Flood Hazard Mapping Using Two Digital Elevation Models: Application in a Semi-Arid Environment of Morocco

The High Atlas of Morocco is a semi-arid mountainous environment that frequently suffers from natural hazards. For example, the watersheds upstream of Marrakech city are subject to extreme floods, caused by heavy rains. These episodes are frequent and often devastating, as was the August 1995 event that caused hundreds of deaths in the Ourika Valley. The purpose of this work is to characterize the risk of flooding in this valley, by simulating the water levels and the floodplain extension. This watershed of the Ourika is characterized by a high relief, a rugged topography and a low permeability substratum. To perform this hydraulic simulation, the resolution and accuracy of Digital Elevation Models (DEM) can strongly impact the results in terms of water levels and flow velocities during floods. Two digital elevation models (DEM) were compared: a DEM ASTER with a spatial resolution of 30 m and a DEM derived from stereoscopic images of Pleiades with a resolution of 4 m. Using a hydraulic model (HEC-RAS) and the two DEM resolutions, flood areas corresponding to different return periods are simulated and compared. For the assessment of the two DEM, many areas are selected that are characterized by different types of exposure: highly frequented tourist areas near a regional road and agricultural areas on alluvial terraces, where cultivated fields and infrastructure are vulnerable. The results showed that the high-resolution Pleiades DEM allows for accurate mapping of floodplains in complex terrain, as it realistically representsthe topography and allows correct simulation of observed water levels. This study highlights the added value of a high-resolution remote sensing for flood modeling in areas where data are scarce

Mapping snow depth in open alpine terrain from stereo satellite imagery

International audienceTo date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pléiades satellite over an open alpine catchment (14.5 km2) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a −0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pléiades-derived snow depths. The median of the residuals is −0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pléiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km2). The UAV-derived snow depth map exhibits the same patterns as the Pléiades-derived snow map, with a median of −0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pléiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available

Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data

The unprecedented precision of the altimetry satellite ICESat-2 and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystems and water resources monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for three years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off elevation sources, including ATL06 and external digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) provided a poor temporal and spatial coverage, limiting its utility. However, using airborne lidar or satellite photogrammetry elevation models as snow-off elevation source yielded an accuracy of ~0.2 m (bias), a precision of ~0.5 m for low slopes and ~1.2 m for steeper areas, compared to eight reference airborne lidar snow depth maps. The snow depth derived from ICESat-2 ATL06 will help address the challenge of measuring the snow depth in unmonitored mountainous areas.</p

A snow cover climatology for the Pyrenees from MODIS snow products

International audienceThe seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations , satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively , for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snow-pack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97 % (κ = 0.85) for MOD10A1 and 96 % (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96 %, κ = 0.77; MYD10A1: 95 %, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hy-droclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50 % of the time above 1600 m between December and April. We finally analyze the snow patterns for the atypical winter 2011–2012. Snow cover duration anomalies reveal a deficient snowpack on the Span-ish side of the Pyrenees, which seems to have caused a drop in the national hydropower production

The Pyrenean glaciers (South West Europe) in 1850 and 2011: a new cross-border inventory based on aerial images and field surveys

International audienceThe Pyrenees mountain range hosts the southernmost glaciers in Europe (south of 43°N). Some of these glaciers were studied by scientists since the end of the 19th century. However, a comprehensive and accurate inventory of their present-day extent was still missing up to now. The Pyrenean glaciers were classified as “nominal glaciers” in the Randolph Glacier Inventory (RGI Release 4.0). Nominal glaciers are those which are known to exist but are recorded only collectively or approximately in the source inventories. Here we present a new inventory of the Pyrenean glaciers. We used aerial ortho-images with a ground resolution of 0.5 m from the Spanish and French National cartographic institutes acquired in summer 2010 and 2012 to outline all known glaciers in the Pyrenees. This resolution was adapted to the small size of the glacier in the area (< 1 km²). In addition, field surveys helped us to determine or modify glaciers front positions at the end of the 2011 hydrological cycle (i.e. 1st October 2011). From the 107 nominal glaciers that were listed in the RGI v4.0 only 31 glaciers are actual glaciers in 2011. In 1850, the total glaciated area in the Pyrenees was around 20 km2, in 2011 it was 3 km2 according to our latest inventory. This dataset provides a basis to study the fate of the glaciers in the Pyrenees, including the 80 Pyrenean glaciers that vanished from the previous inventories

Inducing Water Productivity from Snow Cover for Sustainable Water Management in Ibrahim River Basin, Lebanon

International audienceThe aim of this paper is to explore the effects and linkages between snow cover areas, distribution, probability and measured water discharge along east Mediterranean coastal watershed using moderate-resolution satellite images (MODIS-Terra). The Nahr Ibrahim River is a typical Lebanese watershed with an area of 326 km2 stretching between the sea and mountainous terrain to the east. The largest snow cover often exists in January-February with snow-free conditions between June and November. Image analysis enabled to analyze the temporal variability of the mean and maximum monthly areas of snow cover between 2000 and 2013. Snow cover dynamics were compared with the discharge from main springs (Afqa and Rouaiss) feeding the river and the probability of snow cover was estimated. The mean monthly snow cover, snow melting rates and springs discharge were found to be in direct relationship. In addition, the measured water discharge at the river mouth was found to be higher than the discharge of the two main feeding springs. This indicates a contribution of groundwater to the stream flow, which is again in direct connection with snow melting at the upper bordering slopes and probably from neighboring watersheds. Considering the characteristics of the mountainous rocks (i.e. Sinkholes, fissured and karstified limestone), the pedo-climatic and land cover conditions affect the hydrological regime which is directly responding to the area and temporal distribution of snow cover, which appears after two months from snowing events. This is reflected on water productivity and related disciplines (Agricultural yield, floods). This study highlights the potential of satellite snow detection over the watershed to estimate snow cover duration curve, forecast the stream flow regime and volume for better water management and flood risk preparedness

The Multiple Snow Data Assimilation System (MuSA v1.0)

Accurate knowledge of the seasonal snow distribution is vital in several domains including ecology, water resources management, and tourism. Current spaceborne sensors provide a useful but incomplete description of the snowpack. Many studies suggest that the assimilation of remotely sensed products in physically based snowpack models is a promising path forward to estimate the spatial distribution of snow water equivalent (SWE). However, to date there is no standalone, open-source, community-driven project dedicated to snow data assimilation, which makes it difficult to compare existing algorithms and fragments development efforts. Here we introduce a new data assimilation toolbox, the Multiple Snow Data Assimilation System (MuSA), to help fill this gap. MuSA was developed to fuse remotely sensed information that is available at different timescales with the energy and mass balance Flexible Snow Model (FSM2). MuSA was designed to be user-friendly and scalable. It enables assimilation of different state variables such as the snow depth, SWE, snow surface temperature, binary or fractional snow-covered area, and snow albedo and could be easily upgraded to assimilate other variables such as liquid water content or snow density in the future. MuSA allows the joint assimilation of an arbitrary number of these variables, through the generation of an ensemble of FSM2 simulations. The characteristics of the ensemble (i.e., the number of particles and their prior covariance) may be controlled by the user, and it is generated by perturbing the meteorological forcing of FSM2. The observational variables may be assimilated using different algorithms including particle filters and smoothers as well as ensemble Kalman filters and smoothers along with their iterative variants. We demonstrate the wide capabilities of MuSA through two snow data assimilation experiments. First, 5 m resolution snow depth maps derived from drone surveys are assimilated in a distributed fashion in the Izas catchment (central Pyrenees). Furthermore, we conducted a joint-assimilation experiment, fusing MODIS land surface temperature and fractional snow-covered area with FSM2 in a single-cell experiment. In light of these experiments, we discuss the pros and cons of the assimilation algorithms, including their computational cost.</p

Kalideos OSR MiPy : un observatoire pour la recherche et la démonstration des applications de la télédétection à la gestion des territoires

International audienceCes dernières années, le CESBIO a mis en place un Observatoire Spatial Régional 'OSR' : un dispositif d'observation couplant mesures de terrain et télédétection dans le sud-ouest de la France. L'OSR se base sur des acquisitions mensuelles de données satellitaires à résolution décamétrique depuis 2002 et sur des sites expérimentaux lourdement instrumentés (mesures en continu de flux d'eau et de carbone) à partir de 2004. Ce dispositif a été reconnu service d'observation par l'INSU/CNRS en 2007 et site KALIDEOS par le CNES fin 2009 : 'KALIDEOS OSR MiPy'. Le site atelier correspond à une emprise d'image SPOT, soit environ 50x50 km et couvre une grande diversité de milieux (pédologie, topographie), d'occupation et d'utilisation des sols, de pratiques et de modalités de gestion (agricole, forestière...) et de conditions climatiques (fort gradient de déficits hydriques estivaux). Pour la télédétection, ce site a servi la préparation de SMOS, et il soutient maintenant en priorité à la préparation des missions VENμS et Sentinel-2. Les aspects radar, imagerie thermique et les approches multi-capteurs se développent depuis peu. Le traitement du signal, la physique de la mesure et l'amélioration de la qualité des données constituent le premier axe de recherche. Au niveau thématique, le CESBIO a pour priorité les suivis et les modélisations des agrosystèmes de grandes cultures. L'implication récente d'autres partenaires scientifiques ou gestionnaires a permis d'initier des travaux sur d'autres aspects, comme la biodiversité, l'aménagement du territoire, le suivi de l'extension urbaine, les risques environnementaux, la santé des forêts, l'enfrichement, la diversité et la productivité des prairies. La valorisation des 10 années d'archives 2002-2011 débute et semble très pertinente pour la caractérisation en haute et en basse résolution des conséquences d'années climatiques atypiques (2003, 2011) sur les éco-agro-systèmes. L'extrapolation des résultats obtenus sur ce site atelier à toute la région Midi-Pyrénées ou à la chaine des Pyrénées est aussi initiée

Evolution of Ossoue Glacier (French Pyrenees) since the end of the Little Ice Age

International audienceLittle is known about the fluctuations of the Pyre-nean glaciers. In this study, we reconstructed the evolution of Ossoue Glacier (42 • 46 N, 0.45 km 2), which is located in the central Pyrenees, from the Little Ice Age (LIA) onwards. To do so, length, area, thickness, and mass changes in the glacier were generated from historical data sets, topo-graphical surveys, glaciological measurements (2001–2013), a ground penetrating radar (GPR) survey (2006), and stereo-scopic satellite images (2013). The glacier has receded considerably since the end of the LIA, losing 40 % of its length and 60 % of its area