A Self-calibrating Runoff and Streamflow Remote Sensing Model for Ungauged Basins Using Open-access Earth Observation Data

Due to increasing pressures on water resources, there is a need to monitor regional water resource availability in a spatially and temporally explicit manner. However, for many parts of the world, there is insufficient data to quantify stream flow or ground water infiltration rates. We present the results of a pixel-based water balance formulation to partition rainfall into evapotranspiration, surface water runoff and potential ground water infiltration. The method leverages remote sensing derived estimates of precipitation, evapotranspiration, soil moisture, Leaf Area Index, and a single F coefficient to distinguish between runoff and storage changes. The study produced significant correlations between the remote sensing method and field based measurements of river flow in two Vietnamese river basins. For the Ca basin, we found R2 values ranging from 0.88–0.97 and Nash–Sutcliffe efficiency (NSE) values varying between 0.44–0.88. The R2 for the Red River varied between 0.87–0.93 and NSE values between 0.61 and 0.79. Based on these findings, we conclude that the method allows for a fast and cost-effective way to map water resource availability in basins with no gauges or monitoring infrastructure, without the need for application of sophisticated hydrological models or resource-intensive data

ASCAT Surface State Flag (SSF): Extracting information on surface freeze/thaw conditions from backscatter data using an empirical threshold-analysis algorithm

Information on soil surface state is valuable for many applications such as climate studies and monitoring of permafrost regions. C-band scatterometer data indicate good potential to deliver information on surface freeze/thaw. Variation in state or amount of water contained in the soil causes significant alteration of dielectric properties of the soil which is markedly observable in scatterometer backscattered signal. A threshold-analysis method is developed to derive a set of parameters to be used in evaluating the normalized backscatter measurements through decision trees and anomaly detectionmodules for determination of freeze/thaw conditions. The model parameters are extracted from two years (2007–2008) backscatter data from ASCAT scatterometer onboard Metop satellite collocated with ECMWF ReAnalysis (ERA-Interim) soil temperature. Backscatter measurements are flagged as indicator of frozen/unfrozen surface, and snowmelt or existing water on the surface. The output product, so-called surface state flag (SSF), compares well with two modeled soil temperature data sets as well as the air temperature measurements from synoptic meteorological stations across the northern hemisphere. The SSF time series are also validated with soil temperature data available at four in situ observation sites in Siberian and Alaska regions showing the overall accuracy of about 80% to 90%

Recent glacier surface snowpack melt in Novaya Zemlya and Severnaya Zemlya derived from active and passive microwave remote sensing data

The warming rate in the Russian High Arctic (RHA) (36~158˚E, 73~82˚N) is outpacing the pan-Arctic average, and its effect on the small glaciers across this region needs further examination. The temporal variation and spatial distribution of surface melt onset date (MOD) and total melt days (TMD) throughout the Novaya Zemlya (NovZ) and Severnaya Zemlya (SevZ) archipelagoes serve as good indicators of ice mass ablation and glacier response to regional climate change in the RHA. However, due to the harsh environment, long-term glaciological observations are limited, necessitating the application of remotely sensed data to study the surface melt dynamics. The high sensitivity to liquid water and the ability to work without solar illumination and penetrate non-precipitating clouds make microwave remote sensing an ideal tool to detect melt in this region. This work extracts resolution-enhanced passive and active microwave data from different periods and retrieves a decadal melt record for NovZ and SevZ. The high correlation among passive and active data sets instills confidence in the results. The mean MOD is June 20th on SevZ and June 10th on NovZ during the period of 1992-2012. The average TMDs are 47 and 67 days on SevZ and NovZ from 1995 to 2011, respectively. NovZ had large interannual variability in the MOD, but its TMD generally increased. SevZ MOD is found to be positively correlated to local June reanalysis air temperature at 850hPa geopotential height and occurs significantly earlier (~0.73 days/year, p-value \u3c 0.01) from 1992 to 2011. SevZ also experienced a longer TMD trend (~0.75 days/year, p-value \u3c 0.05) from 1995 to 2011. Annual mean TMD on both islands are positively correlated with regional summer mean reanalysis air temperature and negatively correlated to local sea ice extent. These strong correlations might suggest that the Russian High Arctic glaciers are vulnerable to the continuously diminishing sea ice extent, the associated air temperature increase and amplifying positive ice-albedo feedback, which are all projected to continue into the future

The effect of assimilating satellite derived soil moisture in SiBCASA on simulated carbon fluxes in Boreal Eurasia

Boreal Eurasia is a region where the interaction between droughts and the carbon cycle may have significant impacts on the global carbon cycle. Yet the region is extremely data sparse with respect to meteorology, soil moisture and carbon fluxes as compared to e.g. Europe. To better constrain our vegetation model SiBCASA, we increase data usage by assimilating two streams of satellite derived soil moisture. We study if the assimilation improved SiBCASA's soil moisture and its effect on the simulated carbon fluxes. By comparing to unique in situ soil moisture observations, we show that the passive microwave soil moisture product did not improve the soil moisture simulated by SiBCASA, but the active data seem promising in some aspects. The match between SiBCASA and ASCAT soil moisture is best in the summer months over low vegetation. Nevertheless, ASCAT failed to detect the major droughts occurring between 2007 and 2013. The performance of ASCAT soil moisture seems to be particularly sensitive to ponding, rather than to biomass. The effect on the simulated carbon fluxes is large, 5-10% on annual GPP and TER, and tens of percent on local NEE, and 2% on area-integrated NEE, which is the same order of magnitude as the inter-annual variations. Consequently, this study shows that assimilation of satellite derived soil moisture has potentially large impacts, while at the same time further research is needed to understand under which conditions the satellite derived soil moisture improves the simulated soil moisture

EPS/Metop-SG Scatterometer Mission Science Plan

89 pages, figures, tablesThis Science Plan describes the heritage, background, processing and control of C-band scatterometer data and its remaining exploitation challenges in view of SCA on EPS/MetOp-SGPeer reviewe

Exploring the potential of high temporal resolution X-band SAR time series for various permafrost applications with ground truth observations in the Lena River Delta, Siberia.

Permafrost is a subsurface phenomenon that cannot be directly monitored with satellite remote sensing. A variety of indirect approaches are currently being developed which aim to measure permafrost-related processes and environmental variables. Results of these studies aid the planning of future satellite missions which will allow large-scale permafrost monitoring. This thesis contributes to this ongoing effort by assessing the potential of repeat-pass TerraSAR-X (TSX) time series for permafrost-related applications. For the first time, multi-year Synthetic Aperture Radar (SAR) data with high temporal (11 days) and spatial (3 m) resolution was analysed for a region characterized by continuous permafrost in the Siberian Arctic. Extensive in situ data was collected during three summer and winter expeditions to validate and interpret remote sensing results. Three case studies were carried out: (i) the detection of land surface changes (e.g. ground freezing and thawing, surface wetness variations, snow cover onset and melt); (ii) monitoring bedfast lake ice and ice phenology (freeze-up, melt onset, break-up); and (iii) differential SAR interferometry (DInSAR) for thaw subsidence monitoring. For the first two case studies, time series of both backscatter intensity and 11-day interferometric coherence (i.e. a measure of phase stability between two SAR images) were investigated. Backscatter intensity was generally shown to be insensitive to the land surface changes but responded to events that occurred at the time of TSX acquisition (rain, snow shower, melt/freeze crust on snow). Interferometric coherence decreased dramatically across the entire image upon snow cover onset and melt, permitting the possible use of coherence for the monitoring of these events. Backscatter intensity was found to be an excellent tool for the detection and monitoring of bedfast lake ice due in part to improved temporal resolution compared to previously used SAR systems. Ice phenology was mostly well tracked with backscatter intensity. Interferometric coherence was found to be sensitive to the lake ice grounding and to the onset of surface melt on the lakes with bedfast ice. The investigation of coherence was a useful preparative step for the following DInSAR analysis. For the third case study, coherent 11-day and 22-day interferograms were available only for one summer of the two-year TSX time series. The cumulative DInSAR displacement strongly underestimated the subsidence observed on the ground. In situ observations revealed high variability of subsidence, which likely caused errors in phase unwrapping. Conventional DInSAR processing might therefore not be suitable for the accurate representation of permafrost thaw subsidence. This study highlights the importance of field measurements for the quantification of thaw subsidence with DInSAR, which were mostly omitted in the previous studies. All in all, this thesis shows the limitations and potential of TSX time series to spatially and temporally monitor permafrost. It thus provides an important contribution to the methodological development of a long-term permafrost monitoring scheme

Contribution à la représentation des hautes latitudes dans un modèle de surface (gel des sols et diagnostics de performances)

L'importance climatique des hautes latitudes est exacerbée par le contexte actuel du réchauffement climatique, de part de leur forte sensibilité à ces changements et en raison des rétroactions globales majeures qu'elles sont susceptibles d'engendrer. La modélisation offre un moyen d'estimer ces impacts dans les temps passés, présents et futurs, tout en quantifiant les incertitudes procédant des imperfections de notre connaissance de ces environnements et de leur représentation. L'amélioration et l'évaluation de la représentation des hautes latitudes dans les modèles de climat globaux répondent donc à de forts enjeux scientifiques et sociétaux : c'est dans ce cadre précis que s'inscrit mon travail de thèse. Le gel des sols est une spécificité majeure des régions circum-arctiques, porteuse d'implications climatiques aux plans thermiques, hydrologiques et biogéochimiques. Une paramétrisation des impacts hydrologiques du gel des sols a été introduite dans le schéma hydrologique multi-couches du modèle de surfaces continentales ORCHIDEE : ses effets sur le contenu en eau des sols et le régime hydrologique des principaux bassins de l'Arctique ont été évalués par comparaison à des données de terrain, révélant la plus-value d'une telle représentation mais aussi les lacunes résiduelles de la modélisation, qui touchent à l'absence de représentation des réservoirs temporaires d'eau de surface et, sans doute, d'une paramétrisation sous-maille du gel des sols. Parallèlement, une représentation des effets thermiques du gel des sols développée pour un modèle antérieur à ORCHIDEE a été révisée et évaluée à différentes échelles spatiales par comparaison à des données observationnelles : si la représentation de l'énergie de chaleur latente augmente la température des sols soumis au gel saisonnier, un biais froid subsiste dans la modélisation, imputable à une représentation imparfaite de la neige. Une étude de sensibilité conduite sur cette variable en confirme les implications thermiques mais aussi biogéochimiques à l'échelle des régions circum-arctiques, sous-tendues par les importantes quantités de matière organique que ces régions renferment. Alors que les caractéristiques de la neige sont souvent représentées comme spatialement uniformes dans les modèles de climat globaux, la simple prise en compte du caractère particulièrement isolant de la neige de taïga engendre des changements importants dans le cycle du carbone aux hautes latitudes, et souligne les incertitudes entachant notre représentation actuelle de ces écosystèmes. Les propriétés thermiques de la neige n'en sont pas l'unique vecteur, mais une évaluation détaillée de notre modélisation sur un site de permafrost arctique (station de Bayelva, Svalbard) désigne la neige comme une source majeure des incertitudes associées à notre modélisation des hautes latitudes, au travers de représentations inadaptées de son albédo, sa rugosité de surface, son contenu variable en eau liquide pouvant accommoder de l'eau de pluie. En termes hydrologiques, l'absence de représentation spécifique des zones de montagne, des caractéristiques hydrauliques des sols à granulométrie grossière du Haut-Arctique, et des nombreuses étendues d'eau libre des régions circum-arctiques, limite notre capacité à représenter raisonnablement des principales caractéristiques de l'hydrologie de surface de ces régions. Le diagnostique de ces limites définit autant de potentiels d'amélioration de la modélisation des hautes latitudes, sources possibles de développements futurs.Focus has recently increased on high-latitude climatic processes as awareness rose about the extreme sensitivity of the Arctic to climate change and its potential for major positive climate feedbacks. Modelling offers a powerful tool to assess the climatic impact of changes in the northern high-latitude regions, as well as to quantify the range of uncertainty stemming from the limits of our knowledge and representation of these environments. My PhD project, dedicated to the improvement of a land-surface model for high-latitude regions and the evaluation of its performances, tackles therefore an issue of concern both for science and society. Soil freezing is a major physical process of boreal regions, with climatic implications. Here, a parameterization of the hydrological effects of soil freezing is developed within the multi-layer hydrological scheme of the land-surface model ORCHIDEE, and its performance is evaluated against observations at different scales, including remotely-sensed data. Taking the hydrological impact of soil freezing into account improves our representation of soil moisture and river discharges over the pan-Arctic land-surface area. However, residual inaccuracies suggest that potential for improvement lies in the representation of temporary surface water reservoirs like floodplains, surface ponding, and, possibly, the introduction of a subgrid variability in soil freezing. Hydrological modelling at high latitudes would also benefit from a specific treatment of mountainous areas and a revision of soil textural input parameters to account for abundant coarse-grained soils in the High-Arctic. Concomitantly, the thermal parameterization of soil freezing in ORCHIDEE is revised and evaluated against field data: latent heat effects yield a reduction but no suppression of a model cold bias in winter soil temperatures, part of which is imputed to the coarse representation of snow in the model. A sensitivity study performed on the insulative properties of taiga vs. tundra snow over the pan-Arctic terrestrial domain confirms the thermal implications of snow and outlines its consequences for carbon cycling at high-latitudes, calling for an appropriate representation of snow-vegetation interactions. Snow is furthermore implicated in identified flaws of the modelled surface energy balance, the components of which are precisely compared with a one-year high quality dataset collected at an Arctic permafrost site in Svalbard. Inaccuracies are diagnosed to stem from the representation of albedo, surface roughness and liquid water percolation and phase change within the snowpack. These diverseSAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF