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Le système terre est en train de basculer d’un état vers un autre, entraînant avec lui la modification du cycle hydrologique et par conséquent, des stratégies de gestion des ressources en eau. Mais qu’en est-il pour les Ardennes belges, où les précipitations sont particulièrement abondantes comparées au reste du pays ? Le déclin des réserves en eau est-il à craindre pour cette région? Dans le but d’évaluer les impacts du changement climatique sur les ressources en eau de Spa et de Bru, une détection de tendance sur les composantes du bilan hydrogéologique ainsi que sur d’autres variables dérivées, comme des indices d’aridité, fût menée au moyen de tests statistiques (régressions, tests de Mann-Kendall et de Pettitt). Les données utilisées s’étendent entre 1971 et 2100. Elles proviennent d’observations ainsi que de simulations. Ces dernières sont issues du Modèle Atmosphérique Régional (MAR) et du modèle sol et zone vadose EPICgrid, forcé par MAR de 2020 à 2050 en incluant différents scénarios climatiques. Il en résulte que l’ensemble des variables va dans la même direction, à savoir vers un tarissement de la ressource sur le long terme, même si toutes les tendances ne sont pas significatives. Ce déclin peut être expliqué par la combinaison de l’intensification de l’évapotranspiration, qui induit des sécheresses de plus en plus sévères, avec les changements de précipitations, notamment au travers de leur quantité annuelle et de leur saisonnalité. La manière dont la future végétation et le relief particulier devraient influencer l’évapotranspiration a également été étudiée et montre qu’une végétation plus ouverte composée d’arbustes devrait diminuer l’évapotranspiration réelle, tandis que le relief ne montre pas d’effet global sur les rayonnements solaires interceptés en surface. Les recommandations de cette étude visent à établir une stratégie d’adaptation pour l’avenir afin de concilier les ambitions de captage avec le renouvellement de la ressource, impactée par le changement climatique comme démontré par ce mémoire. Climate change is expected to profoundly affect hydrological fluxes and therefore alter water resources management. In the Belgian Ardennes, where rainfall is abundant and water scarcity might not represent a major concern, global warming consequences must though be evaluated. In order to assess these potential effects on the Spa and the Bru springs, a trend detection was carried out using statistical tests (regressions, Mann-Kendall and Pettitt tests) on water cycle components along with other variables such as aridity indices. The data used range from 1971 to 2100 and include both observations and simulations. The Regional Atmospheric Model (MAR) and the EPICgrid soil and vadose zone model, forced by MAR from 2020 to 2050 and including different climatic scenarios, provided the simulated data. Even if trends are not all significant, they all point in the same direction, towards a long term resources decline. The depletion is due to intensified evapotranspiration leading to increasingly severe droughts and likely decreasing total annual precipitation as well as changes in their seasonality. In addition, the way in which future vegetation and the particular topography should influence evapotranspiration was also investigated. It showed that open shrublands should decrease the actual evapotranspiration while the topography shows no overall effect on the solar radiation intercepted at the surface. The recommendation of this study is to establish a strong adaptation strategy for the future in order to meet the catchment ambitions with the renewal of the resources, impacted by climate change as demonstrated by this thesis.

Changement climatique --- gestion des ressources en eau --- recharge des aquifères --- précipitations --- évapotranspiration --- aridité --- changement de végétation --- Spa --- climate change --- water resources management --- groundwater recharge --- precipitation --- evapotranspiration --- aridity index --- vegetation changes --- Spa --- Sciences du vivant > Sciences de l'environnement & écologie --- Physique, chimie, mathématiques & sciences de la terre > Sciences de la terre & géographie physique

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This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools.

Research & information: general --- bfast --- Mann-Kendall --- Sen's slope --- East Africa --- NDVI --- breakpoint analysis --- vegetation trends --- greening --- browning --- Kenya --- Uganda --- trend analysis --- land use --- land cover --- spatial heterogeneity --- mining development --- geographically weighted regression (GWR) --- Mann-Kendall --- arid and semi-arid areas --- salinization --- irrigated systems --- Niger River basin --- salinity index --- vegetation index --- TI-NDVI --- Sentinel-2 images --- high temporal resolution --- wind erosion modeling --- RWEQ --- GEE --- central Asia --- spatial-temporal variation --- land degradation --- archetypes --- self-organizing maps --- drivers --- savannah --- Nigeria --- reference levels --- REDD+ --- greenhouse gas emissions --- Xishuangbanna --- monitoring and reporting --- Normalised Difference Vegetation Index (NDVI) --- Vegetation Condition Index (VCI) --- drought --- land use-land cover --- remote sensing --- Botswana --- developing countries --- Google Earth Engine --- Landsat time series analysis --- semi-arid areas --- sustainable land management programmes --- precipitation --- breakpoints and timeseries analysis --- ecosystem structural change --- BFAST --- land degradation neutrality --- SDG --- land productivity --- Landsat --- vegetation-precipitation relationship --- soil organic carbon --- Kobresia pygmaea community --- unmanned aerial vehicle --- Gaofen satellite --- spatial distribution --- aridity index --- satellite-based aridity index --- remote sensing index --- salinized land degradation index (SDI) --- Amu Darya delta (ADD) --- satellite imagery --- gully mapping --- machine learning --- random forest --- support vector machines --- South Africa --- semi-arid environment --- shrub encroachment --- slangbos --- Earth observation --- time series --- Sentinel-1 --- Sentinel-2 --- Synthetic Aperture Radar (SAR) --- Soil Adjusted Vegetation Index (SAVI) --- Kyrgyzstan --- pastures --- MODIS --- land surface phenology --- drought impacts --- drought adaptation --- drought index --- vegetation resilience --- drought vulnerability --- standardized precipitation evapotranspiration index --- AVHRR --- bfast --- Mann-Kendall --- Sen's slope --- East Africa --- NDVI --- breakpoint analysis --- vegetation trends --- greening --- browning --- Kenya --- Uganda --- trend analysis --- land use --- land cover --- spatial heterogeneity --- mining development --- geographically weighted regression (GWR) --- Mann-Kendall --- arid and semi-arid areas --- salinization --- irrigated systems --- Niger River basin --- salinity index --- vegetation index --- TI-NDVI --- Sentinel-2 images --- high temporal resolution --- wind erosion modeling --- RWEQ --- GEE --- central Asia --- spatial-temporal variation --- land degradation --- archetypes --- self-organizing maps --- drivers --- savannah --- Nigeria --- reference levels --- REDD+ --- greenhouse gas emissions --- Xishuangbanna --- monitoring and reporting --- Normalised Difference Vegetation Index (NDVI) --- Vegetation Condition Index (VCI) --- drought --- land use-land cover --- remote sensing --- Botswana --- developing countries --- Google Earth Engine --- Landsat time series analysis --- semi-arid areas --- sustainable land management programmes --- precipitation --- breakpoints and timeseries analysis --- ecosystem structural change --- BFAST --- land degradation neutrality --- SDG --- land productivity --- Landsat --- vegetation-precipitation relationship --- soil organic carbon --- Kobresia pygmaea community --- unmanned aerial vehicle --- Gaofen satellite --- spatial distribution --- aridity index --- satellite-based aridity index --- remote sensing index --- salinized land degradation index (SDI) --- Amu Darya delta (ADD) --- satellite imagery --- gully mapping --- machine learning --- random forest --- support vector machines --- South Africa --- semi-arid environment --- shrub encroachment --- slangbos --- Earth observation --- time series --- Sentinel-1 --- Sentinel-2 --- Synthetic Aperture Radar (SAR) --- Soil Adjusted Vegetation Index (SAVI) --- Kyrgyzstan --- pastures --- MODIS --- land surface phenology --- drought impacts --- drought adaptation --- drought index --- vegetation resilience --- drought vulnerability --- standardized precipitation evapotranspiration index --- AVHRR

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• RefWorks (Direct export to RefWorks)

This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools.

bfast --- Mann–Kendall --- Sen’s slope --- East Africa --- NDVI --- breakpoint analysis --- vegetation trends --- greening --- browning --- Kenya --- Uganda --- trend analysis --- land use --- land cover --- spatial heterogeneity --- mining development --- geographically weighted regression (GWR) --- Mann-Kendall --- arid and semi-arid areas --- salinization --- irrigated systems --- Niger River basin --- salinity index --- vegetation index --- TI-NDVI --- Sentinel-2 images --- high temporal resolution --- wind erosion modeling --- RWEQ --- GEE --- central Asia --- spatial-temporal variation --- land degradation --- archetypes --- self-organizing maps --- drivers --- savannah --- Nigeria --- reference levels --- REDD+ --- greenhouse gas emissions --- Xishuangbanna --- monitoring and reporting --- Normalised Difference Vegetation Index (NDVI) --- Vegetation Condition Index (VCI) --- drought --- land use-land cover --- remote sensing --- Botswana --- developing countries --- Google Earth Engine --- Landsat time series analysis --- semi-arid areas --- sustainable land management programmes --- precipitation --- breakpoints and timeseries analysis --- ecosystem structural change --- BFAST --- land degradation neutrality --- SDG --- land productivity --- Landsat --- vegetation-precipitation relationship --- soil organic carbon --- Kobresia pygmaea community --- unmanned aerial vehicle --- Gaofen satellite --- spatial distribution --- aridity index --- satellite-based aridity index --- remote sensing index --- salinized land degradation index (SDI) --- Amu Darya delta (ADD) --- satellite imagery --- gully mapping --- machine learning --- random forest --- support vector machines --- South Africa --- semi-arid environment --- shrub encroachment --- slangbos --- Earth observation --- time series --- Sentinel-1 --- Sentinel-2 --- Synthetic Aperture Radar (SAR) --- Soil Adjusted Vegetation Index (SAVI) --- Kyrgyzstan --- pastures --- MODIS --- land surface phenology --- drought impacts --- drought adaptation --- drought index --- vegetation resilience --- drought vulnerability --- standardized precipitation evapotranspiration index --- AVHRR --- n/a --- Sen's slope

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Groundwater is an essential and vital water resource for drinking water production, agricultural irrigation, and industrial processes. Having a better understanding of physical and chemical processes in aquifers enables more reliable decisions and reduces investments concerning water management. This Special Issue on “Water Flow, Solute, and Heat Transfer, in Groundwater” of Water focuses on the recent advances in groundwater dynamics, and it includes high-quality papers that cover a wide range of issues on different aspects related to groundwater: protection from contamination, recharge, heat transfer, hydraulic parameters estimation, well hydraulics, microbial community, colloid transport, and mathematical models. This integrative volume aims to transfer knowledge to hydrologists, hydraulic engineers, and water resources planners, who are engaged in the sustainable development of groundwater resources.

artificial ground freezing method --- groundwater flow --- temperature field --- freezing wall --- effective hydraulic conductivity --- fractured media --- gravitational force --- numerical method --- rock penetration --- colloid size --- colloid transport --- underground water-sealed oil storage cavern --- seawater intrusion --- island tidal environment --- vertical water curtain system --- multi-physical field coupling --- scenario-based projections --- HYDRUS 1-D --- aridity index --- water balance --- grassland --- root water stress --- groundwater protection --- wellhead protection area (WHPA) --- uncertainty analysis --- soil moisture --- groundwater recharge --- evapotranspiration --- vadose zone --- soil hydraulic property --- climate --- NAPL --- volume averaging --- upscaling --- mass transfer --- fractured aquitard --- groundwater pollution --- microbial community’s diversity --- dehalogenation --- tribromoneopentyl alcohol --- 1-bromo-1-chloroethane --- geothermal water reservoir --- well spacing --- direct geothermal district heating system --- indirect geothermal district heating system --- multiobjective optimization --- technical and economic evaluation --- Richards’-equation --- simulation --- algebraic multigrid --- preconditioner --- residual saturation --- porous media --- permeability --- entrapped air --- two-phase flow --- ascending relief well --- groundwater --- seepage --- sand-tank --- modeling --- Dupuit formula --- Dupuit-Thiem formula --- porous and fractured media --- contaminant transport --- heat transfer --- parameters --- colloids --- microbial community --- field and laboratory studies --- mathematical modeling