Made available in DSpace on 2017-07-10T19:24:12Z (GMT). No. of bitstreams: 1 Gisele Gollin 2015.pdf: 3252968 bytes, checksum: 739819d25020783e08e374315f3e2ee1 (MD5) Previous issue date: 2015-08-20 / This study aims to estimate hydric availability in Piquiri River basin based on the historical flow series and precipitation from 1980 to 2010 in order to associate them to the rainfall estimates provided by Eta, a regional weather model, until 2098. The series of annual minimum flows (Q7) and minimum of seven-day flows with a registering period of ten years (Q7,10) were submitted to statistical analysis to identify the probabilistic model that best fitted the data for each station. Thus, in order to obtain the retention curve, a procedure was carried out based on the obtained frequency classes. The average values of annual rainfall, precipitation of the driest quarter, precipitation of the wettest quarter, precipitation of the driest semester and precipitation of the wettest quarter of the basin were determined using the IDW interpolation method using a geographic information system (SIG). From all precipitation and flow obtained values, regressions were performed among (Q7), (Q7,10), (Q 90%), (Q 95%) flows and rainfalls (total annual, the driest quarter, the wettest quarter, the driest semester and the wettest semester) associated with the drainage area. Standard statistical tests were carried out to assure the quality of the generated model.For estimates of future flows, it was necessary to obtain data of future annual rainfall, simulated by the weather model Eta, from 2010 to 2098, which were provided by the Weather Forecasting and Climate Studies Center (CPTEC/INPE). The independent variable that best corresponds to the proposed standards during the study was the total annual rainfall in order to define the rainfall-runoff basin model. According to the future data of annual rainfall and drainage area, through the rainfall-runoff model, it was possible to obtain estimates of future minimum flows and carry out the trend analysis of time series with the series of future flow estimates. Therefore, a simple linear filter was used for smoothing the data series. It was not possible to find a pattern of rainfall related to the driest and wettest months in Piquiri River basin. Multiple linear model fitted best to the data, whose coefficient of determination (R)2was 0.67. The charts concerning generated trend analysis showed little increase in total annual rainfall index, simulated for the future in the studied region, when compared to the historical series. It was also observed that both members of the Eta model showed similar results. The values of minimum flows estimated for the future have provided to the basin an area without water deficit under natural conditions / O objetivo deste trabalho foi estimar a disponibilidade hídrica na bacia hidrográfica do Rio Piquiri por meio das séries históricas de vazão e precipitação no período de 1980 2010 e relacioná-las com as estimativas de precipitação fornecidas pelo modelo climático regional Eta até o ano de 2098. As séries de vazões mínimas anuais (Q7) e vazões mínimas com sete dias de duração com um período de retorno de dez anos (Q7,10) para cada estação foram submetidas à análise estatística, para identificar o modelo probabilístico que melhor se ajustasse aos dados. Para a obtenção da curva de permanência, realizou-se o procedimento baseado na obtenção de classes de frequência. Os valores da média de precipitação anual, precipitação do trimestre mais seco, precipitação do trimestre mais chuvoso, precipitação do semestre mais seco e precipitação do semestre mais chuvoso sobre a bacia foram determinados utilizando o método de interpolação IDW por um sistema de informação geográfica (SIG). A partir de todos os valores de precipitação e vazão encontrados, foram realizadas as regressões entre as vazões (Q7), a (Q7,10), a (Q 90%), a (Q 95%) e as precipitações (total anual, trimestre mais seco, trimestre mais chuvoso, semestre mais seco e semestre mais chuvoso) juntamente com a área de drenagem. Foram realizados testes estatísticos padrão para comprovar a qualidade do modelo gerado. Para a estimativas de vazões futuras, foi necessário obter os dados de precipitação total anual futuros simulados pelo modelo climático Eta, para o período de 2010 a 2098, os quais foram fornecidos pelo Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE).A variável explicativa que melhor correspondeu aos padrões propostos durante o estudo para definir o modelo chuva-vazão da bacia foi a precipitação total anual. De posse dos dados futuros de precipitação total anual e área de drenagem, através do modelo chuva-vazão, foram obtidas as estimativas de vazões mínimas futuras e realizada a análise de tendência da série histórica juntamente com a série de estimativas de vazão futura. Para tanto, empregou-se um filtro linear simples para a suavização da série de dados. Não foi possível encontrar um padrão de pluviosidade em relação aos meses mais secos e mais chuvosos na bacia hidrográfica do rio Piquiri. O modelo linear múltiplo foi o que melhor se ajustou aos dados, cujo coeficiente de determinação (R)2foi igual a 0,67. Os gráficos de análise de tendência gerados indicaram pequeno aumento no índice de precipitação total anual simulado para o futuro na região estudada, em comparação à série histórica, e observouseque os dois membros do modelo Eta apresentaram resultados semelhantes. Os valores de vazões mínimas, estimados para o futuro, conferem à bacia uma área sem restrições hídricas em condições naturais.

Made available in DSpace on 2017-05-12T14:47:28Z (GMT). No. of bitstreams: 1 Gisele Gollin 2015.pdf: 3252968 bytes, checksum: 739819d25020783e08e374315f3e2ee1 (MD5) Previous issue date: 2015-08-20 / This study aims to estimate hydric availability in Piquiri River basin based on the historical flow series and precipitation from 1980 to 2010 in order to associate them to the rainfall estimates provided by Eta, a regional weather model, until 2098. The series of annual minimum flows (Q7) and minimum of seven-day flows with a registering period of ten years (Q7,10) were submitted to statistical analysis to identify the probabilistic model that best fitted the data for each station. Thus, in order to obtain the retention curve, a procedure was carried out based on the obtained frequency classes. The average values of annual rainfall, precipitation of the driest quarter, precipitation of the wettest quarter, precipitation of the driest semester and precipitation of the wettest quarter of the basin were determined using the IDW interpolation method using a geographic information system (SIG). From all precipitation and flow obtained values, regressions were performed among (Q7), (Q7,10), (Q 90%), (Q 95%) flows and rainfalls (total annual, the driest quarter, the wettest quarter, the driest semester and the wettest semester) associated with the drainage area. Standard statistical tests were carried out to assure the quality of the generated model.For estimates of future flows, it was necessary to obtain data of future annual rainfall, simulated by the weather model Eta, from 2010 to 2098, which were provided by the Weather Forecasting and Climate Studies Center (CPTEC/INPE). The independent variable that best corresponds to the proposed standards during the study was the total annual rainfall in order to define the rainfall-runoff basin model. According to the future data of annual rainfall and drainage area, through the rainfall-runoff model, it was possible to obtain estimates of future minimum flows and carry out the trend analysis of time series with the series of future flow estimates. Therefore, a simple linear filter was used for smoothing the data series. It was not possible to find a pattern of rainfall related to the driest and wettest months in Piquiri River basin. Multiple linear model fitted best to the data, whose coefficient of determination (R)2was 0.67. The charts concerning generated trend analysis showed little increase in total annual rainfall index, simulated for the future in the studied region, when compared to the historical series. It was also observed that both members of the Eta model showed similar results. The values of minimum flows estimated for the future have provided to the basin an area without water deficit under natural conditions / O objetivo deste trabalho foi estimar a disponibilidade hídrica na bacia hidrográfica do Rio Piquiri por meio das séries históricas de vazão e precipitação no período de 1980 2010 e relacioná-las com as estimativas de precipitação fornecidas pelo modelo climático regional Eta até o ano de 2098. As séries de vazões mínimas anuais (Q7) e vazões mínimas com sete dias de duração com um período de retorno de dez anos (Q7,10) para cada estação foram submetidas à análise estatística, para identificar o modelo probabilístico que melhor se ajustasse aos dados. Para a obtenção da curva de permanência, realizou-se o procedimento baseado na obtenção de classes de frequência. Os valores da média de precipitação anual, precipitação do trimestre mais seco, precipitação do trimestre mais chuvoso, precipitação do semestre mais seco e precipitação do semestre mais chuvoso sobre a bacia foram determinados utilizando o método de interpolação IDW por um sistema de informação geográfica (SIG). A partir de todos os valores de precipitação e vazão encontrados, foram realizadas as regressões entre as vazões (Q7), a (Q7,10), a (Q 90%), a (Q 95%) e as precipitações (total anual, trimestre mais seco, trimestre mais chuvoso, semestre mais seco e semestre mais chuvoso) juntamente com a área de drenagem. Foram realizados testes estatísticos padrão para comprovar a qualidade do modelo gerado. Para a estimativas de vazões futuras, foi necessário obter os dados de precipitação total anual futuros simulados pelo modelo climático Eta, para o período de 2010 a 2098, os quais foram fornecidos pelo Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE).A variável explicativa que melhor correspondeu aos padrões propostos durante o estudo para definir o modelo chuva-vazão da bacia foi a precipitação total anual. De posse dos dados futuros de precipitação total anual e área de drenagem, através do modelo chuva-vazão, foram obtidas as estimativas de vazões mínimas futuras e realizada a análise de tendência da série histórica juntamente com a série de estimativas de vazão futura. Para tanto, empregou-se um filtro linear simples para a suavização da série de dados. Não foi possível encontrar um padrão de pluviosidade em relação aos meses mais secos e mais chuvosos na bacia hidrográfica do rio Piquiri. O modelo linear múltiplo foi o que melhor se ajustou aos dados, cujo coeficiente de determinação (R)2foi igual a 0,67. Os gráficos de análise de tendência gerados indicaram pequeno aumento no índice de precipitação total anual simulado para o futuro na região estudada, em comparação à série histórica, e observouseque os dois membros do modelo Eta apresentaram resultados semelhantes. Os valores de vazões mínimas, estimados para o futuro, conferem à bacia uma área sem restrições hídricas em condições naturais.

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.

Die Bemessung von Bauwerken an oder in Fließgewässern erfordert die Kenntnis des statistischen Hochwasserregimes. Beispielsweise legen Hochwasserschutzkonzeptionen häufig ein Hochwasser zu Grunde, welches in einem Jahr mit der Wahrscheinlichkeit von 1/100 auftritt. Ein extremeres Hochwasser wird für den Nachweis der Standsicherheit großer Stauanlagen nach DIN 19700-12 mit einem Hochwasser der jährlichen Eintrittswahrscheinlichkeit von 1/10000 benötigt. Ein solches Hochwasser kann bereits wegen des instationären Klimas nicht allein aus Durchflussmessdaten abgeleitet, sondern lediglich idealisiert dargestellt werden. Das resultiert nicht zuletzt daraus, dass der Mensch natürlich Zeuge eines so unwahrscheinlichen Ereignisses werden kann. Jedoch kann er die Unwahrscheinlichkeit nicht nachweisen. Jedes Berechnungsschema, mit welchem ein so unwahrscheinliches Ereignis abgeschätzt werden soll, wird nur begrenzt zuverlässig sein. Das Ziel der Arbeit ist es daher, die Schätzung etwas zuverlässiger zu gestalten. Grundsätzlich gilt, dass ein Modell umso mehr bzw. sicherere Ergebnisse liefern kann, je mehr Daten in das Modell eingehen. Direkt mit dem Durchfluss gekoppelt sind Angaben zu historischen Hochwasserereignissen bzw. qualitative Einschätzungen kleinräumiger Ereignisse. Eine wichtige Datenquelle neben den Durchflussartigen ist der mit dem Durchfluss kausal verbundene Niederschlag und dessen zu vermutendes Maximum in einem Gebiet. Wird zusätzlich regional vorgegangen, können räumliche Aspekte und Strukturen in größeren Einzugsgebieten berücksichtigt werden. Diese stärken bzw. erweitern die lokalen Berechnungsgrundlagen und gewährleisten ein räumlich konsistentes Bild. Im Umkehrschluss kann das Durchflussregime regionalisiert werden, um Informationen an nicht bemessenen Orten bereitstellen zu können. Aus den genannten erweiterten Berechnungsgrundlagen lassen sich drei Anknüpfungspunkte schließen: (i) Es muss eine sehr flexible und dennoch plausible Darstellungsmöglichkeit des statistischen Niederschlagsregimes bis zum vermutlichen Maximum formuliert werden. (ii) Das entwickelte Niederschlagsregime muss mit dem Durchflussregime gekoppelt werden, um die Informationen nutzen zu können. (iii) Die anschließende Regionalisierung muss die verschachtelte baumartige Struktur hydrologischer Einzugsgebiete berücksichtigen. Punkt (i) wird durch eine zweigeteilte Verteilungsfunktion gelöst. Damit werden die ideale Darstellung des wahrscheinlicheren Bereiches und der plausible Verlauf bis zum Maximum miteinander verbunden. Bezüglich Punkt (ii) wird ein neues Kopplungsprinzip entwickelt. Dieses basiert auf der Annahme, dass ein je nach Gebiet gültiger maximaler Scheitelabflussbeiwert existiert, welcher asymptotisch erreicht wird. Im Ergebnis erhält die Durchflussverteilung mit der Abflussbeiwertapproximation einen oberen Grenzwert in Abhängigkeit von Niederschlagsmaximum und Scheitelabflussbeiwert. Entsprechend der Vorgaben in Punkt (iii) wird die Referenzpegelmethode entwickelt. Diese basiert darauf, dass ähnliche Einzugsgebiete äquivalente Hochwasserscheitel generieren. Damit können bekannte Hochwasserereignisse eines Referenzpegels auf unbeobachtete Teileinzugsgebiete übertragen werden. Bei der Wahl des Referenzpegels wird u.a. die Topologie der Einzugsgebiete berücksichtigt. Die gesamte Strategie kann auf große Untersuchungsgebiete angewandt werden. Am Beispiel sächsischer Flüsse wird die Vorgehensweise von der Datenhomogenisierung bis hin zum extremen Hochwasserdurchfluss an einem unbeobachteten Querschnitt erläutert. / The dimensioning of different constructions at and in streams respectively requires knowlegde on the flood situation at site. For instance flood protection concepts often base on a peak discharge of the annual recurrence probability of 1/100. A more severe flood of an annual recurrence probability of 1/10000 is used to confirm the stability of large dams following DIN 19700-12. Such a flood cannot be deduced from runoff data only, but rather shown in an idealised way. It results not least on the fact, that human can witness a very improbable flood event. But is it not possible to verify the improbability. Every modelling scheme that is confronted with the deduction of such an extreme flood event will be of limited reliability. The task\'s aim will therefore be to make the estimation more reliable. Generally the more data a model involves the more trustworthy the results will become. Directly coupled with runoff are historical flood data and qualitative details of small scale flood events respectively. Aside runoff information an important data source is precipitation data, which is coupled with runoff data in a causal way, and the possible maximum precipitation. If additionally whole regions are examined it is possible to consider regional facets and structures of larger catchments. These strengthen and expand local modelling basics and provide a regional consistent result. Vice versa the flood regime can be regionalised to gain information at unobserved cross sections. Out of the described expanded modelling basics follow three links: (i) It is necessary to find a flexible but still plausible formulation of the statistical precipitation regime until the probable maximum precipitation. (ii) The formulation of point i) has to be coupled with the flood regime to include these information. (iii) The adjacent regionalisation has to account for the nested and arboreal structure of hydrological catchments. Point (i) will be solved by a split distribution function. That allows the ideal display of the more probable domain as well as the characteristics until the probable maximum. Regarding point (ii) a new principle of coupling will be developed. It bases on the assumption that a regional maximum runoff coefficient exists and it will be gained asymptotically. As a result of the runoff coefficient approximation the runoff distribution function gets an upper limit depending on maximum precipitation and runoff coefficient. Respecting the guidelines in point (iii) the reference gauge method will be developed. It bases upon the fact, that likewise catchments generate equivalent peak discharges. For this reason it is possible to carry known peak discharges of a reference gauge onto unobserved subcatchments. Among other things the choice of a reference gauge accounts for the topology of the catchments. The whole strategy can be applied to large catchments what is exemplarily shown in Saxon streams. Beginning with a data homogenisation to the point of discharges of extreme low exceedance probabilities at unobserved cross sections the whole procedure is shown.

Die deterministische Modellierung des Niederschlags-Abfluss(N-A)-Prozesses mit flächendifferenzierten, prozessbasierten Modellen ist von zahlreichen Unsicherheiten beeinflusst. Diese Unsicherheiten resultieren hauptsächlich aus den genutzten Daten, die Messfehlern unterliegen sowie für eine flächendifferenzierte Modellierung entsprechend aufbereitet werden müssen, und der Abstraktion der natürlichen Prozesse im Modell selbst. Da N-A-Modelle in der hydrologischen Praxis vielfältig eingesetzt werden, sind Zuverlässigkeitsaussagen im Hinblick auf eine spezielle Anwendung nötig, um das Vertrauen in die Modellergebnisse zu festigen. Die neu entwickelte Strategie zur Analyse und Simulation der Unsicherheiten eines flächendifferenzierten, prozessbasierten N-A-Modells ermöglicht eine umfassende, globale und komponentenbasierte Unsicherheitsbestimmung. Am Beispiel des mesoskaligen Einzugsgebiets der Schwarzen Pockau/Pegel Zöblitz im mittleren Erzgebirge wird der Einfluss maßgebender Unsicherheiten im N-A-Prozess sowie deren Kombination zu einer Gesamt-Unsicherheit auf den Gebietsabfluss aufgezeigt. Zunächst werden die maßgebenden Unsicherheiten separat quantifiziert, wobei die folgenden Methoden eingesetzt werden: (i) Monte-Carlo Simulationen mit flächendifferenzierten stochastischen Bodenparametern zur Analyse des Einflusses unsicherer Bodeninformationen, (ii) Bayes’sche Inferenz und Markov-Ketten-Monte-Carlo Simulationen, die eine Unsicherheitsbestimmung der konzeptionellen Modellparameter der Abflussbildung und -konzentration ermöglichen und (iii) Monte-Carlo Simulationen mit stochastisch generierten Niederschlagsfeldern, die die raum-zeitliche Variabilität interpolierter Niederschlagsdaten beschreiben. Die Kombination der Unsicherheiten zu einer hydrologischen Unsicherheit und einer Gesamt-Unsicherheit erfolgt ebenfalls mit Monte-Carlo Methoden. Dieses Vorgehen ermöglicht die Korrelationen der Zufallsvariablen zu erfassen und die mehrdimensionale Abhängigkeitsstruktur innerhalb der Zufallsvariablen empirisch zu beschreiben. Die Ergebnisse zeigen für das Untersuchungsgebiet eine Dominanz der Unsicherheit aus der raum-zeitlichen Niederschlagsverteilung im Gebietsabfluss gefolgt von den Unsicherheiten aus den Bodeninformationen und den konzeptionellen Modellparametern. Diese Dominanz schlägt sich auch in der Gesamt-Unsicherheit nieder. Die aus Messdaten abgeleiteten Unsicherheiten weisen eine Heteroskedastizität auf, die durch den Prozessablauf geprägt ist. Weiterhin sind Indizien für eine Abhängigkeit der Unsicherheit von der Niederschlagsintensität sowie strukturelle Defizite des N-A-Modells sichtbar. Die neu entwickelte Strategie ist prinzipiell auf andere Gebiete und Modelle übertragbar. / Modelling rainfall-runoff (R-R) processes using deterministic, spatial distributed, process-based models is affected by numerous uncertainties. One major source of these uncertainties origins from measurement errors together with the errors occurring in the process of data processing. Inadequate representation of the governing processes in the model with respect to a given application is another source of uncertainty. Considering that R-R models are commonly used in the hydrologic practise a quantification of the uncertainties is essential for a realistic interpretation of the model results. The presented new framework allows for a comprehensive, total as well as component-based estimation of the uncertainties of model results from spatial distributed, process-based R-R modelling. The capabilities of the new framework to estimate the influence of the main sources of uncertainties as well as their combination to a total uncertainty is shown and analysed at the mesoscale catchment of the Schwarze Pockau of the Ore Mountains. The approach employs the following methods to quantify the uncertainties: (i) Monte Carlo simulations using spatial distributed stochastic soil parameters allow for the analysis of the impact of uncertain soil data (ii) Bayesian inference und Markov Chain Monte Carlo simulations, yield an estimate of the uncertainty of the conceptual model parameters governing the runoff formation and - concentration processes. (iii) Monte Carlo simulations using stochastically generated rainfall patterns describing the spatiotemporal variability of interpolated rainfall data. Monte Carlo methods are also employed to combine the single sources of uncertainties to a hydrologic uncertainty and a total uncertainty. This approach accounts for the correlations between the random variables as well as an empirical description of their multidimensional dependence structure. The example application shows a dominance of the uncertainty resulting from the spatio-temporal rainfall distribution followed by the uncertainties from the soil data and the conceptual model parameters with respect to runoff. This dominance is also reflected in the total uncertainty. The uncertainties derived from the data show a heteroscedasticity which is dominated by the process. Furthermore, the degree of uncertainty seems to depend on the rainfall intensity. The analysis of the uncertainties also indicates structural deficits of the R-R model. The developed framework can principally be transferred to other catchments as well as to other R-R models.

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.

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 / 新制・課程博士 / 博士(工学) / 甲第23163号 / 工博第4807号 / 新制||工||1752(附属図書館) / 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 田中 茂信, 准教授 佐山 敬洋 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The diploma thesis deals with the evaluation of hydrological drought in the Bouřlivec and Loučenský stream basins, located in the northwest of the Czech Republic in the Ore Mountains. Available hydrological and climatological data series from two limnographic and four climatological stations were used to characterize the hydrological drought. The intensity of the occurrence of hydrological drought in the stream basins of interest was assessed using the method of threshold values and the method of insufficient volumes. According to the results of the work, the hydrological year 2020 was marked as extremely low in water on both monitored profiles, which points to the accumulating causes of drought from previous years. In terms of hydrological drought, the year 2018 was also significant. The diploma thesis also aims to detect trends in data series of precipitation, air temperature and inflow into the Všechlapy reservoir using the Mann-Kendall test. The results of statistical testing of the trend point to an increasing trend of air temperature and a decreasing trend of the inflow into the Všechlapy reservoir. A significant trend in the precipitation data series was not confirmed. Trend testing was preceded by an assessment of the homogeneity of the available data sets. Last but not least, emphasis is...

The aim of this work is to quantify the natural water retention capacity of the landscape in selected catchments and determine the significance of selected climatic and geographic basin factors on components of retention capacity. 18 rainfall-runoff events were selected in 11 catchments for quantification of the natural water retention capacity of landscape. Land cover, geomorphological, pedological and hydrological conditions were analyzed for this basin using GIS tools. Historical rainfall-runoff events for which were restored historical land cover were also evaluated in this work. Two different methods were used for the quantification of retention capacity, one of them was used in two variants. A rainfall-runoff models and simulated scenarios of land cover (positive and negative) were constructed in two selected catchments in HEC-HMS. The work also use previously performed simulation scenarios of land cover formulated by other authors. Total final set of 33 rainfall-runoff events were subjected to statistical correlation and regression analysis. The goal of these analyses was to determine the significance of individual parameters assessed in relation to the components of natural water retention of catchment.

<p>Saturated hydraulic conductivity (<em>K</em>_<em>s</em>) is among the most important soil properties that influence the partitioning of rainfall into surface and subsurface waters and is needed for understanding and modeling hydrologic processes at the field-scale. Field-scale variability of <em>K</em>_<em>s</em> is often represented as a lognormal random field, and its parameters are assessed either by making local- or point-scale measurements using instruments such as permeameters and infiltrometers or by calibrating probabilistic models with field-scale infiltration experiments under natural/artificial rainfall conditions. This research quantifies the uncertainty in the <em>K</em>_<em>s</em> random field when using observations from the above techniques and provides recommendations as to what constitutes a good experiment to assess the field-scale variability of <em>K</em>_<em>s</em>. Infiltration experiments with instruments sampling larger areas (or volumes) are typically expected to be more representative of field conditions than those sampling smaller ones; hence, the uncertainty arising from the field-scale natural rainfall-runoff experiments was evaluated first. A field-averaged infiltration model and Monte Carlo simulations were employed in a Bayesian framework to obtain the possible <em>K</em>_<em>s</em> random fields that would describe experimental observations over a field for a rainfall event. Results suggested the existence of numerous parameter combinations that could satisfy the experimental observations over a single rainfall event, and high variability of these combinations among different events, thereby providing insights regarding the identifiable space of <em>K</em>_<em>s</em> distributions from individual rainfall experiments. The non-unique parameter combinations from multiple rainfall events were subsequently consolidated using an information-theoretic measure, which provided a realistic estimate of our ability to quantify the spatial variability of <em>K</em>_<em>s</em> in natural fields using rainfall-runoff experiments. </p> <p>  </p> <p>With the resolving ability from rainfall-runoff experiments constrained due to experimental limitations, the <em>K</em>_<em>s</em> estimates from in-situ point infiltration devices could provide additional information in conjunction with the rainfall-runoff experiments. With this hypothesis, the role of three in-situ point infiltration devices --- the double-ring infiltrometer, CSIRO version of tension permeameter, and Guelph constant-head permeameter --- was then evaluated in characterizing the field-scale variability of <em>K</em>_<em>s</em>. Results suggested that <em>K</em>_<em>s</em> estimates from none of the instruments could individually represent the field conditions due to the presence of measurement and structural errors besides any sampling biases; hence any naive efforts at assimilating their data (e.g., data pooling, instrument-specific transforms, etc.) and augmenting with field-scale rainfall-runoff observations as informative prior distributions would not be fruitful. In the absence of benchmarks establishing the true <em>K</em>_<em>s</em> field, it is also impossible to quantify these errors; therefore, a posterior coarsening method was used to alleviate their impact when estimating the field-scale variability of <em>K</em>_<em>s</em>. </p> <p>  </p> <p>Finally, the impact of censored moments on the maximum likelihood (ML) estimates of the <em>K</em>_<em>s</em> distribution parameters was studied. Results highlighted the rainfall event's ability to only be able to resolve a fraction of the <em>K</em>_<em>s</em> field, and that the time and duration of peak rainfall intensity play a role in resolving the <em>K</em>_<em>s</em> field, besides the peak rainfall intensity. The reliability of the ML estimates is a function of the fraction of the <em>K</em>_<em>s</em> field resolved by the rainfall event, until a limit when the estimates start to overfit the calibration data. Rainfall-runoff experiments for which the ML estimates resolve 30--80 % of the <em>K</em>_<em>s</em> distribution are likely to be good calibration events. </p>