specific yield

The decrease in rainfall, the increase in drought and the development of agriculture in recent years have led to an increase in the consumption of underground water and an increasing decline in water levels. In this study, using version 10 of GMS software, the condition of Qazvin Plain aquifer was modeled in two stable states for October 2017 and unstable from October 2017 to September 2018. The sensitivity analysis of the model was performed with respect to the parameters of hydraulic conductivity and specific yield, and these parameters were determined after calibration and validation of the model. The sensitivity analysis of the model with respect to the two mentioned parameters shows that the model is more sensitive to changes in hydraulic conductivity compared to changes in specific yield. The root mean square error in stable and unstable state was 0.84 and 1.06 m, respectively, and the absolute mean error was 0.66 and 0.75 m, respectively, which shows the high accuracy of the model simulation. The average value of hydraulic conductivity in the aquifer area was estimated as 14.06 m/day and specific drainage was 0.064. Then the underground water level in 6 scenarios of changing the irrigation systems (maintaining the existing situation, increasing the irrigation level under pressure, changing the systems to surface, changing the systems to rain, changing the systems to drip and irrigation with 100% efficiency) was simulated. The results showed that assuming that the underground water extraction is constant, in the surface irrigation scenario, the underground water level will be at its highest level with 30% return water and in drip irrigation conditions at its lowest level with 3.6% return water.

Increasing groundwater consumption and water table level leads to changes in hydrodynamic properties of the aquifer especially the parameters of hydraulic conductivity and specific yield. In this study, that was conducted in 2021 using GMS model version. 10 in Qazvin aquifer, the coefficients of hydraulic conductivity and specific yield of aquifer in three census periods of 2002, 2009 and 2018 after calibration and validation of the model in two cases steady and unsteady were determined and compared. The root mean square errors in the steady state  for the proposed periods were 0.86, 0.73 and 0.84 m, respectively, and in the unsteady state were 1.7, 0.93 and 1.06 m, respectively. That shows high accuracy of the model simulation. The average hydraulic conductivity in the aquifer was estimated for the years of 2002, 2009 and 2018 which was 19.13, 16.85 and 14.06 meters per day and the average specific yield was 0.078, 0.071 and 0.064, respectively. The results showed that over time and by decreasing the groundwater level, the parameters of hydraulic conductivity and specific yield decrease. Since 2015 due to the measures taken for balancing and artificial recharge plan, the slope rate of hydraulic conductivity has decreased from 0.38 to 0.31. Also the slope rate of special discharge has decreased from 0.00117 to 0.00078. The main reason for this decreasing trend can be the destruction of soil structure and effective reduction of porosity indicating the irreversibility of the aquifer to its previous state. Therefore, it is necessary to pay attention to these changes regarding the recharge of aquifers and return water from irrigation systems.

The water movement in the aquifer is studied using the basic equations of flow, i.e. Darcy, continuity and mass survival equations, which are differently analyzed in the case of confined and unconfined aquifers. In these equations, hydrodynamic coefficients and other characteristics of the aquifer are used. Therefore, the determination of hydrodynamic coefficients of aquifer is necessary for groundwater studies. The most important characteristics of the aquifer i.e. hydrodynamic coefficients can be determined across the aquifer using modeling. If the aquifer model is properly provided, it can be a useful tool for better recognition of aquifer characteristics and also predicting the impact of different management plans on the water resources of the region. In this study, groundwater modeling was performed to determine the hydrodynamic coefficients in the unconfined aquifer of Kermanshah plain using GMS 7.1 software. The results showed that the amount of hydraulic conductivity in the Kermanshah plain aquifer varies from 0.1 to 30 meter per day and the amount of specific yield varies from 0.02 to 0.4. The amounts of computed water table by the model and the observed water table in the piezometers have high correlation and the root mean square error value is always less than one, which indicates the acceptable accuracy of the model for simulating the aquifer status.

Groundwater resources, as one of the most important factors in sustainable development, need to be intensely considered. Numerical models such as Modflow and MT3D is an applied tool for simulation and management of groundwater flow and solute transport. In this study, Shahrekord aquifer modeling is provided by the use of monthly data’s including hydraulic heads, depletion volume of the wells, springs and qanats, precipitation values. This model has been developed based on the assessment of the hydraulic conductivity and specific yield coefficients in the calibration process. The study year was divided to 12 monthly stress period for calibration (10 periods) and verification (2 periods). The results showed that the hydraulic conductivity from 6 to 16 m/day and specific yield from 0.03 to 0.07 were varied. The predicted water table in calibration process in comparison to observed values of water levels on piezometers with variance of 0.63. These results confirm the need model of groundwater flow prediction. Moreover, Effective molecular diffusion coefficient, longitudinal dispersity and distribution coefficient were calibrated to achieve acceptable variance between observed and calculated nitrate concentration. The most contaminant particles are in the south zone of aquifer where is the nearby urban wastewater wells. Moreover, the central and south parts of plain have the suitable situations for groundwater discharge because of the high amount of transmissivity.

Field capacity (FC) and permanent wilting point (PWP) are efficacious in determining net irrigation water depth. However, direct measurement of these properties is tedious, time consuming and costly especially on large scale. Soil pedotransfer functions (PTFs) as the indirect methods can replace by the direct methods. In this study, performance of the six available pedotransfer functions on FC and PWP moisture content predicting was evaluated on 112 soil samples that were collected from the north and northeast regions of Iran. The Root Mean Square Error (RMSE) values of menioned available PTFs were changed between 0.05 to 0.17 and 0.03 to 0.13 in moisture prediction on FC and PWP points, respectively. Therefore new PTFs were developed by Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) techniques based on soil properties (90 samples) and the results were validated on different soils (22 samples). The results showed that both MLR technique with assigning the RMSE values approximately 0.035, 0.01, 0.027 and 0.024 to predict soil moisture content on FC and PWP, total available water and specific yield and ANN technique with assigning the values approximately 0.013, 0.007, 0.015 and 0.013 to the same properties, evaluated in appropriate performance. The results also showed that using variables such as geometric mean and geometric standard deviation particle diameter, fractal dimension and air-entry suction, for the first one on input variables of PTFs, improved the accuracy of the results significantly, although accepting of this theory requires more studies.

Nowadays, due to the high potential of advanced simulation models for groundwater, these models are comprehensively applied in the management and exploitation of groundwater resources. The aim of this study was to investigate and simulate the groundwater resources in Kouhpayeh-Segzi watershed and in particular estimate the hydrodynamic coefficients of unconfined aquifer. After preparation of input layers, efficient parameters in modeling, boundary conditions and aquifer gridding were determined. Then, based on the available data, the model was run and calibrated in a steady state for the water year 2002 and in a transient state for water years between 2002 and 2004. The simulation outputs were confidently verified for the water year 2005. The results indicated that the hydraulic conductivities and storage coefficients were ranged on sub-basin from 15.26 to 19.87 m/day and 0.0107 to 0.0186, respectively. From aquifer's hydrograph for a period from 1995 to 2012, water level dropped about 25 cm. This may be due to two irrigation networks (green area). This leads to rising water level. By ignoring these recharge areas, water level declined up to 80 cm per year. With sensitivity analysis in transient state to evaluate the efficacy of each parameter, the accuracy of the results of calibration model was confirmed. In addition, the hydraulic head values computed by MODFLOW were in good agreement with those that were collected from all piezometers.

Simulation of Aquifer behavior has great importance in order to identifying the measurement of operation and planning for sustainable usage of these resources. That is why groundwater models predicts qualitative and quantitative aquifer behavior by hydrological، hydraulically and hydrogeological parameters. Since appropriate identification of these parameters increases aquifer simulating accuracy therefore estimating reasonable values of model parameters is crucial real situations planning. In this study one model is provided according to advanced optimization methods for calibrating aquifer hydrodynamics parameters (Sy and k) in Birjand plains. The recommended model is a combination of simulating and optimizing model (Cuckoo Optimization Algorithm) in MATLAB. Calibration period was one year (water year 2010-2011) with monthly13 Stress period. In order to evaluating the value of optimized parameter (calibration period) Validation period was one year period (water year 2011-2012) with 13 monthly Stress period. The accuracy of calibration and validation of model was evaluated by Mean Absolute Error (MAE)، Root Mean Square Error (RMSE) and Mean Error (ME) criteria. The amounts of these criteria were respectively 0. 48، 0. 73 and 0. 17 in calibration period and these were respectively 0. 63، 0. 89 and 0. 32 in validation period. Results revealed that presented approach has high accuracy for reasonable estimation aquifer parameters.

In this investigation groundwater modeling is attempted monitoring water table fluctuations of Jiroft basin using PMWIN computer model. Parameters like hydraulic conductivity, specific yield and groundwater abstraction and recharge were estimated by matching of the data from 41 observation wells for the period 1381-1386 to those predicted by the model using automatic calibration procedure with PEST. Verification of the model for a 6 month period in 1387 showed that the predicted water levels had a good match with the observed water levels with a root mean square error of 0.865. The verified model was used for the prediction of groundwater table behavior for the next 4 years.