This study is concerned with the effect that mean annual precipitation (P) has on the relationship between bankfull channel width (Wbf) and drainage area (Ada). Several other studies have been conducted in which relationships were developed for predicting Wbf as a function of Ada and P. In most cases, however, the relationships were developed for specific regions, e.g., physiographic regions. This study is unusual in that it evaluates the relationship between Wbf, Ada, and P over a broad area (i.e., across a range of geologic, terrestrial, and climatic environments). In one study, where a broad area was considered, the relationship between Wbf, Ada, and P was found to be linear. The dataset for this study was compiled from data in U.S. Geological Survey flood-flow-frequency reports, regional curve studies (i.e., studies in which Wbf vs. Ada relationships are developed) and other sources. A total of 435 sites that span across 12 states of the continental U.S. are represented in the dataset. Streams represented in the dataset are alluvial and have widths from 1 to 110 m, drainage areas from 0.50 to 22,000 km2, and mean annual precipitation depths ranging from 22 to 277 cm/yr. Data from the U.S. Environmental Protection Agency's Wadeable Streams Assessment study were employed in validating the results of this study. An analysis of covariance (ANCOVA) model was developed and it was determined that the intercept coefficient for the relationship between Wbf and Ada varies as follows: for P < 50 cm/yr the intercept coefficient (α) is constant; for 50 cm/yr ¡Ü P ¡Ü 100 cm/yr, α increases with P, and for P ¡Ý100 cm/yr, α is again constant. Across all values of P, the slope coefficient is constant (90% Confidence level). Changes in the relationship between Wbfand Ada are attributed to vegetation by noting that biome types changes from shrubland to forest as P increases from 50 to 100 cm/yr. These findings can be incorporated in regional curve studies and landscape evolution models (i.e., models which aim to integrate hydrology, land use history, geomorphology and climate change with models of vegetation succession).

Water availability in the ecosystem is one of the most crucial environmental factors that determines global terrestrial biome distribution. However, aridity/humidity conditions in the geologic past are difficult to quantify, mainly owing to the lack of a proper parameter. By using modern global climatic data, we here examine five selected previously proposed aridity indices (AIs), in which the climatic variables involved, including both precipitation and temperature, are simple and likely available in studies of paleoclimatology and paleoecology, although with different degrees of uncertainty. They were first evaluated along the modern climatic zones of eastern China, with the main metric of Thornthwaite humidity index (HI) and with the supplementary reference of soil moisture index (SMI) and near-ground atmospheric relative humidity (RH). Then AIs and the mean annual precipitation (MAP) were further statistically compared with HI, SMI, and RH, respectively, based on 1189 monitored data sets from meteorological stations over the world. The results show that the Köppen aridity index (AIKöppen), expressed as mean annual precipitation divided by mean annual temperature plus a constant of 33, is the most accurate and precise index among all selected indices, supported by the highest correlation coefficient respectively to HI, SMI, and RH, three widely-employed major indicators sensitive to hydrological dynamics in climatology and meteorology. Specifically, AIKöppen does well mirror corresponding HI along four representative transects from North America, South America, Africa, and Australia, which cover the typical arid and humid climates and span the main terrestrial biome types. Moreover, our results also distinctly reveal that, as also shown by many studies on modern climate, precipitation alone is inadequate to measure the hydrological condition, because both temperature and evapotranspiration are two other critical factors that strongly influence water balance in the ecosystem, meanwhile evapotranspiration is mainly affected by temperature. Based on the validated AIKöppen, we briefly discuss the aridity/humidity condition in China during the middle Miocene. The results demonstrate that moisture did decrease westward, but it is also clear that western China in the middle Miocene appears not to have been as dry as previously thought, indicated by the AIKöppen values representing a sub-humid to humid climate.

Water availability in the ecosystem is one of the most crucial environmental factors that determines global terrestrial biome distribution. However, aridity/humidity conditions in the geologic past are difficult to quantify, mainly owing to the lack of a proper parameter. By using modern global climatic data, we here examine five selected previously proposed aridity indices (AIs), in which the climatic variables involved, including both precipitation and temperature, are simple and likely available in studies of paleoclimatology and paleoecology, although with different degrees of uncertainty. They were first evaluated along the modern climatic zones of eastern China, with the main metric of Thornthwaite humidity index (HI) and with the supplementary reference of soil moisture index (SMI) and near-ground atmospheric relative humidity (RH). Then AIs and the mean annual precipitation (MAP) were further statistically compared with HI, SMI, and RH, respectively, based on 1189 monitored data sets from meteorological stations over the world. The results show that the Köppen aridity index (AIKöppen), expressed as mean annual precipitation divided by mean annual temperature plus a constant of 33, is the most accurate and precise index among all selected indices, supported by the highest correlation coefficient respectively to HI, SMI, and RH, three widely-employed major indicators sensitive to hydrological dynamics in climatology and meteorology. Specifically, AIKöppen does well mirror corresponding HI along four representative transects from North America, South America, Africa, and Australia, which cover the typical arid and humid climates and span the main terrestrial biome types. Moreover, our results also distinctly reveal that, as also shown by many studies on modern climate, precipitation alone is inadequate to measure the hydrological condition, because both temperature and evapotranspiration are two other critical factors that strongly influence water balance in the ecosystem, meanwhile evapotranspiration is mainly affected by temperature. Based on the validated AIKöppen, we briefly discuss the aridity/humidity condition in China during the middle Miocene. The results demonstrate that moisture did decrease westward, but it is also clear that western China in the middle Miocene appears not to have been as dry as previously thought, indicated by the AIKöppen values representing a sub-humid to humid climate.

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Tesis por compendio / [ES] La mayoría de los estudios científicos pronostican un incremento en la frecuencia y magnitud de los episodios de precipitaciones extremas como consecuencia de los efectos del cambio climático. Además, se espera que en un plazo de 50 años el 80% de la población mundial viva en zonas propensas a inundaciones. Este incremento en la peligrosidad, vulnerabilidad y en la exposición al peligro de lluvias intensas supone un aumento significativo en el riesgo de inundaciones, ya de por si elevado, que manifiesta la urgente necesidad de tomar medidas encaminadas a reducir la vulnerabilidad y desarrollar metodologías capaces de estimar con la mayor precisión posible la magnitud y la probabilidad de ocurrencia de estos posibles fenómenos extremos. En esta última dirección va dirigida la presente tesis doctoral, presentando una nueva metodología basada en el uso de generadores meteorológicos estocásticos para la estimación de la frecuencia de avenidas extremas tanto en escenarios de clima actual como de cambio climático. Más allá del paradigma de la tormenta de diseño y de los estudios tradicionales de análisis de frecuencia de inundaciones, la metodología propuesta en esta tesis se basa en la simulación sintética continua: generador meteorológico estocástico + modelo hidrológico espacialmente distribuido. El uso de generadores meteorológicos estocásticos para el análisis de frecuencia de inundaciones es una práctica cada vez más común dentro de la comunidad hidrológica. Sin embargo, es necesario disponer de observaciones largas y completas para obtener estimaciones de cuantiles confiables para altos períodos de retorno. La novedad que introduce la metodología propuesta se basa en la integración de estudios regionales de precipitación máxima en la implementación del generador meteorológico, lo que reduce considerablemente la incertidumbre en las estimaciones de cuantiles (especialmente aquellos asociados a eventos de baja frecuencia) debida a los usualmente cortos y escasos registros hidrometeorológicos de los que se dispone hasta la fecha. Esta tesis se presenta como un compendio de cinco publicaciones: tres de ellas ya publicadas y dos en proceso de revisión en revistas indexadas en el Journal Citation Report. Estos documentos narran la progresión de la metodología a lo largo de diversas etapas hasta llegar al enfoque final. Inicialmente concebida para el clima actual a escala diaria, la metodología fue posteriormente adaptada a escala subdiaria y finalmente desarrollada para su aplicación en escenarios de clima futuro. A lo largo de este proceso, se abordaron estudios de incertidumbre asociados a la cantidad de información que involucran tanto las estimaciones de cuantiles de precipitación como de inundación. Las metodologías se han implementado en dos casos de estudio: Rambla de la Viuda (Castellón) y; la cuenca del río Segura, cuyos resultados han evidenciado la solidez y eficacia de las metodologías. En el ámbito de la modelización meteorológica, los resultados han sido consistentes y satisfactorios, demostrando la capacidad de la metodología para representar con precisión las complejidades de los patrones climáticos. Asimismo, en el ámbito hidrológico, la metodología ha exhibido una eficaz capacidad para representar y simular los procesos relacionados con el ciclo del agua, ofreciendo resultados coherentes y satisfactorios en la estimación de caudales y eventos de inundación tanto en clima actual como en clima futuro. Esta consistencia en la robustez de la metodología, tanto en la modelización meteorológica como hidrológica, respalda su aplicabilidad y confiabilidad en entornos y condiciones climáticas diversas. / [CA] La majoria dels estudis científics pronostiquen un increment de la freqüència i la magnitud dels episodis de precipitacions extremes a conseqüència dels efectes del canvi climàtic. A més, s'espera que en un termini de 50 anys el 80% de la població mundial habite en zones propenses a inundacions. Aquest acreixement en la perillositat, vulnerabilitat i exposició al perill de pluges intenses suposa un augment significatiu del risc d'inundacions, ja de per si elevat, que manifesta la urgent necessitat de prendre mesures encaminades a reduir la vulnerabilitat i desenvolupar metodologies que permeten estimar amb la major precisió possible la magnitud i la probabilitat d'ocurrència d'aquests possibles fenòmens extrems. En aquesta última direcció va dirigida la present tesi doctoral, que presenta una nova metodologia basada en l'ús de generadors meteorològics estocàstics per a l'estimació de la freqüència d'avingudes extremes, tant en escenaris de clima actual com de canvi climàtic. Més enllà del paradigma de la tempesta de disseny i dels estudis tradicionals d'anàlisis de freqüència d'inundacions, la metodologia proposada en aquesta tesi es basa en la simulació sintètica contínua: generador meteorològic estocàstic + model hidrològic espacialment distribuït. L'ús de generadors meteorològics estocàstics per a l'anàlisi de freqüència d'inundacions és una pràctica cada vegada més comuna dins de la comunitat hidrològica. No obstant això, és necessari disposar d'observacions llargues i completes per a obtindre estimacions de quantils de confiança per a alts períodes de retorn. La novetat que introdueix la metodologia proposada es basa en la integració d'estudis regionals de precipitació màxima en la implementació del generador meteorològic, la qual cosa redueix considerablement la incertesa en les estimacions de quantils (especialment d'aquells associats a esdeveniments de baixa freqüència) a causa dels usualment curts i escassos registres hidrometeorològics dels quals es disposa fins a la data. Auqesta tesi es presenta com un compendi de cinc publicacions: tres d'elles en ja publicades i dos en procés de revisió en revistes indexades en el Journal Citation Report. Aquests documents narren la progressió de la metodologia al llarg de diverses etapes fins arribar a l'enfocament final. Inicialment concebuda per al clima actual a escala diària, la metodologia va ser posteriorment adaptada a escala subdiària i finalment desenvolupada per a la seua aplicació en escenaris de clima futur. Al llarg d'aquest procés, es van abordar estudis d'incertesa associats a la quantitat d'informació que involucren tant les estimacions de quantils de precipitació com d'inundació. Les metodologies s'han implementat en dos casos d'estudi: Rambla de la Vídua (Castelló) i; la conca del riu Segura, els resultats del qual han evidenciat la solidesa i eficàcia de les metodologies. En l'àmbit de la modelització meteorològica, els resultats han estat consistents i satisfactoris, ja que han demostrat la capacitat de la metodologia per a representar amb precisió les complexitats dels patrons climàtics. Així mateix, en l'àmbit hidrològic, la metodologia ha exhibit una eficaç capacitat per a representar i simular els processos relacionats amb el cicle de l'aigua, i ens ha oferit resultats coherents i satisfactoris en l'estimació de cabals i esdeveniments d'inundació tant en clima actual com en clima futur. Aquesta consistència en la robustesa de la metodologia, tant en la modelització meteorològica com en la hidrològica, recolza la seua aplicabilitat i confiabilitat en entorns i condicions climàtiques diverses. / [EN] Most scientific studies predict an increase in the frequency and magnitude of extreme precipitation events as a consequence of climate change effects. Furthermore, it is expected that within 50 years, 80% of the global population will reside in flood-prone areas. This heightened risk, vulnerability, and exposure to intense rainfall hazards signify a significant rise in the flood risk, already elevated. It underscores the urgent need to implement measures to reduce vulnerability and develop methodologies capable of accurately estimating the magnitude and probability of occurrence of these potential extreme events. This doctoral thesis is directed towards this objective, presenting a new methodology based on the use of stochastic weather generators for estimating the frequency of extreme floods in both current and climate change scenarios. Beyond the Design Storm paradigm and traditional Flood Frequency Analysis studies, the methodology proposed in this thesis relies on continuous synthetic simulation: stochastic weather generator + spatially distributed hydrological model. The use of stochastic weather generators for Flood Frequency Analysis is becoming increasingly common within the hydrological community. However, reliable quantile estimates for high return periods require long and complete observations. The innovation introduced by the proposed methodology lies in the integration of regional studies of maximum precipitation into the implementation of the weather generator, significantly reducing uncertainty in quantile estimates (especially those associated with low-frequency events) due to the typically short and limited hydrometeorological records available to date. This thesis is presented as a compilation of five publications: three already published and two under review in journals indexed in the Journal Citation Report. These documents narrate the progression of the methodology through various stages to its final approach. Initially conceived for the current climate at a daily scale, the methodology was later adapted to a subdaily scale and ultimately developed for application in future climate scenarios. Throughout this process, uncertainty studies were addressed concerning the amount of information involving both precipitation and flood quantile estimates. The methodologies have been implemented in two case studies: Rambla de la Viuda (Castellón) and the Segura River basin, with results demonstrating the robustness and effectiveness of the methodologies. In the field of meteorological modeling, the results have been consistent and satisfactory, showcasing the methodology's ability to accurately represent the complexities of climate patterns. Likewise, in the hydrological domain, the methodology has exhibited effective capabilities in representing and simulating processes related to the water cycle, offering coherent and satisfactory results in the estimation of flows and flood events in both current and future climates. This consistency in the robustness of the methodology, both in meteorological and hydrological modeling, supports its applicability and reliability in diverse environmental and climatic conditions. / This work was supported by the Spanish Ministry of Science and Innovation through the research projects TETISCHANGE (RTI2018-093717-B-100) and TETISPREDICT (PID2022-141631OB-I00). Funding for the Open Access charge has been provided by Universitat Politècnica de València / Beneyto Ibáñez, C. (2024). On the Use of Weather Generators for the Estimation of Low-Frequency Floods under a Changing Climate [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/205179 / Compendio