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Seattle, United States
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Nunez J.H.,Water Center for Arid | Verbist K.,Ghent University | Wallis J.R.,Yale University | Schaefer M.G.,MGS Engineering Consultants | And 2 more authors.
Journal of Hydrology | Year: 2011

Droughts are among the most important natural disasters, particularly in the arid and semiarid regions of the world. Proper management of droughts requires knowledge of the expected frequency of specific low magnitude precipitation totals for a variety of durations. Probabilistic approaches have often been used to estimate the average recurrence period of a given drought event. However, probabilistic model fitting by conventional methods, such as product moment or maximum likelihood in areas with low availability of long records often produces highly unreliable estimates. Recognizing the need for adequate estimates of return periods of severe droughts in the arid and semiarid region of Chile, a regional frequency analysis method based on L-moments (RFA-LM) was used for estimating and mapping drought frequency. Some adaptations to the existing procedures for forming homogeneous regions were found necessary. In addition, a new 3-parameter distribution, the Gaucho, which is a special case of the 4-parameter Kappa distribution, was introduced, and the analysis procedure was improved by the developments of two new software tools named L-RAP, to perform the RFA-LM analysis, and L-MAP, to map the resulting drought maps. Eight homogeneous sub-regions were delineated using the Gaucho distribution and used to construct return period maps for drought events with 80% and 40% precipitation of the normal. The study confirms the importance of a sub-regional homogeneity test, and the usefulness of the Gaucho distribution. The RFA-LM showed that droughts with a 40% precipitation of the normal have return periods that range from 4. years at the northern arid boundary of the study area to 22. years at the southern sub-humid boundary. The results demonstrate the need for different thresholds for declaring a drought than those currently in use for drought characterization in north-central Chile. © 2011 Elsevier B.V.

Nathan R.,University of Melbourne | Scorah M.,Hydrology and Risk Consulting | Jordan P.,Jacobs | Lang S.,Hydrology and Risk Consulting | And 3 more authors.
The Art and Science of Water - 36th Hydrology and Water Resources Symposium, HWRS 2015 | Year: 2015

This paper describes the development and application of two largely independent methods to estimate the annual exceedance probability (AEP) of Probable Maximum Precipitation (PMP). One method is based on the Stochastic Storm Transposition (SST) approach, which combines the "arrival" and "transposition" probabilities of an extreme storm using the total probability theorem. The second method - termed "Stochastic Storm Regression" - combines frequency curves of point rainfalls with regression estimates of areal rainfalls; the regression relationship is derived using local and transposed storms, and the final exceedance probabilities are derived using the total probability theorem. The methods are applied to two large catchments (with areas of 3550 km2 and 15280 km2) located in inland southern Australia. In addition, the SST approach is used to derive regional estimates for standardised catchments within the Inland GSAM region. Careful attention is given to the uncertainty and sensitivity of the estimates to underlying assumptions, and the results are used to help formulate draft ARR recommendations. © 2015, Engineers Australia. All rights reserved.

Micovic Z.,BC Hydro | Schaefer M.G.,MGS Engineering Consultants | Taylor G.H.,Applied Climate Services
Journal of Hydrology | Year: 2015

The focus of the study is firmly on PMP estimates derived through meteorological analyses and not on statistically derived PMPs. Theoretical PMP cannot be computed directly and operational PMP estimates are developed through a stepwise procedure using a significant degree of subjective professional judgment. This paper presents a methodology for portraying the uncertain nature of PMP estimation by analyzing individual steps within the PMP derivation procedure whereby for each parameter requiring judgment, a set of possible values is specified and accompanied by expected probabilities. The resulting range of possible PMP values can be compared with the previously derived operational single-value PMP, providing measures of the conservatism and variability of the original estimate. To our knowledge, this is the first uncertainty analysis conducted for a PMP derived through meteorological analyses. The methodology was tested on the La Joie Dam watershed in British Columbia. The results indicate that the commonly used single-value PMP estimate could be more than 40% higher when possible changes in various meteorological variables used to derive the PMP are considered. The findings of this study imply that PMP estimates should always be characterized as a range of values recognizing the significant uncertainties involved in PMP estimation. In fact, we do not know at this time whether precipitation is actually upper-bounded, and if precipitation is upper-bounded, how closely PMP estimates approach the theoretical limit. © 2014 Elsevier B.V.

Micovic Z.,BC Hydro | Hartford D.N.D.,BC Hydro | Schaefer M.G.,MGS Engineering Consultants | Barker B.L.,MGS Engineering Consultants
Stochastic Environmental Research and Risk Assessment | Year: 2016

The traditional and still prevailing approach to characterization of flood hazards to dams is the inflow design flood (IDF). The IDF, defined either deterministically or probabilistically, is necessary for sizing a dam, its discharge facilities and reservoir storage. However, within the dam safety risk informed decision framework, the IDF does not carry much relevance, no matter how accurately it is characterized. In many cases, the probability of the reservoir inflow tells us little about the probability of dam overtopping. Typically, the reservoir inflow and its associated probability of occurrence is modified by the interplay of a number of factors (reservoir storage, reservoir operating rules and various operational faults and natural disturbances) on its way to becoming the reservoir outflow and corresponding peak level—the two parameters that represent hydrologic hazard acting upon the dam. To properly manage flood risk, it is essential to change approach to flood hazard analysis for dam safety from the currently prevailing focus on reservoir inflows and instead focus on reservoir outflows and corresponding reservoir levels. To demonstrate these points, this paper presents stochastic simulation of floods on a cascade system of three dams and shows progression from exceedance probabilities of reservoir inflow to exceedance probabilities of peak reservoir level depending on initial reservoir level, storage availability, reservoir operating rules and availability of discharge facilities on demand. The results show that the dam overtopping is more likely to be caused by a combination of a smaller flood and a system component failure than by an extreme flood on its own. © 2015, Springer-Verlag Berlin Heidelberg.

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