Effects of temporal resolution of input precipitation on the performance of hydrological forecasting

Flood prediction systems rely on good quality precipitation input data and forecasts to drive hydrological models. Most precipitation data comes from daily stations with a good spatial coverage. However, some flood events occur on sub-daily time scales and flood prediction systems could benefit from using models calibrated on the same time scale. This study compares precipitation data aggregated from hourly stations (HP) and data disaggregated from daily stations (DP) with 6-hourly forecasts from ECMWF over the time period 1 October 2006–31 December 2009. The HP and DP data sets were then used to calibrate two hydrological models, LISFLOOD-RR and HBV, and the latter was used in a flood case study. The HP scored better than the DP when evaluated against the forecast for lead times up to 4 days. However, this was not translated in the same way to the hydrological modelling, where the models gave similar scores for simulated runoff with the two datasets. The flood forecasting study showed that both datasets gave similar hit rates whereas the HP data set gave much smaller false alarm rates (FAR). This indicates that using sub-daily precipitation in the calibration and initiation of hydrological models can improve flood forecasting

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

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

The monetary benefit of early flood warnings in Europe

Effective disaster risk management relies on science-based solutions to close the gap between prevention and preparedness measures. The consultation on the United Nations post-2015 framework for disaster risk reduction highlights the need for cross-border early warning systems to strengthen the preparedness phases of disaster risk management, in order to save lives and property and reduce the overall impact of severe events. Continental and global scale flood forecasting systems provide vital early flood warning information to national and international civil protection authorities, who can use this information to make decisions on how to prepare for upcoming floods. Here the potential monetary benefits of early flood warnings are estimated based on the forecasts of the continental-scale European Flood Awareness System (EFAS) using existing flood damage cost information and calculations of potential avoided flood damages. The benefits are of the order of 400 Euro for every 1 Euro invested. A sensitivity analysis is performed in order to test the uncertainty in the method and develop an envelope of potential monetary benefits of EFAS warnings. The results provide clear evidence that there is likely a substantial monetary benefit in this cross-border continental-scale flood early warning system. This supports the wider drive to implement early warning systems at the continental or global scale to improve our resilience to natural hazards

Cultural Context in the Effort to Improve Oral Health Among Alaska Native People: The Dental Health Aide Therapist Model

The Alaska Native people in rural Alaska face serious challenges in obtaining dental care. Itinerant care models have failed to meet their needs for more than 50 years. The dental health aide therapist (DHAT) model, which entails training midlevel care providers to perform limited restorative, surgical, and preventive procedures, was adopted to address some of the limitations of the itinerant model. We used quantitative and qualitative methods to assess residents’ satisfaction with the model and the role of DHATs in the cultural context in which they operate. Our findings suggest that the DHAT model can provide much-needed access to urgent care and is beneficial from a comprehensive cultural perspective

Forecast convergence score: a forecaster's approach to analysing hydro-meteorological forecast systems.

In this paper the properties of a hydro-meteorological forecasting system for forecasting river flows have been analysed using a probabilistic forecast convergence score (FCS). The focus on fixed event forecasts provides a forecaster's approach to system behaviour and adds an important perspective to the suite of forecast verification tools commonly used in this field. A low FCS indicates a more consistent forecast. It can be demonstrated that the FCS annual maximum decreases over the last 10 years. With lead time, the FCS of the ensemble forecast decreases whereas the control and high resolution forecast increase. The FCS is influenced by the lead time, threshold and catchment size and location. It indicates that one should use seasonality based decision rules to issue flood warnings

Evaluation of the Dental Health Aide Therapist Workforce Model in Alaska (Final Report)

In January 2008, the W.K. Kellogg Foundation, in collaboration with ANTHC, the Rasmuson Foundation, and the Bethel Community Services Foundation, requested that an experienced organization provide an independent, detailed, and objective evaluation of the initial implementation of the Dental Health Aide Therapist (DHAT) program

Potential of pan-european seasonal hydrometeorological drought forecasts obtained from a multihazard early warning system

Drought early warning systems (DEWS) have been developed in several countries in response to high socioeconomic losses caused by droughts. In Europe, the European Drought Observatory (EDO) monitors the ongoing drought and forecasts soil moisture anomalies up to 7 days ahead and meteorological drought up to 3 months ahead. However, end users managing water resources often require hydrological drought warning several months in advance. To answer this challenge, a seasonal pan-European DEWS has been developed and has been running in a preoperational mode since mid-2018 under the EU-funded Enhancing Emergency Management and Response to Extreme Weather and Climate Events (ANYWHERE) project. The ANYWHERE DEWS (AD-EWS) is different than other operational DEWS in the sense that the AD-EWS provides a wide range of seasonal hydrometeorological drought forecasting products in addition to meteorological drought, that is, a broad suite of drought indices that covers all water cycle components (drought in precipitation, soil moisture, runoff, discharge, and groundwater). The ability of the AD-EWS to provide seasonal drought predictions in high spatial resolution (5 km × 5 km) and its diverse products mark the AD-EWS as a preoperational drought forecasting system that can serve a broad range of different users' needs in Europe. This paper introduces the AD-EWS and shows some examples of different drought forecasting products, the drought forecast score, and some examples of a user-driven assessment of forecast trust levels.</p

Imbalanced land-surface water budgets in a numerical weather prediction system

There has been a significant increase in the skill and resolution of numerical weather prediction models (NWPs) in recent decades, extending the time scales of useful weather predictions. The land-surface models (LSMs) of NWPs are often employed in hydrological applications, which raises the question of how hydrologically representative LSMs really are. In this paper, precipitation (P), evaporation (E) and runoff (R) from the European Centre for Medium-Range Weather Forecasts (ECMWF) global models were evaluated against observational products. The forecasts differ substantially from observed data for key hydrological variables. In addition, imbalanced surface water budgets, mostly caused by data assimilation, were found on both global (P-E) and basin scales (P-E-R), with the latter being more important. Modeled surface fluxes should be used with care in hydrological applications and further improvement in LSMs in terms of process descriptions, resolution and estimation of uncertainties is needed to accurately describe the land-surface water budgets

Skilful seasonal forecasts of streamflow over Europe?

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the Ensemble Streamflow Prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to seven months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40% of Europe. Patterns in the EFAS seasonal streamflow hindcasts skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim to improve climate-model based seasonal streamflow forecasting

Effect of sequence length, sequence frequency, and data acquisition rate on the performance of a hadamard transform time-of-flight mass spectrometer

AbstractVarious factors influencing the performance of a Hadamard transform time-of-flight mass spectrometer (HT-TOFMS) have been investigated. Using a nitrogen corona discharge to produce an ion stream of N2+, N3+, and N4+, it is found for spectra containing only N4+ that the signal-to-noise ratio (SNR) closely approaches the value calculated from the ion background by assuming that the ion background follows a Poisson distribution. In contrast, for a more intense beam containing N2+, N3+, and N4+, the SNR is less than its theoretical value because of the appearance of discrete spikes in the mass spectrum caused by deviations in the actual modulation sequence from the ideal one. These spikes can be reduced, however, by decreasing the modulation voltage. Under these optimized conditions, the pseudo-random sequence length is varied to understand how it alters SNR, mass resolution, and scan speed. When the length of the pseudo-random sequence is doubled, the SNR increases by 2 while the time necessary to record a mass spectrum also doubles. Mass resolution can be varied between 500 and 1200 at m/z = 609 as the sequence length, modulation speed (10 MHz, 25 MHz), and acquisition rate (up to 50 MHz) are changed. Scan speeds of 6000 passes per s can be obtained using a sequence containing 4095 elements modulated at 25 MHz. The capability to tailor the HT-TOFMS to increase the scan speed and resolution with a constant 50% duty cycle makes the technique extremely appealing as a mass analyzer for measuring rapid changes in the composition of an ion stream