ALBERT

Description: Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.

Description: In this paper we present a novel approach for flood hazard analysis of the whole Mekong Delta with a particular focus on the Vietnamese part. Based on previous studies identifying the flood regime in the Mekong delta as non-stationary (Delgado et al., 2010), we develop a non-stationary approach for flood hazard analysis. Moreover, the approach is also bi-variate, as the flood severity in the Mekong Delta is determined by both maximum discharge and flood volume, which determines the flood duration. Probabilities of occurrences of peak discharge and flood volume are estimated by a copula. The flood discharges and volumes are used to derive synthetic hydrographs, which in turn constitute the upper boundary condition for a large-scale hydrodynamic model covering the whole Mekong Delta. The hydrodynamic model transforms the hydrographs into hazard maps. In addition, we extrapolate the observed trends in flood peak and volume and their associated non-stationary extreme value distributions to the year 2030 in order to give a flood hazard estimate for the near future. The uncertainty of extreme flood events in terms of different possible combinations of peak discharge and flood volume given by the copula is considered. Also, the uncertainty in flood hydrograph shape is combined with parameter uncertainty of the hydrodynamic model in a Monte Carlo framework yielding uncertainty estimates in terms of quantile flood maps. The proposed methodology sets the frame for the development of probabilistic flood hazard maps for the entire Mekong Delta. The combination of bi-variate, non-stationary extreme value statistics with large-scale flood inundation modeling and uncertainty quantification is novel in itself. Moreover, it is in particular novel for the Mekong Delta: a region where not even a standard hazard analysis based on a univariate, stationary extreme value statistic exists.

Description: Automatic and multi-objective calibration of hydrodynamic models is – compared to other disciplines like e.g. hydrology – still underdeveloped. This has mainly two reasons: the lack of appropriate data and the large computational demand in terms of CPU-time. Both aspects are aggravated in large-scale applications. However, there are recent developments that improve the situation on both the data and computing side. Remote sensing, especially radar-based techniques proved to provide highly valuable information on flood extents, and in case high precision DEMs are present, also on spatially distributed inundation depths. On the computing side the use of parallelization techniques brought significant performance gains. In the presented study we build on these developments by calibrating a large-scale 1-dimensional hydrodynamic model of the whole Mekong Delta downstream of Kratie in Cambodia: we combined in-situ data from a network of river gauging stations, i.e. data with high temporal but low spatial resolution, with a series of inundation maps derived from ENVISAT Advanced Synthetic Aperture Radar (ASAR) satellite images, i.e. data with low temporal but high spatial resolution, in an multi-objective automatic calibration process. It is shown that an automatic, multi-objective calibration of hydrodynamic models, even of such complexity and on a large scale and complex as a model for the Mekong Delta, is possible. Furthermore, the calibration process revealed model deficiencies in the model structure, i.e. the representation of the dike system in Vietnam, which would have been difficult to detect by a standard manual calibration procedure.

Description: Sediment dynamics play a major role in the agricultural and fishery productivity of the Mekong Delta. However, the understanding of sediment dynamics in the delta, one of the most complex river deltas in the world, is very limited. This is a consequence of its large extent, the intricate system of rivers, channels and floodplains, and the scarcity of observations. This study quantifies, for the first time, the suspended sediment transport and sediment deposition in the whole Mekong Delta. To this end, a quasi-2D hydrodynamic model is combined with a cohesive sediment transport model. The combined model is calibrated using six objective functions to represent the different aspects of the hydraulic and sediment transport components. The model is calibrated for the extreme flood season in 2011 and shows good performance for 2 validation years with very different flood characteristics. It is shown how sediment transport and sediment deposition is differentiated from Kratie at the entrance of the delta on its way to the coast. The main factors influencing the spatial sediment dynamics are the river and channel system, dike rings, sluice gate operations, the magnitude of the floods, and tidal influences. The superposition of these factors leads to high spatial variability of sediment transport, in particular in the Vietnamese floodplains. Depending on the flood magnitude, annual sediment loads reaching the coast vary from 48 to 60% of the sediment load at Kratie. Deposited sediment varies from 19 to 23% of the annual load at Kratie in Cambodian floodplains, and from 1 to 6% in the compartmented and diked floodplains in Vietnam. Annual deposited nutrients (N, P, K), which are associated with the sediment deposition, provide on average more than 50% of mineral fertilizers typically applied for rice crops in non-flooded ring dike floodplains in Vietnam. Through the quantification of sediment and related nutrient input, the presented study provides a quantitative basis for estimating the benefits of annual Mekong floods for agriculture and fishery, and is an important piece of information with regard to the assessment of the impacts of deltaic subsidence and climate-change-related sea level rise on delta morphology.

Description: Calibration of hydrodynamic models is – compared to other disciplines like e.g. hydrology – still underdeveloped. This has mainly two reasons: the lack of appropriate data and the large computational demand in terms of CPU-time. Both aspects are aggravated in large-scale applications. However, there are recent developments that improve the situation on both the data and computing side. Remote sensing, especially radar-based techniques proved to provide highly valuable information on flood extents, and in case high precision DEMs are present, also on spatially distributed inundation depths. On the computing side the use of parallelization techniques brought significant performance gains. In the presented study we build on these developments by calibrating a large-scale 1-D hydrodynamic model of the whole Mekong Delta downstream of Kratie in Cambodia: we combined in-situ data from a network of river gauging stations, i.e. data with high temporal but low spatial resolution, with a series of inundation maps derived from ENVISAT Advanced Synthetic Aperture Radar (ASAR) satellite images, i.e. data with low temporal but high spatial resolution, in an multi-objective automatic calibration process. It is shown that an automatic, multi-objective calibration of hydrodynamic models, even of such complexity and on a large scale and complex as a model for the Mekong Delta, is possible. Furthermore, the calibration process revealed model deficiencies in the model structure, i.e. the representation of the dike system in Vietnam, which would have been difficult to detect by a standard manual calibration procedure.

Description: Sediment dynamics play a major role for the agricultural and fishery productivity of the Mekong Delta. However, the understanding of sediment dynamics in the Mekong Delta, one of the most complex river deltas in the world, is very limited. This is a consequence of its large extent, the intricate system of rivers, channels and floodplains and the scarcity of observations. This study quantifies, for the first time, the suspended sediment transport and sediment-nutrient deposition in the whole Mekong Delta. To this end, a quasi-2-D hydrodynamic model is combined with a cohesive sediment transport model. The combined model is calibrated automatically using six objective functions to represent the different aspects of the hydraulic and sediment transport components. The model is calibrated for the extreme flood season in 2011 and shows good performance for the two validation years with very different flood characteristics. It is shown how sediment transport and sediment deposition vary from Kratie at the entrance of the Delta to the coast. The main factors influencing the spatial sediment dynamics are the setup of rivers, channels and dike-rings, the sluice gate operations, the magnitude of the floods and tidal influences. The superposition of these factors leads to high spatial variability of sediment transport, in particular in the Vietnamese floodplains. Depending on the flood magnitude, the annual sedimentation rate averaged over the Vietnamese floodplains varies from 0.3 to 2.1 kg m−2 yr−1, and the ring dike floodplains trap between 1 and 6% of the total sediment load at Kratie. This is equivalent to 29 × 103–440 × 103 t of nutrients (N, P, K, TOC) deposited in the Vietnamese floodplains. This large-scale quantification provides a basis for estimating the benefits of the annual Mekong floods for agriculture and fishery, and is important information for assessing the effects of deltaic subsidence and climate change related sea level rise.