Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe

Abstract

Abstract. Traditionally, navigation-related forecasts in central Europe cover short-to medium-range lead times linked to the travel times of vessels to pass the main waterway bottlenecks leaving the loading ports. Without doubt, this aspect is still essential for navigational users, but in light of the growing political intention to use the free capacity of the inland waterway transport in Europe, additional lead time supporting strategic decisions is more and more in demand. However, no such predictions offering extended lead times of several weeks up to several months currently exist for considerable parts of the European waterway network. This paper describes the set-up of a monthly to seasonal forecasting system for the German stretches of the international waterways of the Rhine, Danube and Elbe rivers. Two competitive forecast approaches have been implemented: the dynamical set-up forces a hydrological model with postprocessed outputs from ECMWF general circulation model System 4, whereas the statistical approach is based on the empirical relationship ("teleconnection") of global oceanic, climate and regional hydro-meteorological data with river flows. The performance of both forecast methods is evaluated in relation to the climatological forecast (ensemble of historical streamflow) and the well-known ensemble streamflow prediction approach (ESP, ensemble based on historical meteorology) using common performance indicators (correlation coefficient; mean absolute error, skill score; mean squared error, skill score; and continuous ranked probability, skill score) and an impact-based evaluation quantifying the potential economic gain.The following four key findings result from this study: (1) as former studies for other regions of central Europe indicate, the accuracy and/or skill of the meteorological forcing used has a larger effect than the quality of initial hydrological conditions for relevant stations along the German waterways.(2) Despite the predictive limitations on longer lead times in central Europe, this study reveals the existence of a valuable predictability of streamflow on monthly up to seasonal timescales along the Rhine, upper Danube and Elbe waterways, and the Elbe achieves the highest skill and economic value. (3) The more physically based and the statistical approach are able to improve the predictive skills and economic value compared to climatology and the ESP approach. The specific forecast skill highly depends on the forecast location, the lead time and the season. (4) Currently, the statistical approach seems to be most skilful for the three waterways investigated. The lagged relationship between the monthly and/or seasonal streamflow and the climatic and/or oceanic variables vary between 1 month (e.g. local precipitation, temperature and soil moisture) up to 6 months (e.g. sea surface temperature).Besides focusing on improving the forecast methodology, especially by combining the individual approaches, the focus is on developing useful forecast products on monthly to seasonal timesc...

Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity

“…It is important to note that while this activity focused on a flood event, decisions made by the groups would almost certainly have differed if the SHF had indicated drought conditions. The impacts of drought have the potential to affect larger areas, for longer (Bloomfield and Marchant, 2013), notably with respect to agriculture (Li et al, 2017), reservoir management (Turner et al, 2017) and navigation (Meißner et al, 2017). The difference in response between water sector users supports the notion that tailoring SHF information to specific user groups will improve uptake and ability to inform decision-making (Jones et al, 2015;Lorenz et al, 2015;Vaughan et al, 2016;Soares et al, 2018), an area currently being explored by the IMPREX Risk Outlook (IMPREX, 2018b).…”

“…This has the potential to benefit humanitarian action and economic decision-making, e.g. to provide early warning of potential flood and drought events, assist with water quality monitoring, and ensure optimal management and use of water resources for public water supply, agriculture, and industry (Chiew et al, 2003;Arnal et al, 2017;Li et al, 2017;Meißner et al, 2017;Turner et al, 2017). SHF systems covering a range of spatial scales have been developed -Hydrological Outlook UK forecasts at a national level CEH, 2018) -while the Copernicus European and Global Flood Awareness Systems (EFAS and GloFAS) provide operational forecasts over larger scales (JRC, 2018a, b).…”

Characterizing Flood Impact on Swiss Floodplains Using Interannual Time Series of Satellite Imagery

“…-Qmax: yearly maximum discharge [65], [66] -NM7Q2: number of days with a daily average discharge lower than the lowest average discharge observed over seven consecutive days with a return period of two years (extracted from the FOEN reports). Commonly used to describe the effect of droughts periods [67].…”

Application of commensurability method for the long-term forecasting of the highest summer floods on the Danube River at Bratislava

“…All these approaches are quantitative methods of forecasting. In general, for the Danube River basin, simplified methods and a stochastic approach have been used for long-term forecasting (for periods exceeding 10 days) (Pekárová et al 2007;Khrystyuk 2014;Komma et al 2017;Meissner et al 2017). However, quantitative hydrological forecasts are not as reliable as they need to be.…”