An assessment of simulated runoff from global models

This thesis assesses long-term runoff projections from global multi-model ensembles used in hydrological impact studies. Firstly, the study investigates global-scale changes in frequency of high and low flow days towards the end of the current century, quantifying the relative contribution to uncertainty from global climate (GCMs) and global impact models (GIMs). Results show increases in high flows for northern latitudes and in low flows for several hotspots worldwide. Overall, GCMs provide the largest uncertainty; but GIMs are the greatest source of uncertainty in snow-dominated regions. Secondly, the ability of a set of GIMs to reproduce observed runoff is evaluated at the regional scale, indicating that GIMs capture well trends in low, medium, and high flows, but differ from observations with respect to medium and high flows timing. Thirdly, the contribution to uncertainty from GCMs, GIMs, Representative Concentration Pathways (RCPs), and internal variability is quantified for transient runoff until 2099. Over the USA, GCMs and GIMs are responsible for the largest uncertainty. Efforts to improve runoff projections should thus focus on GCMs and GIMs. In particular, GIMs should be evaluated in the region of study, so that models reproducing unrealistic runoff can be excluded, potentially yielding greater confidence in ensemble projections

Going Beyond the Ensemble Mean: Assessment of Future Floods From Global Multi‐Models

Future changes in the occurrence of flood events can be estimated using multi-model ensembles to inform adaption and mitigation strategies. In the near future, these estimates could be used to guide the updating of exceedance probabilities for flood control design and water resources management. However, the estimate of return levels from ensemble experiments represents a challenge: model runs are affected by biases and uncertainties and by inconsistencies in simulated peak flows when compared with observed data. Moreover, extreme value distributions are generally fit to ensemble members individually and then averaged to obtain the ensemble fit with loss of information. To overcome these limitations, we propose a Bayesian hierarchical model for assessing changes in future peak flows, and the uncertainty coming from global climate, global impact models and their interaction. The model we propose allows use of all members of the ensemble at once for estimating changes in the parameters of an extreme value distribution from historical to future peak flows. The approach is applied to a set of grid-cells in the eastern United States to the full and to a constrained version of the ensemble. We find that, while the dominant source of uncertainty in the changes varies across the domain, there is a consensus on a decrease in flood magnitudes toward the south. We conclude that projecting future flood magnitude under climate change remains elusive due to large uncertainty mostly coming from global models and from the intrinsic uncertain nature of extreme values

Evaluation of global impact models' ability to reproduce runoff characteristics over the central United States

The central United States experiences a wide array of hydrological extremes, with the 1993, 2008, 2013, and 2014 flooding events and the 1988 and 2012 droughts representing some of the most recent extremes, and is an area where water availability is critical for agricultural production. This study aims to evaluate the ability of a set of global impact models (GIMs) from the Water Model Intercomparison Project to reproduce the regional hydrology of the central United States for the period 1963–2001. Hydrological indices describing annual daily maximum, medium and minimum flow, and their timing are extracted from both modeled daily runoff data by nine GIMs and from observed daily streamflow measured at 252 river gauges. We compare trend patterns for these indices, and their ability to capture runoff volume differences for the 1988 drought and 1993 flood. In addition, we use a subset of 128 gauges and corresponding grid cells to perform a detailed evaluation of the models on a gauge-to-grid cell basis. Results indicate that these GIMs capture the overall trends in high, medium, and low flows well. However, the models differ from observations with respect to the timing of high and medium flows. More specifically, GIMs that only include water balance tend to be closer to the observations than GIMs that also include the energy balance. In general, as it would be expected, the performance of the GIMs is the best when describing medium flows, as opposed to the two ends of the runoff spectrum. With regards to low flows, some of the GIMs have considerably large pools of zeros or low values in their time series, undermining their ability in capturing low flow characteristics and weakening the ensemble's output. Overall, this study provides a valuable examination of the capability of GIMs to reproduce observed regional hydrology over a range of quantities for the central United States

Uncertainties in projected runoff over the conterminous United States

Projections of runoff from global multi-model ensembles provide a valuable basis for the estimation of future hydrological extremes. However, projections suffer from uncertainty that originates from different error sources along the modeling chain. Hydrological impact studies have generally partitioned these error sources into global impact and global climate model (GIM and GCM, respectively) uncertainties, neglecting other sources, including scenarios and internal variability. Using a set of GIMs driven by GCMs under different representative concentration pathways (RCPs), this study aims to partition the uncertainty of future flows coming from GIMs, GCMs, RCPs, and internal variability over the CONterminous United States (CONUS). We focus on annual maximum, median, and minimum runoff, analyzed decadally over the twenty-first century. Results indicate that GCMs and GIMs are responsible for the largest fraction of uncertainty over most of the study area, followed by internal variability and to a smaller extent RCPs. To investigate the influence of the ensemble setup on uncertainty, in addition to the full ensemble, three ensemble configurations are studied using fewer GIMs (excluding least credible GIMs in runoff representation and GIMs accounting for vegetation and CO2 dynamics), and excluding intermediate RCPs. Overall, the use of fewer GIMs has a minor impact on uncertainty for low and medium flows, but a substantial impact for high flows. Regardless of the number of pathways considered, RCPs always play a very small role, suggesting that improvement of GCMs and GIMs and more informed ensemble selections can yield a reduction of projected uncertainties

Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by biascorrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty

A participatory web-GIS system associated to decentralized flood risk management indicators

A presente pesquisa propôs o desenvolvimento e a aplicação de um web-GIS interativo alimentado por usuários visando ao mapeamento do risco de inundações por meio da coleta de dados de ameaça, exposição e vulnerabilidade percebidos pela população. Foi também estimado o risco de inundação a partir de uma expressão de indicadores propostos por Mendiondo (2008). As duas metodologias foram aplicadas em sub-bacias urbanas da cidade de São Carlos. Foram realizadas entrevistas com a população da cidade para coletar dados de percepção de risco, enquanto se desenvolvia o web-GIS, para o qual, uma vez terminado, foram transferidos os referidos dados online. O portal se mostrou uma ferramenta de uso simples e confiável. As estimativas de risco calculadas por meio da expressão citada levaram a concluir que as sub-bacias com maior risco de inundação são as dos córregos Tijuco Preto e Medeiros. Entretanto, o risco estimado a partir da análise de percepção evidenciou as sub-bacias Gregório e Santa Maria Madalena como as de maior risco de inundação. As duas ferramentas apresentaram-se valiosas e econômicas para estimativa de risco de inundação em ambiente urbano, podendo constituir ótimos sistemas de apoio à decisão. O webGIS, em particular, é potencialmente útil para informar aos moradores sobre quais são as áreas de risco de inundação na cidade.This dissertation presents the development and application of an interactive web-GIS in which internet users map flood risk collaboratively by filling up a geotagged form with questions on flood hazard, exposure and vulnerability. Flood risk was also assessed through the use of a set of environmental risk indicators proposed by Mendiondo (2008). The two methodologies were applied to six urban watersheds of the city of São Carlos (State of São Paulo, Brazil). Interviews including questions asked on the web-GIS were carried out in city streets while the portal was being developed. Thus perceived risk data gathered from the interviews was later transferred online onto the web-GIS. The web-GIS proved to be an easy to use and intuitive tool. According to the results of risk calculation obtained with the indicators expression the watersheds with higher flood risk were the Tijuco Preto and Medeiros, which were also the ones with smallest area and higher population density. The results of perceived risk, which was assessed through the analysis of the interviews data, gave evidence that Gregorio and Santa Maria Madalena where the watersheds at higher risk. These watersheds are the two which experience a higher rate of occurrence on a year basis. The two approaches for assessing risk proved to be consistent and relatively inexpensive for the estimate of flood risk in urban areas, with the potential of representing valid decision support systems. The webGIS is a particularly interesting solution as a medium of information to inhabitants on the level of risk to which they are exposed

Evolutions observées dans les débits des rivières en France

Synthèse vulgarisée de plusieurs rapports techniquesInternational audienceLes situations de pénurie d'eau (étiages accentués en rivière, baisses soutenues de nappes phréatiques) font l'objet d'une attention croissante notamment en raison de l'observation de l'augmentation de déséquilibres en diverses régions entre ressources et usages de toutes natures. Ces déséquilibres, plus apparents encore à travers les sécheresses récentes-en dépit du retour d'années humides-risquent, pour une part au moins, d'être aggravés par les perspectives de changement climatique, mais aussi plus généralement de changement global (démo-graphie, demandes agricole et énergétique, urbanisation...). La France bénéficie d'un réseau de suivi des débits des rivières excep-tionnel par son étendue et son ancienneté. Il a été possible d'analyser avec des outils mathématiques l'évolution sur ces quarante dernières années de caractéristiques hydrologiques fondamentales comme les étiages, le débit moyen (ou module), et les hautes eaux. Il en ressort des évolutions significatives sur certains territoires et pour certaines variables, allant globalement dans le sens d'une raréfaction de la ressource, et d'une aggravation des étiages