Beyond flood probability assessment: An integrated approach for characterizing extreme water levels along transitional environments

2019 ◽  
Vol 152 ◽  
pp. 103512 ◽  
Author(s):  
Juan Del-Rosal-Salido ◽  
Pedro Folgueras ◽  
Miguel Ortega-Sánchez ◽  
Miguel Á. Losada
Keyword(s):  
Integrated Approach ◽  
Water Levels ◽  
Probability Assessment ◽  
Extreme Water Levels ◽  
Flood Probability ◽  
Transitional Environments

scholarly journals The role of the reef–dune system in coastal protection in Puerto Morelos (Mexico)

2018 ◽  
Vol 18 (4) ◽  
pp. 1247-1260 ◽  
Author(s):  
Gemma L. Franklin ◽  
Alec Torres-Freyermuth ◽  
Gabriela Medellin ◽  
María Eugenia Allende-Arandia ◽  
Christian M. Appendini
Keyword(s):  
Sand Dunes ◽  
Coastal Flooding ◽  
Water Levels ◽  
Coastal Protection ◽  
Dune System ◽  
Fore Reef ◽  
Extreme Water Levels ◽  
Reef Environments ◽  
Storm Impact

Abstract. Reefs and sand dunes are critical morphological features providing natural coastal protection. Reefs dissipate around 90 % of the incident wave energy through wave breaking, whereas sand dunes provide the final natural barrier against coastal flooding. The storm impact on coastal areas with these features depends on the relative elevation of the extreme water levels with respect to the sand dune morphology. However, despite the importance of barrier reefs and dunes in coastal protection, poor management practices have degraded these ecosystems, increasing their vulnerability to coastal flooding. The present study aims to theoretically investigate the role of the reef–dune system in coastal protection under current climatic conditions at Puerto Morelos, located in the Mexican Caribbean Sea, using a widely validated nonlinear non-hydrostatic numerical model (SWASH). Wave hindcast information, tidal level, and a measured beach profile of the reef–dune system in Puerto Morelos are employed to estimate extreme runup and the storm impact scale for current and theoretical scenarios. The numerical results show the importance of including the storm surge when predicting extreme water levels and also show that ecosystem degradation has important implications for coastal protection against storms with return periods of less than 10 years. The latter highlights the importance of conservation of the system as a mitigation measure to decrease coastal vulnerability and infrastructure losses in coastal areas in the short to medium term. Furthermore, the results are used to evaluate the applicability of runup parameterisations for beaches to reef environments. Numerical analysis of runup dynamics suggests that runup parameterisations for reef environments can be improved by including the fore reef slope. Therefore, future research to develop runup parameterisations incorporating reef geometry features (e.g. reef crest elevation, reef lagoon width, fore reef slope) is warranted.

scholarly journals What are the key drivers of regional differences in the water balance on the Tibetan Plateau?

2015 ◽  
Vol 12 (4) ◽  
pp. 4271-4314 ◽  
Author(s):  
S. Biskop ◽  
F. Maussion ◽  
P. Krause ◽  
M. Fink
Keyword(s):  
Tibetan Plateau ◽  
Water Balance ◽  
Hydrological Modeling ◽  
Integrated Approach ◽  
Water Levels ◽  
The Tibetan Plateau ◽  
Nam Co ◽  
Water Balance Components ◽  
South Central ◽  
Lake Basins

Abstract. Lake-level fluctuations in closed basins on the Tibetan Plateau (TP) indicate climate-induced changes in the regional water balance. However, little is known about the region's key hydrological parameters, hampering the interpretation of these changes. The purpose of this study is to contribute to a more quantitative understanding of these controls. Four lakes in the south-central part of the TP were selected to analyze the spatiotemporal variations of water-balance components: Nam Co and Tangra Yumco (indicating increasing water levels), and Mapam Yumco and Paiku Co (indicating stable or slightly decreasing water levels). We present the results of an integrated approach combining hydrological modeling, atmospheric-model output and remote-sensing data. The hydrological model J2000g was adapted and extended according to the specific characteristics of closed lake basins on the TP and driven with "High Asia Refined analysis (HAR)" data at 10 km resolution for the period 2001–2010. Our results reveal that because of the small portion of glacier areas (1 to 7% of the total basin area) the contribution of glacier melt water accounts for only 14–30% of total runoff during the study period. Precipitation is found to be the principal factor controlling the water-balance in the four studied basins. The positive water balance in the Nam Co and Tangra Yumco basins was primarily related to larger precipitation amounts and thus higher runoff rates in comparison with the Paiku Co and Mapam Yumco basins. This study highlights the benefits of combining atmospheric and hydrological modeling. The presented approach can be readily transferred to other ungauged lake basins on the TP, opening new directions of research. Future work should go towards increasing the atmospheric model's spatial resolution and a better assessment of the model-chain uncertainties, especially in this region where observational data is missing.

scholarly journals Cloud and cluster computing in uncertainty analysis of integrated flood models

2012 ◽  
Vol 15 (1) ◽  
pp. 55-70 ◽  
Author(s):  
V. Moya Quiroga ◽  
I. Popescu ◽  
D. P. Solomatine ◽  
L. Bociort
Keyword(s):  
Uncertainty Analysis ◽  
Cluster Computing ◽  
Uncertainty Propagation ◽  
Integrated Approach ◽  
Computer Time ◽  
Monte Carlo Sampling ◽  
Water Levels ◽  
Efficient Technology ◽  
Management Actions ◽  
Complex Models

There is an increased awareness of the importance of flood management aimed at preventing human and material losses. A wide variety of numerical modelling tools have been developed in order to make decision-making more efficient, and to better target management actions. Hydroinformatics assumes the holistic integrated approach to managing the information propagating through models, and analysis of uncertainty propagation through models is an important part of such studies. Many popular approaches to uncertainty analysis typically involve various strategies of Monte Carlo sampling of uncertain variables and/or parameters and running a model a large number of times, so that in the case of complex river systems this procedure becomes very time-consuming. In this study the popular modelling systems HEC-HMS, HEC-RAS and Sobek1D2D were applied to modelling the hydraulics of the Timis–Bega basin in Romania. We considered the problem of studying how the flood inundation is influenced by uncertainties in water levels of the reservoirs in the catchment, and uncertainties in the digital elevation model (DEM) used in the 2D hydraulic model. For this we used cloud computing (Amazon Elastic Compute Cloud platform) and cluster computing on the basis of a number of office desktop computers, and were able to show their efficiency, leading to a considerable reduction of the required computer time for uncertainty analysis of complex models. The conducted experiments allowed us to associate probabilities to various areas prone to flooding. This study allows us to draw a conclusion that cloud and cluster computing offer an effective and efficient technology that makes uncertainty-aware modelling a practical possibility even when using complex models.

scholarly journals Assessing the extreme risk of coastal inundation due to climate change: A case study of Rongcheng, China

2017 ◽  
Author(s):  
Aiqing Feng ◽  
Jiangbo Gao ◽  
Shaohong Wu ◽  
Yanzhong Li ◽  
Xiliu Yue
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
Water Levels ◽  
Assessment Model ◽  
Rcp Scenarios ◽  
Extreme Water Levels ◽  
Extreme Risk ◽  
Extreme Flood

Abstract. Extreme water levels, caused by the joint occurrence of storm surges and high tides, always lead to super floods along coastlines. Given the ongoing climate change, this study explored the risk of future sea-level rise on the extreme inundation by combining P-III model and losses assessment model. Taking Rongcheng as a case study, the integrated risk of extreme water levels was assessed for 2050 and 2100 under three Representative Concentration Pathways (RCP) scenarios of 2.6, 4.5, and 8.5. Results indicated that the increase in total direct losses would reach an average of 60 % in 2100 as a 0.82 m sea-level rise under RCP 8.5. In addition, affected population would be increased by 4.95 % to 13.87 % and GDP (Gross Domestic Product) would be increased by 3.66 % to 10.95 % in 2050 while the augment of affected population and GDP in 2100 would be as twice as in 2050. Residential land and farmland would be under greater flooding risk in terms of the higher exposure and losses than other land-use types. Moreover, this study indicated that sea-level rise shortened the recurrence period of extreme water levels significantly and extreme events would become common. Consequently, the increase in frequency and possible losses of extreme flood events suggested that sea-level rise was very likely to exacerbate the extreme risk of coastal zone in future.

scholarly journals TIME-VARYING EMULATOR FOR SHORT- AND LONG-TERM ANALYSIS OF COASTAL FLOODING (TESLA-FLOOD)

2018 ◽  
pp. 4
Author(s):  
Dylan Anderson ◽  
Peter Ruggiero ◽  
Fernando J. Mendez ◽  
Ana Rueda ◽  
Jose A. Antolinez ◽  
...  
Keyword(s):  
Sea Level ◽  
Storm Surges ◽  
Coastal Flooding ◽  
Water Levels ◽  
Sea Level Anomalies ◽  
Extreme Water Levels ◽  
Flooding Risk ◽  
The Individual ◽  
Flooding Events

The ability to predict coastal flooding events and associated impacts has emerged as a primary societal need within the context of projected sea level rise (SLR) and climate change. The duration and extent of flooding is the result of nonlinear interactions between multiple environmental forcings (oceanographic, meteorological, hydrological) acting at varying spatial (local to global) and temporal scales (hours to centuries). Individual components contributing to total water levels (TWLs) include astronomical tides, monthly sea level anomalies, storm surges, and wave setup. Common practices often use the observational record of extreme water levels to estimate return levels of future extremes. However, such projections often do not account for the individual contribution of processes resulting in compound TWL events, nor do they account for time-dependent probabilities due to seasonal, interannual, and long-term oscillations within the climate system. More robust estimates of coastal flooding risk require the computation of joint probabilities and the simulation of hypothetical TWLs to better constrain the projection of extremes (Serafin [2014]).

scholarly journals EXTREME WATER LEVEL EXCEEDANCE PROBABILITIES AROUND AUSTRALIA

2012 ◽  
Vol 1 (33) ◽  
pp. 53
Author(s):  
Leigh MacPherson ◽  
Ivan David Haigh ◽  
Matthew Mason ◽  
Sarath Wijeratne ◽  
Charitha Pattiaratchi ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Water Level ◽  
Return Period ◽  
Meteorological Data ◽  
Storm Surges ◽  
Value Theory ◽  
Water Levels ◽  
Sea Levels ◽  
Extreme Water Level ◽  
Extreme Water Levels

The potential impacts of extreme water level events on our coasts are increasing as populations grow and sea levels rise. To better prepare for the future, coastal engineers and managers need accurate estimates of average exceedance probabilities for extreme water levels. In this paper, we estimate present day probabilities of extreme water levels around the entire coastline of Australia. Tides and storm surges generated by extra-tropical storms were included by creating a 61-year (1949-2009) hindcast of water levels using a high resolution depth averaged hydrodynamic model driven with meteorological data from a global reanalysis. Tropical cyclone-induced surges were included through numerical modelling of a database of synthetic tropical cyclones equivalent to 10,000 years of cyclone activity around Australia. Predicted water level data was analysed using extreme value theory to construct return period curves for both the water level hindcast and synthetic tropical cyclone modelling. These return period curves were then combined by taking the highest water level at each return period.

Sign in / Sign up

Export Citation Format

Share Document