Kourosh Mohammadi

Calibrating DRASTIC using field measurements, sensitivity analysis and statistical methods to assess groundwater vulnerability

The objective of this research is to indicate how the vulnerability potential to pollution may be assessed more accurately by correcting both the ratings and weights of the parameters used in the popular EPA DRASTIC method. In order to demonstrate the applicability of the proposed method, the Astaneh Aquifer located in northern Iran was selected. Nitrate concentrations were used to correlate the pollution potential in the aquifer to the DRASTIC index. The results indicated that the modified DRASTIC was significantly superior to the original method.

Estimating Water Retention with Pedotransfer Functions Using Multi-Objective Group Method of Data Handling and ANNs

Abstract Pedotransfer functions (PTFs) have been developed to estimate soil water retention curves (SWRC) by various techniques. In this study PTFs were developed to estimate the parameters (θs, θr, α and γ) of the Brooks and Corey model from a data set of 148 samples. Particle and aggregate size distribution fractal parameters (PSDFPs and ASDFPs, respectively) were computed from three fractal models for either particle or aggregate size distribution. The most effective model in each group was determined by sensitivity analysis. Along with the other variables, the selected fractal parameters were employed to estimate SWRC using multi-objective group method of data handling (mGMDH) and different topologies of artificial neural networks (ANNs). The architecture of ANNs for parametric PTFs was different regarding the type of ANN, output layer transfer functions and the number of hidden neurons. Each parameter was estimated using four PTFs by the hierarchical entering of input variables in the PTFs. The inclusion of PSDFPs in the list of inputs improved the accuracy and reliability of parametric PTFs with the exception of θs. The textural fraction variables in PTF1 for the estimation of α were replaced with PSDFPs in PTF3. The use of ASDFPs as inputs significantly improved α estimates in the model. This result highlights the importance of ASDFPs in developing parametric PTFs. The mGMDH technique performed significantly better than ANNs in most PTFs.

GIS DRASTIC model for groundwater vulnerability estimation of Astaneh-Kouchesfahan Plain, Northern Iran.

In this study, the groundwater vulnerability to pollution was evaluated for Astaneh-Kouchesfahan Plain, Northern Iran using GIS DRASTIC model. Based upon available data, six thematic maps were generated and intrinsic vulnerability map was developed based upon calculations from various mapped layers and DRASTIC index. The results show that low, moderate, high and very high groundwater vulnerability risk zones cover around 12, 52, 28 and 8% of the area, respectively. Finally, in order to verify the model, the categorised DRASTIC map was compared with a categorized TDS map and the results shows that the areas including enhanced values of TDS correspond with those with higher DRASTIC ratings.

Aquifer vulnerability assessments using DRASTIC, Weights of Evidence and the Analytic Element Method

Abstract In arid and semi-arid regions of the world, sustainable social-economic development relies almost exclusively on the availability of good quality groundwater. Pro-active management of these resources is vital, and reliable assessments of aquifer vulnerability are an important component of the overall management plan. In southwest Iran, the universally popular DRASTIC method of vulnerability assessment was implemented using the Analytic Element Method (AEM) to determine the “depth to water” input parameter, and compared to vulnerability assessments obtained using the standard DRASTIC approach. Vulnerability maps were also prepared through statistical analysis of aquifer characteristics and water quality data using the Weights of Evidence (WoE) approach. A comparison of the four vulnerability maps produced for the region showed DRASTIC, with and without AEM refinement, to be a reliable method of vulnerability assessment. The AEM proved to be a valuable means of estimating the depth to water input parameter when well data are severely limited. Editor D. Koutsoyiannis Citation Abbasi, S., Mohammadi, K., Kholghi, M.K., and Howard, K., 2013. Aquifer vulnerability assessments using DRASTIC, Weights of Evidence and the Analytic Element Method. Hydrological Sciences Journal, 58 (1), 1–12.

Improvement in estimation of soil water retention using fractal parameters and multiobjective group method of data handling

Soil water retention characteristic is required for modeling of water and substance movement in unsaturated soils and need to be estimated using indirect methods. Point pedotransfer functions (PTFs) for prediction of soil water content at matric suctions of 1, 5, 25, 50, and 1500 kPa were developed and validated using a data-set of 148 soil samples from Hamedan and Guilan provinces, Iran, by multiobjective group method of data handling (mGMDH). In addition to textural and structural properties, fractal parameters of the power-law fractal models for both particles and aggregates distributions were also included as predictors. Their inclusion significantly improved the PTFs’ accuracy and reliability. The aggregate size distribution fractal parameters ranked next to the particle size distribution (PSD) in terms of prediction accuracy. The mGMDH-derived PTFs were significantly more reliable than those by artificial neural networks but their accuracies were practically the same. Similarity between the fractal behavior of particle and void size distributions may contribute to the improvement of the derived PTFs using PSD fractal parameters. It means that both distributions of the pore and particle size represent the fractal behavior and can be described by fractal models.

Hydrogeochemistry and groundwater quality assessment of Astaneh-Kouchesfahan Plain, Northern Iran

In this study, the hydrochemical characteristics of 230 bore well samples were analysed in Astaneh-Kouchesfahan Plain. Data interpretation shows that alkaline earths (Ca2+ and Mg2+) exceed the alkalis (Na+ and K+) and weak acids (HCO3–) exceed the strong acids (Cl– and SO42–) and Ca-HCO3 type is the dominant hydrochemical facies. The distribution patterns of the abundant parameters show that changes in chemical composition occurred in the middle, southwest and west of the area due to either natural geochemical process and/or anthropogenic activities. The results of factor analysis show that factor 1 of the pre-monsoon and factor 2 of the post-monsoon have high loading in the ions Na+ and Cl–. Furthermore, it is indicated that there is an increase in the loadings of Ca2+, SO42–, HCO3–, Mg2+ and K+ in post-monsoon compared to pre-monsoon due to the effect of precipitation and subsequent dissolution of the calcareous rocks and fertiliser.