This paper presents a comparison of the predictive capability of three hydrological models, and a mean ensemble of these models, in a heavily influenced catchment in Peninsular India: GWAVA (Global Water AVailability Assessment) model, SWAT (Soil Water Assessment Tool) and VIC (Variable Infiltration Capacity) model. The performance of the three models and their ensemble were investigated in five sub-catchments in the upstream reaches of the Cauvery river catchment. Model performances for monthly streamflow simulations from 1983–2005 were analysed using Nash-Sutcliffe efficiency, Kling-Gupta efficiency and percent bias. The predictive capability for each model was compared, and the ability to accurately represent key catchment hydrological processes is discussed. This highlighted the importance of an accurate spatial representation of precipitation for input into hydrological models, and that comprehensive reservoir functionality is paramount to obtaining good results in this region. The performance of the mean ensemble was analysed to determine whether the application of a multi-model ensemble approach can be useful in overcoming the uncertainties associated with individual models. It was demonstrated that the ensemble mean has a better predictive ability in catchments with reservoirs than the individual models, with Nash-Sutcliffe values between 0.49 and 0.92. Therefore, utilising multiple models could be a suitable methodology to offset uncertainty in input data and poor reservoir operation functionality within individual models.

The frequency analysis and risk assessment of extreme precipitation and streamflow at basin scales are essential for effective hydrologic design and water resource management activities. Processes that generate streamflow are influenced by both catchment characteristics and environmental conditions. As a result of climate change, human-induced changes in land use patterns (urbanization, deforestation, encroachment of flood plains), and faulty reservoir operations, the stationarity of streamflow assumption is questionable in flood frequency analysis. The changing climate has continued to alter the intensity, duration, and frequency of extreme events in the region, and the current status of climate change impacts on hydrology calls for the evaluation of a non-stationarity approach for extremes to enhance effective planning. This study aims to investigate the non-stationarity of streamflow and hydrologic sensitivity of catchments of the Godavari River basin located in peninsular India to changing climatic circumstances using a multi-model ensemble based on CMIP6 climate models. Firstly, Mann Kendall (MK) test is performed to detect the presence of temporal trends in the observed annual maximum streamflow series at 14 gauging stations distributed across the basin. Then peak flow series are analyzed using stationary and non-stationary models assuming invariant shape parameters and linear functions as location and scale parameters with time as a covariate. A generalized extreme value (GEV) distribution coupled with downscaled climate projections is employed to assess the probability distribution of extreme events. Results show that only 2 out of 14 streamflow series show temporal trends, suggesting that using physically based covariates instead of time can provide a better fitting. The return period can be shortened by more than one-tenth of its length, and flood risk is projected to increase significantly between the historical and future periods. These findings provide insights into non-stationary extreme streamflow behaviour, emphasizing the importance of identifying dominant drivers for changes in flooding under climate change.

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.

Catchments are complex self-organizing environmental systems for which the form, drainage network, channel geometries, soil and vegetation, are all an outcome of co-evolution and adaptation to the ecological, geomorphologic and land-forming processes. Quantification of hydrological signatures provides vital information about the complex system properties and the functional behaviour of catchments. This work aims at evaluating catchment similarity with respect to geomorphology and hydrological signatures such as runoff ratio, flow duration curves and peak flows for calibrating and upscaling model parameters. The study is carried out on the sub-catchments of Cauvery river basin which is a major river basin in Peninsular India. The basin is characterized by extensive regional variability in surface and groundwater availability and large-scale shift in land use patterns in recent decades. With a significant number of anthropogenic interventions such as check dams and reservoirs, the basin faces water management challenges at the local, regional and basin scales. Hydrological signatures derived from elevation, streamflow and meteorological data are used to evaluate geomorphologic and hydrological similarity between the sub-catchments. We employ the physically based macroscale Variable Infiltration Capacity (VIC) model coupled with a routing model to simulate the streamflow. Streamflow simulations are carried out for various sub-catchments delineated based on discharge gauging stations. Model parameters are estimated and hydrological signatures are assessed for effective model calibration. Impact of interventions on flow signatures at the catchment scale is also assessed. This work can significantly improve the scientific understanding of variability of hydrological processes at various scales and provide useful insights for development of scaling relationships. It can also aid in examining the model parameter transferability across scales.

Estimation of morphometric indices can be useful in defining similarity relationships between catchments over a wide range of scales and it facilitates the effective understanding of hydrogeologic processes. This study aims at evaluating morphometric parameters to investigate geomorphologic similarity between the sub-catchments of the Cauvery river basin which is a major river basin in Peninsular India. The Digital Elevation Model (DEM) obtained from Shuttle Radar Topographic Mission (SRTM) at 30 m spatial resolution is used for assessing the linear, areal and relief aspects of morphometric analysis. The stream network analysis of sub-catchments reveals that the basin is dominated by streams of lower order and the Cauvery basin can be characterized as a seventh order basin. Linear parameters indicate that the basin is subjected to less structural disturbances. Assessment of areal parameters shows that most of the sub-catchments have elongated shape, low drainage density and course drainage texture. Evaluation of relief parameters suggests that the sub-catchments have mild slopes with moderate ruggedness and resistant soil surface. The sub-catchments are found to be geomorphologically similar in behaviour and this analysis can throw insight on development of scaling relationships as well as hydrological predictions in ungauged areas of the drainage basin.