Integrating lumped hydrological modelling with GIS-based flow accumulation for spatiotemporal streamflow estimation

Estimating water availability in terms of runoff volume over time and space is crucial for identifying suitable locations for micro-scale rainwater harvesting (RWH) structures such as loose stone check dams and gabions, which are constructed along stream networks. Traditional hydrological assessments often rely on empirical methods, such as the Soil Conservation Service - Curve Number (SCS-CN) method, which have limitations in representing spatial variability in streamflow availability along drainage networks across different time scales. While rainfall-runoff models can model streamflow at variable time scales, they provide streamflow values only at the outlet of the catchment. To address these gaps under the conditions of limited gauge availability, this study proposes a lumped–spatial hybrid framework that combines a rainfall–runoff model with a GIS-based flow accumulation scheme to estimate spatiotemporally varying streamflow along the drainage network of small-sized catchments. Two rainfall-runoff models, GR4J and TOPMODEL, were selected for streamflow modeling. The combined approach was applied to an experimental catchment of 1150 km 2 in the Ovens River in southeast Australia, covering the period from 1999 to 2020. The streamflow models calibrated for the catchment were integrated with a flow accumulation scheme in GIS to develop a grid-based stream discharge accumulation (GSDA) map at a 10 m resolution. The spatiotemporal GSDA maps were analyzed at annual, monthly, and seasonal timescales. Monthly GSDA maps were validated against upstream gauging station data from Bright, Harrislane, and Harrietville, resulting in NSE values of 0.75, 0.75, and 0.72 for GR4J and 0.62, 0.6, and 0.45 for TOPMODEL, respectively. The annual GSDA highlights wet and dry years, while monthly and seasonal maps capture flow peaks, low-flow periods, and temporal runoff trends across the catchment. Unlike the SCS–CN method, which provides simplified runoff estimates, the GSDA framework offers temporally dynamic and spatially explicit insight into streamflow availability relevant for RWH planning. By estimating available water volumes at candidate stream locations and accounting for temporal variability in harvestable runoff, the proposed approach enhances the reliability of RWH site selection and structure design based on water availability.