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Soil moisture is an important variable in hydrological modelling used for real time flood forecasting and water resources management. However, it is a very challenging task to measure soil moisture over a hydrological catchment using conventional in-situ sensors. Remote sensing is gaining popularity due to its large coverage suitable for soil moisture measurement at a catchment scale albeit there are still many knowledge gaps to be filled in. This thesis focuses on investigating soil moisture estimation from remote sensing satellite and land surface model (LSM) coupled with a Numerical Weather Prediction (NWP) model. A hydrological-based approach has been conducted to assess/evaluate the estimated soil moisture using event-based water balance and Probability Distributed Model (PDM). An Advance Microwave Scanning Radiometer (AMSR) and a physically- based Land Parameters Retrieval Model (LPRM) have been used to retrieve surface soil moisture over the sturdy area. The LPRM vegetation and roughness parameters have been empirically calibrated by a new approach proposed in this thesis. The relevant parameters are calibrated on the hydrological model through achieving the best correlation between the observation-based catchment storage and the retrieved surface soil moisture. The development of the land surface model coupled with the NWP model is used to estimate soil moisture at different combinations of soil layers. The optimal combination of the top two layers is found to have the best performance when compared to the catchment water storage. Regression-based mathematical models have been derived to predict the catchment storage from the estimated soil moisture based on both satellite remote sensing and the LSM-NWP model. Three schemes are proposed to examine the behaviour of soil moisture products over different seasons in order to find the appropriate formulas in different scenarios. Finally, weighted coefficients and arithmetic average data fusion methods are explored to integrate two independent soil moisture products from the AMSR-E satellite and the LSM-NWP. It has been found that the merged output is a significant improvement over their individual estimates. The implementation of the fusion technique has provided a new opportunity for information integration from satellite and NWP model. Keywords: Soil moisture, Satellite remote sensing, satellite, land surface model, NWP model, rainfall-runoff model, water balance, PDM model

Soil moisture is an integral part of the Earth's hydrological cycle. Therefore, accurate estimation of the Earth's changing soil moisture is required to achieve sustainable land and water management to augment Numerical Weather Prediction (NWP) and forecasting skill, and to develop improved flood and drought monitoring capability. Unfortunately, most of the locations in the world do not have accurate soil moisture information on a relevant spatial and temporal scale. However, after latest advances in remote sensing and mesoscale models, it is now possible to estimate soil moisture using passive microwave satellite imaging such as Soil Moisture and Ocean Salinity (SMOS) and/or mesoscale model like Weather Research and Forecasting (WRF)-NOAH Land Surface Model (LSM). L-band passive remote sensing and WRF-NOAH LSM are potentially very useful for soil moisture sensing due to its all-weather capabilities and in-depth physics oriented relationship between soil emissivity and soil moisture, applicable for a diverse land use/land cover. In commensurate with new era in soil moisture remote sensing, this thesis explores the potential of SMOS satellite and WRFNOAH LSM for soil moisture retrieval over the temperate maritime climate. Also, soil moisture deficit (SM I) is found to be an integral component for irrigation scheduling, drought and flood prediction. Hence, the main focus of this thesis is the evaluation of soil moisture datasets as a method to effectively determine the SMD. All major areas of the improvement aided by the SMOS and WRF NOAH LSM arc addressed. Several novel approaches and investigations dealing with the SMOS soil moisture retrieval using Microwave Polarisation Difference Index (M PDI) and Radiative Transfer Equations arc examined. Input data (soil roughness, land surface temperature and vegetation opacity) sensitivity of different retrieval configurations are evaluated using the various algorithms. Thus, the thesis includes ( I) initial evaluation of SMOS satellite and ECMWF downscaled soil moisture using WRF-NOAH LSM with special reference to sensitivity of growing and non growing seasons; (2) assessment of land parameter retrieval model and tau-omega rationale; (3) a modified soil moisture retrieval algorithm from SMOS brightness temperature; and (4) sensitivity and uncertainty analysis of mesoscale model based product for SMD prediction. Further through this study, SMOS soil moisture downscaling schemes using artificial intelligence techniques with MODIS LST have also been proposed to improve the spatial resolution at a catchment scale and finally, data fusion techniques for improving soil l moisture deficit are presented with the SMOS and WRF-NOAII LSM. The overall finding indicates that the SMOS and WRF-NOAH LSM using ECMWF have been proven not only to improve data quality and soil moisture deficit estimation, but also have a great potential in fostering the soil moisture research and applications. The studies presented in this thesis will enhance our understanding of the Earth's water cycle, will help improve ECMWF forecast, SMOS algorithm, NWP and will lead to better water resource management practices.

The spatial and temporal dynamics of surface, 0-0.06m, soil moisture over a 24Ha agricultural site is examined by using spatially intensive empirical point measurements. Statistical analyses of the soil moisture indicate a variable spatial structure with antecedent rainfall and time of the year having the greatest influence on the spatial field. Static and dynamic indices do not have consistent statistically significant relationships with the soil moisture fields. The spatial correlation structure has a temporal evolution, in terms of the amount of spatial variance and the organisation of the spatial soil moisture field, which is dependent on the mean moisture content. Several interpolation procedures are considered to analyse the linkage between measurement and modelling scale. Ordinary kriging provides the best goodness of fit between the computed realisation and the empirical data, but simplifies the data and a value for the uncertainty value is not calculable. Conditional simulation allows for the assessment of the uncertainty, but with a reduced accuracy between the representation and the empirical data. Comparison of the surface moisture and hydrological flux within the profile shows that the soil moisture at this depth is disassociated from the hydrological processes at depth. One-dimensional modelling of the moisture fluxes returns a close association between the modelled and measured moisture, even with inaccurate modelling of the fluxes. Thus, limiting the applicability of shallow surface soil moisture in the internal validation of current generations of hydrological models.

This research has endeavoured to characterise soil water flow vectors across a distribution of plots within two undistributed tropical rain forest catchments in Southeast Asia. The research focused on the potentially contrasting flow pathways through two different soil types: the Ferric Acrisol of the Jungle Falls catchment (Singapore), and the Haplic Alisol of the W8S5 catchment (Sabah, Malaysia). The research also sought to determine the uncertainty associated with the flow characterisation methodologies. Flow pathways were determined using two quite separate techniques within each experimental plot. A traditional Darcy-approach (i.e. use of the Darcy-Buckingham equation) was used in combination with an artificial tracer approach, to determine if sound flow predictions can be made from local measurements of hydraulic conductivity and capillary potential. Analysis of the results indicates that the flow pathways within the two soils contrasted markedly. Tracer evidence suggests that soil water movement within the Ferric Acrisol (Jungle Falls catchment) was predominantly vertical. In the Haplic Alisol (W8S5 catchment), the dominant flow pathway of the tracer was laterally though A and B1 horizons. Often rapid tracer breakthrough velocities were observed, which exceeded the measured soil saturated hydraulic conductivity by several orders of magnitude. This infers the macropores are an important flow route within both the Ferri Acrisol and the Haplic Alisol. In general, the Darcy-based approach failed to predict the velocity and dominant pattern of the tracer flows. This resulted from problems associated with the measurement of the soil parameters needed to solve the Darcy-Buckingham equation. Uncertainty analysis of the measurement and empirical techniques used to derive the Darcy-Buckingham equation parameters indicated that there is serious potential for error, particularly in the derivation of saturated hydraulic conductivity.

L’imperméabilisation des sols en ville génère des problématiques aigües au niveau du cycle de l’eau urbaine : dégradation de la qualité des eaux de ruissellement, saturation des réseaux de collecte, risque d’inondation. Parmi différentes solutions, la construction de toitures végétalisées offre de nouvelles perspectives dans la gestion de ces eaux pluviales urbaines. De telles structures jouent en effet un rôle de régulation hydrique en retardant les pics de débit lors des pluies d’orage et plus globalement en diminuant les flux envoyés vers les réseaux. L’objectif de cette thèse est de quantifier et de modéliser les performances hydriques ce type de Technosol urbain, en intégrant à la fois les variations saisonnières et le vieillissement de la toiture végétalisée. Le travail repose en premier lieu sur une caractérisation physique et hydrique des constituants des toitures, à travers une démarche pour partie originale de transposition des méthodes développées sur les sols. Ensuite, un suivi expérimental (monitoring des flux et paramètres météorologiques) de quatre modalités de toitures – dont deux équipées d’une structure innovante de stockage d’eau – a été effectué à deux échelles : le laboratoire et le bâtiment. La modélisation et la simulation numérique du transport de l’eau a enfin été effectuée à l’aide du logiciel HYDRUS-1D, avec le formalisme des équations de Richards qui décrivent le transfert en conditions insaturées et la résolution de van Genuchten-Mualem. Les recherches ont permis de caractériser, sur une base physique robuste, les écoulements au sein de ces milieux poreux complexes. Une estimation des performances de différentes modalités de toitures au cours de trois années climatiques est proposée en contexte climatique Lorrain. La démarche de modélisation permet de décrire fidèlement les transferts à l’échelle du laboratoire mais tend à sous-estimer les flux in situ. À plus long terme, ces travaux permettent d’envisager aussi bien la simulation du comportement de toitures végétalisées sous d’autres climats, que des développements technologiques basées sur des nouvelles associations de constituants. / The sealing in cities highly degrades the buffer and filter functions of soils which generates and/or emphasizes major environmental issues (e.g. urban heat island, flooding, pollution of the runoff water). Among other technologies, advances in green roof engineering provide solutions for the management of urban rainwater. Indeed, green roofs can highly contribute to water regulation service by delaying run-off peaks and decreasing water fluxes to storm water collection network. The purpose of this work is to quantify and model the hydric performances of such an urban Technosol by taking into account the seasonal variations and the aging of the green roof. Physic and hydric measurements were conducted on the green roof constituents. Then, water fluxes and meteorological parameters were monitored in four green roofs parcels – including two with an innovative water storage structure – both at the lab and the building scales. Finally, the hydrodynamics of green roofs was modeled and numerically investigated with HYDRUS-1D in the framework of the Richards equations and the van Genuchten-Mualem model that describe unsaturated flows. As a result: i) the water flows inside these complex porous media were physically characterized, ii) the hydric performances of different parcels over three years, under Lorraine climate, were evaluated, iii) the model approach reached to a good description of the hydraulic behavior at the lab-scale but tends to underestimate in situ water fluxes. Beyond that, this work can provide a robust approach to simulate water transfer in green roofs under different climates or situations and may also contribute to further technological development