ARF : a multifractal analysis

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005.Includes bibliographical references (leaves 110-115).The Areal Reduction Factor (ARF) [eta] is a key parameter in the design for hydrologic extremes. For a basin of area A, [eta](A, D, 7) is the ratio between the area-average rainfall intensity over a duration D with return period T and the point rainfall intensity for the same D and T. Besides depending on A, D and possibly T, the ARF is affected by the shape of the basin and by a number of seasonal, climatic and topographic characteristics. Another factor on which ARF depends is the advection velocity, Vad, of the rainfall features. Commonly used formulas and charts for the ARF have been derived by smoothing or curve-fitting empirical ARFs extracted from raingauge network records. Here we derive some properties of the ARF under the assumption that space-time rainfall is exactly or approximately multifractal. We do so for various shapes of the rainfall collecting region and for Vad = 0 and Vad [not equal to] 0. When Vad = 0, a key parameter in the analysis is the ratio Ures = Vres/Ve between the "response velocity" Vres = L/D, where L is the maximum linear dimension of the region, and the "evolution velocity" Ve, = Le/De, where Le and De are the characteristic linear dimension and characteristic duration of organized rainfall features. The effect of Vad [not equal to] 0 depends on the shape of the region. For highly elongated basins, both the direction and magnitude of advection are influential, whereas for regular shaped regions only the magnitude Vad matters. We review ways in which rainfall has been observed to deviate from exact multifractality and models that capture such deviations. We show how the ARF behaves when rainfall is a bounded cascade in space and time.(cont.) We also investigate the effect of estimating areal rainfall from raingauge network measurements. We find that bounded-cascade deviations from multifractality and sparse spatial sampling distort in similar ways the scaling properties of the ARF. Finally we show how one can reproduce various features of empirical ARF charts by using multifractal and bounded cascade models and considering the effects of sparse spatial sampling.by Andreas Langousis.S.M

Extreme rainfall intensities and long-term rainfall risk from tropical cyclones

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2009.Includes bibliographical references (leaves 78-85).We develop a methodology for the frequency of extreme rainfall intensities caused by tropical cyclones (TCs) in coastal areas. The mean rainfall field associated with a TC with maximum tangential wind speed Vmax, radius of maximum winds Rmax, and translation speed Vmax, is obtained using a physically-based model, whereas rainfall variability at both large scales (from storm to storm) and small scales (due to rainbands and local convection) is modeled statistically. The statistical component is estimated using precipitation radar (PR) data from the TRMM mission. Taylor's hypothesis is used to convert spatial rainfall intensity fluctuations to temporal fluctuations at a given location A. The combined physical-statistical model gives the distribution of the maximum rainfall intensity at A during a period of duration D for a TC with characteristics (Vmax, Rmax, Vt) that passes at a given distance from A. To illustrate the use of the model for long-term rainfall risk analysis, we formulate a recurrence model for tropical cyclones in the Gulf of Mexico that make landfall between longitudes 85°-95°W. We then use the rainfall and recurrence models to assess the rainfall risk for New Orleans. For return periods of 100 years or more and long averaging durations (D around 12-24 hours), tropical cyclones dominate over other rainfall event types, whereas the reverse is true for shorter return periods or shorter averaging durations.by Andreas Langousis.Ph.D

HESS Opinions: "Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability"

Since 1990 extensive funds have been spent on research in climate change. Although Earth Sciences, including climatology and hydrology, have benefited significantly, progress has proved incommensurate with the effort and funds, perhaps because these disciplines were perceived as “tools” subservient to the needs of the climate change enterprise rather than autonomous sciences. At the same time, research was misleadingly focused more on the “symptom”, i.e. the emission of greenhouse gases, than on the “illness”, i.e. the unsustainability of fossil fuel-based energy production. Unless energy saving and use of renewable resources become the norm, there is a real risk of severe socioeconomic crisis in the not-too-distant future. A framework for drastic paradigm change is needed, in which water plays a central role, due to its unique link to all forms of renewable energy, from production (hydro and wave power) to storage (for time-varying wind and solar sources), to biofuel production (irrigation). The extended role of water should be considered in parallel to its other uses, domestic, agricultural and industrial. Hydrology, the science of water on Earth, must move towards this new paradigm by radically rethinking its fundamentals, which are unjustifiably trapped in the 19thcentury myths of deterministic theories and the zeal to eliminate uncertainty. Guidance is offered by modern statistical and quantum physics, which reveal the intrinsic character of uncertainty/entropy in nature, thus advancing towards a new understanding and modelling of physical processes, which is central to the effective use of renewable energy and water resources

UPStream: Automated hydraulic design of pressurized water distribution networks

Hydraulic design of pressurized water distribution networks constitutes a time consuming process in engineering applications, requiring proper selection of pipe diameters so certain regulatory constrains are met. UPStream® is an open-source software, which combines EPANET’s computational engine and a simple hydraulic gradient-based recursive approach for selection of pipe diameters, to automatically design pressurized water distribution networks, based on user-defined pressure and flow velocity constraints. To the best of our knowledge, there is no available open-source software for this purpose, which allows for case-specific modifications/interventions by advanced users, as well as extensions to weight between alternative design strategies. Therefore, UPStream® is expected to serve as a useful tool/platform for educational/academic purposes, research, and engineering practice. Keywords: Water distribution networks, Hydraulic design, Pressurized pipe networks, MATLAB, EPANE

Long-term rainfall risk from tropical cyclones in coastal areas

We develop a methodology for the frequency of extreme rainfall intensities caused by tropical cyclones (TCs) in coastal areas. The model does not account for landfall effects. This makes the developed framework best suited for open water sites and coastal areas with flat topography. The mean rainfall field associated with a TC with maximum tangential wind speed V[subscript max], radius of maximum winds R[subscript max], and translation speed Vt is obtained using a physically based model, whereas rainfall variability at both large scales (from storm to storm) and small scales (due to rainbands and local convection) is modeled statistically. The statistical component is estimated using precipitation radar data from the Tropical Rainfall Measuring Mission. Taylor's hypothesis is used to convert spatial rainfall intensity fluctuations to temporal fluctuations at a given location A. The combined physical-statistical model gives the distribution of the maximum rainfall intensity at A during an averaging period D for a TC with characteristics (V[subscript max], R[subscript max], V[subscript t]) that passes at a given distance from A. To illustrate the use of the model for long-term rainfall risk analysis, we formulate a recurrence model for tropical cyclones in the Gulf of Mexico that make landfall between longitudes 85° and 95°W. We then use the rainfall and recurrence models to assess the rainfall risk for New Orleans. For return periods of 100 years or more and long averaging durations (D around 12–24 h), tropical cyclones dominate over other rainfall event types, whereas the reverse is true for shorter return periods or shorter averaging durations.Alexander S. Onassis Public Benefit Foundation (Scholarship F-ZA 054/2005–2006

Modelling of rainfall maxima at different durations using max-stable processes

<div>The multivariate extreme value distribution (MEVD) has been used to model the dependence of rainfall block maxima at different temporal resolutions, as a means of estimating intensity-duration-frequency (IDF) curves for engineering applications. It is characterized by max-stability, which assumes that under proper renormalization, the rainfall block maxima at different temporal resolutions are extreme value distributed and the degree of their dependence remains invariant to the severity of the event. Due to these properties, and contrary to other commonly used approaches, MEVD allows for more conservative return level estimates at those durations used for model fitting. Max-stable processes are continuous extensions of MEVD, which are more flexible, and allow for extrapolation to temporal resolutions beyond those used for model fitting. Here we: 1) propose using max-stable processes to model rainfall block maxima, 2) apply the Brown-Resnick, Schlather and extremal-t models to hourly rainfall data, and 3) compare the obtained results to traditional approaches for IDF estimation. We discuss advantages and limitations regarding the use of max-stable processes in IDF estimation, and their potential use in hydrologic practice.</div