The model
The TOPKAPI (TOPographic Kinematic APproximation and Integration) model is a fully-distributed physically-based hydrologic model that can be used in realtime operational flood forecasting.
The Digital Elevation Model (DEM) subdivides the application catchment by means of squared cells: each cell is assigned a value for the physical parameters represented in the model.
Due to its physical soundness, the parameters of the model can be derived from digital elevation maps, soil maps and vegetation or land use maps in terms of slopes, soil permeability, channel and surface
roughness. TOPKAPI reproduces the behaviour of the main component of the hydrologic cycle. Beside subsurface, overland and channel flow, it includes components representing infiltration, percolation,
evapo-transpiration and snowmelt, plus a lake/reservoir component and a parabolic routing component based on Muskingum-Cunge method. Being a fully distributed model, TOPKAPI allows to study the evolution of all the hydrological state variables of the catchment: rainfall, temperature, evapotranspiration, soil moisture conditions, snow accumulation and runoff generation. TOPKAPI model can be used as part of real-time flood forecasting systems or for off-line stand alone applications. Main features The present version of the TOPKAPI model is the result of an intense review that has transformed it from an academic model developed at University of Bologna (Italy) to a real-time operational model. The main features of TOPKAPI model include:
Reduced execution times suitable for distributed model calibrations and realtime operational applications;
Easy calibration due to physically meaningful parameters whose values can be retrieved from Digital elevation maps, soil maps, land use and vegetation maps;
TOPKAPI can track the spatial variability of runoff conditions in the catchment. As opposed to semi-distributed modelling, TOPKAPI provides hydrologic prediction atany point of the channel network
(distributed 1D output);
Being a fully-distributed model, TOPAKPI can consider the spatial variability in precipitation fields, fully exploiting distributed rainfall estimates such as th ones produced by RADAR networks;
Ability to resolve basin hydrologic response at very fine temporal (few minutes) and spatial (100-1000 m) scales;
Possibility to run the model at different time scales, up to daily simulations.
Ability to represent the behaviour of the main components of the hydrological cycle producing not only stream flow forecast but also distributed information on soil moisture, evapo-transpiration, snow
accumulation, etc. (2D output maps). In addition to instantaneous basin states, the model generates the catchment water balance.
Possibility to be easily coupled with hydraulic models. Possibility to run continuous simulations.

In 2008 TOPKAPI model has been enrolled in
NOAA’s Distributed Model Intercomparison
Project Phase 2 (DMIP2)
Preliminary results showed at AMS Annual
Meeting 2009 pointed out the outstanding
behaviour of the model in the project’s case
TOPKAPI is part of PROGEA’s real-time flood forecasting system EFFORTS.
Recent applications
TOPKAPI model has been widely applied in Italy and abroad. In Italy it has been recently used to
implement the hydrologic model of the Po catchment (main Italian river) and it has been included
in the operational real-time flood forecasting system. Other applications in Italy include main
national rivers like Arno (through Florence), Tiber (through Rome), Adige and Reno.
In 2008 TOPKAPI has been implemented in China on the Yellow river, between XiaoLandgDi Dam
and HuaYuanKou and it is part of Progea’s EFFORTS real-time flood forecasting system run by
Yellow River Conservancy Commission at ZhengZhou premises, Henan Province.
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