Evaluation of Softening of Clayey Soil Stabilized with Sewage Sludge Ash and Lime

Production of sewage sludge have raised increasing concerns due to negative environmental effect. Sewage Sludge Ash (SSA) is used as a new type of additive for clay. Laboratory tests were performed on clay samples to study the mechanism of sewage sludge ash (SSA) and Hydrated Lime (HL) soil stabilization. Different SSA contents (0, 5, 10, 15%) and hydrated lime (0, 1, 3 and 5%) were added to the soil samples. 288 samples were prepared, and unconfined compressive strength tests were carried out. The samples were tested under optimum water content and also saturated conditions with three replications. The results of the coefficient of softening indicated that by adding SSA and hydrated lime to clay soil simultaneously, the stabilized clay soils can be applied in the moist and saturated condition. According to the results, the samples of SSA contents 0% with hydrated lime 5% and SSA contents 10% with hydrated lime 5% can be placed in the vicinity of moisture

Hydrologic drought indices analysis by regionalization methods in southwest of Iran

11 p.International audienceDrought is a recurrent extreme climate event with tremendous hazard for every specter of natural environment and human lives. Drought analysis usually involves characterizing drought severity, duration and intensity. Usually, long-term datasets of hydrometric and hydrochemical information are needed to begin an evaluation of dominant low flow (as hydrologic drought indices) producing processes however, in many catchments, these data are not available. A major research challenge in ungauged basins is to quickly assess the dominant hydrological processes of watersheds. In this paper, for developing regional models, low flow analysis has been performed by 3 regression methods (multivariate regression, low flow index method, regionalization model of frequency formula parameters) and Hybrid low flow model in Karkheh basin (southwestern of Iran). Estimated error for four methods show although hybrid method can also use for low flow regionalization analysis but multivariate regression and low flow index methods are more suitable for this purpose

Conditioning DRASTIC model to simulate nitrate pollution case study: Hamadan-Bahar plain

One of the major causes of groundwater pollution in Hamadan-Bahar aquifer in western Iran is a non-point source pollution resulting from agricultural activities. Withdrawal of over 88% of drinking water from groundwater resources, adds urgency to the studies leading to a better management of water supplies in this region. In this study, the DRASTIC model was used to construct groundwater vulnerability maps based on the "intrinsic” (natural conditions) and "specific” (including management) concepts. As DRASTIC has drawbacks to simulate specific contaminants, we conditioned the rates on measured nitrate data and optimized the weights of the specific model to obtain a nitrate vulnerability map for the region. The performance of the conditioned DRASTIC model improved significantly (R 2=0.52) over the intrinsic (R 2=0.12) and specific (R 2=0.19) models in predicting the groundwater nitrate concentration. Our study suggests that a locally conditioned DRASTIC model is an effective tool for predicting the region's vulnerability to nitrate pollution. In addition, comparison of groundwater tables between two periods 30years apart indicated a drawdown of around 50m in the central plain of the Hamadan-Bahar region. Our interpretation of the vulnerability maps for the two periods showed a polluted zone developing in the central valley requiring careful evaluation and monitorin

Effectiveness of Vetiver system in improving biological characteristics and electrical conductivity of wastewater

The increasing population and development of agricultural and industrial activities have put excessive pressure on freshwater resources. As a result, wastewater treatment has received growing attention in recent years. It seems more necessary in arid and semi-arid regions such as Iran, where we face climate change and a lack of rainfall (Mohammadi Moghadam et al., 2015; Nikmanesh et al., 2018). However, wastewater is one of the most critical environmental pollutants. If the microbial quality of the effluent and its hygienic aspects are not taken into account, its reuse poses a severe risk to human health and the environment (Abedi-Koupai et al., 2021). Therefore, the primary purpose of disinfection effluent from municipal wastewater treatment plants is to reduce the concentration of water-borne pathogens to less than the amount of infectious. Disinfection is done by physical and chemical methods. In most parts of the world, chlorine is the premier option for disinfecting effluents. That said, the adverse effects of chlorine effluent disinfection on humans and the environment have led to the possibility of using phytoremediation to improve the biological properties of water (Keddy, 2010). The Vetiver (VS) system for wastewater treatment is an innovative phytoremediation technology that has fantastic potential. This plant can grow in saline environments (Sanicola et al., 2019). Moreover, it can significantly improve the water quality parameters (Abedi-Koupai et al., 2021). Therefore, this study aims to investigate the possibility of using Vetiver in urban wastewater hydroponically to evaluate its efficiency in removing and refining pathogens, especially gastrointestinal coliforms. Our purpose is to use the treated water in the agriculture sector for irrigation

Quantification of Groundwater Recharge in the Karvan Aquifer in Isfahan (Iran) Using the CRD Model

Identification of the net groundwater recharge is essential for groundwater modeling and water resources management.  Due to its simplicity and its minimum stochastic parameter requirements, the CRD model has been widely applied to estimate recharge. Rainfall is the main source of groundwater recharge in the Karvan area in Isfahan(Iran). The area is located in the semi-arid zone and there is no source of recharge other than rainfall. Estimation of groundwater recharge from rainfall is not an easy task since it depends on many uncertain parameters. The cumulative rainfall departure (CRD) model was used in this study to estimate the net groundwater recharge from rainfall. The cumulative rainfall departure (CRD) model is based on the principle of water balance and does not require much data as is the case with other conventional methods of recharge estimation. The CRD model was conducted using the optimization method to minimize the root mean square error (RMSE) between the measured and the simulated groundwater head. The results indicated that the annual amount of groundwater recharge from rainfall in the Karvan Aquifer in Isfahanis about 48.07 million m3