A few year ago, I felt the necessity to built a less distributed model than GEOtop, but, at the same time, less lumped than my Peakflow model based in the GIUH theory. The model had to follow the new informatics envisioned in the GEOFRAME talk (see one of my first post for reference, and the post on adopting OMS3). The occasion was some financial support coming from the Adige river basin Authority. That, not only started the JGrass-NewAGE model, but also the migration of JGrass to the Eclipse Rich Client Platform, the implementation of a Postgres/Postgis database suited to contain a digital watershed model.
The first implementation of the model was based on the OpenMI, but as explained a couple of posts ago, we migrated to the OMS3 platform, and the second implementation of the model can be now found here.
The paper I am introducing, talk about the rainfallrunoff core of JGrass-NewAGE, and presents a discussion of its predictive capacity. The model focuses on the hydrological balance of medium scale to large scale basins, and considers statistics of the processes at the hillslope scale. The whole modeling system consists of six main parts: (i) estimation of energy balance; (ii) estimation of evapotranspiration; (iii) snow modelling; (iv) estimation of runoff production; (v) aggregation and propagation of flows in channel, and (vi) description of intakes, out-takes, and reservoirs. This paper details the processes, of runoff production, and aggregation/propagation of flows on a river network. The system is based on a hillslope-link geometrical partition of the landscape, so the basic unit, where the budget is evaluated, consists of hillslopes that drain into a single associated link rather than cells or pixels. To this conceptual partition corresponds an implementation of informatics that uses vectorial features for channels, and raster data for hillslopes. Runoff production at each channel link is estimated through a combination of the Duffy (1996) model and a GIUH model for estimating residence times in hillslope. Routing in channels uses equations integrated for any channels' link, and produces discharges at any link end, for any link in the river network. The model has been tested against measured discharges according to some indexes of goodness of fit such as RMSE and Nash Sutcliffe. The characteristic ability to reproduce discharge in any point of the river network is used to infer some statistics, and notably, the scaling properties of the modeled discharge.
The full paper is available at the GMMD site. Any comment from you is welcomed.