ABSTRACT
Incipient groundwater salinization has been identified in many arid and semi-arid regions where groundwater is increasingly used for irrigation, but the dominant processes at stake in such context are yet uncertain. Groundwater solutes originates from various sources such as atmospheric inputs, rock dissolution and fertilizer residues, and their concentration is controlled by hydrological processes, in particular evapotranspiration. Here, we propose a deconvolution method to identify the sources and processes governing the groundwater Chloride concentration in agricultural catchments, using the relative variations of Sodium and Chloride and using a neighbouring pristine catchment as a reference for the release rate of Na by weathering. We applied the deconvolution method to the case of the Kabini Critical Zone Observatory, South India, where groundwater was sampled in 188 farm tubewells in the semi-arid catchment of Berambadi and in 5 piezometers in the pristine catchment of Mule Hole. In Berambadi, groundwater composition displayed a large spatial variability with Cl contents spanning 3 orders of magnitude. The results showed that the concentration factor due to evapotranspiration was on average about 3 times more than in the natural system, with higher values in the valley bottoms with deep Vertisols. Linked with this process, large concentration of Chloride originating from rain was found only in these areas. At the catchment scale, about 60 percent of the Chloride found in groundwater originates from fertilizer inputs. These results show that Potassium fertilization as KCl is an important source of groundwater salinization in semi-arid context, and stress that identifying dominant drivers is crucial for designing efficient mitigation policies.
ABSTRACT
Previous work has shown that Lagrangian methods are more efficient for modeling the transport of chemicals in a water distribution system. Two such methods, the Lagrangian Time-Driven Method (TDM) and Event-Driven Method (EDM) are compared for varying concentration tolerance and computational water quality time step. A new hybrid method (EDMNET) is developed which improves the accuracy of the Lagrangian methods. All the above methods are incorporated in an existing hydraulic simulation model. The integrated model is run for different network problems under varying conditions. The TDM-generated solutions are affected by both concentration tolerance and water quality time step, whereas EDM solutions are dependent on concentration tolerance. The EDMNET solutions are less sensitive to variations in these parameters. The threshold solutions are determined for all the methods and compared. The hybrid method simulates the nodal concentrations accurately with least maximum segmentation of network and reasonable computational effort as compared to the other Lagrangian methods.
