A robust hydrological assessment is challenging in regions where human interference, within all aspects of the hydrological system, significantly alters the flow regime of rivers. The challenge was to extend a large-scale water resources model, GWAVA, to better represent water resources without increasing the model complexity. A groundwater and a regulated reservoir routine were incorporated into GWAVA using modifications of the existing AMBHAS-1D and Hanasaki methodologies, respectively. The groundwater routine can be varied in complexity when sufficient input data is available but fundamentally is driven by three input parameters. The reservoir routine was extended to account for the presence of large, regulated reservoirs using two calibratable parameters. The additional groundwater processes and reservoir regulation was tested in two highly anthropogenically influenced basins in India: the Cauvery and Narmada. The inclusion of the revised groundwater routine improved the simulation of streamflow in the headwater catchments and was successful in improving the representation of the baseflow component. In addition, the model was able to produce a time series of daily groundwater levels, recharge to groundwater and groundwater abstraction. The regulated reservoir routine improved the simulation of streamflow in catchments downstream of major reservoirs, where the streamflow was largely reflective of reservoir releases, when calibrated using downstream observed streamflow records. The model was able to provide a more robust representation of the annual volume and daily outflow released from the major reservoirs and simulate the major reservoir storages adequately. The addition of one-dimensional groundwater processes and a regulated reservoir routine proved successful in improving the model performance and traceability of water balance components, without excessively increasing the model complexity and input data requirements.

Recently, there has been renewed interest in the performance, functionality, and sustainability of traditional small-scale storage interventions (check dams, farm bunds and tanks) used across India for the improvement of local water security. The Central Groundwater Board of India is en-couraging the construction of such interventions for the alleviation of water scarcity. It is of critical importance to understand the hydrological effect of these interventions at basin scales to maximise their effectiveness. The quantification of small-scale interventions in hydrological modelling is often neglected, especially in large-scale modelling exercises. A bespoke version of the GWAVA model was developed to assess the impact of interventions on the water balance of the Cauvery Basin and two smaller sub-catchments. Model results demonstrate that farm bunds appear to have a negligible effect on the estimated average annual simulated streamflow at the outlets of the two sub-catchments and the basin whereas tanks and check dams have a more significant effect. In-terventions generally were found to increase evaporation losses across the catchment. The model adaption used in this study provides a step-change in the conceptualisation and quantification of the consequences of small-scale storage interventions in large- or basin-scale hydrological models.

This paper presents a comparison of the predictive capability of three hydrological models in a heavily influenced catchment in Peninsula India. In catchments where there is a high dependence on both streamflow and groundwater to meet demands, it is of importance to capture the catchment processes correctly. This study highlights the performance evaluation of a multi-model ensemble consisting of GWAVA (Global Water AVailability Assessment) model, SWAT (Soil Water Assessment Tool) and VIC (Variable Infiltration Capacity) model for comparative purposes and the key catchment hydrological processes. The three models were compared in several sub-catchments in the upstream reaches of the Cauvery river catchment. Model performances for monthly streamflow simulations from 1983 – 2005 were analysed for five catchments in the Upper Cauvery. The analysis was undertaken using Nash- Sutcliffe Efficiency, Kling- Gupta Efficiency and percent bias. Additionally, a mean ensemble is presented. The application of a multi-model ensemble approach can be useful in overcoming the uncertainties associated with individual models. The ensemble mean has a better predictive ability in catchments with reservoirs than the individual models. Utilising multiple models could be a suitable methodology to offset uncertainty in input data and poor reservoir operation functionality within individual models. This study has highlighted the importance of an accurate spatial representation of precipitation for input into hydrological models and comprehensive reservoir functionality is paramount to obtaining good results in this region.