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Showing 33 results for Groundwater
Analysis of surface and ground water changes in Semnan watershed using SWAT model
Sh. Nasiri, N. Farrahi, A. N. Ziaei,
Volume 24, Issue 2 (7-2020)
Abstract
One of the most important and complex processes in the watersheds is the identification and prediction of surface water changes. The main processes associated with surface water include precipitation, percolation, evapotranspiration and runoff. In this research, the semi-distributed model, SWAT, was used to simulate ground water and surface water in Semnan catchment in a monthly scale. A sensitivity analysis was perfomed to evaluate and demonstrate the influence of the model parameters on the four major components of water budget including surface runoff, lateral flow, groundwater and evapotranspiration. River discharge data from 2004 to 2014 were used for the calibration and those of 2014 to 2016 were applied for the validation. The results of sensitivity analysis showed that the most sensitive parameters were: SoL_K(Saturated hydraulic conductivity), CH_K2 (Effective hydraulic conductivity in main channel), RCHRG_DP(Deep aquifer percolation fraction and CN2 (Moisture condition II curve number). The simulation accuracy using Nash-Sutcliffe and coefficient of determination for Shahrmirzad, Darjazin, and Haji Abad hydrometric stations was about 0.60 to 0.80 and 0.80 to 0.90 for the calibration and validation period, respectively, showing a good performance in the simulation of river flow. According to the water balance results, about 87.6% of the total inflow into the watershed was actual evapotranspiration, 3% was surface run off, 3% was percolation, and the rest was related to the soil moisture storage.

Qualitative Assessment of the Coastal Plain of Talesh using the Modified DRASTIC Vulnerability Method
H. Mahmoudpour, S. Janatrostami, A. Ashrafzadeh,
Volume 24, Issue 3 (11-2020)
Abstract
Given the fact that the DRASTIC index is ineffective in addressing the saltwater uprising issue in coastal plains, in the present study, three factors including land use, distance to shoreline, and differences between groundwater and sea level were added to the DRASTIC index. The proposed modification to DRASTIC was validated using the measured electrical conductivity (EC) data gathered from groundwater monitoring wells throughout the Talesh Plain. The results showed that the coefficient of correlation between the map of EC over the region and the modified DRASTIC was 0.52, while for the original DRASTIC, the coefficient was 0.45, thereby implying a stronger relationship between EC and the modified DRASTIC in the Talesh Plain. Sensitivity analysis also showed that DRASTIC and the modified DRASTIC were the most sensitive to, respectively, depth to groundwater (D) and land use (Lu). According to the single-parameter sensitivity analysis results, depth to water table and net recharge were the most effective parameters in DRASTIC,  whereas the modified DRASTIC was the most sensitive to land use and depth to groundwater. It could be concluded that modifying the DRASTIC index would result in decreasing the area of very high and high vulnerable classes, and the area classified as low and moderate vulnerable could be increased.

Simulating and Optimizing the Conjunctive Use of Surface and Groundwater Resources Using the System Dynamics Approach (A Case Study: Dashte-Abbas Irrigation Network)
H. Alizadeh, A. Hoseini, M. Soltani,
Volume 24, Issue 3 (11-2020)
Abstract
The construction of irrigation network and the water transfer from Karkheh Dam to Dashte-Abbas, due to neglecting the groundwater resources has increased groundwater level and waterlogging of the agricultural land in the recent years. The aim of this study was, therefore, to optimize the conjunctive use of surface and groundwater resources in Dashte-Abbas to minimize waterlogging problems and achieve the maximum net income. For this purpose, the behavior of groundwater was simulated using the system dynamics (SD) approach. The conjunctive use of surface and groundwater resources was then optimized using the Vensim multi-criteria optimization method with the objective function of maximizing the net income of the plain. The SD model calibration was done using climatic, hydrological, agricultural, and environmental data from the 2001-2009 time period; then it was validated based on the information from the 2009-2016 period. Evaluation of the developed SD model showed that the model had high accuracy in simulating key variables such as groundwater levels (ME=60cm, R2=97%, RMSE=47cm) and groundwater salinity (RMSE=100μS/cm, R2=74%, and ME=123μS/cm). Furthermore, the results of the optimization model showed that the optimum use of surface and groundwater resources for the agricultural demand was 65% and 35%, respectively. To sum up, it could be concluded that with the optimization of the conjunctive use of surface and groundwater resource, s about 10 MCM of water consumption could be annually saved to irrigate almost 800 ha of the new lands.

Evaluation of Quantitative and Qualitative Indices of Plain and Aquifer on Optimum Location of Artificial Recharge Ponds (A Case Study of Khanmirza Plain, Chaharmahal Bakhtiari Province)
F. Kaboudvand, S. S. Mehdizadeh,
Volume 24, Issue 4 (2-2021)
Abstract
The Khanmirza plain is one of Iran’s fertile plains that is located in Chaharmahal Bakhtiari province. Agriculture in the area is very prosperous, but the lack of rain and over-harvesting from consumption wells has led to a reduction in groundwater levels, even causing land subsidence. Moreover, the high usage of chemical manures, especially nitrate manures, has increased the number of solutes and chemical materials in the groundwater. Thus, for this plain, making artificial ponds is important to modify the storage of the aquifer. In this study, to define the optimum locations of the artificial ponds, the effect of 12 factors was considered. The analytic hierarchy process (AHP) method was used to introduce the weight of each parameter in comparison to other factors. Afterward, the spatial priority of all factors was derived using the Geographic Information System (GIS) technique. The produced GIS layers were laid on each other and the optimum locations were obtained. Agricultural drainage was an effective index for recharge purposes. The results of the study demonstrated that groundwater level decline got the maximum weight (40%), while the land slope had the minimum weight, since the vicinity to available floodways was considered as an independent criterion. The results also showed that regions with a total area of 18 km2 in north and north-west of the Khanmirza plain could be the optimum and most suitable places for artificial ponds construction.

Analysis of Groundwater Balance of Samalqan Plain Aquifer Using SWAT and MODFLOW Models
Sh. Nasiri, H. Ansari, A.n. Ziaei,
Volume 25, Issue 3 (12-2021)
Abstract
Reducing surface water resources and successive droughts and consequently excessive use of groundwater resources, especially for agricultural purposes, have caused irreparable damage to the natural resources of the country. In the meantime, knowing the status of the water balance of the plain can help to effective management of water resources in the region. Samalqan plain is located in a semi-arid climate in North Khorasan Province. Since the surface water resources for water supply are not very reliable, so, the main source of water supply in the region is well. Due to the existence of rivers in the plain, the low thickness of the alluvium, groundwater level fluctuations, and the high uncertainty in the calculation of hydrodynamic coefficients, the need for careful hydrogeological studies and determining the role of each parameter affecting groundwater is necessary. This study was conducted to simulate the Samalqan aquifer and analysis of water balance for the years 2003 to 2013 using the MODFLOW model. To identify the groundwater recharge rate, this component was estimated by the SWAT model. Calibration and validation of the model with an error of 1.1% and 1.2%, respectively, indicated that an appropriate estimation between the simulated and observed heads. Assessment of the groundwater hydrograph in the observation wells showed that the groundwater level in most places has many monthly and seasonal fluctuations. After drawing the potential lines of the plain, the inputs and outputs were identified, and using the reserve volume changes, the water balance was determined. The results showed that the water balance of the plain was negative and the reservoir deficit was estimated at 9.14 million cubic meters. Therefore, this model can be used to predict the future situation of aquifer and the management of water resources in the region.

Investigation of Ground Waters Quality Using Multivariate Statistical Techniques (Case Study: Maragheh-Bonab Plain, East Azerbaijan Province)
M. Amini,
Volume 25, Issue 4 (3-2022)
Abstract
Investigation and analysis of groundwater quality to monitor contamination and identify the most important pollutants and pollution points is one of the research fields. The objective of this research was to plan to improve groundwater quality on various spatial and temporal scales. Groundwater information of Maragheh-Bonab plain was collected from 26 wells in 10 years (2001-2011) with 454 sampling points from East Azerbaijan Regional Water Organization and was analyzed using multivariate statistical techniques such as DFA and PCA. Analyzed Variables are included Mg, Ca, Cation, K, Na, TDS, TH, SAR, EC, Anion, pH, Cl, SO4, CO3, and HCO3. Results of PCA showed that variables such as cation, HCO3، TDS، SAR، EC، Anion ،Cl, Ca, and TH were identified as important variables which they can great impacts on the groundwater quality of this region and in the other hand DFA showed which mentioned variables can discriminate land uses and geology formations in primary and normal distribution data with power discriminatory of 68.7 %, 92.2 %, and 66.5 %, 89.1 %, respectively. Investigation of the spatial position of elements using interpolation technique in Maragheh-Bonab plain showed that variables concentration in lowlands are high and 20 villages and their surrounding farms are exposed to high contamination risk of groundwater.

Heavy Metals Pollution Assessment in Groundwater Resources of Hamadan-Bahar Plain in 2018
A. Ghobadi, M. Cheraghi, S. Sobhan Ardakani, B. Lorestani, H. Merrikhpour,
Volume 26, Issue 1 (5-2022)
Abstract
The qualitative assessment of groundwater resources as the most important sources of drinking and agricultural water is very important. Therefore, the present study was conducted to evaluate the quality of heavy metals in groundwater resources of the Hamadan-Bahar plain in 2018 using water quality indices. In so doing, a total of 120 groundwater samples were collected from 20 stations during the spring and summer seasons and the values of physico-chemical parameters were determined based on the standard methods and also the content of heavy metals was determined using inductively coupled plasma spectroscopy (ICP). The results showed that the mean concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn (µg /L) in the samples in the spring season were 5.08, 0.260, 1.05, 2.70, 1.50, 0.490, 1.50, 7.48, and 1.75, respectively, and in the summer season were 20.7, 0.220, 0.950, 7.12, 1.34, 0.490, 1.29, 8.23, and 2.08, respectively and except for As in the summer season, the mean content of other elements was lower than maximum permissible limits established by WHO for drinking water. Meanwhile, the mean values of Cd, HPI, HEI, MI, and PoS indices in the spring season with -7.51, 9.91, 1.42, 1.42, and 328, respectively, indicate the water quality was categorized as low, low, low, low and moderately affected and in the summer season with -5.90, 10.0, 3.04, 3.04, and 673, respectively, were categorized as low, low, low, moderately affected, and high pollution. Due to the extensive use of agricultural inputs, especially chemical and organic fertilizers and chemical pesticides containing heavy metals by farmers in the study area, the possibility of increasing the concentration of heavy metals in the soil and their penetration into groundwater aquifers will not be unexpected in the medium term. Therefore, periodic monitoring in groundwater resources of the study area is recommended.

Prediction of Groundwater Level Using Artificial Neural Networks Based on Efficient Input Variables Selection by Partial Mutual Information Algorithm
F. Zarif, A. Asareh, M. Asadiloor, H. Fathian, D. Khodadadi Dehkordi,
Volume 26, Issue 2 (9-2022)
Abstract
An accurate and reliable prediction of groundwater level in a region is very important for sustainable use and management of water resources. In this study, the generalized feedforward (GFF) and radial basis function (RBF) of artificial neural networks (ANNs) have been evaluated for monthly predicting groundwater levels in the Dezful-Andimeshk plain in southwestern Iran. The partial mutual information (PMI) algorithm was used to determine efficient input variables in ANNs. The results of using the PMI algorithm showed that efficient input variables for monthly predicting groundwater level for piezometers affected by water discharge and recharge include only water level in the current month. Also, efficient input variables for predicting the water level for piezometers affected only by water discharge include the water level in the current month, the water level in the previous month, the water level in the previous two months, transverse coordinates of piezometers to UTM, the water level in the previous three months, the water level in the previous four months, the water level in the previous five months and longitudinal coordinates of piezometers to UTM. In addition, efficient input variables of monthly predicting groundwater level for piezometers neither affected by water discharge nor water recharge, respectively, include the water level in the current month, the water level in the previous month, the water level in the previous two months, the water level in the previous three months, the water level in the previous four months, the water level in the previous five months, the water level in the previous six months, transverse coordinates of piezometer to UTM and longitudinal coordinates of piezometer to UTM. The results indicated that the GFF network is more accurate than the RBF network for monthly predicting groundwater level for piezometers including water discharge and recharge and piezometers including only water discharge. Also, the RBF network is more accurate for monthly predicting groundwater levels for piezometers that include neither water discharge nor recharge than the GFF network.

Modeling of Malayer Aquifer by MODFLOW Groundwater Model and SWAT Surface Water Simulation Model
G.m. Samadi, F. Mousavi, H. Karami,
Volume 26, Issue 3 (12-2022)
Abstract
The impact of different management options on the region and the existing conditions can be evaluated with minimal cost and time to select the most practical case using various tools including mathematical models. In this study, the SWAT hydrological model was performed from 2009 to 2019 using climatic, hydrological, and hydrometric data in the Malayer catchment, and the final model was validated by SWAT-CUP. To reduce the amount of uncertainty in the input parameters to the MODFLOW model, using the values of surface recharge from the implementation of the SWAT hydrological model, quantitative modeling of Malayer aquifer was performed more reliably in GMS software by using MODFLOW model. After modeling the study area in the 2009-2018 period and calibrating the model in the years from 2018 to 2019, the mean values of absolute error (MAE) were 0.35-0.65 m, and root means square error (RMSE) was 0.62-0.94 m, which seems acceptable considering computational and observational heads equal to 1650 m. Results of water level changes in observation wells located in the Malayer region indicate that the groundwater level in the aquifer has decreased by an average value of 9.7 m in the 10-year study period.

Evaluation of ANFIS-GWO Combined Model in Predicting Groundwater Level of Saveh Zarandieh Plain, Iran
S. Bigdeli, K. Ebrahimi, A. Hoorfar, A.a. Davudirad,
Volume 26, Issue 4 (3-2023)
Abstract
In this study, the accuracy of the Adaptive Network-Based Fuzzy Inference System (ANFIS) in integrating with the Gray Wolf Algorithm (ANFIS-GWO) in predicting groundwater level was evaluated for the first time using unpublished observational data from 1998 to 2018 in the Zarandieh aquifer, central Iran. Three observational wells were randomly selected for analysis. Assessment of evaluation criteria demonstrated that among the proposed scenarios using the hybrid model, the D scenario was selected as the optimal scenario with input data including the previous month's groundwater level, precipitation, temperature, and groundwater extraction. In the D scenario, parameters including MAPE, RMSE, and NASH were 0.29 m, 0.47 m, and 0.99, respectively for the first observational well. Also, C scenario with input data including the previous month's groundwater level, precipitation, and groundwater extraction for the second observational well, for the same parameters mentioned above equal to 0.20 m, 0.26 m, and 0.99. As well for the third observational well, the A scenario with input data including the previous month's groundwater level for the same parameters equal to 0.29 m, 0.41 m, and 0.99 as the optimal scenarios were selected using the ANFIS-GWO model. Based on the results, the Gray wolf algorithm in training the ANFIS model was able to reduce the average forecast error by equal to 0.03 (RMSE) and 0.02 (MAPE) meter and increased the average NASH value equal to 0.01 and increased the accuracy of predictions.

Spatiotemporal Variations Modelling of Water Table Surface using GIS in Sahneh-Biston Plain Aquifer
K. Shirani, R. Arfania, Y. Fereydoni, R. Naderi Samani, M. Shariati, M. Faizi,
Volume 26, Issue 4 (3-2023)
Abstract
Groundwater is always considered one of the important water resources, especially in arid and semi-arid regions of the world, such as Iran. In recent decades, it has decreased drastically due to excessive use. The objective of this study was to determine the best interpolation method and evaluation of the spatiotemporal variations for the groundwater level in the Sahneh-Biston plain of Kermanshah province during three decades from 1991 to 2020. At first, four Gaussian, linear, spherical, and power semi-variograms were obtained for observations. Then, the best semi-variogram and interpolation methods were selected among the evaluated methods for zoning the groundwater level in the region. The lowest value of the sum of RMSE, MBE, and MAE error criteria and the highest coefficient of determination (R2) between observations and estimates in all three decades and the average of the entire period were calculated and considered to evaluate the most appropriate semi-variogram and interpolation methods for spatial distribution. The results showed that the ordinary kriging method with Gaussian semi-variogram is the best method to estimate the groundwater level in the Sahneh-Biston plain. The average difference between the minimum and maximum groundwater levels based on the observation wells of the study area and the zonation method is from 1279 to 1372 meters and 1289 to 1409 meters during the studied period time, respectively. The groundwater level is placed in more depth with the proximity to the central and southern regions. The maximum decrease and increase of groundwater level variations have been 12 and 19 meters during three decades, respectively. Also, the underground water level variations during these three decades showed that both the second and third decades compared to the first decade and the third decade compared to the second decade have increased in more than 50% of the region. This increase can be caused by the optimum management and water use in these years. Therefore, groundwater level monitoring provides effective help for experts and users in planning and optimal management of groundwater for the sustainable development of water resources.

Trend Analysis and Change Points in Time Series of Water Level of Shallow and Deep Wells in Gorganrood Watershed
T. Mohammadi, V. Sheikh, A. Zare, M. Salarijazi,
Volume 27, Issue 3 (12-2023)
Abstract
A quantitative study of groundwater resources and accurate monitoring of changes over time, especially in areas facing limited water resources, is considered essential for proper management and sustainable exploitation of these resources. Golestan province, one of the semi-arid provinces of Iran has faced a drop in the groundwater level and an increase in the salinity of the groundwater due to the excessive withdrawals from the groundwater table and the reduction of atmospheric precipitation in the past few years. Gorgan Plain with an area of about 4727 square kilometers is one of the largest plains in Iran and the most important plain of Golestan province in terms of water supply for agricultural and drinking purposes. In this plain, there is a network of piezometers and observation wells that include continuous monthly measurements for more than 30 years. The objective of this research was to investigate the changes in the groundwater level of shallow (30 years (1989-2018)) and deep (22 years (1997-2018)) wells. The Man-Kendall method was used to reveal the trend and Pettitt, Normal Standard, and Buishand methods were used to identify sudden change points in a time series of groundwater levels in 49 shallow wells and 12 deep wells. The results of this research showed that the groundwater level in most of the studied wells had a significantly decreasing trend at a significant level of 5%. Also, the largest amount of groundwater loss was in the southern and southwestern parts of the plain, which can be attributed to a large amount of water taken from the wells due to their proximity to urban areas and some local conditions such as the proximity of the wells of this area are located in altitudes and at the entrance border of the aquifer. In the same way, as it rises, the fall decreases in the middle of the plain, and the amount of fall decreases in the northern areas and the edge of the Caspian Sea. It can be related to the proximity to the Caspian Sea and the high water table, and as a result, the inappropriate quality of water and land (high salinity and low fertility), which has caused the water withdrawal from this area to be less.

Temporal and Spatial Estimation of Quality Variables of Groundwater Resources Based on Intelligent Methods
A.r. Emadi, R. Fazloula, S. Zamanzad-Ghavidel, R. Sobhani4, S. Nosrat-Akhtar,
Volume 27, Issue 3 (12-2023)
Abstract
As one of the most necessary human needs, groundwater resources play a key role in the economic and political processes of societies. Climatic and land-use changes made serious challenges to the quantity and quality of groundwater resources in the Tehran-Karaj study area. The main objective of the present study is to develop a method based on individual intelligent models, including adaptive neural-fuzzy inference system (ANFIS), gene expression programming (GEP), and combined-wavelet (WANFIS, WGEP) methods for temporal and spatial estimation of total hardness (TH), total dissolved solids (TDS), and electrical conductivity (EC) variables in the groundwater resources of the Tehran-Karaj area for statistical period of 17 years (2004-2021). The results showed that 
combined-wavelet models have higher performance than individual models in estimating three selected variables. So that the performance improvement percentage of the WANFIS model compared to ANFIS and WGEP model compared to GEP, taking into account the evaluation index of root mean square error (RMSE) were obtained (23.713%, 18.018%), (12.581%, 33.116%), and (6.433%, 12.995%) for TH, TDS, and EC variables, respectively. The results indicated a very high spatial and temporal compatibility of the estimated values of the WGEP model with the observed values for all three qualitative variables in the Tehran-Karaj area. The results showed that the concentration of qualitative variables of groundwater resources from the north to the south of the study area has an upward trend for all three qualitative variables. In urban areas, pollution caused by sewage and population increase, as well as in agricultural areas, the use of chemical fertilizers and their continued infiltration into groundwater resources and 
over-extraction of groundwater resources aggravate their pollution. Therefore, in the study area, climatic changes and the type of land use are strongly related to the quality of groundwater resources.
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