NewAge is a semi-distributed hydrological model that models the whole hydrological cycle, including radiation budget, evapotranspiration, snow modelling, hillslope runoff, runoff aggregation, and flood propagation. It is designed to be fast and easy to use. NewAge represents the topology of hillslopes and the river network as an oriented graph. It performs water and energy budgets for each hillslope based on modified Duffy and Utah Energy Balance models. The model outputs include effective rainfall, radiation, temperature, wind, and snow water equivalent. Case studies applying NewAge to the Passirio and Adige rivers in Italy are presented.

1. NewAge: a semi-distributed hydrological model as a dynamical system
Riccardo Rigon1, Silvia Franceschi2, Andrea Antonello2, Stefano Endrizzi3, and Giuseppe Formetta1
1 Department of Civil and Environmental Engineering - CUDAM, University of Trento, Italy (riccardo.rigon@ing.unitn.it, formetta@ing.unitn.it); 2HydroloGIS - Soluzioni Open Source per l’Ambiente - Via Siemens 9, 39100 Bolzano (info@hydrologis.com); 3 Centre of
Hydrology - University of Saskatchewan - Saskatoon – Canada, (stefano.end@gmail.com)
What is cool about NewAge? Fig. (4): Adige River with Case Study and Results
outlet to Bozen and its
NewAge models the whole hydrological cycle, fig.(1): the hillslopes-link splitting using Here we report about two case studies regarding the two
jgrass tools
radiation budget and evapotranspiration part; the snow rivers Passirio and Adige with outlet in Bozen, fig(4), and
modelling; the hillslope runoff budget; the runoff covering respectively the discharge and the snow cover
aggregation and the flood propagation. However, it is estimation. This last is compared to MODIS product. A
designed to be fast and easy to use. more detailed description is given in Formetta et al. 2010
As other models is based on the idea that the prognostic and Endrizzi et al. 2010.
variables are given for an “elementary area” such that Fig. (1): NewAge hydrological component All the NewAge component are used in the first
each “hillslopes” constitutes the elementary grid element simulation: after spatializing the hydro-meteorological
of the model and is connected to the others by the data using ordinary kriging and the meteo data
channel network. Its topology is represented by an interpolator JAMI. Both the water and the energy budget
oriented graph, whose links are numbered through a are performed.
generalisation of the Pfafstetter ordering (Verdin K, Fig. (2):Informatic Structure The simulation period is six month period between
of the NewAge Informatic
1999). However this information is retained as a System 01/10/2008 and 31/03/2009; after a manual calibration
geometric feature in a database. during the first month, the optimal parameters set is used
The mass budget for each hillslope is performed for the last period.
according to a suitable modification of Duffy (1996) The results are shown in fig.(5): solid line represents
dynamical model of hillslope runoff. Differently from measured discharge and dashed line the simulated
traditional rainfall-runoff models, the discharge is Fig.(5): Passirio river hydrogram and ietogram during sumulation period: 01-10/2008 –
discharge.
31/03/2009
evaluated in each link of the river network according to
Cuencas (2005). Radiation is calculated accounting for In the second simulation the energy balance component
the sub-hillslope variability using a suitable scheme is tested focusing on the Snow Water Equivalent (SWE)
described in Antonello et al. 2010 and Endrizzi et al 2010. output, quantitatively identified with the snow cover at
Snow is modelled by a custom implementation of the
. ground. The results in fig.(7) summarizes the comparison
Fig. (3): Water Budget: Duffy
Utah Energy Balance concepts which outperforms two states dynamic system between SWE computed by the model and estimated
schematization
traditional degree-days models traditionally used in this using unsupervised classification of satellite images
large scale todays. Evapotranspiration estimation uses Fig.(7): SWE comparison between MODIS Fig. (8): Unsupervised classification of
MODIS Aqua, 250m ground resolution and 721 bands.
the Penman-Monteith formula, and includes hillslope AQUA images and NewAge outputs MODIS AQUA image, 17/09/2008 The result of unsupervised classification of Modis image
. .
variability in land use, soil cover and hydrological state. is a raster in which one distinguishes between covered
Flood wave propagation for the main streams can be and no snow covered zones. For model output, at the
estimated using a semi-implicit solver of the 1D de Saint first, the zones with SWE>0 are classified as snow
Venant equation. And above all, each model is a The Energy Budget The Water Budget covered zone and viceversa; than, to account for the
“component” and can be substituted easily by others decreasing of model output SWE because is the mean
The application of NewAge interopolator components The water balance component integrates the continuity
without rewriting the model code. value on all the hillslope, the zones with SWE>threshold
provides input data for Energy Balance Model which equation on the partial volumes occupied by saturated
are classified as snow covered zone and viceversa.
introduces, to improve computational efficiency, an and unsaturated portion of a hillslope, like a dynamic
energetic index that weighs the spatial distribution of solar system in two state variables: the volume stored per unit
The Informatic Structure radiation based on the topographic properties of the area in the saturated system, S1[L], and unsaturated, S2
The Informatic System NewAge consists of three main basin. An energetic index (IE) is defined as the ratio [L], fig.(3). The equations used are mostly linear and References
compoments whose interactions are depicted in Fig. (2): between incoming solar shortwave radiation and the those deemed non linear functions are approximated by
second order polynomial (Duffy,1996). A kinematic GIUH A. Antonello, S. Franceschi, G. Formetta & R. Rigon: NewAge System
same quantity calculated ignoring the topographic effects
for basin scale forecasting and menagement of hydrological budget:
• Environmental Data Center (EDC): a Geographic SQL (slope, aspect, ecc). IE is then averaged in time (monthly, model for residence time (Rinaldo, A. & I. Rodriguez- informatic structure. In preparing for GMD
DataBase contains all the model input data. It is builded seasonally) and in space (on hillslope area). Iturbe, 1996) is implemented to simulate the outflow of a
hillslope. Splitting a soil volume in unsaturated part, Duffy, C. J. (1996), A Two-State Integral-Balance Model for Soil Moisture
up PostgressSQL System and enriched by geographic The model solves both conservation mass and energy
and Groundwater Dynamics in Complex Terrain, Water Resour. Res.,
features though PostGIS extension. This allow one to equation for the mass of snow: identified by the subscript 1, and in a saturated, the 32(8), 2421–2434.
menage and query both hydro-meteorological data but subscript 2, and considering the boundary as mobile, the
 dT* continuity equations gives: Endrizzi, S., Formetta G, Franceschi S., Antonello A. e Rigon R.,
also vectorial feauters (hillslope and network features); C p ⋅ dt = ΔR(i,t ) + ΔH* f (i,t ) NewAge System for basin scale forecasting and menagement of
 (1)
  dS1 hydrological budget: energy balance and something more. In preparing for
dM* ΔH* f  = f01 − g12 − f10
• J-Grass DataMaster: a simple and usefull web service  =P−  dt GMD

 dt λf  (2)
automatically implements the query to J-Hydro hiding the dS2 Formetta G., Franceschi S., Antonello A., Cordano E., Mantilla R. e

user the complexity of the SQL language. It also allows 
 dt
= f02 + g12 − f20 Rigon R., NewAge System for basin scale forecasting and menagement of
one both to visualize selected data and to upload output The model outputs are, for each time-step of the hydrological budget: runoff generation, aggregations and propagation. In
model in J-Hydro. simulation, effective rainfall, net shortwave radiation,
€ The analitic form of the functions linking the flows to the preparing for GMD
temperature, wind velocity and SWE. state variables are specified in Duffy (1996) e Mantilla & Gregersen JB, Gijsbers PJA, Westen SJP (2007) OpenMI: Open modelling
• J-Grass GIS: contains all the hydrological model of the Gupta (2005) and Formetta et al (2010).
€ interface. Journal of Hydroinformatics, 09.3, 175-191. doi: 10.2166/hydro.
informatic system NewAge. Through simple interfaces the 2007
user can specify input data and parameter values. The Rinaldo, A. & I. Rodriguez-Iturbe, The geomorphological theory of
models are implemented following OpenMI 1.4 standard thehydrologic response, Hydrol. Processes, 10(6), 803-844, 1996;
Gregesen et al. (2007) and include an OGC grid Ricardo Mantilla, Vijay K. Gupta, A GIS Framework to Investigate the
coverage service based on geotools libraries to efficiently Process Basis for Scaling Statistics on River Networks - Geoscience and
deal with large volumes of spatial data. A new version Remote Sensing Letters, Number 4, 2005.
based on OMS3 is going to be available.