HEPEX: Connecting the dots in hydrologic ensemble predictions

<p>Since 2004, HEPEX (Hydrologic Ensemble Prediction Experiment) has built a community of researchers and practitioners around the world. After 15 years, its mission continues to be very relevant: to establish a more integrated view of hydrologic forecasting. In this view, data assimilation, hydro-meteorological modelling chains, user behavioural-decision models, pre- and post-processing techniques, expert knowledge, participatory co-evolution of knowledge and user needs, communication and visualisation tools, training material, games and decision support systems are connected to enhance operational services, early warning systems and water management applications. Great progress has been made over the years in terms of using ensemble hydro-meteorological forecasting, but there are still institutional, scientific and operational challenges that the community faces. Here, we present the full range of HEPEX activities, such as workshops, conference sessions, testbeds, learning material and our long-running portal (www.hepex.org). We show how HEPEX can continue to be a relevant network in the coming decades. A large part of that answer lies in the fact that our members use the platform to continuously share their research, make announcements, report on workshops, projects and meetings, and hear about related research and operational challenges. It is also a forum for early career scientists to become increasingly involved in hydrologic forecasting science and applications.</p>

A framework to characterize flood events of defined return period ranges using functional boxplots

<p>To assess the safety of dams, design floods are typically used as a basis. Of particular interest are events with a return period of 1’000 years and even rarer events derived from that with help of simple return period conversion factors given by design codes. However, both the peaks and even more the flood volumes of such rare events are subject to large uncertainties due to limited length and spatial coverage of gauge records. Bivariate approaches can help reduce the uncertainty related to the flood volumes. Nevertheless, both univariate and bivariate approaches require long-term observations on which the return periods of flood events can be calculated.</p><p>In this study, we make use of very long simulated hydrographs in hourly resolution for Swiss catchments (scale range: ~300–18’000 km²). The hydrographs span about 300’000 years each and stem from a hydro-meteorological modelling chain starting with a stochastic multi-site weather generator. With these hydrographs, we develop a framework to characterize design floods through a realistic hydrograph using functional data analysis as well as hydrographs that envelope 50%, say, of the most central observations (corresponding to the 25% and 75% quantiles in a univariate setting).</p><p>In a first step, we assigned the simulated annual maximum flood events to return period classes of 100, 1000 and 10000 years. We then built clusters of similar events within each class using functional clustering. Here we explore some of the possibilities of the approach and in particular show how sensitive the functional clustering is to the choice 1) of event characterization (peak only, flood peak and volume, flood volume given a minimum flood peak), and 2) to the separation of event and baseflow of the selected events in the bivariate case and 3) to the different functional latent mixture models that are applied within the functional clustering.</p>

Assimilating satellite soil moisture and flood extent maps into a flood prediction model.

<p>The main objective of this study is to investigate how innovative satellite earth observation techniques that allow for the estimation of soil moisture and the mapping of flood extents can help in reducing errors and uncertainties in conceptual hydro-meteorological modelling especially in ungauged areas where potentially no or limited runoff records are available. A spatially distributed conceptual hydrological model is first developed allowing for the simulation of soil moisture and flood extent. Using as forcing of this model rainfall and air temperature time series provided in the globally and freely available ERA5 database it is then possible to carry out long-term simulations of soil moisture, discharge and flood extent. Next, time series of soil moisture and flood extent observations derived from freely available satellite image databases are jointly assimilated into the hydrological model in order to retrieve optimal parameter sets. For this assimilation experiment, we take benefit of recently introduced Particle Filters with tempering that circumvent some of the usual particle filter limitations such as degeneracy and sample impoverishment. As a proof of concept, we set up an identical twin experiment based on synthetically generated observations and we evaluate the performance of the calibrated model.</p>

Hypothetical route of the introduction of Schmallenberg virus into Ireland using two complementary analyses

Ireland lost its official freedom from Schmallenberg virus (SBV) in October 2012. The route of introduction is uncertain, with long-distance displacement of infected Culicoides, biting midges, by suitable wind flows considered to be the most likely source. The authors investigated the potential introduction of SBV into Ireland through a Culicoides incursion event in the summer of 2012. They conducted SBV serology on archived bovine sera to identify the prospective dispersal window, then used atmospheric dispersion modelling during periods around this window to identify environmental conditions the authors considered suitable for atmospheric dispersal of Culicoides from potential infected source locations across Southern England. The authors believe that there was one plausible window over the summer of 2012, on August 10–11, based on suitable meteorological conditions. They conclude that a potential long-range transportation event of Culicoides appears to have occurred successfully only once during the 2012 vector competent season. If these incursion events remain at a low frequency, meteorological modelling has the potential to contribute cost-effectively to the alert and response systems for vectorborne diseases in the future.

Surface melt and ponding on Larsen C Ice Shelf and the impact of föhn winds

A common precursor to ice shelf disintegration, most notably that of Larsen B Ice Shelf, is unusually intense or prolonged surface melt and the presence of surface standing water. However, there has been little research into detailed patterns of melt on ice shelves or the nature of summer melt ponds. We investigated surface melt on Larsen C Ice Shelf at high resolution using Envisat advanced synthetic aperture radar (ASAR) data and explored melt ponds in a range of satellite images. The improved spatial resolution of SAR over alternative approaches revealed anomalously long melt duration in western inlets. Meteorological modelling explained this pattern by föhn winds which were common in this region. Melt ponds are difficult to detect using optical imagery because cloud-free conditions are rare in this region and ponds quickly freeze over, but can be monitored using SAR in all weather conditions. Melt ponds up to tens of kilometres in length were common in Cabinet Inlet, where melt duration was most prolonged. The pattern of melt explains the previously observed distribution of ice shelf densification, which in parts had reached levels that preceded the collapse of Larsen B Ice Shelf, suggesting a potential role for föhn winds in promoting unstable conditions on ice shelves.