Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas

© 2019 by the authors. High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, five passive microwave remotely sensed SM products are collected over the QTP, including those from the soil moisture active passive (SMAP), soil moisture and ocean salinity INRA-CESBIO (SMOS-IC), Fengyun-3B microwave radiation image (FY3B), and two SM products derived from the advanced microwave scanning radiometer 2 (AMSR2). The two AMSR2 products are generated by the land parameter retrieval model (LPRM) and the Japan Aerospace Exploration Agency (JAXA) algorithm, respectively. The SM products are evaluated through a two-stage data comparison method. The first stage is direct validation at the grid scale. Five SM products are compared with corresponding in situ measurements at five in situ networks, including Heihe, Naqu, Pali, Maqu, and Ngari. Another stage is indirect validation at the regional scale, where the uncertainties of the data are quantified by using a three-cornered hat (TCH) method. The results at the regional scale indicate that soil moisture is underestimated by JAXA and overestimated by LPRM, some noise is contained in temporal variations in SMOS-IC, and FY3B has relatively low absolute accuracy. The uncertainty of SMAP is the lowest among the five products over the entire QTP. In the SM map composed by five SM products with the lowest pixel-level uncertainty, 66.64% of the area is covered by SMAP (JAXA: 19.39%, FY3B: 10.83%, LPRM: 2.11%, and SMOS-IC: 1.03%). This study reveals some of the reasons for the different performances of these five SM products, mainly from the perspective of the parameterization schemes of their corresponding retrieval algorithms. Specifically, the parameterization configurations and corresponding input datasets, including the land-surface temperature, the vegetation optical depth, and the soil dielectric mixing model are analyzed and discussed. This study provides quantitative evidence to better understand the uncertainties of SM products and explain errors that originate from the retrieval algorithms

Retrieving landscape freeze/thaw state fromSoil Moisture Active Passive (SMAP) radar and radiometer measurements

Over one-third of the global land area undergoes a seasonal transition between predominantly frozen and non-frozen conditions each year, with the land surface freeze/thaw (FT) state a significant control on hydrological and biospheric processes over northern land areas and at high elevations. The NASA Soil Moisture Active Passive (SMAP) mission produced a daily landscape FT product at 3-km spatial resolution derived from ascending and descending orbits of SMAP high-resolution L-band (1.4 GHz) radar measurements. Following the failure of the SMAP radar in July 2015, coarser (36-km) footprint SMAP radiometer inputs were used to develop an alternative daily passive microwave freeze/thaw product. In this study, in situ observations are used to examine differences in the sensitivity of the 3-km radar versus the 36-km radiometer measurements to the landscape freeze/thaw state during the period of overlapping instrument operation. Assessment of the retrievals at high-latitude SMAP core validation sites showed excellent agreement with in situ flags, exceeding the 80% SMAP mission accuracy requirement. Similar performance was found for the radar and radiometer products using both air temperature and soil temperature derived FT reference flags. There was a tendency for SMAP thaw retrievals to lead the surface flags due to the influence of wet snow cover conditions on both the radar and radiometer signal. Comparison with other satellite derived FT products showed those derived from passive measurements (SMAP radiometer; Aquarius radiometer; Advanced Microwave Scanning Radiometer - 2) retrieved less frozen area than the active products (SMAP radar; Aquarius radar)

The ASCAT soil moisture product: a review of its specifications, validation results, and emerging applications

Many physical, chemical and biological processes taking place at the land surface are strongly influenced by the amount of water stored within the upper soil layers. Therefore, many scientific disciplines require soil moisture observations for developing, evaluating and improving their models. One of these disciplines is meteorology where soil moisture is important due to its control on the exchange of heat and water between the soil and the lower atmosphere. Soil moisture observations may thus help to improve the forecasts of air temperature, air humidity and precipitation. However, until recently, soil moisture observations had only been available over a limited number of regional soil moisture networks. This has hampered scientific progress as regards the characterisation of land surface processes not just in meteorology but many other scientific disciplines as well. Fortunately, in recent years, satellite soil moisture data have increasingly become available. One of the freely available global soil moisture data sets is derived from the backscatter measurements acquired by the Advanced Scatterometer (ASCAT) that is a C-band active microwave remote sensing instrument flown on board of the Meteorological Operational (METOP) satellite series. ASCAT was designed to observe wind speed and direction over the oceans and was initially not foreseen for monitoring soil moisture over land. Yet, as argued in this review paper, the characteristics of the ASCAT instrument, most importantly its wavelength (5.7 cm), its high radiometric accuracy, and its multiple-viewing capabilities make it an attractive sensor for measuring soil moisture. Moreover, given the operational status of ASCAT, and its promising long-term prospects, many geoscientific applications might benefit from using ASCAT soil moisture data. Nonetheless, the ASCAT soil moisture product is relatively complex, requiring a good understanding of its properties before it can be successfully used in applications. To provide a comprehensive overview of the major characteristics and caveats of the ASCAT soil moisture product, this paper describes the ASCAT instrument and the soil moisture processor and near-real-time distribution service implemented by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). A review of the most recent validation studies shows that the quality of ASCAT soil moisture product is – with the exception of arid environments –comparable to, and over some regions (e.g. Europe) even better than currently available soil moisture data derived from passive microwave sensors. Further, a review of applications studies shows that the use of the ASCAT soil moisture product is particularly advanced in the fields of numerical weather prediction and hydrologic modelling. But also in other application areas such as yield monitoring, epidemiologic modelling, or societal risks assessment some first progress can be noted. Considering the generally positive evaluation results, it is expected that the ASCAT soil moisture product will increasingly be used by a growing number of rather diverse land applications.The Austrian Science Fund (FWF) through the Vienna Doctoral Programme on Water Resource Systems (http://www.waterresources.at/,DK-plusW1219-N22

Estimation of Surface Moisture Content and Evapotranspiration Using Weightage Approach.

Soil moisture (MC) and evapotranspiration (ET) are considered as the most significant boundary conditions controlling most of the hydrological cycle’s processes. However, monitoring them continuously over large areas using the high temporal-resolution optical satellites is very demanding. Satellites such as the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), have a coarse spatial resolution in their images. Thus it not only impedes the acquisition of an accurate MC and ET but also represents multispectral reflections from the holistic surface features. This beside their dependence on vegetation and ground coefficient when assessing MC and ET. The study aims to enhance the spatial accuracy by weighting the MC produced from different surface cover classes within the pixel. MC for each pixel is segmented into three (3) different classes namely urban, vegetation and multi surface cover according to their respective MC weightage. Secondly, to generate an improved actual ETa map by overlaying the segmented MC with a rectified ETo. Images from AVHRR and MODIS satellites were selected in order to generate MC and ET maps. Two powerful MC algorithms were used based on land Surface Temperature (Ts), vegetation Indices (VI) and field measurements of MC; which were conducted at variable depths to examine the depth influence on MC and Ts magnitudes

Estimation of turbulent surface heat fluxes using sequences of remotely sensed land surface temperature

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 330-366).Fluxes of heat and moisture at the land-surface play a significant role in the climate system. These fluxes interact with the overlying atmosphere and influence the characteristics of the planetary boundary layer (e.g. temperature and water vapor content), ultimately influencing the presence and growth of low level clouds and precipitation. Nevertheless, there is currently no network of in situ sensors that can map these fluxes globally. Recently a number of studies have focused on the estimation of surface energy flux components based on the assimilation of land surface temperature (LST) within a variational data assimilation (VDA) framework. This study provides the theoretical basis for why sequences of LST contain the necessary information to estimate surface fluxes with minimal reliance on ancillary data and empirical parameterizations. Furthermore this study addresses one of the main drawbacks of the existing VDA models. They use the simple force-restore equation for soil heat diffusion as a physical constraint. The force-restore equation provides a simplified description of the LST dynamics. Also, its performance is highly affected by the specification of a deep ground temperature. These shortcomings cause significant errors in the diurnal dynamics of heat diffusion in the soil and ultimately the retrieval of components of surface energy balance. This study advances the VDA scheme by using the full heat diffusion equation as a constraint in lieu of the forcerestore approximation. The new VDA scheme is tested over several experimental field sites. The results show that inclusion of the heat diffusion equation decreases the phase error associated with the ground heat flux diurnal cycle, and improves surface heat flux estimation. The VDA scheme is further advanced by incorporating model uncertainty in order to account for measurement and model errors. Tests indicate that the VDA scheme with model uncertainty captures measurement errors as well as structural model errors. In order to provide coupled estimates of surface heat fluxes and vegetation dynamics, remotely sensed LST and fraction of photosynthetically active radiation are assimilated into a surface energy balance and a vegetation dynamics model. The application of the assimilation over West Africa shows that the scheme provides reliable estimates of important vegetation dynamics parameters that are required for understanding the role of plant phenology on surface energy balance and vice-versa.by Sayed Mohyeddin Bateni.Ph.D

Empirical approach to satellite snow detection

Lumipeitteellä on huomattava vaikutus säähän, ilmastoon, luontoon ja yhteiskuntaan. Pelkästään sääasemilla tehtävät lumihavainnot (lumen syvyys ja maanpinnan laatu) eivät anna kattavaa kuvaa lumen peittävyydestä tai muista lumipeitteen ominaisuuksista. Sääasemien tuottamia havaintoja voidaan täydentää satelliiteista tehtävillä havainnoilla. Geostationaariset sääsatelliitit tuottavat havaintoja tihein välein, mutta havaintoresoluutio on heikko monilla alueilla, joilla esiintyy kausittaista lunta. Polaariradoilla sääsatelliittien havaintoresoluutio on napa-alueiden läheisyydessä huomattavasti parempi, mutta silloinkaan satelliitit eivät tuota jatkuvaa havaintopeittoa. Tiheimmän havaintoresoluution tuottavat sääsatelliittiradiometrit, jotka toimivat optisilla aallonpituuksilla (näkyvä valo ja infrapuna). Lumipeitteen kaukokartoitusta satelliiteista vaikeuttavat lumipeitteen oman vaihtelun lisäksi pinnan ominaisuuksien vaihtelu (kasvillisuus, vesistöt, topografia) ja valaistusolojen vaihtelu. Epävarma ja osittain puutteellinen tieto pinnan ja kasvipeitteen ominaisuuksista vaikeuttaa luotettavan automaattisen analyyttisen lumentunnistusmenetelmän kehittämistä ja siksi empiirinen lähestymistapa saattaa olla toimivin vaihtoehto automaattista lumentunnistusmenetelmää kehitettäessä. Tässä työssä esitellään kaksi EUMETSATin osittain rahoittamassa H SAFissa kehitettyä lumituotetta ja niissä käytetyt empiiristä lähestymistapaa soveltaen kehitetyt algoritmit. Geostationaarinen MSG/SEVIRI H31 lumituote on saatavilla vuodesta 2008 alkaen ja polaarituote Metop/AVHRR H32 vuodesta 2015 alkaen. Lisäksi esitellään pintahavaintoihin perustuvat validointitulokset, jotka osoittavat tuotteiden saavuttavan määritellyt tavoitteet.Snow cover plays a significant role in the weather and climate system, ecosystems and many human activities, such as traffic. Weather station snow observations (snow depth and state of the ground) do not provide highresolution continental or global snow coverage data. The satellite observations complement in situ observations from weather stations. Geostationary weather satellites provide observations at high temporal resolution, but the spatial resolution is low, especially in polar regions. Polarorbiting weather satellites provide better spatial resolution in polar regions with limited temporal resolution. The best detection resolution is provided by optical and infra-red radiometers onboard weather satellites. Snow cover in itself is highly variable. Also, the variability of the surface properties (such as vegetation, water bodies, topography) and changing light conditions make satellite snow detection challenging. Much of this variability is in subpixel scales, and this uncertainty creates additional challenges for the development of snow detection methods. Thus, an empirical approach may be the most practical option when developing algorithms for automatic snow detection. In this work, which is a part of the EUMETSAT-funded H SAF project, two new empirically developed snow extent products for the EUMETSAT weather satellites are presented. The geostationary MSG/SEVIRI H32 snow product has been in operational production since 2008. The polar product Metop/AVHRR H32 is available since 2015. In addition, validation results based on weather station snow observations between 2015 and 2019 are presented. The results show that both products achieve the requirements set by the H SAF

Changes in extreme hydroclimate events in Interior Alaskan boreal forest watersheds

Thesis (Ph.D.) University of Alaska Fairbanks, 2014The high latitude regions of the globe are responding to climate change at unprecedented magnitudes and rates. As the climate warms, extreme hydroclimate events are likely to change more than the mean events, and it is the extreme changes that present a risk to society, the economy and the environment of the north. The subarctic boreal forest is one of the largest ecosystems in the world and is greatly understudied with respect to hydroclimate extremes. Thus, defining a baseline for changing extremes is the first step towards planning and implementing adaptation measures to reduce risk and costs associated with the changing extremes. This thesis focuses on quantitative analysis of extreme events using historical data and future model projections of changing temperature, precipitation and streamflow in the Interior forested region of boreal Alaska. Historically, shifts in the climate have resulted in declining magnitudes of peak flow for snow dominated and glacial Interior Alaskan basins. However, changes are variable and dependent upon watershed topography, permafrost conditions, and glacial extents. Therefore, adjacent basins respond in considerably different ways to the same climate drivers. For example, peak streamflow events in the adjacent Salcha and Chena River basins had different responses to changes in climate. In the higher elevation Salcha basin, maximum streamflow increased as spring temperatures increased but in the lower elevation Chena, winter precipitation was a control on increases in maximum streamflow, while both were influenced by the Pacific Decadal Oscillation. Analysis of hydrologic change must take this variability into account to understand extreme hydroclimate responses and correctly account for process shifts. To examine future changes in peak streamflow, the implementation and parameterization of hydrologic models to simulate hydroclimate extremes is required. In the northern latitudes of the world, there is a sparse observational station network that may be used for evaluation and correction of hydrologic models. This presents a limitation to science in these regions of the globe and has led to a paucity of research results and consequently, a lack of understanding of the hydrology of northern landscapes. Input of observations from remote sensing and the implementation of models that contain parameterizations specific to northern regions (i.e. permafrost) is one aim of this thesis. Remote sensing of snow cover extent, an important indicator of climate change in the north, was positively validated at snow telemetry sites across Interior Alaska. Input of the snow cover extent observations into a hydrologic model used by the Alaska Pacific River Forecast Center for streamflow flood forecasting improved discharge estimates for poorly observed basins, whereas the discharge estimates in basins with good quality river discharge observations improved little. Estimates of snow water equivalent were improved compared to station results and the adaptation of the model parameters indicated that the model is more robust, particularly during the snowmelt period when model simulations are error prone. Use of two independent hydrologic models and multiple global climate models (GCMs) and emission scenarios to simulate changes in future hydroclimate extremes indicated that large regime shifts are projected for snowmelt dominated basins of Interior Alaska. The Chena River basin, nearby Fairbanks, Alaska, is projected to be rainfall dominated by the 2080s, with smaller snowmelt peaks. Return intervals for flooding will increase by one-and-one half to double the flow volume magnitude compared to the historical return interval. Frequency of extreme streamflow events will increase five times the mean increase. These changes in extreme streamflow events necessitate further research on the implications for infrastructure, ecology and economy to constrain risk associated with the projected regime shift in boreal forested watersheds of Interior Alaska

Estimation of water resources on continental surfaces by multi-sensor microwave remote sensing

L'estimació dels recursos hídrics de les superfícies continentals a escala regional i global és fonamental per a una bona gestió dels recursos hídrics. Aquesta estimació cobreix una àmplia gamma de temes i camps, incloent-hi la caracterització dels sòls i dels recursos hídrics a l’escala de la conca, la modelització hidrològica i la predicció i la cartografia d'inundacions. En aquest context, la caracterització dels estats de la superfície continental, per a obtenir millors paràmetres d’entrada als models hidrològics, és essencial per millorar la precisió en la simulació de cabals, sequeres i inundacions. L’estimació del contingut d’aigua en el sistema, incloses les diferents masses d’aigua i l’aigua lliure en el sòl, és especialment necessària per a una descripció precisa dels processos hidrològics i, en general, del cicle de l’aigua a les superfícies continentals. Per caracteritzar millor els processos hidrològics, les intervencions antropogèniques no es poden negligir. L'home influeix en el cicle de l'aigua, principalment mitjançant el reg i la construcció de preses, fet que s’ha de quantificar correctament. L’objectiu de la tesi és la millora de l’estimació remota dels recursos hídrics, incloent-hi la quantificació dels factors antròpics, mitjançant l’ús de diversos sensors llançats recentment, aprofitant recents desenvolupaments en la tecnologia de teledetecció. Amb l'arribada de les constel·lacions Sentinel (Sentinel-1, 2, 3), disposem de millors eines per estimar els recursos hídrics, incloent-hi els impactes humans, amb una major precisió i cobertura. Aquest treball de tesi consta principalment de dues línies de recerca on s’estimen les intervencions humanes en el cicle hidrològic: la cartografia del reg (com a aplicació en humitat del sòl), i el forçament d’embassaments en simulacions hidrològiques (com a aplicació de l’altimetria). En la primera linia s’estima la humitat del sòl a partir de l’anàlisi estadística de les dades SAR de Sentinel-1. Es desenvolupen dues metodologies per obtenir la humitat del sòl amb una resolució espacial de 100 m basant-se en la interpretació de les dades de Sentinel-1 obtingudes amb la polarització VV (vertical-vertical), que es combina amb dades òptiques Sentinel-2 per a l'anàlisi dels efectes de la vegetació. Com aplicació de la humitat del sòl, es cartografia el reg en diverses condicions meteorològiques, i amb una alta resolució espacial i temporal. Es proposa una metodologia per a la cartografia del reg mitjançant dades SAR obtingudes en polaritzacions VV (vertical-vertical) i VH (vertical-horitzontal). A partir de la sèrie temporal Sentinel-1, s’analitzen diferents estadístiques i mètriques, incloent-hi el valor mitjà, la variància del senyal, la longitud de la correlació i la dimensió fractal, a partir dels quals es classifiquen els arbres irrigats, els cultius irrigats i els cultius no irrigats. En la segona línia, s’estima el nivell dels embassaments a partir de les dades d’altimetria de Sentinel-3, amb l’altímetre SAR (SRAL), basant-se en diferents algorismes per millorar la precisió. Aquest estudi presenta tres algorismes especialitzats o retrackers destinats a obtenir el nivell de la superfície dels cossos d’aigua estudiats, minimitzant la contaminació de les formes d’ona degut al sòl que els envolta. Es compara el rendiment del mètode proposat de selecció de la porció d’ona amb tres retrackers, és a dir, un retracker de llindar, el retracker del centre de gravetat (OCOG) i un retracker de base física de dos passos. S’obtenen sèries temporals del nivell de la làmina d’aigua d’embassaments situats a la conca del riu Ebre (Espanya). Com aplicació, les sèries de nivell dels embassaments obtingudes s’utilitzen per a forçar els embassaments en simulacions hidrològiques.La estimación de los recursos hídricos de las superficies continentales a escala regional y global es fundamental para una buena gestión de los recursos hídricos. Esta estimación cubre una amplia gama de temas y campos, incluyendo la caracterización de los suelos y de los recursos hídricos a escala de cuenca, la modelización hidrológica y la predicción y la cartografía de inundaciones. En este contexto, la caracterización de los estados de la superficie continental, para obtener mejores parámetros de entrada para los modelos hidrológicos, es esencial para mejorar la precisión en la simulación de caudales, sequías e inundaciones. La estimación del contenido de agua en el sistema, incluidas las diferentes masas de agua y el agua libre en el suelo, es especialmente necesaria para una descripción precisa de los procesos hidrológicos y, en general, del ciclo del agua en las superficies continentales. Una caracterización precisa de los procesos hidrológicos requiere no descuidar las intervenciones humanas. El hombre influye en el ciclo del agua, principalmente mediante el riego y la construcción de embalses, lo que se debe cuantificar correctamente. El objetivo de la tesis es la mejora de la estimación remota de los recursos hídricos, incluyendo la cuantificación de los factores humanos, mediante el uso de varios sensores lanzados recientemente, aprovechando recientes desarrollos en la tecnología de teledetección. Con la llegada de las constelaciones Sentinel (Sentinel-1, 2, 3), disponemos de mejores herramientas para estimar los recursos hídricos, incluyendo los impactos humanos, con una mayor precisión y cobertura. Este trabajo de tesis consta principalmente en dos ejes de investigación donde se estiman las intervenciones humanas en el ciclo hidrológico: la cartografía del riego (como aplicación en humedad del suelo), y el forzamiento de embalses en simulaciones hidrológicas (como aplicación de la altimetría). En relación al primer eje, se estima la humedad del suelo a partir del análisis estadístico de los datos SAR de Sentinel-1. Se desarrollan dos metodologías para obtener la humedad del suelo con una resolución espacial de 100 m basándose en la interpretación de los datos de Sentinel-1 obtenidas con la polarización VV (vertical-vertical), que se combina con datos ópticas Sentinel-2 para el análisis de los efectos de la vegetación. Como aplicación de la humedad del suelo, se cartografía el riego en diversas condiciones meteorológicas, y con una alta resolución espacial y temporal. Se propone una metodología para la cartografía del riego mediante datos SAR obtenidos en polarizaciones VV (vertical-vertical) y VH (vertical-horizontal). A partir de la serie temporal Sentinel-1, se analizan diferentes estadísticas y métricas, incluyendo el valor medio, la varianza de la señal, la longitud de la correlación y la dimensión fractal, a partir de los cuales se clasifican los árboles irrigados, los cultivos irrigados y los cultivos no irrigados. En el segundo eje, se estima el nivel de los embalses a partir de los datos de altimetría de Sentinel-3, con el altímetro SAR (SRAL), basándose en diferentes algoritmos para mejorar la precisión. Este estudio presenta tres algoritmos especializados o retrackers destinados a obtener el nivel de la superficie de los cuerpos de agua estudiados, minimizando la contaminación de las formas de onda debido al suelo que los rodea. Se compara el rendimiento del método propuesto de selección de la porción de onda con tres retrackers, es decir, un retracker de umbral, el retracker del centro de gravedad (OCOG) y un retracker de base física de dos pasos. Se obtienen series temporales del nivel de la lámina de agua de embalses situados en la cuenca del río Ebro (España). Como aplicación, las series de nivel de los embalses obtenidas se utilizan para forzar los embalses en simulaciones hidrológicas.The estimation of the water resources of the continental surfaces at a regional and global scale is fundamental for good water resources management. This estimation covers a wide range of topics and fields, including the characterisation of soils and water resources at the basin scale, hydrological modelling and flood prediction and mapping. In this context, the characterisation of the states of the continental surface, to obtain better input parameters for hydrological models, is essential to improve the precision in the simulation of flows, droughts, and floods. The estimation of the water content in the system, including the different water bodies and the free water in the soil, is especially necessary for a precise description of the hydrological processes and, in general, of the water cycle on the continental surfaces. To better characterise hydrological processes, human interventions cannot be neglected. Humans influence the water cycle, mainly through irrigation and the construction of reservoirs, which must be correctly quantified. The objective of the thesis is the improvement of the remote estimation of water resources, including the quantification of human factors, using several sensors recently launched, taking advantage of recent developments in remote sensing technology. With the arrival of the Sentinel constellations (Sentinel-1, 2, 3), we have better tools to estimate water resources, including human impacts, with greater precision and coverage. This thesis consists mainly of two parts where human interventions in the water cycle are considered: irrigation cartography (as an application of soil moisture), and the forcing of reservoirs in hydrological simulations (as an application of altimetry). Firstly, soil moisture is estimated from the statistical analysis of Sentinel-1 SAR data. Two methodologies are developed to obtain soil moisture with a spatial resolution of 100 m based on the interpretation of Sentinel-1 data collected with the VV polarization (vertical-vertical), which is combined with optical data of Sentinel-2 for the analysis of the effects of vegetation. Secondly, irrigation is mapped under various meteorological conditions, including high spatial and temporal resolution. A methodology for irrigation mapping is proposed using SAR data obtained in VV (vertical-vertical) and VH (vertical-horizontal) polarizations. With Sentinel-1 time series, different statistics and metrics are analysed, including the mean value, the variance of the signal, the correlation length and the fractal dimension, based on which the classification of irrigated trees, irrigated crops, and non-irrigated crops are derived. Finally, the level of the reservoirs is estimated from the Sentinel-3 altimetry data, with the SAR altimeter (SRAL), based on different algorithms to improve the accuracy. This study presents three specialised algorithms or retrackers designed to obtain the level of the surface of the studied inland bodies of water, minimising the contamination of the waveforms due to the surrounding soil. The performance of the selection method of the proposed wave portion is compared with three retrackers, that is, the centre of gravity retracker (OCOG) and the two-step physical-based retracker. Temporal series of the water level of reservoirs located in the basin of the Ebro River (Spain) are obtained. As an application, the level series of the reservoirs obtained are used to force the reservoirs in hydrological simulations.L'estimation et le suivi des ressources en eau des surfaces continentales aux niveaux régional et global est essentielle pour la gestion du bilan hydrique, particulièrement dans le contexte des changements climatiques et anthropiques. Ils couvrent un large éventail de thèmes et de domaines, incluant la caractérisation des ressources en eau à l'échelle du bassin, la modélisation hydrologique ainsi que la prévision et la cartographie des inondations. Dans ce contexte, la caractérisation des états de surface, en tant que paramètres d’entrée dans les modèles hydrologiques, est essentielle pour obtenir une meilleure précision de la simulation, qui est liée à la précision prévisionnelle des débits des cours d’eau et le suivi des sécheresses et des inondations. L'estimation de la teneur en eau des surfaces continentales, incluant l’état hydrique du sol et les niveaux des surfaces couvertes d’eau, est particulièrement nécessaire pour une description précise des processus hydrologiques et plus généralement du cycle de l'eau sur les surfaces continentales. Afin de mieux comprendre les processus hydrologiques, l'influence humaine (l’effet anthropique) sur le cycle de l'eau nécessite une évaluation fine. Elle est particulièrement liée à la gestion de l’irrigation et la construction de barrages. L'objectif de la thèse était d'améliorer l'estimation des ressources en eau et une meilleure caractérisation des interventions anthropiques à travers l'utilisation de nouveaux capteurs satellitaires multi-configurations du programme européen Copernicus. Avec le développement de la technologie de télédétection spatiale, et plus particulièrement avec l’arrivée des constellations Sentinel (Sentinel-1, 2, 3) à haute résolution spatiale et temporelle, il existe un meilleur outil pour estimer les états des surfaces continentales. Ce travail de thèse comprend principalement deux priorités liées à des interventions humaines dans le cycle hydrologique:la cartographie de l'irrigation en tant que action humaine liée directement à l'humidité du sol et le forçage des barrages dans un modèle de simulation de rivière en tant qu'application liée à l’estimation du niveau de l'eau libre. Un premier axe de recherche a été basé sur une analyse statistique des données SAR Sentinel-1 pour caractériser l’état hydrique du sol. Deux méthodes ont été développées pour estimer ce paramètre avec une résolution spatiale de 100 m. Elles sont basées sur des approches de détection de changement à partir des données Sentinel-1 acquises en polarisation VV (verticale-verticale), combinées aux données optiques Sentinel-2 pour corriger les effets de la végétation. L’application consistait à cartographier l'irrigation, avec des résolutions spatiale et temporelle élevées. Une méthodologie de cartographie de l'irrigation utilisant des données SAR Sentinel-1 a été proposée. Elle estbasée sur les acquisitions en polarisations VV (vertical-vertical) et VH (vertical-horizontal). A partir de la série temporelle des mesures Sentinel-1, des paramètres statistiques tel que la valeur moyenne, la variance du signal, la longueur de corrélation temporelle et la dimension fractale, sont analysées, en fonction du type de culture; cultures annuelles irriguées, arbres irrigués et cultures pluviales. Des classifications supervisées utilisant les approches Random Forest et SVM sont testées. En deuxième axe, l'estimation de la hauteur de la surface de l'eau à partir des données altimétriques de Sentinel-3 avec l’altimètre SAR (SRAL) a été réalisée à l'aide de différents algorithmes afin d'améliorer la précision sur des petites surfaces. Cette étude présente trois algorithmes spécialisés (ou retrackers) dédiées à la minimisation de la contamination des sols par les formes d’ondes permettant de récupérer les niveaux d’eau à partir de données altimétriques SAR sur des masses d’eaux intérieures. Les performances de la méthode de sélection de portion de forme d'onde proposée avec trois retrackers, à savoir, le retracker à seuil, le retracker à centre de gravité décalé (OCOG) et le retracker à base physique à 2 étapes, sont comparées. Des séries chronologiques de niveaux d'eau sont extraites pour les masses d'eau du bassin de l'Èbre (Espagne). Une application des produits altimétriques est proposée. Le produit de niveau d’eau a été utilisé comme paramètre d’entrée pour analyser l’effet tampon des barrages dans les simulations de débits fluviaux

Land Ecosystems and Hydrology

The terrestrial biosphere is an integral component of the Earth Observing System (EOS) science objectives concerning climate change, hydrologic cycle change, and changes in terrestrial productivity. The fluxes o f CO2 and other greenhouse gases from the land surface influence the global circulation models directly, and changes in land cover change the land surface biophysical properties o f energy and mass exchange. Hydrologic cycle perturbations result from terrestrially-induced climate changes, and more directly from changes in land cover acting on surface hydrologic balances. Finally, both climate and hydrology jointly control biospheric productivity, the source o f food, fuel, and fiber for humankind. The role of the land system in each of these three topics is somewhat different, so this chapter is organized into the subtopics of Land-Climate, Land-Hydrology, and Land-Vegetation interactions (Figures 5.1, 5.2, and 5.3)

Laboratory for Atmospheres 2008 Technical Highlights

The 2008 Technical Highlights describes the efforts of all members of the Laboratory for Atmospheres. Their dedication to advancing Earth Science through conducting research, developing and running models, designing instruments, managing projects, running field campaigns, and numerous other activities, is highlighted in this report. The Laboratory for Atmospheres (Code 613) is part of the Earth Sciences Division (Code 610), formerly the Earth Sun Exploration Division, under the Sciences and Exploration Directorate (Code 600) based at NASA s Goddard Space Flight Center in Greenbelt, Maryland. In line with NASA s Exploration Initiative, the Laboratory executes a comprehensive research and technology development program dedicated to advancing knowledge and understanding of the atmospheres of Earth and other planets. The research program is aimed at understanding the influence of solar variability on the Earth s climate; predicting the weather and climate of Earth; understanding the structure, dynamics, and radiative properties of precipitation, clouds, and aerosols; understanding atmospheric chemistry, especially the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and advancing our understanding of physical properties of Earth s atmosphere. The research program identifies problems and requirements for atmospheric observations via satellite missions. Laboratory scientists conceive, design, develop, and implement ultraviolet, infrared, optical, radar, laser, and lidar technology for remote sensing of the atmosphere. Laboratory members conduct field measurements for satellite data calibration and validation, and carry out numerous modeling activities. These modeling activities include climate model simulations, modeling the chemistry and transport of trace species on regional-to-global scales, cloud-resolving models, and development of next-generation Earth system models. Interdisciplinary research is carried out in collaboration with other laboratories and research groups within the Earth Sciences Division, across the Sciences and Exploration Directorate, and with partners in universities and other Government agencies. The Laboratory for Atmospheres is a vital participant in NASA s research agenda. Our Laboratory often has relatively large programs, sizable satellite missions, and observational campaigns that require the cooperative and collaborative efforts of many scientists. We ensure an appropriate balance between our scientists responsibility for these large collaborative projects and their need for an active individual research agenda. This balance allows members of the Laboratory to continuously improve their scientific credentials. Members of the Laboratory interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratory raises the public s awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. The Laboratory makes substantial efforts to attract new scientists to the various areas of atmospheric research. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of our science products. This report describes our role in NASA s mission, gives a broad description of our research, and summarizes our scientists major accomplishments during calendar year 2008. The report also contains useful information on human resources, scientific interactions, and outreach activities