Mélanie Trudel

Quick Profiler (QuiP): a friendly tool to extract roughness statistical parameters using a needle profiler

QuiP is a graphical user interface (GUI) developed in MATLAB to extract and analyze soil surface profile measurements obtained from a needle profiler in a few minutes. Surface roughness parameters can be extracted from any needle profiler with simple modifications to the tool. QuiP calculates many statistics useful in radar remote sensing while generating the profiles. Furthermore, a QuiP function can be used to join several profiles. Long profiles can therefore be created from a short profiler (e.g., 1 m) that is easier to carry and handle in the field. Extraction of profiles by QuiP is repeatable and therefore reduces user’s errors from data processing.

Using RADARSAT-2 polarimetric and ENVISAT-ASAR dual-polarization data for estimating soil moisture over agricultural fields

There are several challenges in estimating soil moisture from radar remote sensing over agricultural fields in eastern Canada. To begin, snow cover or frozen ground is observed from November to April. From April to May, agricultural activities (e.g., ploughing and sowing) change the surface roughness from week to week thereby limiting the applicability of multitemporal and multi-incidence angle approaches. Techniques using a priori information on surface roughness are difficult to apply since the type of crop often changes from year to year. Here, we present an approach using effective roughness parameters (i.e., effective root mean square height and effective correlation length) that are obtained using an empirical relationship (independent of the crop type) between the root mean square height and the correlation length. The effective parameters allow us to resolve the Integral Equation Model for observed incidence angle and backscattering coefficient in HH and VV polarizations (σ°HH and σ°VV) using a look-up table. An additional challenge is posed by the growth of vegetation that begins in May. Three-component decompositions and radar vegetation indices were used to characterize the vegetation in agricultural fields. Surface backscattering coefficients in HH and VV polarizations (σ°SURF_HH and σ°SURF_VV) were calculated using the decompositions. An improvement in estimates of soil moisture was observed with the use of surface backscattering coefficients for bare soil and sparsely vegetated fields instead of the total backscattering.

Application of Target Decomposition Theorems Over Snow-Covered Forested Areas

This paper compares two well-known polarimetric decomposition theorems, Cloude-Pottier and Freeman-Durden, applied to L- and C-band Airborne Polarimetric Synthetic Aperture Radar (AIRSAR-POLSAR) data acquired during the Cold-Land Processes Field Experiments. Three field campaigns were carried out in February 2002, March 2002, and March 2003 over a snow-covered open terrain, a sparse coniferous forest, and a dense coniferous forest. The analysis evaluates the ability of the two target decomposition methods for the identification and understanding of the main scattering mechanisms.

Impacts and Adaptation to Climate Change Using a Reservoir Management Tool to a Northern Watershed: Application to Lièvre River Watershed, Quebec, Canada

The purpose of this study is to evaluate the impact of climate change (CC) on the management of the three reservoirs in the Lièvre River watershed and to investigate adaptation strategies to CC. To accomplish this objective, a reservoir management tool was developed. The tool integrates: hydrological ensemble streamflow predictions; a stochastic optimization model; a neural network model; and a water balance model. Five climate projections from a regional climate model, under current (1961–2000) and future (2041–2070) climate scenarios, were used. Adjustments to the reservoirs operating rules were used as an adaptation strategy to limit flooding in the watershed and also in the Montreal Archipelago located downstream of the watershed. A number of constraints in the reservoirs of the Lièvre watershed are related to summer recreational activities, which would start earlier in future climate. Modifications of these constraints were simulated to take into account socio-economic impacts of climate change on reservoirs operation. Results show that greater quantities of water would have to be stored in the Lièvre River watershed in the future, to decrease the risk of flooding in the Montreal Archipelago. The reservoir located at the downstream end of the watershed would be more vulnerable and its reliability may decrease in the future. Adaptation measures reduced the inter-annual variability of the reservoir level under future climate conditions. The reservoir management tool is an example of a no-regrets strategy, as it will contribute to improve the tools currently available to manage the reservoirs of the Lièvre River watershed.

Vulnerability of Water Demand and Aquatic Habitat in the Context of Climate Change and Analysis of a No-Regrets Adaptation Strategy: Study of the Yamaska River Basin, Canada

AbstractClimate change will have a significant impact on the hydrological cycle. This paper presents the results of a pilot project for the Yamaska River in Quebec. The objective of this project is to evaluate the river’s vulnerability to low flows attributable to climate change and to analyze a no-regrets adaptation strategy at locations identified as vulnerable. The vulnerability was evaluated using statistical indicators (low flow indices) based on long-term observations at four locations in the basin. A distributed physically-based hydrological model in use in Quebec was calibrated and validated against observed streamflow data to properly represent low flows. Hydrological simulations used seven climate projections provided by the north american regional climate change assessment program (NARCCAP) s project. Also, five members of the canadian regional climate model (CRCM), nested with the coupled global climate model (CGCM) under the special report on emission scenarios (SRES) A2 emission scenario, we...

Using Remotely Sensed MODIS Snow Product for the Management of Reservoirs in a Mountainous Canadian Watershed

The objective of this study is to analyze relationships between the variability of MODIS derived snow covered area (SCA) and flood dynamics for the management of reservoirs. The study was conducted in the Nechako River Basin in British Columbia (Canada). Relationships were analyzed between daily SCA calculated from filtered MODIS images and the fraction of the flood volume that had already entered the reservoir during the snowmelt period. Results indicate a robust (R2 = 0.87) and significant (p < 0.001) correlation over a 14-years (2000-2013) period. A similar analysis was conducted for each sub-basin, producing an even more robust relationship (R2 = 0.90) for the Tahtsa Lake sub-basin. Two distinct relationships corresponding to years with either large or small spring runoff were identified by classifying years according to their maximum snow water equivalents (SWE), peak inflows and flood volume, thus improving the correlations. These empirical relationships are a simple forecasting tool that does not require any additional data other than MODIS SCA and SWE measurements. This straightforward approach can be applied to other mountainous watersheds dominated by snow accumulation and melt.