الهامه عبادی

The depletion of surface water resources has necessitated uncontrolled groundwater abstraction in various regions worldwide, resulting in substantial reductions in groundwater table levels. As populations continue to expand, the extraction of these essential resources has intensified, posing a significant threat to natural reserves. This study aims to monitor groundwater levels through the analysis of satellite imagery and to investigate the correlation between these levels and land use patterns. To accomplish this objective, relevant satellite images were acquired and subjected to appropriate pre-processing. An object-oriented methodology was employed to generate land use classification maps for two distinct years, alongside a land use change map covering a fifteen-year period from 2000 to 2015. Moreover, groundwater level maps for the study area were produced for both years utilizing the Gaussian method, recognized as the most accurate approach. The findings indicate a robust and significant relationship between land use and groundwater levels, revealing that areas with higher vegetation exhibit lower groundwater levels compared to other regions. This phenomenon can be attributed to the hydrological dynamics that facilitate the movement of water from higher potential zones to these areas. Additionally, irrigated agricultural practices demonstrated the most pronounced average decline in water levels relative to other land uses, underscoring the excessive reliance on groundwater for irrigation in the study area. The results further illustrate that the conventional kriging method with Gaussian variance surpasses other techniques in estimating groundwater table depths across both statistical periods. Analysis through conventional kriging reveals a general decline in groundwater levels throughout the majority of the plain during the study period, with a maximum decrease of 40 meters and an average reduction of 15 meters.

Soil erosion is one of the most important geomorphological processes on the earth's surface, which has accelerated due to human intervention. This process causes many damages such as loss of fertile soils, destruction of infrastructure and filling of dams. In the assessment of soil erosion, several factors should be used in a combined and integrated manner. In this regard, in basins without data or with limited data, a set of geomorphological indicators can be used in combination with other indicators and the erosion potential can be evaluated. In the current research, the erosion potential of Firouzabadchay catchment area located in Ardabil province has been evaluated. In this regard, 13 indicators, mainly geomorphological, were used. In order to combine and overlapped the layers, fuzzy logic was used in the context of the geographic information system (GIS). The results show the high potential of soil erosion in the surface of the Firozabad catchment area. Several factors are effective in the erodibility of the basin's soils, which in this context can be the wide outcrop of Quaternary alluvial formations, gypsum marls, lahar and volcanic ash, weak vegetation, predominance of steep slopes, high drainage density, existence of numerous streams, high values of roughness number and long slopes. In zones of the study basin where several factors affecting erosion have favorable conditions, the rate of erosion has intensified. In this regard, we can mention the central sub-basins of the study basin, which are among the critical areas of the basin due to the presence of alluvial and marl formations, weak vegetation, high slope, high drainage density and several other factors.

One of the important conditions for optimal use of land is obtaining information about landuse patterns and their changes over time. Landuse is usually defined based on human use of land, emphasizing the role of land in economic activities. Today, remote sensing technology is considered as the main element in landuse monitoring. The aim of the current research is to extract landuse maps for the years 2000 and 2021 in FirozabadKhalkhal region and to investigate the changes made in the studied time period in the region using the images of ETM and OLI sensors of Landsat. Also, checking the capability of basic pixel and object-oriented methods for landuse classification is another purpose of this study. In the current research, the object-oriented technique nearest neighbor algorithm and the vector machine method supporting the pixel-based algorithm have been used for landuse classification. Then, to verify the accuracy of these two methods, the overall accuracy and Kappa were extracted. The results of this evaluation show the high accuracy of the object-oriented method in extracting land use classes. Based on the results of the detection of landuse changes in the studied time period, the highest amount of changes occurred is related to the use of good pasture to poor pasture with a value of 51.72 square kilometers, followed by forest to good pasture with a value of 30.11 and the lowest changes It is related to the use of pasture and water with the amount of 0.03 square kilometers. The reasons for these changes are the increase in population, indiscriminate grazing of livestock, incorrect and illegal use of different lands. The use of more parameters such as scale, shape, compactness, color, texture, smoothness criterion and pattern for landuse classification in the object oriented technique can be considered as an innovation of the present study.

Land surface temperature is an important indicator in the study of ground energy balance models on a regional and global scale. Due to the limitations of meteorological stations, remote sensing can be a good alternative to estimating surface temperature. In the present study, the relationship between different land uses and ground surface temperature in Kosar city and spatial autocorrelation has been investigated using Moran index. Landsat 8 (OLI) and Landsat 5 (TM) satellite images were used for this purpose. The present study was carried out in four main stages: a) preparing images for 1987 and 2015, b) making the necessary predictions, c) preparing a classification map using the object-oriented method, and d) extracting the earth's surface temperature with Separate window algorithm. The results showed that dryland and rangeland agricultural uses in 1987 and 2015 have higher temperatures than other uses, due to the dryness of selected agricultural products in the selected period (June), which caused the temperature to rise. Is. In contrast, the use of water areas due to their high heat capacity in these years have the minimum average temperature. In addition, hot and cold clusters of Kosar thermal islands were extracted using the hot spot analysis index (Hotspot). Finally, the analysis of spatial autocorrelation with global Moran indices showed that the surface temperature of Kosar city has a spatial structure and is distributed in the form of clusters.

 
Landslides are one of the major geological problems around the world that cause compaction of subsurface layers. The cause of this phenomenon can be attributed to human activities such as uncontrolled abstraction of groundwater and natural activities such as earthquakes. Landslides are also one of the main geological hazards in the region, causing serious damage to buildings, roads, infrastructure and bridges. According to the US Geological Survey, subsidence involves the collapse or subsidence of the earth's surface, which can have a small displacement vector. Therefore, identifying and monitoring the subsidence phenomenon is one of the most important and vital issues to maintain stability in the regions. For this purpose, researchers use various methods to study and observe this phenomenon, which are divided into three categories based on the position of the tools used: Subsurface methods, Ground Based methods and Remote Sensing methods. One of the most important of these methods is remote sensing, which collects data from the air or space using satellites, airplanes, or unmanned vehicles and balloons. Radar interference or InSAR, as one of the methods of processing radar images in active remote sensing, is one of the most accurate and economical methods that allows the detection and detection of differences in altitudes created in the shortest time and for large areas. 

The study area is located in western Iran and one of the parts of Kermanshah city located in Kermanshah province is located in the area between latitudes 42 degrees and 9 minutes north and longitude 36 degrees and 2 minutes east. Radar interferometry studies in this study were taken by sentinel 1 satellite imagery of the C band. In this study, data from Sentinel 1 satellite in C-band were used. Using image processing with SARSCAPE 5.2 plugin in ENVI 5.3 software platform and using interferometry method, areas exposed to subsidence and the amount of subsidence in each area were determined. In the present study, the relationship between groundwater level drop and subsidence of Mahidasht plain has been investigated. For this purpose, groundwater depth data of 31 piezometer wells in Mahidasht plain were used. In terms of time, considering the accurate and available statistics, the statistics of 1394 and 1398 were cited. The steps of the research were as follows: after preparing the statistics of piezometric wells, the data reconstruction method was used to eliminate the deficiencies in the study data. The reconstruction method used, which was used only to correct the defects in the data, is the interpolation method, which was performed by Neural Power software (based on artificial neural network). To normalize the data, logarithmic transformations were used in SPSS 16 software and GS+ software was used for geostatistical analysis.

 Examination of subsidence status during the study years shows that from 2015 to 2020, the rate of subsidence has increased. In Figure 1, the areas marked in red have the highest subsidence, the areas marked in green and yellow have the least subsidence, and the areas marked in black have no subsidence. According to the subsidence map of the region, the maximum average subsidence rate in the study area reaches 16 cm. According to the extracted subsidence map of the study area, it is observed that the highest amount of subsidence occurred in the eastern part of Mahidasht plain, which decreased to the west of the plain, so that in the western and south western part of the plain, the lowest Subsidence is observed.Relationship between groundwater extraction and land subsidence phenomenon Considering that groundwater abstraction is one of the important causes of subsidence in Mahidasht plain, in order to explain the trend of groundwater level changes, the general trend of annual water level of all wells were examined. According to the groundwater level interpolation map, the groundwater depth in Mahidasht plain varies from a maximum of 21.62 meters in 1994 to a maximum of 24.71 meters in 1998.

Land subsidence is a pervasive phenomenon in the world, which has had a significant quantitative and qualitative manifestation in recent decades, mainly due to the improper exploitation of groundwater resources and the intensification of its decline. In the present study, the relationship between groundwater level drop and subsidence of Mahidasht plain has been investigated. Examination of statistics related to the depth of study wells as well as groundwater level zoning maps confirm the decrease of groundwater level. In fact, over-harvesting and lack of balance between feeding the aquifers and draining them has caused the water table in the region to follow a continuous downward trend, with the emptying of water in the cavities of the aquifer and the displacement of water in these cavities with Air reduces the equilibrium pressure between the layers. Due to the disturbance of the balance between the pressure and the weight of the upper layers, due to the force of the weight of the upper layers, the aqueous layers are compressed and the water table decreases and because this decrease has a direct relationship with subsidence. Therefore, in order to deal with this environmental problem, it is recommended to prevent the development of subsidence in the region or to minimize the occurrence of this phenomenon as much as possible by managing land use in the area of subsidence and also adequate supervision over the extraction of underground resources.

Today, soil erosion and sediment production are considered a danger to humans and their lives, so in areas where soil erosion is not controlled, soils gradually erode and lose their fertility. The aim of this study is to model the relationship between the amount of suspended sediment load and the geomorphic features of the Nirchai River Basin.

In this study, GIS was used to extract geomorphic features and its relationship with sedimentation. Stepwise multivariate regression analysis was used to determine the relationship between geomorphic characteristics and sedimentation of each sub-basin. The results of investigating the relationship between geomorphic characteristics and sediment in sub-basins showed that the amount of sediment produced had a positive correlation with the volume of flow and the form factor of the basin and was significant at the level of 5 percent. Also, in order to identify the factors affecting the amount of sediment in the basin among the existing variables, the principal component analysis method was used.

The results show that among 25 variables affecting sediment production, four factors of area, basin coefficient, environment and discharge were 37/78, 25/47, 18/5 and 11/22 percent of variance of all variables of research.

Therefore, it is concluded that in total, all the effective factors of the four final extracted factors were able to explain 92.9 percent of the variance of all research variables.

Background and Objective :

Groundwater is the most important source of fresh water in the world. Drinking water for two billion people is supplied directly from groundwater and is used to irrigate the world's largest food supply. Improper harvesting of groundwater reservoirs has led to the fact that the amount of feeder feed is not responsive to harvesting and the groundwater level has dropped. The drop in groundwater levels has led to problems such as drying up water wells, declining river and lake discharge, lowering water quality, increasing pumping costs and water extraction and land subsidence. Awareness of water level changes is necessary to understand the status of groundwater aquifers and their optimal management. By assessing groundwater level fluctuations, it can be used to manage water resources. One of the major applications of remote sensing is the detection and determination of land use changes. Using remote sensing, it is possible to study and identify various phenomena. The aim of this study was to investigate the effect of different land use on groundwater using interpolation geostatistical methods as well as object-oriented classification methods for land use mapping.

Materials and Methods:

 Ardabil plain is a mountainous plain located in northwestern Iran and east of the Azerbaijani plateau. The plain covers an area of 990 km2 among the highlands around it and in terms of political divisions includes parts of the cities of Ardabil and Namin. The data used in this study included a Landsat 8 satellite image of the OLI surveyor for the 2015 land use map, as well as a Landsat TM 5 surveyor for the 1987 land use plan. Also, in this study, the groundwater depth data of 43 piezometer wells in Ardabil plain were used. In this research, after preparing the statistics of piezometric wells, the data reconstruction method was used to eliminate the deficiencies in the study data. Reconstruction, which was used only to correct deficiencies in the data, is an interpolation method performed by the Neural Power software (based on the artificial neural network). To normalize the data, logarithmic transformations were used in SPSS and GS+ software was used for geostatistical analysis. ENVI software was used for atmospheric and radiometric corrections and ArcGIS software was used to extract the layer map.

Results and Discussion:

 The largest area in 1987 belongs to the irrigated agricultural class with an area of 51840 hectares. The second area belongs to the rainfed agricultural class, which has the largest area with 48,790 hectares. The smallest area also belongs to the use of water with 88.65 hectares. Looking at the uses of 1394, the results showed significant differences in such a way that the use of irrigated agriculture with 10.17 hectares has increased significantly compared to 1987. After extracting the land use change map to select the best intrusion model from among the various models, all models were evaluated and only the models that were more accurate than the other models were selected. The highest average water level was recorded in 1987 for agricultural agriculture and the lowest average water level was recorded for the forest area. Considering the land use map and the groundwater level map of 1394, the above analysis is confirmed and as it is known, the highest average water level this year belongs to the use of irrigated agriculture with 20.17 meters and the lowest average recorded water level is related to the use of the forest is 11.45 meters. Compared to 1987, water use has had a decrease in water level, which has reduced the water level of dams and also reduced the volume of water in rivers and even dried up several of these rivers. After water use, one of the most interesting uses that need to be analyzed and the reason for its search is the use of irrigated agriculture. This land use has the highest water level drop in 1987 and in 2015 it has faced the highest water level drop. The reason can be attributed to the over-harvesting of groundwater for irrigated crops that need more irrigation. Due to the fact that the Rain-fed crops in the study area are mostly wheat and do not need water or needless, but the amount of groundwater level in 2015 compared to 1987 has been accompanied by a significant decline. The use of pastures in 2015 compared to 1987 has dropped significantly, which indicates the critical situation of groundwater and excessive use of these resources.

Conclusion:

 In this study, in the first step, in order to classify and then examine the changes that occurred in a certain period of time in the study area. In order to classify the relevant images, An object-oriented classification method was used in eCognition software and the relevant outputs were extracted in ArcGIS software. Evaluation of classification accuracy for 2015 has a very high accuracy so that the overall accuracy and coefficient of the extracted Kapa at the highest possible level, the overall accuracy of 100% and the coefficient of Kapa 0.99 and for the year 1987 was extracted with less accuracy and general accuracy for In 1987, 98% and the Kappa coefficient was 0.95. After extracting the land use change map to select the best intrusion model from among the various models, all models were evaluated. Due to ME and RMSE values, the curing method has higher accuracy than other methods. Among the various modes of the curing method, the Gaussian model has the highest accuracy. According to the results, the most changed use in this area has been the use of pastures in irrigated agriculture and Rain-fed agriculture. This change shows that the increase in the use of irrigated agriculture and Rain-fed agriculture in this area has been accompanied by a decrease in the use of rangelands, which indicates the destruction of pastures. According to the groundwater level map, the highest average water level was recorded in 1987 for irrigated agricultural use and the lowest average water level was recorded for the forest area. Also, the highest average water level in 2015 belongs to the use of irrigated agriculture with 20.17 meters and the lowest average recorded water level is related to forest use with 11.45 meters. One of the interesting uses that need to be analyzed and the reason for its search is the use of irrigated agriculture. This land use has the highest water level drop in 1987 and in 2015 it has faced the highest water level drop. The reason can be attributed to the over-harvesting of groundwater for irrigated crops that need more irrigation. In general, all uses in 2015 compared to 1366 have faced a decrease in water balance. As a result of these changes, farmers have made more use of groundwater resources, which has led to a drop in groundwater levels over a 28 years period in the study area. This overuse is enough to reduce the average level of the plain by 4.9 meters during the mentioned period.

So that the morphological and transverse changes of the Ghezelozan River have been evident in recent years and caused some problems. In this study, the detection of river side changes was carried out using satellite imagery of TM and OLI Landsat 5 and 8 in the period 1993 to 2013, during which an interval of 158 km from the Ghezelozan River, using the transect method evaluated. The channel duct was divided into 24 transects based on morphology and the process of change. The average migration rate of the Gezelozan River duct has been around 4.47 m / year over the past 20 years. The highest transhumance rate between 1993 and 2013, at 10.58 m / year, is related to transect 16, resulting in 52.51 hectares on the right bank of the river. Overall, the results show that during the period 1993 to 2013, close to 207.14 hectares was added to the right bank of the river and nearly 215.31 hectares from the right bank were decreased. Also, in this study, sinusoidal index was used to study the shape of the duct flat, based on which there are 15 sinusoidal transects.

Due to high salinity of surface waters in Tabriz plain, which is one of the major concerns about irrigation and sustainable agriculture in the area, farmers exploit groundwater as supplement for surface water to irrigate their fields. This study aimed to apply Algebraic and Geo-statistical models for mapping groundwater depth through Tabriz plain over a period of 13 years (1380 to 1392) using data collected from 42 piezometric wells. Used models include Inverse Distance Weighted (IDW) and Radial Basis Functions (RBF), as representative of algebraic methods and Kriging as representative of Geo-statistical methods. Selection of appropriate method and validation of models were done by means of cross validation, mean bias error (MBE), root mean square error (RMSE) and coefficient of determination (R2). Results indicated that Kriging is more precise than other methods for zoning mapping the depth of groundwater, and the output map corresponds highly with land use, drainage networks, geology and through the study area. So, the method is considered to as the best model to zoning mapping the groundwater depth through Tabriz plain. Also, comparison of groundwater depth zoning maps over examined periods is indicative of an increase in groundwater depth in Southeast, East, South and partly North of the study area. This increase of groundwater depth could be related to improper exploitation of groundwater resources considering given garden lands located on the parts of the study area

The aim of this study was investigating the impacts of Bukan's Dam construction on hydrological indices based on the Flow Duration Curves (FDCs) of the Zarrinehrood River during the pre (1955-1971) and post-dam (1972-2011) construction periods. For this aim, nineteen hydrologic indices were calculated in four groups of Peak Flow, Flow Duration, Low Flows and Flow Variability. In this regard, the Flow Duration Curves were plotted for both pre and post-dam construction periods. Based on the results, the values of 1-day maximum flow and the average of daily flow in the post-dam construction period decreased by 13% and 7.5%, respectively. However, the values of the index for 1-day minimum flow in the post-dam period increased by 4.7 percent. The results showed that at 50% of the flow duration time in post dam construction period the amount of discharge was increased 40%, which related to the impact of the dam on the flow of the Zarrinehrood River. The average magnitude of the rising rate relative to the average flow discharge in the pre and post periods of the dam were 97.71 and 79.18 cubic meters per second respectively, which indicated a 18% decrease in the flow of river flooding during the period after the dam construction. In the post-dam period, the average amount of discharge increased in summer season. In conclusion, the construction of the dam had reduced the flood variation related indices and increased the indices of the flow related to the duration components.

Groundwater (GW) is the most important source of freshwater on our planet. The use of groundwater has increased manifolds in the recent past due to increased water demands owing to the accelerated growth of population and industrialization. Over-exploitation of groundwater resources over the past few decades has caused quantative and qualitative constraints.Today, groundwater resources encounter with numerous problems such as loss, declination of level, chemical wastewater of industries and agriculture inputs, salting and etc. This issue is very significant in arid and semi-arid areas due to low precipitation and limited recharge of aquifers. Considering the issues, it is essential and highly needed for a comprehensive, accurate and reliable estimating of groundwater level in aquifers of arid and semi-arid areas. In this context, various interpolation methods have been initiated in environment of geographic information system (GIS) to determine the spatial variation of groundwater level. Correct selection of one method among several ones is important and basic step related to water resources management. Sarab plain is one of the fertile plains of East Azarbayjan province, NW Iran, where inhabitants economy is based on agriculture and ranch. Due to arid and semi-arid climate, life of human associations is greatly depends to water resources supplied in streams and aquifers in this area. Thus, the knowledge of spatial variation of groundwater level based on scientific and accurate estimation is essential in order to optimal exploitation and management of groundwater resources in the study area. This research aimed at optimum estimation of spatial variation of GW over Sarab plain by comparison of various interpolation methods and presentation of zoning map of GW in the area.
Methods and Meterial: Data include the sample data of GW depth collected from 50 wells over Sarab plain were used. We use the data of 2012 year, considering the most newest and reliable data. The process of the research is so that firstly, database of groundwater depth was prepared in GIS environment. Then, spatial statistics of the variable based on various interpolation methods was analyzed. In this regard, the aim is to choose the most suitable method for mapping the groundwater level zoning using cross-validation method and relevant criteria (mean bias error (MBE), root mean square error (RMSE) and square of correlation coefficient (R2) between estimate and observed rates).Used interpolation methods include algebraic and geo-statistical models that follow:- Algebraic Interpolation

In Algebraic methods one or more procedures fitted to set of observed points (z) with definite coordinates. Algebraic interpolation can be exact or approximate, so that if observed values are considered as exact value (having no error or uncertainty) at the sampling sites, using a precise method for interpolation is recommended. But, if we consider some uncertainty for variable, we may select a smoothed method. So, we can use various mathematical functions for fitting the interpolation levels to given points in this group of interpolation methods. Algebraic methods used in this research include Inverse Distance Weighted (IDW) and Radial Basis Functions (RBFs).
- Geo-statistical Interpolation Methods (Kriging) Geostatistics is an effective tool for modeling the spatial structure of various physical parameters. This approach include methods based on statistical properties of the spatial series of given variable such as mean and standard deviation. It analyses the spatial variation of the variable using different semi-variogram models to obtain the best linear unbiased estimators of spatially dependent data.

The results of comparison and validation of the methods are as follow:-Inverse distance weighted (IDW):In this method we used at least 8 to at most 10 neighborhood points for mapping the groundwater level, having lowest error among other points based on cross-validation. RMSE and MBE of this method are 10/78 and 1/26, respectively.
- Radial Basis Functions (RBF):Cross-validation of RBFs showed that the spline with tension model has lowest estimate error among others. RMSE and MBE of the method are 10/62 and 0/27, respectively. Furthermore, resulting map of this method was smoother than IDW map.
- Geo-statistics (Kriging)
Since the used data in this method should have normal distribution, we transformed the data into normal form by log normal method. Results of the comparison of Kriging models based on Cross-Validation showed that the Rational Quadratic model had lowest estimate error in among models of this approach. So, we used this model for zoning of groundwater level. RMSE and MBE of the method are 9/79 and -0/76, respectively.
Totally, the comparison of Algebraic and geo-statistical models indicated that the Kriging method was the most accurate method for estimating the spatial variation of groundwater level in study area (table 1). This fact was attributed to consider the spatial structure of data in one hand, and reduction of variance of them in other hand. Furthermore, zoning maps of groundwater level showed that groundwater level over Sarab plain was high. Spatially, groundwater level was high in southern sections compared to northern sections.

We examine the accuracy and efficiency of interpolation methods including Inverse Distance Weighted (IDW), Radial Basis Functions (RBFs) and Kriging to spatial estimation of groundwater level in Sarab plain, NW Iran. Results indicated that Kriging was the most efficient and accurate model among others for estimation and zoning the groundwater level in the study area, having lowest estimation error (RMSE= 9/79) and highest square of the correlation coefficient between estimate and observed rates (R2= 0/31). This fact can related to considering the spatial distribution and structure of used data by Kriging. In this regard, Kriging minimizes the amount of variance to enhance the prediction power of interpolation model. Also, this method prevents the impact of absolute minimum and maximum rates within data. Resulting zoning map of groundwater level over the plain showed lower groundwater depth in southern areas respect to northern areas. This geographic distGrounwater Level, Interpolation, Algebraic Models, Geo-statistical Models, Sarab plain.
ribution of the variable may be attributed such factors as lithology, drainage system and human activities and exploitations of water resources, need to further study in future. It should be more attention from water resources planners and policy makers to areas with high groundwater level, considering the relationship between GW depth and such hazards as water loss, water pollution and subsidence.

The study addressed Mshginshahr County for ecotourism assessment, because of having ýnatural potentials, aimed to ecotourism zoning using fuzzy multi-criteria analysis in the ýarea. In this regard, data and information of 9 environmental criteria including climate, ýslope, aspect, elevation, distance from streams, density of vegetation, soil, lithology and ýdistance to faults was collected according to different library documents. Preparation, ýmanagement and analysis of data were performed by geographic information system ýý(GIS), finalized by zonal mapping of ecotourism potential in the area. Results of the ýzoning map showed that there is good potential for ecotourism in the area. Also, the ýmap has a suitable agreement with environmental properties of the area. According to ýecotourism potential zoning map, about 17 percent of the county had high ecotourism ýcapability and 72 percent of it had low ecotourism capability. Spatial concentrationþ þof ýecotourism suitable extents in the south, occupied by good ranges and forests, persuades ýus to prioritize the development of ecotourism in the zone. In contrast, domination the ýunfavorable climate and consequently poor vegetation cover in northern half of the ýcounty have decreased the ecotourism potential in this zone, so that apart from a few ýscattered locations in the north, most of the northern half of the county has low ýecotourism potential.ý