جستجوی مقالات مرتبط با کلیدواژه « پهنه بندی » در نشریات گروه « جغرافیا »

Landslides represent a significant natural hazard, causing substantial damage and economic losses worldwide. Accurate landslide susceptibility assessment is crucial for mitigating these risks. This study employs a Geographic Information System (GIS) and the Analytical Hierarchy Process (AHP) to investigate and map landslide susceptibility in the Kiasar 1:100,000 quadrangle, Iran. This study employed a comprehensive set of influencing factors to assess landslide susceptibility including geology, slope, aspect, precipitation, seismicity, faults and folds, distance to roads, distance to rivers, erosion, and land use. Among the selected criteria, precipitation and slope were assigned the highest weights of 0.27 and 0.22, respectively, reflecting their significant influence on landslide occurrence. Conversely, drainage and land use received the lowest weights of 0.034, indicating their relatively lesser impact. The study findings revealed that approximately 6% (151.68 square kilometers) of the total study area (2500 square kilometers) is classified as susceptible to landslides. This corresponds to 22% of the total area occupied by villages within the investigated region. Furthermore, field verifications confirmed that the main power transmission lines and primary oil pipelines are not exposed to landslide hazards. However, some mines within the study area were identified as being at risk. Within the study area, two industrial facilities – a bakery and a fruit preservation plant – were identified as being located within landslide-prone zones. The high correlation between historical landslide occurrences and the methodology employed in this research suggests that the adopted approach is well-suited for landslide susceptibility mapping in mountainous regions characterized by climatic and vegetation diversity.

Text Landslides are one of the types of large-scale processes that cause many human and financial losses in many parts of Iran and the world every year. The increase in population and the expansion of human settlements in mountainous areas, the difficulty of predicting the occurrence of landslides and the numerous factors influencing the occurrence of this phenomenon, reveal the necessity of landslide risk zoning. Identifying the effective factors in the occurrence of this phenomenon and its risk zoning is one of the basic and practical methods to achieve its forecasting, control and monitoring solutions. By using field studies, geological and topographical maps, and by reviewing the researches and studies done in this field, as well as examining the existing conditions in the studied area, 9 factors of elevation, slope, slope direction, lithology, distance from the fault. , the distance from the river, the distance from the communication roads, land use and rainfall were investigated as factors affecting the occurrence of landslides. Therefore, the purpose of this research is to investigate and analyze the most important factors involved in creating the risk of landslides in Garami city and to identify the prone areas that will probably be involved in landslides in the near future. In this research, the zoning of prone areas was done with the Aras multi-criteria algorithm in the Edrisi software environment, and according to the results of landslide risk zoning; The criteria of land use, slope, and lithology are the most important factors involved in creating the risk of landslides in the study area with weight coefficients of 0.187, 0.152, 0.152, and 0.142, respectively, and are 361.99 and 450.32, respectively. A square kilometer of the area has a very high probability of danger. Finally, it can be said that the most important factor involved in increasing the amount and potential of landslides in Germi city is the change of land use and the increase of agricultural land and livestock pastures.

The aim of this study was to assess the climate capability of agricultural areas in Kurdistan province for the cultivation of four medicinal plants: chicory, fennel, foxglove, and shallot. Numerous studies have been conducted on the zoning of agricultural products and medicinal plants, but the optimal location of these four plants in Kurdistan province has not been done. To do this, first, using meteorological data from eight synoptic stations, climatic criteria such as annual precipitation, altitude, average temperature during flowering period and average temperature during plant growth period were extracted and entered into the geographic information system quantitatively. Then interpolation of each of these criteria and conversion of them into information layers based on the minimum RMSE was performed. Finally, based on classification and overlapping weighting function, the results showed that 94.8% of agricultural lands in the province are climatically suitable and very suitable for cultivation of chicory and fennel medicinal plants. For foxglove and shallot plants, this amount reaches 47.2%. The conclusion that can be drawn from this study is that climatic variables such as precipitation, altitude and average temperature during flowering period for chicory and fennel medicinal plants create much less limitation than foxglove and shallot medicinal plants. The results of this capability assessment can be used as an effective guide for agricultural extension experts, farmers and developers of these plants in the province’s regions.

Flooding is one of the most important challenges facing human civilization and its impact is expected to increase due to climate change and massive urbanization. The purpose of this research is to zonate flood occurrence using WMS hydrological model with GIS integration in Shahristanak watershed, one of the sub-basins of Karaj dam in Alborz province. In this study, geological maps 1:100000, topography 1:2000 and 1:50000, soil 1:100000, and data from synoptic and rain gauge stations are considered as the most basic data of this research for flood zoning in Shahristanak catchment area. Also, ArcGIS 10.3, WMS software was used to analyze and prepare maps. A modified version of TOPAZ model along with WMS was used to calculate the flow direction from the DEM active area. The results show that in the upstream and downstream of the catchment basin, as we move away from the center of the river, the area of water depth increases. While in some places upstream of the river, the water depth is less. In other words, the lower the water depth, the greater its area, and the greater the water depth, the smaller its area. Most of the area is 4.03 meters deep, which is equal to 44.2 hectares. The area of the depth of 8.06 meters is equal to 14.5 hectares, the area of the depth of 12.09 meters is equal to 4.6 hectares, the area of the depth of 16.12 meters is equal to 1.4 hectares, and the area of the depth of 20.15 meters is equal to 1.1. It is hectares. In general, the WMS model and its integration with GIS is for flood zoning and determining risk ranges in the region.

The growing population and development of cities along rivers in the area of canals and their blockage have created flood-prone areas and increased the damage caused by it. The purpose of this study is to zoning flood risk in the city of Maragheh . have been used criteria, the distance from the river, distance from drainage lines, population density, residential density, slope, dem, aspect, land use. the layers were weighted by network analysis Process (ANP) method using Super Decisions software. According to the coefficients obtained in the ANP model, the waterway factor with a coefficient of 0/7500 had the highest value and the land use factor with a coefficient of 0/0895 had the lowest value for creating floods, and then all layers were fuzzy in GIS environment and with weight Hanging the layers and combining them by gamma method, the final flood zoning plan was prepared. Based on the results, areas with very high flood risk in the city center along the Sufi Chai River with an area of 3/126 hectares. They are located in areas 1, 2 and 3 and areas with low flood risk in the outskirts of the city with an area of 13/595 hectares in areas 5 and 7, respectively. The results from integration of ANP and Fuzzy models, as approved in previuos studies, indicate their high efficiency in identifying the areas with high flood risk. Therefore, it is essential to consider the zoning layers in planinig proceses, particularly rsik assessment

In recent years, the population growth, the increase in irrigated land and economic development have caused the increase in the demand for groundwater resources all over the world. In arid and semi-arid regions where surface water does not have a significant amount due to low rainfall and high evapotranspiration, people lives mainly depend on groundwater. As a result, it is necessary to identify the groundwater potential areas and determine its recharge areas using accurate technologies. So, the aim of this research is to compare the method of multi- influencing factors with the fuzzy method for determining the potential of groundwater in a part of Kebar-Fordo watershed, Qom city, Iran.

For this purpose, a part of Kebar-Fordo watershed located in Qom province was selected. Six factors layer, viz. slope, annual rainfall, distance from river, geology, soil, and landuse were considered and classified based on groundwater potential susceptibility in different scales. Multi-influencing factor method can determine the groundwater potential of the region by assigning appropriate weight to different effective factors. In this approach, the layers were combined in Arc-GIS after determining the weight of the layers. In the fuzzy method, the layers of six factors were converted to fuzzy based on the linear function, and then the layers were incorporated using the gamma function. Finally, the statistics of observation points and accuracy index were used in order to evaluate the models,

The slope map represents that most part of the studied area (78.56%) has a "0-1" class while "1-3", "3-9" and "9-25" slope classes could be observed in 19.97, 1.29 and 0.18% of the total area, respectively. The soil texture has a significant effect on the infiltration and percolation of the surface water movement towards the groundwater. Therefore, in this research, the soil factor has been investigated as one of the input factors to the models. Soils with high permeability are more suitable for groundwater recharge and vice versa. The soil texture of the area consists of sandy loam, loam, sandy clay loam, and clay loam textures, which cover 3.73, 90.72, 0.23, and 5.32% of the total area, respectively, with a rank of four to one  for groundwater potential. In this study, geology map showed that Qft2 formation has the largest area (88.98%) and Plc formation is in the second rank (4.9%). Qft1, Qs.d and Mur units have an area of 2.22, 2.12 and 1.10% and the smallest area belongs to OMq formation (0.68%). Also, different types of land use in the study area were agriculture, garden, rangeland, bareland, and resendential area. The land use map showed that the largest area of this area was ariculture landuse (77.18%), while garden and rangeland covered 0.07 and 6.5% of the total area, respectively. Bareland and residential area comprise 2.94%, 13.31% of the total area, respectively. Among the different landuses, agriculture and residential area have the highest and lowest ranks in groundwater recharge. The rainfall map was categorized with four classes. The classes of 140-156, 156-168, 168-182, and 182-203 mm layers include 14.15, 48.92, 21.84 and 15.09% of the total area with the rank of one to four for groundwater recharge, respectively. The map of distance from the stream was divided into four categories: "0-659", "659-1480", "1480-2675" and "2675-4939" meters, which comprise 46.33%, 34.15%, 15.72% and 3.8% of the total area, respectively. In the method of multi influencing factor, the distance from the stream (8.33%) and the geological factor (25%) were the lowest and highest weights. In this regard, the factors of rainfall, slope, soil, landuse have 20.83%, 16.67%, 16.67% and 12.5% weights, respectively. Then, the groundwater potential map was prepared through overlaying in ArcGIS and the studied area was classified into suitable and unsuitable classes. The suitable class covers 75.15% of the studied area and the unsuitable class covers 24.85% of the total area. In the fuzzy method, the unsuitable class comprises 43.63% and suitable class covers 56.37% of the area. In order to evaluate the models, the statistics of the observation points were applied which the accuracy of the multi- influencing factor and fuzzy models was calculated as 71.42 and 78.57%, respectively.

Preparation of groundwater potential map is necessary to adopt management measures of rainfall storage and groundwater recharge in arid and semi-arid regions and it can be used for sustainable management of groundwater resources. The findings of this research revealed both model's accuracy in the studied area.

Floods are one of the natural hazards that cause financial and human losses every year. This research was carried out to determine the flood risk zones in the Friesian watershed with Artificial Neural Network Model and Support Vector Machine to identify the influential factors in the occurrence of floods in the region, necessary measures for control, planning and protective and management measures in to reduce the risk of flooding.

This was an applied, analytical and developmental study carried out in 2023 in Firizi watershed. 14 environmental parameters were used for flood risk zoning. Then, 150 flood points in the basin were extracted using satellite images and randomly divided into 70% for model training and 30% for validation. Then, the layers were weighted, and the flood potential maps were classified into 5 categories: Very high, high, medium, low, and very low, using the natural fracture method. Then, the accuracy of the models used in the research was investigated using the Receiver Operating Characteristic method.

The research assessed the accuracy of the models by employing the Receiver Operating Characteristic approach. The collected findings indicate that the Artificial Neural Network model outperformed the Support Vector Machine model, with an Area Under the Curve value of 0.923 compared to 0.898.

The flooding in the basin primarily affected areas with gentle slopes, rocks that are resistant to water flow and not easily penetrated, lower altitudes, and lands located next to rivers (known as floodplains). The basin contains areas that are classified as high and extremely high-risk, primarily in its central and outflow regions.

Flood zoning maps provide valuable information about the nature of flood and its effect on floodplain lands. A set of effective factors must be defined to map flood susceptibility or, in general, to develop a model for assessing natural disaster risk. The factors affecting flood were used in eastern catchment area of lake Urmia which include altitude, slope, distance from the river, topographic moisture index, topographic position index, roughness index, curvature level, topographic curvature section, total curvature, NDVI index, land use, lithology and rainfall according to the experiences of experts and researchers reported in previous studies. After preparing the effective layers on the flood and the point layer of the flood points, as well as performing the linear test, five methods including Multiple Linear Regression, Partial Least Squares Model, Quantile Regression, Ridge Regression and Robust Regression were used for modeling and predictions. Then the ROC curve was used to validate the results. The results of this validation showed that the partial least squares (PLS) and multiple linear regression (MLR) models with the maximum area under the curve (AUC) (0.983 and 0.997, respectively) and the lowest standard deviation (0.015 and 0.018, respectively) ) have performed better. Among these two models, PLS has slightly better results than MLR. Finally, a random forest model was used to determine the importance of the input factors, and it was found that the factors of height, distance from the waterway and slope percentage are the most influential factors on floods in the study area.

Today, due to population increase, industrial development, excessive exploitation, droughts, exploitation of underground water has multiplied. Therefore, identifying areas with underground water as one of the important sources for providing drinking water, agriculture, and various industries is considered to be one of the important and necessary issues in water resources management. The purpose of this research is to investigate and zonate the areas with underground water in Khorram Abad plain located in Lorestan province using convolutional neural network method. For this purpose, maps of nine factors affecting underground water were first prepared in the ArcGist environment. In the convolution method, the number of samples was determined as the ratio between the training set and the test set was 70:30, and the convolution neural network framework was used as 2 convolution layers and 2 integration layers, 2 complete connections. layers and finally the sigmoid layer was used for classification from the 3-3 convolution kernel, the Relu function as the activation function and the cross entropy function as the loss function. The obtained maps were classified into 5 classes: very good, good, average, low and very low. Confusion matrix was also used to validate the results of the model. 30% of the real data was used for evaluation, which resulted in an overall accuracy of 92%, that is, the model was able to correctly identify 92% of the data as underground water and 93% as the absence of underground water. The analysis of the groundwater potential map of the convolutional neural network model shows that about 57% of the area is in low groundwater conditions and 43% of the area is in good groundwater conditions.

Floods are considered one of the most important and abundant geomorphic hazards in the country, which cause a lot of damage every year. Aji Chai basin, located in East Azerbaijan province, witnesses devastating floods every year due to its large area and special topographical conditions. Therefore, the main aim of this study is to prepare a flood hazard potential map in this basin. To achieve this aim, 18 parameters effective in the occurrence of this hazard and two statistical methods of frequency ratio (FR) and statistical index (SI) have been used. The investigated parameters were Elevation, Slope, Aspect, Rainfall, Distance to the river, River density, Normalized Difference Vegetation Index, land use, Distance to bridge, Distance to dam, lithology, hydrological soil groups, Topographic wetness index, Sediment transport index, Stream power index, Drainage texture, Geomorphology and earth curvature. The location of the past flood points in the area was used to determine the parameters weight and implement the research models. The final maps were prepared from the product of the weights of each parameter class in their information layers and were classified into five classes using the Natural Breaks tool. Study the final maps showed that hazard zones spatial distribution patterns were similar in both models. In this way, the areas downstream of the basin and around the main streams of the area are the most dangerous zones. The accuracy evaluation of the results of both models with the ROC curve showed that the values of the area under the curve for SI and FR models were 0.945 and 0.919, respectively, which shows the excellent performance of both models in preparing flood hazard maps.

Drought affects a wide range of climates and ecosystems. Meanwhile, the effect radius of the drought phenomenon is more in rural areas than other areas, because rural economy and life rely relatively heavily on natural resources and agricultural activities. The present study was carried out with the aim of grouping and prioritizing the villages of Qorveh and Dehgolan counties in order to show the difference in the severity of drought and the degree of vulnerability caused by it. The data obtained from calculating the severity of drought showed that the counties of Qorveh and Dehgolan had a mild drought during the studied years. Also, in the discussion of drought vulnerability in the studied settlements, 13 villages were selected as samples and their vulnerability was measured using certain variables. 100% of the surveyed villages in Qorveh and Dehgolan counties have drought experience. The results of Tuki's grouping show that the sample villages are different in terms of vulnerability in the level of indicators of income from the main and secondary livelihoods of the household, exploitation of agricultural water, diversity of household livelihoods and reduction of the area under water cultivation. The biggest difference between villages is the level of access to agricultural water sources. Finally, using the spline interpolation method in the GIS system, the studied villages were zoned in terms of drought severity and degree of vulnerability.Key words: vulnerability of villages, water shortage crisis, zoning, drought

The aim of this research was to identify and rank the factors influencing the choice of architectural type and zoning based on climate conditions using the best and worst methods. Library and field methods were used to collect data. Data collection tools are databases related to climatology in Ahvaz metropolis. In order to determine the weight of each factor, the opinions of experts and ANP were used, and the factors were ranked according to the weight of each factor. The findings showed that among the obtained weights, pollution prevention with weight (0.099), sunny hours with weight (0.097) and access with relative weight (0.096) have the highest weights among the sub-indexes obtained, which are in the first ranks to They placed third. Other weights were based on the weights obtained in other ranks. Other weights were based on the weights obtained in other ranks.Other weights were based on the weights obtained in other ranks.

Earthquake is one of the natural disasters on earth that causes a lot of economic and human losses every year. Although this natural hazard cannot be predicted with current science, use of technology and technological progress, makes it possible to plan properly to reduce damages. These measures are the result of recognizing and examining the potential areas of the earth where there is a possibility of earthquake risk, and by taking advantage of it and analyzing them, the necessary preparation for earthquake prevention or control can be obtained. In this purpose, the geographic information system plays a significant role in the integration of related maps. In this research, the impact of various factors on the occurrence of earthquakes and the zoning of earthquake risk in Kermanshah county has been investigated. In order to achieve this, the fuzzy hierarchical analysis method was used to obtain the weight of each of the studied criteria and the degree of their impact, and by obtaining the small values of the weight of each criterion, a fuzzy weight map of the criteria was prepared and finally a risk map. The acceptability of different areas of Kermanshah county has been obtained. The results show that 15.6% of Kermanshah county is at risk of earthquake with "high" degree and 16.7% with "very high" degree. Also, 18.2 percent of the villages in Kermanshah county are at risk of earthquake with "very high" degree and 17.7 percent with "high" degree, and in the urban area of Kermanshah, the risk of earthquake with "very high" degree is equal to 6.3%. And it covers 18.1% of the area of Kermanshah city with "high" grade.

Currently, the utilization of the carrying capacity, which denotes the maximal number of individuals partaking in a natural sport or recreational activity at a specific moment without inducing alterations in the surroundings, is widely employed in the realm of management. The objective of this investigation is to ascertain the recreational and sporting capacity of the Dena region within the Kohgiluyeh and Boyer Ahmad province.

This is an applied mixed study carried out in 2020-2021 in Dena region. The Ecological Capability Evaluation Model (ECE) and Sport Tourism Capacity (STCC) were utilized. Additionally, the geographic notification system was implemented to finalize the layers and generate the maps. Subsequent to the validation of the present uses, three categories of capacity were approximated, namely physical, genuine, and effective physical board capacity. Consequently, appropriate zones were identified for a diverse array of concentrated and widespread recreational activities.

Findings: 

The estimated daily capacity of the study site's physical carrying capacity was determined to be 18255600. In order to calculate the actual carrying capacity of the study site, five limiting factors and thirteen parameters were utilized, resulting in a capacity of 24152158 per day. These coefficients were then employed to calculate the effective carrying capacity of the management parameters. Notably, the highest rating was attributed to the "variety of recreational uses" and "diversity of sports uses" (3.4 and 3.3 respectively), while the lowest rating was given to "Sanitation and Health" (1.6). Consequently, the effective carrying capacity for the study site was established at 10626949 people per day. The study area was further divided into four zones based on concentrated and extensive tourism, encompassing the mountain-forest ecosystem, mountainous region, plain area, rangelands and aquatic ecosystems.

The extensive tourism endeavors conducted in the northern region of the study vicinity, encompassing the mountain and forest ecosystems, alongside the plain ecosystem, have resulted in the most substantial degree of detrimental impact.

Landslides is considered as one of the major natural hazards in mountainous areas. Identifying the effective factors in the occurrence of landslides in a basin and zoning its risk is one of the basic tools to achieve solutions to control this phenomenon and select the most appropriate and practical management option. The present study aimed to evaluate the factors affecting the occurrence of landslides and its zoning using the LIM model. For this purpose, after obtaining the weight of each of the factor maps and the weight column of each unit (including: altitude, slope, slope direction, drainage density, distance from the river, distance from the road, lithological units, distance from the fault, Vegetation, land use, annual rainfall and soil hydrological groups) The final weight and landslide zining map was obtained using a model from the algebraic sum of the 11 factor layers. According to the results, arounf 34 % of the study area located in the range of high to very high risk, around 41 % in the range of low to very low potential risk, and the rest in the range of medium potential of landslide occurrence. The results of the maximum values obtaned for the final weight of different variables indiated that slope, distance from the road, land use, vegetation, height, lithology, distance from the river, rainfall, soil hydrological group, slope direction and the distance from the fault have the most to the least influence on the occurrence of landslides in the studied region, respectively. In general, the research results can provide useful information to planners in various sectors, including agriculture, industry, environment, etc.

Landslide can be defined as mass movement of materials on sloping slopes under the influence of mass gravity and triggering factors such as earthquakes, floods and heavy rains. This phenomenon is one of the natural hazards that causes a lot of loss of life and money every year in mountainous, rainy and seismic areas. By zoning the risk of landslides, it is possible to identify sensitive areas with high potential for landslides and by providing solutions, appropriate control and conduting effective management methods, the occurrence of landslides can be partially prevented or the damages caused by them can be reduced.

In this research, the effect of the rainfall system of April 2018 on the occurrence of landslides in Boyer Ahmad and Dena counties in Kohgiluyeh and Boyer Ahmad province has been investigated. The zoning of landslide risk has been performed using Haeri-Sami experimental model and the integration of thematic rock maps based on geology, slope angle, length of fault, length of road and river, amount of rain, intensity of rain and earthquake have been done in the scale of 1:1500000. After preparing the landslide zoning map, by carefully examining the Google Earth images, the areas of the studied areas where the potential of landslides were expected to be higher were identified. Then, during the extensive field visits, the geographical coordinates of the observed landslides were recorded and by preparing the point coordinates of the landslides in the Arc Map software environment and transferring them to the Google Earth images, the location of the landslides was recorded. The identification and range of each location was prepared in the form of a polygon file and transferred to the Arc Map software environment, and in this way a digital map of the distribution of landslides in the studied area was prepared. The density ratio index (Dr) was used to evaluate the landslide risk zoning map.

The results showed that only in terms of the geological factor, about 23% of the area under study has a high sensitivity to the occurrence of landslides, while other factors including the slope angle (73%), fault length (99%), and length of roads and rivers (98%) have little sensitivity to the occurrence of landslides. In terms of the amount of rainfall, in the average rainfall mode (78% of the region) it has moderate sensitivity and in the mode of April 2018 rainfall, 82% of the region is of medium sensitivity and 10% of high sensitivity with regard to the occurrence of landslides. In terms of the intensity of rainfall (79%) and earthquakes, about 58% of the area under study has a medium sensitivity to the occurrence of landslides. Landslide risk in 4 classes: no risk, very low risk, low risk and medium risk, respectively, have an area distribution of 15.1, 36.07, 43.33 and 5.5% in the case of average rainfall and 22.54, 7.9, 38.03 and 31.53% in the case of April 2018 rainfall. In the average rainfall, about 94% of the studied area is in the classes without risk to low risk of landslides, and in the rainfall of April 2018, about 69% is in the low and medium risk range.

Based on the results of landslide risk zoning, it can be said that the occurrence of landslide risk in the study area based on the studied model and the mutual conditions of the effective parameters in the average rainfall is almost low and in the rainfall of April 2018, the risk is low to moderate. Therefore, it can be concluded that the rainfall in April 2018 has a relatively significant effect on the risk of landslides. In connection with the evaluation of the efficiency of the model using the density ratio index, the model has been able to separate the landslide risk zones well, and in the very low risk class, the amount of rainfall is more accurate in both cases.

Assessments of water quality have recently developed and now include surface and groundwater pollution issues. Permanent changes occurring in the quality of groundwater, especially those affecting drinking water and salinization of water sources, are considered to be a serious threat to rural development. Unfortunately, many people lack enough knowledge about the importance of groundwater and the harmful effects of environmental pollution on these valuable resources. The present study has investigated the quality of potable groundwater in the rural parts of central Ardabil County using multi-criteria decision-making models and geostatistical analysis in GIS environment. Parameters such as EC, PH, SO4-, Cl-, Na and TH (in terms of CaCo3) have been used to create an overall picture of the quality of potable groundwater resources in Ardabil County based on which related zoning map was developed in geographic information system. The kriging interpolation method was also used to obtain the spatial distribution of the parameters and the simple additive weighting method was used to weigh and rank the layers. According to the final map of water quality, approximately 36% of the central Ardabil County (around 88 square kilometers, mainly in the southern part of the study area) has access to optimal quality of drinking water. On the other hand, low quality of drinking water is observed in the northern and northeastern parts which cover 46% of the study area (112 square kilometers). Moreover, a direct relationship is observed between the population density and the density of deep and semi-deep wells and the decrease in the quality of water.            

The present study has applied library research and field study methods. Rstudio and Arc GIS 10 software were also used to perform related analyses. Study Area Case study area includes 243 square kilometers of the central Ardabil County consisting of three cities and nineteen villages as illustrated in Figure 1. The following methods were used in this research:1- Direct rating 2- Kriging interpolation 3- Standardization method 4- Simple weighing method 5- Fuzzification of the final data The following parameters have also been used to assess the quality of drinking water:1- Electrical conductivity (EC) 2- Chlorine level (Cl-) 3-The amount of sulfate (SO4+) 4- The amount of nitrate (Na) 5 Total water hardness(TH) 6- Water acidity level (PH)

Groundwater chemical quality is primarily assessed using parameters such as changes in the amount of dissolved salts, and limitations on various uses of water especially water used for drinking. Table 1 shows different types of conventional kriging methods selected through the method test for the parameters. These can be obtained using the mutual evaluation method and RMS error. Factors affecting the quality of drinking water are then ranked and weighted according to the expert opinions. The final quality map is thus prepared. Layers are then standardized in accordance with data description and the results are presented in Table 1. It also exhibits maximum permissible and desirable level of non-toxic chemicals in drinking water in accordance with the Iranian Standards and Industrial Research Institute (ISIRI) and the World Health Organization (WHO) standard, along with the maximum permissible level of mineral substances in drinking water. Semivariograms used for kriging interpolation are also presented. Table 2 shows the RMS and RMSE errors as well as the average standard error of the water quality parameters in the study area. The interpolated primary layers are presented in Figure 3. The final map prepared for the quality of potable water in the study area indicates that the quality of groundwater in the northern part and a little section of the central part (46% or 112 square kilometers of the study area) is unfavorable. This includes 8 villages of the County. 6 villages have access to drinking water with semi-optimal quality and 5 villages are located in the optimal area of water quality. Accordingly, the quality of potable groundwater decreases drastically as we move towards the northern and northeastern parts of the study area, and the lowest quality of groundwater is observed in the most northerly part of the study area (covering 46% of the study area). Figure 4 shows the density of deep and semi-deep wells, the amount of annual harvest from rivers in the central part of Ardabil (in thousand cubic meters per year), the population density and industrial areas in this region. A direct relationship is therefore observed between population density, the density of existing wells, the level of water extraction from rivers and the sharp drop in the quality of groundwater. According to the reports prepared by Ardabil Regional Water Company, around 32 million cubic meters of water is annually needed to meet the drinking requirements of urban and rural uses, which can seriously damage the quality of underground water in the area.

According to the final map of groundwater quality, only 36% of the study area (88 square kilometers) has access to drinking water with favorable quality which can be a great concern for planners and managers. Finally, it is suggested to use geostatistical methods and geographic information system as a useful tool to assess the quality of underground water. These methods can gradually replace the old methods and thus prepare more accurate statistics, increase the efficiency of water-related projects, and reduce their cost.

Floods are one of the most destructive natural disasters that cause huge and frequent human losses ,financial and resource losses all over the world(Mishra & Sinha, 2020,1). Flash floods are caused by heavy rains and due to the sudden accumulation and release of runoff from upstream to downstream. This natural phenomenon is the result of the activity of two groups of different parameters. The first group is the meteorological features that change according to space and time. The second group of fixed parameters includes geomorphological and geological characteristics(Youssef et al, 2011,755).Therefore, identification and zoning of areas prone to flood risk is necessary for sustainable development planning and protection of human societies(Farhan & Ayed, 2017, 719). The Ojan Chai basin, which has been flooded in recent years, especially due to human intervention in basin system. One of the most unprecedented floods occurred in this basin in 2016. Therefore, according to the history of flooding in this basin, it is necessary to assess and zoning the risk of sudden flood. The aim of the current research is to evaluate and zoning flash flood-prone areas in the basin based on physiographic characteristics, which is the basis of the modified flash flood potential index (MFFPI).