Deriving optimal operational policies for off-stream man-made reservoir considering conjunctive use of surface- and groundwater at the Bar dam reservoir (Iran)

Study region: The off-stream artificial Bar lake, built in 2015 to store the flood flows of the Bar river for domestic and industrial needs and with the objective to intentionally recharge the aquifer, is situated in the Razavi Khorasan province (Iran). Study focus: We present a methodology, based on the combination of a MODFLOW groundwater flow model for estimating seepage rates, and an optimization model, for the management and operation of an artificial reservoir considering surface/groundwater interactions for satisfying 12 Mm3/year of water demand. We simulated the reliable amount of water that can be supplied from the reservoir, considering reservoir seepage, maximizing water supply yields subject to the water supply reliability requirements, and the additional intentional volume of groundwater recharge. New hydrological insights for the region: Our results demonstrate the reliability of conjunctive use of surface-and ground-water in water scarce areas by exploiting reservoir infrastructures with relevant leakage losses, also for creating additional aquifer storage. In such systems, man-induced changes of lake stages can significantly affect the volume of water that seeps through the lakebed. The aquifer, under managed aquifer recharge operations, may then provide the resource not satisfied by the reservoir release, fulfilling 100 % reliability of water supply. The conjunctive use of surface- and ground-water, by improving water security, may open new sustainability views for leaking reservoirs, even if they were not initially designed for increasing aquifer recharge, in many areas worldwide

Characterization, geostatistical modeling and health risk assessment of potentially toxic elements in groundwater resources of northeastern Iran

Study region: Northeastern Iran. Study focus: In northeastern Iran, water needed for municipal and agricultural activities mainly comes from groundwater resources. However, it is subject to substantial anthropogenic and geogenic contamination. We characterize the sources of groundwater contamination by employing an integrated approach that can be applied to the identification of large-scale contamination sources in other regions. An existing dataset of georeferenced water quality parameters from 676 locations in northeast of Iran was analyzed to investigate the geochemical properties of groundwater. Gridding of the parameters graphically illustrates the areas affected by high concentrations of As, Cl−, Cr, Fe, Mg2+, Na+, NO3−, Se, and SO42-. We then identified potential anthropogenic and geogenic contamination sources by employing random forest (RF) regression modeling. New hydrological insights for the region: Random forest (RF) models show that the major ions, As, Cr, Fe, and Se content of groundwater are mainly determined by geology in the study area. Modeling also links groundwater NO3− contamination with sewage discharge into aquifers as well as the application of nitrogenous and animal-waste fertilizers. Areas of high salinity result from evaporate deposits and irrigation return flow. Medium to high non-carcinogenic health risk is found in areas with high concentrations of geogenic As and Cr in groundwater. Our approach can be applied elsewhere to analyze regional groundwater quality and associated health risks as well as identify potential sources of contamination.Water Resource