquifer vulnerability zoning map karst plain elster by using COP. This model uses three parameters including lining (O) the concentra flow(C) and precipitation regime (P) to assess the vulnerability of groundwater against pollution GIS software. The results showed that the plain with an area 7.8 km2 was dominated in terms of vulnerability, being in the middle class. Other classes, respectively, were low with the area 18.69 km2, high with the area 0.65 km2 as part of the northeast plain, and much less with the area of 0.6 km2 , The results of the sensitivity analysis also showed that at the factorization (P) due to appropriate rainfall area, the maximum impact was in determining the vulnerability of the area. And the factor (C) minimum has impact on determining the vulnerability of the area. Due to the small size of the mature karst area, the wide extent of non-karst region was shown for the verification of results related to electrical conductivity data (EC) against discharge wells in the region with the high vulnerability and moderate. A comparison was made too.
M. Mokarram, A. R. Zarei, Mohammad Javad Amiri,
Volume 22, Issue 3 (11-2018)
Abstract
The aim of this study was to evaluate the effect of increasing DEM spatial resolution on the assessment of the morphometric characteristics of waterways, as well as analysis and modeling of it by using RS and GIS techniques. In this study, which was carried out in the south of Darab city DEM 90 m (as one of the most usable data in waterway modeling), increase spatial resolution of DEM attraction algorithm in neighboring pixels with two models including: touching and quadrant neighboring models to estimate the value of sub-pixels. After manufacturing output images for sub pixels in 2, 3 and 4 scales with different neighborhoods, the best scale with the most appropriate type of neighborhood was determined using ground control points (270 points); then, the values of RMSE were calculated for them. The results showed that with using the Attraction model, the accuracy of the output of images was improved and the spatial resolution of them was increased. Among scales with different neighborhoods, 3 scales and quadrant neighboring model exhibited the most accuracy by the lowest value of RMSE for the DEM 90 meter. Evaluation of waterways morphometric features showed that DEM extracted from attraction algorithm had more ability and accuracy in waterways extraction, Extraction of morphometric complications, and information in the study area.
K. Nosrati, M. Heydari, M. Hoseinzadeh, S. Emadoddin,
Volume 22, Issue 3 (11-2018)
Abstract
Ziarat drainage basin, in the southern part of Gorgan city, is exposed to mass movement, especially landslide occurrence, due to geologic, geomorphologic, and anthropogenic reasons. The objectives of this study were to predict landslide susceptibility and to analyze the effective factors using rare events logistic regression. In view of this, the map layers of the variables including geology, land use, slope, slope aspect, distance of road, distance of fault and distance of river were prepared using topographic and geologic maps and aerial photo interpretation. In addition, the map layers of the soil variables including the percent of clay, silt, sand, and saturation water as well as plasticity limit index were determined based on the laboratory analysis of 32 soil samples collected from landslide sites and 32 soil samples obtained from non-occurrence landslide sites. The controlling factors of landslide were determined using rare events logistic regression analysis; then based on their coefficients, the landslide risk zoning map was prepared and validated. The landslide risk zoning map was classified in five different hazard classes ranging from very low risk to very high risk; the very high risk class with 16.8 km2 was assigned as the having the highest percent of the catchment area. The results of the model validation showed that the rare events logistic regression model with the receiver operating characteristic (ROC) of 0.69 could be a suitable prediction model for the study area. The results of this study could be, therefore, useful for corrective actions and watershed management landslide high-risk zones.
Z. Abbasi, H. Azimzadeh, A. Talebi, A. Sotoudeh,
Volume 22, Issue 4 (12-2018)
Abstract
Groundwater quality evaluation is very necessary to provide drinking water. Groundwater excessive consumption can cause subsidence and penetration of saline groundwater into freshwater aquifers in Ajabshir Plain, on the Urmia lake margin. The main goal of the current project was to evaluate the groundwater quality by employing the qualitative indices of groundwater and GIS. Ten parameters of 15 wells including EC, TDS, total hardness as well as the concentration of Ca++, Na+, Mg++, K+, SO4--, HCO3- and Cl- were analyzed. At first, the maps of parameters concentration were prepared by the kiriging method. Then based on WHO drinking water standards, the maps were standardized and ranked for drawing the maps of quality indices. The results showed that quality index changes were in the range of moderate (61) to acceptable (81). Removing the single map method of sensitivity analysis detected the quality index was more sensitive to the K+ parameter. Finally, the quality index from the eastern north to the western south of Ajabshir Plain and the other areas was ranked in the acceptable and moderate classes, respectively.
V. Sarvi, H. R. Matinfar,
Volume 23, Issue 1 (6-2019)
Abstract
In the face of rapid growth of the population and the need for food production sectors, one of the ways to achieve this is to increase the production per unit area. In modern agriculture, the preparation of soil fertility map seems to be necessary to plan for appropriate use of fertilizers for crops. This study was conducted to prepare a distinct map for evaluating the soil fertility according to soil chemical properties in 191 soil samples of Ardabil Plain in Ardabil Province. To achieve this goal, the available N and P, K, EC, Fe, Zn, Mn and the organic matter of soil were mapped using geostatistical Kriging estimator into the Geographic Information System (GIS) by the ArcGIS software. The Analytical Hierarchy Process (AHP) was used for weighting the soil fertility factors as the input data. Then, a membership functions was defined for each factor by factorial scoring and the map of soil fertility was prepared and classified by using the AHP technique into the GIS program. The results showed that most of nitrogen and phosphorus with the weight of 0.293, 0.202 had the mostly infraction on the soil fertility and production. Survey map of the distribution showed that most of the factors were studied in the northern region with the low nutrients. The results also showed that 23.7 percent of cultivated land fertility maps had a poor fertility status, 28.3 percent of the land had a moderate fertility status, 25.4 percent of the land was good and the fertile land with 22.6 percent had a very good fertility status.
Sh. Mohammadi, E. Karimian,
Volume 23, Issue 4 (12-2019)
Abstract
Nowadays, water supply for the sectors of household consumption, agriculture, green spaces and industry is currently one of the most important challenges for governments in many parts of the world, especially in arid and semi-arid climate regions such as Iran. The aim of this study was to simulate the amount of run-off from the daily precipitation for Sarpol-e Zahab city, for the purpose of estimating the required amount of water for the irrigation of the green spaces of the city. In this study. After providing information and using the Digital Elevation Model (DEM) map of city, all individual sub-basins of the basin were produced. All data related to creating and overlaying hydrologic, climatologic and physiographic layers were used according to the HEC-HMS hydrologic model. The run-off depth and flood volume of each sub-basin were obtained through the SCS method. Then the required amount of water for the green areas of Sarpol-e Zahab city was calculated. The efficient rainfall was estimated using four methods including SCS, 80 percentage, reliability, and USDA for each month, separately. Finally, the amount of needed water for the green area was obtained using these four mentioned methods. The results indicated that the role of curve number in the infiltration rate was more than other variants. Impermeability of urban basins and changes was created due to the growth and development of the city such as removal of vegetation, soil compaction, creation of the water collection and leading surface waters, decreasing the amount of water penetrating to soil significantly. The amount of surface water for sub-basins was estimated to be 266000 cubic meters. Besides, the results showed the amount of required water for 5 months of the year (from early May to September late) using four methods of SCS, 80percentage, reliability and USDA was equal to 243525, 238062, 267865 and 236458 cubic meters, respectively. The amount of the estimated runoff volume was 266,000 cubic meters. Regarding the area of green spaces in Sarpol-e Zahab city and its daily need of water, this volume of water could supply the required amount of water to irrigate the green area of the city for five months (From May to September).
N. Alian, M. M. Ahmadi, B. Bakhtiari,
Volume 23, Issue 4 (12-2019)
Abstract
One of the most important problems in flood manegment is the damages induced by this phenomenon. Expected annual damage (EAD) is an important index for basin vulnerability against flood. Prediction of flood damages requires the analysis of spatial and temporal risk and must be calculated by the combination of hydrologic, hydraulic and economic models. In this research, the uncertainty was considered in the flood risk analysis. The probability of flood occurrence was calculated by the parabolistic model. By using the river analysis systems software (HEC-RAS) and the geographic information system (GIS) and utilizing the Google-Earth software, the floodplains of Zayande Roud river in Esfahan province were investigated with the return period of 25, 50, 100, 200 and 500 years. The Monte Carlo method was also sed to perform the uncertainty analysis in the proposed method. The logarithmic persion type III was selected as the best distribution of flood. The damage-stage relationship was calculated as well. Based on the uncertinity analysis, the river discharge could be regarded as the major parameter in the uncertainty of EAD.
J. Zahiri, M. Ashnavar,
Volume 23, Issue 4 (12-2019)
Abstract
Hydrodynamic models proposed for simulating flow hydraulic in rivers assume the flow in one direction and simulate the hydraulic parameters based on the one-dimensional Saint-Venant equations. In this research, a two-dimensional HEC-RAS model was used to simulate the flow in the Karun River, between Mollasani and Farsiat stations. Geographic information system (GIS) and river cross sections were used to prepare the altitude map using the satellite image of the study area. Modeling results in river bends showed that the maximum velocity occurred in the outer bend, which coincided with the flow mechanism in the bends. Based on the results, grid type and density have little effect on flow depth modeling. However, the characteristics of the mesh used had a great influence on the velocity distribution, so that the regular high-density mesh had the best accuracy in simulating the flow velocity. Statistical analysis showed that the RMSE for the flow discharge and flow depth were 17.95 m3/s and 0.05 m, respectively. In addition, the Nash–Sutcliffe efficiency index was calculated to be above 0.9 for the discharge and flow depth, which could be considered as a desirable value.
F. Kaboudvand, S. S. Mehdizadeh,
Volume 24, Issue 4 (11-2020)
Abstract
The Khanmirza plain is one of Iran’s fertile plains that is located in Chaharmahal Bakhtiari province. Agriculture in the area is very prosperous, but the lack of rain and over-harvesting from consumption wells has led to a reduction in groundwater levels, even causing land subsidence. Moreover, the high usage of chemical manures, especially nitrate manures, has increased the number of solutes and chemical materials in the groundwater. Thus, for this plain, making artificial ponds is important to modify the storage of the aquifer. In this study, to define the optimum locations of the artificial ponds, the effect of 12 factors was considered. The analytic hierarchy process (AHP) method was used to introduce the weight of each parameter in comparison to other factors. Afterward, the spatial priority of all factors was derived using the Geographic Information System (GIS) technique. The produced GIS layers were laid on each other and the optimum locations were obtained. Agricultural drainage was an effective index for recharge purposes. The results of the study demonstrated that groundwater level decline got the maximum weight (40%), while the land slope had the minimum weight, since the vicinity to available floodways was considered as an independent criterion. The results also showed that regions with a total area of 18 km2 in north and north-west of the Khanmirza plain could be the optimum and most suitable places for artificial ponds construction.
J. Chezgi, M. Asiyaei,
Volume 25, Issue 1 (5-2021)
Abstract
Erosion causes the reduction and degradation and the soil fertility; one of its most important consequences, endangering the food security of the inhabitants of the area. Therefore, to reduce erosion, it needs to be controlled and managed using good soil conservation methods. It is only necessary to manage and control the full impact of the factors affecting the soil first. If there is a critical state of erosion in the four watersheds, identifying the precise location of erosion will be done quickly and with less cost; thus, further erosion control and counter-operation will be feasible. In this study, geographic information system and decision making models of AHP and ANP in Bagheran region of Birjand were used to determine the erosion prone areas. First, 10 effective criteria including rain, slope, slope direction, soil, geology, permeability, vegetation, land use, distance from road and village, were determined on the erosion in the area based on the expert opinion and library studies. Next, the questionnaires were sent to experts to explore g the impact of the criteria on erosion; after completing the questionnaires based on Expert Choice and Supper Decision software, the relative importance of the criteria was obtained. The maps were then compiled and integrated according to the relative importance of the criteria. Rainfall factor had the greatest impact on the erodibility of the area in the AHP method with the relative importance of 0.21 and the vegetation criterion with the weight of 0.158 in the ANP method had the most impact on the determination of erosion prone areas. Finally, the erodibility map of the area was obtained based on the presented models. Subsequently, the region was classified into five classes of erosion susceptibility, with areas of moderate sensitivity having the most area in both models. In the lower and upper classes, the ANP method performed better; in the middle classes the AHP method performed better.
Y. Esmaeli, F. Yosefvand, S. Shabanlou, M.a. Izadbakhsh,
Volume 27, Issue 2 (9-2023)
Abstract
The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively.
