From the Proceedings of the 1972 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - May 5-6, 1972, Prescott, Arizona / In order to design culverts and bridges, it is necessary to compute an estimate of the design flood. Regionalization of flows by regression analysis is currently the method advocated by the U.S. Geological Survey to provide an estimate of the culvert and bridge design floods. In the regression analysis a set of simultaneous equations is solved for the regression coefficients which will be used to compute a design flood prediction for a construction site. The dependent variables in the set of simultaneous equations are the historical estimates of the design flood computed from the historical records of gaged sites in a region. If a log normal distribution of the annual peak flows is assumed, then the historical estimate of the design flood for site i may be computed by the normal as log Q(d,i) = x(i) + k(d)s(i). However because of the relatively small samples of peak flows commonly used in this problem, this paper shows that the historical estimate should be computed by to log Q(d,i) = X(i) + t(d,n-1) √((n+1)/n) s(i) where t(d,n-1) is obtained from tables of the Student's t. This t-estimate when used as input to the regression analysis provides a more realistic prediction in light of the small sample size, than the estimate yielded by the normal.

Since 1971, a number of flood frequency models have been developed for river basins in Malawi for use in the design of hydraulic structures, but the varied nature of their results have most often given a dilemma to the design engineer due to differences in magnitudes of calculated floods for given return periods. All the known methods for flood frequency analysis developed in country so far have not used a homogeneity test for the river basins from which the hydrological data has been obtained. This study was thus conducted with a view to resolving this problem and hence improve the design of hydraulic structures such as culverts, bridges, water intake points for irrigation schemes, and flood protection dykes. In light of the above, during the course of this study the applicability of existing methods in the design of hydraulic structures was assessed. Also, the study investigated how land use and land cover change influence the frequency and magnitude of floods in the study area, and how their deleterious impacts on the socio-economic and natural environment in the river basins could be mitigated / Environmental Sciences / M. Sc. (Environmental Management)

The rapid urban growth in many Brazilian cities in the twentieth century occurred without the proper planning and infrastructure. In these cities, floods cause great material and human losses every year. Therefore, the authorities and community must propose and implement flood control measures after detailed studies of the characteristics of the watershed . Thus, hydrological simulations of the stream Jataí watershed located in Uberlândia/MG, was performed using the software ABC - Complex Watershed Analysis, from the University of São Paulo considering the return period of 100 years for the project rain. This watershed has an area of 15.99 km² and was discretized by sub-basins considering the land use and occupation at the current urbanization and critical scenario (fully urbanized and occupied basin). The damping reservoir existent in the study area were considered in the simulations and it was proposed the implementation of a parallel damping reservoir near to the watershed output. The sub-basins 02 and 08 simulated alone at the critical scenario provided the highest maximum flow rates of 193.17 and 162.78 m³/s respectively. Furthermore, the damping reservoirs 02 and 05 showed the largest decreases of input hydrogram peak flow with maximum reductions of 86.3 and 76.6% respectively at the current urbanization scenario. The implementation of the proposed parallel damping reservoir allowed the reduction of peak flows at the basin outlet of 26.8% from 211.65 to 154.87 m³/s in the current scenario and 22.3% reduction from 262.28 to 203, 86 m³/s at the critical urbanization scenario. Based on these results, it is possible to conclude that the damping reservoirs are very important to control runoff and it is necessary and urgent to implement new flood control measures in the Jataí stream watershed to reduce the inconvenience caused by heavy intensity rains. / O rápido crescimento urbano de muitas cidades brasileiras no século XX ocorreu sem o planejamento e infraestrutura adequados. Nessas cidades, as enchentes causam grandes prejuízos materiais e humanos todos os anos. Diante disso, é dever das autoridades e comunidade propor e implementar medidas de controle de enchentes após estudos detalhados das características da bacia hidrográfica. Neste sentido, foram realizadas simulações hidrológicas da microbacia hidrográfica do córrego Jataí, em Uberlândia/MG, com a utilização do software ABC Análise de Bacias Complexas da Universidade de São Paulo, considerando o período de retorno de 100 anos para a chuva de projeto. Esta microbacia possui área de 15,99 km² e foi discretizada por sub-bacias considerando o uso e ocupação do solo nos cenários de urbanização atual e crítico (bacia plenamente urbanizada e ocupada). Nas simulações foram considerados os reservatórios de amortecimento existentes na área de estudo, além de se propor a implantação de um reservatório de amortecimento paralelo próximo ao exutório da microbacia. As sub-bacias 02 e 08 simuladas isoladamente no cenário crítico forneceram as maiores vazões máximas de 193,17 e 162,78 m³/s respectivamente. Além disso, os reservatórios de amortecimento 02 e 05 apresentaram as maiores reduções das vazões de pico do hidrograma de entrada com reduções máximas de 86,3 e 76,6% no cenário atual respectivamente. A proposta de implantação do reservatório de amortecimento paralelo permitiu a redução das vazões de pico no exutório em 26,8% de 211,65 para 154,87 m³/s no cenário atual e em 22,3% de 262,28 para 203,86 m³/s no cenário crítico. Diante dos resultados obtidos, conclui-se que os reservatórios de amortecimento têm função importante no controle do escoamento superficial, sendo necessária e urgente a implantação de novas medidas de controle de enchentes na microbacia do córrego Jataí para reduzir os transtornos causados por chuvas intensas. / Mestre em Engenharia Civil

The recent high profile flooding events – that have occurred in many parts of the world – have drawn attention to the need for new and improved methods for water resources assessment, water management and the modelling of large-scale flooding events. In the case of the Zambezi Basin, a review of the 2000 and 2001 floods identified the need for tools to enable hydrologists to assess and predict daily stream flow and identify the areas that are likely to be affected by flooding. As a way to address the problem, a methodology was set up to derive catchment soil moisture statistics from Earth Observation (EO) data and to study the improvements brought about by an assimilation of this information into hydrological models for improving reservoir management in a data scarce environment. Rainfall data were obtained from the FEWSNet Web site and computed by the National Oceanic and Atmospheric Administration Climatic Prediction Center (NOAA/CPC). These datasets were processed and used to monitor rainfall variability and subsequently fed into a hydrological model to predict the daily flows for the Zambezi River Basin. The hydrological model used was the Geospatial Stream Flow Model (GeoSFM), developed by the United States Geological Survey (USGS). GeoSFM is a spatially semi-distributed physically-based hydrological model, parameterised using spatially distributed topographic data, soil characteristics and land cover data sets available globally from both Remote Sensing and in situ sources. The Satellite rainfall data were validated against data from twenty (20) rainfall gauges located on the Lower Zambezi. However, at several rain gauge stations (especially those with complex topography, which tended to experience high rainfall spatial variability), there was no direct correlation between the satellite estimates and the ground data as recorded in daily time steps. The model was calibrated for seven gauging stations. The calibrated model performed quite well at seven selected locations (R2=0.66 to 0.90, CE=0.51 to 0.88, RSR=0.35 to 0.69, PBIAS=−4.5 to 7.5). The observed data were obtained from the National Water Agencies of the riparian countries. After GeoSFM calibration, the model generated an integration of the flows into a reservoir and hydropower model to optimise the operation of Kariba and Cahora Bassa dams. The Kariba and Cahora Bassa dams were selected because this study considers these two dams as the major infrastructures for controlling and alleviating floods in the Zambezi River Basin. Other dams (such as the Kafue and Itezhi-Thezi) were recognised in terms of their importance but including them was beyond the scope of this study because of financial and time constraints. The licence of the reservoir model was limited to one year for the same reason. The reservoir model used was the MIKE BASIN, a professional engineering software package and quasi-steady-state mass balance modelling tool for integrated river basin and management, developed by the Denmark Hydraulic Institute (DHI) in 2003. The model was parameterised by the geometry of the reservoir basin (level, area, volume relationships) and by the discharge-level (Q-h) relationship of the dam spillways. The integrated modelling system simulated the daily flow variation for all Zambezi River sub-basins between 1998 and 2008 and validated between 2009 and 2011. The resulting streamflows have been expressed in terms of hydrograph comparisons between simulated and observed flow values at the four gauging stations located downstream of Cahora Bassa dam. The integrated model performed well, between observed and forecast streamflows, at four selected gauging stations (R2=0.53 to 0.90, CE=0.50 to 0.80, RSR=0.49 to 0.69, PBIAS=−2.10 to 4.8). From the results of integrated modelling, it was observed that both Kariba and Cahora Bassa are currently being operated based on the maximum rule curve and both remain focused on maximising hydropower production and ensuring dam safety rather than other potential influences by the Zambezi River (such as flood control downstream – where the communities are located – and environmental issues). In addition, the flood mapping analysis demonstrated that the Cahora Bassa dam plays an important part in flood mitigation downstream of the dams. In the absence of optimisation of flow releases from both the Kariba and Cahora Bassa dams, in additional to the contribution of any other tributaries located downstream of the dams, the impact of flooding can be severe. As such, this study has developed new approaches for flood monitoring downstream of the Zambezi Basin, through the application of an integrated modelling system. The modelling system consists of: predicting daily streamflow (using the calibrated GeoSFM), then feeding the predicted streamflow into MIKE BASIN (for checking the operating rules) and to optimise the releases. Therefore, before releases are made, the flood maps can be used as a decision-making tool to both assess the impact of each level of release downstream and to identify the communities likely to be affected by the flood – this ensures that the necessary warnings can be issued before flooding occurs. Finally an integrated flood management tool was proposed – to host the results produced by the integrated system – which would then be accessible for assessment by the different users. These results were expressed in terms of water level (m). Four discharge-level (Q-h) relationships were developed for converting the simulated flow into water level at four selected sites downstream of Cahora Bassa dam – namely: Cahora Bassa dam site, Tete (E-320), Caia (E-291) and Marromeu (E-285). However, the uncertainties in these predictions suggested that improved monitoring systems may be achieved if data access at appropriate scale and quality was improved.

Present days are characterized by raising awareness of natural hazards, especially the risk of flood events. Extreme floods are connected with large - scale material damage and also endanger human lives. That's why the issue of flood formation and its possibility of forecasting has became disccused topic these days. Research of passed floods provides principles of effective flood protection in specific area. The main aim of this thesis is to analyse flood events that passed in the uper Opava river basin, concretely the source area containing the Černá, Střední and Bílá Opava river basins. This analysis refers about the flood frequency, different seasonal regime of floods occurence and looks for the relationship between atmospheric conditions and origin of flood events in the period of 1963 to 1997. Part of this thesis also summarizes main types of floods raised in the source area and compares different flood threat of the Černá, Střední and Bílá Opava rivers. There is also mentioned some basic differences of drainage formation, natural conditions and rainfall distribution in specific catchment area.

Streamflow forecasting is a fundamental component of various water resources management systems, ranging from flood control and mitigation to long-term planning of irrigation and hydropower systems. In the context of floods, a probabilistic forecasting system is required for proper and effective decision-making. Therefore, the primary goal of this research is the development of an advanced ensemble-based streamflow forecasting framework to better quantify the predictive uncertainty and generate enhanced probabilistic forecasts. This research started by comprehensively evaluating the performances of various lumped conceptual models in data-poor watersheds and comparing various Bayesian Model Averaging (BMA) modifications for probabilistic streamflow simulation. Then, using the concept of BMA, two novel probabilistic post-processing approaches were developed to enhance streamflow forecasting performance. The combination of the entropy theory and the BMA method leads to an entropy-based Bayesian Model Averaging (En-BMA) approach for enhanced probabilistic streamflow and precipitation forecasting. Also, the integration of the Hydrologic Uncertainty Processor (HUP) and the BMA methods is proposed for probabilistic post-processing of multi-model streamflow forecasts. Results indicated that the MACHBV and GR4J models are highly competent in simulating hydrological processes within data-scarce watersheds, however, the presence of the lower skill hydrologic models is still beneficial for ensemble-based streamflow forecasting. The comprehensive verification of the BMA approach in terms of streamflow predictions has identified the merits of implementing some of the previously recommended modifications and showed the importance of possessing a mutually exclusive and collectively exhaustive ensemble. By targeting the remaining limitation of the BMA approach, the proposed En-BMA method can improve probabilistic streamflow forecasting, especially under high flow conditions. Also, the proposed HUP-BMA approach has taken advantage of both HUP and BMA methods to better quantify the hydrologic uncertainty. Moreover, the applicability of the modified En-BMA as a more robust post-processing approach for precipitation forecasting, compared to BMA, has been demonstrated. / Thesis / Doctor of Philosophy (PhD) / Possessing a reliable streamflow forecasting framework is of special importance in various fields of operational water resources management, non-structural flood mitigation in particular. Accurate and reliable streamflow forecasts lead to the best possible in-advanced flood control decisions which can significantly reduce its consequent loss of lives and properties. The main objective of this research is to develop an enhanced ensemble-based probabilistic streamflow forecasting approach through proper quantification of predictive uncertainty using an ensemble of streamflow forecasts. The key contributions are: (1) implementing multiple diverse forecasts with full coverage of future possibilities in the Bayesian ensemble-based forecasting method to produce more accurate and reliable forecasts; and (2) developing an ensemble-based Bayesian post-processing approach to enhance the hydrologic uncertainty quantification by taking the advantages of multiple forecasts and initial flow observation. The findings of this study are expected to benefit streamflow forecasting, flood control and mitigation, and water resources management and planning.

<p> The hydrological cycle is affected by land use variability. Land use spatial and temporal variability has the power to alter watershed runoff, water resource quantity and quality, ecosystems, and environmental sustainability. In recent decades, agriculture lands, pastures, plantations, and urban areas have increased, resulting in significant increases in energy, water, and fertilizer usage, as well as significant biodiversity losses. </p>

This research was aimed to evaluate the possibility of using satellite precipitation products (SPPs) and Numerical Weather Prediction (NWP) of precipitation for better hydrologic simulations and flood forecasting in the trans-boundary Chenab River Basin (CRB) in Pakistan. This research was divided into three parts. In the first part, two renowned SPPs, i.e., global precipitation mission (GPM) IMERG-F v6 and tropical rainfall measuring mission (TRMM) 3B42 v7, were incorporated in a semidistributed hydrological model, i.e., the soil and water assessment tool (SWAT), to assess the daily and monthly runoff pattern in Chenab River at the Marala Barrage gauging site in Pakistan. The results exhibit higher correlation between observed and simulated discharges at monthly timescale simulations rather than daily timescale simulations. Moreover, results show that IMERG-F is superior to 3B42 by indicating higher R2, higher Nash–Sutcliffe efficiency (NSE), and lower percent bias (PBIAS) at both monthly and daily timescale. In the second part, three latest half-hourly (HH) and daily (D) SPPs, i.e., 'IMERG-E', 'IMERGL', and 'IMERG-F', were evaluated for daily and monthly flow simulations in the SWAT model. The study revealed that monthly flow simulation performance is better than daily flow simulation in all sub-daily and daily SPPs-based models. Results depict that IMERGHHF and IMERG-DF yield the best performance among the other latency levels of SPPs. However, the IMERG-HHF based model has a reasonably higher daily correlation coefficient (R) and lower daily root mean square error (RMSE) than IMERG-DF. IMERG-HHF displays the lowest PBIAS for daily and monthly flow validations and it also represents relatively higher values of R2 and NSE than any other model for daily and monthly model validation. Moreover, the sub-daily IMERG based model outperformed the daily IMERG based model for all calibration and validation scenarios. IMERG-DL based model demonstrates poor performance among all of the SPPs, in daily and monthly flow validation, with low R2, low NSE, and high PBIAS. Additionally, the IMERG-HHE model outperformed IMERG-HHL. In the third and last part of this research, coupled hydro-meteorological precipitation information was used to forecast the 2016 flood event in the Chenab River Basin. The gaugecalibrated SPP, i.e., Global Satellite Mapping of Precipitation (GSMaP_Gauge), was selected to calibrate the Integrated Flood Analysis System (IFAS) model for the 2016 flood event. Precipitation from the Global Forecast System (GFS) NWP, with nine different lead times up to 4 days, was used in the calibrated IFAS model. This study revealed that the hydrologic simulations in IFAS, with global GFS forecasts, were unable to predict the flood peak for all lead times. Later, the Weather Research and Forecasting (WRF) model was used to downscale the precipitation forecasts with one-way and two-way nesting approaches. It was found in this study that the simulated hydrographs in the IFAS model, at different lead times, from the precipitation of two-way WRF nesting exhibited superior performance with the highest R2, NSE and the lowest PBIAS compared with one-way nesting. Moreover, it was concluded that the combination of GFS forecast and two-way WRF nesting can provide high-quality precipitation prediction to simulate flood hydrographs with a remarkable lead time of 96 h when applying coupled hydrometeorological flow simulation.

Issues arising from climate change and long-term natural climate variability have become the focus of much recent research. In this study, we specifically explore the impacts of long-term climate variability and climate changes upon flood frequencies. The analyses of the flood frequencies are carried out in a comparative manner in catchments located in semiarid-temperate and tropical landscapes in Australia, namely Perth, Newcastle and Darwin, using a process-based derived flood frequency approach. The derived flood frequency analyses are carried out using deterministic rainfall-runoff models that capture the intrinsic water balance variability in the study catchments, and driven by temporal rainfall event sequences that are generated by a stochastic rainfall model that incorporates temporal variabilities over a multiplicity of time scales, ranging from within-event, between-event to seasonal, multi-annual and multi-decadal time scales. Six climate scenarios are considered for Newcastle, that combine the ENSO (El Niño Southern Oscillation) and IPO (Inter-decadal Pacific Oscillation) modes of variability, and six different climate scenarios are considered for Perth and Darwin that combine these different ENSO modes and step changes in climate (upwards or downwards) that occurred in 1970 in both regions, which were identified through statistical analysis. The results of the analyses showed that La Niña years cause higher annual maximum floods compared to El Niño and Neutral years in all three catchments. The impact of ENSO on annual maximum floods in the Newcastle catchment is enhanced when the IPO is negative and for Perth, the impact of ENSO weakens in the post-1970 period, while it strengthens in Darwin in the same period. In addition, the results of sensitivity and scenario analyses with the derived flood frequency model explored the change of dominant runoff generation processes contributing to floods in each of the study catchments. These analyses highlighted a switch from subsurface stormflow to saturation excess runoff with a change of return period, which was much more pronounced in Perth and Darwin, and not so in Newcastle. In Perth and Darwin this switch was caused by the interactions between the out-of-phase seasonal variabilities of rainfall and potential evaporation, whereas the seasonality was much weaker in Newcastle. On the other hand, the combination of higher rainfall intensities and shallower soil depths led to saturation excess runoff being the dominant mechanism in Newcastle across the full range of return periods. Consequently, within-storm rainfall intensity patterns were important in Newcastle in all major flood producing events (all return periods), where they were only important in Perth and Darwin for floods of high return periods, which occur during wet months in wet years, when saturation excess runoff was the dominant mechanism. Additionally, due to the possibility of a change of process from subsurface stormflow to saturation excess when conditions suited this switch, the estimates of flood frequency are highly uncertain especially at high return periods (in Darwin and Perth) and much less in Newcastle (when no process change was involved).

From the Proceedings of the 1972 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - May 5-6, 1972, Prescott, Arizona / Almost all runoff from semiarid rangeland watersheds in southern Arizona results from intense highly variable thunderstorm rainfall. Abstractions, or transmission losses, are important in diminishing streamflow, supporting riparian vegetation and providing natural groundwater recharge. A flood routing procedure is developed using data from the walnut gulch experimental watershed, where flood movement and transmission losses are represented by a system using storage in the channel reach as a state variable which determines loss rates. Abstractions are computed as a cascade of general components in linear form. Wide variation in the parameters of this linear model with increasing inflow indicates that a linear relation between losses and storage is probably incorrect for ephemeral channels.