A Study on Coastal Flooding and Risk Assessment under Climate Change in the Mid-Western Coast of Taiwan

Hsu, Todd; Shih, Dong Sin; Li, Chi Yu; Lan, Yuan–Jyh; Lin, Yu Chen

doi:10.3390/w9060390

Cited by 34 publications

(22 citation statements)

References 46 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By the response matrix technique (Gorelick, 1983), the relationship between pumpage and drawdown can be expressed as: where β(l, k, j, t) = unit response coefficient representing the drawdown of the l-th layer at the k-th control point at the end of the t-th time period due to a unit pumpage at the j-th pumping well during the i-th time period. From Equation (Hsu, Shih, Li, Lan, & Lin, 2017), the head difference between the t-th and (t-1)-th time periods can be determined by:…”

Section: Solving Groundwater Management Modelmentioning

confidence: 99%

“…Although GWM could not stop SLR, it can nonetheless assist reducing the combined impacts of SLR and land subsidence. According to Hsu et al (2017), the rate of SLR along the southwest coast of Taiwan is estimated to be about 3 mm/yr. With 8-10 mm/yr increase in levee freeboard through GWM in the near-shore low-lying area, the levee reliability against overtopping under the threat of SLR can be sustained.…”

Section: Sea Level Risementioning

confidence: 99%

See 1 more Smart Citation

Flood hazard mitigation in land subsidence prone coastal areas by optimal groundwater pumping

Chang

Tsai

Yang³

2019

J Flood Risk Management

View full text Add to dashboard Cite

Continuing land subsidence can aggravate flood hazard and diminish the effectiveness of existing flood mitigation systems. This paper presents a study of groundwater‐ pumping management for mitigating flood hazard in a subsidence infested area in the southwest coast of Taiwan. An optimal groundwater‐pumping model is developed for preventing flood hazard from worsening and for satisfying the groundwater demand. In an area where the land is susceptible to pumping‐induced subsidence, the study shows that proper long‐term pumping strategy to manage spatial–temporal variation of future land subsidence should be an integral part of flood risk management as it can sustain the effectiveness of the flood mitigation measures.

show abstract

Section: Solving Groundwater Management Modelmentioning

confidence: 99%

Section: Sea Level Risementioning

confidence: 99%

Flood hazard mitigation in land subsidence prone coastal areas by optimal groundwater pumping

Chang

Tsai

Yang³

2019

J Flood Risk Management

View full text Add to dashboard Cite

show abstract

“…Some coastal regions around the world have been categorised and evaluated using various coastal vulnerability indices [27], which have been developed in recent decades by incorporating various physical, geomorphological, socio-economic, and geological parameters within a myriad of formulations [28][29][30][31][32][33][34][35][36][37][38][39][40]. Vulnerability assessments have now become commonplace in the fields of physical and economic geography, environmental science, and other related research areas, such as climate change, sustainability, and ecology [41].…”

Section: Introductionmentioning

confidence: 99%

Building Blocks: A Quantitative Approach for Evaluating Coastal Vulnerability

Kantamaneni

Aher

et al. 2017

Water

View full text Add to dashboard Cite

Climate change and associated factors such as global and regional sea-level rise; the upsurge in high-intensity flooding events; and coastal erosion are pulse and press disturbances that threaten to increase landslides in coastal regions. Under these circumstances; a rigorous framework is required to evaluate coastal vulnerability in order to plan for future climate change scenarios. A vast majority of coastal vulnerability assessments across the globe are evaluated at the macro level (city scale) but not at the micro level (small town scale); particularly in the United Kingdom (UK). In order to fill this vital research gap; the current study established a coastal vulnerability index termed here as the Micro Town Coastal Vulnerability Index (MTCVI) and then applied it to Barton-on-Sea; which is a small coastal town of the Hampshire region; England; UK. MTCVI was evaluated for Barton-on-Sea coastal vulnerability by integrating both novel and existing parameters. Results suggest that the entire shoreline frontage (2 km) exhibits very high coastal vulnerability and is prone to various coastal hazards such as landslides; erosion; and wave intrusion. This suggests that Barton-on-Sea coastal amenities will require a substantial improvement in shoreline protection measures. In this study; GIS (geographic information system) coastal vulnerability and landslide maps were generated; and these maps can be used by the local authorities; district councils; coastal engineers; and planners to improve and design coastal management strategies under the climate change scenarios. Meanwhile; the methodology used in this study could also be applied to any other suitable location in the world depending on the availability of the data.

show abstract

“…The previously mentioned work by Niroomandi et al[9] makes use of wave hindcast from the NCEP's Climate Forecast System and a SWAN wave model validated with buoy measurement, to characterize their temporal and spatial variabilities of extreme SWH. Applications of wave models to risk assessment have been reported, among others, in [20,21].Other useful results are provided in [22], where a 44-year long wave hindcast data base built up with a WAVEWATCH-III model were used to produce statistics on extreme SWH and compared with buoy data in the Biscay bay. In [23], data produced by SWAVE wave model driven by ECMWF ERA-Interim wind data were used to compute SWH 100 years extreme values in various locations.…”

mentioning

confidence: 99%

“…[9] makes use of wave hindcast from the NCEP's Climate Forecast System and a SWAN wave model validated with buoy measurement, to characterize their temporal and spatial variabilities of extreme SWH. Applications of wave models to risk assessment have been reported, among others, in [20,21].…”

mentioning

confidence: 99%

An Experimental Assessment of Extreme Wave Evaluation by Integrating Model and Wave Buoy Data

Reale¹,

Dentale²,

Furcolo³

et al. 2020

Water

View full text Add to dashboard Cite

Calculating the significant wave height (SWH) in a given location as a function of the return time is an essential tool of coastal and ocean engineering; such a calculation can be carried out by making use of the now widely available weather and wave model chains, which often lead to underestimating the results, or by means of in situ experimental data (mostly, wave buoys), which are only available in a limited number of sites. A procedure is hereby tested whereby the curves of extreme SWH as a function of the return time deriving from model data are integrated with the similar curves computed from buoy data. A considerable improvement in accuracy is gained by making use of this integrated procedure in all locations where buoy data series are not available or are not long enough for a correct estimation. A useful and general design tool has therefore been provided to derive the extreme value SWH for any point in a given area.data raises however various issues: apart from the obvious problem of reliability of the model chains of both the atmospheric and the sea wave parts, an important aspect is the way through which ground truth wave data are assimilated into the analysis. Most of the assimilation procedures are carried out with satellite altimeter data, which are scattered in time (at many hours' intervals) and wide apart in space (tens or hundreds of kilometers), so extreme SWH values may often be missed. It is also worth noting that the sampling time of the models, i.e., the time interval at which data are stored and released, is often higher than the standard sampling time of buoys, thus causing a negative bias on the estimated extreme values [1][2][3].In order to overcome these problems, an integrated procedure [4] was been proposed by some of the authors of the present paper whereby the curves of extreme SWH as a function of the return time T R (in the following: SWH(T R )) deriving from synthetic data are compared and calibrated with the similar curves computed from buoy data in different locations. This provides a way of deriving SWH(T R ) curves for sites where no experimental data are available.The present paper presents an extension of the same technique and provides an experimental authentication of the methodology based on a new large set of reliable data along the coasts of the USA.The determination of the probability of extreme SWH is one of the main problems of coastal, offshore, and marine engineering, so that the relevant literature is not only extensive, but also increasing with time as the technology improves and the requirements become more stringent. Therefore, in the following, only contributions which are connected to the aims of this paper will be considered.All the procedures are substantially based on fitting Extreme Value Probability Distributions (in the following: EVPD) to buoy recorded time series of SWH; references on the general problem date back to many years ago [5], however Goda's textbook [6] is still the most common reference for maritime engineering, even though many authors...

show abstract

A Study on Coastal Flooding and Risk Assessment under Climate Change in the Mid-Western Coast of Taiwan

Cited by 34 publications

References 46 publications

Flood hazard mitigation in land subsidence prone coastal areas by optimal groundwater pumping

Flood hazard mitigation in land subsidence prone coastal areas by optimal groundwater pumping

Building Blocks: A Quantitative Approach for Evaluating Coastal Vulnerability

An Experimental Assessment of Extreme Wave Evaluation by Integrating Model and Wave Buoy Data

Contact Info

Product

Resources

About