scholarly journals Application of geographic weighted regression to establish flood-damage functions reflecting spatial variation

Water SA ◽  
2019 ◽  
Vol 34 (2) ◽  
pp. 209 ◽  
Author(s):  
Ling-Fang Chang ◽  
Chun-Hung Lin ◽  
Ming-Daw Su
Keyword(s):  
Spatial Variation ◽  
Flood Damage ◽  
Weighted Regression ◽  
Damage Functions ◽  
Geographic Weighted Regression

Assessing Risk Factors for Short Birth Interval Hot Spots using Geographically Weighted Regression: Findings from a Nationally Representative Survey Data

2021 ◽  
Author(s):  
Mohammad Zahidul Islam ◽  
Md. Mostafizur Rahman ◽  
Md. Nuruzzaman Khan ◽  
M Mofizul Islam
Keyword(s):  
Spatial Variation ◽  
Birth Interval ◽  
Hot Spots ◽  
Protective Factor ◽  
Public Health Problem ◽  
Least Square ◽  
Weighted Regression ◽  
Geographic Variations ◽  
Explanatory Variables ◽  
Short Birth Interval

Abstract Background Short Birth Interval (SBI) is a public health problem in most low- and lower-middle-income countries. Understanding geographic variations in SBI, particularly SBI hot spots and associated factors, may help intervene with tailored programs. This study identified the geographical hot spots of SBI in Bangladesh and the factors associated with them. `Methods We analyzed women’s data extracted from the 2017/18 Bangladesh Demographic and Health Survey and the healthcare facility data extracted from the 2017 Service Provision Assessment. Moran’s I was used to examine the spatial variation of SBI in Bangladesh whereas the Getis-Ord G*i (d) was used to determine the hot spots of SBI. The Geographical Weighted Regression (GWR) was used to explore the spatial variation of SBI on explanatory variables. The explanatory variables included in the GWR were selected using the exploratory regression and ordinary least square regression model. Results Data of 5941 women were included in the analyses. Around 26% of the total births in Bangladesh had occurred in short intervals. A majority of the SBI hot spots were found in the Sylhet division, and almost all SBI cold spots were in the Rajshahi and Khulna divisions. No engagement with formal income-generating activities, high maternal parity, and history of experiencing the death of a child were significantly associated with SBI in the Sylhet region. Women’s age of 34 years or less at the first birth was a protective factor of SBI in the Rajshahi and Khulna divisions. Conclusion The prevalence of SBI in Bangladesh is highly clustered in the Sylhet division. We recommend introducing tailored reproductive health care services in the hot spots instead of the existing uniform approach across the country.

scholarly journals Uncertainties in Coastal Flood Risk Assessments in Small Island Developing States

2019 ◽  
Author(s):  
Matteo U. Parodi ◽  
Alessio Giardino ◽  
Ap van Dongeren ◽  
Stuart G. Pearson ◽  
Jeremy D. Bricker ◽  
...  
Keyword(s):  
Flood Risk ◽  
Input Data ◽  
Flood Damage ◽  
Small Island ◽  
Small Island Developing States ◽  
Damage Functions ◽  
Current Time ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
The Impact

Abstract. Considering the likely increase of coastal flooding in Small Island Developing States (SIDS), coastal managers at the local and global level have been developing initiatives aimed at implementing Disaster Risk Reduction (DRR) measures and adapting to climate change. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which are often subject to the scarcity of sufficiently accurate input data for insular states. We analysed the impact of uncertain inputs on coastal flood damage estimates, considering: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with an impact model (Delft-FIAT) for a case study at the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDF) and digital elevation model (DEM) dominate the overall damage estimation uncertainty. We find that, when introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive error in CFR assessments in SIDS. The findings of this research can help to prioritise the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.

scholarly journals Estimation of an absolute flood damage curve based on an Austrian case study under a dam breach scenario

2010 ◽  
Vol 10 (4) ◽  
pp. 881-894 ◽  
Author(s):  
F. Prettenthaler ◽  
P. Amrusch ◽  
C. Habsburg-Lothringen
Keyword(s):  
Future Development ◽  
Damage Assessment ◽  
Field Data ◽  
Flood Damage ◽  
Damage Function ◽  
Damage Potential ◽  
Dam Breach ◽  
Damage Functions ◽  
Austrian Case

Abstract. To date, in Austria no empirical assessment of absolute damage curves has been realized on the basis of detailed information on flooded buildings due to a dam breach, presumably because of the lack of data. This paper tries to fill this gap by estimating an absolute flood-damage curve, based on data of a recent flood event in Austria in 2006. First, a concise analysis of the case study area is conducted, i.e., the maximum damage potential is identified by using raster-based GIS. Thereafter, previous literature findings on existing flood-damage functions are considered in order to determine a volume-water damage function that can be used for further flood damage assessment. Finally, the flood damage function is cross validated and applied in prediction of damage potential in the study area. For future development of the estimated flood damage curve, and to aid more general use, we propose verification against field data on damage caused by natural waves in rivers.

scholarly journals DEVELOPMENT OF FLOOD DAMAGE FUNCTIONS BASED ON INSURANCE LOSS DUE TO 2015 KANTO-TOHOKU HEAVY RAINFALL

2017 ◽  
Vol 73 (4) ◽  
pp. I_1279-I_1284
Author(s):  
Rikito HISAMATSU ◽  
Ken KAWABE ◽  
Yusuke MIZUNO ◽  
Yoshinobu SHINOZUKA ◽  
Kei HORIE
Keyword(s):  
Heavy Rainfall ◽  
Flood Damage ◽  
Damage Functions

Modeling the Spatial Variation in U.S. Airfares Utilizing Geographically Weighted Regression

2014 ◽  
Vol 5 (4) ◽  
pp. 54-71
Author(s):  
Hilton A. Cordoba ◽  
Russell L. Ivy
Keyword(s):  
Spatial Variation ◽  
Influencing Factors ◽  
Geographically Weighted Regression ◽  
Regression Models ◽  
Yield Management ◽  
Weighted Regression ◽  
Local Models ◽  
Multivariate Approach ◽  
Global Models ◽  
Economic Changes

Modeling airline fares is quite challenging due to the constantly changing fare structure of the airlines in response to competitors, yield management principles, and a variety of political and economic changes, and has become more complex since deregulation. This paper attempts to add to the literature by providing a more in-depth look at fare structure using a multivariate approach. A total 6,200 routes between 80 primary U.S. airports are analyzed using linear and geographically weighted regression models. The results from the global models reinforce some of the expectations mentioned in the literature, while the local models provide an opportunity to analyze the spatial variation of influencing factors and predictability.

Tradeoffs in water extremes: combining hydraulic and economic modeling to assess the economic and financial viability of de Lastras de Cuéllar Dam, Spain

2020 ◽  
Author(s):  
Héctor González López ◽  
C. Dionisio Pérez-Blanco ◽  
Laura Gil-García
Keyword(s):  
Value Added ◽  
Flood Damage ◽  
Hydrologic Model ◽  
Economic Modeling ◽  
Adaptation Strategies ◽  
Regulated River ◽  
Damage Functions ◽  
Flood Depth ◽  
Operation Rules ◽  
Floods And Droughts

<p><strong>Abstract</strong></p><p>Growing population and water demand (e.g for irrigation, water supply) and the vagaries of climate, now aggravated due to climate change, intensify societal exposure to water extremes and the economic and environmental impact of floods and droughts in Mediterranean basins. The Douro River Basin Authority (DRBA) in central Spain is assessing whether to build a dam in the Cega Catchment (Spain) with the twofold objective of substituting irrigation withdrawals from overallocated aquifers with relatively more abundant surface water, and of mitigating flood damage in the middle and lower stretches of the Cega River -the only non-regulated river in the DRB. This paper assesses and compares the costs of two alternative adaptation strategies to growing scarcity and more frequent and intense water extremes, namely dam construction v. the statu quo strategy where no dam is built. To this end, a Positive Multi-Attribute Utility Programing (PMAUP) that mimics farmer´s behavior and responses is used to assess the impacts on agricultural employment and gross value added of selected strategies in the irrigation sector; while the hydrologic model River Analysis System (HEC-RAS) is used to simulate the economic impact of flood events considering standard return periods, based on the global flood depth-damage functions developed by Huizinga et al. (2017). Both models are used to run 900 simulations reproducing alternative socioeconomic and climatic/hydrologic scenarios. The result is a database representing multiple plausible futures, which is used to identify vulnerabilities of proposed adaptation strategies and potential tradeoffs between responses -notably those referring to the design and operation rules of the dam, and the potential impact of floods and droughts. This methodology and the resultant database are combined with experts’ knowledge through robust decision-making tools to identify the preferred (i.e. robust) adaptation policy.</p>

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