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RISK-LEVEL ASSESSMENT SYSTEM ON
BENGAWAN SOLO’S FLOOD PRONE AREAS
USING AHP AND WEB GIS
ICT-ASIA 2015
25-26 May 2015
SEARCA, Los Banos, Laguna, Philippines
H A R I S R A H A D I A N TO
A R N A FA R I Z A
J A UA R I A K H M A D N U R H A S I M
D E PA R T M E N T O F I N F O R M AT I C S A N D C O M P U T E R E N G I N E E R I N G
E L E C T R O N I C S E N G I N E E R I N G P O LY T E C H N I C I N S T I T U T E O F S U R A B AYA
rhadint@it.student.pens.ac.id
CONTENTS
Introduction
Background
Problem
Idea
Theory
Result
Future Works
Indonesia as Disaster Supermarket Country
Indonesia Data and Information, National Disaster Management Authority (BNPB)
Frequent Disaster in Indonesia
Indonesia Data and Information, National Disaster Management Authority (BNPB)
Bengawan Solo River Basin
The longest river in Java, it is
approximately 600 km in
length
Located on East Java and
Central
Java
Province,
Indonesia. It is comprised of
17 Regencies and 3 Cities
In 2007, the Bengawan Solo
river basin flooded Central and
East Java, causing around $170
million economic damage.
Flood Prone Areas in East Java
The Impact of Flood
Floods are considered to be the most common natural disaster
worldwide during the last decades. Their consequences are not
only environmental but economic as well, since they may cause
damages to urban areas and agricultural lands and may even
result in loss of lives (Merz et al. 2010).
Indonesia Data and Information, National Disaster Management Authority (BNPB)
Problems
The national government has created a de-centralized structure to
prepare and respond to disasters and climate change. However, these
structures are often lacking and funding is frequently diverted from
preparation and mitigation to emergency response, and many lack the
organizational capability necessary to mitigate disasters.
The increase in floods and their destructive results worldwide require
an ongoing improvement on identification and mapping of flood
hazard. (Kundzewicz and Kaczmare 2000; Ebert et al. 2009).
Idea
Build web-based risk-level assessment system that comprehend
hazards, vulnerabilities, and capacities summarized in risk analysis and
integrated with Geographical Information System so it can map the
region based on its risk level
Disaster Risk Assessment
R : Disaster Risk
H : Hazard Threat
V : Vulnerability
C : Adaptive Capacity
General Guidelines for Disaster Risk Assessment, National Disaster Management Authority (BNPB)
Flood Risk Assessment
Indicators used for semi-quantitative risk analysis will be selected based
on the suitability and availability. The formula described above still
apply, but will contain an index value not real value. In analogy Human
Development Index (HDI) of the UNDP, to make the index comparable
at least in the dimensions, the index used in the analysis were
converted into a value between 0 and 1, where 0 is the minimum value
of the original indicator, and 1 is the maximum value.
In the case of the low numbers are many and varied in amount
sometimes high, will be converted logarithmic (Log10) than linear
conversion.
The core of the risk mapping methodology for a tree structure indicator,
where risk index forming the root end of the analysis.
General Guidelines for Disaster Risk Assessment, National Disaster Management Authority (BNPB)
Analytic Hierarchy Process
In the semi-quantitative analysis, particularly about the lack of
information about factors sensitivity is compensated by a
weighting factor. Best weighting factors obtained through
consensus of expert opinion. A methodology appears to a
consensus such is the Analytic Hierarchy Process (AHP). This
methodology has been developed by Thomas L. Saaty began in
1970, and was originally intended as a tool for decision-making.
AHP is a measurement methodology through comparison pairwise and depend on the judgment of experts to gain scale
priority. This is the scale that measures the relative form.
Comparisons are made with using the absolute rating scale,
which represents how much the indicator dominating the other
with respect to a particular disaster.
General Guidelines for Disaster Risk Assessment, National Disaster Management Authority (BNPB)
The Hierarchy
Number of Population
Exposure
Percentage of Impact Area
Number of Population
Exposure per District
East Java Contingency Plan on Bengawan Solo Flood, National Disaster Management Authority (BNPB)
Risk Value
As explained earlier, the Risk map has been prepared based on an
index of hazard, vulnerability and capacity. Modifications should
be made to the above formula so it can be used in semiquantitative. Multiplication with a capacity inverted (1-C)
performed, rather than division with C, to avoid high value in the
case of extreme values of the low value of C, or error in terms of
the empty values of C. The result of multiplying the index must be
corrected by showing the root of 1 / n, for regains its original
dimensions
General Guidelines for Disaster Risk Assessment, National Disaster Management Authority (BNPB)
Risk-Level Division
Furthermore, the values that were derived from were grouped
into three risk levels. This classification was done by using the
optimization method of classes distribution natural breaks (Jenks
1967).
The Jenks optimization method, also called the Jenks natural
breaks classification method, is a data classification method
designed to determine the best arrangement of values into
different classes. This is done by seeking to minimize each class’
average deviation from the class mean, while maximizing each
class’ deviation from the means of the other groups. In other
words, the method seeks to reduce the variance within classes
and maximize the variance between classes.
Result
Conclusion
There are three level risk-level on Bengawan Solo’s flood-prone areas
based on the analysis of hazards, vulnerabilities, and capacities
There are 5 low-risk districts, 17 medium-risk districts, and 14 high-risk
districts on the flood-prone areas
Future Works
Flood prediction and forecating system
Evaluation and upgrading the system
Assessment on the following disaster when the flood occured
References
Indonesia Data and Information, National Disaster Management Authority
(BNPB)
Merz B, Kreibich H, Schwarze R, Thieken A (2010) Assessment of economic
flood damage. Nat Hazards Earth Syst Sci 10:1679–1724
Kundzewicz W, Kaczmare Z (2000) Coping with hydrological extremes. Water
Int 25:66–75
Ebert A, Kerle N, Stein A (2009) Urban social vulnerability assessment with
physical proxies and spatial metrics derived from air- and spaceborne
imagery and GIS data. Nat Hazards 48:275–294
Jenks G (1967) The Data Model Concept in Statistical Mapping. Int Year b
Cartogr 7:186–190
General Guidelines for Disaster Risk Assessment, National Disaster
Management Authority (BNPB)
THANK YOU
rhadint@it.student.pens.ac.id