Jean-Pierre Fortin

Determination of the drainage structure of a watershed using a digital elevation model and a digital river and lake network

Abstract Distributed hydrological models require a detailed definition of a watersheds internal drainage structure. The conventional approach to obtain this drainage structure is to use an eight flow direction matrix (D8) which is derived from a raster digital elevation model (DEM). However, this approach leads to a rather coarse drainage structure when monitoring or gauging stations need to be accurately located within a watershed. This is largely due to limitations of the D8 approach and the lack of information over flat areas and pits. The D8 approach alone is also unable to differentiate lakes from plain areas. To avoid these problems a new approach, using a digital river and lake network (DRLN) as input in addition to the DEM, has been developed. This new approach allows for an accurate fit between the DRLN and the modelled drainage structure, which is represented by a flow direction matrix and a modelled watercourse network. More importantly, the identification of lakes within the modelled network is now possible. The proposed approach, which is largely rooted in the D8 approach, uses the DRLN to correct modelled flow directions and network calculations. For DEM cells overlapped by the DRLN, flow directions are determined using DRLN connections only. The flow directions of the other DEM cells are evaluated with the D8 approach which uses a DEM that has been modified as a function of distance to the DRLN. The proposed approach has been tested on the Chaudiere River watershed in southern Quebec, Canada. The modelled watershed drainage structure showed a high level of coherence with the DRLN. A comparison between the results obtained with the D8 approach and those obtained by the proposed approach clearly demonstrated an improvement over the conventionally modelled drainage structure. The proposed approach will benefit hydrological models which require data such as a flow direction matrix, a river and lake network and sub-watersheds for drainage structure information.

The potential of times series of C-Band SAR data to monitor dry and shallow snow cover

A study was conducted to assess the potential of C-band synthetic aperture radar (SAR) data to determine the snow water equivalent (SWE). A multitemporal (three winters) SAR data set was obtained using the Convair-580 from the Canada Centre for Remote Sensing (CCRS) over a watershed in the Appalachian Mountains in Southern Quebec, Canada. The SAR data were relatively calibrated using extended targets (coniferous stands). Extensive ground measurements were done simultaneously to each of the seven flights, in order to measure the snow cover characteristics (depth, density, SWE, liquid water content, temperature, and dielectric profiles) as well as the soil characteristics (moisture, temperature). To estimate the SWE of a given snowpack, a model which links the scattering coefficient to the physical parameters of the snow cover and the underlying soil has been developed. The model is based on the ratio of the scattering coefficient of a field covered by snow to the scattering coefficient of a field without snow. The analysis has revealed that volume scattering from a shallow dry snow cover (SWE<20 cm) is undetectable. The backscattering power is dominated by soil surface scattering, the latter varying with the decrease of liquid water content in the surface layer with decreasing soil temperature below 0/spl deg/C. Then, the scattering ratio decreases proportionally to the dielectric constant of the soil in winter. Furthermore, a unique relationship for three acquisition dates has been found between the thermal resistance, R, of the snow pack and the backscattering power ratio. Then, the spatial distribution of the power ratio should depict the spatial distribution of R, given spatially uniform climatological conditions over the study area. Since linear relationships between SWE and R have been observed, it should be possible to estimate the SWE of shallow dry snow cover with C-band SAR data using few ground truthing data in an open area when the soil is frozen.

Determination of snow water equivalent using RADARSAT SAR data in eastern Canada

In the 1998-1999 winter, the operational feasibility of using RADARSAT SAR data to estimate the spatial distribution of snow water equivalent (SWE) in a large hydroelectric complex managed by Hydro-Quebec (La Grande River watershed) has been successfully demonstrated. This watershed is located in the subarctic climatic region in the north-west of the Quebec province. The vegetation consists of moderately dense to open Black Spruce forests, open lands, burned lands and peat bogs. In the last few years, an original approach well adapted for this region has been developed to estimate the SWE from SAR data (ERS-1, RADARSAT). This approach is based on the fact that the snow cover characteristics influence the underlying soil temperature which influences the dielectric properties of the soil and then the recorded backscattering signal. Then, a linear relationship between the backscattering ratios of a winter image and a snow-free (fall) image, and the snowpack thermal resistance (thermal insulation properties) has been established. Consequently, the algorithm infers the SWE from the estimated thermal resistance and the measured mean density of the snowpack. This algorithm has been implemented within a MapInfo application that has been named EQeau. It allows mapping of the spatial distribution of the estimated SWE at the desired level (pixel, square grid, sub-watershed). During the 1998-1999 winter, EQeau has been used successfully in a pre-operational mode using calibrated Wide beam images (W1) from RADARSAT. The algorithm has given mean estimated SWE values similar to the SWE values derived from Hydro-Quebec snow transects (relative difference between 1% and 13%). Also, the SWE increase measured from January to March 1999 is clearly detected on the maps covering almost 77 000 km 2 . The next steps will be the evaluation of the ScanSAR images and the demonstration of the economical advantages of using RADARSAT data in a hydrological forecasting system.

Potential and limitations of RADARSAT SAR data for wet snow monitoring

Based on Canadian Satellite (RADARSAT) synthetic aperture radar (SAR) images and simulations from a radar-backscattering model, the authors determined that conventional wet snow-mapping algorithms should perform optimally for a snowpack with a liquid-water content /spl ges/3%, at low incidence angle (/spl theta/=20-30/spl deg/) and for a rather smooth surface (rms height /spl les/2.1 mm).

The potential of RADARSAT data to estimate the snow water equivalent based on results from ERS-1

Data from over 40 ERS-1 images acquired over Quebec has been analysed. From those results, it is expected that RADARSAT data will permit the monitoring of the snow cover parameters of a given watershed. Both standard mode data and SCANSAR data could be used to map the extent of the wet snow cover or the frozen soil in specific areas. Calibrated standard mode data should give also some information about the spatial distribution of the SWE, although the need for a model with regionalized parameters is expected.

UTILISATION DE BOISES DE CONIFÈRES POUR ÉTALONNER DES DONNÉES RADAR (RAS)

SUMMARYFor three consecutive winters, INRS-Eau conducted the acquisition of SAR data (C and × bands) over a snow-covered basin in southern Quebec. A total of seven flights were carried out. To analyse quantatively this SAR data set, a calibration of the backscattering signal was essential. However, all calibration methods using target points, either absolute or relative, were discarded due to numerous technical difficulties during the flights. An original approach was thus developed to relatively calibrate the SAR data.Coniferous stands (Abies balsamea) have been chosen as a standard, on the assumption that the backscattering power from pine trees remains constant all winter. The methodology hinge on correcting the backscattering power profile of the pine trees with the angle of incidence. According to the scattering properties of the pine needles, the corrected profile should follow a cosine law. It has been estimated that the corrected profile confident interval is less than 1,0 dB for C band data. Howe...

Potential of Ers-1 Sar Data for Snow Cover Monitoring

The aim of this study is to develop a methodology to map the snow cover parameters (extent, state, liquid water content, snow water equivalent) from an orbiting SAR sensor (ERS-1 and eventually RADARSAT) and to use the resulting information as input to an hydrological simulation model. During the winter of 1992, ERS-1 scenes were ac uired over an agricultural region located to the EAST of Qut%ec City, in Eastern Canada. Snow cover and soil state were characterized by ground measurements over a number of sites in order to interpret quantitatively the SAR data. The pro osed methodology is based on the results of a previous study &ne at INRS-Eau. Those results suggest that a model based on the thermal properties of the snow cover could be developed to estimate the Snow Water Equivalent (SWE) with SAR data using a minimum of ground data. The preliminary analysis of the ground data indicates that a relationship between the surface temperature of the soil and the thermal resistance of the snow cover, similar to that found before, can be obtained. However, it is expected that a specific relationship could be obtained between the signal ratio and the thermal resistance of the snowpack for each soil type. Preliminary results of the SAR data analysis will be presented at the Symposium.

Processing Of Remotely Sensed Data To Derive Useful Input Data For The Hydrotel Hydrological Model

A new hydrological model, called HYDROTEL, has been developed recently [4,5]. Characterized by a modular structure and the ability to simulate spatially distributed processes, this model is able to make good use of remotely sensed (R.S.) data and digital terrain models. In practice, R.S. data are processed by IMATEL, a complementary software. In this paper, the emphasis is made on the transformation of R.S. data into useful informations for HYDROTEL, with actual or future algorithms integrated into our software package or available elsewhere. In particular, R.S. data are already, or may be, used for the estimation of watershed characteristics (topography, drainage network, river reaches, lake area, land-use and soil types) as well as for the estimation of meteorological variables (liquid or solid precipitations, characteristics of the snow cover and actual evapotranspiration).

Results from model comparisons with ERS-1 and field data for snow water equivalent estimation

An operational methodology for monitoring snow cover, particularly snow water equivalent (SWE), for a given watershed by merging information coming from RADARSAT images, snow surveys and a hydrological model is under development at INRS-Eau. A first model, which links the scattering coefficient to the physical parameters of the snow cover and the underlying soil has been developed. However, in order to understand better the various processes and their relationships, it was found necessary to apply more specific and detailed models describing each of the processes identified in that general model. A snow accumulation and melt model is being used to simulate the temperature profile both in the snow cover and in the underlying soil, as well as the density and particle diameter of the snow layers. Surface scattering from agricultural surfaces is also being modeled by one of the three usual models (small perturbations, physical optics or geometrical optics) depending on surface roughness. Finally, volume scattering from the snow cover as well as attenuation of surface scattering by snow cover are also investigated by a model. Results from those models are discussed with comparisons between ERS-1 and field data.

Effet du pourcentage et de la distribution des surfaces boisées sur les crues de fonte de neige

Following a review of the influence of deforestation on basin runoff, it is shown how a mathematical model could be used advantageously to simulate the effect of a variation in forest cover on snowmelt runoff and provide important data for basin management. Whereas most of the previous investigations were dealing with small experimental basins, simulations with the CEQUEAU square-grid system model on a > 3000 km2 basin confirm clearly the possibility to modify the snowmelt synchronization between different parts of a basin by changing the distribution and/or percentage of its forest cover. For instance, in the given example, if the forest cover had been distributed uniformly so as to occupy 50% of the total area of the basin, the maximum runoff would have been reduced by approximately one third, whereas a complete deforestation over 670 m would have led to a larger maximum runoff.