جستجوی مقالات مرتبط با کلیدواژه « groundwater level » در نشریات گروه « جغرافیا »

The phenomenon of land subsidence can cause irreparable financial and human losses and damage many surface and subsurface structures in urban areas and their suburbs. According to the definition of the Geological Institute of the United States of America, the phenomenon of land subsidence includes the collapse or downward settlement of the earth's surface, which can have a small displacement vector, it is said to occur gradually and instantaneously on a large scale. The most important cause of the regional subsidence of the earth's surface in the sedimentary basins of arid and semi-arid regions is the condensation and compaction of sediments due to excessive extraction of groundwater sources. If watery clay layers are placed between sand layers, this phenomenon will be observed more widely and more acutely. Land subsidence usually occurs with a time delay after the long-term extraction of underground water resources. The amount of subsidence depends on the thickness and compressibility of layers, length of loading time, degree, and type of applied stress. With the decrease of the underground water level, the increase of the effective stress caused by the decrease of the pore water pressure causes subsidence. Usually, it takes time to reduce the water pressure and increase the effective tension; Therefore, following the reduction of the piezometric level, subsidence will occur with a time delay. Subsidence caused by the drop in fluid level mainly takes place in unconsolidated or semi-consolidated sediments that are located in the vicinity of sand layers. In such conditions, inelastic compaction occurs due to the increase of effective stress in the soil, the arrangement of the soil grains is disturbed and the thickness of the vertical layer decreases. In the areas where the sediments are not very thick and the underground water extraction continues indiscriminately, lines and cracks are observed on the surface of the land, especially agricultural land, and it is known as the Shaq phenomenon. The phenomenon of subsidence due to the withdrawal of underground water can have different intensities and destructive effects according to the geological situation and geotechnical characteristics of the region. In the sedimentary basins of arid and semi-arid regions, including the Mashhad Plain, the most important cause of ground subsidence is the density of underground water tables due to excessive water extraction. This situation is especially critical in the area where excessive pumping of aquifers containing sand layers is located between impermeable clay layers and causes subsidence. This phenomenon is also happening in Iran, and it is visible, especially in the eastern and central regions of the country, which suffer from drought and the water supply through underground water extraction has greatly increased. Mashhad Plain is one of the areas with a very high subsidence rate, which needs to be given more attention. Land subsidence is a dangerous global problem, and geometric methods are not suitable for extensive and serious monitoring of land deformation.

Radar interferometry with artificial valve is a remote sensing technique. In which two or more radar images are used to produce digital elevation models or to map the displacement of the earth's surface. In the above article, using radar data and using radar interferometry technique and small baseline time series analysis, the time series of land subsidence phenomenon in Mashhad is monitored and measured.In the present study, using radar interferometry and SBAS time series method, in the period from 2014 to 2021 in Mashhad city, by selecting 38 Sentinel-1 images with a suitable time interval, the average speed of land subsidence and uplift in the studied area was estimated.Then, to determine the main factors of this event, the studied area was investigated in terms of changes in the underground water level and tectonics.

The results of the analysis of the time series of the images showed that in Mashhad, the maximum ground displacement is between -77 and +8 mm, and the areas with subsidence are located in the northern parts of Mashhad, which is recorded between 30 and 30 mm. 77 mm subsidence per year. To determine the cause of this event, tectonic assessment and the status of underground water exploitation in this period and its relationship with land subsidence and earthquake data in the area were investigated.

The results of the research showed that the maximum subsidence rate is 77 mm in the area of Mashhad in the period of 7 years from 2014 to 2021 and is related to the north of Mashhad. It should be noted that while advancing towards the city center from the north, you should look for irreparable damage shortly. To check the accuracy of interferometry and interpret the results and investigate the possible cause of the subsidence of Mashhad city, the trend of changes in the water level in piezometric wells, this factor in the occurrence of subsidence in the region was investigated. The information on piezometric wells was obtained in the city of Mashhad, the results of which strongly showed the water level in the past years, which is based on the cause of subsidence in this area. Only in the center is the temporary rise of the underground water level due to the feeding of the urban Mashhad aquifer.Then, to investigate the tectonic participation in the subsidence event, the history of earthquakes and the fault network of the region were evaluated, which confirmed the absence of the investigated earthquakes (maximum 3.8 on the Richter scale) in the region and its surroundings, and there is no fault network within the area of the subsidence assets. did not have. There is no activity. The probability of supposition and the possibility of technology playing a role in the subsidence event is insignificant. Small cracks are mainly created near mental wells or agricultural water exploitation wells and are scattered much more.

Land subsidence is one of the most important geomorphic hazards that has a slow motion but destructive effects in the long run. For the spatial analysis of the amount of displacement, the data on changes of the ground surface from Sentinel A1 for a period of 3 years (2017-2020) through the radar interferometric method and SNAP software were used. Field observations were also made to evaluate the research results. The results showed that the rate of land subsidence has increased from 2017 to 2020, from 2.6 cm in 2017 to 7.8 cm in 2020. Moreover, the groundwater hydrograph in the central plain of Ghaen has significantly decreased, so that the rate of water level drop in the plain level has been about 1.30 meters during 5 years (from 2014 to March 2020), i.e, about 26 cm per year. In addition, the analysis of spatial autocorrelation and Moran index (0.984) confirmed the clustering of subsidence event under the influence of water level changes in the study area. The correlation results also showed that there was a small correlation between the factor “changes in water level” and “land subsidence rate” (p = -0.138), which is an indirect relationship, i.e., the higher the groundwater abstraction (or the lower the water level), the higher the amount of subsidence. But due to the level of significance (sig = 0.585) this relationship is not significant.

Land subsidence induced by soil consolidation is one of the natural hazards that occur gradually. This phenomenon has reached its critical state in most regions of Iran. Factors affecting subsidence are groundwater level depletion, land cover, soil type, elevation, slops gradient, rock bed depth, etc. The causes of subsidence should be investigated so that decisions could be based on the real characteristics of the region. Decrease in groundwater level is one of the most important factors that influences subsidence but due to the complexity of the relationship between subsidence and other factors, a direct linear relationship between groundwater level and subsidence cannot be considered. The study aimed to investigate the relationship between subsidence and groundwater changes through relationship between the two parameters in the period 2014 to 2018 in Isfahan. In this regard, the time series of radar interferometry and the time series of water levels of piezometric wells in the Isfahan were studied. The results show that in 12% of the wells, no correlation exists, in 9%, poor positive ignorable correlation, in 12%, fair positive correlation, in 48%, significant positive correlation, in 6%, poor negative ignorable correlation, in 4% fair negative correlation and in 9% there is a strong and negative significant correlation between the subsidence rate and the groundwater level. Correlation values show the complexity of the relationship between subsidence and water level depletion. Therefore, the relationship between subsidence and its causative factors requires more detailed studies and comprehensive models.

Groundwater is the most important source of water in many parts of the world, used in drinking water, agriculture, industry and related ecosystems. However, the lack of control over human activities and climate change can lead to the destruction of these valuable resources.Accordingly, in this study, the groundwater level of Parishan catchment in Fars province in the period 2008 to 2019 in relation to groundwater abstraction has been investigated and using Madflu modeling in different scenarios to reduce the level of aquifer for future years. Predict for different areas of this basin in order to show different degrees of crisis in different parts of the basin.

Parishan Lake catchment area is one of the semi-enclosed cups in Fars province (Kazerun city) between the eastern longitude of "251-52" to "501-43" and the northern latitude of "25.22" to "29.27". This basin leads from the north to the Kazerun basin, from the east to the Boram basin, from the south and west to the Jarreh and Baladeh basins. The area of this basin is 225 square kilometers, of which 40 percent (90 square kilometers) is covered with heights and 60 percent (135 square kilometers) is covered with plains and lakes. The maximum altitude of Parishan Basin is 1800 meters and the minimum altitude is 855 meters above sea level, and these altitudes extend from northwest to southeast.

In the present study, data and information from the study area such as exploitation and observation wells data including data related to 25 exploration wells and 960 exploitation wells were collected from Fars Water Resources Management Organization (Fars Water Organization Statistics, 1398). After collecting the required data, the conceptual model of the area was determined as a geometric form and based on the parameters that have the greatest impact on the aquifer. Then other characteristics of the aquifer such as permeable and non-permeable boundaries were determined using lithological properties parameters, geological characteristics and characteristics of boundary formations in the region as well as inlet and outlet flow to boundary cells in the range. And Natrova was prepared in the aquifer and by preparing intermediate maps, the amount of groundwater reduction in different parts of the zoning basin and the extent of expansion of critical areas were determined.Madflow is a physical, three-dimensional model capable of stable and unstable simulations of free-pressed and free-pressed aquifers. The Madflu model solves the equation governing groundwater flow based on the finite difference method. In this regard, Marvdasht aquifer is networked into smaller cells, assuming that the characteristics of the aquifer are uniform in each cell. According to the law of mass conservation and groundwater movement, the equation governing groundwater flow is obtained as a second-order partial differential equation. This equation is given as (Equation 1) in unstable, inhomogeneous and three-dimensional conditions.T_XX (∂^2 h)/(∂ x^2 )+T_YY (∂^2 h)/(∂y^2 ) +T_zz (∂^2 h)/(∂z^2 )=S ∂h/∂t±R ( x,y,z) In this equation, ℎ: height of the hydraulic load; ((𝑥, 𝑦, 𝑧: flow directions; 𝑡: time; [𝑇]: 𝑇𝑧𝑧, 𝑇𝑦𝑦, 𝑇𝑥𝑥; aquifer transfer coefficients in the directions (x, y, z);: S storage coefficient; 𝑅 (𝑥, 𝑦, 𝑧): Power supply (positive sign (or discharge) is a negative signDue to the fact that abstraction of groundwater by agricultural wells is one of the important causes of water reduction in the troubled basin. In order to explain the trend of groundwater level changes, the general trend of the annual water level of all observation wells (25 piezometers) in the period 1398-1387 was studied.The results of simulation of groundwater level reduction in Parishan basin showed that this model with high spatial variability power well determines the effect of different parameters on groundwater level in different parts of the aquifer. In the study area, 960 wells and 25 piezometric wells with different uses of agriculture, drinking and industry have been located, which are scattered in other places except in the southern parts of the plain. The concentration of these wells in the central areas is higher due to flat ground and in the northern areas due to higher groundwater levels.In this research, the sensitivity analysis method combined with the calibration step has been used. The results of sensitivity analysis of effective parameters in calibration of Parishan Basin aquifer showed the maximum effect of hydraulic conductivity parameters and horizontal hydraulic conductivity anisotropy and a set of linear groups of waterways. Hydraulic conductivity of the aquifer is one of the parameters that has a high uncertainty in this model and by changing the values of this parameter, the model shows great sensitivity. Therefore, the reason for the high sensitivity of the aquifer hydraulic conductivity is the existence of wells with high discharge in these areas, so it is consistent with the statistics received from the Fars Regional Water Organization. Also, the anisotherapy parameter has a significant sensitivity in this model.In order to check the accuracy of the model after the calibration step in the unstable state, it is necessary to refer to the mean errors calculated by the software. According to what has been said before, RMSE error is one of the best criteria for measuring the error rate. The following is a table of average error types calculated by the software and a series of related calculations.The results of calculating the water balance in the aquifer of Parishan Basin, which was done during the period (1387-1388) indicate that the amount of 42.4 million cubic meters of water has been reduced from the constant storage of the aquifer. As a result, the amount of water entering the area, in addition to dependence on the physical conditions of the disturbed basin, such as hydrodynamic coefficients and gravity, is directly dependent on the amount of pumping discharge wells. Therefore, by increasing the abstraction from the aquifer, a change in the amount of exchange volume of the effective parameters in the balance can be expected.

The Earth's solid crust has not been fixed throughout the history of geology but is constantly changing under the influence of internal and external factors. These elevation changes in the form of subsidence and elevation significantly increase the trend of environmental hazards that affect of these hazards causes severe damage to the natural environment and human effects (Zare Kamali et al., 2017).According to the US Geological Survey, the phenomenon of subsidence involves the collapse or subsidence of the earth's surface, which can have a small displacement vector, which is said to occur gradually and instantly on a large scale (Geological Survey, 2011). The most important cause of subsidence of surface areas in sedimentary basins of arid and semi-arid regions is the compaction and compaction of sediments due to improper extraction of groundwater aquifers (Zhou et al., 2015). If wet clay layers are located between the sand layers, this phenomenon will be observed more widely and acutely (Liu et al., 2006). Land subsidence usually occurs with a time delay after prolonged abstraction of groundwater resources (Scott, 1979). The amount of subsidence depends on the thickness and compressibility of the layers, the duration of loading, the degree and type of stress (Signa et al., 2014).Research dataThe purpose of this study is to monitor land surface changes and identify areas with subsidence and uplift and identify the rate of these changes in the area and finally to investigate the causes and factors affecting the occurrence or exacerbation. For this purpose, first the Sentinel-1 radar image series with suitable time and place difference (maximum 150 meters) including 25 images (Table 1) in the period 2014 to 2021 with Ascending direction and also 12.5 meters Dem related to ALOS PALSAR sensor from the space agency site. Europe (Vertex) was prepared.In addition to radar data, information about the trend of changes in the level of piezometric wells in the region and also the average monthly precipitation of the region to compare and investigate the causes of subsidence in the study area were provided by the Water Resources Management Company and the Meteorological Organization, respectively.

In the present study, using the SBAS time series method in the period 2014 to 2021 in the metropolitan area of Karaj by selecting 25 Sentinel-1 images with appropriate time and place distance, the average subsidence velocity, and land subsidence in the study area was estimated.To determine the main factors of this event, the study area was examined in more detail in terms of mining, tectonic activity, land use in terms of construction of massive structures, and finally changes in groundwater level. Then to investigate the causes and factors. The decreasing trend of groundwater level and precipitation in the region during the last 6 years was also examined.

The results of time series analysis of interferometric images show that in Karaj metropolis the number of land surface changes was between -145 to +15 mm and the areas with subsidence in the northwestern part of the study area are Mehrshahr which recorded subsidence between 100 and 145 mm. To determine the main factors of this event, the Mehrshahr region was examined more precisely in terms of mining, tectonic activity, land use in terms of construction of buildings and massive structures, and finally changes in groundwater level, which showed that only water level changes. Underground in the region has a trend corresponding to subsidence in the Mehrshahr area. To investigate the causes and factors of the declining trend of groundwater level, rainfall in the region during the last 6 years was examined. On groundwater recharge and eventually subsidence.

The importance and increasing monitoring of land status, especially in order to identify the occurrence of subsidence that has occurred in recent years and following the drought and over-exploitation of groundwater resources have caused more attention by researchers in this regard. In the present study, due to the importance of the subject and the study area, the rate of subsidence and its relationship with groundwater level changes were evaluated. The results showed that in the metropolis of Karaj in the period of 6 years 2014 to 2021, the highest rate of land movement was between -145.27 to +15 mm.Therefore, according to the results of the present study and the direct relationship between subsidence in Karaj metropolis with groundwater decline, it seems necessary to monitor the use of groundwater in the region, especially in agriculture, because the current trend in the use of groundwater Recent droughts will lead to irreparable risks of subsidence in the region.

Irregular abstraction of groundwater aquifers in the country has caused a sharp decline in the aquifer water level and the destruction of aquatic aquifers. In this study, in order to investigate the groundwater level of Marvdasht-Kharameh aquifer, located in Fars province, in relation to the uncontrolled abstraction of groundwater from the data of 81 piezometric wells in the period (2018-2018), the Modflow model was simulated. Also, the results of calculating the water balance of 7,500 wells in the basin indicate that the amount of 1100 million cubic meters of water from the aquifer constant storage has been reduced over a period of 10 years. According to the prepared interpolation maps, the highest rate of groundwater loss has occurred in Dorodzan, Ramjerd and Shool areas. Therefore, it is in line with the statistics of the Fars Regional Water Organization that there are wells with high discharge in these areas. According to the maps prepared from Marvdasht aquifer, due to the alluvial nature of the groundwater aquifer, the effect of water level drop can be observed from a short distance. On the other hand, in the intermediate maps, the coefficient of hydraulic conductivity parameter indicates that the rate of aquifer drop in the northwest, center and southeast of the basin has the highest value, which is appropriate with 11% relative error confirms modeling. Finally, by performing two scenarios of 10 and 30% reduction,

One of the ways of sustainable management of groundwater resources is to model the groundwater level of the plains in order to identify water potentials and long-term planning based on the status of aquifers. In this study, MODFLOW code, which is one of the codes in GMS7.1 software, was used to simulate the groundwater flow of Minab plain aquifer. To investigate the observational and computational level of groundwater in the study area, information about the water table of 16 observation wells in the plain was used. The constructed model was initially calibrated assuming the current was constant and the parameters affecting the model including hydraulic conductivity and feed were optimized. Then, the model was calibrated assuming that the flow is unstable in 12 time steps (October 1991 to September 1992) and the specific discharge parameter was optimized. According to the calculated balance of the aquifer, the total feeding of the aquifer is 1409.443 million cubic meters, and the total discharge from the aquifer is 1640.1011.1 million cubic meters, which is negative due to the higher output of the aquifer than the input, and the balance of the plain is negative. It will cause a sharp drop in the groundwater level in the coming years.

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

Due to an intense loss in groundwater level and a high decrease in reservoir capacity, the Marand plain has been banned since 1991. However, since 1994, the groundwater level been dropping year by year. As a result, many wells and qanats have been dried or their discharge capacity has been decreased, which has caused a lot of problems for the operating organizations. In this study, to investigate and manage the groundwater level variation in the Marand plain, three scenarios including supplying all consumption from groundwater resources, supplying drinking and industry consumption from the Aras River, and supplying drinking and industry consumption from the Aras River and applying the optimal management of the consumption for agricultural uses were defined. The water balance equation was used to establish the relationship between input, output, storage in an aquifer, and a variation of groundwater level in the Marand plain was estimated based on the available data (2005-2014). Finally, the zoning of the groundwater level was done for the September 1398 and the results were compared with the September 1393. In this research, the Marand plain with an area of 562.22 km2 in the northwest of East Azerbaijan province was selected as a case study. Investigating the hydrological and meteorological parameters of the Marand plain between the years 1982 and 2013 showed that the average annual precipitation was 283 mm, the average annual temperature was 12.8°C, and the average annual pan evaporation was 104 mm. The aim of this research was to estimate the spatial and temporal variation of the groundwater level of the Marand plain. For this purpose, the water balance estimation was done by using Excel and the zoning of groundwater level variation was done by using ArcGIS. A groundwater level analysis of the Marand plain was carried out based on the 50 observations of wells during 2005 to 2014. In this period, according to the groundwater level data, the aquifer parameters, such as the loss of the groundwater level and the amount of water withdrawal from the aquifer were determined. Then, various scenarios were defined for assessing the status of the aquifer.
Result and The analysis of the groundwater level in the Marand Plain in a year statistical period (1982-2013) showed that the groundwater level of the plain had decreased about 16.56 m. Also the average annual groundwater level of the plain decreased about 48 cm between the years 2005 and 2015.
By applying the first scenario, in the next five years, the fall of the groundwater level in the zone 1 will be 2.35 m, in the zone 2 will be 2.25m, in the zone 3 will be 2.6m, and in the zone 4 will be 2.45m.
Also the area of the zone 4 had increased from 246 km2 to 252 km2 which indicated a further fall of the groundwater level in a large area of the plain. By applying the second scenario, in the next five years, the growth of the groundwater level in the zone 1 will be 1.74 m, in the zone 2 will be 1.67 m, in the zone 3 will be 1.93 m, and in the zone 4 will be 1.82 m. Indeed, following this trend, the groundwater level after 14 years will return to the situation of 10 years ago (2005). In addition, after 46 years, it will return to the situation of 32 years ago (1982). By applying the third scenario, in the next five years, the growth of the groundwater level in the zone 1 will be 4.78 m, in the zone 2 will be 4.58 m, in the zone 3 will be 5.29 m, and in the zone 4 will be 4.99 m. Following this trend, the groundwater level after 5 years will return to the situation of 10 years ago (2005). After 17 years, it will return to the situation of 32 years ago (1982). The aim of this research was to estimate the spatial and temporal variation of the groundwater level in the Marand plain. The results showed that the annual average groundwater level had decreased 48 cm/year between the years 2005 and 2014. Also by applying the first scenario, with an intensified decline in the groundwater level in all zones, the status of the Marand aquifer becomes more critical. For example, in some areas, the groundwater level will decease about 2.6 m. By applying the second scenario, the groundwater level will increase at least 1.67 m and utmost 1.93m and by following this trend, after 14 years, the aquifer will return to the situation of 2005. Also by applying the third scenario, the groundwater level will increase at least 4.78 m and utmost 5.29m and by following this trend, after 5 years, the aquifer will return to the situation of 2005.

The impact of natural and human factors that affect the level of Darab Plain was evaluated to determine the role of each of these factors in decreasing the level of groundwater occurrence. In recent decades, Simultaneity climate change and increasing population, industry and agriculture cause’s ambiguity in cognition of more effective factors in decreasing underground water reserves in the country. Darab plain in the south-eastern of Fars province has an important role in the field of agriculture and horticulture in the country. However, many natural factors affect, but from the natural, precipitation and evaporation were studied as the most important factors affecting the level of underground waters. From the human factors also seem to indiscriminate exploitation and numerous drilling deep and semi-deep wells have a significant impact on underground water resources. To assessment, the trend of data was used Mann- Kendall test and was applied Sen’s slope estimator to calculate data slope. Pearson correlation coefficient was applied to evaluate the relationship between groundwater level data with the data of precipitation and the exploitation of them. By comparing the natural parameters trend and the exploitation of water resources in the region, it can be concluded that natural factors have been little effective in decreasing the level of underground water and human activities played a significant role.

Isfahan province is one of the driest provinces in central part of the country center where two-thirds of its water requirement is supplied by groundwater resources. In recent years with population growth and the increase of water demand in different sectors of agriculture, industry, drinking, and health, groundwater resources have faced a lot of pressure. So, Understanding the behavior of the groundwater body and its long term trends are essential for making any management decision in areas. Mann–Kendall statistical test has been commonly used in many researches to assess the significance of trends in hydro-meteorological time series. As well as, geostatistical analysis has been theoretically defined and applied by many researchers, they have emphasized that geostatistics is a management and decision support system tool for analyzing spatial and temporal variations of groundwater level fluctuations. Geostatistical approaches can provide more helpful, reliable and efficient tools to increase the number of measurement points at unsampled locations, and variogram analyses for examining structural relationship of data (Rakhmatullaev et al. 2011).

In this study, the temporal and spatial variations of groundwater level for Isfahan-Borkhar, Najafabad and Chadegan plains with a 25 years period (1990-2015) investigated. Monthly water level data have been collected from 29, 40 and 8 observation wells in Isfahan-Borkhar, Najafabad and Chadegan plains, respectively during the study period. Precipitation data from synoptic, and climatology stations.were used in this research.
The trend analyses were done at monthly, seasonally and annual scales using Mann-Kendall Test and Sen's slope estimator nonparametric methods by Matlab 7.11 software. The Mann-Kendall test is a non-parametric method used for trend analysis of time series data. In this method, the presence of a statistically significant trend evaluated using Z value (equation 1).
(1)
A positive value of Z indicates an increasing trend and negative value indicates decreasing trend.
In this research, null hypothesis (H0) was that “there is no trend in time series of groundwater levels” is rejected if the absolute value of Z is greater than ±1.96 and ±2.58 in 5% and 1% level of significance, respectively. If value of Z is out of this range, null hypothesis is accepted and there isn’t any trend in time series (Yin et al. 2015). The groundwater level hydrograph was drawn also for each plain during 25 years (January 1990 to October 2015) in Excel software.
Prior to the geostatistical estimation, its require a model that compute a semivariogram value for any possible sampling interval. The experimental semivariograms were fitted with various theoretical models like spherical, exponential, Gaussian, linear and power in GS+ software. The underground water level zoning maps was prepared by Ordinary Kriging method for every year of the study period. Spatial zoning maps were prepared and ultimately, iso-falling map was provided at the beginning and end of the study in Arc GIS 10 package.

The Spatial distribution of trend by the Mann-Kendal test for annual groundwater level data indicated a general trend in all plains where most piezometers groundwater level is negative. the piezometer wells with positive trend were so low and the most positive trend is related to Isfahan plain. In Chadegan plain there wasn’t any positive trend in piezometers level.
The investigation of trend line slopes revealed that in average, the groundwater level of Isfahan-Borkhar, Najafabad and Chadegan plains has been decreased about 0.468, 1.12, 0.638 m y-1, respectively. The general trend of the groundwater level hydrograph shows that the level and storage of water continuously decreased in the last years.
Gaussian variogram model was the best for spatial structure of these data. Generally, the spatial pattern of zoning Groundwater maps indicated that direction of groundwater flow is northwest to southeast in all study plains. As well as, iso-falling map showed that groundwater level has dropped in most parts of the plains during the study period, Which was in agreement with this research (Rahmati et al. 2014, Azareh et al, 2014, De Brito Neto et al. 2016). The cuase of this agreement could be vulnerability of arid region ecosystems into human interference and other stressful factors.

Due to the lack of rainfall trend in the most of the stations across study area, the major cause of reduced groundwater could be related to human factors. overexploitation, growth of population, and increasing number of wells are the most important factors in decreasing of groundwater table. So the decision to management groundwater in the study area is required. it is necessary to immediately practice water conservation methods and water harvesting systems in the study area to prevent the causes of more damages to the available water resource

In this study is predicted the groundwater level of Sharif Abad catchment using some artificial intelligence models. For this purpose used of monthly groundwater levels for modeling in the three observed wells located in the Sharif Abad watershed of Qom. To compare the results of the hybrid model of wavelet analysis-neural network (WNN), genetic programming (GP) multiple linear regression (MLR) and artificial neural network (ANN), two criteria of root mean squared error (RMSE) and nash-sutcliffe coefficient of efficiency (E) is used. The results of the study indicated that the WNN models provide more accurate monthly groundwater level predicted in compared to the ANN, GP and MLR models so the nash-sutcliffe coefficient in WANN model for piezometers 1, 2 and 3 are 0.98, 0.98 and 0.95, respectively.

Groundwater is the main supply of drinking and agriculture demands in Meshginshahr plain located on Northwest of Iran in the Province of Ardebil. The investigation of groundwater level fluctuations is necessary for effective groundwater management in this plain. For this purpose, artificial intelligence methods are interested due to high ability, cost effectiveness, needing less data, and fast running. This study presents a supervised committee fuzzy logic (SCFL) model to predict groundwater level at three piezometers in the study area. For implementing SCFL model, first fuzzy logic models such as Mamdani fuzzy logic (MFL), Larsen fuzzy logic (LSL) and Sugeno fuzzy logic (SFL) were applied to predict groundwater level using precipitation, temperature, discharge of abstraction wells and groundwater level with one month lag data. Then a supervised committee fuzzy logic as a non-linear model was used to combine the outputs of individual fuzzy models to reap the advantages of all three models simultaneously. Three different criteria RMSE, MAE and R2 were used to assess the prediction efficiency and accuracy of models. Based on results, MAE values of SCFL model are 0.12, 0.04 and 0.03 for piezometer 1, 2, and 3 respectively for training step. It presents the superiority of SCFL model over the individual fuzzy models. Also SCFL model could reduce prediction RMSE to 6% for piezometer 1 and 8%, 14% for piezometers number 2 and 3 respectively.

Groundwateris oneof the most importantsourcesoffresh waterneededinthe world. Inthis study,climate data of precipitation, temperature and evaporation in sevenmeteorologicalstation;were been used at 20-yearperiod(90-1370). The researchmethodis acausalmanner. Thecorrelation and regressionstatistical methodswere used to studyvariation of precipitation onaquiferwater levels. Average of totalrainfallmonthly ofcatchmentwas calculated using of data from the1430cell of 240maps(20 yearsx 12months), respectively. Review of iso-drop maps show that underground water level has dropped in someareas up to44meters. On the other hand, with respect tomaps ofgroundwatermovement, this result can be applied a firm management on removalofgroundwater. Because the wateris movingaround theaquifertoitscenter due to lawrelated dishes. Soyouincrease theharvestbypalmCentral Plainswells, wellssharplyagainstaplainedgeand causingthemtoshrivel. Our studyshowed aquite directrelationship between precipitation with water levelbutrelationship of temperature andevaporation with waterbalance is reversed. Therefore theprocess of consumption mustbe formulatedin such a waythat the amount of water fedbyrainfallcouldbe accountable for the discharge.

Groundwater is the main water resource for agricultural demands in arid and semiarid regions. An Sustainable agriculture requires a precise management and scheduling on utilizing these resources which in turn needs adequate knowledge about spatial variability of groundwater level for a given time period. As traditional interpolation methods do not consider spatial correlation between groundwater level observations, geostatistical methods are used for spatial variability analysis and mapping of groundwater level. In this study first a semivariogram is used to investigate the spatial correlation of groundwater level data from 59 observation wells in Kuhpayeh-Sagzi aquifer (Esfahan Province). Semivariogram analysis was performed for groundwater level data from 2002 to 2009 and for wet (Ordibehesht) and dry (Mehr) seasons. Also Kriging is used to interpolate groundwater level data over the study area and the results are compared with those achieved by inverse distance weighing method. Geostatistical analysis is performed using GS+. Based on results obtained in this study, the best semivariogram model for groundwater level for all time periods was spherical. Moreover the ratio of nugget effect (C0) to Sill showed that groundwater level data are strongly correlated over space for all years and for both wet and dry seasons. The smallest range of influence (36850 m) was found for wet season in 2002-2003 and the largest range of influence (40220 m) was found for dry season in 2007-2008. The cross-validation results showed the better performance of ordinary Kriging in comparison to inverse distance weighting. Based on the generated maps, the lowest groundwater level was seen in southeast and highest groundwater level was seen in center, south and southwest of the study area.

In this article, a hybrid, artificial neural network-geostatistics (Kriging) methodology is utilized to predict the spatiotemporal groundwater level in Davarzan plain in Khorasan Razavi province in Iran. The data for the study were the groundwater levels of 5 piezometers from September 2003 to April 2012 which were recorded on monthly basis. Neural network was used for predict the groundwater level of the successive months and geostatistic were used to estimate the groundwater level at any desired point in the plain. To determine the accuracy and efficiency of model, the method was tested on a new piezometer (Bagherabad) at the first stage. The results were compared with the actual value. And the results (E=0.812) show the efficiency of model. Then, based on appropriate achieved results, the groundwater level was predicted in the month ahead. The results show that neural network with average coefficient of determination (E=0.688) and Gaussian variogram with (R2=0.657) had high efficiency for predicting the groundwater level in this plain.
[1]- Assistant Prof., Dept., of Civil Eng.; University of Qom; Iran (Corresponding author), Email:[email protected].
[2]- M.A Student; Hydr
Spatiotemporal Groundwater Level Forecasting in Davarzan Plain
Article 1, Volume 1, Issue 4, Winter 2017, Page 1-19 XML PDF (854 K)
Abstract
Taher Rajayee[1]*
Fatemeh Pouraslan[2]
Abstract
In this article, a hybrid, artificial neural network-geostatistics (Kriging) methodology is utilized to predict the spatiotemporal groundwater level in Davarzan plain in Khorasan Razavi province in Iran. The data for the study were the groundwater levels of 5 piezometers from September 2003 to April 2012 which were recorded on monthly basis. Neural network was used for predict the groundwater level of the successive months and geostatistic were used to estimate the groundwater level at any desired point in the plain. To determine the accuracy and efficiency of model, the method was tested on a new piezometer (Bagherabad) at the first stage. The results were compared with the actual value. And the results (E=0.812) show the efficiency of model. Then, based on appropriate achieved results, the groundwater level was predicted in the month ahead. The results show that neural network with average coefficient of determination (E=0.688) and Gaussian variogram with (R2=0.657) had high efficiency for predicting the groundwater level in this plain.

Physical development of rural areas can be effective when occur conducted and controlled، and، options are reviewed and evaluated for this purpose before the site selection of them. In the present study using ten villages of KHAF county as the study area and identifying the status quo، first identified restrictive criteria involved in the physical development of these villages، and using descriptive - analytical method and using Analytical Hierarchy Process (AHP) model، have been selected with the aim of determining the best location for the physical development of rural areas. In this way، criteria involved in the physical development of these rural areas each one accordingly as a layer of map and the weight of each one was determined using pairwise comparison method (AHP). Mentioned steps were performed using Expert Choice software. Results showed that criteria: ground slope، distance from the watercourse and the distance from the fault respectively with 0. 315، 0. 179 and 0. 108 points have most effect in locating development side of the villages. Then these layers has combined using weight of each layer in GIS and using the weighted overlay model، and thus the resulting output represents the total criteria for selecting optimal locations for future development of the villages. The results of this study indicate that among the sample rurals، only in 4 rural Mehrabad، Barabad، Sade and Sijavand، the proposed side development of Hadi plan consistent with absolutely proper and proper sheet of the future development of rural areas.

Physical development of rural areas can be effective when occur conducted and controlled، and، options are reviewed and evaluated for this purpose before the site selection of them. In the present study using ten villages of KHAF county as the study area and identifying the status quo، first identified restrictive criteria involved in the physical development of these villages، and using descriptive - analytical method and using Analytical Hierarchy Process (AHP) model، have been selected with the aim of determining the best location for the physical development of rural areas. In this way، criteria involved in the physical development of these rural areas each one accordingly as a layer of map and the weight of each one was determined using pairwise comparison method (AHP). Mentioned steps were performed using Expert Choice software. Results showed that criteria: ground slope، distance from the watercourse and the distance from the fault respectively with 0. 315، 0. 179 and 0. 108 points have most effect in locating development side of the villages. Then these layers has combined using weight of each layer in GIS and using the weighted overlay model، and thus the resulting output represents the total criteria for selecting optimal locations for future development of the villages. The results of this study indicate that among the sample rurals، only in 4 rural Mehrabad، Barabad، Sade and Sijavand، the proposed side development of Hadi plan consistent with absolutely proper and proper sheet of the future development of rural areas.

Groundwater has always been considered as one of the major sources of drinking and agricultural water supply, especially in arid and semi-arid areas. Ground water systems simulations because of their inherent complexity are not readily possible. The goal of this research is prediction of groundwater level fluctuation in Shabestar Plain, West of East Azerbaijan province, using artificial neural networks (ANN). The 9 years data sets (1380-1388) from 15 piezometers that uniformly disperse on the whole plain is applied for ANN model training. The four inputs ANN model were monthly data set from temperature, rainfall, Daryanchay discharge, groundwater level in each piezometer with one month delay (t0-1). The groundwater level was the only output of the ANN model. The results of this research showed that the ANN model with TRAINLM training function and with TANSIG activation function are capable to monthly prediction of groundwater level in 3 years period with high accuracy R2=99.63, RMSE=1.43 in training step and R2=99.16, RMSE= 1.167 in validation step in study area.