Risk Assessment in Bengawan Solo

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RISK-LEVEL ASSESSMENT SYSTEM ONBENGAWAN SOLO’S FLOOD PRONE AREAS

USING AHP AND WEB GIS

ICT-ASIA 2015

25-26 May 2015

SEARCA Los Banos Laguna Philippines

HAR IS R AHAD IANT O

AR NA FAR IZA

JAU AR I AK HMAD NU R HASIM

D EPAR T MENT O F IN FO R MAT ICS AND CO M PU T ER ENG INEER ING

EL ECT R O NICS ENG I NEER ING PO L YT ECHNIC INST IT U T E O F SU R ABAYA

[email protected]



CONTENTSIntroduction

Background

Problem

Idea

Theory

Result

Future Works



Indonesia as Disaster Supermarket Country

IndonesiaDataandInformation,NationalDisasterManagementAuthority(BNPB)



Frequent Disaster in Indonesia




Bengawan Solo River Basin

The longest river in Java, it isapproximately 600 km inlength

Located on East Java andCentral Java Province,Indonesia. It is comprised of 17 Regencies and 3 Cities

In 2007, the Bengawan Solo

river basin flooded Central andEast Java, causing around $170million economic damage.



Flood Prone Areas in East Java



The Impact of FloodFloods are considered to be the most common natural disasterworldwide during the last decades. Their consequences are notonly environmental but economic as well, since they may causedamages to urban areas and agricultural lands and may even

result in loss of lives (Merz et al. 2010).




ProblemsThe national government has created a de-centralized structure toprepare and respond to disasters and climate change. However, thesestructures are often lacking and funding is frequently diverted frompreparation and mitigation to emergency response, and many lack the

organizational capability necessary to mitigate disasters.The increase in floods and their destructive results worldwide requirean ongoing improvement on identification and mapping of floodhazard. (Kundzewicz and Kaczmare 2000; Ebert et al. 2009).



IdeaBuild web-based risk-level assessment system that comprehendhazards, vulnerabilities, and capacities summarized in risk analysis andintegrated with Geographical Information System so it can map theregion based on its risk level



Disaster Risk Assessment

R : Disaster Risk

H : Hazard Threat

V : Vulnerability

C : Adaptive Capacity

GeneralGuidelinesforDisasterRiskAssessment,NationalDisasterManagementAuthority(BNPB)



Flood Risk AssessmentIndicators used for semi-quantitative risk analysis will be selected basedon the suitability and availability. The formula described above stillapply, but will contain an index value not real value. In analogy HumanDevelopment Index (HDI) of the UNDP, to make the index comparable

at least in the dimensions, the index used in the analysis wereconverted into a value between 0 and 1, where 0 is the minimum valueof the original indicator, and 1 is the maximum value.

In the case of the low numbers are many and varied in amountsometimes 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.




Analytic Hierarchy ProcessIn the semi-quantitative analysis, particularly about the lack of information about factors sensitivity is compensated by aweighting factor. Best weighting factors obtained throughconsensus of expert opinion. A methodology appears to a

consensus such is the Analytic Hierarchy Process (AHP). Thismethodology has been developed by Thomas L. Saaty began in1970, and was originally intended as a tool for decision-making.AHP is a measurement methodology through comparison pair-wise 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 otherwith respect to a particular disaster.




The Hierarchy



Percentage of Impact Area

Number of Population

Exposure

Number of Population

Exposure per District

EastJavaContingencyPlanonBengawanSoloFlood,NationalDisasterManagementAuthority(BNPB)



Risk Value

As explained earlier, the Risk map has been prepared based on an

index of hazard, vulnerability and capacity. Modifications shouldbe made to the above formula so it can be used in semi-quantitative. Multiplication with a capacity inverted (1-C)performed, rather than division with C, to avoid high value in thecase 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 becorrected by showing the root of 1 / n, for regains its originaldimensions




Risk-Level DivisionFurthermore, the values that were derived from were groupedinto three risk levels. This classification was done by using theoptimization method of classes distribution natural breaks (Jenks1967).

The Jenks optimization method, also called the Jenks naturalbreaks classification method, is a data classification methoddesigned to determine the best arrangement of values intodifferent 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 otherwords, the method seeks to reduce the variance within classesand maximize the variance between classes.



Result













ConclusionThere are three level risk-level on Bengawan Solo’s flood-prone areasbased on the analysis of hazards, vulnerabilities, and capacities

There are 5 low-risk districts, 17 medium-risk districts, and 14 high-riskdistricts on the flood-prone areas



Future WorksFlood prediction and forecating system

Evaluation and upgrading the system

Assessment on the following disaster when the flood occured



ReferencesIndonesia Data and Information, National Disaster Management Authority(BNPB)

Merz B, Kreibich H, Schwarze R, Thieken A (2010) Assessment of economicflood damage. Nat Hazards Earth Syst Sci 10:1679 –1724

Kundzewicz W, Kaczmare Z (2000) Coping with hydrological extremes. WaterInt 25:66 –75

Ebert A, Kerle N, Stein A (2009) Urban social vulnerability assessment withphysical proxies and spatial metrics derived from air- and spaceborneimagery and GIS data. Nat Hazards 48:275 –294

Jenks G (1967) The Data Model Concept in Statistical Mapping. Int Year bCartogr 7:186 –190

General Guidelines for Disaster Risk Assessment, National DisasterManagement Authority (BNPB)



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Risk Assessment in Bengawan Solo