A key piece of information necessary for water management is accurate streamflow information. However, the available data and resources for gathering information vary around the world. This study forms a part of a research effort to improve discharge estimations for a montane rainforest stream located in the San Lorencito headwater catchment in Costa Rica. The aim of this study is to improve the current rating curve where the high flow part is currently ungauged and look at the impact of adding a high flow estimation to the rating curve. When adding information that is not gauged data, it is important to make sure that the information is unbiased. It can also be questioned if information based on less accurate observations will aid a model. The high flow estimation in this study was calculated using the Manning’s equation based on a survey after a flood event in August 2015. Field measurements were performed at the location in February 2017 and were added to the already existing data record from the gauging station dating back to 2015. Based on the previous data together with the new measurements, rating curves and corresponding hydrographs were established. The impact of adding the Manning’s estimation included a statistical assessment and comparison of the different rating curves and hydrographs. Results showed that at higher flows, the rating curve without the Manning’s point estimated higher discharge than the rating curve determined including the Manning’s point. However, at low flows below 0.9 𝑚3/𝑠 (or around a stage of 0.4 𝑚), the rating curve without the Manning’s point is estimating less discharge than the rating curve including the Manning’s point. Error plots and the uncertainty intervals in the graphs illustrate that the uncertainty at high flows are reduces when including a high flow estimation. The results suggest that it is preferable to add information, even if it has a lot of uncertainty, to no information at all. / Pålitlig flödestatistik och god kunskap gällande vattenföringen i vattendrag är mycket viktiga förutsättningarna för att kunna förvalta vattenresurser på ett hållbart sätt. Tyvärr har inte alla länder samma möjligheter och resurser att samla in den nödvändiga informationen vilket leder till att tillgänglig data är begränsad i vissa delar av världen. Denna studie utgör en del av ett forskningsprojekt i Costa Rica vars syfte är att förbättra uppskattningen av vattenföringen för ett vattendrag som rinner genom ett regnskogsområde. Målet med denna studie är att förbättra den nuvarande avbördningskurvan och undersöka effekten av att lägga till uppskattade värden för höga flöden där det för tillfället saknas data. Under februari 2017 genomfördes flödesmätningar på plats i Costa Rica. Mätningarna användes tillsammans med tidigare uppmätt flödesdata för att bestämma avbördningskurva och motsvarande hydrograf. För att uppskatta det höga flödet användes Mannings ekvation. Beräkningar har utgått från en störtflod som skedde i augusti 2015 och parametrar till ekvationen har baserats på de spår vattnet orsakad på terrängen och vegetation som kunde observeras i efterhand. Slutligen har en statistik bedömning genomförts där effekten på avbördningskurvan och hydrografen av att inkludera en vattenföringspunkt beräknad med Mannings ekvation har studerats. Följden av att ta med en Manningspunkt innebar att avbördningskurvan planades ut och inte uppskattade lika drastiska vattenföringar vid höga vattennivåer. Vid låga flöden under 0.9 𝑚3/𝑠 uppskattade däremot avbördningskurvan med Manningspunkten lägre vattenföring än kurvan utan Manningspunkten. Genom att introducera ett uppskattat vattenföringsvärde med Mannings ekvation minskade osäkerheten för avbördningskurvan och hydrografen vid höga flöden. Resultaten antyder att det är fördelaktigt att införa uppskattade värden där det saknas information.

The transfer of sparingly soluble gases across the air-water interface has significant effects on the distribution of the constituents in aquatic ecosystems. Gas-liquid transfer rate determines the flux of the sparingly soluble gases driven by the concentration difference. Considerable stream-driven gas-liquid transfer rate formulae have been developed. They have reasonable predictions in one-dimensional uniform flows. However, their applications in more complex cases such as three-dimensional flows are problematic. Furthermore, the wind effects are not incorporated into these formulae. New models need to be developed for gas-liquid transfer rate in three-dimensional flows that incorporate the effects of both wind and streamflow. In this study, first, a model of gas-liquid transfer rate in non-isotropic turbulent flows is developed. Second, a general stream-driven gas-liquid transfer rate model is developed for the normal ranges of water depth and flow velocity in natural rivers. Third, a wind-stream-driven gas-liquid transfer rate model is developed. Fourth, a model of surface renewal rate caused by turbulence from transition location of shear flows is developed. Fifth, a gas-liquid transfer rate model for wind and dynamic three-dimensional flow systems is developed. A computer program is coded and applied to various cases from simple one-dimensional uniform flow systems to complex wind and dynamic three-dimensional flow systems. A specific model can be selected from the series models for a specific application based on the application requirements and the acceptable computation complexity.

No description available.

<p>Traditional methods for flood estimation can be categorized as (1) simplified methods, e.g., regression analysis, (2) frequency analysis of streamflow data, (3) design storm-based precipitation-runoff modeling, and ( 4) continuous precipitation-runoff simulation modeling. The new approach - the Analytical Probabilistic Stormwater Model - was developed as an alternative to provide an efficient way of getting realistic estimation of peak discharges of desired frequencies for use in stormwater management of urban areas. To extend APSWM's application to rural areas, a series of comparisons were made between the calibrated design storm-based OTTHYMO model results, frequency analysis results and APSWM results for the Ganaraska River watershed. Special considerations were given to the transformation of the input parameter values of OTTHYMO model to those of APSWM. Comparable results were obtained for large floods, while APSWM may underestimate peak discharges of low return periods. Upon further testing and development, APSWM may be used for large rural areas.</p> / Thesis / Master of Engineering (MEngr)

Several different approaches are applied in low flow frequency analysis. Each method's theory and application is explained. The methods are (1) physically based recession model dealing with time series, (2) log-Pearson type III and mixed log-Pearson type III using annual minimum series, (3) Double Bounded pdf using annual minimum series, (4) Partial Duration Series applying truncated and censored flows. Each method has a computer program for application. One day low flow analysis was applied to 15 stations, 10 perennial streams and 5 intermittent streams. The physically based method uses the exponential baseflow recession with duration, initial recession flow, and recharge due to incoming storm as random variables, and shows promise as an alternative to black box methods, and is appealing because it contains the effect of drought length. Log-Pearson is modified to handle zero flows by adding a point mass probability for zero flows. Another approach to zero flows is the Double Bounded probability density function which also includes a point mass probability for zero flows. Maximum likelihood estimation is used to estimate distribution parameters. Partial Duration Series is applied due to drawbacks of using only one low flow per year in annual minimum series. Two approaches were used in Partial Duration Series (i) truncation, and (ii) censorship which represent different low flow populations. The parameters are estimated by maximum likelihood estimation. / M.S.

Tennessee has a long history of meteorological hazards that have caused property damage and loss of life. Given climate change and variability, it is imperative to look at trends to ascertain changes spatiotemporally. Space-time cubes, a novel geographic tool, were used to analyze historical heavy precipitation (1-, 2-, and 5-year returns), floods, and flash flood data in Tennessee counties to assess the trends, identify emerging hotspots/cold spots and display changes over space and time. For all return periods, trends analysis revealed that heavy precipitation events are increasing in several counties across the state, with middle Tennessee identified as a hotspot. While floods and flash flood event trends are mixed (with both increases and decreases) across the state counties, related property damages are increasing, especially in middle Tennessee. This study is an important step to understanding spatiotemporal trends and will be useful in federal, state, and county hazard mitigation planning.

Algumas abordagens para o problema de Planejamento Ótimo da Operação de Sistemas Hidrotérmicos (POOSH) utilizam modelos estocásticos para representar as vazões afluentes dos reservatórios do sistema. Essas abordagens utilizam, em geral, técnicas de Programação Dinâmica Estocástica (PDE) para resolver o POOSH. Por outro lado, muitos autores têm defendido o uso dos modelos determinísticos ou, particularmente, a Programação Dinâmica Determinística (PDD) por representar de forma individualizada a interação entre as usinas hidroelétricas do sistema. Nesse contexto, esta dissertação tem por objetivo comparar o desempenho da solução do POOSH obtida via PDD com a solução obtida pela PDE, que emprega um modelo Markoviano periódico, com distribuição condicional Log-Normal Truncada para representar as vazões. Além disso, é realizada a análise com abordagem bayesiana, no modelo de vazões, para estimação dos parâmetros e previsões das vazões afluentes. Comparamos as performances simulando a operação das usinas hidroelétricas de Furnas e Sobradinho, considerando séries de vazões geradas artificialmente / Some approaches for problem of Optimal Operation Planning of Hydrothermal Systems (OOPHS) use stochastic models to represent the inflows in the reservoirs that compose the system. These approaches typically use the Stochastic Dynamic Programming (SDP) to solve the OOPHS. On the other hand, many authors defend the use of deterministic models and, particularly, the Deterministic Dynamic Programming (DDP) since it individually represents the interaction between the hydroelectric plants. In this context, this dissertation aims to compare the performance of the OOPHS solution obtained via DDP with the one given by SDP, which employs a periodic Markovian model with conditional Truncated Log-Normal distribution to represent the inflows. Furthermore, it is performed a bayesian approach analysis, in the inflow model, for estimating the parameters and forecasting the inflows. We have compared the performances of the DDP and SDP solutions by simulating the hydroelectric plants of Furnas and Sobradinho, employing artificially generated series

Study region Nyangores River watershed, headwater catchment of Mara River basin in Kenya. Study focus Climate variability and human activities are the main drivers of change of watershed hydrology. The contribution of climate variability and land use change to change in streamflow of Nyangores River, was investigated. Mann Kendall and sequential Mann Kendall tests were used to investigate the presence and breakpoint of a trend in discharge data (1965–2007) respectively. The Budyko framework was used to separate the respective contribution of drivers to change in discharge. Future response of the watershed to climate change was predicted using the runoff sensitivity equation developed. New hydrological insights for the region There was a significant increasing trend in the discharge with a breakpoint in 1977. Land use change was found to be the main driver of change in discharge accounting for 97.5% of the change. Climate variability only caused a net increase of the remaining 2.5% of the change; which was caused by counter impacts on discharge of increase in rainfall (increased discharge by 24%) and increase in potential evapotranspiration (decreased discharge by 21.5%). Climate change was predicted to cause a moderate 16% and 15% increase in streamflow in the next 20 and 50 years respectively. Change in discharge was specifically attributed to deforestation at the headwaters of the watershed.

Algumas abordagens para o problema de Planejamento Ótimo da Operação de Sistemas Hidrotérmicos (POOSH) utilizam modelos estocásticos para representar as vazões afluentes dos reservatórios do sistema. Essas abordagens utilizam, em geral, técnicas de Programação Dinâmica Estocástica (PDE) para resolver o POOSH. Por outro lado, muitos autores têm defendido o uso dos modelos determinísticos ou, particularmente, a Programação Dinâmica Determinística (PDD) por representar de forma individualizada a interação entre as usinas hidroelétricas do sistema. Nesse contexto, esta dissertação tem por objetivo comparar o desempenho da solução do POOSH obtida via PDD com a solução obtida pela PDE, que emprega um modelo Markoviano periódico, com distribuição condicional Log-Normal Truncada para representar as vazões. Além disso, é realizada a análise com abordagem bayesiana, no modelo de vazões, para estimação dos parâmetros e previsões das vazões afluentes. Comparamos as performances simulando a operação das usinas hidroelétricas de Furnas e Sobradinho, considerando séries de vazões geradas artificialmente / Some approaches for problem of Optimal Operation Planning of Hydrothermal Systems (OOPHS) use stochastic models to represent the inflows in the reservoirs that compose the system. These approaches typically use the Stochastic Dynamic Programming (SDP) to solve the OOPHS. On the other hand, many authors defend the use of deterministic models and, particularly, the Deterministic Dynamic Programming (DDP) since it individually represents the interaction between the hydroelectric plants. In this context, this dissertation aims to compare the performance of the OOPHS solution obtained via DDP with the one given by SDP, which employs a periodic Markovian model with conditional Truncated Log-Normal distribution to represent the inflows. Furthermore, it is performed a bayesian approach analysis, in the inflow model, for estimating the parameters and forecasting the inflows. We have compared the performances of the DDP and SDP solutions by simulating the hydroelectric plants of Furnas and Sobradinho, employing artificially generated series

Study region Nyangores River watershed, headwater catchment of Mara River basin in Kenya. Study focus Climate variability and human activities are the main drivers of change of watershed hydrology. The contribution of climate variability and land use change to change in streamflow of Nyangores River, was investigated. Mann Kendall and sequential Mann Kendall tests were used to investigate the presence and breakpoint of a trend in discharge data (1965–2007) respectively. The Budyko framework was used to separate the respective contribution of drivers to change in discharge. Future response of the watershed to climate change was predicted using the runoff sensitivity equation developed. New hydrological insights for the region There was a significant increasing trend in the discharge with a breakpoint in 1977. Land use change was found to be the main driver of change in discharge accounting for 97.5% of the change. Climate variability only caused a net increase of the remaining 2.5% of the change; which was caused by counter impacts on discharge of increase in rainfall (increased discharge by 24%) and increase in potential evapotranspiration (decreased discharge by 21.5%). Climate change was predicted to cause a moderate 16% and 15% increase in streamflow in the next 20 and 50 years respectively. Change in discharge was specifically attributed to deforestation at the headwaters of the watershed.