Large‐scale hydrology: advances in understanding processes, dynamics and models from beyond river basin to global scale

Cloke, Hannah; Hannah, David M.

doi:10.1002/hyp.8059

Cited by 21 publications

(19 citation statements)

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“…Hydrological drought is generally related to the deficit of surface runoff, streamflow, reservoir, or groundwater level. Since it is directly linked to drought impacts, it is argued that more attention is needed to study the hydrological drought (Cloke & Hannah, 2011;Mishra & Singh, 2010;Pozzi et al, 2013). The commonly used hydrologic drought indicators include Palmer Hydrologic Drought Index (PHDI) (Palmer, 1965), runoff or streamflow percentile, Standardized Runoff Index (SRI) (Shukla & Wood, 2008), or reservoir level (Hayes et al, 2011).…”

Section: Hydrological Droughtmentioning

confidence: 99%

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Hao

Singh

Xia

2018

Reviews of Geophysics

394

232

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Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large‐scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high‐quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

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Section: Hydrological Droughtmentioning

confidence: 99%

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Hao

Singh

Xia

2018

Reviews of Geophysics

394

232

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“…the value of discharge that is equalled or exceeded 80% of the time) are used commonly to identify periods of high and low flow, respectively, while more extreme thresholds are (for example) one or three independent peaks per year (Bayliss & Jones, 1993;Robson & Reed, 1999) Teuling et al, 2013;Trambauer et al, 2014;Van Loon et al, 2014). Indices are valuable for detecting trends and other changes in regional and global river flow (Cloke & Hannah, 2011;Gudmundsson et al, 2012;. However, our knowledge of extreme flow characteristics is influenced substantially by the spatial and temporal extent of observational records (Hannaford et al, 2013;Hall et al, 2014).…”

Section: Definition Of Extreme Hydroclimatic Eventsmentioning

confidence: 99%

Hydroclimatology of extreme river flows

et al. 2015

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1. Floods and droughts are recurrent events with characteristics of frequency, magnitude, duration and timing occupying the opposing extremes of natural river flow regimes. This hydrological variability, driven by climate and meteorology and modified by river basin processes, is a key determinant of physicochemical river habitat influencing the structure and function of freshwater communities. 2. A changing (warming) climate is projected to alter water and heat inputs to river systems that drive river flow, and thus, hydrological processes may be subject to unprecedented future change, resulting in potentially unprecedented river flow extremes. 3. We review the hydroclimatology of extreme river flows in changing climates and draw case studies from the European temperate regions. 4. Specifically, we adopt a 'catchment perspective', in which an understanding of meteorological and hydrological processes is used to (i) conceptually define extreme river flows, (ii) explain the (natural) climatic and catchment processes that drive extreme river flows, (iii) discuss future potential changes driven by an anthropogenically modified climate and (iv) identify uncertainties associated with projections of future climate-driven hydrological shifts.

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“…The use of large scale hydrological models and atmospheric land surface schemes for producing global scale hydrological products is of increasing interest (Cloke and Hannah, 2011) and have been employed on continental scale to derive flood hazard maps (see for example Barredo et al, 2007) In this work we derive global maps of flood return periods using a homogenous approach across the globe. Producing "consistent" maps of flood hazard can be a first step, for instance, in understanding flood risk at the global scale, although they cannot and should not replace local detailed information for local flood risk studies where it exists.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Pappenberger

Dutra

Wetterhall

et al. 2012

Hydrol. Earth Syst. Sci.

199

177

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Abstract. Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979-2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25 × 25 km grid, which is then reprojected onto a 1 × 1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25 × 25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.

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Large‐scale hydrology: advances in understanding processes, dynamics and models from beyond river basin to global scale

Cited by 21 publications

References 50 publications

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Hydroclimatology of extreme river flows

Deriving global flood hazard maps of fluvial floods through a physical model cascade

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