Good estimates of soil hydraulic parameters and their distribution in a catchment is essential for crop and hydrological models. Measurements of soil properties by experimental methods are expensive and often time consuming, and in order to account for spatial variability of these parameters in the catchment, it becomes necessary to conduct large number of measurements. Estimation of soil parameters by inverse modelling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise for heterogeneous layered soils. Although extensive soil data is becoming more and more available at various scales in the form of digital soil maps there is still a large gap between this available information and the input parameters needed for hydrological models. Inverse modeling has been extensively used but the spatial variability of the parameters and insufficient data sets restrict its applicability at the catchment scale. Use of remote sensed soil moisture data to estimate soil properties using the inverse modeling approach received attention in recent years but yielded only an estimate of the surface soil properties. However, in multilayered and heterogeneous soil systems the estimation of soil properties of different layers yielded poor results due to uncertainties in simulating root zone soil moisture from remote sensed surface soil moisture. Surface soil properties can be estimated by inverse approach using surface soil moisture data retrieved from remote sensing data. Since soil moisture retrieved from remote sensing is representative of the top 5 cm only, inversion of models using surface soil moisture cannot give good estimates of soil properties of deeper layers. Crop variables like biomass and leaf area index are sensitive to the deeper layer soil properties. The main focus of this study is to develop a methodology of estimation of root zone soil hydraulic properties in heterogeneous soils by crop model based inversion techniques. Further the usefulness of the radar soil moisture and leaf area index in retrieving soil hydraulic properties using the develop approach is be tested in different soil and crop combinations. A brief introduction about the soil hydraulic properties and their importance in agro-hydrological model is discussed in Chapter 1. Soil water retention parameters are explained in detail in this chapter. A detailed review of the literature is presented in chapter 2 to establish the state of art on the following: (i) estimation of soil hydraulic properties, (ii) role of crop models in estimating soil hydraulic properties, (iii) retrieval of surface soil moisture using water cloud model from SAR data, (iv) retrieval of leaf area index from SAR (synthetic aperture radar) data and (v) modeling of root zone soil moisture and potential recharge. The thesis proposes a methodology for estimating the root zone soil hydraulic properties viz. field capacity, wilting point and soil thickness. To test the methodology developed in this thesis for estimating the soil hydraulic properties and their uncertainty, three synthetic experiments were conducted by inversion of STICS (Simulateur mulTIdiscplinaire pour les Cultures Standard) model for maize crop using the GLUE (Generalized Likelihood Uncertainty Estimation) approach. The estimability of soil hydraulic properties in a layer-wise heterogeneous soil was examined with several sets of likelihood combinations, using leaf area index, surface soil moisture and above ground biomass. The robustness of the approach is tested with parameter estimation (model inversion) in two different meteorological conditions. The details of the numerical experiments and the several likelihood and meteorological cases examined are given in Chapter 3. The likelihood combination of leaf area index and surface soil moisture provided consistently good estimates of soil hydraulic properties for all soil types and different meteorological cases. Relatively wet year provided better estimates of soil hydraulic properties as compared with a dry year. To validate the approach of estimating root zone soil properties and to test the applicability of the approach in several crops and soil types, field measurements were carried out in the Berambadi experimental watershed located in the Kabini river basin in south India. The profile soil measurements were made for every 10 cm upto 1 m depth. Maize, Marigold, Sunflower, Sorghum and Turmeric crops were monitored during the four year period from 2010 to 2013. Crop growth parameters viz. leaf area index, above ground biomass, yield, phenological stages and crop management activities were measured/monitored at 10 day frequency for all the five crops in the study area. The details of the field experiments performed, the data collected and the results of the model inversion using the ground measured data are given in Chapter 4. The likelihood combination of leaf area index and surface soil moisture provided consistently lower root mean square error (1.45 to 2.63 g/g) and uncertainty in the estimation of soil hydraulic properties for all soil crop and meteorological cases. The uncertainty in the estimation of soil hydraulic properties was lower in the likelihood combination of leaf area index and soil moisture. Estimability of depth of root zone showed sensitivity to the rooting depth. Estimating root zone soil properties at field plot scale using SAR data (incidence angle 24o, wave length 5.3 GHz) of RADARSAT-2 is presented in the Chapter 5. In the first step, an approach of estimating leaf area index from radar vegetation index using the parametric growth curve of leaf area index and the retrieval of soil moisture using water cloud model are given in Chapter 5. The parameters of the growth curve and the leaf area index are generated using a time series of RADARSAT-2 for two years 2010-2011 and 2011-12 for the crops (maize, marigold, sunflower, sorghum and turmeric) considered in this study. The surface soil moisture is retrieved using the water cloud model, which is calibrated using the ground measured values of leaf area index and surface soil moisture for different soils and crops in the study area. The calibration and validation of LAI and water cloud models are discussed in this Chapter. Eventually, the retrieved leaf area index and surface soil moisture from RADARSAT-2 data were used to estimate the soil hydraulic properties and their uncertainty in a similar manner as discussed in Chapter 4 for various crop and soil plots and the results are presented in Chapter 5. The mean and uncertainty in the estimation of soil hydraulic properties using inversion of remote sensing data provided results similar to the estimates from inversion of ground data. The estimates of soil hydraulic properties compared well (R2 of 0.7 to 0.80 and RMSE of 2.1 to 3.16 g/g) with the physically measured vales of the parameters. In Chapter 6, root zone soil moisture and potential recharge are modelled using the STICS model and the soil hydraulic parameters estimated using the RADARSAT-2 data. The potential recharge is highly sensitive to the water holding capacity of rooting zone. Variability in the root zone soil moisture for wet and dry years for different soil types on irrigated and non-irrigated crops were investigated. Potential recharge from different crop and soil types were compared. The uncertainty in the estimation of potential recharge due to uncertainty in the estimation of field capacity is quantified. The root zone soil moisture modeled by STICS showed good agreement with the measured root zone soil moisture in all crop and soil cases. This was tested for both dry and wet year and provides similar results. The temporal variability of root zone soil moisture was also modeled well by the STICS model; the model also predicted well the intra-soil variability of soil moisture of root zone. The results of the modeling of root zone soil moisture and potential recharge are presented in Chapter 6. At the end, in Chapter 7, the major conclusions drawn from the various chapters are summarized.

Les interactions entre les processus de surface et de sub-surface sont des composantes clés du cycle hydrologique que les modèles hydrologiques doivent représenter pour obtenir des prédictions cohérentes et précises dans un contexte de gestion durable de la ressource en eau. Les modèles hydrologiques intégrés qui décrivent de façon physique les processus et leurs interactions sont de conception récente. La plupart de ces modèles s‘appuient sur l’équation de Richards 3D pour décrire les processus d’écoulement souterrain. Cette approche peut être problématique compte tenu de contraintes importantes sur le maillage et sur la résolution numérique. Ce travail de thèse propose un modèle hydrologique intégré qui s’appuie sur approche innovante à dimension réduite pour simplifier les écoulements de surface et souterrains d'un bassin versant. Les différents compartiments du modèle sont d’abord testés indépendamment puis couplés. Les résultats montrent que l’approche proposée décrit précisément les processus hydrologiques considérés tout en améliorant de façon significative l’efficacité générale du modèle. / Interactions between surface and subsurface flow processes are key components of the hydrological water cycle. Accounting for these interactions in hydrological modelsis mandatory to provide relevant and accurate predictions for water quality and water resources management. Fully-integrated hydrological models that describe with aphysical meaning the hydrological processes and their interactions are recent. Most of these models rely upon the resolution of a 3D Richards equation to describe subsurface flow processes. This approach may become intractable because of the heavy constrains on both meshing and numerical resolution. This PhD proposes a new integrated hydrological model on the idea of dealing with dimensionally reduced flow in both the surface and sub-surface compartments of a watershed. The different compartments of the model are first tested independently and then coupled. The results show that the proposed approach allows for a proper and precise depiction ofthe hydrological processes enclosed in the model while providing significant gain incomputational efficiency.

Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. For this, a key aspect is access to a dense network of long and good-quality hydro-meteorological data. Unfortunately, such ideal data are sparse or non-existent in Central America. In addition, the existing methods for hydro-climatic studies need to be revised and/or improved to find the most suitable for the region’s climate, geography and hydro-climatic data situation. This work has the ultimate goal to support the reduction of risks associated with hydro-climatic-induced disasters in Central America. This was sought by developing ways to reduce data-related uncertainties and by improving the available methods to study and understand hydro-climatic variability processes. In terms of data-uncertainty reduction, this thesis includes the development of a high resolution air temperature dataset and a methodology to reduce uncertainties in a hydrological model at ungauged basins. The dataset was able to capture the spatial patterns with a detail not available with existing datasets. The methodology significantly reduced uncertainties in an assumed-to-be ungauged catchment. In terms of methodological improvements, this thesis includes an assessment of the most suitable combination of (available) meteorological datasets and drought indices to characterise droughts in Central America. In addition, a methodology was developed to analyse drought propagation in a tropical catchment, in an automated, objective way. Results from the assessment and the drought propagation analysis contributed with improving the understanding of drought patterns and generating processes in the region. Finally, a methodology was proposed for assessing changes in both hydrological extremes in a consistent way. This contrasts with most commonly used frameworks that study each extreme individually. The method provides important characteristics (frequency, duration and magnitude), information that can be useful for decisions within risk reduction and water management. The results presented in this thesis are a contribution, in terms of hydro-climatic data and assessment methods, for supporting risk reduction of disasters related with hydro-climatic extremes in Central America. / Översvämningar och torka inträffar ofta i Mellanamerika och orsakar stora skador på samhälle, ekonomi och miljö. En kritisk del av riskreduceringen är förståelsen av mekanismerna bakom extremhändelserna, och deras rumsliga och tidskarakteristik. En nyckelfaktor är tillgång till långa tidsserier av rumsligt täckande hydrometeorologiska data av bra kvalitet. I Mellanamerika är sådana ideala data tyvärr sällsynta eller saknas helt. Dessutom behöver befintliga metoder för hydro-klimatisk analys revideras och/eller förbättras för att identifiera de mest lämpade metoderna för regionens klimat, geografi och situationen vad gäller hydrologiska och meteorologiska data. Det övergripande syftet med denna avhandling har varit att stödja arbetet med riskreducering i Mellanamerika vid hydrologiska extremhändelser som sätts igång av extrema väderhändelser. För att bidra till detta utvecklades metoder för att minska datarelaterade osäkerheter och för att förbättra tillgängliga metoder för att studera och förstå de processer som ligger bakom variabiliteten i hydrologi och klimat. Dataosäkerheten minskades genom utveckling av ett nytt dataset för lufttemperatur med hög rumslig upplösning och en metodik för att begränsa osäkerheten i modellberäknad vattenföring i ett område där det saknas observationer. Det nya datasetet kunde fånga rumsliga mönster på en detaljnivå som hittills inte varit möjlig. Metodiken möjliggjorde en klar minskning i osäkerheten hos vattenföringen i ett avrinningsområde som behandlades som om det saknade data. Avhandlingen innehåller också en metodik för att fastlägga den mest lämpade kombinationen av tillgängliga klimatdataset och torkindex för att karakterisera torka i Mellanamerika. Därutöver utvecklades en metod för att studera torkans fortplantning i ett tropiskt avrinningsområde på ett objektivt och automatiserat sätt. Slutligen föreslås en metod för att hantera förändringar av både översvämning och torka på ett konsistent sätt  som förenklar användningen av resultaten  för en beslutsfattare. Dessa metoder bedömdes användbara för att förbättra karakteriseringen och förståelsen av extrema hydrologiska händelser i Mellanamerika. Resultaten i denna avhandling ger bidrag till förståelsen av hydrologiska och klimatextremer genom förbättrade data och analysmetoder som i förlängningen kommer att stödja riskreduceringsarbetet i Mellanamerika. / Las sequías e inundaciones son frecuentes en Centroamérica y causan grandes problemas sociales, económicos y ambientales. Un aspecto crucial en la reducción del riesgo consiste en entender los mecanismos que causan dichos eventos, y sus características espacio-temporales. Para lograr esto es necesario tener acceso a una red de datos hidro-meterológicos densa, con series largas, y de buena calidad. Desafortunadamente, este no es el caso en Centroamérica. Además, los métodos para hacer estudios hidro-climáticos requieren ser evaluados y/o mejorados para asegurar su aplicabilidad en la región (su clima, su geografía y los datos disponibles). Este trabajo tiene como meta apoyar la reducción del riesgo de desastres asociados a eventos hidro-meteorológicos extremos en Centroamérica. Esto se consigue a partir de la reducción de incertidumbres asociadas a los datos, y de la mejora de métodos para el estudio de la variabilidad hidro-climática. Para reducir la incertidumbre de los datos, este trabajo incluye el desarrollo de una base de datos de temperatura de alta resolución y el desarrollo de una metodología para reducir las incertidumbres en datos simulados de caudal. Con la nueva base de datos se logra reconocer patrones espaciales a un nivel de detalle no antes captado por otras bases de datos. Por otro lado, la metodología redujo significativamente las incertidumbres de los datos simulados de caudal. En cuanto a métodos, esta tesis incluye una evaluación para encontrar la mejor combinación de índices de sequía y base de datos para la caracterización de sequías en la región. Además, se desarrolló una metodología para analizar la propagación de la sequía en una cuenca tropical, de una manera objetiva y automatizada. Los resultados de estos dos pasos ayudaron a mejorar la comprensión de los patrones y los mecanismos de generación de las sequías. Finalmente, se incluyó un método para evaluar los cambios en los patrones de sequías e inundaciones de una manera consistente, y no de manera individual como usualmente se ha hecho. Así fue posible obtener la frecuencia, duración y magnitud en ambos extremos hidrológicos. Esta información podría constituir una herramienta  útil para el manejo del riesgo y del recurso hídrico.

Groundwater is the only fresh water resource in the semi-arid to hyper-arid Western Dead Sea catchment. Due to exploitation of groundwater the water level is decreasing in the surrounding Cretaceous aquifer system and sustainable water management is needed in order to prevent the progressive yields and contamination of those water resources. In addition, the water level of the Dead Sea decreases dramatically by at least one meter per year. This is connected to channel off the water from the Jordan River to supply intensive agriculture in the semi-arid to hyper-arid region. Hydrological and hydro-geological analysis and modelling in arid regions, like the study area, frequently suffer from data scarcity and uncertainties regarding rainfall and discharge measurements. The study showed that spatial and temporal interpolations as well as additional methods (e.g. empirical relationships and simultaneous numerical approaches) were suitable tools to overcome data shortage for modelling. Water balances are the result of a calibrated model and are the basis for sustainable management of surface and subsurface water resources. The present study investigates beside the hydrological characterisation of selected sub-catchments (wadis) also the hydro-geology of the Judean limestone aquifer and calculates a comprehensive water balance of the entire western flank of the Dead Sea by the application of two numerical open source codes: OpenGeoSys (OGS) and J2000g. The calibrated two-dimensional hydrological model J2000g provides a 33 years time series of temporal and spatial distributed groundwater recharge for the numerical groundwater flow model of OGS. The mean annual groundwater recharge of 139.9 · 10^6 m^3ˑ a^-1 is nearly completely depleted by abstractions from pumping wells close to the replenishment area in the Judea Mountains.

Driven by many factors, the water supply services (streamflow and groundwater) of many rivers in the dryland area of China have declined significantly. This aggravates the inherent severe water shortages and results in increased severity in the water use conflicts that are threatening sustainable development in the region. Innovative strategies towards more water-efficient land management are vital for enhancing water quantity to ensure water supply security. A key step in the successful development and implementation of such measures is to understand the response of hydrological processes and related services to changes in land management and climate. To this end, it was decided to investigate these processes and responses in the upper reaches of the Jing River (Jinghe), an important meso-scale watershed in the middle reaches of the Yellow River on the Loess Plateau (NW China). It has been shown that vegetation restoration efforts (planting trees and grass) are effective in controlling soil erosion on the Loess Plateau. Shifts in land cover/use lead to modifications of soil physical properties. Yet, it remains unclear if the hydraulic properties have also been improved by vegetation restoration. A better understanding of how vegetation restoration alters soil structure and related soil hydraulic properties, such as water conductivity and soil water storage capacity, is necessary. Three adjacent sites, with comparable soil texture, soil type, and topography but contrasting land cover (Black locust forest, grassland, and cropland), were investigated in a small catchment in the upstream Jinghe watershed (near Jingchuan, Gansu province). Seasonal variations of soil hydraulic properties in topsoil and subsoil were examined. Results revealed that the type of land use had a significant impact on field-saturated, near-saturated hydraulic conductivity, and soil water characteristics. Specifically, conversion from cropland to grass or forests promotes infiltration capacity as a result of increased saturated hydraulic conductivity, air capacity, and macroporosity. Moreover, conversion from cropland to forest tends to promote the formation of mesopores that increase soil water storage capacity. Tillage in cropland temporarily created well-structured topsoil, but also compacted subsoil, as indicated by low subsoil saturated hydraulic conductivity, air capacity, and plant available water capacity. An impact of land cover conversion on unsaturated hydraulic conductivities was not identified, indicating that changes in land cover do not affect functional meso- and microporosity. Changes in soil hydraulic properties and associated hydrological processes and services due to soil conservation efforts need to be considered, should soil conservation measures be implemented in water-limited regions for sustaining adequate water supply. To differentiate between the impacts of land management and climate change on streamflow, the variation of annual streamflow, precipitation, potential evapotranspiration, and climatic water balance in a small catchment of the upstream Jinghe watershed (near Pingliang, Gansu province) was examined during the period of 1955 – 2004. During this time the relative contributions of changes in land management and climate to the reduction of streamflow were estimated. A statistically significant decreasing trend of -1.14 mm y-1 in annual streamflow was detected. Furthermore, an abrupt streamflow reduction due to afforestation and construction of terraces and check-dams was identified around 1980. Remarkably, 74% of the total reduction in mean annual streamflow can be attributed to the soil conservation measures. Among various conservation measures, streamflow could be considerably reduced by afforestation and terracing (including damland creation), due to their low contribution to water yield. In contrast, slope farmland and grassland can maintain a certain level of water supply services due to higher runoff coefficients. According to a meta-analysis of the published studies on the Loess Plateau, the impact of changes in land management on annual streamflow appears to diminish with increasing catchment size while the impact of climate change appears uniform across space. This means that there is a dependency between the catchment size and the response of hydrological processes to environmental change. At least at the local scale, it appears that well-considered land management may help to ensure the water supply services. Due to limited surface water availability, groundwater is an essential water source for supporting ecosystem and socio-economic development in the dryland region. However, the groundwater process is susceptible and vulnerable to changes in climate and landscape (i.e., land cover and form) that in turn can result in profound adverse consequences on water supply services in water-limited regions. In addition, an improved understanding of the response of groundwater related processes to natural and artificial disturbances is likely to ensure more secure and more sustainable governance and management of such regions, as well as better options for adapting to climate change. Yet, this topic has seldom been researched, especially in areas that have already experienced large-scale alteration in landscape and are located in dryland regions, such as the Loess Plateau. Therefore, an investigation of the baseflow variation along the landscape change was conducted. The average annual baseflow has significantly decreased at catchment scale during the period of 1962 – 2002 without any obvious significant change in climate. At decadal scale, the reduction accounts for approximately 9% in the 1970s, 48% in the 1980s, and 92% in the 1990s, while the baseflow index declines averaging 5%, 16% and 67%, respectively. All of the monthly baseflow levels dropped at varying rates except in January, among which July was the most severe in terms of both magnitude (-4.17) and slope (-0.09 mm y-1). In perspective of landscape change, landform change (terrace and check-dam) tends to reduce baseflow by reallocation of surface fluxes and retention for crop growth causing limited deep drainage in other areas. Land cover change (i.e., afforestation) reduced the baseflow to a larger extent by enhanced evapotranspiration and thus hampered deep drainage as suggested by the soil moisture measurement underneath. The study indicates that knowledge about baseflow formation on catchment scale needs further improvement. Integrated soil conservation and water management for optimizing landscape structure and function in order to balance soil (erosion) and water (supply) related hydrological ecosystem services is vital. The governing processes to the changes of water-supply-services-related hydrological process (e.g., streamflow) are assumed to be different across space. To this end, the factors controlling streamflow were investigated on both a small and large scale. Streamflow in small catchments was found to be mainly controlled by precipitation and land cover type. On a larger scale, evaporative demand was found to be another additional major driving force. Hydrological modeling is a frequently used tool for the assessment of impacts of land use and climate change on water balance and water fluxes. However, application of the Soil and Water Assessment Tool (SWAT) model in the upstream Jinghe watershed was unsuccessful due to difficulties in calibration. The inability of the SWAT model to take the influence of terraces on steep slopes into consideration and the method how to calculate lateral flow were the main reasons for unsatisfactory calibration, at least for the current version of SWAT used in this study. Alternatively, Budyko’s frameworks were applied to predict the annual and long-term streamflow. However, the effect of changes in land management (e.g., afforestation) on streamflow could not be assessed due to a lack of vegetation factors. Therefore, an empirical analysis tool was derived based on an existing relationship for estimation. This method was found to be the most effective in reproducing the annual and long-term streamflow. The incorporation of temporal changes in land cover and form in the approach enables the estimation of the possible impact of soil conservation measures (e.g., afforestation or terracing). The importance of adaptive land management strategies for mitigating water shortage and securing the water supply services on the Loess Plateau was highlighted. A cross-sectoral view of the multiple services offered by managed ecosystems at different spatial scales under changing environments needs to be integrated to improve adaptive land management policy. In a water limited environment, such as the Loess Plateau, multiple ecosystem services including hydrological services need to be balanced with minimum trade-offs. This can only be achieved when management is based on a holistic understanding of the interdependencies among various ecosystem services and how they might change under alternative land management.

Groundwater is the only fresh water resource in the semi-arid to hyper-arid Western Dead Sea catchment. Due to exploitation of groundwater the water level is decreasing in the surrounding Cretaceous aquifer system and sustainable water management is needed in order to prevent the progressive yields and contamination of those water resources. In addition, the water level of the Dead Sea decreases dramatically by at least one meter per year. This is connected to channel off the water from the Jordan River to supply intensive agriculture in the semi-arid to hyper-arid region. Hydrological and hydro-geological analysis and modelling in arid regions, like the study area, frequently suffer from data scarcity and uncertainties regarding rainfall and discharge measurements. The study showed that spatial and temporal interpolations as well as additional methods (e.g. empirical relationships and simultaneous numerical approaches) were suitable tools to overcome data shortage for modelling. Water balances are the result of a calibrated model and are the basis for sustainable management of surface and subsurface water resources. The present study investigates beside the hydrological characterisation of selected sub-catchments (wadis) also the hydro-geology of the Judean limestone aquifer and calculates a comprehensive water balance of the entire western flank of the Dead Sea by the application of two numerical open source codes: OpenGeoSys (OGS) and J2000g. The calibrated two-dimensional hydrological model J2000g provides a 33 years time series of temporal and spatial distributed groundwater recharge for the numerical groundwater flow model of OGS. The mean annual groundwater recharge of 139.9 · 10^6 m^3ˑ a^-1 is nearly completely depleted by abstractions from pumping wells close to the replenishment area in the Judea Mountains.:Acknowledgements Abstract Nomenclature Content List of Figures List of Tables 1 Introduction 1.1 Motivation 1.2 State of the Field 1.3 General research questions 1.4 Challenges 1.5 Structure of the Thesis 2 Theory and Methods 2.1 Data analysis 2.2 Governing equations 2.2.1 Surface Flow - Hydrological Model: J2000g 2.2.2 Subsurface Flow - Groundwater Flow Model: OpenGeoSys 2.3 Groundwater recharge 3 Study area 3.1 Study site selection 3.2 Geography 3.2.1 Climate 3.2.2 Soils 3.2.3 Vegetation 3.2.4 Land use 3.3 Hydrology 3.3.1 Wadis 3.3.2 Flashfloods 3.3.3 Dead Sea 3.4 Geology 3.5 Hydro-geology 3.5.1 Springs 3.5.2 Well fields 4 Hydrological Model 4.1 Conceptual Model 4.2 Hydrological Model J2000g 4.2.1 Data base 4.2.2 Simulation results from J2000g 5 Structural geological model 5.1 Stratigraphy 5.2 Database 5.3 Workflow 6 Numerical groundwater flow model 6.1 Work flow of 2D and 3D meshing 6.2 Parametrisation 6.3 Boundary conditions 6.4 Model Set-up 6.5 Calibration of Steady-State model 6.6 Transient Model 6.6.1 Model assumptions 6.6.2 Challenges 6.6.3 Preliminary results 7 Conclusions and Outlook 7.1 Important results from the hydrological model 7.2 Important results from the geological structural model 7.3 Important results from the hydro-geological model 7.4 Deficiencies 7.5 Outlook References 8 Enclosed Publications

River streamflow forecasting is traditionally based on real-time measurements of rainfall over catchments and discharge at the outlet and upstream. These data are processed in mathematical models of varying complexity and allow to obtain accurate predictions for short times. In order to extend the forecast horizon to a few days - to be able to issue early warning - it is necessary to take into account the weather forecasts. However, the latter display the property of sensitivity to initial conditions, and for appropriate risk management, forecasts should therefore be considered in probabilistic terms. Currently, ensemble predictions are made using a numerical weather prediction model with perturbed initial conditions and allow to assess uncertainty. <p><p>The research began by analyzing the meteorological predictions at the medium-range (up to 10-15 days) and their use in hydrological forecasting. Precipitation from the ensemble prediction system of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used. A semi-distributed hydrological model was used to transform these precipitation forecasts into ensemble streamflow predictions. The performance of these forecasts was analyzed in probabilistic terms. A simple decision model also allowed to compare the relative economic value of hydrological ensemble predictions and some deterministic alternatives. <p><p>Numerical weather prediction models are imperfect. The ensemble forecasts are therefore affected by errors implying the presence of biases and the unreliability of probabilities derived from the ensembles. By comparing the results of these predictions to the corresponding observed data, a statistical model for the correction of forecasts, known as post-processing, has been adapted and shown to improve the performance of probabilistic forecasts of precipitation. This approach is based on retrospective forecasts made by the ECMWF for the past twenty years, providing a sufficient statistical sample. <p><p>Besides the errors related to meteorological forcing, hydrological forecasts also display errors related to initial conditions and to modeling errors (errors in the structure of the hydrological model and in the parameter values). The last stage of the research was therefore to investigate, using simple models, the impact of these different sources of error on the quality of hydrological predictions and to explore the possibility of using hydrological reforecasts for post-processing, themselves based on retrospective precipitation forecasts. <p>/<p>La prévision des débits des rivières se fait traditionnellement sur la base de mesures en temps réel des précipitations sur les bassins-versant et des débits à l'exutoire et en amont. Ces données sont traitées dans des modèles mathématiques de complexité variée et permettent d'obtenir des prévisions précises pour des temps courts. Pour prolonger l'horizon de prévision à quelques jours – afin d'être en mesure d'émettre des alertes précoces – il est nécessaire de prendre en compte les prévisions météorologiques. Cependant celles-ci présentent par nature une dynamique sensible aux erreurs sur les conditions initiales et, par conséquent, pour une gestion appropriée des risques, il faut considérer les prévisions en termes probabilistes. Actuellement, les prévisions d'ensemble sont effectuées à l'aide d'un modèle numérique de prévision du temps avec des conditions initiales perturbées et permettent d'évaluer l'incertitude.<p><p>La recherche a commencé par l'analyse des prévisions météorologiques à moyen-terme (10-15 jours) et leur utilisation pour des prévisions hydrologiques. Les précipitations issues du système de prévisions d'ensemble du Centre Européen pour les Prévisions Météorologiques à Moyen-Terme ont été utilisées. Un modèle hydrologique semi-distribué a permis de traduire ces prévisions de précipitations en prévisions d'ensemble de débits. Les performances de ces prévisions ont été analysées en termes probabilistes. Un modèle de décision simple a également permis de comparer la valeur économique relative des prévisions hydrologiques d'ensemble et d'alternatives déterministes.<p><p>Les modèles numériques de prévision du temps sont imparfaits. Les prévisions d'ensemble sont donc entachées d'erreurs impliquant la présence de biais et un manque de fiabilité des probabilités déduites des ensembles. En comparant les résultats de ces prévisions aux données observées correspondantes, un modèle statistique pour la correction des prévisions, connue sous le nom de post-processing, a été adapté et a permis d'améliorer les performances des prévisions probabilistes des précipitations. Cette approche se base sur des prévisions rétrospectives effectuées par le Centre Européen sur les vingt dernières années, fournissant un échantillon statistique suffisant.<p><p>A côté des erreurs liées au forçage météorologique, les prévisions hydrologiques sont également entachées d'erreurs liées aux conditions initiales et aux erreurs de modélisation (structure du modèle hydrologique et valeur des paramètres). La dernière étape de la recherche a donc consisté à étudier, à l'aide de modèles simples, l'impact de ces différentes sources d'erreur sur la qualité des prévisions hydrologiques et à explorer la possibilité d'utiliser des prévisions hydrologiques rétrospectives pour le post-processing, elles-même basées sur les prévisions rétrospectives des précipitations. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Tesis por compendio / [ES] El cambio climático indudablemente afectará los eventos de nieve ya que se espera que la temperatura y la precipitación cambien en el futuro. Las montañas españolas se ven especialmente afectadas por esta situación, ya que el almacenamiento de nieve se concentra en periodos muy concretos del año hidrológico y juega un papel muy importante en la gestión de los recursos hídricos. En este estudio se realiza en primer lugar un análisis del comportamiento de los fenómenos complejos relacionados con la nieve en las cuatro principales regiones montañosas de España en los próximos 50 años. El modelo hidrológico ASTER se aplica utilizando como insumo básico datos de temperatura y precipitación, estimados bajo un escenario de cambio climático. Los resultados muestran diferentes cambios en los caudales máximos y promedio esperados, dependiendo de la muy diferente magnitud y signo de los cambios en la precipitación. Puede producirse un aumento de los episodios de inundación como consecuencia de una compleja relación entre los cambios en las precipitaciones y un aumento de las intensidades máximas de deshielo que oscilan entre el 2,1% en los Pirineos y el 7,4% en la Cordillera Cantábrica. Sin embargo, los patrones comunes se muestran en una menor duración de las reservas de masa de nieve, que se espera que ocurra 45 días antes para la Cordillera Cantábrica, y alrededor de 30 días para el resto de las regiones montañosas estudiadas. Los cambios observados también conducen a una disminución preocupante del efecto regulador de los fenómenos relacionados con la nieve en los ríos españoles, con una disminución de la acumulación media de nieve que oscila entre un 28% para Pirineos y Sierra Nevada y un 42% para el Sistema Central y la Cordillera Cantábrica. Se espera una disminución del caudal medio, que fluctúe desde el 2,4% en los Pirineos hasta el 7,3% en la Cordillera Cantábrica, aumentando únicamente en el Sistema Central un 4,0%, siendo necesario desarrollar nuevas medidas de adaptación al cambio climático. Por otro lado, con el fin de lograr una mejor estimación del Equivalente de agua de nieve (SWE) utilizando una red meteorológica y de profundidad de nieve (SD) económica y extensa; y que mejore la calibración del modelo hidrológico ASTER, se proporcionan nuevos modelos de regresión de densidad de nieve (SDEN). A partir del gran banco de datos de densidad de nieve (SDEN) existente para los Pirineos españoles, siendo una de las zonas más importantes y mejor monitorizadas del mundo, se evalúan modelos de regresión lineal simple y múltiple que relacionan SDEN con la intra-dependencia del tiempo anual y otros factores como la precipitación acumulada estacional, las temperaturas promedio de 7 días, la profundidad de la nieve (SD) y la elevación. Los resultados mostraron tasas de densificación similares sin mostrar un patrón espacial. La tasa de densificación para el conjunto de muestras manuales se fijó en 1,2 x 10-3 kg/L/día, muy similar al conjunto de medidas automáticas. Los resultados aumentan el conocimiento sobre SDEN en los Pirineos, aunque hay que tener en cuenta la alta variabilidad espacial encontrada. Finalmente, se estudian los efectos que el cambio climático puede tener en las inundaciones para un caso de estudio de una cuenca nival de la Cordillera Cantábrica. Usando diferentes modelos climáticos, considerando un escenario de emisiones de gases de efecto invernadero comparativamente altas (RCP8.5), con datos diarios de temperatura y precipitación entre los años 2007-2070, y comparando los resultados en términos relativos, se estiman el caudal y la variación del riesgo de inundación debido al cambio climático. En el caso concreto de Reinosa, el modelo climático MRI-CGCM3 muestra que el cambio climático provocará un aumento significativo de habitantes potenciales afectados y daños económicos por riesgo de inundaciones. / [CA] El canvi climàtic afectarà indubtablement els esdeveniments de neu ja que s'espera que la temperatura i la precipitació canvien en el futur. Les muntanyes espanyoles estan especialment afectades per aquesta situació, ja que l'emmagatzematge de neu es concentra en períodes molt concrets de l'any hidrològic i juga un paper molt important en la gestió dels recursos hídrics. En aquest estudi es fa una anàlisi del comportament dels fenòmens complexos relacionats amb la neu a les quatre principals regions muntanyoses d'Espanya en els propers 50 anys. El model hidrològic ASTER s'aplica utilitzant com a insum bàsic dades de temperatura i precipitació, estimades sota un escenari de canvi climàtic. Els resultats mostren diferents canvis en els cabals màxims i la mitjana esperada, depenent de la molt diferent magnitud i signe dels canvis en la precipitació. Es pot produir un augment dels episodis d'inundació com a conseqüència d'una relació complexa entre els canvis en les precipitacions i un augment de les intensitats màximes de desglaç que oscil¿len entre el 2,1% als Pirineus i el 7,4% a la Serralada. Cantàbrica. Tot i això, els patrons comuns es mostren en una menor duració de les reserves de massa de neu, que s'espera que ocórreguen 45 dies abans per a la Serralada Cantàbrica, i al voltant de 30 dies per a la resta de les regions muntanyoses estudiades. Els canvis observats també condueixen a una disminució preocupant de l'efecte regulador dels fenòmens relacionats amb la neu als rius espanyols, amb una disminució de l'acumulació mitjana de neu que oscil¿la entre un 28% per als Pirineus i Sierra Nevada i un 42% per al Sistema Central i la Serralada Cantàbrica. S'espera una disminució del cabal mitjà, que fluctua des del 2,4% als Pirineus fins al 7,3% a la Serralada Cantàbrica, augmentant únicament al Sistema Central un 4,0%, i cal desenvolupar noves mesures d'adaptació al canvi climàtic. D'altra banda, per tal d'aconseguir una estimació millor de l'Equivalent d'aigua de neu (SWE) utilitzant una xarxa meteorològica i de profunditat de neu (SD) econòmica i extensa que condueix a millorar el calibratge del model hidrològic ASTER, es proporcionen nous models de regressió de densitat de neu (SDEN). A partir del banc de dades més significatiu de densitat de neu (SDEN) als Pirineus espanyols, i sent una de les zones més importants i millor monitorizades del mon per a mostrejos manuals in situ i mesures automàtiques, s'avaluen models de regressió lineal simple i múltiple que relacionen SDEN amb intra-dependència del temps anual i altres factors com la precipitació acumulada estacional, les temperatures mitjana de 7 dies, la profunditat de la neu (SD) i l'elevació. La precipitació estacional acumulada va presentar una influència més dominant que la precipitació diària, sent usualment el segon factor determinant de SDEN més dominant, seguit per la temperatura. Les temperatures mitjanes van mostrar el millor ajustament a SDEN. Els resultats van mostrar taxes de densificació similars, sense mostrar un patró espacial. La taxa de densificació per al conjunt de mostres manuals es va fixar en 1,2 x 10-3 kg/L/dia, molt semblant al conjunt de mesures automàtiques. Els resultats augmenten el coneixement sobre SDEN als Pirineus, encara que cal tindre en compte l'alta variabilitat espacial trobada. Finalment, s'estudien els efectes que el canvi climàtic pot tindre en les inundacions per a un cas d'estudi d'una conca nival de la Serralada Cantàbrica. Usant diferents models climàtics, considerant un escenari d'emissions de gasos d'efecte hivernacle comparativament altes (RCP8.5), amb dades diàries de temperatura i precipitació dels anys 2007-2070, i comparant els resultats en termes relatius, la taxa de flux i la variació del ri / [EN] Climate change undoubtedly will affect snow events as temperature and precipitation are expected to change in the future. Spanish mountains are especially affected by that situation since snow storage is there focused on very specific periods of the hydrological year and plays a very important role in the management of water resources. In this study, an analysis of the behaviour of the complex snow-related phenomena in the four main mountain regions of Spain in the next 50 years is conducted. The ASTER hydrological model is applied using temperature and precipitation data as basic input, estimated under a climate change scenario. Results show different changes in the maximum and average expected flows, depending on the very different magnitude and sign of changes in precipitation. An increase of flooding episodes may occur as a result of a complex relationship between changes in precipitation and an increase in maximum snowmelt intensities that range from 2.1% in the Pyrenees to 7.4% in the Cantabrian Mountains. However, common patterns are shown in a shorter duration of the snow bulk reserves, expected to occur 45 days earlier for the Cantabrian Mountains and about 30 days for the rest of the studied mountain regions. Changes observed also lead to a concerning decrease in the regulatory effect of the snow-related phenomena in the Spanish rivers, with a decrease in the average snow accumulation that ranges from about 28% for the Pyrenees and Sierra Nevada to 42% for the Central System and the Cantabrian Mountains. A decrease in average flow is expected, fluctuating from 2.4% in the Pyrenees to 7.3% in Cantabrian Mountains, only increasing in the Central System by 4.0%, making all necessary to develop new adaptation measures to climate change. To achieve a better estimation of Snow Water Equivalent (SWE) using an economical and extensive snow depth (SD) and meteorological network that leads to improving the calibration of ASTER hydrological model, new snow density (SDEN) regression models are given in this work. Based on the most significant dataset of snow density (SDEN) in the Spanish Pyrenees for on-site manual samples and automatic measurements, as one of the most important and best-monitored areas in the world, single and multiple linear regression models are evaluated that relate SDEN with intra-annual time dependence and other drivers such as the seasonal accumulated precipitation, 7-day average temperatures, snow depth (SD) and elevation. The seasonal accumulated precipitation presented a more dominant influence than daily precipitation, usually the second most dominant SDEN driver, followed by temperature. Average temperatures showed the best fitting to SDEN. The results showed similar densification rates without showing a spatial pattern. The densification rate for the set of manual samples was 1.2 x 10-3 kg/L/day, very similar to the set of automatic measurements. The results increase knowledge on SDEN in the Pyrenees, although the high spatial variability that has been found must be regarded. Finally, climate change's effects on floods are studied in a case study of a snow basin in the Cantabrian Mountains. Using different climate models, regarding a scenario of comparatively high greenhouse gas emissions (RCP8.5), with daily temperature and precipitation data from the years 2007-2070, and comparing results in relative terms, flow rate and flood risk variation due to climate change are estimated. In the specific case of Reinosa, the MRI-CGCM3 climate model shows that climate change will cause a significant increase of potentially affected inhabitants and economic damage due to flood risk / Lastrada Marcén, JE. (2022). Study of the Climate Change Effect on the Snow Water Resources in the Spanish Mountains [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/188951 / Compendio