Spatial Analysis

The advent of technology significantly contributed to disaster risk assessment by providing satellite images of land cover and data on the topography of landforms. The spatial analysis approach incorporated these data, along with actual measurements from the field and from monitoring stations, to determine which areas are highly susceptible to flooding. This approach allows large-scale flood risk assessment using data available thus developing an appropriate strategy to minimize the effects of flooding [2].

Climate Adaptation Effectiveness

Applying flood depth-damage function while considering river velocity and river flow duration would allow for a more accurate projection of flood damage in an area. It is shown that flooding can occur due to increase in rainfall but will worsen if urbanization in an area continues. Aside from rainfall and urbanization, presence of inundated areas and flood depth should also be taken into consideration when accounting for flood damage [2].

Climate Hazards

  • Rain-Induced Flooding

Locations

  • Pasig-Marikina San Juan River, Manila, NCR (National Capital Region)

Adaptation Sectors

  • Disaster Risk Reduction
  • Urban

CCET Instuments

  • Research and Development

Target Group based on Vulnerability

Basic Sectors:
  • Businesses
  • Children
  • Formal Labor and Migrant Workers
  • Indigenous Peoples
  • Persons with Disabilities
  • Senior Citizens
  • Urban Poor
  • Women
  • Workers in the Informal Sector
  • Youth and Students

Evaluations

Economic / Financial Effectiveness
Mid

The flood damage for the year 2030 in the areas below were calculated including the percentage increase in the inundated areas and flood depth. Increasing flood depth contributed to the majority of the flood damage in different cities except for San Mateo, Rizal. The major contributor to flood damage varies in one area to another [1][2][3]. Pasig: 525% total damage; 116% flood depth; 38% inundated areas Taytay: 1468% total damage; 223% flood depth; 37% inundated areas San Mateo: 252% total damage; 41% flood depth; 105% inundated areas With the data and projections available, to minimize and avoid flood risk and related economic loss, appropriate strategies should be planned and implemented such as the creation of structural and non-structural measures.

Technical Feasibility
Low

Knowledge and experience in spatial analysis is required to use this approach. In spatial analysis, three components worked together to create a flood risk assessment. (1) Inputting a high flow discharge to observe how the water is distributed in the area and simulating flooding considering water depth and inundation area. (2) Determining which areas are affected by the flood simulation. (3) Application of flood depth-damage function to determine direct flood damage as well as interviews with the locals on how the area is affected due to previous flooding events [2].

Social Acceptability
No Evidence

There is no indication yet showing social acceptability for this solution.

Environmental Impact
N/A

There is no direct environmental impact for this solution.

Mitigation co-benefit

There is no direct mitigation co-benefit for this solution.

Keywords

flood, spatial analysis, flood prone areas, flood risk reduction, flood loss and damages, spatial mapping; geo-spatial mapping; spatial modelling and analysis

References

[1] Fohrer N, Haverkamp S, Eckhardt K, Frede HG (2001) Hydrologic response to land use changes on the catchment scale. Phys Chem Earth Part B Hydrol Oceans Atmos 26 (7–8):577–582. https://doi.org/10.1016/S1464-1909(01)00052-1
[2] Kefi, M., Mishra, B., Masago, Y., and Fukushi, K. (2020). Analysis of flood damage and influencing factros in urban catchments: case studies in Manila, Philippines, and Jakarta, Indonesia. Natural Hazards, 104. pp. 2461-2487. https://doi.org/0.1007/s11069-020-04281-5
[3] Rafiei Emam A, Mishra BK, Kumar P, Masago Y, Fukushi K (2016) Impact assessment of climate and land-use changes on flooding behavior in the Upper Ciliwung River, Jakarta, Indonesia. Water 8(12):559. https://doi.org/10.3390/w8120559