An assessment of scale issues related to the configuration of the ACRU model for design flood estimation

Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.There is a frequent need for estimates of design floods by hydrologists and engineers for the design of hydraulic structures. There are various techniques for estimating these design floods which are dependent largely on the availability of data. The two main approaches to design flood estimation are categorised as methods based on the analysis of floods and those based on rainfall-runoff relationships. Amongst the methods based on the analysis of floods, regional flood frequency analysis is seen as a reliable and robust method and is the recommended approach. Design event models are commonly used for design flood estimation in rainfall-runoff based analyses. However, these have several simplifying assumptions which are important in design flood estimation. A continuous simulation approach to design flood estimation has many advantages and overcomes many of the limitations of the design event approach. A major concern with continuous simulation using a hydrological model is the scale at which should take place. According to Martina (2004) the “level” of representation that will preserve the “physical chain” of the hydrological processes, both in terms of scale of representation and level of description of the physical parameters for the modelling process, is a critical question to be addressed. The objectives of this study were to review the literature on different approaches commonly used in South Africa and internationally for design flood estimation and, based on the literature, assess the potential for the use of a continuous simulation approach to design flood estimation. Objectives of both case studies undertaken in this research were to determine the optimum levels of catchment discretisation, optimum levels of soil and land cover information required and, to assess the optimum use of daily rainfall stations for the configuration of the ACRU agrohydrological model when used as a continuous simulation model for design flood estimation. The last objective was to compare design flood estimates from flows simulated by the ACRU model with design flood estimates obtained from observed data. Results obtained for selected quaternary catchments in the Thukela Catchment and Lions River catchment indicated that modelling at the level of hydrological response units (HRU’s), using area weighted soils information and more than one driver rainfall station where possible, produced the most realistic results when comparing observed and simulated streamflows. Design flood estimates from simulated flows compared reasonably well with design flood estimates obtained from observed data only for QC59 and QCU20B

New Approach to Estimate Extreme Flooding Using Continuous Synthetic Simulation Supported by Regional Precipitation and Non-Systematic Flood Data

[EN] Stochastic weather generators combined with hydrological models have been proposed for continuous synthetic simulation to estimate return periods of extreme floods. Yet, this approach relies upon the length and spatial distribution of the precipitation input data series, which often are scarce, especially in arid and semiarid regions. In this work, we present a new approach for the estimation of extreme floods based on the continuous synthetic simulation method supported with inputs of (a) a regional study of extreme precipitation to improve the calibration of the weather generator (GWEX), and (b) non-systematic flood information (i.e., historical information and/or palaeoflood records) for the validation of the generated discharges with a fully distributed hydrological model (TETIS). The results showed that this complementary information of extremes allowed for a more accurate implementation of both the weather generator and the hydrological model. This, in turn, improved the flood quantile estimates, especially for those associated with return periods higher than 50 years but also for higher quantiles (up to approximately 500 years). Therefore, it has been proved that continuous synthetic simulation studies focused on the estimation of extreme floods should incorporate a generalized representation of regional extreme rainfall and/or non-systematic flood data, particularly in regions with scarce hydrometeorological records.This research was funded by the Spanish Ministry of Science and Innovation through the research projects TETISCHANGE (RTI2018-093717-B-100) and EPHIMED (CGL2017-86839-C3-1-R), both cofounded with FEDER European funds.Beneyto, C.; Aranda Domingo, JÁ.; Benito, G.; Francés, F. (2020). New Approach to Estimate Extreme Flooding Using Continuous Synthetic Simulation Supported by Regional Precipitation and Non-Systematic Flood Data. Water. 12(11):1-16. https://doi.org/10.3390/w12113174S1161211Stedinger, J. 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Geophysical Research Letters, 42(5), 1560-1567. doi:10.1002/2015gl063238Furrer, E. M., & Katz, R. W. (2008). Improving the simulation of extreme precipitation events by stochastic weather generators. Water Resources Research, 44(12). doi:10.1029/2008wr007316Evin, G., Favre, A.-C., & Hingray, B. (2018). Stochastic generation of multi-site daily precipitation focusing on extreme events. Hydrology and Earth System Sciences, 22(1), 655-672. doi:10.5194/hess-22-655-2018Metzger, A., Marra, F., Smith, J. A., & Morin, E. (2020). Flood frequency estimation and uncertainty in arid/semi-arid regions. Journal of Hydrology, 590, 125254. doi:10.1016/j.jhydrol.2020.125254Zaman, M. A., Rahman, A., & Haddad, K. (2012). Regional flood frequency analysis in arid regions: A case study for Australia. Journal of Hydrology, 475, 74-83. doi:10.1016/j.jhydrol.2012.08.054Merz, R., & Blöschl, G. (2008). Flood frequency hydrology: 1. Temporal, spatial, and causal expansion of information. 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A review of applied methods in Europe for flood-frequency analysis in a changing environment

The report presents a review of methods used in Europe for trend analysis, climate change projections and non-stationary analysis of extreme precipitation and flood frequency. In addition, main findings of the analyses are presented, including a comparison of trend analysis results and climate change projections. Existing guidelines in Europe on design flood and design rainfall estimation that incorporate climate change are reviewed. The report concludes with a discussion of research needs on non-stationary frequency analysis for considering the effects of climate change and inclusion in design guidelines. Trend analyses are reported for 21 countries in Europe with results for extreme precipitation, extreme streamflow or both. A large number of national and regional trend studies have been carried out. Most studies are based on statistical methods applied to individual time series of extreme precipitation or extreme streamflow using the non-parametric Mann-Kendall trend test or regression analysis. Some studies have been reported that use field significance or regional consistency tests to analyse trends over larger areas. Some of the studies also include analysis of trend attribution. The studies reviewed indicate that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant increasing trends at regional or national level of extreme streamflow. For some smaller regions increases in extreme streamflow are reported. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows. Climate change projections have been reported for 14 countries in Europe with results for extreme precipitation, extreme streamflow or both. The review shows various approaches for producing climate projections of extreme precipitation and flood frequency based on alternative climate forcing scenarios, climate projections from available global and regional climate models, methods for statistical downscaling and bias correction, and alternative hydrological models. A large number of the reported studies are based on an ensemble modelling approach that use several climate forcing scenarios and climate model projections in order to address the uncertainty on the projections of extreme precipitation and flood frequency. Some studies also include alternative statistical downscaling and bias correction methods and hydrological modelling approaches. Most studies reviewed indicate an increase in extreme precipitation under a future climate, which is consistent with the observed trend of extreme precipitation. Hydrological projections of peak flows and flood frequency show both positive and negative changes. Large increases in peak flows are reported for some catchments with rainfall-dominated peak flows, whereas a general decrease in flood magnitude and earlier spring floods are reported for catchments with snowmelt-dominated peak flows. The latter is consistent with the observed trends. The review of existing guidelines in Europe on design floods and design rainfalls shows that only few countries explicitly address climate change. These design guidelines are based on climate change adjustment factors to be applied to current design estimates and may depend on design return period and projection horizon. The review indicates a gap between the need for considering climate change impacts in design and actual published guidelines that incorporate climate change in extreme precipitation and flood frequency. Most of the studies reported are based on frequency analysis assuming stationary conditions in a certain time window (typically 30 years) representing current and future climate. There is a need for developing more consistent non-stationary frequency analysis methods that can account for the transient nature of a changing climate

Sub-daily simulation of mountain flood processes based on the modified soil water assessment tool (SWAT) model

Floods not only provide a large amount of water resources, but they also cause serious disasters. Although there have been numerous hydrological studies on flood processes, most of these investigations were based on rainfall-type floods in plain areas. Few studies have examined high temporal resolution snowmelt floods in high-altitude mountainous areas. The Soil Water Assessment Tool (SWAT) model is a typical semi-distributed, hydrological model widely used in runoff and water quality simulations. The degree-day factor method used in SWAT utilizes only the average daily temperature as the criterion of snow melting and ignores the influence of accumulated temperature. Therefore, the influence of accumulated temperature on snowmelt was added by increasing the discriminating conditions of rain and snow, making that more suitable for the simulation of snowmelt processes in high-altitude mountainous areas. On the basis of the daily scale, the simulation of the flood process was modeled on an hourly scale. This research compared the results before and after the modification and revealed that the peak error decreased by 77% and the time error was reduced from +/- 11 h to +/- 1 h. This study provides an important reference for flood simulation and forecasting in mountainous areas

Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model

This paper highlights the usefulness of the minimum information and parametric pair-copula construction (PCC) to model the joint distribution of flood event properties. Both of these models outperform other standard multivariate copula in modeling multivariate flood data that exhibiting complex patterns of dependence, particularly in the tails. In particular, the minimum information pair-copula model shows greater flexibility and produces better approximation of the joint probability density and corresponding measures have capability for effective hazard assessments. The study demonstrates that any multivariate density can be approximated to any degree of desired precision using minimum information pair-copula model and can be practically used for probabilistic flood hazard assessment

Open TURNS: An industrial software for uncertainty quantification in simulation

The needs to assess robust performances for complex systems and to answer tighter regulatory processes (security, safety, environmental control, and health impacts, etc.) have led to the emergence of a new industrial simulation challenge: to take uncertainties into account when dealing with complex numerical simulation frameworks. Therefore, a generic methodology has emerged from the joint effort of several industrial companies and academic institutions. EDF R&D, Airbus Group and Phimeca Engineering started a collaboration at the beginning of 2005, joined by IMACS in 2014, for the development of an Open Source software platform dedicated to uncertainty propagation by probabilistic methods, named OpenTURNS for Open source Treatment of Uncertainty, Risk 'N Statistics. OpenTURNS addresses the specific industrial challenges attached to uncertainties, which are transparency, genericity, modularity and multi-accessibility. This paper focuses on OpenTURNS and presents its main features: openTURNS is an open source software under the LGPL license, that presents itself as a C++ library and a Python TUI, and which works under Linux and Windows environment. All the methodological tools are described in the different sections of this paper: uncertainty quantification, uncertainty propagation, sensitivity analysis and metamodeling. A section also explains the generic wrappers way to link openTURNS to any external code. The paper illustrates as much as possible the methodological tools on an educational example that simulates the height of a river and compares it to the height of a dyke that protects industrial facilities. At last, it gives an overview of the main developments planned for the next few years