A simple approximation to multifractal rainfall maxima using a generalized extreme value distribution model

Langousis, Andreas; Cârsteanu, A. A.; Deidda, Roberto

doi:10.1007/s00477-013-0687-0

Cited by 36 publications

(30 citation statements)

References 42 publications

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“…The partial relative uncertainty component on rainfall depth threshold with respect to each parameter has been evaluated: the largest values are found in the Alpine area, generally below 10 %, with few exceptions, notably the ξ component, reaching 19 % in the extreme northwest. In principle, these results could be further improved by allowing a direct dependence on duration of the GEV shape parameter (Veneziano et al, 2009;Langousis et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…In recent works (Veneziano et al, 2009;Langousis et al, 2013) a GEV with shape parameter ξ dependent on duration is advocated as the most appropriate distribution for rainfall annual maxima and for durations of finite length. We remark that, by means of the spatial bootstrap technique proposed here, the sensitivity to outliers is effectively reduced (Sect.…”

Section: Depth-duration-frequency Curves and Scale Invariancementioning

confidence: 99%

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A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

Uboldi¹,

Sulis

Lussana

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Estimation of extreme event distributions and depth-duration-frequency (DDF) curves is achieved at any target site by repeated sampling among all available raingauge data in the surrounding area. The estimate is computed over a gridded domain in Northern Italy, using precipitation time series from 1929 to 2011, including data from historical analog stations and from the present-day automatic observational network. The presented local regionalisation naturally overcomes traditional station-point methods, with their demand of long historical series and their sensitivity to very rare events occurring at very few stations, possibly causing unrealistic spatial gradients in DDF relations. At the same time, the presented approach allows for spatial dependence, necessary in a geographical domain such as Lombardy, complex for both its topography and its climatology. The bootstrap technique enables evaluating uncertainty maps for all estimated parameters and for rainfall depths at assigned return periods.

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Section: Discussionmentioning

confidence: 99%

Section: Depth-duration-frequency Curves and Scale Invariancementioning

confidence: 99%

A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

Uboldi¹,

Sulis

Lussana

et al. 2014

Hydrol. Earth Syst. Sci.

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“…Distributed hydrologic models have been applied to study the hydrologic impacts of future climate change scenarios, with forcing provided by general (GCMs) or regional (RCMs) climate models (e.g., Abbaspour et al, 2009;Cayan et al, 2010;Montenegro and Ragab, 2012;Liuzzo et al, 2010;Sulis et al, 2011). In Mediterranean areas, conducting studies based on this approach is challenging for two reasons.…”

Section: G Mascaro Et Al: Distributed Hydrologic Modeling Of a Sparmentioning

confidence: 99%

“…Rainfall models based on the multifractal theory have been extensively used to characterize and simulate the rainfall statistics at different spatial and temporal scales (see, e.g., Schertzer and Lovejoy, 1987;Over and Gupta, 1996;Menabde et al, 1997;Deidda et al, 2004;Langousis, 2005, 2010;Langousis et al, 2009Langousis et al, , 2013. Our objective is to downscale daily precipitation observed by a network of gages and produce gridded maps at hourly resolution.…”

Section: Precipitation Downscaling Toolmentioning

confidence: 99%

Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrometeorological downscaling

Mascaro

Piras

Deidda

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations. In this work, we present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin (RMB), a medium-sized watershed (472.5 km 2 ) located in an agricultural area in Sardinia, Italy. In the RMB, precipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources of uncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available. The methodology proposed here can be also used to disaggregate outputs of climate models and conduct high-resolution hydrologic simulations with the goal of quantifying the impacts of climate change on water resources and the frequency of hydrologic extremes within medium-sized basins.

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“…Disaggregation methods are based on the assumption that rainfall is a multifractal scale invariant process inheriting its scaling properties from external forcing, usually atmospheric turbulence (Perica and Foufoula-Georgiou 1996;Deidda et al 1999;Badas et al 2006;Venugopal et al 2006). The spatial variability of rainfall is modelled through multifractal cascades (Groppelli et al 2011;Gires et al 2012;Langousis et al 2013;Mascaro et al 2013). If multifractality is demonstrated, the major advantages are related to the light parameterization and a rather simple Stoch Environ Res Risk Assess probabilistic structure of the model (Veneziano et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a spatial rainfall generator for generating high resolution precipitation projections over orographically complex terrain

Camera

Bruggeman

Hadjinicolaou

et al. 2016

Stoch Environ Res Risk Assess

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Space-time variability of precipitation plays a key role as driver of many environmental processes. The objective of this study is to evaluate a spatiotemporal (STG) Neyman-Scott Rectangular Pulses (NSRP) generator over orographically complex terrain for statistical downscaling of climate models. Data from 145 rain gauges over a 5760-km 2 area of Cyprus for 1980-2010 were used for this study. The STG was evaluated for its capacity to reproduce basic rainfall statistical properties, spatial intermittency, and extremes. The results were compared with a multi-single site NRSP generator (MSG). The STG performed well in terms of average annual rainfall (?1.5 % in comparison with the 1980-2010 observations), but does not capture spatial intermittency over the study area and extremes well. Daily events above 50 mm were underestimated by 61 %. The MSG produced a similar error (?1.1 %) in terms of average annual rainfall, while the daily extremes ([50-mm) were underestimated by 11 %. A gridding scheme based on scaling coefficients was used to interpolate the MSG data. Projections of three Regional Climate Models, downscaled by MSG, indicate a 1.5-12 % decrease in the mean annual rainfall over Cyprus for 2020-2050. Furthermore, the number of extremes ([50-mm) for the 145 stations is projected to change between -24 and ?2 % for the three models. The MSG modelling approach maintained the daily rainfall statistics at all grid cells, but cannot create spatially consistent daily precipitation maps, limiting its application to spatially disconnected applications. Further research is needed for the development of spatial non-stationary NRSP models.

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A simple approximation to multifractal rainfall maxima using a generalized extreme value distribution model

Cited by 36 publications

References 42 publications

A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrometeorological downscaling

Evaluation of a spatial rainfall generator for generating high resolution precipitation projections over orographically complex terrain

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