TY - JOUR A1 - Vorogushyn, Sergiy A1 - Apel, Heiko A1 - Kemter, Matthias A1 - Thieken, Annegret T1 - Analyse der Hochwassergefährdung im Ahrtal unter Berücksichtigung historischer Hochwasser T1 - Analysis of flood hazard in the Ahr Valley considering historical floods JF - Hydrologie und Wasserbewirtschaftung N2 - The flood disaster in July 2021 in western Germany calls for a critical discussion on flood hazard assessment, revision of flood hazard maps and communication of extreme flood scenarios. In the presented work, extreme value analysis was carried out for annual maximum peak flow series at the Altenahr gauge on the river Ahr. We compared flood statistics with and without considering historical flood events. An estimate for the return period of the recent flood based on the Generalized Extreme Value (GEV) distribution considering historical floods ranges between about 2600 and above 58700 years (90% confidence interval) with a median of approximately 8600 years, whereas an estimate based on the 74-year long systematically recorded flow series would theoretically exceed 100 million years. Consideration of historical floods dramatically changes the flood quantiles that are used for the generation of official flood hazard maps. The fitting of the GEV to the time series with historical floods reveals, however, that the model potentially inadequately reflects the flood population. In this case, we might face a mixed sample, in which extreme floods result from very different processes compared to smaller floods. Hence, the probabilities of extreme floods could be much larger than those resulting from a single GEV model. The application of a process-based mixed flood distribution should be explored in future work.
The comparison of the official HQextrem flood maps for the AhrValley with the inundation areas from July 2021 shows a striking discrepancy in the affected areas and calls for revision of design values used to define extreme flood scenarios. The hydrodynamic simulations of a 1000-year return period flood considering historical events and of the 1804 flood scenario compare much better to the flooded areas from July 2021, though both scenarios still underestimated the flood extent.
Particular effects such as clogging of bridges and geomorphological changes of the river channel led to considerably larger flooded areas in July 2021 compared to the simulation results. Based on this analysis, we call for a consistent definition of HQextrem for flood hazard mapping in Germany, and suggest using high flood quantiles in the range of a 1,000-year flood. Flood maps should additionally include model-based reconstructions of the largest, reliably documented historical floods and/or synthetic worst-case scenarios. This would be an important step towards protecting potentially affected population and disaster management from surprises due to very rare and extreme flood events in future. N2 - Die Hochwasserkatastrophe im Juli 2021 in Westdeutschland erfordert eine kritische Diskussion über die Abschätzung der Hochwassergefährdung, Aktualisierung von Hochwassergefahrenkarten und Kommunikation von extremen Hochwasserszenarien. In der vorliegenden Arbeit wurde die Extremwertstatistik für die jährlichen maximalen Spitzenabflüsse am Pegel Altenahr im Ahrtal mit und ohne Berücksichtigung historischer Hochwasser berechnet und verglichen. Die Schätzung der Wiederkehrperiode für das aktuelle Hochwasser mittels Generalisierter Extremwertverteilung (GEV) unter Berücksichtigung historischer Hochwasser schwankt zwischen etwa 2.600 und über 58.700 Jahren (90%-Konfidenzintervall) mit einem Median bei etwa 8.600 Jahren, wogegen die Schätzung, die nur auf der systematisch gemessenen Abflusszeitreihe von 74 Jahren basiert, theoretisch eine Wiederkehrperiode von über 100 Millionen Jahren ergeben würde. Die Berücksichtigung der historischen Hochwasser führt zu einer dramatischen Änderung der Hochwasserquan- tile, die für eine Gefahrenkartierung zugrunde gelegt werden. Die Anpassung der GEV an die Zeitreihe mit historischen Hochwassern zeigt dennoch, dass das GEV-Modell möglicherweise die Grundgesamtheit der Hochwasser im Ahrtal nicht adäquat abbilden kann. Es könnte sich im vorliegenden Fall um eine gemischte Stichprobe handeln, in der die extremen Hochwasser im Vergleich zu kleineren Ereignissen durch besondere Prozesse hervorgerufen werden. Somit könnten die Wahrscheinlichkeiten von extremen Hochwassern deutlich größer sein, als aus dem GEV-Modell hervorgeht. Hier sollte in Zukunft die Anwendung einer prozessbasierten Mischverteilung untersucht werden. Der Vergleich von amtlichen Gefahrenkarten zu Extremhochwassern (HQextrem) im Ahrtal mit den Überflutungsflächen vom Juli 2021 zeigt eine deutliche Diskrepanz in den betroffenen Gebieten und die Notwendigkeit, die Grundlagen zur Erstellung der Extremszenarien zu überdenken. Die hydrodynamisch-numerischen Simulationen von 1.000-jährlichen Hochwassern (HQ1000) unter Berücksichtigung historischer Ereignisse und des größten historischen Hochwassers 1804 können die Gefährdung des Juli-Hochwassers 2021 deutlich besser widerspiegeln, wenngleich auch diese beiden Szenarien die Überflutungsflächen unterschätzen. Besondere Effekte wie die Verklausung von Brücken und die geomorphologischen Änderungen im Flussschlauch führten zu noch größeren Überflutungs- flächen im Juli 2021, als die Simulationsergebnisse zeigten. Basierend auf dieser Analyse wird eine einheitliche Festlegung von HQextrem bei Hochwassergefahrenkartierungen in Deutschland vorgeschlagen, die sich an höheren Hochwasserquantilen im Bereich von HQ1000 orientiert. Zusätzlich sollen simulationsbasierte Rekonstruktionen von den größten verlässlich dokumentierten historischen Hochwassern und/oder synthetische Worst-Case-Szenarien in den Hochwassergefahrenkarten gesondert dargestellt werden. Damit wird ein wichtiger Beitrag geleistet, um die potenziell betroffene Bevölkerung und das Katastrophenmanagement vor Überraschungen durch sehr seltene und extreme Hochwasser in Zukunft besser zu schützen. KW - Extreme value statistics KW - historical floods KW - flood hazard mapping; KW - inundation simulation KW - Ahr River KW - Extremwertstatistik KW - historische Hochwasser KW - Gefahrenkarten KW - Überflutungssimulation KW - Ahr Y1 - 2022 U6 - https://doi.org/10.5675/HyWa_2022.5_2 SN - 1439-1783 VL - 66 IS - 5 SP - 244 EP - 254 PB - Bundesanst. für Gewässerkunde CY - Koblenz ER - TY - JOUR A1 - Triet, Nguyen Van Khanh A1 - Dung, Nguyen Viet A1 - Merz, Bruno A1 - Apel, Heiko T1 - Towards risk-based flood management in highly productive paddy rice cultivation BT - concept development and application to the Mekong Delta JF - Natural hazards and earth system sciences N2 - Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost-benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam. Y1 - 2018 U6 - https://doi.org/10.5194/nhess-18-2859-2018 SN - 1561-8633 VL - 18 IS - 11 SP - 2859 EP - 2876 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Triet, Nguyen Van Khanh A1 - Dung, Nguyen Viet A1 - Merz, Bruno A1 - Apel, Heiko T1 - Towards risk-based flood management in highly productive paddy rice cultivation BT - concept development and application to the Mekong Delta T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost-benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 931 KW - climate change KW - hazard analysis KW - sea level KW - Tho city KW - Vietnam KW - damage KW - uncertainty KW - models KW - floodplains KW - hydrology Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-446032 SN - 1866-8372 IS - 931 SP - 2859 EP - 2876 ER - TY - JOUR A1 - Thieken, Annegret A1 - Apel, Heiko A1 - Merz, Bruno T1 - Assessing the probability of large-scale flood loss events: a case study for the river Rhine, Germany JF - Journal of flood risk management N2 - Flood risk analyses are often estimated assuming the same flood intensity along the river reach under study, i.e. discharges are calculated for a number of return periods T, e.g. 10 or 100 years, at several streamflow gauges. T-year discharges are regionalised and then transferred into T-year water levels, inundated areas and impacts. This approach assumes that (1) flood scenarios are homogeneous throughout a river basin, and (2) the T-year damage corresponds to the T-year discharge. Using a reach at the river Rhine, this homogeneous approach is compared with an approach that is based on four flood types with different spatial discharge patterns. For each type, a regression model was created and used in a Monte-Carlo framework to derive heterogeneous scenarios. Per scenario, four cumulative impact indicators were calculated: (1) the total inundated area, (2) the exposed settlement and industrial areas, (3) the exposed population and 4) the potential building loss. Their frequency curves were used to establish a ranking of eight past flood events according to their severity. The investigation revealed that the two assumptions of the homogeneous approach do not hold. It tends to overestimate event probabilities in large areas. Therefore, the generation of heterogeneous scenarios should receive more attention. KW - damage estimation KW - discharge pattern KW - exposure KW - flood risk analysis KW - frequency analysis KW - land-use KW - population density Y1 - 2015 U6 - https://doi.org/10.1111/jfr3.12091 SN - 1753-318X VL - 8 IS - 3 SP - 247 EP - 262 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Steirou, Eva A1 - Gerlitz, Lars A1 - Apel, Heiko A1 - Sun, Xun A1 - Merz, Bruno T1 - Climate influences on flood probabilities across Europe JF - Hydrology and earth system sciences : HESS N2 - The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods. Y1 - 2019 U6 - https://doi.org/10.5194/hess-23-1305-2019 SN - 1027-5606 SN - 1607-7938 VL - 23 IS - 3 SP - 1305 EP - 1322 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Seibert, Mathias A1 - Merz, Bruno A1 - Apel, Heiko T1 - Seasonal forecasting of hydrological drought in the Limpopo Basin BT - a comparison of statistical methods T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Nino and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42% explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 626 KW - sea-surface temperature KW - southern Africa KW - neural-network KW - summer rainfall KW - Atlantic-Ocean KW - river-basin KW - predictability KW - variability KW - prediction KW - climate Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418442 IS - 626 SP - 1611 EP - 1629 ER - TY - JOUR A1 - Seibert, Mathias A1 - Merz, Bruno A1 - Apel, Heiko T1 - Seasonal forecasting of hydrological drought in the Limpopo Basin BT - a comparison of statistical methods JF - Hydrology and earth system sciences : HESS N2 - The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Nino and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42% explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts. Y1 - 2017 U6 - https://doi.org/10.5194/hess-21-1611-2017 SN - 1027-5606 SN - 1607-7938 VL - 21 SP - 1611 EP - 1629 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Nguyen Viet Dung, A1 - Merz, Bruno A1 - Bardossy, Andras A1 - Apel, Heiko T1 - Handling uncertainty in bivariate quantile estimation - An application to flood hazard analysis in the Mekong Delta JF - Journal of hydrology N2 - The hydrological load causing flood hazard is in many instances not only determined by peak discharge, but is a multidimensional problem. While the methodology for multivariate frequency analysis is well established, the estimation of the associated uncertainty is rarely studied. In this paper, a method is developed to quantify the different sources of uncertainty for a bivariate flood frequency analysis. The method is exemplarily developed for the Mekong Delta (MD), one of the largest and most densely populated river deltas worldwide. Floods in the MD are the basis for the livelihoods of the local population, but they are also the major hazard. This hazard has, however, not been studied within the frame of a probabilistic flood hazard analysis. The nature of the floods in the MD suggests a bivariate approach, because the societal flood severity is determined by both peak discharge and flood volume. The uncertainty caused by selection of statistical models and parameter estimation procedures are analyzed by applying different models and methods. For the quantification of the sampling uncertainty two bootstrapping methods were applied. The developed bootstrapping-based uncertainty estimation method shows that large uncertainties are associated with the estimation of bivariate flood quantiles. This uncertainty is much larger than the model selection and fitting uncertainty. Given the rather long data series of 88 years, it is concluded that bivariate flood frequency analysis is expected to carry significant uncertainty and that the quantification and reduction of uncertainty merit greater attention. But despite this uncertainty the proposed approach has certainly major advantages compared to a univariate approach, because (a) it reflects the two essential aspects of floods in this region, (b) the uncertainties are inherent for every bivariate frequency analysis in hydrology due to the general limited length of observations and can hardly be avoided, and (c) a framework for the quantification of the uncertainties is given, which can be used and interpreted in the hazard assessment. In addition it is shown by a parametric bootstrapping experiment how longer observation time series can reduce the sampling uncertainty. Based on this finding it is concluded that bivariate frequency analyses in hydrology would greatly benefit from discharge time series augmented by proxy or historical data, or by causal hydrologic expansion of time series. (C) 2015 Elsevier B.V. All rights reserved. KW - Bivariate flood quantile KW - Copulas KW - Uncertainty estimation KW - Bootstrapping KW - Mekong Delta Y1 - 2015 U6 - https://doi.org/10.1016/j.jhydrol.2015.05.033 SN - 0022-1694 SN - 1879-2707 VL - 527 SP - 704 EP - 717 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Nguyen Nghia Hung, A1 - Delgado, José Miguel Martins A1 - Güntner, Andreas A1 - Merz, Bruno A1 - Bardossy, Andras A1 - Apel, Heiko T1 - Sedimentation in the floodplains of the Mekong Delta, Vietnam. Part I: suspended sediment dynamics JF - Hydrological processes N2 - Suspended sediment is the primary source for a sustainable agro-ecosystem in the Mekong Delta by providing nutrient input for the subsequent cropping season. In addition, the suspended sediment concentration (SSC) plays an important role in the erosion and deposition processes in the Delta; that is, it influences the morphologic development and may counteract the deltaic subsidence and sea level rise. Despite this importance, little is known about the dynamics of suspended sediment in the floodplains of the Mekong Delta. In particular, quantitative analyses are lacking mainly because of data scarcity with respect to the inundation processes in the floodplains. In 2008, therefore, a comprehensive in situ system to monitor the dynamics of suspended sediment in a study area located in the Plain of Reeds was established, aiming at the characterization and quantification of suspended sediment dynamics in the deeply inundated parts of the Vietnamese part of the Mekong Delta. The monitoring system was equipped with seven water quality-monitoring stations. They have a robust design and autonomous power supply suitable for operation on inundated floodplains, enabling the collection of reliable data over a long period of time with a high temporal resolution. The data analysis shows that the general seasonal dynamics of suspended sediment transport in the Delta is controlled by two main mechanisms: the flood wave of the Mekong River and the tidal backwater influences from the coast. In the channel network, SSC decreases exponentially with distance from the Mekong River. The anthropogenic influence on SSC could also be identified for two periods: at the start of the floodplain inundation and at the end of the flood period, when subsequent paddy rice crops are prepared. Based on the results, we recommend an operation scheme for the sluice gates, which intends to distribute the sediment and thus the nutrients equally over the floodplain. KW - Mekong Delta KW - floodplain KW - suspended sediment KW - sediment dynamics KW - floodplain sedimentation Y1 - 2014 U6 - https://doi.org/10.1002/hyp.9856 SN - 0885-6087 SN - 1099-1085 VL - 28 IS - 7 SP - 3132 EP - 3144 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Nguyen Nghia Hung, A1 - Delgado, José Miguel Martins A1 - Guentner, Andreas A1 - Merz, Bruno A1 - Bardossy, Andras A1 - Apel, Heiko T1 - Sedimentation in the floodplains of the Mekong Delta, Vietnam Part II: deposition and erosion JF - Hydrological processes N2 - Deposition and erosion play a key role in the determination of the sediment budget of a river basin, as well as for floodplain sedimentation. Floodplain sedimentation, in turn, is a relevant factor for the design of flood protection measures, productivity of agro-ecosystems, and for ecological rehabilitation plans. In the Mekong Delta, erosion and deposition are important factors for geomorphological processes like the compensation of deltaic subsidence as well as for agricultural productivity. Floodplain deposition is also counteracting the increasing climate change induced hazard by sea level rise in the delta. Despite this importance, a sediment database of the Mekong Delta is lacking, and the knowledge about erosion and deposition processes is limited. In the Vietnamese part of the Delta, the annually flooded natural floodplains have been replaced by a dense system of channels, dikes, paddy fields, and aquaculture ponds, resulting in floodplain compartments protected by ring dikes. The agricultural productivity depends on the sediment and associated nutrient input to the floodplains by the annual floods. However, no quantitative information regarding their sediment trapping efficiency has been reported yet. The present study investigates deposition and erosion based on intensive field measurements in three consecutive years (2008, 2009, and 2010). Optical backscatter sensors are used in combination with sediment traps for interpreting deposition and erosion processes in different locations. In our study area, the mean calculated deposition rate is 6.86kg/m(2) (approximate to 6mm/year). The key parameters for calculating erosion and deposition are estimated, i.e. the critical bed shear stress for deposition and erosion and the surface constant erosion rate. The bulk of the floodplain sediment deposition is found to occur during the initial stage of floodplain inundation. This finding has direct implications on the operation of sluice gates in order to optimize sediment input and distribution in the floodplains. KW - Mekong delta KW - sediment dynamics KW - deposition KW - erosion KW - floodplain sedimentation Y1 - 2014 U6 - https://doi.org/10.1002/hyp.9855 SN - 0885-6087 SN - 1099-1085 VL - 28 IS - 7 SP - 3145 EP - 3160 PB - Wiley-Blackwell CY - Hoboken ER -