Stefano Endrizzi1, Giacomo Bertoldi1, Markus Neteler2, Riccardo Rigon1

1Dept.of Civil and Environmental Engineering, University of Trento, Italy (stefano.endrizzi@ing.unitn.it)

2ITC-IRST (Center for Scientific and Technological Research), Trento, Italy

In this contribution the snow covered areas of the 250 km2 Brenta River basin in Trentino (Italy) are studied using the distributed hydrological model GEOtop and data from polar orbiting satellite platforms (MODIS).

REPRODUCTION OF SPATIAL PATTERNS OF SNOW MELT WITH THE HYDROLOGIC DISTRIBUTED MODEL GEOtop

Summary

MODIS 8 day composite

GEOtop (Bertoldi et al., 2004; Rigon et al., 2005) is a fully distributed hydrological model. It can be regarded as both a rainfall-runoff model simulating the hydrological cycle in a continuous mode and an attempt to incorporate an adequate treatment of hydrological variability at small scales into Land Surface Models (LSM) . Like a rainfall-runoff model it calculates the discharge at the outlet of the watershed and estimates the surface and subsurface water fluxes, the water content in both the saturated and the unsaturated portions of the soil layer. Like an LSM it estimates the local values and the spatial distribution of numerous hydro-meteorological variables, such as snow cover, soil moisture, surface temperature, radiative fluxes, turbulent heat fluxes and heat fluxes in the soil, taking into account the topography effects (slope and aspect), the solar radiation dependence on the weather conditions, and the soil and snow physics.The snow accumulation and melting module (Zanotti et al., 2004) in GEOtop is an adaptation of the UEB model (Tarboton and Luce, 1996). The snow cover is characterized by 3 state variables: SWE (snow water equivalent), U (internal energy, which defines both the energy content and the liquid fraction of the snow) and t (age of snow; used for albedo calculation). The state variables are solved at each time step solving numerically the energy balance equations.

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a 36-channel sensor measuring the spectral range from visible to thermal-infrared. It was launched as part of the payload of the Terra (12/1999) and Aqua (5/2002) satellites. Among other products, daily and 8-day composite snow related maps are produced at 500 m and 1000 m resolution. The maps created over land include daily snow albedo and 8-day maximum snow extent. For the latter multiple days of observations for a cell are examined. If snow cover is found for at least one day, the cell is indicated as snow. Other values are lake ice, cloud, ocean, inland water, land and night. If no snow is found in the cell, the most frequent value of the other classes is assigned. Due to the 8-day compositing technique the impact of clouds is minimized (Riggs et al., 2003).In this study we used the MOD10A2 8-day composite maximum snow extent data at level V004. The data were processed in GRASS GIS (Neteler, 2005).

Case study

Conclusions

ReferencesBertoldi G, Tamanini D, Zanotti F, Rigon R. 2004. GEOtop: a hydrological balance model. Technical report. University of Trento (Italy). E-Prints. http://eprints.biblio.unitn.it/archive/00000551/ (4 April 2004)

Neteler M. 2005. Time series processing of MODIS satellite data for landscape epidemiological applications. International Journal of Geoinformatics. Special Issue on FOSS/GRASS 2004 & GIS-IDEAS 2004, 1(1), pp. 133-138, March 2005

Rigon R, Bertoldi G, Over T. 2005. GEOtop: a distributed model of the hydrological cycle for the remote sensing era. Submitted to J.of Hydromet.

Riggs G A, Hall D H, Salomonson V V. 2003. MODIS Snow Products User Guide. Electronic document: http://modis-snow-ice.gsfc.nasa.gov/sugkc.html

Tarboton D G, Luce C H. 1996. “Utah Energy Balance Snow Accumulation and Melt Model (UEB)," Computer model technical description and users guide. Utah Water Research Laboratory and USDA Forest Service Intermountain Research Station.

Zanotti F, Endrizzi S, Bertoldi G, Rigon R. 2004. The GEOtop snow module. Hydrol. Proc., 18:3667-3679. DOI:10.1002/hyp.5794.

Focusing on the Brenta river basin, a simulation with GEOtop is performed from October 2003 to June 2004.Precipitation is interpolated using kriging techniques from data measured in several meteorological stations located throughout the basin. Temperature is assumed to decrease with elevation with a constant lapse rate (0.56 ºC/100 m) close the wet lapse rate. Solar radiation is distributed in the basin according to slope, aspect and shadows.

River Brenta basinclosed at Borgo Valsugana

Two lakes of 5.3 and 1.1 km2

Area of the basin: 251.4 km2Min elevation: 340 m a.s.l.

Max elevation: 2303 m a.s.l.Average elevation: 936 m a.s.l.

Trentino (Italy)

• The GEOtop maps show a good agreement with the MODIS maps in autumn and in spring, during the melting time (although there are some errors in the remotely sensed data), when the snow spatial patterns are mainly dominated by elevation (maps 1, 5, 7, 8, 9, 10).

· Differential melting in north facing and south facing slopes (maps 5, 6, 7) is predicted.

· GEOtop overestimates the snow limit elevation in late autumn (maps 2, 6), probably because of the incorrect assumption of the lapse rate.

· GEOtop underestimates the snow melting in winter (maps 3, 4), as it underestimates the surface temperature in winter for clear sky days, probably because of an incorrect parameterization of turbulence heat fluxes under strong stability conditions in a non-homogeneous topography.

· MODIS maps are affected by some errors, like some snow cover spots at low elevations (maps 1, 9, 10) and snow free areas in north facing vegetated or steep slopes at high elevations during winter.

Surface energy balance and heat fluxes

Qc

HRn Qe Qp

Qm G

G1

G2

ENERGY BALANCE AT THE SURFACE

Conduction heat flux in the soil (G1, G2, ….)

Qc = conduction heat flux from the snow surface to the snow cover center (accounts for the effects of the vertical variability of temperature in the snow cover)

Rn = net radiation

H = sensible heat flux

Qe = latent heat flux

Qp = heat flux advected by precipitation

Ts = temperature of the snow surface

T1 = temperature of the snow

Soil multilayer model with a finite difference implicit scheme (Crank-Nicholson method)

MELTING HEAT FLUX AND CONDUCTION HEAT FLUX TOWARDS THE SOIL

( ) ( ) ( ) 0=−+−− cpfsessn QQTQTHTR

( )1TTCKQ ssssc −⋅⋅⋅= ρ

SN

OW

AT

MO

SP

HE

RE

SO

IL

This map is an example of a snow cover 8-day composite MODIS map overlaid with the DEM (Digital Elevation Model) of the whole Trentino region. Snow covered areas are shown in white color, snow free areas are brown, clouds yellow.

Here 8-day averaged SWE maps provided by the GEOtop model (250 m resolution) and snow cover extension 8-days composite MODIS maps (500 m resolution) for the Brenta river basin are shown.

MODIS SNOW COVER GEOtop SWE MODIS SNOW COVER GEOtop SWE

24 Oct 200331 Oct 2003Map 1

9 Nov 200316 Nov 2003Map 2

11 Dec 200318 Dec 2003Map 3

1 Jan 20038 Jan 2003Map 4

25 Jan 20041 Feb 2004Map 5

26 Feb 20044 Mar 2004Map 6

5 Mar 200412 Mar 2004Map 7

29 Mar 20045 Apr 2004Map 8

22 Apr 200429 Apr 2004Map 9

8 May 200415 May 2004Map 10

GEOtop predicted SWE (mm)

MODIS land classification

0

616

• The MODIS 8-day composite classification algorithm shows a few problems in mixed-land use, complex topography areas.

· The meteorological forcings of GEOtop should be more realistic as it is a strong approximation to assume a constant lapse rate. However, GEOtop will be soon coupled to an area limited atmospheric model.

· The best results are in spring, when the turbulent energy fluxes are stronger.

· The GEOtop model reproduces quite well the physical features of snow melting, and in the near future can be an effective tool to upscale and downscale remotely sensed data at different resolutions.

The model

Simulation resultsDiscussion