Note:

The influence of climate and antecedent moisture conditions on hydrological and biogeochemical fluxes was studied and contrasted in three nested, high-elevation, snowmelt-dominated catchments in the Sierra Nevada, California and one basin-floor, semi-arid catchment in southeastern Arizona. Investigations were completed within a different two-year period at each site, with the second year being climatically different (typically drier) than the first. Spring snowmelt, widespread winter frontal precipitation, and episodic summer rains induce surface water flow in these catchments, though the timing and magnitude of nutrient redistribution among soil and stream compartments varies in each. Surface water flow from spring snowmelt in high-elevation catchments travels through the subsurface or across the surface as direct runoff A more typical process producing surface water flow in semi-arid catchments is flooding during episodic or widespread rainfall. Hydrograph separations at Emerald Lake, Topaz Lake and Marble Fork catchments in Sequoia National Park, California, revealed that the majority of snowmelt flowed through soil before entering the stream in both average and highsnow years. The Emerald Lake watershed had a higher fraction of old water in its outflow in the average accumulation year because of the previous year's high accumulation and longer melt season. A mixing model analysis performed of the upper San Pedro River, Arizona, for wet and dry years showed that summer flood hydrographs were composed mainly of precipitation and surface runoff in both years, though a higher soil-water input occurred in the wetter year and in early season floods in the dry year. Stream and soil water nitrate concentrations were higher during floods in the dry year. Early season floods in the dry year exhibited more variability in stream water nitrate and sulfate, whereas late season flood concentrations reflected a well-mixed system and therefore less variation of these species during flood hydrographs. These data showed that periods of below average precipitation preceding major runoff periods result both in less soil water and solute export during summer floods in basin-floor catchments and less direct snowmelt in high-elevation catchments. Hydrologic and solute export in each catchment, despite their differing geographical locations, responds in similar ways to climate variability.

The present work focuses on the sources and transport of water vapor to the La Plata Basin (LPB), and the role of groundwater dynamics on the simulation of hydrometeorological conditions over the basin. In the first part of the study an extension to the Dynamic Recycling Model (DRM) is developed to estimate the water vapor transported to the LPB from different regions in South America and the nearby oceans, and the corresponding contribution to precipitation over the LPB. It is found that more than 23% of the precipitation over the LPB is from local origin, while nearly 20% originates from evapotranspiration from the southern Amazon. Most of the moisture comes from terrestrial sources, with the South American continent contributing more than 62% of the moisture for precipitation over the LPB. The Amazonian contribution increases during the positive phase of El Niño and the negative phase of the Antarctic Oscillation. In the second part of the study the effect of a groundwater scheme on the simulation of terrestrial water storage, soil moisture and evapotranspiration (ET) over the LPB is investigated. It is found that the groundwater scheme improves the simulation of fluctuations in the terrestrial water storage over parts of the southern Amazon. There is also an increase in the soil moisture in the root zone over those regions where the water table is closer to the surface, including parts of the western and southern Amazon, and of the central and southern LPB. ET increases in the central and southern LPB, where it is water limited. Over parts of the southeastern Amazon the effects of the groundwater scheme are only observed at higher resolution, when the convergence of lateral groundwater flow in local topographical depressions is resolved by the model. Finally, the effects of the groundwater scheme on near surface conditions and precipitation are explored. It is found that the increase in ET induced by the groundwater scheme over parts of the LPB induces an increase in near surface specific humidity, accompanied by a decrease in near surface temperature. During the dry season, downstream of the regions where ET increases, there is also a slight increase in precipitation, over a region where the model has a dry bias compared with observations. During the early rainy season, there is also an increase in the local convective available potential energy. Over the southern LPB, groundwater induces an increase in ET and precipitation of 13 and 10%, respectively. Over the LPB, the groundwater scheme tends to improve the warm and dry biases of the model. It is suggested that a more realistic simulation of the water table depth could further increase the simulated precipitation during the early rainy season.

Three major teleconnections, Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO), in warm and cool phases, effect precipitation in Florida. The effects of the oscillation phases on the precipitation characteristics are analyzed by using long-term daily precipitation data, on different temporal (annual, monthly, and daily) and spatial scales, utilizing numerous indices, and techniques. Long-term extreme precipitation data for 9 different durations is used to examine the effects of the oscillation phases on the rainfall extremes, by employing different parametric and non-parametric statistical tests, along with Depth-Duration- Frequency analysis. Results show that Florida will experience higher rainfall when AMO is in the warm phase, except in the panhandle and south Florida, while PDO cool phase is positively correlated with precipitation, except for the southern part of the peninsula. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2013.

Previsões probabilísticas de precipitação foram obtidas a partir de um conjunto de simulações pelo modelo WRF e utilizadas como condição de contorno no modelo hidrológico TopModel para previsão hidrometeorológica na bacia do Rio Iguaçu, no estado do Paraná. Nas simulações de cheias, durante o período de elevação do volume de precipitação, o erro médio aritmético do conjunto de previsões foi menor que cada um dos membros utilizados nesse conjunto, indicando melhor destreza do conjunto médio em relação a qualquer previsão determinística. Na dissipação dos sistemas precipitantes, alguns membros obtiveram resultados melhores que o conjunto médio e, em geral, as previsões são confluentes. As melhores previsões de precipitação com o WRF foram obtidas com as combinações de microfísica Lin e convecção de Kain Fritsch, microfísica WSM 5 e convecção de Kain Fritsch e simulações defasadas em 6 horas. As simulações inicializadas em horários mais próximos da ocorrência do fenômeno não garantiram uma melhoria na distribuição de precipitação na bacia. A avaliação do sistema de previsão por conjuntos pelo índice de Brier (IB) e seus termos demonstrou níveis suficientes de confiabilidade e destreza para ser utilizada na maioria dos eventos de precipitação sobre a bacia do rio Iguaçu. Os valores do IB estiveram entre 0,15 e 0,3 com picos isolados. Os valores obtidos para o termo de incerteza estiveram entre 0,1 e 0,25 indicando bons resultados visto que o desejável é o mais próximo de zero. Nos eventos de chuva, o termo de confiabilidade apresentou valores próximos a 0,2 no período da manhã e valores entre 0,3 e 0,4 no período da tarde, com um acréscimo no final da integração. O índice de acerto foi de 60 % a 90 % durante o período de integração (48 horas) para o conjunto médio de previsões e entre 50 a 80% para a previsão determinística. Em todos os horários de simulação o erro de fase foi maior que o erro de amplitude, possivelmente devido aos atrasos da propagação dos sistemas precipitantes e aos efeitos de ajuste das condições físicas iniciais da atmosfera. Os erros de fase e amplitude foram menores na previsão probabilística em todo o período de integração. Assim como na previsão de precipitação, nas simulações de vazão o erro de fase foi maior que o erro de amplitude, indicando que o atraso nas previsões de variação da vazão ainda é o um desafio na previsão hidrometeorológica. Observou-se que o modelo hidrológico é bastante sensível a previsão de precipitação e, portanto, a melhoria das previsões de vazão é diretamente proporcional a diminuição dos erros nas previsões de precipitação. / Probabilistic forecast of precipitation from WRF model simulations was used as input in hydrological TopModel for streamlines forecast in Iguaçu Basin, Parana, southern Brazil. The arithmetic error of precipitation ensemble forecast was smaller than each individual member forecast error in the streamflow increase stage. It means the use of ensemble forecast was better than any deterministic forecast. But when the streamflow decreases, the results are confluent and some individual member forecast was better than ensemble. Simulations using Lin microphysical parameterization and Kain Fritsch, WSM 5 and Kain Fritsch and 6h lagged obtained the better results of precipitation over the basin. The use of runs with initial conditions near the precipitation time did not guarantee better results in the distribution of precipitation on the basin. The Brier Score (BS) of the ensemble system demonstrated that the system is very skillful with values between 0.15 and 0.3. Both uncertainty and reliability terms of BS, 0.1 0.25 and 0.2- 0.4, respectively, were encouraging for use hourly ensemble forecast of precipitation on the watershed. Ensemble forecast provide high values of hit scores (0.6 to 0.9) than deterministic forecast (0.5 to 0.8) at all period of integration. Due the delay in the forecasts of the precipitation systems, the phase error is predominant over amplitude during all time. Both errors were reduced using the ensemble forecasts. The phase errors in hydrological were greater than amplitude such as precipitation forecasts. Thus, for increase streamflow forecast it should reduced the errors in QPF forecasts.

Significant challenges in water resources management arise because of the ever-increasing pressure on the world’s heavily exploited and limited water resources. These stressors include demographic growth, intensification of agriculture, climate variability, and climate change. These challenges to water resources are usually tackled using a top-down approach, which suffers from many limitations including the use of a limited set of climate change scenarios, the lack of methodology to rank these scenarios, and the lack of credibility, particularly on extremes. The bottom-up approach, the recently introduced approach, reverses the process by assessing vulnerabilities of water resources systems to variations in future climates and determining the prospects of such wide range of changes. While it solves some issues of the top-down approach, several issues remain unaddressed. The current project seeks to provide end-users and the research community with an improved version of the bottom-up framework for streamlining climate variability into water resources management decisions. The improvement issues that are tackled are a) the generation of a sufficient number of climate projections that provide better coverage of the risk space; b) a methodology to quantitatively estimate the plausibility of a future desired or undesired outcome and c) the optimization of the size of the projections pool to achieve the desired precision with the minimum time and computing resources. The results will hopefully help to cope with the present-day and future challenges induced mainly by climate. In the first part of the study, the adequacy of stochastically generated climate time series for water resources systems risk and performance assessment is investigated. A number of stochastic weather generators (SWGs) are first used to generate a large number of realizations (i.e. an ensemble of climate outputs) of precipitation and temperature time series. Each realization of the generated climate time series is then used individually as an input to a hydrological model to obtain streamflow time series. The usefulness of weather generators is evaluated by assessing how the statistical properties of simulated precipitation, temperatures, and streamflow deviate from those of observations. This is achieved by plotting a large ensemble of (1) synthetic precipitation and temperature time series in a Climate Statistics Space (CSS), and (2) hydrological indices using simulated streamflow data in a Risk and Performance Indicators Space (RPIS). The performance of the weather generator is assessed using visual inspection and the Mahalanobis distance between statistics derived from observations and simulations. A case study was carried out using five different weather generators: two versions of WeaGETS, two versions of MulGETS and the k-nearest neighbor weather generator (knn). In the second part of the thesis, the impacts of climate change, on the other hand, was evaluated by generating a large number of representative climate projections. Large ensembles of future series are created by perturbing downscaled regional climate models’ outputs with a stochastic weather generator, then used as inputs to a hydrological model that was calibrated using observed data. Risk indices calculated with the simulated streamflow data are converted into probability distributions using Kernel Density Estimations. The results are dimensional joint probability distributions of risk-relevant indices that provide estimates of the likelihood of unwanted events under a given watershed configuration and management policy. The proposed approach offers a more complete vision of the impacts of climate change and opens the door to a more objective assessment of adaptation strategies. The third part of the thesis deals with the estimation of the optimal size of SWG realizations needed to calculate risk and performance indices. The number of realizations required to reach is investigated utilizing Relative Root Mean Square Error and Relative Error. While results indicate that a single realization is not enough to adequately represent a given stochastic weather generator, results generally indicate that there is no major benefit of generating more than 100 realizations as they are not notably different from results obtained using 1000 realizations. Adopting a smaller but carefully chosen number of realizations can significantly reduce the computational time and resources and therefore benefit a larger audience particularly where high-performance machines are not easily accessible. The application was done in one pilot watershed, the South Nation Watershed in Eastern Ontario, yet the methodology will be of interest for Canada and beyond. Overall, the results contribute to making the bottom-up more objective and less computationally intensive, hence more attractive to practitioners and researchers.

Using ERA40 and independent observations, I assess how well Amazon surface water budget is estimated. ERA40 basin wide annual precipitation (P) agrees with observations showing an underestimation of 10%, whereas runoff (R) is underestimated by a larger margin (~25%). Observed residual of precipitation and runoff (P-R) is better estimated by ERA40 P-R than actual ET which includes soil moisture nudging. Nudging is necessary during the dry season to produce realistic ET and compensate for low soil moisture recharge during the wet season. Insufficient recharge may be caused by: underestimation of rainfall amount and intensity; a shallow root layer in the model that does not represent the deep soil water reservoir of the Amazonian forest. The physical links between changes in wet season onset and synoptic scale systems are investigated in the second part of my work. A delayed wet season onset is consistent with a decreasing number of cold air incursion (CAI) days in southern Amazon during 1979-2001. CAI variability in southern Amazon is related to SST in the tropical Pacific and Indian Oceans. The first mode of co-variability shows that during El Nio (La Nia) a strong (weak) subtropical jet stream over South America is related to decreased (increased) CAI days during SON. The second mode shows warm western Indian Ocean also related to strong subtropical jet stream. The absence a well defined subpolar jet stream, favors the northward displacement of transient waves into central South America, but shows little response in southern Amazon. CAI days reconstructed from the first and second modes do not present any significant trend in southern Amazon. CAI days reconstructed from the third mode of co-variability reproduces SON observed trend. This mode describes negative (positive) anomalies in CAI days associated with cold (warm) SST anomalies, anomalous wavetrain in the tropical Pacific and Walker Cell displacement that are unfavorable (favorable) to the incursion of CAI into southern Amazon. This mode's temporal evolution correlates with the Pacific Decadal Oscillation (PDO), suggesting that its recent gradual signal shift reflected on the interannual response of southern Pacific atmospheric patterns, hence on the behavior of transients propagation.

Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Environmental Sciences." Includes bibliographical references (p. 106-112).

The South Saskatchewan River Basin (SSRB) is amongst the largest watersheds in Canada. It is an ecologically diverse region, containing Montane Cordillera, Boreal Plains and Prairie ecozones. The SSRB is subject to chinooks, which bring strong winds, high temperatures and humidity deficits that alter the storage of water during winter. Approximately 40% of winter days experience chinooks. Ablation during chinooks has not been quantified; it is not known how much water evaporates, infiltrates or runs off. The aim of this thesis is to characterise the spatial variability of surface water fluxes as affected by chinooks over SSRB subbasins and ecozones. The objectives are addressed using detailed field observations and physically based land surface modelling. Eddy covariance was deployed at three prairie sites. During winter chinooks, energy for large evaporative fluxes were provided by downward sensible heat fluxes. There was no evidence of infiltration until March. The Canadian Land Surface Scheme (CLASS) coupled to the Prairie Blowing Snow Model (PBSM) was used as the modelling platform. A multi-physics version of CLASSPBSM was developed, consisting of two parameterisation options each for sixteen processes. Field observations were used to evaluate each of the configurations. Three parameterisations provide both best snow and best soil water simulations: iterative energy balance solution, air temperature and wind speed based fresh snow density and de Vries’ soil thermal conductivity. The model evaluation highlighted difficulties simulating evaporation and uncertainty in simulating infiltration into frozen soils at large scales. A single model configuration is selected for modelling the SSRB. Modelling showed that the SSRB generally experiences no net soil water storage change until March, confirming field observations. Chinooks generally reduce net terrestrial water storage, largely due to snowmelt and subsequent evaporation and runoff. The Prairie ecozone is that which is most strongly affected by chinooks. The Montane Cordillera ecozone is affected differently by chinooks; blowing snow transport increases during winter and runoff increases during spring. The Lower South Saskatchewan is the subbasin most affected by chinooks. The Red Deer is the subbasin least affected by chinooks.

Le 22 Août 2005 une crue intense s'est produite sur le bassin versant du Vorz, détruisant partiellement le hameau de la Gorge. Cet évènement a mis en évidence les difficultés à anticiper les conditions hydrométéorologiques en montagne où elles sont extrêmement variables spatialement et temporellement, et souvent faiblement instrumentées. De ce constat est né le projet de mettre en place un réseau d'instrumentation hydrométéorologique original sur le bassin versant du Vorz, afin d'y observer les phénomènes naturels et hydrologiques s'y produisant, de mieux les appréhender, et de construire les outils et méthodes nécessaires à leur modélisation. Après deux saisons de mesures, les premiers résultats ont montré que le réseau mis en place permet d'obtenir des informations à haute résolution spatiale et temporelle sur les processus hydrométéorologiques. Malgré son installation dans le milieu difficile de la montagne (accessibilité, froid, énergie,...), une très bonne fiabilité a pu être mise en avant, ainsi que des perspectives de transposition à d'autres bassins versants, et ce, pour un faible coût financier. L'originalité du réseau est de réaliser un multi-échantillonnage de nombreux paramètres hydrométéorologiques (pluviométrie, température, neige, insolation,...), avec des résolutions spatiales (10 à 50 mètres) et temporelles (horaire à moins) permettant d'envisager une modélisation hydrologique à différentes échelles, aussi bien pour la gestion des ressources en eau (long terme) que pour la prévention des crues (court terme). Les capteurs mis en place constituent un ensemble complémentaire et indissociable de divers instruments de mesure: iButtons (air et sol), totalisateurs, pluviomètres, appareils photographiques. La mise au point d'un capteur de mesure innovant de cartographie automatique de la couverture neigeuse (SnoDEC), à partir d'images photographiques classiques, prises à pas de temps régulier (5 à 7 images par jours) a été réalisée au cours de ce travail. Il permet de quantifier l'hérogénéité spatiale et temporelle des phénomènes d'enneigement sur le versant, prépondérants sur son hydrologie, au vue de la persistance nivale (5 à 10 mois). L'ensemble de ce dispositif permet de disposer d'une importante base de données, et de mettre en oeuvre différentes techniques d'interpolations des variables hydrométéorologiques sur l'ensemble du bassin versant. Ainsi, des cartographies précises du champ de température et de pluviométrie seront disponibles au pas de temps journalier. En outre, le capteur SnoDEC permettra d'analyser et quantifier l'hétérogénétité spatio-temporelle (altitude, exposition, vitesse de fonte,...) de la couverture nivale. A partir de ces données, on pourra mieux appréhender les mécanismes hydrologiques en jeu sur le site et dessiner les contours des modélisations futures. Dans le même temps, les données disponibles pourront être combinées afin de mettre en évidence des phénomènes difficilement mesurables (limite pluie/neige, inversion thermiques,...), qui serviront à l'avenir à contraindre de manière précise les modèles nivologiques et hydrologiques. Au travers des différents paramètres instrumentés, et grâce à l'utilisation de l'imagerie, ce réseau est capable de mesurer des variables relevant de nombreux champs disciplinaires (dynamique glaciaire, cyle végétatif,...). Il s'inscrit ainsi, par son approche interdisciplinaire, dans une volonté de mise en place d'un réseau de mesure à coût limité, destiné à l'ensemble des acteurs de l'étude et la recherche des milieux de la montagne. / In August 2005, a intense flashflood occurs on the Vorz catchment affecting the village of Saint-Agnès. This event highlighed the difficulties to forecast the hydrometeorological conditions in mountain areas where they are extremely variable in space and time (spatially and temporally) and frequently poored monitored. From this observation a project was funded to implement an original meteorological monitoring system on the catchment, in order to observe the natural and hydrologic phenomena to better understand them and to build methods and tools for their modeling. After two years of monitoring, the first results showed that the network implement allows to obtain informations on hydrometeorological process at high spatial and temporal resolution. In spite of the installation in a harsh mountain environment (access, cold, energy,...) a very good reliability, and a lot of perspectives of transpositon on other catchments have been point up for low investment costs.The originality of the network is to achieved a multi-sampling on a lot of hydrometeorological parameters (rain, temprature, snow, insulation,...), with spatial (10 to 50 meters) and temporal (hourly or less) resolution to performed a hydrological modeling at different scale both for the water ressource management (long term) or flashflood prevention (short term). The Sensors use in the network constitute a complementary and indivisible set of monitoring system: iButtion (air and soil temperature), rain gauge, totalizer, cameras. The development of an innovative sensor for automatic cartography of the snow cover (SnoDEC) from terrestrail photographies was achived during this work. This sensor allows to quantify spatial and temporal heterogeneity of snow cover evolution on the catchment, with images taken at regular time steps (5 to 7 frames per day). This heterogenity is essential for understand and modelling the hydrology considering the strong snow persistence (5 to 10 months). The dense network set up on the catchment enable us to collect a large database and implement different interpolation techniques on hydrometeorological process on the catchment. Thus, accurate maps of temperatures and rain are created with a daily or hourly timestep. Furthermore, the SnoDEC sensor will permit to analyse and quantify the spatial and temporal heterogeneity (elevation, aspect, velocity of melting,...) of the snow cover. From the database, we will better understand the hydrological mechanisms occuring on the site, and we will build the first ideas and method for the future modelisation. In the same time, the available data will be combinate in order to highlight phenomena very difficult to measure (rain/snow limit, thermical inversion,...) and that will be use in the future to constraint accurately the snow and hydrologic models. Because of the different parameters monitored and the use of imagery, the network is able to measure variables from many field of study (glacier dynamic, vegetative cycle,...). Thereby, with its interdisciplinary approach the network think to implement a monitoring system at low cost in destination of the actors of study and research in mountain.