Made available in DSpace on 2015-05-14T12:09:08Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 7934601 bytes, checksum: 83089393956abb6b7fa32c5295791684 (MD5) Previous issue date: 2012-03-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / A major difficulty for studies of small hydrological watersheds is the lack of good quality time series of hydrologic data, mainly because the flow rates in small watersheds are not monitored. Another important issue is that available rainfall runoff models are almost always developed focusing on watersheds of medium and large scale. Regionalization studies have become an important tool to attempt to overcome these limitations. Suitable in most of the hydrological studies is the regionalization of rainfall runoff-model parameters by using specific characteristics of a watershed. A tool was developed in a Geographic Information System which automatically gets the physical characteristics of watersheds from a digital elevation model by selecting the outlet and then generating the rainfall runoff model parameters with neural networks. This study uses data from small dams in the semi-arid region of northeastern Brazil. The developed methodology is applied using target watersheds for the parameter estimation. The results show that the developed tool can be very useful for rainfall runoff estimation in small watersheds. / Uma das maiores dificuldades para os estudos de pequenas bacias hidrográficas é a falta de séries históricas de dados hidrológicos, principalmente porque a fluviometria em pequenas bacias hidrográficas não é monitorada. Outra questão importante é que, os modelos chuva-vazão disponíveis quase sempre são desenvolvidos com foco em bacias de médio e grande porte. Estudos de regionalização se tornaram uma ferramenta importante para tentar superar essas limitações. A regionalização de parâmetros de modelos chuva-vazão, usando características específicas das bacias hidrográficas, é adequada para a maioria dos estudos hidrológicos. Uma ferramenta foi desenvolvida em um Sistema de Informação Geográfica, que determina automaticamente as características físicas das bacias hidrográficas a partir de um modelo digital de elevação, e, em seguida, gera os parâmetros do modelo chuva-vazão com redes neurais artificiais. Este trabalho usa dados de pequenas barragens na região semiárida do Nordeste do Brasil. A metodologia desenvolvida é aplicada e avaliada utilizando também o método da bacia meta para a estimativa dos parâmetros. Os resultados mostram que a ferramenta desenvolvida pode ser muito útil para o estudo da relação chuva-vazão em bacias hidrográficas de pequeno porte.

In 1910, Paris experienced its biggest flood in the 20th century. In 2010, for the anniversary of this event – supposed to happen every 100 years ! – the flood prediction model that is now used on the Seine basin was tested on its simulation,… and failed to reproduce the observed flood volume. This paper will try to explain, and correct, such disappointing results. Many hypotheses have been tested and based on their results, it has been decided to develop a frost module in order to assess the influence of this phenomenon – that is not taken into account by the lumped hydrological model that is used – on the flood formation. A soil temperature model using air temperature as input data was also designed because soil temperature data were not available in 1910. The addition of the frost module did not, however, bring many improvements to the 1910 flood simulation because frost is a too rare phenomenon on the Seine basin for the module to be correctly calibrated. However, new perspectives are presented to continue the research on this phenomenon.

付記する学位プログラム名: グローバル生存学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19975号 / 工博第4219号 / 新制||工||1653(附属図書館) / 33071 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 立川 康人, 教授 寶 馨, 教授 堀 智晴 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

<p>Society-induced changes to the environment are altering the effectiveness of existing management strategies for sustaining natural and agricultural ecosystem productivity. At the watershed scale, natural and agro-ecosystems represent complex spatiotemporal stochastic processes. In time, they respond to random rainfall events, evapotranspiration and other losses that are spatially variable because of heterogeneities in soil properties, root distributions, topography, and other factors. To quantify the environmental impact of anthropogenic activities, it is essential that we characterize the evolution of space and time patterns of ecosystem fluxes (e.g., energy, water, and nutrients). Such a characterization then provides a basis for assessing and managing future anthropogenic risks to the sustainability of ecosystem productivity.</p><p>To characterize the space and time evolution of watershed scale processes, this dissertation introduces a mean field approach to watershed hydrology. Mean field theory (also known as self-consistent field theory) is commonly used in statistical physics when modeling the space-time behavior of complex systems. The mean field theory approximates a complex multi-component system by considering a lumped (or average) effect of all individual components acting on a single component. Thus, the many body problem is reduced to a one body problem. For watershed hydrology, a mean field theory reduces the numerous point component effects to more tractable watershed averages resulting in a consistent method for linking the average watershed fluxes (evapotranspiration, runoff, etc.) to the local fluxes at each point.</p><p>The starting point for this work is a general point description of the soil moisture, rainfall, and runoff system. For this system, we find the joint PDF that describes the temporal variability of the soil water, rainfall, and runoff processes. Since this approach does not account for the spatial variability of runoff, we introduce a probabilistic storage (ProStor) framework for constructing a lumped (unit area) rainfall-runoff response from the spatial distribution of watershed storage. This framework provides a basis for unifying and extending common event-based hydrology models (e.g. Soil Conservation Service curve number (SCS-CN) method) with more modern semi-distributed models (e.g. Variable Infiltration Capacity (VIC) model, the Probability Distributed (PDM) model, and TOPMODEL). In each case, we obtain simple equations for the fractions of the different source areas of runoff, the spatial variability of runoff and soil moisture, and the average runoff value (i.e., the so-called runoff curve). Finally, we link the temporal and spatial descriptions with a mean field approach for watershed hydrology. By applying this mean field approach, we upscale the point description with the spatial distribution of soil moisture and parameterize the numerous local interactions related to lateral fluxes of soil water in terms of its average. With this approach, we then derive PDFs that represent the space and time distribution of soil water and associated watershed fluxes such as evapotranspiration and runoff.</p> / Dissertation

Influence of catchment spatial subdivision on the accuracy of the snow accumulation and snowmelt model Abstract This thesis is focused on influence of catchment spatial subdivision on the accuracy of rainfall-runoff model simulations. A hydrological model HEC-HMS developed by U.S. Army Corps of Engineers was applied in the thesis. Study area includes two experimental catchments; Bystřice River basin and Zlatý Brook basin. Both catchments are located in the Krušné Mountains. The research in catchments has been carried out by the Department of Physical Geography and Geoecology since 2008. The influence of four different horizontal and vertical catchments delineation on runoff simulations was analyzed. The simulations were performed in two two-year periods 11/2008-10/2010 and 11/2010-10/2012. The attention was mainly aimed to snowmelt component of the model, for which temperature index method was chosen. The results of simulations were compared with water stages data measured in catchments outlets and with data from winter field measurements (snow depth and snow water equivalent). The results from both catchments showed that higher accuracy of simulation of the snow water equivalent was reached by dividing the catchments into more elevation zones. However, each of the catchments behaved in different way. The...

Snow accumulation and snowmelt research is one of the most important hydrological issues in mountain areas World-wide. Spring snowmelt, usually in the combination with intensive rainfall or high air temperature, is one of the most common causes of flooding in the Czech Republic. Mathematical modeling of hydrological processes belongs to effective instruments of flood protection and finds its use in a variety of areas. For example, water management, hydrological forecasts for agriculture, information for dam regulation or for recreational areas and water sports are all affected. This thesis focuses on snow accumulation and snowmelt modeling with use of the empirical Degree-day method. This method is based on the relationship between snowmelt rate and air temperature. The American HAC-HMS programme is used for the simulation of hydrological processes. The main goal of this thesis is to calibrate the model and to simulate snow accumulation, snowmelt and run-off from the watershed. The experimental basin 'Ptačí potok' is situated in the central part of the Šumava Mountains, in altitude of about 1,200 m. Two winter seasons, 2011 and 2012, were simulated. Simulations showed high reliability and correct calibration of the Temperature index snowmelt model. Simulations of the snow water equivalent evolution...

Les modèles pluie-débit sont des outils essentiels pour de nombreuses applications hydrologiques, notamment la prévision des crues. L’objet de cette thèse est d’examiner les performances d’un modèle événementiel distribué, dont l’intérêt est de résumer la représentation des processus à la phase de crue, et la condition initiale à un indice de saturation du bassin facilement observable ou accessible. Ce dernier dispense de modéliser la phase inter-crue, et simplifie la paramétrisation et le calage du modèle. Le modèle étudié combine une fonction de production type SCS et une fonction de transfert type lag and route, appliquées à une discrétisation du bassin en mailles carrées régulières.Le modèle est d’abord testé sur le bassin versant du Real Collobrier. Ce bassin méditerranéen est suivi depuis plus de 50 ans par l’IRSTEA, et dispose d’une exceptionnelle densité de mesures de pluies et de débits. Cet environnement favorable permet de limiter les incertitudes sur l’estimation des pluies et d’évaluer les performances intrinsèques du modèle. Dans ces conditions, les crues sont bien reconstituées à l’aide d’un jeu de paramètres unique pour l’ensemble des épisodes testés, à l’exception de la condition initiale du modèle. Celle-ci apparaît fortement corrélée avec l’humidité du sol en début d’épisode, et peut être prédéterminée de façon satisfaisante par le débit de base ou l’indice w2 fourni par le modèle SIM de Météo-France. Les performances du modèle sont ensuite étudiées en dégradant la densité des pluviomètres, et rendent compte du niveau de performances du modèle dans les cas que l’on rencontre le plus souvent. .La variabilité spatiale des paramètres du modèle est étudiée à l’échelle de différents sous-bassins du Real Collobrier. La comparaison a permis de mettre en évidence et de corriger un effet d’échelle concernant l’un des paramètres de la fonction de transfert. Les relations entre la condition initiale du modèle et les indicateurs d’humidités des sols en début d’épisode restent bonnes à l’échelle des sous-bassins, mais peuvent être significativement différentes selon les sous-bassins. Une seule relation ne permet pas de normaliser l’initialisation du modèle sur l’ensemble des sous-bassins, à une échelle spatiale de quelques km2 ou dizaines de km2. Dans le cas de l’indice d’humidité du sol w2, une explication possible est que cet indice ne prend pas en compte suffisamment finement les propriétés des sols. Enfin, la variabilité spatiale des paramètres du modèle est étudiée à l’échelle d’un échantillon d’une quinzaine de bassins méditerranéens de quelques centaines de km2, associés à des paysages et des fonctionnements hydrologiques divers. La comparaison montre qu’à cette échelle, le lien entre les indicateurs de saturation du bassin et la condition initiale peut rester stable par type de bassin, mais varie significativement d’un type de bassin à l’autre. Des pistes sont proposées pour expliquer cette variation.En conclusion, ce modèle événementiel distribué représente un excellent compromis entre performances et facilité de mise en œuvre. Les performances sont satisfaisantes pour un bassin donné ou pour un type de bassin donné. L’analyse et l’interprétation de la variabilité spatiale des paramètres du modèle apparaît cependant complexe, et doit faire l’objet du test d’autres indicateurs de saturation des bassins, par exemple mesures in situ ou mesures satellitaires de l’humidité des sols. / Rainfall-runoff models are essential tools for many hydrological applications, including flood forecasting. The purpose of this thesis was to examine the performances of a distributed event model for reproducing the Mediterranean floods. This model reduces the parametrization of the processes to the flood period, and estimates the saturation of the catchment at the beginning of the event with an external predictor, which is easily observable or available. Such predictor avoids modelling the inter-flood phase and simplifies the parametrization and the calibration of the model. The selected model combines a distributed SCS production function and a Lag and Route transfer function, applied to a discretization of the basin in a grid of regular square meshes.The model was first tested on the Real Collobrier watershed. This Mediterranean basin has been monitored by IRSTEA for more than 50 years and has an exceptional density of rainfall and flow measurements. This favourable environment made it possible to reduce the uncertainties on the rainfall input and to evaluate the actual performances of the model. In such conditions, the floods were correctly simulated by using constant parameters for all the events, but the initial condition of the event-based model. This latter was highly correlated to predictors such as the base flow or the soil water content w2 simulated by the SIM model of Meteo-France. The model was then applied by reducing the density of the rain gauges, showing loss of accuracy of the model and biases in the model parameters for lower densities, which are representative of most of the catchments.The spatial variability of the model parameters was then studied in different Real Collobrier sub-basins. The comparison made it possible to highlight and correct the scale effect concerning one of the parameters of the transfer function. The catchment saturation predictors and the initial condition of the model were still highly correlated, but the relationships differed from some sub-catchments. Finally, the spatial variability of the model parameters was studied for other larger Mediterranean catchments, of which area ranged from some tenth to hundreds of square kilometres. Once more, the model could be efficiently initialized by the base flow and the water content w2, but significant differences were found from a catchment to another. Such differences could be explained by uncertainties affecting as well the rainfall estimation as the selected predictors. However, the relationships between the initial condition of the model and the water content w2 were close together for a given type of catchment.In conclusion, this distributed event model represents an excellent compromise between performance and ease of implementation. The performances are satisfactory for a given catchment or a given type of catchment. The transposition of the model to ungauged catchment is less satisfactory, and other catchment saturation indicators need to be tested, e.g. in situ measurements or satellite measurements of soil moisture.

TEMPORAL EVALUATION OF SNOW DEPLETION CURVES DERIVED FOR UPPER EUPHRATES BASIN AND APPLICATIONS OF SNOWMELT RUNOFF MODEL Marim, G&ouml / khan M.S., Department of Geodetic and Geographic Information Technologies Supervisor: Prof.Dr.A.&Uuml / nal Sorman September 2008, 112 pages Water is becoming very important issue day by day with descending usable water and energy resources. In the aspect of water resources management, especially for the optimum reservoir management, predicting runoff for large reservoirs by applying hydrologic model is a recent and crucial topic. The most important model input and predictor parameters to estimate runoff for the mountainous regions are to be distribution of rainfall / temperature and snow cover area, (SCA). It is seen that many predictor variables should be integrated with Geographic Information Systems (GIS) and Remote Sensing Techniques especially for hydrologic model variable preparation. Satellite products have the potential for obtaining those kinds of data in near real time. In this study, the changes of SDC are generated by the analysis of optical satellite and by using SDC as an input to hydrological models runoff is simulated for Upper Euphrates Basin (10215.7 km2) which is a sub basin of Euphrates Basin. Largest dams of Turkey / Keban, Karakaya and Atat&uuml / rk are located on Euphrates River. Optimum operations of these dams depend on forecasting incoming water in early summer season. Euphrates River is fed mainly from snowmelts in spring or early summer time.65-70 % of the annual flow is contributed from snowmelt in that region. Main objective of this study is to obtain the spatially and temporally distributed SCA percentages from optical satellite, which are required as one of the main input variables of the hydrological model used in the application. SCA percentages and SDC are obtained for snowmelt years 2004-2007 by using high temporal resolution optical remote sensing data: Terra Moderate Resolution Imaging Spectroradiometer (MODIS). In this study, Terra MODIS snow cover map product, MOD10A1 which has a spatial resolution of 500 m is used. As a hydrological model Snowmelt Runoff Model (SRM) was applied. SRM was built up on the well-known degree day approach. In this study SRM is simulated for two years 2006 and 2007.The simulation results are compared and resultant model parameters are obtained for future runoff forecast studies. In this study, beside recommendations, discussions on the variables and SRM parameters are also provided.

Snow indicates the potential stored water volume that is an important source of water supply, which has been the most valuable and indispensable natural resource throughout the history of the world. Euphrates and Tigris, having the biggest dams of Turkey, are the two largest trans-boundary rivers that originate in Turkey and pass throughout the water deficit nations Syria, Iran, Iraq and Saudi Arabia bringing life as well as water all their way. Snowmelt runoff originating from the mountains of Eastern Turkey accounts for 60 to 70 % of total annual discharge observed in Euphrates and Tigris. For an optimum operation of the dams, maximizing energy production, mitigation of floods and satisfying water rights, hydrological models which can both simulate and forecast the river discharges of Euphrates and Tigris are needed. In this study a hydrological model, snowmelt runoff model (SRM), is used in conjunction with remote sensing and geographic information systems to forecast the river discharges in the headwaters of Euphrates River, Upper Euphrates Basin. NOAA and MODIS satellite images were used to derive the snow covered area (SCA) information required by SRM. Linear reduction methodologies based on accumulated air temperature, with constant or varying gradient, were developed to get the continuous daily SCA values from the discrete daily satellite images. Temperature and precipitation forecasts were gathered from two different numerical weather prediction models, namely European Center for Medium Range Weather Forecasts (ECMWF) and Mesoscale Model Version 5 (MM5) from Turkish State Meteorological Services. These data sets provided t+24 hour forecasts of both temperature and precipitation. Temperature, precipitation and SCA information are fed into SRM. Discharge forecasts obtained from the model outputs are compared with the observed values. The overall performance of the model was seen as promising. Possible reasons of the mismatches between the forecasted and observed values are searched. Experiences gained throughout the study are summarized and recommendations on further forecast studies are mentioned.

L'estimation d'indices d'étiage est d'une grande importance pour une meilleure connaissance de la ressource en eau disponible et en déduire des règles de gestion de cette ressource et des risques associés. Idéalement, ces indices sont calculés en sites jaugés à partir de longues chroniques de débits mesurés. En sites non jaugés, ces indices doivent être estimés. Cette thèse s'inscrit dans le projet d'amélioration de l'outil informatique " LoiEau " utilisé par les DREAL et les Agences de l'eau. Le principal objectif est de développer un modèle hydrologique simple et flexible pour estimer tous les indices d'étiage souhaités à des intervalles de temps journaliers ou supérieurs en sites non jaugés. La simplicité du modèle repose sur l'hypothèse forte que deux paramètres plus facilement régionalisables suffisent à estimer les indices avec une précision voulue. Cette précision dépend de la fonction objectif qu'il a fallu adapter aux faibles débits pour caler convenablement les paramètres du modèle sur des sites jaugés. Le modèle se veut flexible dans le sens où il est applicable à une large variété de bassins versants. Il a été comparé au modèle journalier à quatre paramètres GR4J et au modèle mensuel à deux paramètres LoiEau en s'intéressant aussi à la façon de régionaliser les paramètres. Des comparaisons ont également été réalisées avec une méthode d'estimation dite stochastique d'un indice d'étiage classique. Ces travaux montrent le potentiel du modèle à deux paramètres et l'avantage du pas de temps journalier, la variabilité temporelle des précipitations n'étant pas sans conséquence sur l'estimation de débits moyens en raison de la non-linéarité des modèles pluies-débits. / Estimating low-flow indices is of paramount importance to understand low flows and to manage water resources and risk assessments. These indices are derived from time-series of river discharges that are measured at gauged sites over long periods. At ungauged sites, the indices must be estimated. This research work is part of a project to improve “LoiEau”, a software package that is used by French regional environmental or water agencies. The main objective is to develop a simple and flexible rainfall-runoff model to simulate low-flow indices of ungauged sites at daily or longer time intervals. The model simplicity relies on the strong assumption that two free parameters are sufficient to provide accurate enough estimates of low-flow indices, yet making easier the regionalisation of models. The model accuracy depends on the objective function that is used to calibrate model parameters on gauged sites and had to be adapted to low-flow simulations. The model is flexible in the sense that it is designed to fit to a wide variety of catchments and hydro-meteorological behaviours. This model was compared with GR4J, a daily rainfall-runoff model which involves four parameters, and LoiEau, a monthly model. Comparisons were also carried out with a stochastic estimation method applied to a specific low-flow index. This research work shows the potential of the two-parameter model, but also the advantage of a daily time step to account for the temporal variability of precipitations, which is not without consequence on the assessment of average discharges due to the nonlinearity of rainfall-runoff models.