FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3091492738> ?p ?o ?g. }

• W3091492738 endingPage "4023" @default.
• W3091492738 startingPage "3991" @default.
• W3091492738 abstract "Abstract. Streamflow drought forecasting is a key element of contemporary drought early warning systems (DEWS). The term streamflow drought forecasting (not streamflow forecasting), however, has created confusion within the scientific hydrometeorological community as well as in operational weather and water management services. Streamflow drought forecasting requires an additional step, which is the application of a drought identification method to the forecasted streamflow time series. The way streamflow drought is identified is the main reason for this misperception. The purpose of this study, therefore, is to provide a comprehensive overview of the differences between different drought identification approaches to identify droughts in European rivers, including an analysis of both historical drought and implications for forecasting. Streamflow data were obtained from the LISFLOOD hydrological model forced with gridded meteorological observations (known as LISFLOOD-Simulation Forced with Observed, SFO). The same model fed with seasonal meteorological forecasts of the European Centre for Medium-Range Weather Forecasts system 5 (ECMWF SEAS 5) was used to obtain the forecasted streamflow. Streamflow droughts were analyzed using the daily and monthly variable threshold methods (VTD and VTM, respectively), the daily and monthly fixed threshold methods (FTD and FTM, respectively), and the Standardized Streamflow Index (SSI). Our results clearly show that streamflow droughts derived from different approaches deviate from each other in their characteristics, which also vary in different climate regions across Europe. The daily threshold methods (FTD and VTD) identify 25 %–50 % more drought events than the monthly threshold methods (FTM and VTM), and accordingly the average drought duration is longer for the monthly than for the daily threshold methods. The FTD and FTM, in general, identify drought occurrences earlier in the year than the VTD and VTM. In addition, the droughts obtained with the VTM and FTM approaches also have higher drought deficit volumes (about 25 %–30 %) than the VTD and FTD approaches. Overall, the characteristics of SSI-1 drought are close to what is being identified by the VTM. The different outcome obtained with the drought identification methods illustrated with the historical analysis is also found in drought forecasting, as documented for the 2003 drought across Europe and for the Rhine River specifically. In the end, there is no unique hydrological drought definition (identification method) that fits all purposes, and hence developers of DEWS and end-users should clearly agree in the co-design phase upon a sharp definition of which type of streamflow drought is required to be forecasted for a specific application." @default.
• W3091492738 created "2020-10-08" @default.
• W3091492738 creator A5017859362 @default.
• W3091492738 creator A5062859909 @default.
• W3091492738 date "2021-07-08" @default.
• W3091492738 modified "2023-10-18" @default.
• W3091492738 title "Streamflow drought: implication of drought definitions and its application for drought forecasting" @default.
• W3091492738 cites W1481493079 @default.
• W3091492738 cites W1733387413 @default.
• W3091492738 cites W1966053895 @default.
• W3091492738 cites W1969025394 @default.
• W3091492738 cites W1981410107 @default.
• W3091492738 cites W1983659260 @default.
• W3091492738 cites W1987213677 @default.
• W3091492738 cites W1987223597 @default.
• W3091492738 cites W2002993215 @default.
• W3091492738 cites W2005027894 @default.
• W3091492738 cites W2008406497 @default.
• W3091492738 cites W2012316213 @default.
• W3091492738 cites W2025163177 @default.
• W3091492738 cites W2030997108 @default.
• W3091492738 cites W2046548554 @default.
• W3091492738 cites W2050590406 @default.
• W3091492738 cites W2058697310 @default.
• W3091492738 cites W2060742029 @default.
• W3091492738 cites W2062030462 @default.
• W3091492738 cites W2066266401 @default.
• W3091492738 cites W2066869547 @default.
• W3091492738 cites W2067811735 @default.
• W3091492738 cites W2068154595 @default.
• W3091492738 cites W2077968790 @default.
• W3091492738 cites W2079436405 @default.
• W3091492738 cites W2081385040 @default.
• W3091492738 cites W2084539466 @default.
• W3091492738 cites W2085622134 @default.
• W3091492738 cites W2087692861 @default.
• W3091492738 cites W2098395575 @default.
• W3091492738 cites W2101108516 @default.
• W3091492738 cites W2102306542 @default.
• W3091492738 cites W2103897732 @default.
• W3091492738 cites W2104157175 @default.
• W3091492738 cites W2104923199 @default.
• W3091492738 cites W2108747251 @default.
• W3091492738 cites W2110283898 @default.
• W3091492738 cites W2112652250 @default.
• W3091492738 cites W2115040356 @default.
• W3091492738 cites W2115787587 @default.
• W3091492738 cites W2131168193 @default.
• W3091492738 cites W2136624080 @default.
• W3091492738 cites W2140990633 @default.
• W3091492738 cites W2142313203 @default.
• W3091492738 cites W2144425071 @default.
• W3091492738 cites W2158238669 @default.
• W3091492738 cites W2158952405 @default.
• W3091492738 cites W2163564649 @default.
• W3091492738 cites W2168643429 @default.
• W3091492738 cites W2169047369 @default.
• W3091492738 cites W2169130133 @default.
• W3091492738 cites W2171772062 @default.
• W3091492738 cites W2190221061 @default.
• W3091492738 cites W2305228282 @default.
• W3091492738 cites W2402979397 @default.
• W3091492738 cites W2492367495 @default.
• W3091492738 cites W2525497107 @default.
• W3091492738 cites W2527936139 @default.
• W3091492738 cites W2556551185 @default.
• W3091492738 cites W2566149158 @default.
• W3091492738 cites W2602478233 @default.
• W3091492738 cites W2742138420 @default.
• W3091492738 cites W2750579652 @default.
• W3091492738 cites W2765130651 @default.
• W3091492738 cites W2786406624 @default.
• W3091492738 cites W2800227153 @default.
• W3091492738 cites W2800422393 @default.
• W3091492738 cites W2808732975 @default.
• W3091492738 cites W2900002673 @default.
• W3091492738 cites W2901925076 @default.
• W3091492738 cites W2937854818 @default.
• W3091492738 cites W2979488047 @default.
• W3091492738 cites W2982405828 @default.
• W3091492738 cites W2983826499 @default.
• W3091492738 cites W2990208435 @default.
• W3091492738 cites W3006264628 @default.
• W3091492738 cites W3013127151 @default.
• W3091492738 cites W3017759183 @default.
• W3091492738 cites W3021324401 @default.
• W3091492738 cites W3087031736 @default.
• W3091492738 cites W3087748803 @default.
• W3091492738 cites W3094178618 @default.
• W3091492738 cites W4245758598 @default.
• W3091492738 doi "https://doi.org/10.5194/hess-25-3991-2021" @default.
• W3091492738 hasPublicationYear "2021" @default.
• W3091492738 type Work @default.
• W3091492738 sameAs 3091492738 @default.
• W3091492738 citedByCount "15" @default.
• W3091492738 countsByYear W30914927382021 @default.
• W3091492738 countsByYear W30914927382022 @default.
• W3091492738 countsByYear W30914927382023 @default.

• next