and human impacts upon water resources, it is critical to provide information about current and future variations in hydrological characteristics.
By elucidating patterns and drivers of hydrological response, it is possible to assess those regions and time-periods most susceptible to climate change/
variability and anthropogenic influences and, thus, inform decision-makers so that water related hazards and stress (e.g. floods and droughts) may be mitigated.
Thus, the aim of EURO FRIEND Project 3 is to identify and understand variations in hydrological behavior at a range of spatial (within-basin to global) and temporal (event to multi-decadal) scales.
(3) spatial variability of precipitation regimes across Turkey (Şaris; Hannah; Eastwood); and (4) trends across the full range of flow duration curve percentiles for Wales and the English Midlands (Dixon; Lawler).
A highly active area of EURO FRIEND Project 3 research is large-scale climate-hydrology interactions.
Researchers at the University of Rouen (Massei and Laignel) quantified River Seine precipitation and discharge variability over the last half-century and
assessed links with the North Atlantic Oscillation (NAO). LOESS filtering associated with continuous wavelet transform revealed the presence of a long-term trend, and 5 – 9 year and 17 year fluctuations (Figure 2.10). After removal of annual cyclicity in discharge, the detected trend and inter-annual modes linked to NAO were found to explain up to 23 % of total daily River Seine flow variance from 1950 – 2008.
Similar inter-annual variations as detected in Seine river flow were found in small watersheds and in the piezometric oscillations of the Chalk aquifer around the Seine estuary (Massei and Laignel). Depending on the hydrogeological context (notably thickness of surficial deposits and Chalk aquifer depth), a differential filtering of the climate-driven inter-annual modes of variability was produced (Figure 2.11).
The role of basin properties as a modifier of the climate signal in river flows was assessed more widely for 104 gauged basins across mainland Great Britain (Laizé; Hannah). In this study, regional climate (precipitation, potential evaporation, soil moisture deficit etc.) variables were found to have stronger association with seasonal flows than atmospheric circulation (NAO), with the best predictors varying with season.
Figure 2.9
Map of river flow regime based on the twelve reference hydrographs for France (Sauquet et al., 2008).
Ongoing research on large-scale climate- hydrology interactions is focused on the UK (Lavers; Prudhomme;
Hannah), Turkey (Şaris;
Hannah; Eastwood) and around the Mediterranean (Kordomenidi; Hannah).
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Figure 2.10 Morlet continuous wavelet spectra of River Seine (a) daily discharge and (b) mean daily precipitation on the Seine watershed.
At an even larger spatial scale, climate-river flow links have been assessed across lowland and mountain environments of northern Europe (Kingston et al., 2009). As part of this work, an inverse climate-river flow relationship was found between northern and southern Scandinavian river flows that are explained by differences in the relative contribution of melt water to river flow between these regions, their latitudinal separation, and orographic effects on precipitation distribution (Figure 2.12).
Researchers at the UK Centre for Ecology and Hydrology (CEH) have evaluated the association between Circulation Types (CTs) and flood occurrence
across Europe. Relationships were assessed for 488 river basins, including data from the FRIEND Euro-pean Water Archive (EWA) and using CTs from 64 weather type catalogues developed within COST733 Action. Results showed variation in CT-flood
associations due to differences in flood generation mechanisms in different regions and the seasonal CT frequency (Prudhomme; Genevier).
As well as floods, the association between CT frequencies and the development of regional hydro-logical drought has been investigated for Great Britain and Denmark as part of COST733 Action (Fleig; Tallaksen; Hisdal; Hannah; Section 2.3.1).
Figure 2.11
Effect of geological setting, including the presence of karst, on the evolution of statistical descriptors: from top to bottom, lag (response)-time to precipitation, persistence (autocorrelation) and filtering capability of the hydro-system (spectral bandwidth) decrease.
In collaboration, CEH, the Walker Institute at University of Reading and water consultants JBA have explored coherence of drought in Europe using indicators of rainfall and stream flow deficit.
Correlation in drought occurrence between regions was found to be low generally; but multivariate analyses revealed broad continental-scale patterns possibly related to large-scale atmospheric circulation indices such as the NAO and the East Atlantic-West Russia pattern.
At the transcontinental scale, an inverse and lagged correlation has been identified for river flow in autumn between eastern North America and northern Europe (Kingston; Hannah; Lawler; McGregor;
Figure 2.13). These trans-Atlantic tele-connections are stronger than the temporal autocorrelation of autumn European river flow and suggest potential for using North American river flow as a harbinger (lead-time predictor) of European river flow.
Research on modeling hydrological fluxes/budgets and water use has focused recently on a developing a vulnerability index (VI) to quantify human vulnerability to climate change induced decreases of renewable groundwater resources (Figure 2.14).
Figure 2.12 Composite precipitation anomaly between November high minus low river flow years (1968 – 1997) for rivers in NW Norway, which is indicative of inverse correlation of river flow between NW and SE Scandinavia.
The new VI combines projected decrease of Ground-Water Recharge (GWR) with a sensitivity indicator
that is a composite of: a water scarcity indicator, an indicator for dependence of water supply on ground-water and the Human Development Index (Döll, 2009) change scenarios.
The prediction and forecasting of hydrological variability is a growing area of research within EURO FRIEND Project 3. The method of Bayesian merging developed to correct biases in climate model seasonal forecasts was adapted by CEH to evaluate the capability of Global Climate Model (GCM) to forecast Europe’s climate several month ahead. Precipitation hindcasts with 1- to 3-month lead time of seven ensemble runs developed for the European DEMETER project were compared with the ENSEMBLES gridded observational dataset and biases of each model assessed. Monthly hindcasts where merged with rainfall climatology according to the performances of their corresponding GCM to produce probabilistic ensemble forecasts.
These forecasts where disaggregated to a daily time-step using an analogue-based technique, generating 20-member ensembles time series for each grid, then input into the G2G gridded hydrological model (Dadson et al., 2008) to generate daily river flow hindcasts.
Figure 2.13 Composite 500 hPa geopotential height anomaly between October high and low river flow years for rivers in eastern North America, which is indicative of inverse correlation of river flow between eastern North America and northern Europe.
Figure 2.14 Vulnerability index VI showing human vulnerability to climate change induced decreases of renewable groundwater resources by 2055 for four climates.
Initial results show that the merged forecasts perform better than climatology for 1-month lead time; but, at a 3-month lead, biases are generally too large for forecasts to significantly outperform the climatology
Figure 2.15 (a) observed rainfall, (b) historical climatology, (c) Bayesian merged DEMETER hind casts ensemble mean and (d) river flow hind casts (in mm) for February 1995 (28 Feb for river flow).
(Figure 2.15). Additional research is ongoing on seasonal river flow forecasting using outputs from dynamical models, statistical models and combined approaches (Lavers; Prudhomme; Hannah).
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2.3.3 Techniques for Extreme Rainfall and