Changing climate both increases and decreases European river floods

Climate change has led to concerns about increasing river floods resulting from the greater water-holding capacity of a warmer atmosphere. These concerns are reinforced by evidence of increasing economic losses associated with flooding in many parts of the world, including Europe. Any changes in river floods would have lasting implications for the design of flood protection measures and flood risk zoning. However, existing studies have been unable to identify a consistent continental-scale climatic-change signal in flood discharge observations in Europe, because of the limited spatial coverage and number of hydrometric stations. Here we demonstrate clear regional patterns of both increases and decreases in observed river flood discharges in the past five decades in Europe, which are manifestations of a changing climate. Our results—arising from the most complete database of European flooding so far—suggest that: increasing autumn and winter rainfall has resulted in increasing floods in northwestern Europe; decreasing precipitation and increasing evaporation have led to decreasing floods in medium and large catchments in southern Europe; and decreasing snow cover and snowmelt, resulting from warmer temperatures, have led to decreasing floods in eastern Europe. Regional flood discharge trends in Europe range from an increase of about 11 per cent per decade to a decrease of 23 per cent. Notwithstanding the spatial and temporal heterogeneity of the observational record, the flood changes identified here are broadly consistent with climate model projections for the next century, suggesting that climate-driven changes are already happening and supporting calls for the consideration of climate change in flood risk management

Megafloods in Europe can be anticipated from observations in hydrologically similar catchments

Megafloods that far exceed previously observed records often take citizens and experts by surprise, resulting in extremely severe damage and loss of life. Existing methods based on local and regional information rarely go beyond national borders and cannot predict these floods well because of limited data on megafloods, and because flood generation processes of extremes differ from those of smaller, more frequently observed events. Here we analyse river discharge observations from over 8,000 gauging stations across Europe and show that recent megafloods could have been anticipated from those previously observed in other places in Europe. Almost all observed megafloods (95.5%) fall within the envelope values estimated from previous floods in other similar places on the continent, implying that local surprises are not surprising at the continental scale. This holds also for older events, indicating that megafloods have not changed much in time relative to their spatial variability. The underlying concept of the study is that catchments with similar flood generation processes produce similar outliers. It is thus essential to transcend national boundaries and learn from other places across the continent to avoid surprises and save lives

A downward approach to identifying the structure and parameters of a process-based model for a small experimental catchment

An intensive field monitoring programme was conducted in 1998 and 1999 in an 84 ha catchment located on the North Island of New Zealand. The data collected includes six soil moisture patterns, 12 soil moisture time-series, flow at the outlets of two subcatchments of 56 ha and 28 ha, rainfall and other meteorological data. This data set was used in a downward approach to constrain the conceptualisations and the parameters of a terrain-based distributed model, aiming to simulate the spatial and temporal variability of the soil moisture and the flow response observed in the two subcatchments. The principal mechanism producing runoff was assessed by a preliminary data analysis, involving rainfall, flow and soil moisture time-series as well as the simulation of infiltration processes at the point scale. Runoff was identified as being mainly produced by saturation excess across the entire monitoring period, despite the high intensity rainfall observed in that area. The model soil-water-retention parameters were determined from the soil moisture patterns. The other soil parameters controlling the soil transmissivity were determined by calibration against the observed flow in 1999 in the 56 ha subcatchment, accumulated at the daily scale. The analysis of the flow data at the hourly scale illustrated the need for a more complex subsurface transmissivity function in order to produce lateral storm flow with a larger range of celerity. A simple solution was to modify the decay of the lateral transmissivity with the soil moisture content by adding a second component activated only for soil moisture close to saturation. The additional parameters were calibrated against the observed hourly flow in 1999 in the 56 ha subcatchment. The remaining data were used for validation purposes. This data-driven, downward approach to identifying the model conceptualisation and parameters resulted in a model capable of reproducing the observed catchment behaviour while minimising model complexity

On the computation of the quasi-dynamic wetness index with multiple-flow-direction algorithms

The quasi-dynamic wetness index, in its original development, was computed by calculating the travel time along all the possible upslope flow paths on a contour-based terrain network. In more recent applications the same approach has been extended to gridded digital elevation models with single-flow-direction algorithms. Multiple-flow-direction algorithms, although more effective in representing flow paths, have not been used because they are not practicable with the established methodology. We propose an alternative method for computing the quasi-dynamic wetness index based on the numerical integration of the linear-kinematic wave equation. This method can be applied to any of the terrain-based flow-direction algorithms currently published. The method is robust and efficient

On the definition of the flow width for calculating specific catchment area patterns from gridded elevation data

Specific catchment area (SCA) patterns are commonly computed on grids using flow direction algorithms that treat the flow as coming from a point source at the pixel centre. These algorithms are all ambiguous in the definition of the flow width to be associated with a pixel when computing the SCA. Different methods for computing the flow width have been suggested, without giving an objective reason. In the few cases where this issue has been specifically discussed, the flow width is derived from subjective analysis and incorrect conceptualizations. This paper evaluates alternative approaches for defining the flow width when computing SCA patterns, by comparing theoretical and computed SCA patterns on sloping planes, inward and outward cones. The performances of the different methods are discussed in relation to two dimensionless parameters: (1) the global resolution, defined as the ratio of a characteristic length of the study area to the grid size and (2) the upslope area resolution, defined as the ratio of the theoretical SCA to the grid size. The optimal methods are identified by specific threshold values of these dimensionless parameters. We conclude that assuming the flow width invariant and equal to the grid size is generally the best approach in most practical circumstances

Role of Vegetation on Slope Stability under Transient Unsaturated Conditions

We examine the role of vegetation on the stability of shallow soils under unsaturated transient regime. Two main positive effects of the vegetation on slope stability are discussed: i) a geo-mechanical effect, i.e., the reinforcement of soil by plant roots; ii) a soil-hydrological effect, i.e., the soil suction regime affected by root water uptake. The root distribution is assessed by an eco-hydrological model, which predicts the root density as function of local climatic conditions in growing season and soil hydrological properties. The predicted root distribution is employed for assessing the vertical variability of both the apparent soil cohesion provided by roots and the root water uptake. A one-dimensional model of vertical soil water dynamics is employed for simulating soil suction regime, assumed representative of well-drained soils on steep forested plane slopes. The geo-mechanical and the soil-hydrological effects on slope stability are examined with an infinite slope stability model, generalized for unsaturated conditions. We show that in the case of a loamy-sand soil under a Mediterranean climatic regime, the geo-mechanical effect tends to be more relevant than the soil-hydrological effect during the rainy season, within depths up to twice the average root depth

Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions

Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0forecasts. Impact of individual forecast variables on ET0forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0forecast performances