flow annual maxima; peaks over threshold; trend detection; nonstationary flood frequency analysis; climate change; Wallonia; débits maximums annuels; POT; tendances; analyse fréquentielle non stationnaire; changements climatiques; Wallonie
Abstract :
[en] This study aims at analysing trends in high flows by examining annual maxima (AM), peaks over threshold (POTs) and the number of peaks per year (frequency) in 84 catchments across the Walloon region of Belgium. Trends were identified using statistical tests (regression analysis, Mann-Kendall and Pettitt tests).
Almost 12 % of the sites show a trend in the magnitude of AM and frequency, and 6% show a trend in the magnitude of POTs. Globally, more negative trends have been detected, but the proportion of positive trends is higher in the Scheldt catchment than in the Meuse catchment. The results of nonstationary analysis indicate important changes in the magnitude of the 100-year flood (up to 18 % increase/11 % decrease in 10 years) and the frequency of peak flows (up to 42 % increase/31 % decrease). These changes could therefore impact future flood risk management in Wallonia. However, the time-series are short (30–50 years) and some uncertainty remains. Understanding the mechanisms responsible for the trends is essential to obtain better estimates of future flood flows. A first analysis of potential drivers reveals that changes in precipitation match the trends in high flows, and lower snowfall quantities and higher evapotranspiration rate, caused by the increase in temperature, could have contributed to the decrease in high flows in some regions. [fr] Cette étude a pour but d'analyser les tendances dans l’amplitude et la fréquence des pics de crue (débits maximums annuels, POTs et nombre de pics par an) dans 84 bassins versants de Wallonie. Les tendances ont été détectées à l'aide des tests statistiques de régression linéaire, Mann-Kendall et Pettitt.
Presque 12% des stations de mesure analysées montrent une tendance significative dans l’amplitude des maximums annuels et la fréquence, et 6% montrent une tendance dans l’amplitude des POTs. Globalement, le nombre de tendances négatives est plus élevé, mais la proportion de tendances positives est plus grande dans le bassin de l’Escaut que dans le bassin de la Meuse. Les résultats de l’analyse fréquentielle non stationnaire indiquent des changements importants dans l'amplitude et la fréquence des crues de période de retour de 100 ans (jusqu'à 18% d'augmentation/11% de diminution en 10 ans pour l'amplitude, et jusqu'à 42% d'augmentation/31% de diminution pour la fréquence). Ces changements pourraient dès lors avoir des répercussions sur la gestion des crues en Wallonie. Cependant, les séries chronologiques analysées sont courtes (30 à 50 ans) et une certaine incertitude persiste. Comprendre les mécanismes responsables des tendances est essentiel afin d’obtenir de meilleures estimations des débits de crue futurs. Une première analyse des facteurs potentiellement responsables révèle que les changements dans les précipitations correspondent aux tendances dans les débits de crue, et que les quantités de neige plus faibles ainsi que les taux d’évapotranspiration plus élevés, causés par l’augmentation des températures, pourraient avoir contribué à la diminution des débits de crue dans certaines régions.
Disciplines :
Environmental sciences & ecology
Author, co-author :
Grandry, Maud ; Université de Liège - ULiège > Département GxABT > Echanges Eau-Sol-Plantes
Gailliez, Sébastien; Service public de Wallonie > Agriculture, Ressources naturelles et Environnement > Direction des Cours d'Eau non navigables
Brostaux, Yves ; Université de Liège - ULiège > Département GxABT > Modélisation et développement
Degré, Aurore ; Université de Liège - ULiège > Département GxABT > Echanges Eau-Sol-Plantes
Language :
English
Title :
Looking at trends in high flows at a local scale: The case study of Wallonia (Belgium)
Alternative titles :
[fr] Analyse des tendances dans les débits de crue à l'échelle locale : L'étude de cas de la Wallonie
Publication date :
October 2020
Journal title :
Journal of Hydrology: Regional Studies
eISSN :
2214-5818
Publisher :
Elsevier, Netherlands
Volume :
31
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
HydroTrend
Funders :
SPW Agriculture, Ressources naturelles et Environnement - Service Public de Wallonie. Agriculture, Ressources naturelles et Environnement
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Alfieri, L., Burek, P., Feyen, L., Forzieri, G., Global warming increases the frequency of river floods in Europe. Hydrol. Earth Syst. Sci. 19 (2015), 2247–2260, 10.5194/hess-19-2247-2015.
Archfield, S.A., Hirsch, R.M., Viglione, A., Blöschl, G., Fragmented patterns of flood change across the United States. Geophys. Res. Lett. 43 (2016), 10232–10239, 10.1002/2016GL070590.
Blöschl, G., Hall, J., Viglione, A., Perdigão, R.A.P., Parajka, J., Merz, B., Lun, D., Arheimer, B., Aronica, G.T., Bilibashi, A., Boháč, M., Bonacci, O., Borga, M., Čanjevac, I., Castellarin, A., Chirico, G.B., Claps, P., Frolova, N., Ganora, D., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S., Kireeva, M., Kiss, A., Kjeldsen, T.R., Kohnová, S., Koskela, J.J., Ledvinka, O., Macdonald, N., Mavrova-Guirguinova, M., Mediero, L., Merz, R., Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski, I., Salinas, J.L., Sauquet, E., Šraj, M., Szolgay, J., Volpi, E., Wilson, D., Zaimi, K., Živković, N., Changing climate both increases and decreases European river floods. Nature 573 (2019), 108–111, 10.1038/s41586-019-1495-6.
Coles, S., An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics. 2001, Springer, London, UK, 10.1007/978-1-4471-3675-0.
Cunnane, C., A particular comparison of annual maxima and partial duration series methods of flood frequency prediction. J. Hydrol. 18 (1973), 257–271, 10.1016/0022-1694(73)90051-6.
Cunnane, C., A note on the Poisson assumption in partial duration series models. Water Resour. Res. 15 (1979), 489–494, 10.1029/WR015i002p00489.
Delgado, J.M., Apel, H., Merz, B., Flood trends and variability in the Mekong river. Hydrol. Earth Syst. Sci. 14 (2010), 407–418, 10.5194/hess-14-407-2010.
Gilleland, E., Katz, R.W., extRemes 2.0: an extreme value analysis package in r. J. Stat. Softw., 72, 2016, 10.18637/jss.v072.i08.
Giuntoli, I., Renard, B., Lang, M., Floods in France. Kundzewicz, Z., (eds.) Changes in Flood Risk in Europe, 2012, IAHS Special Publication. IAHS Press and CRC Press, Wallingford, UK, 199–211, 10.1201/b12348-10.
Hamed, K.H., Ramachandra Rao, A., A modified Mann-Kendall trend test for autocorrelated data. J. Hydrol. 204 (1998), 182–196, 10.1016/S0022-1694(97)00125-X.
Interagency Advisory Committee on Water Data, Guidelines for Determining Flood Flow Frequency: Bulletin 17B of the Hydrology Subcommittee. 1982, U.S. Department of the Interior, Geological Survey, Office of Water Data Coordination, Reston.
IPCC, Climate change 2014: synthesis report. Pachauri, R.K., Meyer, L.A., (eds.) Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 2014, IPCC, Geneva, Switzerland [Core Writing Team.
Kundzewicz, Z., Changes in Flood Risk in Europe. 2012, IAHS special publication. IAHS Press and CRC Press, Wallingford, UK.
Kundzewicz, Z.W., Robson, A.J., Change detection in hydrological records—a review of the methodology. Hydrol. Sci. J. 49 (2004), 7–19, 10.1623/hysj.49.1.7.53993.
Lang, M., Ouarda, T.B.M.J., Bobée, B., Towards operational guidelines for over-threshold modeling. J. Hydrol. 225 (1999), 103–117, 10.1016/S0022-1694(99)00167-5.
Li, Zhanling, Wang, Y., Zhao, W., Xu, Z., Li, Zhanjie, Frequency analysis of high flow extremes in the yingluoxia watershed in Northwest China. Water, 8, 2016, 215, 10.3390/w8050215.
Madsen, H., Lawrence, D., Lang, M., Martinkova, M., Kjeldsen, T.R., A Review of Applied Methods in Europe for Flood-frequency Analysis in a Changing Environment: Floodfreq COST Action ES0901: European Procedures for Flood Frequency Estimation. 2013, Centre for Ecology & Hydrology on behalf of COST, Wallingford, UK.
Mangini, W., Viglione, A., Hall, J., Hundecha, Y., Ceola, S., Montanari, A., Rogger, M., Salinas, J.L., Borzì, I., Parajka, J., Detection of trends in magnitude and frequency of flood peaks across Europe. Hydrol. Sci. J. 63 (2018), 493–512, 10.1080/02626667.2018.1444766.
Merz, B., Vorogushyn, S., Uhlemann, S., Delgado, J., Hundecha, Y., HESS Opinions “More efforts and scientific rigour are needed to attribute trends in flood time series.”. Hydrol. Earth Syst. Sci. 16 (2012), 1379–1387, 10.5194/hess-16-1379-2012.
Milly, P.C.D., Betancourt, J., Falkenmark, M., Hirsch, R.M., Kundzewicz, Z.W., Lettenmaier, D.P., Stouffer, R.J., Dettinger, M.D., Krysanova, V., On critiques of “Stationarity is dead: whither water management?”: on critiques of “Stationarity is dead: whither water management?”. Water Resour. Res. 51 (2015), 7785–7789, 10.1002/2015WR017408.
Pohlert, T., Trend: Non-parametric Trend Tests and Change-point Detection. R Package Version 1.1.0. 2018 https://CRAN.R-project.org/package=trend.
R Core Team, R: a Language and Environment for Statistical Computing. 2017, R Foundation for Statistical Computing, Vienna, Austria.
Ribatet, M., Dutang, C., POT: Generalized Pareto Distribution and Peaks over Threshold. R Package Version 1.1-6. 2016 https://CRAN.R-project.org/package=POT.
Robson, A.J., Jones, T.K., Reed, D.W., Bayliss, A.C., A study of national trend and variation in UK floods. Int. J. Climatol. 18 (1998), 165–182, 10.1002/(SICI)1097-0088(199802)18:2<165::AID-JOC230>3.0.CO;2-#.
Rybski, D., Neumann, J., A review on the pettitt test. Kropp, J., Schellnhuber, H.-J., (eds.) In Extremis. Disruptive Events and Trends in Climate and Hydrology, 2011, Springer, Berlin, Heidelberg, 202–213, 10.1007/978-3-642-14863-7_10.
Santander Meteorology Group, Fume: FUME Package. R Package Version 1.0. 2012 https://cran.r-project.org/src/contrib/Archive/fume/.
Scarrott, C., MacDonald, A., A review of extreme value threshold estimation and uncertainty quantification. REVSTAT 10 (2012), 33–60.
Sen, P.K., Estimates of the regression coefficient based on Kendall's tau. J. Am. Stat. Assoc. 63 (1968), 1379–1389, 10.1080/01621459.1968.10480934.
Serinaldi, F., Kilsby, C.G., Stationarity is undead: uncertainty dominates the distribution of extremes. Adv. Water Resour. 77 (2015), 17–36, 10.1016/j.advwatres.2014.12.013.
Serinaldi, F., Kilsby, C.G., The importance of prewhitening in change point analysis under persistence. Stoch. Environ. Res. Risk Assess. 30 (2016), 763–777, 10.1007/s00477-015-1041-5.
Serinaldi, F., Kilsby, C.G., Lombardo, F., Untenable nonstationarity: an assessment of the fitness for purpose of trend tests in hydrology. Adv. Water Resour. 111 (2018), 132–155, 10.1016/j.advwatres.2017.10.015.
Sohier, C., Degré, A., Dautrebande, S., J. Hydrol. 369 (2009), 350–359, 10.1016/j.jhydrol.2009.02.041.
SPW - DGO3 - DEMNA - DEE, Rapport Sur l’état De l'environnement Wallon 2017 (REEW 2017). spw éditions, 2017, Jambes, Belgique.
Šraj, M., Viglione, A., Parajka, J., Blöschl, G., The influence of non-stationarity in extreme hydrological events on flood frequency estimation. J. Hydrol. Hydromech. 64 (2016), 426–437, 10.1515/johh-2016-0032.
Svensson, C., Kundzewicz, W.Z., Maurer, T., Trend detection in river flow series: 2. Flood and low-flow index series. Hydrol. Sci. J., 2005, 50, 10.1623/hysj.2005.50.5.811.
Taesombut, V., Yevjevich, V., Use of partial flood series for estimating distributions of maximum annual flood peak. Hydrology Papers, 1978, Colorado State University, Fort Collins.
Thober, S., Kumar, R., Wanders, N., Marx, A., Pan, M., Rakovec, O., Samaniego, L., Sheffield, J., Wood, E.F., Zink, M., Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degrees global warming. Environ. Res. Lett., 13, 2018, 014003, 10.1088/1748-9326/aa9e35.
Viglione, A., Merz, B., Viet Dung, N., Parajka, J., Nester, T., Blöschl, G., Attribution of regional flood changes based on scaling fingerprints. Water Resour. Res. 52 (2016), 5322–5340, 10.1002/2016WR019036.
Vogel, R.M., Yaindl, C., Walter, M., Nonstationarity: flood magnification and recurrence reduction factors in the United States. JAWRA J. Am. Water Resour. Assoc. 47 (2011), 464–474, 10.1111/j.1752-1688.2011.00541.x.
Willems, P., A time series tool to support the multi-criteria performance evaluation of rainfall-runoff models. Environ. Model. Softw. 24 (2009), 311–321, 10.1016/j.envsoft.2008.09.005.
Willems, P., Multidecadal oscillatory behaviour of rainfall extremes in Europe. Clim. Change 120 (2013), 931–944, 10.1007/s10584-013-0837-x.
Wyard, C., Scholzen, C., Fettweis, X., Van Campenhout, J., François, L., Decrease in climatic conditions favouring floods in the south-east of Belgium over 1959-2010 using the regional climate model MAR. Int. J. Climatol. 37 (2017), 2782–2796, 10.1002/joc.4879.
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.