scholarly journals Economic Impact Evaluation and Household Adaptation to Extreme Weather Events in the Municipality of Bay, Laguna, Philippines

Author(s):  
Joela Mizchelle A. Dela Vega ◽  
Joshua G. Jomao-as ◽  
Francis Jhun T. Macalam ◽  
Kevin John R. Lino ◽  
Merry Joy R. Ilagan

Bay is one of the municipalities in the province of Laguna that is situated along the coast of Laguna de Bay, and is particularly vulnerable to natural disasters including typhoons and flash floods. Among these, Barangay Dila, San Isidro, and Tagumpay located in low-lying elevation of the Municipality of Bay were not spared by the impacts caused by the disaster. Hence, the study site was conducted in these flood-prone areas of the Municipality. In this study, it highlights the impacts and adaptation of the household to extreme weather events. Specifically, the study aims to identify, quantify, and monetized (whenever possible) the household's impacts of extreme floods and typhoons; described the adaptation actions undertaken by the households; and to evaluate the factors that significantly affect the choice of adaptation activities. The data used in this study was collected through a survey of 90 households. In selecting the household, random sampling was employed using the data that was acquired from the municipality. The selected household heads were interviewed using the structured sample questionnaire. Probit regression was employed to test the significant factors of the choices of adaptation activities of the household. The study revealed that the impacts of extreme weather events on the households of Bay, Laguna could be considered to be ranging from moderate to severe cases depending on the geographical location of the households. Also, households of Bay, Laguna considers the height of flood and distance from bodies of water as significant factors for undertaking adaptation actions.

2014 ◽  
Vol 9 (sp) ◽  
pp. 699-708 ◽  
Author(s):  
Lihui Wu ◽  
◽  
Haruo Hayashi ◽  

The purpose of this study is to explore the impact of disasters on international tourism demand for Japan by applying Autoregressive Integrated Moving Average (ARIMA) intervention models that focus on evaluating change patterns and the duration of effects by observing variations in parameters. Japan suffered a variety of disasters, especially natural disasters due to its geographical location, so we have divided these disasters into three types: geological disasters, extreme weather events and “others” such as terrorist attacks, infectious diseases, and economic crises. Based on the principle of preparing for the worst, we selected 4 cases for each disaster type, for 12 in all. Results suggest that (1) large-scale disasters such as great earthquakes impacted negatively on inbound tourism demand for Japan; (2) not all disasters resulted in an abrupt drop in inbound tourist arrivals, extreme weather events, for example, did not decrease inbound tourism demand significantly; (3) impact caused by disasters was temporary.


Author(s):  
K. G. Jubilo ◽  
M. R. Algodon ◽  
E. M. Torres ◽  
Z. D. Abraham ◽  
A. Ide-Ektessabi ◽  
...  

Abstract. We search for lost bodies of water in the cities of Manila, Tacloban, Iloilo, Cebu, Davao, and Naga by aligning their digitized Spanish-era and American-era maps to Google maps. These vanished ancient waterways can either become flooding hazards in case of extreme weather events, or liquefaction hazards, in case of earthquakes. Digitized historical maps of the cities were georectified, overlaid on current Google maps, and checked for potential missing bodies of water. Inspection through field visits and interviews with locals were conducted to verify the actual status of suspected sites. The validation identified lost, found, and even new bodies of water. There was also evidence of affected buildings, rainless flooding, and a “new normal” for the meaning of flooding among frequently inundated residents.


2018 ◽  
Author(s):  
Peter C. Balash, PhD ◽  
Kenneth C. Kern ◽  
John Brewer ◽  
Justin Adder ◽  
Christopher Nichols ◽  
...  

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