Résultat de la recherche
Towards unprecedented spatiotemporal observations in hydrological systems using Uncrewed Vehicles
L'amélioration de la gestion des ressources en eau a été un grand défi et l'utilisation appropriée de l'eau est d'une grande importance pour les écosystèmes et la population humaine dans le monde entier. Le changement climatique affecte le cycle de l'eau et donc l'utilisation de l'eau et les activités humaines dans le monde entier. Il est donc de plus en plus nécessaire de mieux surveiller les ressources en eau et de comprendre les processus hydrogéologiques qui se déroulent dans les systèmes hydrologiques et hydrogéologiques. La technologie de la télédétection a été intensivement utilisée pour surveiller les masses d'eau, mais jusqu'à présent principalement par le biais de satellites et d'avions pilotés. Cependant, des limites subsistent en termes de résolution des données et de manque de données in situ dans les zones isolées et difficilement accessibles. Il est donc nécessaire de disposer de technologies plus avancées permettant d'observer l'eau à des échelles spatiales et temporelles plus fines. Dans ce contexte, les drones, avec leur technologie autonome innovante et leurs résolutions spatio-temporelles élevées, ouvrent une nouvelle ère dans l'étude des systèmes hydrogéologiques. Les véhicules aériens sans pilote (UAV) ont été utilisés dans les études hydrogéologiques en raison de leur souplesse opérationnelle, notamment leur capacité à voler à basse altitude, dans des environnements difficiles et à tout moment, à faible coût. Cette souplesse permet de surmonter les faibles résolutions spatiales et temporelles des données satellitaires et les coûts élevés de l'acquisition de données par des avions pilotés. Outre les drones, les véhicules de surface sans pilote (USV) ont également été utilisés pour l'étude des océans en raison de leur autonomie et de leur navigation à longue distance. Leurs fréquences d'échantillonnage élevées et leur capacité à échantillonner directement la surface de l'océan et pas seulement quelques mètres en dessous, les rendent plus favorables que les plateformes de mesure in situ traditionnelles telles que les bouéesou d'autres bateaux habités. L'objectif de cette thèse de doctorat est d'améliorer la compréhension des processus hydrogéologiques en utilisant cette technologie innovante des véhicules sans pilote. En combinant diverses plateformes et données de télédétection, nous avons produit de nouveaux ensembles de données pour la communauté scientifique avec des résolutions spatio-temporelles sans précédent. Nos études, qui utilisent ces données transportées par des véhicules sans pilote avec des résolutions spatio-temporelles sans précédent, prouvent l'efficacité et le potentiel de la technologie des véhicules sans pilote. Nous menons quatre études différentes liées à différents processus hydrogéologiques dans différents environnements. La première étude est une contribution technique aux techniques de cartographie de la neige à l'aide de la technologie LiDAR embarquée sur drone. La deuxième étude, qui est la toute première étude menée sur un terrain forestier escarpé à l'aide d'un LiDAR embarqué sur un drone, démontre l'effet de la structure de la canopée et du rayonnement solaire sur la formation de motifs de neige dans les pentes forestières escarpées. Nous avons également obtenu des contributions techniques précieuses pour des campagnes similaires à venir. La troisième étude porte sur la dynamique de la température de surface de la mer sur la côte californienne et prouve que Saildrone, un bateau de surface sans équipage, est capable de valider les produits satellitaires grâce à sa fréquence d'échantillonnage d'une minute. Il s'agit de la première étude comparant les produits satellitaires MODIS niveau 2 et MUR (Multi-scale Ultrahigh Resolution) niveau 4 sur la côte californienne et de la première étude évaluant la précision des niveaux de qualité MODIS niveau 2 sur la côte californienne. La dernière étude vise à cartographier la matière organique de la couche arable à haute résolution en exploitant les propriétés spectrales du sol ainsi que les analyses traditionnelles en laboratoire. ABSTRACT The improvement of water resources management has been a big challenge and the appropriate use of water is of high importance for the ecosystems and the human population globally. Climate change affects the water cycle and therefore water use and human activities around the world. There is therefore an increased need for better monitoring of the water resources and the understanding of the hydrogeological processes that take place in hydrological and hydrogeological systems. Remote sensing technology has been intensively used to monitor water bodies, but so far mainly via satellites and crewed aircraft. However, there are still limitations in terms of data resolution and lack of in situ data in isolated and difficultly accessible areas. Therefore, there is a need for more advanced technologies that can observe the water at finer spatial and temporal scales. In this context, uncrewed vehicles with their innovative autonomous technology and their high spatiotemporal resolutions open a new era in the study of hydrogeological systems. Uncrewed aerial vehicles (UAVs) have been used in hydrogeological studies due to their operational flexibilities such as their ability to fly at low altitudes, in challenging environments, and whenever the user needs them at low costs. These flexibilities overcome the low spatial and temporal resolutions of the satellite data and the high costs of crewed aircraft data acquisitions. Besides the UAVs, uncrewed surface vehicles (USVs) have also been used in ocean studies due to their autonomous and long-range navigation. Their high sampling frequencies and their ability to directly sample the ocean surface and not just a few meters underneath, make them more favorable than traditional in situ measurement platforms such as buoys or other crewed boats. The aim of this Ph.D. thesis is to improve the understanding of hydrogeological processes using this innovative technology of uncrewed vehicles. By combining various remote sensing platforms and data, we produced new datasets for the scientific community with unprecedented spatiotemporal resolutions. Our studies, using these uncrewed vehicle-borne data with their unprecedented spatiotemporal resolutions, prove the efficiency and potential of the uncrewed vehicle technology. We pursue four different studies related to different hydrogeological processes in different environments. The first study is a technical contribution to snow mapping techniques using UAVborne LiDAR technology. The second study, which is the first-ever study conducted in steep forested terrain using UAV-borne LiDAR demonstrates the effect of canopy structure and solar radiation in the formation of snow patterns within the steep forested slopes. We also extract valuable technical contributions for similar future campaigns. The third study focuses on sea surface temperature dynamics on the California Coast and proves that Saildrone, an uncrewed surface boat, is capable of validating satellite products with its one-minute sampling frequency. It is the first study to compare MODIS level-2 with Multi-scale Ultra-high Resolution (MUR) level-4 satellite products over the California Coast and the first one to assess the accuracy of MODIS level-2 quality levels over the California Coast. The last study aims at mapping topsoil organic matter at high resolution by exploiting the soil spectral properties along with traditional laboratory analysis.
Uav-Based LIDAR High-Resolution Snow Depth Mapping in the Swiss Alps: Comparing Flat and Steep Forests
Snow depth mapping in Alpine forests is of high importance for hydrogeology, ecology, tourism, and natural hazards prevention. Different remote sensing approaches have been employed for the precise mapping of snow depth within forests. However, optical sensors cannot provide below-canopy information. While Airborne Laser Scanning (ALS) systems have been used successfully in this context and allow obtaining data below canopies, the costs of acquisitions are very high, not allowing frequent data acquisitions. UAV-based Lidar technology potentially can provide the critical below-canopy information at lower cost and allows for frequent acquisitions. First attempts to employ a UAV-based Lidar system in forests have proven promising, but they are limited to flat forests and to grid-level snow depth calculations. In this study, we present UAV-based Lidar data of both flat and steep forests. Different Lidar processing workflows are analyzed and compared, and snow depth algorithms are used both at the point and the grid level. Whereas the UAV-Lidar system proved capable of mapping snow in both environments, the steep forests' data processing comes with greater challenges, especially for the 3D registration, ground classification, and point-to-point snow depth calculations.
Simulation of nitrogen dynamics in lowland polders using a new coupled modelling approach: Insights into management
A new modelling framework, the Polder Hydrology and Nitrogen modelling System (PHNS), was developed to simulate the nitrogen dynamics and processes in polder systems. PHNS is a mass-balance model that simulates water and nitrogen dynamics in soil and surface water systems through integrating the WALRUS-paddy, MUSLE, and INCA models. The model explicitly considers the interactions among surface water, groundwater, and vadose water, as well as irrigation, pumping, and fertilizer application, which are the key processes controlling the nitrogen cycle in polders. The sensitivity analysis, calibration, and validation of the developed model were conducted in a Chinese agricultural polder by using three years of measured hydro-meteorological data. The calibrated and validated results proved that the model has a good performance with an R2 of 0.748 and a Nash- Sutcliffe (NS) efficiency coefficient of 0.619 for total nitrogen (TN) concentration during the validation period. The nitrogen budget results (net export of 40.4 kg/ha/yr) revealed that the polder is a nitrogen source for downstream freshwater systems. Reducing the amount of fertilizers, retaining crop residues, and restoring aquatic plants in surface water are effective countermeasures for reducing nitrogen export from polders. This study provides an efficient modelling tool and useful insights into polder management.
Efficient multi-objective calibration and uncertainty analysis of distributed snow simulations in rugged alpine terrain
In mountainous terrain, reliable snow simulations are crucial for many applications. However, except in highly instrumented research catchments, meteorological data are usually limited, and so the interpolated spatial fields used to force snow models are uncertain. Moreover, certain potentially important processes cannot presently be simulated at catchment scales using entirely physical algorithms. It is therefore often appropriate to introduce empirical parameters into otherwise physically-based snow models. Many opportunities to incorporate snow observations into the parameter estimation process now exist, but they remain to be fully exploited. In this context, a novel approach to the calibration of an energy balance-based snow model that additionally accounts for gravitational redistribution is presented. Several important parameters were estimated using an efficient, gradient-based method with respect to two complementary observation types – Landsat 8-derived snow extent maps, and reconstructed snow water equivalent (SWE) time-series. When assessed on a per-pixel basis, observed patterns were ultimately reproduced with a mean accuracy of 85%. Spatial performance metrics compared favourably with those previously reported, whilst the temporal evolution of SWE at the stations was also satisfactorily captured. Subsequent uncertainty and data worth analyses revealed that: i) the propensity for model predictions to be erroneous was substantially reduced by calibration, ii) pre-calibration uncertainty was largely associated with two parameters which modify the longwave component of the energy balance, but this uncertainty was greatly diminished by calibration, and iii) a lower elevation SWE series was particularly valuable, despite containing comparatively few observations. Overall, our work demonstrates that contemporary snow models, observation technologies, and inverse approaches can be combined to both constrain and quantify the uncertainty associated with simulations of alpine snow dynamics.
Noble gases as tracers of surface water – groundwater interactions: insights from novel field and modelling approaches
Understanding the interactions between surface water (SW) and groundwater (GW) in alluvial aquifer systems is of critical importance for the sustainable management of water resources. Advances in realtime and continuous measurement of a range of hydrological tracers provide new opportunities for the characterization of SW-GW dynamics at unprecedented spatiotemporal resolutions. Amongst several promising tracer methods, noble gases are particularly well-adapted to the study of SW-GW interactions, and provide an integrated signal on the flow paths and travel times of water. Capitalizing on the insights offered by novel measurement technologies requires tracer interpretation methods that appropriately capture tracer transport processes in dynamic environmental conditions. However, recourse to highly-simplified tracer interpretation methods, conceptually detached from the complexity of natural systems, is still widespread. In such cases, the potentially rich information content of tracer measurements may be underutilized. This thesis aims at investigating how established and emerging noble gas tracer methods can be optimally used - and when they should be avoided - for the study of SW-GW interactions in alluvial aquifer systems. To this end, a range of novel laboratory, field, and modelling approaches are employed to systematically assess the applicability, limitations, and potential of some gas tracer methods toward informing SW-GW exchange processes. The first gas tracer method examined is the 222Rn apparent age model, which is widely used to estimate the ages of very young GW (days to weeks). High-resolution measurements of the spatial distribution of 222Rn emanation rates in an alluvial aquifer reveal significant spatial heterogeneity in 222Rn production. The explicit simulation of 222Rn in synthetic mass-transport models shows that this level of heterogeneity, combined with mixing of GW, can result in strongly biased estimates of GW age, effectively limiting the applicability of the 222Rn apparent age method to a limited range of field conditions. Although temporal changes in 222Rn concentrations may reveal insights into GW age dynamics, the information content of 222Rn measurements may be best extracted through the integration of 222Rn observations in the calibration process of physics-based flow and transport models. Indeed, the second part of this thesis is devoted to exploring how the explicit simulation of tracer concentrations and the assimilation of untransformed tracer data in highly parameterized, physicsbased models may inform model parameters and ultimately predictions of management interest. Within this framework, the joint assimilation of hydraulic and noble gas data (222Rn and helium), acquired over the course of a novel tracer injection experiment, is shown to strongly inform model parameters and reduce predictive uncertainty of several important water management quantities, such as GW age, SW-GW mixing ratios, and SW infiltration fluxes, far beyond what is achieved with “traditional” hydraulic data alone. These results build upon mounting evidence as to the benefits of explicitly simulating and assimilating diverse observation types with physically-based flow and transport models, avoiding the layer of conceptual simplification and potential bias accrued with simplified tracer interpretation models. Finally, the successful combination of novel gas injection methods, developed over the course of this project, and the assimilation of high-resolution gas tracer measurements in an explicit tracer simulation framework strongly support further developments of (noble) gas tracer methods and tracer-numerical model synergies.
Transit-time and temperature control the spatial patterns of aerobic respiration and denitrification in the riparian zone
During the flow of stream water from losing reaches through aquifer sediments, aerobic and anaerobic respiration (denitrification) can deplete dissolved oxygen and nitrate (NO3 - ), impacting water quality in the floodplain and downstream gaining reaches. Such processes, which vary in time with short and longterm changes in stream flow and temperature, need to be assessed at the stream corridor scale to fully capture their effects on net turnover, but this has rarely been done. To address this gap, we combine a fully-integrated 3D transient numerical flow model with temperature-dependent reactive transport along advective subsurface flow paths to assess aerobic and anaerobic respiration dynamics at the stream corridor scale in a predominantly losing stream. Our results suggest that given carbon availability (as an electron donor), complete NO3 - removal occurred further away from the stream after complete oxygen depletion and was relatively insensitive to variations in temperature and transit-times. Conversely, transittimes and oxygen concentrations constrained nitrate removal along short hyporheic flow paths. Even under limited carbon availability and low-temperatures, NO3 - removal fractions (RNO3) will be greater at locations further from the stream than along shorter hyporheic flow paths (RNO3=0.4 and RNO3=0.1, respectively). With increasing temperature, the relative effects of stream flow and solute concentrations on biogeochemical turnover and the redox zonation around the stream decreased. The study highlights the importance of seasonal variations of stream flow and temperature for water quality at the streamcorridor scale. It also provides an adaptive framework to assess and quantify reach-scale turnover around dynamic streams.
Cross-sphere modelling to evaluate impacts of climate and land management changes on groundwater resources
Climate change affects both water resources and agricultural production.With rising temperatures and decreasing summer precipitation, it is expected that agricultural production will be increasingly limited by drought. Where surface- or groundwater resources are available for irrigation, an increase inwaterwithdrawals for irrigation is to be expected. Therefore, quantitative approaches are required to anticipate and manage the expected conflicts related to increased water abstraction for irrigation. This project aims to investigate how agricultural production,water demand for irrigation, runoff and groundwater dynamics are affected by future climate change and howclimate change impacts combinedwith changes in agriculturalwater use affect groundwater dynamics. To answer these research questions, a comprehensive, loosely coupled model approach was developed, combining models from three disciplines: an agricultural plant growth model, a hydrological model and a hydrogeological model. The model coupling was implemented and tested for an agricultural area located in Switzerland inwhich groundwater plays a significant role in providing irrigationwater. Our suggested modelling approach can be easily adapted to other areas. The model results show that yield changes are driven by drought limitations and rising temperatures. However, an increase in yieldmay be realized with an increase in irrigation. Simulation results showthat thewater requirement for irrigation without climate protection (RCP8.5) could increase by 40% by the end of the century with an unchanged growing season and by up to 80%with varietal adaptations. With climate changemitigation (RCP2.6) the increase inwater demand for irrigationwould be limited to 7%. The increase in irrigation (+12mm) and the summer decrease in recharge rates (~20mm/month)with decreasing summer precipitation causes a lowering of groundwater levels (40 mm) in the area in the late summer and autumn. This impact may be accentuated by an intensification of irrigation and reduced by extensification.
A systematic methodology to calibrate wellbore failure models, estimate the in-situ stress tensor and evaluate wellbore cross-sectional geometry
Deep geothermal boreholes, often drilled to the crystalline basement, suffer from borehole breakouts that compromise borehole stability and/or lead to low drilling performance. These issues increase the cost of deep geothermal projects and lead to irregular cross-sectional geometries that may entangle well completion (e.g., packer isolation for zonal stimulation, cementing, etc.). Thus, the proper knowledge of rock strength, state of stress and their interactions at the closest vicinity of the borehole is key to the success of deep geothermal drilling. Typically, the magnitudes of the vertical and minimum horizontal principal stresses, 𝑆𝑣 and 𝑆ℎ𝑚𝑖𝑛, respectively, can be estimated while 𝑆𝐻𝑚𝑎𝑥 is difficult to constrain. This paper presents a systematic methodology to jointly evaluate the heterogeneous distributions of the stress tensor principal components and orientations, and the rock strength properties (e.g. cohesion, friction). Model parameters are estimated from measurements available during or shortly after drilling, i.e., breakout width, breakout extent/depth of penetration, breakout orientation and drilling induced tensile fractures. Additionally, measurements of estimated parameters or transformations of them can be considered in the calibration in a generic manner (e.g., 𝑆ℎ𝑚𝑖𝑛 interpreted from XLOT). For illustration purposes, the methodology is applied to the extensive borehole data set along the crystalline section of the borehole BS-1, in Basel (Switzerland). The methodology allows us (1) to derive plausible sets of stress and strength parameters reproducing the complex distribution of breakouts along BS-1, and (2) to unveil the paradox of having no borehole breakouts at sections with high density of natural fractures.
Sources of Surface Water in Space and Time: Identification of Delivery Processes and Geographical Sources With Hydraulic Mixing-Cell Modeling
Knowledge of the sources of surface water in riparian zones and floodplains is critical to understanding its role in runoff generation and impact on biogeochemical and ecological processes. In this study, we demonstrate the potential of integrated surface-subsurface hydrologic modeling (HydroGeoSphere) in combination with a hydraulic mixing-cell approach to decipher different sources of surface water and their mixing in space and time. We present a novel approach to processing the model data that allowed us to compare which mechanisms ultimately transferred water to the surface (delivery processes) and from where the surface water originated (geographical sources) for varying wetness states and phases of wetting or drying across 36 test locations within the riparian-stream continuum of an intensively-studied, humid-temperate, forested headwater catchment (45 ha). Consistent with current process understanding for the study site, water exfiltrating from the subsurface was simulated as the dominant source for riparian surface water and intermittent streamflow. The model further helped to specify the relevance of different subsurface stores, revealing a wetness-dependent activation of upslope source areas. Contributions of riparian overland flow and precipitation were minor during all investigated phases of wetting and drying. Moreover, the spatial variability of surface water sources proved to be smaller than expected for the heterogeneous patterns and frequencies of the surface saturation observed and simulated. Based on these findings, we discuss the value of hydraulic mixing-cell modeling to complement the planning and interpretation of field investigations and to enhance process understanding regarding the spatio-temporal sources of surface water.
Salix psammophila afforestations can cause a decline of the water table, prevent groundwater recharge and reduce effective infiltration
Afforestation can reduce desertification and soil erosion. However, the hydrologic implications of afforestation are not well investigated, especially in arid and semi-arid regions. China has the largest area of afforestation in the world, with one-third of the world's total plantation forests. How the shrubs affect evapotranspiration, soil moisture dynamics, and groundwater recharge remains unclear. We designed two pairs of lysimeters, one being 1.2 m deep and the other one 4.2 m deep. Each pair consists of one lysimeter with bare soil, while on the other one a shrub is planted. The different water table depths were implemented to understand how depth to groundwater affects soil moisture and water table dynamics under different hydrological conditions. Soil moisture, water table depth, sap flow, and rainfall were measured concurrently. Our study confirms that for the current meteorological conditions in the Ordos plateau recharge is reduced or even prohibited through the large-scale plantation Salix psammophila. Shrubs also raise the threshold of precipitation required to increase soil moisture of the surface ground. For the conditions we analyzed, a minimum of 6 mm of precipitation was required for infiltration processes to commence. In addition to the hydrological analysis, the density of root distribution is assessed outside of the lysimeters for different water table depths. The results suggest that the root-density distribution is strongly affected by water table depth. Our results have important implications for the determination of the optimal shrub-density in future plantations, as well as for the conceptualization of plant roots in upcoming numerical models.