FY 2018 Operational Feasibility Study Project towards ...

FY 2018 Operational Feasibility Study Project towards

Overseas Deployment of High-Quality Infrastructure

(Republic of Indonesia: Feasibility Study Project for Flood

Disaster Preparedness Planning Assuming the Use of Flood

Simulator and Weather Radar in the Province of Gorontalo)

Study Report

February 2019

Kanematsu Corporation

Japan Weather Association

Table of Contents

1. Profile of the partner country/sector .............................................................................................................. 1

1-1. Economic and financial situations of the partner country .................................................................... 1

1-2. Profile of the target sector of the project............................................................................................ 1

1-3. Current state of the target region ...................................................................................................... 1

2. Study methodology .......................................................................................................................................... 3

2-1. Study content .................................................................................................................................. 3

2-2. Study method, organizational framework, and schedule ..................................................................... 3

(1) Study method ............................................................................................................................... 3

(2) Organizational framework for study implementation ....................................................................... 3

(3) Study schedule .............................................................................................................................. 4

2-3. Study results ................................................................................................................................... 5

(1) Current status of the use of weather radar and flood hazard maps in Japan......................................... 5

(2) Flood simulator-related ............................................................................................................... 10

(3) Weather radar-related .................................................................................................................. 14

(4) Past flood situation ...................................................................................................................... 18

(5) River improvement status (flow rate data collection covering lake water and irrigation) ................... 18

(6) Hosting local workshop and seminar at Gorontalo province ........................................................... 19

(7) Results of discussions held in Jakarta with the Japanese Embassy, the BMKG, and the BNPB .......... 21

(8) Results of activities at COP24 ...................................................................................................... 21

3. Consideration of the content and technical aspects of the project ............................................................ 23

3-1. Background, necessity, etc., of the project ....................................................................................... 23

(1) Background of the project ............................................................................................................ 23

(2) Necessity of the project ............................................................................................................... 23

3-2. Basic guidelines, decisions, etc., on the content of the project ........................................................... 24

3-3. Outline of the project ..................................................................................................................... 25

3-4. Items required to be considered ...................................................................................................... 26

(1) Inclusion in local government budget ........................................................................................... 26

(2) Development of collaboration between related agencies ................................................................. 26

(3) Personnel development and training, etc. ...................................................................................... 26

3-5. Environmental and social impacts associated with project implementation ........................................ 26

(1) Introduction of the radar(s) .......................................................................................................... 26

(2) Introduction of the flood simulator ............................................................................................... 27

4. Financial and economic feasibility ............................................................................................................... 28

4-1. Project cost estimation ................................................................................................................... 28

4-2. Summary of the results of (preliminary) financial/economic analysis ................................................ 29

(1) Prediction of the effect of the installation of the flood simulator ..................................................... 30

(2) Funding feasibility consideration.................................................................................................. 30

5. Project implementation schedule ................................................................................................................. 31

6. Implementation competence of the implementation agencies of the counterpart country ..................... 32

6-1. Profile of the implementation agencies of the counterpart country .............................................. 32

6-2. Organizational framework for project implementation in the counterpart country ..................... 32

6-3. Competence evaluation of the implementation agencies of the counterpart country and

countermeasures ................................................................................................................................ 33

7. Competitive advantages of Japanese enterprises in terms of technology and other aspects ................... 35

7-1. International competitiveness of Japanese enterprises in project bidding (by

equipment/product/service) and probability of winning orders .......................................................... 35

(1) International competitiveness of “Japan-made Flood-Simulator” ............................................. 35

(2) Probability of winning orders for “Japan-made Flood-Simulator” ............................................ 38

7-2. Descriptions and prices of the main materials and equipment expected to be procured from Japan

........................................................................................................................................................... 38

7-3. Measures necessary to help Japanese enterprises to win orders ................................................... 40

8. Prospects of fund procurement for the project ........................................................................................... 41

8-1. Views of the counterpart country’s government and agencies on fund procurement .................... 41

8-2. Movements of related agencies with regards to fund procurement .............................................. 41

8-3. Prospects of project-related fund procurement, the current status of requests for yen loan, and the

likelihood of its approval .................................................................................................................... 43

9. Challenges and action plan towards the realization of the project............................................................ 44

9-1. Progress in fund procurement efforts including requests for UN-GCF and yen loan .................... 44

9-2. Measures expected to be necessary for future funding requests for and provision of UN-GCF, yen

loan, etc. ............................................................................................................................................. 44

9-3. Specific challenges and action plan towards submission of funding requests for UN-GCF funds, yen

loans, etc.; and other issues including horizontal deployment to other countries ................................ 45

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1. Profile of the partner country/sector

1-1. Economic and financial situations of the partner country

Indonesia maintained a high economic growth rate with a real GDP growth rate of 5.0% for 2016 and 5.1% for

2017. The per-capita nominal GDP for 2017 reached $3,876. Boasting a population of 240 million people,

Indonesia has increased its presence as a leading economic power country in the ASEAN region.1

Meanwhile, infrastructure development in Indonesia is lagging behind economic growth. This is the case not

only in terms of worsening traffic jams or a tight power supply and demand balance but also in terms of earthquake,

tsunami, and other natural disaster preparedness and commitment to global warming issues. While Indonesia’s

ratio of outstanding government debt to GDP is in the 20-percent range and is lower than those of its ASEAN

neighbors, the country has been posting fiscal deficits since 2012. The Indonesian government is promoting a

reform for fiscal health restoration.

1-2. Profile of the target sector of the project

Indonesia is populated by approximately 227 million people and extends over a land area of approximately 1.9

million km2. Located in the southern part of South East Asia, the country consists of more than 18,000 islands.

While most of its national territory belongs to tropical rainforest climate, Indonesia has a dry and rainy season.

Disastrous droughts and forest fires frequently occur in the dry season while squalls and heavy rains frequently

cause devastating inundations and floods in the rainy season. In addition, located over the boundaries between the

Pacific Plate, the Eurasian Plate, the Australian Plate, and the Philippine Sea Plate, Indonesia is constantly prone

to natural disasters including earthquakes, volcanic eruptions, and seismically-induced tsunami attacks.

The Bureau of Meteorology, Climate and Geophysics (BMKG) has been in charge of providing weather

observation services. The BMKG has been working on enhancing its information dissemination capability as one

of disaster control measures, through international cooperation and assistance received to improve its observation

equipment and operational capabilities. In 2008, following the recent chains of natural disasters, the central

government established the National Disaster Management Authority (BNPB) for further improvement of disaster

response capabilities. The BNPB collaborates with the BMKG in efforts to develop disaster preparedness plans,

develop regional hazard and risk maps, and enhance disaster response capabilities and disaster preparedness of

disaster-related agencies and communities.

Nevertheless, Regional Disaster Management Agencies (BPBD), BNPB’s regional branches, still fall short of

providing sufficient guidance and support to local governments. Meanwhile, Japan has been providing yen-loan

support, both material and non-material, such as flood control measures or capability building programs.

1-3. Current state of the target region

Typical impacts of climate change in Indonesia include increased sea water levels, increased sea surface water

temperatures, and changes in rainfall patterns. Adaptive challenges resulting from these include, among other

things: increases in floods/extreme weather phenomena; ecosystem destruction; and storm surge-induced or

otherwise induced damage to economy, livelihood, ecosystem, and special areas.

The Province of Gorontalo, the target region of this study project, suffers frequent droughts induced by climate

change such as El Niño. Additional problems associated with the Province are landslide and flood disasters that

1 JETRO “Indonesia: Basic Economic Indicators” at https://www.jetro.go.jp/world/asia/idn/stat_01.html

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result from reduced ecosystem function due to deforestation for slash-and-burn agriculture. As a result, Lake

Limboto has not only diminished in area and depth (area reduced by 60 percent and max. depth reduced to 4

meters from 14 meters over 20 years) but has also come to face various environmental problems due to water

quality deterioration, such as survival crisis of endemic aquatic species and poor fish catches.

Additionally, the Gorontalo Provincial BPBD has been established only very recently and has yet to be able to

cooperate efficiently with the BMKG regional office in issuance of forecasts and warnings. Due to delays in local

government efforts in disaster prevention and environmental conservation, no flood disaster mitigation measures

have been implemented yet and no established data have been made available for estimating losses from disasters.

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2. Study methodology

2-1. Study content

The purposes of this study project are as follows: proposing strategies for using the flood simulator (flood

hazard map development and real-time inundation prediction); lobbying the local government about the

effectiveness of the disaster prevention infrastructure system through a project implementation feasibility study

on the introduction of weather radar; and winning the contract for flood simulator installation financed locally by

the local government budget and/or weather radar installation financed by the UN’s GCF, a yen loan, or any other

foreign funds. The study items are as shown in Table 2-1:

Table 2-1: Study items

Item Details

1) Survey on the use of weather radars and

flood hazard maps in Japan

Investigated cases of their use in Japan and organize basic data

for considering feasible strategies in Gorontalo Province.

2) Current status survey on Gorontalo

Regency

Investigated the current state of precipitation observation,

frequency bands available for the weather radar to be

introduced. Collected information on, among other things, the

following; possible installation sites for the new weather radar;

flood response preparedness; and past flood disasters.

3) Current status survey on irrigation and

anti-flood infrastructure

Investigated the current status of any irrigation project and flood

control infrastructure development along the rivers supplying

water to the target region of this study project.

4) Feasibility study on the introduction of

the “flood simulator” and “weather

radar”

Verified the effectiveness of hazard map development using the

flood simulator. Performed cost-benefit analysis of its

introduction and narrowed down the list of possible weather

radar installation sites to analyze the effect and cost-benefit of

the introduction.

2-2. Study method, organizational framework, and schedule

(1) Study method

This study was conducted under the organization shown below according to the schedule shown below. A

total of six field investigation visits were made mainly to Gorontalo Regency and Gorontalo City governments,

the BMKG Regional Office, the Regional Disaster Management Agency (BPBD), the Ministry of Public Works

(PU) Regional Office, and Regional River Bureau (BWSSII); these visits were preceded and followed by

analysis work in Japan.

As explained below in the study results, the collaborative work with these government-affiliated

organizations consisted mainly of grasping the current state and activities, collecting related data, and

conducting joint on-site surveys. Regarding future equipment installation, a hearing was held in Jakarta with

related departments and agencies.

(2) Organizational framework for study implementation

The organizational framework for implementing this study project is as shown in Figure 2-1:

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Figure 2-1: Organizational framework for study implementation

(3) Study schedule

The schedule for this study project is as shown in Figure 2-2:

作業項目 Work item

8 月 August

9 月 September

10 月 October

11 月 November

12 月 December

1 月 January

2 月 February

1.計画準備 1. Planning and preparation

2.本邦の気象レーダ・洪水ハザードマップの活用状況調査

2. Survey on use of weather radar and flood hazard maps

in Japan

3.ゴロンタロ県における現状調査 3. Current status survey in Gorontalo Regency

3.1 洪水シミュレータ関連データ確認収集 3.1 Flood simulator-related data check and collection

3.2 気象一般、既存レーダーのデータ収集分析 3.2 Collection and analysis of general meteorological and

existing radar data

3.3 灌漑、洪水状況（既往洪水水位等）の調査 3.3 Survey on irrigation/flood status (past flood water

作業項目

▲

実施スケジュール詳細

6．追加1回目（10月20日～31日）では、関係者会合及びワークショップ・シンポジウム開催に向けた詳細打ち合わせを実施。兼松、ゴーベルDKMが参加。7．追加2回目（10月29日～11月10日）では、関係者会合及び追加情報収集活動を実施。パスコ、ゴーベルDKMが参加。8. 経産省との打ち合わせは、契約打ち合わせ、及び報告書確認打ち合わせも入れて合計5回実施。

　▲　　　　▲

1. 出張回数は6回実施、COP24にも参加。各出張期間と内容は下記の通り。追加調査2回については個別報告書は提出していない。2. 1回目（8月4日～10日）ではキックオフ、プレゼン説明、及び関連部署等との個別協議を実施。兼松、日本気象協会、パスコ、ゴーベルDKM、Daemeter社が参加。3. 2回目（9月25日～10月6日）では、資料収集、追加現場調査、ワークショップ準備等を実施。日本気象協会及びゴーベルDKMが参加。

4. 3回目（11月20日～28日）では、ワークショップを実施し調査結果を共有し、県主催のシンポジウムに参加。またジャカルタにて大使館・BMKG訪問及び関係者会合を　実施。兼松、日本気象協会、日立、パスコ、中外、ゴーベルDKM、Daemeter社が参加

5. 4回目（1月20日～24日）では、大使館・BMKG訪問及び関係者会合を実施。兼松、日本気象協会、ゴーベルDKMが参加。

★4

　経産省打合せ ▲ 契約 ▲

追1　★　追2　★ 3

6.ワークショップ・シンポジウムの実施 COP24

7.報告書の作成

　現地（ゴロンタロ県）調査・訪問 ★ 1 ★ 2 ★

2月

1.計画準備

2.本邦の気象レーダ・洪水ハザードマップの活用状況調査

3.ゴロンタロ県における現状調査 3.1 洪水シミュレータ関連データ確認収集 3.2 気象一般、既存レーダーのデータ収集分析 3.3 灌漑、洪水状況（既往洪水水位等）の調査

4.ゴロンタロ県への気象レーダ導入可能性検討

5.ゴロンタロ県へのDioVISTA導入可能性検討

8月 9月 10月 11月 12月 1月

Outsourcing

Chugai Technos Corp.

Outsourcing

Hitachi, Ltd. Pasco Corp. Indonesia

Gorontalo Regency Govt.

Gobel Group

Cooperation in survey

Daemeter

METI

Commissioning

Coordination/support

for field survey Survey implemented by

Kanematsu Corp. JWA

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levels, etc.)

4.ゴロンタロ県への気象レーダ導入可能性検討 4. Feasibility study on introduction of weather radar in

Gorontalo Regency

5.ゴロンタロ県への Japan-made Flood-Simulator導入可能性検討

5. Feasibility study on introduction of Japan-made Flood-

Simulator in Gorontalo Regency

6.ワークショップ・シンポジウムの実施 6. Holding of workshop/symposium

7.報告書の作成 7. Report preparation

現地（ゴロンタロ県）調査・訪問 Fact-finding missions/visits (Gorontalo Regency)

経産省打合せ Consultations with Ministry of Economy, Trade and

Industry (METI)

追 1 Follow-up 1

追 2 Follow-up 2

契約 Contract

実施スケジュール詳細 Details of implementation schedule

1. 出張回数は 6 回実施、COP24 にも参加。各出張期間と内容は下記の通り。追加調査 2 回については個別報告書は提出していない。

1. Made six visits. Also attended COP24. Periods of these

visits are as given below. No separate report presented

for two follow-up investigation visits.

2. 1 回目（8 月 4 日～10 日）ではキックオフ、プレゼン説明、及び関連部署等との個別協議を実施。兼松、日本気象協会、パスコ、ゴーベル DKM、Daemeter

社が参加。

2. During 1st visit (Aug. 4 to 10), held kick-off meeting,

made presentation, and had individual discussions with

related departments. Participants joined from

Kanematsu, JWA, Pasco, Gobel DKM, and Daemeter.

3. 2 回目（9 月 25 日～10 月 6 日）では、資料収集、追加現場調査、ワークショップ準備等を実施。日本気象協会及びゴーベル DKM が参加。

3. During 2nd visit, (Sept. 25 to Oct. 6), collected data,

conducted additional on-site investigations, made

preparations for workshop, and performed other related

tasks. Participants joined from JWA and Gobel DKM.

4. 3 回目（11 月 20 日～28 日）では、ワークショップを実施し調査結果を共有し、県主催のシンポジウムに参加。またジャカルタにて大使館・BMKG 訪問及び関係者会合を実施。兼松、日本気象協会、日立、パスコ、中外、ゴーベル DKM、Daemeter 社が参加

4. During 3rd visit (Nov. 20 to 28), held workshop to

share survey results. Then, joined symposium hosted by

Regency. Back in Jakarta, paid visits to Japanese

Embassy and BMKG and held stakeholder meeting.

Participants joined from Kanematsu, JWA, Hitachi,

Pasco, Chugai, Gobel DKM, and Daemeter.

5. 4 回目（1 月 20 日～24 日）では、大使館・BMKG

訪問及び関係者会合を実施。兼松、日本気象協会、ゴーベル DKM が参加。

5. During 4th visit (Jan. 20 to 24), paid visits to Japanese

Embassy and BMKG and held stakeholder meeting.

Participants joined from Kanematsu, JWA, and Gobel

DKM.

6．追加 1 回目（10 月 20 日～31 日）では、関係者会合及びワークショップ・シンポジウム開催に向けた詳細打ち合わせを実施。兼松、ゴーベル DKM が参加。

6. During 1st follow-up (Oct. 20 to 31), held stakeholder

meeting and detailed meeting in preparation for and

workshop/symposium. Participants joined from

Kanematsu and Gobel DKM.

7．追加 2 回目（10 月 29 日～11 月 10 日）では、関係者会合及び追加情報収集活動を実施。パスコ、ゴーベル DKM が参加。

7. During 2nd follow-up (Oct 29 to Nov. 10), held

stakeholder meetings and collected additional

information. Participants joined from Pasco and Gobel

DKM.

8. 経産省との打ち合わせは、暫定的に契約打ち合わせも入れて 4 回実施。

8. Four meetings held with METI, tentatively including

contract consultation.

Figure 2-2: Study implementation schedule

2-3. Study results

(1) Current status of the use of weather radar and flood hazard maps in Japan

(i) Weather radar

A weather radar is an instrument to observe precipitation and winds by transmitting radio waves in a range

with a radius of several hundred kilometers and measuring the radio wave reflections from rain drops. In Japan,

a dual-polarization weather radar equipped with a solid-state transmitter was developed by a domestic

manufacturer. Now deployment of weather radar networks is underway to cover the whole country.

A dual-polarization radar simultaneously transmits and receives radio waves that oscillate in horizontal and

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vertical directions. These two types of received signals are processed to calculate rainfall intensities with high

accuracy. Amounts of rainfall can be accurately estimated entirely on the basis of radar data without the need

of relying on rain gauges for corrective calculations. Additionally, the time required from observation until

weather information provision can be reduced to approximately 1 to 2 minutes. Figure 2-3 shows typical

measurements taken by single-polarization dual-polarization radars.

In dual-polarization measurement, as shown in Figure 2-4, longitudinal- and transverse-wave pulses are

transmitted to estimate the shapes of rain drops, thereby significantly improving the observation accuracy. This

allows acquisition of high-resolution data (250-meter mesh, 1-minute intervals) with accuracy almost equivalent

to that achievable by on-ground rain gauges. These data are expected to be useful in various fields of application.

直上メッシュ Overhead mesh

地上雨量計とレーダーメッシュ値の関係 Relationship between rain gauge readings and radar

mesh values

10 分雨量（mm/10 分） 10-minute precipitation (mm/10 minutes)

地上雨量（mm） Ground rainfall amount (mm)

二重偏波レーダ雨量（mm） Precipitation measured by dual-polarization radar (mm)

従来手法レーダ雨量（mm） Precipitation radar-measured by conventional method

(mm)

従来手法（単偏波）は誤差が大きい The conventional method (single-polarization) is prone

to large errors.

二重偏波レーダは地上雨量計による補正なしでも高精度

The dual-polarization radar provides highly accurate

measurements without relying on rain gauges for

corrective calculations.

2017 年 07 月 11 日 July 11, 2017

地上雨量計の直上メッシュと比較 Comparison of precipitation data between radar data on

overhead mesh and rain gauge data

Figure 2-3: Comparison in terms of observation accuracy between conventional and dual-polarization

radars

二重偏波レーダは地上雨量計による補正無しでも高精度

地上雨量 (mm)

二重偏波レーダ雨量(mm)

従来手法レーダ雨量（mm）

地上雨量計の直上メッシュと比較

従来手法（単偏波）は誤差が大きい

radar rain-gauge

直上メッシュ

地上雨量計とレーダーメッシュ値の関係

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レーダ Radar

送信パルス Transmitted pulse

偏波間位相差 Specific differential phase

受信信号 Received signal

降水域 Precipitation area

雨滴の大きさにより雨滴の形状が扁平する性質を利用

The tendency of rain drops to become flatter with size is

used.

Figure 2-4: Principle of measurement using dual-polarization radar

In Japan, replacement is underway of conventional (single-polarization) radars with dual-polarization solid-

state radars. As detailed later, 14 out of 26 C-band weather radars under the control of the Ministry of Land,

Infrastructure, Transport and Tourism (MLIT) have been replaced with dual-polarization radars, most of which

are solid-state radars. A solid-state radar is one equipped with a transmitter built with semiconductors (solid-

state elements). The differences between the types of transmitters are as shown in Table 2-2. Solid-state

transmitters require low transmission power and hence provide a system suitable for use in Indonesia, troubled

with a worsening power shortage. Built with parts having a long service life of over 10 years, these transmitters

excel in terms of maintainability and hence provide operational and economic advantages.

Table 2-2: Comparison of radio wave transmission systems

Item Longevity Lifecycle cost Operability /

maintainability

Unit’s

footprint Transmission power

Magnetron × × × △ Approx. 250 kW

Klystron △ △ × × Approx. 200 kW

Solid-state element ◎ ◎ ◎ ◎ Approx. 6 kW

In Japan, the Japan Meteorological Agency (JMA) and the MLIT each operate a C-band radar observation

network covering the whole country (Figure 2-5). Additionally, the MLIT also operates a country-wide X-band

Polarimetric Radar Information Network (XRAIN) (Figure 2-6). The JMA’s radars are mainly used for daily

numerical prediction calculations and weather forecasts. Meanwhile, the MLIT uses its C-band radars mainly

for river management and disaster prevention purposes such as landslide disaster monitoring while operating

the XRAIN primarily to monitor short downpours in urban areas.

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Figure 2-5: C-band radar observation networks operated by JMA (left: coverage radius = 200 km) and MLIT

(right: coverage radius = 120 km)

Figure 2-6: MLIT’s X-band Polarimetric Radar Information Network (XRAIN) (coverage radius =60 km)

(ii) Flood hazard maps

The Japanese Flood Protection Act requires that each municipality prepare a flood hazard map by adding the

following to flood- and inundation-prone area maps: the methods of disseminating flood-related information

including flood forecasts; locations of disaster refuge areas; and all other information necessary to ensure

efficient and rapid evacuation in the event of a flood disaster. As of March 2017, approximately 1,300

municipalities have made their flood hazard maps open to public access. The MLIT’s hazard map portal site

(https://disaportal.gsi.go.jp/) allows users to view flood hazard maps covering the whole country.

Table 2-3 shows typical applications of flood hazard maps. As an example of evacuation drills using a hazard

map, Figure 2-7 shows snapshots of one conducted in Okura Village, Yamagata Prefecture.

Table 2-3: Typical applications of flood hazard maps

• Disaster prevention lectures using flood hazard maps

• Evacuation drills using hazard maps

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• Water disaster prevention education in collaboration with educational institutions

• River study meetings for promoting better understanding of hazard maps

• PR through mass media (radio)

• Wall or bulletin board displays at community centers, schools, etc.

• Application to evacuation action plan development

Figure 2-7: Typical example of evacuation drill using a flood hazard map

取組主体：大蔵村、大蔵村消防団 Conducted by: Okura Village and its fire brigade

参加人数：住民 71 人（大人 46 人、子ども 25 人） Number of participants: 71 residents (46 adults and 25

children)

取組概要：平成 23 年 9 月の「大蔵村総合防災訓練」において、住民に洪水ハザードマップ、まるごとまちごとハザードマップを理解してもらうため、3 地区に分かれて、ハザードマップを活用した防災訓練を実施

Description of activity: “Okura Village Comprehensive

Disaster Prevention Drill” was held in September 2011.

The participants were divided block by block into three

groups to help them better understand the flood hazard

map and village-wide hazard map.

・まるごとまちごとハザードマップの概要説明 • Briefing of village-wide hazard map

・標識を確認しながら避難誘導訓練 • Evacuation guidance drill conducted checking signs

・避難路の危険箇所などを確認し、評価シートに記入

• Evaluation sheet filled out, checking hazard spots along

evacuation routes.

・避難場所に集合し、アンケート調査を実施 • Participants reassembled at the disaster refuge area to

respond to questionnaire survey.

洪水ハザードマップ Flood hazard map

「平成 23 年度大蔵村総合防災訓練」の様子 Snapshots of “FY 2011 Okura Village Comprehensive

Disaster Prevention Drill”

説明の様子（清水 2・3 地区） Snapshot of briefing (Shimizu Districts 2 and 3)

避難の様子（清水 2・3 地区） Snapshot of evacuation (Shimizu Districts 2 and 3)

説明の様子（合海地区） Snapshot of briefing (Aikai District)

避難の様子（合海地区） Snapshot of evacuation (Aikai District)

An inundation simulation is necessary to develop flood- and inundation-prone area maps for inclusion in a

hazard map. The “Japan-made Flood-Simulator” flood simulator described in the next sub-section allows the

user to easily specify and manipulate the conditions for embankment failure and overtopping and the

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computational conditions for rainfall scenarios. Thus, it serves as an optimal tool for developing flood hazard

maps.

The introduction of “Japan-made Flood-Simulator” to Gorontalo Province will allow the development and

revision of flood hazard maps and their application to evacuation drills and evacuation action planning, thereby

helping to enhance resilience against frequent water disasters.

(2) Flood simulator-related

To ensure the introduction of the “Japan-made Flood-Simulator” flood simulator to Gorontalo Province and

Regency, the Provincial and Regency governments must be lobbied about the simulator’s computational

performance, reproducibility, and operability. Then, this study project conducted a simulation covering the area

shown in Figure 2-8 and evaluated the obtained results.

A high-precision simulation requires accurate data, which are expensive and not readily available. Hence, we

used data provided by the relevant government agencies of Gorontalo Province and open data available on the

Internet. At a workshop held by the Gorontalo Regency Government Office (on November 23, 2018 during our

third stay), we made a presentation of the obtained evaluation results to the Regency Governor and those in

charge of disaster prevention. We also conducted an operational demonstration of “Japan-made Flood-

Simulator.”

Figure 2-8: Area covered by the simulation

(i) Acquisition of data necessary for simulation and its evaluation

In this study project, a list was made of data necessary to introduce “Japan-made Flood-Simulator” and

process analysis results. Then, consideration was given to the availability of such data.

More specifically, we investigated the websites of relevant Indonesian national agencies beforehand in Japan

and then conducted a hearing survey in Indonesia, as shown in Table 2-4, with assistance from Nusantara Secom

InfoTech (NSI), the local subsidiary of Pasco Corporation. These research activities clarified the presence or

absence of existing data and allowed us to grasp the detailed specifications of available existing data and their

availability for use in this project and to estimate the costs and expenses incurred from the use of such data.

Considering the continuity of the project, it is desirable to keep data collection and maintenance costs low. The

11

accuracy of data, however, will directly affect that of “Japan-made Flood-Simulator” analysis results.

Accordingly, we have to devise data collection and maintenance strategies with consideration given to the

balance between accuracy and cost-effectiveness.

Table 2-4: Outline of fact-finding mission on existing data

Period Main agencies visited

Aug. 4 to 10, 2018

BPBD Gorontalo Provincial Office

BMKG Gorontalo Office

PU Gorontalo Provincial Office

BWS Sulawesi Second Office

BPBD Gorontalo Regency Office

BPBD Gorontalo City Office

Oct. 30 to Nov. 8, 2018

Geospatial Information Agency (BIG)

Headquarters

BPBD Gorontalo Provincial Office

BWS Sulawesi Second Office

BPBD Gorontalo Regency Office

Gorontalo City Hall

Bappeda Gorontalo City Office

First, Table 2-5 shows the list of data necessary for a “Japan-made Flood-Simulator” simulation. Table 2-6

shows the survey results on the availability of such data.

Table 2-5: List of input data to “Japan-made Flood-Simulator”

Data item Description/specifications

Map data

• NASA satellite image data (Landsat, etc.)

• DigitalGlobe satellite image data (World View, etc.)

• Aerial photographs • Commercially available map data • Other map data

Elevation data • Satellite-measured elevation data (NASA SRTM) • LiDAR-measured elevation data

River-related data

• Flood hazard map • Flood history maps • River watershed maps

• River centerline data (longitudinal river cross-section survey maps)

• Transverse river cross-section survey maps

• River flow rate analysis results • Time-series river flow rate prediction data

• Flood prediction data based on assumed embankment failure

Precipitation data • Time-series precipitation data (observation data from flow-rate monitoring stations)

River water level

data • Historical and real-time flood water level data

Land use data • Land use data generated from satellite images (USGS GLCC)

• Land use data created by Indonesian government

Data on in-river

structures

• Data on dam specifications, reservoirs, and ponds (drainage discharge volumes and

water levels)

Table 2-6: Results of fact-finding mission on existing data availability

Data item Results of fact-finding mission

Map data

Satellite images: Landsat images are open and available for free.

The National Institute of Aeronautics and Space (LAPAN) delivered Pleiades images,

Worldview images (2013-2018), and SPOT6/7 images (2017-2018) to the BNBP

Gorontalo Provincial Office.

Aerial photographs: 1:10,000 aerial photographs of Gorontalo Province taken by the BIG

in 2012. These are not made open.

Topographic maps: The BIG has been developing 1:5,000 topographic maps of urban

areas since 2015. The target area of this project falls outside of the coverage of these maps.

The 1:50,000 topographic maps prepared by the BIG are available for download and use

free of charge from the BIG portal site (http://tanahair.indonesia.go.id/portal-web).

The BIG has also been developing 1:25,000 topographic maps, the data of which are not

made open and are limited for use within government agencies only.

Elevation data Satellite data: SRTM data are open and available for free.

http://tanahair.indonesia.go.id/portal-web

12

LiDAR data: There are no existing measurement data covering the target area of this study

project.

River-related data

Hazard map: Flood hazard maps prepared by the BPBD. With their parameters and

specifications kept confidential, no judgment can be made as to their practical usability.

Flood history maps: Historical records do exist but not in the form of maps.

River watershed maps: The 1:50,000-scale shapefiles prepared in 2017 by BWSS2 are

open and available for use. There are shapefiles covering the Limboto-Bolango-Bone, the

Paguyaman, and the Landangan river basin.

River centerline (longitudinal and transverse cross-section) data: There are longitudinal

and transverse cross-sections prepared in 2007 by BWSS2. Data are available by

submission of a formal request for use.

Other river data seem to be included in reports prepared by BWSS2.

Precipitation data Monitored and recorded by the BMKG.

River water level

data

Made open in reports prepared by BWSS2. These reports contain water level, flow rate,

and precipitation data from monitoring stations installed along major rivers. BWSS2

annual reports have been prepared since 2002.

Land use data

USGS GLCC: Open and available for free.

Land use maps: Prepared as part of spatial planning at national, provincial, and regency

levels. The responsible agencies are Bappenas and Bappeda. Not made open in the form

of digital data.

Data on in-river

structures Prepared and maintained by BWSS2. Available by submission of a formal request for use.

The results of the fact-finding mission revealed that many of the input data to “Japan-made Flood-Simulator”

are absent in the existing digital datasets. Data absent in the existing digital datasets may be newly created.

In Gorontalo Province, we ran a demonstrative simulation that reproduced the cases of the flood disasters

that hit the Province of Gorontalo in 2013 and 2016. During our first and second stays, we locally collected the

data necessary for the reproduction. Table 2-7 shows the list of collected data.

Table 2-7: List of locally collected data

Description Collected by

River/embankment cross-sections of Bone river, Bolango river and Limboto lake basin BWSSII

Daily precipitations and river flow rates in Bone river, Bolango river and Limboto lake basin

(for recent 10 years) BWSSII

Daily precipitation data from BMKG monitoring stations around Lake Limboto (for recent 10

years)

(i) Stasiun Meteorologi Djalaluddin Gorontalo (ii) Stasiun Geofisika Gorontalo

(iii) Stasiun Klimatologi Tilongkabila Bone Bolango

BMKG

Gorontalo City flood hazard maps (inundation-prone area maps) BMKG

Gorontalo Regency flood hazard maps (inundation-prone area maps) BPBD

(ii) Simulation results and evaluation

The obtained data were entered into “Japan-made Flood-Simulator” to simulate the cases of flood disasters

that hit the Province of Gorontalo in 2013 and 2016.

Figure 2-9 shows the details of the data used for the simulation.

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Rivers

Elevations

Precipitation data

・河川断面図 • River cross-sections

・堤防 • Embankments

－リンボト湖沿い設置済み - Built along Lake Limboto

・標高データ • Elevation data

－衛星データ - Satellite data

－解像度 - Resolution

[オープンデータ] [Open data]

・衛星データ • Satellite data

・解像度：10 ㎞ • Resolution: 10 km

・毎時 • Hourly

Figure 2-9: Open data used for simulation

Figure 2-10 shows the results of the demonstrative simulation conducted in Gorontalo Province.

Figure 2-10: “Japan-made Flood-Simulator” simulation results (left: May 2013; and right: Oct. 2016)

[オープンデータ]

•衛星データ

•解像度: 10 km

•毎時

Data: GSMaP data by Japan Aerospace Exploration Agency (JAXA)

•標高データ

–衛星データ

–解像度

• Horizontal: 30 m

• Vertical: 1 m

Data: High-resolution digital topography data from NASA's Shuttle Radar Topography Mission (SRTM).

•河川断面図

–Bolango River

CS point 1

–Bolango River

CS point 2

–Alo Pohu River

CS point 3

–Biyonga river

CS point 4

•堤防

–リンボト湖沿い

設置済

embankment

14

The primary objective of this demonstration was not simply to obtain high-accuracy simulation results but to

show the usefulness of the software by running simulations using open data, along with transverse data collected

from available sources, without the need for purchasing high-accuracy DEM data.

The simulation results were reviewed by the person in charge on the Indonesian side. The simulator was

highly valued for easy operation, high understandability of the graphic outputs it can generate, and high speed

that reduces the time required for the completion of a simulation.

There were no detailed precipitation data (time-series data), river cross-sections, or inundation area maps

available for this study project. Nevertheless, we consider that the sampling verification results obtained from

four locations, for each of which we conducted a hearing, are valid as far as inundation depths are concerned,

when considering that the historical flood marks and the simulation results showed minor differences ranging

from 0.3 to 0.65 meters (topographic accuracy/error of 1.0 m) as in Figure 2-11. If the differences fall within

the range observed in our demonstrative verification, the simulator will be sufficiently effective for identifying

inundation risks (hazard map development).

For the purpose of early flood warning, the simulator must be also evaluated in terms of river level prediction

accuracy. Accordingly, detailed time-series precipitation data, topographic data, and river data must be loaded

and verified.

過去の洪水痕 Historical flood marks

比較検証 Comparative verification

シミュレーション結果 Simulation results

Figure 2-11: “Japan-made Flood-Simulator” simulation results evaluation

(3) Weather radar-related

(i) Current status of weather radar deployment in Indonesia

Figure 2-12 shows the status (as of January 2018) of the Indonesian weather radar network deployed by the

BMKG. There are 37 C-band radars (coverage radius: 150 km) deployed along with 4 X-band radars (ditto: 60

km). In the northern part of Sulawesi Island, where Gorontalo Province is situated, the C-band radars installed

in Gorontalo and Manado are already in operation for weather monitoring.

Table 2-8 quotes the allocation status of the main frequency bands used for weather radars from the

“Indonesian Table of Frequency Allocation (2003).”2 As of November 2016, Indonesia allocates the 5,540-

5,640-MHz band to 5-cm (C-band) weather radars and the 9,500-MHz band to 3-cm (X-band) weather radars.

2http://kambing.ui.ac.id/onnopurbo/orari-diklat/pemula/teknik/bandplan/CUPLIKAN%20TABEL%20FRQ.PDF

過去の洪水痕シミュレーション結果

FL1 Ilotidia villageSimulation: 1-2 mHistorical : 1.7 m

比較検証

FL2 Tualango villageSimulation: 1-2 mHistorical : 1.35 m

FL3 Detafu villageSimulation: 0.5-1 mHistorical : 0.62 m

FL4 Limboto villageSimulation: 0.5-1 mHistorical : 0.79 m

15

Figure 2-12: Indonesian weather radar network (as of January 2018: coverage radius = 60 km)

(Source: BMKG’s presentation shown at 2018 WMO Regional Conference in RA II (Asia))

Table 2-8: International and Indonesian allocations of frequency bands (MHz)

International allocation Indonesian allocation

Region 1 Region 2 Region 3

5,570-5,650 MHz

Mobile (except aeronautical mobile): 5.446A 5.450A

Radiolocation: 5.450B

Maritime radionavigation:

5.450 5.451 5.452

5,470-5,650MHz

Mobile (except aeronautical mobile): 5.446A

5.450A

Radiolocation: 5.450B

Maritime radionavigation:

5.450 5.451 5.452

9,500-9,800 MHz

Earth exploration-satellite (active)

Radiolocation

Radionavigation

Space research (active)

5.476A

9,500-9,800MHz

Earth exploration-satellite (active)

Radiolocation

Radionavigation

Space research (active)

5.476A

(ii) Fact-finding mission on weather radar deployment in Gorontalo

<First fact-finding mission (Aug. 2018)>

We visited the BMKG Gorontalo Weather Monitoring Office (Stasiun Meteorologi Djalaluddin Gorontalo)

and the BMKG Gorontalo Earthquake Monitoring Office (Stasiun Geofisika Gorontalo) for hearings on the use

of weather radars (Photo 2-1).

The Gorontalo C-band radar is installed on the premises of Stasiun Geofisika Gorontalo, north east to Lake

Limboto. This is a relatively new radar put into operation in January 2012. The radar observation tower is a

four-storey building topped with a radome (radar antenna) at an elevation of 76 m. The third floor

accommodates the machine monitoring room.

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The observation scheme is such that the radar is operated at 9 elevation angles in 10-minute cycles (0.5°→

1.45°→2.4°→3.35°→4.3°→6.0°→9.9°→14.6°→19.5°→0.5°).

This radar is used for weather warning (Severe Weather Warning, issued 2 hours before danger arises) and

also for air traffic control at Gorontalo Airport. The data transmitted from this radar are received at the BMKG

Jakarta Headquarters and combined there with data from other weather radars to make weather predictions

based on the numerical model WRF.

According to the radar site personnel, noises sometimes occur due to radio wave interference in the waters

south-south-east of the radar site but do not become so intense as to affect inland precipitation monitoring or

weather warning issuance.

Photo 2-1: Gorontalo weather radar observation tower (upper left); Area near Lake Limboto as viewed from

observation tower (upper right); radar control machine on 3rd floor of radar observation tower (bottom left); and

radar monitor screen (bottom right)

<Second fact-finding mission (Sept. to Oct. 2018)>

We conducted an on-site survey to qualitatively evaluate 10 locations in Gorontalo Regency in terms of

visibility, site space, road conditions, power supply conditions, and telecommunications conditions. Figure 2-

13 shows the locations of the candidate sites. Table 2-9 shows the itemized evaluation scores on the proposed

introduction of X-band radars.

Located at an elevation of 600 meters in the southern part of Gorontalo Regency and overlooking Gorontalo

Airport and Lake Limboto, the mountain plateaus (Site No.9 Hepu and Site No.10 Bolongga) are the perfect

locations for monitoring rain clouds. These sites, however, have the drawbacks of power supply unavailability,

17

poor road conditions, and poor telecommunications access. Hence, we found it difficult to install new X-band

radars in these locations. During the hearing with the BMKG, it turned out that when they considered installing

C-band radars in 2011, they excluded the very same mountainous sites from the list of candidate installation

sites without conducting an on-site survey. Therefore, the X-band radars should basically be installed on flat-

ground sites with easy access to electric power and telecommunications, even if some radio wave interference

occurs due to the surrounding mountains, and should preferably be installed at the following sites:

• Case of introducing one radar: No.4 Limehe Barat (between Airport and Lake Limboto)

• Case of introducing two radars: No.1 Mulyonegoro (west to Airport) and No.7 Kota Gorontalo (Maqna Hotel)

Figure 2-13: Names and locations of candidate radar sites

Gorontalo Airport Radar site

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Table 2-9: Itemized evaluation scores on the proposed introduction of X-band radars

No. Site name Elevation

(m)

LOS

availability

Site

space

Road

situation

Power

supply

situation

Telecom

situation Evaluation

1 Mulyonegoro 181 〇〇〇〇〇〇

2 Reksonegoro 44 △ ◎ ◎ 〇〇 △

3 Molopatodu 108 △ 〇 △ 〇〇 △

4 Limehe Barat 15 〇〇 ◎ 〇〇〇

5 Ilomangga 13 △ ◎ ◎ 〇〇 △

6 Tomulabutao 15 〇 △ △ 〇〇 △

7 Kota Gorontalo 8 〇 ◎ ◎ 〇〇〇

8 Tanggilingo 19 △ △ 〇〇〇 △

9 Hepu 598 ◎ △ × × × △

10 Bolongga 602 ◎ 〇 × × × △

◎ = Excellent; 〇 = Good; △ = Inferior; × = Poor

(4) Past flood situation

We investigated past flood situations as shown in Figure 2-13.

The investigation results boil down to the following two points:

✓ The past floods experienced at the three locations around Lake Limboto were of types accompanied

by a slow increase/decrease in water level. The maximum flood water levels observed in 2016 were

1.7 m at Ilotidea (F1), 1.35 m at Tualango (F2), and 0.8 m at Kayubulan (F4). The results of this

investigation were used to adjust and correct the flood simulator.

✓ It was ascertained that the flood experienced near the airport and near the confluence of Alo and

Mokaraf Rivers had been of a different type characterized by a high flow velocity. The maximum

flood water level observed also in 2016 was 0.6 m at Datafu (F3). Notably, the flow velocity was 1 m

per second or more.

(5) River improvement status (flow rate data collection covering lake water and irrigation)

We investigated the current status of flood control measures and river improvements as shown in Figure 2-

14.

The investigation results boil down to the following three points:

✓ In accordance with the countermeasure work plan based on, among other things, JICA Master Plan

Study on Flood Control Measures, the countermeasure works have been completed for the most part

(P2 to P5) with some sections still under construction. The construction of the Bolango-Limboto

Communication Canal has been aborted in the middle.

✓ The super embankment east to Lake Limboto (P6: 4-meter height increase) has been completed.

Meanwhile, the floodway downstream to the adjustment sluice gate has not been completed yet.

✓ The Tamalate Flood Interception Channel (P1) was completed in 2015, making a significant

contribution to flood mitigation in Gorontalo City.

19

Figure 2-14: Past flood situations / locations of river improvement status survey points

(6) Hosting local workshop and seminar at Gorontalo province

Local workshop has been held in the 3rd fact-finding mission as shown in Table 2-10 and Photo 2-2. Moreover,

by the request from Gorontalo province, additional presentation has been conducted local seminar in the next

day hosted by Gorontalo province as shown in Table 2-11 and Photo 2-3.

Table 2-10: Outline of local workshop

Item Outline

Venue and time Gorontalo provincial government hall, 23rd-Nov-2018

Paeticipants

Gorontalo provincial governor, personnel concerned with disaster prevention in Gorontalo

province, representative of BPBD in Gorontalo city, personnel concerned with university

and university students (about 100 person)

Contents

Results report of feasibility study project

1) Feasibility Study on Adaptation Program Against flood with Introduction of Flood

Simulator and Weather Radar Systems in Gorontalo District : Japan Weather Association

2) Japan-made Flood-Simulator/Flood -Save the nation from flood by ICT- : Hitachi, Ltd.

3) Progress report of REDD+ project : Kanematsu Corporation

Questions and

comments

(Gorontalo province)

Budget for the installation of weather radar and flood simurator should be managed with

Japan government’s cooperation.

(Dr. Nelson, governor of Gorontalo province)

How Japan government can contribute when Indonesian local government could cover

some costs for the installation?

(Student of Gorontalo university)

How long should rainfall input data be needed when flood simurator is used for real time

operation of early warning?

How do we tune flood simurator software for improving the accuracy of flood

prediction?

20

Photo 2-2: Local workshop

Table 2-11: Outline of local seminar

Item Outline

Venue and time Pentadio (outside stage), 24th-Nov-2018

Paeticipants

Gorontalo state vice governor, Gorontalo provincial governor, personnel concerned with

disaster prevention in Gorontalo state, personnel concerned with university and university

students (about 200 person)

Contents

【AM】

1) Action of the information propagation for the disaster mitigation : BNPB

2) Mechanism of Earthquake, Tsunami and liquefaction in Indonesia : Bandung Institute of

Technology

3) Environmental destruction issue and conservation activities at the Lake Limboto :

Gajamada university

4) Effort for the female-centric community formation of disaster prevention such as river

maintenance : Gorontalo university

【PM】

5) Japan’s experience of past major disasters, information for the disaster prevention and

latest study of Tsunami detection : Japan Weather Association

6) Introduction of Flood simurator “Japan-made Flood-Simulator” and demonstration of

Tsunami prediction in the Gorontalo city : Hitachi, Ltd.

7) Risk assessment in Banda-aceh before and after 2004 Sumatra huge tsunami disaster :

Pasco, Ltd.

Photo 2-3: Local seminar

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(7) Results of discussions held in Jakarta with the Japanese Embassy, the BMKG, and the BNPB

The following are the results of our survey activities in Jakarta, including visits to central government

agencies:

✓ Through the activities in Jakarta, we obtained some tips on building connections with government

officials above the working level and with sponsor countries. We also found the future direction of

the sales promotion activities for the introduction of disaster control infrastructure. It would be

effective to deploy activities in candidate localities, to win the understanding of the relevant provincial

government, and to lobby the central government.

✓ Our visit to the BMKG revealed that the series of disasters during last year prompted the BMKG to

adopt a policy for promoting rapid enhancement of equipment and organizations for monitoring,

forecasting, and warning meteorologically or otherwise dangerous phenomena (it is unknown to us

whether funds from aid agencies are available to the BMKG). More specifically, it turned out that PT

SUCOFINDO (state-operated comprehensive inspection company) will be deeply involved from the

enhancement planning phase through the equipment introduction phase. During the visit for this study

project, we contacted both parties and expect that there will be some headway made.

✓ Our visit to the BNPB revealed that monitoring, forecasting, and warning are the responsibilities of

the BMKG while disaster prevention education activities, which are ex-ante activities, and disaster

response operations, which are ex-post activities, are the main tasks of the BNPB. Hence, it became

clear that the forecasting/warning technology based on coordinated operations of Japan-made Flood-

Simulator and radars is intended for the BMKG. On the other hand, it was confirmed that Japan-made

Flood-Simulator is useful for improving hazard maps for disaster reduction, developing disaster

preparedness plans, and making disaster predictions based on analyses of past data. Therefore, we

decided to continue detailed consideration of the installation site and the content of the proposal to

the BNPB.

✓ Our visit to the Japanese Embassy revealed that JICA stands a slim chance in joining the scheme for

emergency support in Palu. Meanwhile, it seems in line with the intention of the Japanese government

to help the operator entity develop its capacity through a technical cooperation project for long-term

capacity development.

(8) Results of activities at COP24

To publicize the achievements of this study project to countries around the world, Kanematsu Corporation

together with Dr. Nelson, the Governor of Gorontalo Regency, attended the 24th Conference of the Parties to

the United Nations Framework Convention on Climate Change (COP24). During the event, Kanematsu and the

Regency Governor delivered a total of four presentations on this study project at the Indonesian and Japanese

Pavilions. Additionally, Kanematsu efficiently interviewed, among others, government officials and key persons

of both Indonesia and Japan, participants from the GCF and other financial institutions, and those from NGOs

and had discussions with them towards the formulation of this project.

The results of interviews with the Indonesian government officials (Dr. Nur, Special Advisor to the Minister

of Environment and Forestry, Ms. Emma, Director of the Bureau of Climate Change, as well as Mr. Dudi

Rulliadi, Deputy Director for International Climate Finance Division, Center for Climate Finance and

22

Multilateral Policy, Fiscal Policy Agency, Ministry of Finance [MoF]) boil down to the following three points:

✓ Visit both Ministries jointly with Gobel Group and lay the groundwork for the proposal to be

presented to the GCF

✓ Explain the project to the Ministry of Environment and Forestry (MoEF), which is the “Focal Point”

of the proposal to the GCF, and persuade the MoEF to recommend the proposal to the GCF to the

MoF.

✓ Explain the project to the MoF and sound out the MoF about the issuance of “No-objection Letter,”

which is necessary for submission of a “Funding Proposal” to the GCF.

23

3. Consideration of the content and technical aspects of the project

3-1. Background, necessity, etc., of the project

(1) Background of the project

With the recent increase in occurrences of flood disasters around the world including Asian countries,

Indonesian provincial governments are urgently required to introduce an infrastructure system for developing

disaster plans on the basis of theoretical databases and to develop disaster planners from among working-level

officials.

Typical impacts of climate change in Indonesia include increased sea water levels, increased sea surface water

temperatures, and changes in rainfall patterns. Adaptive challenges resulting from these include, among other

things: increases in floods/extreme weather phenomena; ecosystem destruction; and storm surge-induced or

otherwise induced damage to economy, livelihood, ecosystem, and special areas. The Province of Gorontalo

suffers frequent droughts induced by climate changes such as El Niño. Another problem associated with the

Province is landslide and flood disasters that result from reduced ecosystem function due to deforestation for

slash-and-burn agriculture.

Accordingly, this study project proposed that Gorontalo Provincial and Regency Governments should

introduce an infrastructure system (flood simulator and weather radars) as a platform that supports the

governments and all those involved in provincial- and regency-level flood disaster risk management.

(2) Necessity of the project

Gorontalo Province is hit by three or more large-scale floods per year (Photo 3-1) and suffers damage on its

society and economy. In Gorontalo Province, agriculture is a major industry and its expansion is causing more

and more deforestation. This causes forest top soil to erode into rivers and settle on the bottom of Lake Limboto.

Now with diminishing water depths, it is feared that Lake Limboto may disappear. In addition to this, localized

heavy rains induced by climate change adversely contribute to the increasingly frequent occurrences of floods

in Gorontalo Province. In the drainage basins in the target region of this study project, there is rainfall

throughout the year with precipitation peaking in the period from April to June. Thus, Limboto, Bone, and

Bolango Rivers flood nearly every year, causing long-term inundation in urban areas and farm lands (The Study

on Flood Control and Water Management in Limboto-Bolango-Bone Basin in the Republic of Indonesia, Japan

International Cooperation Agency (JICA), Dec. 2002). Although reinforcement works, including emergency

countermeasures, were completed in 2017, specific details still remain unknown to us. Meanwhile, there has

been little progress in the development of a countermeasure planning and implementation framework towards

flood disaster mitigation. Hence, damage amounts and other evaluation data still remain obscure.

24

Photo 3-1: Flood disaster in Gorontalo

(Source: AKSI CEPAT TANGGAP “1,500 Houses Affected by Gorontalo Flood” 2017)

The disaster prevention infrastructure system considered for introduction by this study project with the above

circumstances in mind collects real-time precipitation data from its “weather radars” and loads these data to

“Japan-made Flood-Simulator” to run flood simulations, thereby allowing implementation of ex-ante disaster

prevention measures and helping to minimize damage to the provincial society and economy.

Moreover, the above system can contribute to improving the Disaster Risk Index set by the Indonesian

government. This index is used to evaluate local government-level efforts in disaster risk management and

disaster prevention. This index will be improved when local governments promote disaster prevention efforts

hand-in-hand with residents and academicians as practiced in Japan as part of the Regional Adaptation

Consortium Project.3

If this disaster prevention infrastructure system is introduced in the future, training will be provided for

system operation and hazard map development, whereby the disaster preparedness and response capabilities of

Gorontalo Regency government will be enhanced. Then, collaborative use of the disaster prevention

infrastructure system between the Provincial and Regency governments will help improve the disaster risk index

for Gorontalo Province, thereby leading to reduction or mitigation of natural disaster damage (human lives,

properties, etc.).

As stated in the “Infrastructure System Export Strategy4 ” formulated by the Japanese government, the

introduction of the “Japan-made Flood-Simulator” flood simulator will lead to that of weather radars, thereby

producing a complex ripple effect of infrastructure system export. This will trigger the transfer of advanced

Japanese technology, know-how, systems, and so on to emerging economies, thereby contributing to solving

global-scale issues such as environmental protection and disaster prevention in counterpart countries.

3-2. Basic guidelines, decisions, etc., on the content of the project

On the basis of the study results, the following basic guidelines and a disaster prevention infrastructure

introduction plan (Table 3-1) based thereon were established to study the financial/economic feasibility and cost-

effectiveness of the project.

3 http://www.adaptation-platform.nies.go.jp/lets/conso/index.html 4 http://www.kantei.go.jp/jp/singi/keikyou/dai4/kettei.pdf

25

(Basic guidelines)

⚫ Collaboration is necessary between the following project implementation bodies: the Bureau of

Meteorology, Climate and Geophysics (BMKG) in charge of weather monitoring; and the National

Disaster Management Authority (BNPB) and the Regional Disaster Management Agencies (BPBD), both

in charge of communication/awareness building.

⚫ Going beyond hazard map development based on past data, the project should intend to develop a flood

forecasting warning system based on weather forecast and prediction data. Therefore, coordinated

operation with weather radars is required.

⚫ It is also important to reduce the cost through the use of existing infrastructure and to assist the

implementation bodies in enhancing the capabilities of their system operations personnel.

⚫ To make real-time flood predictions, the input of predictive precipitation data is indispensable. It is

required to introduce a rainfall prediction system (numerical forecasting model) built on the basis of actual

radar measurement data.

⚫ It is desirable to use detailed topographic data to improve the computational accuracy of the flood simulator.

(Optional item)

Table 3-1: Disaster prevention infrastructure introduction plan

Introduction

plan

Details Remarks

1a • Introduction of the flood simulator Usable for disaster prevention education at

universities, disaster prevention agencies, etc.

1b

• Introduction of the flood simulator

• Use of BMKG’s existing C-band weather radars

• Introduction of the rainfall prediction system

This plan will make it possible to make flood

predictions based on radar monitoring data.

2


• Installation of one new X-band weather radar


This plan will make it possible to make more

detailed flood predictions based on radar

monitoring data than possible with C-band radars

in Introduction Plan 1b.

3


• Installation of one new X-band weather radar


This plan will provide higher-quality radar

monitoring data than available with Introduction

Plan 2 and hence make it possible to make more

accurate flood predictions.

Optional

item

• Topographic data improvement for prediction

accuracy enhancement

Detailed topographic data will make it possible to

make more accurate flood predictions.

3-3. Outline of the project

The outline of the project is as shown in Table 3-2 and common to all plans above unless otherwise stated.

Table 3-2: Outline of the project

Item Details

Budgeting

To be budged by Gorontalo Regency and Gorontalo City. Additional consideration

will be required as to the division of financial burden when they introduce the

radar(s). When introducing the radar(s), they will use a yen loan or other means of

financing. In any case, the basic premise is that the purchase must be municipally

budgeted.

Flood simulator installation

site

BPBD Offices in Gorontalo Regency and Gorontalo City.

26

Installation site for radar,

server, etc.

BMKG Gorontalo Office. A system for transferring data via a data line or otherwise

from the radar to the simulator shall also be introduced.

Development of personnel

for introduced radar(s),

server, etc.

To be provided to BPBD Offices in Gorontalo Regency and Gorontalo City. The

same shall apply to BMKG Gorontalo Office if a radar is newly introduced thereto.

Hazard map

improvement/updating

The introduced simulator shall be used to improve or update the current hazard

maps to develop disaster preparedness plans. BPBD shall take initiative in public

awareness building, evacuation drills, etc.

3-4. Items required to be considered

The items required to be considered for the implementation of this project are shown below along with facts

found during this study project:

(1) Inclusion in local government budget

The discussions at the workshop and other occasions revealed that, having long been dependent on

development aid funding from foreign countries and international organizations, Indonesian local governments

are reluctant to purchase equipment with their own budget. Meanwhile, Gorontalo Province, which suffered

damage from the Palu Earthquake and tsunami, is considering its own measures through collaboration with

universities and appears positive about the project, regarding it not only as an anti-flood measure but also as a

measure for saving Lake Limboto from disappearance. Hence, we intend to stay in continuous contact with

Gorontalo Province to lead the Province into budgeting the purchase.

(2) Development of collaboration between related agencies

Both the BMKG Regional Monitoring Office and the provincial, regency, and city BPBD offices under the

National Disaster Management Authority (BNPB) are expected to operate weather radars. Nevertheless,

progress has been slow in developing an organizational framework for data sharing between the former and the

latter and cooperation therebetween in public awareness building activities. Established much later than the

BMKG, the BPBD is considered short of knowledgeable and experienced staff. Hence, the provincial and

central governments will be lobbied to ensure that the provincial government will move to develop collaboration

between the BMKG and the BPBD.

(3) Personnel development and training, etc.

The introductory training provided by the manufacturer and the distributor is far from sufficient for trainees

to achieve a skill level for making full use of the simulator and other equipment for disaster prevention activities.

Therefore, a long-term personnel development plan is necessary along with the budget therefor including the

cost of equipment maintenance by the local governments. It has turned out that the local governments currently

cannot easily afford to budget the purchase of the equipment alone. To enable continuous discussion and support,

we are considering, among other things, periodic visits by Gobel Group.

3-5. Environmental and social impacts associated with project implementation

The following were considered with respect to environmental and social impacts:

(1) Introduction of the radar(s)

Installation on a flat-ground site with easy access to electric power and telecommunications is assumed for

the case of introducing one or two X-band radars (see Section 2-3). In this case, there will be little environmental

27

impact because neither road construction nor tree-clearing for radar site preparation will be necessary. The

installation of the radar(s) and pylon(s) may make the landscape look slightly different than before to the eyes

of the residents around the candidate radar site(s). This, however, will not cause direct inconvenience to their

life. Hence, the resulting impacts on society will be slight, if any.

Another point to keep in mind is that no new environmental or social impacts will occur from the use of

BMKG-owned existing C-band radars. Accordingly, it is desirable to promote the development of a system that

allows the flood simulator to use monitoring data from the existing C-band radars.

(2) Introduction of the flood simulator

When the flood simulator is introduced, a stand-alone desktop PC (Introduction Plan 1a) or a server-type

machine (Introduction Plans 1b to 3) will be delivered to the BPBD Regency Office. There will be no new

environmental and social impacts to the outside. Nor will there be additional points to keep in mind.

28

4. Financial and economic feasibility

4-1. Project cost estimation

Tables 4-1 and 4-2 show the project costs and construction periods for the respective introduction plans.

Introduction Plan 1a proposes that the flood simulator be introduced as stand-alone equipment. This plan is

relatively inexpensive with a price tag of ¥15.4 million because no radar equipment, data server, or rainfall

prediction system is required. Moreover, the time required for introduction is as short as six months. Introduction

Plan 1b involves the introduction of a data server for weather radar data loading, a rainfall prediction system, and

other equipment. Hence, a specification change will occur, requiring the flood simulator to be converted into a

server type.

Table 4-1: Rough estimation of introduction cost for each introduction plan

Item Introduction Plan 1a Introduction Plan 1b Introduction Plan 2 Introduction Plan 3

Configuration - Flood simulator - Flood simulator

- Existing C-band radars

- Flood simulator

- One X-band radar

- Flood simulator

- Two X-band radars

Additional

infrastructure

- Flood simulator - Flood simulator

- Existing radar adjustment

software

- Data exchange server

- Rainfall prediction

system

- Flood simulator

- One X-band radar



system

- Flood simulator

- Two X-band radars



system

Project cost

¥15.4 million

<Breakdown>

- Manufacturing of

flood simulator: ¥11

million

- System design,

training, and

documents: ¥4.4

million

¥81.6 million

<Breakdown>

- Manufacturing of flood

simulator: ¥53 million

- Server and rainfall

prediction system

development: ¥22 million

- System design, training,

and documents: ¥6.6

million

¥530 million

<Breakdown>



- One radar introduced:

¥385 million


prediction system

development: ¥22

million

- Radar pylon

construction, radar

control room, electrical

work, etc.: ¥22 million

- System design,

training, and

documents: ¥48 million

¥970 million

<Breakdown>



- One radar introduced:

¥770 million


prediction system

development: ¥22

million

- Radar pylon

construction, radar

control room, electrical

work, etc.: ¥44 million

- System design,

training, and

documents: ¥81 million

Table 4-2: Project cost breakdown based on Infrastructure Introduction Plans (unit: ¥1,000)

Introdu

ction

plan

Total

project

cost

Flood

simulator

Radar

equipment

Data server

and rainfall

prediction

system

Civil

engineering

work cost

System design cost,

training cost,

document

preparation cost, etc.

Time required for

introduction

(incl. construction

period)

1a 15,400 11,000 - - - 4,400 6 months

1b 81,600 53,000 - 22,000 - 6,600 12 months

2 530,000 53,000 385,000 22,000 22,000 48,000 15 months

3 970,000 53,000 770,000 22,000 44,000 81,000 18 months

* Topographic data improvement cost to be separately charged

For additional information, the preparation cost of the input data to the flood simulator was estimated. As shown

in Table 4-3, three plans were considered for the input data; these plans range from one that uses low-accuracy

29

data available for free to a plan that requires high-accuracy data to be newly created in order to improve the

accuracy of simulations. As a result, the rough estimate for extra cost ranges from ¥3 million to ¥132 million as

shown in Table 4-4.

Table 4-3: Specifications for data preparation

Data item Plan 1: Spec. for existing data Plan 2: Spec. for newly prepared

data

Plan 3: Spec. for newly

prepared data

Map data

1/50,000-scale topographic

maps

50 cm-resolution ortho-photos

(equivalent to 1/10,000-scale maps)

15 cm-resolution ortho-

photos

(equivalent to 1/2,000-

scale maps)

Elevation

data

30-m mesh 5-m mesh 1-m mesh

River-related

data

Approx. 40 cross-sections for

full river reach

390 cross-sections for full river reach 781 cross-sections for full

river reach

Table 4-4: Data preparation cost (unit: ¥1,000)

Data

preparation

plan

Total extra

cost Map data Elevation data River-related data

Data

preparation

period

Plan 1 3,000

1,000

(BIG 1:50,000-scale

maps to be used)

1,000

(NASA’s SRTM to

be used)

1,000

(BWSS2’s longitudinal

and transverse cross-

section data to be used)

1 month

Plan 2 26,500

7,500

(off-the-shelf ortho-

photos to be

purchased)

2,500

(Off-the-shelf DTM

to be purchased)

16,500

(Longitudinal and cross-

sectional river surveys to

be newly performed)

8 months

Plan 3 132,000

22,000

(ortho-photos to be

newly taken)

77,000

(LiDAR survey to be

conducted)

33,000

(Longitudinal and cross-

sectional river surveys to

be newly performed)

12 months

* This table assumes the use of existing precipitation data, river water level data, land use data, and data on in-river structures.

4-2. Summary of the results of (preliminary) financial/economic analysis

On the basis of the infrastructure introduction plans presented in the last section, the cost-effectiveness of the

introduction was considered. The conclusion finds that at present, considerable difficulties are anticipated

regarding the introduction in accordance with Introduction Plan 2 or 3 because:

1) While the flood-prone population may be reduced from the current 178,614 persons to none as part of the

cost-effectiveness of the introduction, no significant monetary effects can be expected to result from

prevention of physical and economic damage.

2) The relevant local government still has a strong tendency to rely on ODA. The introduction of equipment

including the radar is difficult with the disaster preparedness budget of Gorontalo Regency.

Moreover, as observed above in 2-3(3) Weather radar-related survey results, the BMKG has already covered

nearly the whole area of Indonesia with weather radars. Hence, it would be difficult to persuade the BMKG to

spend Indonesia’s own budget to introduce new weather radars. Additionally, as revealed by the results of the fact-

finding mission, Gorontalo Province started to operate weather radars in 2012. Since then, these radars have been

30

in operation and are still relatively new. With a 150-km coverage radius including the drainage basin of Lake

Limboto, the Province has no problems with rainfall monitoring. It is difficult to find a decisive advantage in the

introduction of expensive X-band radars.

Meanwhile, the most inexpensive Introduction Plan 1a is such that the flood simulator will be used stand-alone

for disaster prevention education only. This plan will not lead to any further improvement of the flood warning

system, and the effect of the introduction will be limited. Therefore, Introduction Plan 1b shall be the top-priority

plan for infrastructure introduction under this study project. The results of detailed consideration are presented in

Chapter 5 and onwards.

(1) Prediction of the effect of the installation of the flood simulator

Consideration was given to the effect of the introduction of the flood simulator. As a basic premise, it must

be recognized that the flood simulator does not always provide a constant effect or benefit and that its damage

reduction effect will significantly vary depending on regionality or external forces such as rainfall and river

flow.

Flood vulnerability index evaluation was performed to estimate the size of the potential victim population of

a flood disaster and the amount of the potential economic damage caused thereby. According to BNPB’s Kajian

Risiko Bencana Gorontalo 2016-2020, the potential victim population of Gorontalo region/city can be estimated

to reach 178,614 persons, when assuming vulnerable-age, economically underprivileged, and physically or

mentally challenged groups as victim groups. Meanwhile, the amount of potential material or economic damage

from a flood disaster can be estimated to reach Rp 2.4257 trillion.

The flood simulator is intended for early evacuation of residents and is not intended to reduce damagesuch

as inundation damage to houses or farm lands or losses to economic activities. Therefore, the maximum effect

of the introduction of the flood simulator will be 178,614 lives, assuming that the above-mentioned personal

damage is reduced 100 percent.

(2) Funding feasibility consideration

The findings are as follows: The relevant local government still has a strong tendency to rely on ODA and

hence hopes for infrastructure introduction in the form of material/equipment provision at no cost or through a

yen loan; the disaster preparedness budget remains low and totals only about ¥430 million (2017), including

the amount budgeted to support recovery from the October 2016 Gorontalo Regency-Flood Disaster; and their

equipment introduction budgeting plan has yet to take shape.

31

5. Project implementation schedule

In Chapter 5 onwards, focus is placed on Introduction Plan 1 as presented in 4-1. Table 5-1 shows the schedule

towards the proposal for the introduction of the flood simulator. The Japanese fact-finding mission will continue

the implementation of the project until the end of the current fiscal year. From this coming fiscal year, preferably

after the completion of the study project, a local corporation knowledgeable about the flood simulator (negotiations

underway with several candidates) should take over and start lobbying the provinces of Sulawesi Island. Proposal

activities shall be promoted so that the introduction of the flood simulator will be in view by December 2019. It

is desired that the flood simulator be wedged into the procurement budgets of the provincial governments for FY

2020 to ensure the conclusion of the contract with them.

Table 5-1: Schedule towards the proposal for the introduction of the flood simulator

Period Description

Sept. 2018

(Implemented)

Data collection and on-site surveys for the demonstration version of the flood simulator for

Gorontalo Regency

Nov. 2018

(Implemented)

Presentation of the flood simulator and demonstrative simulations of typical floods at a

workshop and a seminar (two days) in Gorontalo Regency

- Audience: Gorontalo Regency Governor, representative of Gorontalo City BPBD,

disaster management officials of the regency government, and university academics

May 2019 Proposal to Gorontalo Province for export of the flood simulator

Aug. 2019 Start of an expanded feasibility study targeting the governments of Gorontalo, Middle

Sulawesi, and South Sulawesi Provinces in the eastern part of Indonesia

Sept. to Dec.

2019

Starting proposal activities in Indonesia, such as lobbying the above-mentioned provincial

governments into wedging a flood simulator introduction budget into their budget plan

32

6. Implementation competence of the implementation agencies of the counterpart country

6-1. Profile of the implementation agencies of the counterpart country

The flood simulator is intended for introduction to Gorontalo Province. In the case of Gorontalo Province, the

Gorontalo City BPBD (municipal disaster management office) will be responsible for the actual operation of the

flood prediction system. Figure 6-1 shows disaster management organizations at different administrative levels in

Indonesia. The national-level disaster management authority is the BNPB (National Disaster Management

Agency), while regional-level disaster management authorities are the BPBD Offices. The Indonesian Disaster

Management Law requires the government of each province (Provinci), regency (Kabupaten), and city (Kota) to

establish a disaster management office at their respective administrative level.

The input flood predictions data are data provided by the BMKG (Bureau of Meteorology, Climate and

Geophysics), such as ground and radar precipitation measurements, weather predictions, and weather warnings.

The BMKG consists of a head office in Jakarta, five regional headquarters offices, 120 weather stations, 31

seismological stations, and 22 climate change observatories. In Gorontalo Province, they have a weather station,

a seismological station, and a climate change observatory.

If successfully introduced to Gorontalo Province, the simulator will be rolled out to the Middle Sulawesi and

South Sulawesi Provinces, which are also located on Sulawesi Island.

Figure 6-1: Disaster management organizations at different administrative levels in Indonesia

6-2. Organizational framework for project implementation in the counterpart country

The organizations under the BPBD are in place according to the National Disaster Management Agency

Director-General’s Directive No.3/2008 “Guidelines for Establishing Regional Disaster Management Offices.”

The organizational structure is the same at the provincial, regency, and municipal levels. In addition to the BPBD

Director and the Secretariat, there are the following three different working-level departments: (1) Department of

Preventive Measures (damage prevention and mitigation); (2) Emergency Response Department; and (3) Recovery

and Reconstruction Department. The Department of Preventive Measures is responsible for, among other things,

hazard map development, regional disaster management planning, and warning issuance and information

BMKG

Weather Warning

Information

33

dissemination to areas under its jurisdiction. This department is expected to be responsible for the actual operation

and maintenance of the flood prediction system. In the Gorontalo Provincial government, the Meteorological

Bureau (BMKG) in charge of weather radars coexists with Regional Disaster Management Offices (BPBD). In

practice, however, the former and the latter are yet to work in good coordination with each other.

6-3. Competence evaluation of the implementation agencies of the counterpart country and

countermeasures

From the results of the hearing during the fourth mission to Jakarta, it turned out that weather monitoring,

forecasting, and warnings are the responsibility of the BMKG, while disaster prevention education and disaster

response are provided by the BNPB/BPBD. This suggests that the flood prediction system may be introduced to

the respective agencies. Accordingly, this section presents the competence evaluation of the BNPB/BPBD and

BMKG and the measures to be taken.

In Indonesia, to avoid overlap among preventive measures or confusion during emergency response, regional

agencies specializing in disaster management are in place in addition to the central (national) one. In practice,

however, the BNPB, which is above the BPBD in the organizational hierarchy, has among its staff many new

personnel who are from other ministries and agencies and ill-versed in disaster management. Thus, the BNPB is

not ready and able to provide sufficient support to localities. Similarly, provincial, regency, and municipal BPBD

offices are seriously understaffed, under-budgeted, and insufficiently competent in disaster management. Naturally,

the BNPB is expected to provide continuous guidance. As stated above, however, the BNPB cannot afford to

extend support to localities. Moreover, during and after the Palu Earthquake Tsunami Disaster, which occurred in

the central region of Sulawesi Island on September 28, 2018, the central government were forced to take frontline

command. This is partly responsible for the stagnation in preventive measure activities. For the implementation

of this project, it is a matter of urgency that the BPBD, the prospective operator of the flood prediction system,

should enhance disaster preparedness, including preventive measure activities.

The BMKG can make weather predictions using numerical forecasting models. As can be seen from the

variations in monitoring data accuracy between its permanently and non-permanently manned weather stations,

the BMKG still remains unable to provide sufficient maintenance to its weather stations or proper quality control

of monitoring data. In addition, the BMKG has only a limited number of personnel capable of correctly judging

the validity of weather prediction results or the appropriateness of issuing weather watches or warnings. Regional

BMKG offices are also understaffed and under-budgeted, but at an even more severe level than the BPBD.

What we should do to grasp the opportunity for flood prediction system introduction is to lobby the Gorontalo

Provincial government into organizing a mobile disaster management team and promoting coordination between

the BMKG responsible for C-band radar operation and the BPBD responsible for warning information

dissemination. Additionally, through Gobel Group, our local counterpart, we will present the BNPB/BPBD and

the BMKG with a proposal for a capacity building program for providing flood simulator training as detailed in

Table 6-1. With hands-on access to the flood prediction system, the personnel of the respective local agencies

would become able to perform disaster prevention activities more effectively. The introduction of the state-of-the-

art technology would be effective in enhancing the motivation of the staff.

34

Table 6-1: Details of flood simulator training (BNPB/BPBD and BMKG)

No Description

BNPB HQ/

Regional

BPBD

BMKG

HQ

(1) Outline of the flood simulator ○ ○

(2) Installing the flood simulator ○ ○

(3)

Operating the flood simulator (setting the conditions for river

infrastructure such as embankment; and making a flood prediction,

using observed and predicted precipitation data as input values)

○ ○

(4) Creating a flood hazard map using the results of a flood prediction ○

(5)

Developing a river infrastructure improvement plan based on the

results of a preliminary simulation with the inclusion of river

infrastructure settings

○

(6) Developing a regional disaster preparedness plan based on the results

of a flood prediction ○

(7) Converting weather radar monitoring data or weather prediction data

into precipitation input data to flood simulator ○

(8) Issuing a flood watch or warning based on the results of a flood

prediction ○

* Introduction Plan 1a in Table 4-1 intended for BNPB HQ/Regional BPBD while Introduction Plan 1b for

BMKG HQ

35

7. Competitive advantages of Japanese enterprises in terms of technology and other aspects

7-1. International competitiveness of Japanese enterprises in project bidding (by

equipment/product/service) and probability of winning orders

(1) International competitiveness of “Japan-made Flood-Simulator”

Table 7-1 shows the results of a comparison of the flood simulator “Japan-made Flood-Simulator” with

domestic and foreign competing technologies equipped with similar functions. “Japan-made Flood-Simulator”

has the following three competitive advantages:

Table 7-1: Comparison of flood simulators (1)

1. Technology to be

proposed

“Japan-made Flood-

Simulator”

2. Competing technology

Flood-Simulator overseas-

made, A



made, B

Image of

product/techno

logy

Year released 2006 2008 1960

Characteristics

(advantages

and

disadvantages)

Vertical integration system for

professional use, specially

designed for hazard map

development and river water

level prediction. Allows the

user to specify simulation

conditions, create hazard maps

based on diverse conditions,

and develop the resulting

maps into a river water

level/inundated area prediction

system.

Allows automatic collection of

geographic information data,

land use data, and satellite-

monitored rainfall data and their

application to calculation of

river flow rates, etc.

Vertical integration system for

professional use, specially

designed for hazard map


level prediction. Allows the user

to specify simulation conditions,

create hazard maps based on

diverse conditions, and develop

the resulting maps into a river

water level/inundated area

prediction system.

Technological

category

Large category: water budget

software

Small category: hazard map


level prediction


software

Small category: river water level

prediction


software

Small category: riverbed

fluctuation simulation, etc.

Price

(unit price)

Software: ¥3,000,000 and up

Annual maintenance cost:

¥150,000 and up

* Japanese domestic version

Software: ¥0

Annual maintenance cost: ¥0

Software: approx. ¥3,000,000

and up

Annual maintenance cost:

(unknown)

Table 7-1: Comparison of flood simulators (2)

5分経 15分経洪水直

(a) Highly user-friendly, allowing non-specialist users to intuitively run simulations based on various

conditions and settings;

(b) High functionality and convenience that allow high-speed computational processing and real-time

representation of prediction results in 4D-GIS; and

(c) Excellent operability and extensibility that allow organic coordination with precipitation data or

related equipment, such as river water level telemetry gauges, and seamlessly enable future

predictions of river water levels/inundated locations.

36

1. Technology to be proposed

“Japan-made Flood-Simulator”



made, A



made, B

Function (1)

Flood

calculation

function

Capable of 2D-flood

calculations

(Equipped with high-speed

calculation function)

No function Capable of 2D-flood

calculations

(No high-speed calculation

function)

Function (2)

Calculation

results

display

Capable of displaying results

on maps

Interfacing with other systems

such as non-commercial 2D-GIS

is required in order to display

results on maps.


such as commercial 2D-GIS is

required in order to display

results on maps.

Function (3)

Setting and

editing of

calculation

conditions

Allows the user to set and edit

calculation conditions on 4D-

GIS.

Allows the user to set and edit

calculation conditions on 2D-

GIS.


such as commercial 2D-GIS is

required in order to use on-

screen support.

Function (4)

River water

level

prediction

by coupled

simulation

Possible

Function (5)

Creation of

flooded

areas

envelopes

Possible with a one click Not supported by the software

Cost-

efficiency

Initial cost: ¥3,600,000 and up Initial cost: ¥0 Initial cost: approx. 3,000,000

and up

User-

friendliness

Usable by non-specialist users Intended for specialist users Intended for specialist users

Durability There is no wear from using the software.

Safety There is no danger resulting from use of the software.

Environment

-friendliness

Extremely low in power consumption. No environmental impact results from the use of the software.

Market

share in

Japan

No objective research data available

Overseas

market share

No objective research data available

Special

remarks

None None None

Table 7-2 shows the list of patents and awards granted to “Japan-made Flood-Simulator.”

Table 7-2: Patents and awards granted to “Japan-made Flood-Simulator”

Category Evaluation

Patents granted

Japanese patents: 4431545, 4761865, 4959346, 4979322, 5026992,

5337995, 5403726, 5531365, 5873941

US patents: 7603263, 7957945

Chinese patents: PZL200610008661.4, PZL200710089468.2

Moreover, “Japan-made Flood-Simulator” has a proven track record of introduction to flood-disaster prone

Vietnam (FY 2013 Private-Sector Technology Promotion Project for Socio-Economic Development of

37

Developing Countries - ICT-Based Sustainable Disaster Prevention/Reduction System Promotion Project,

JICA). “Japan-made Flood-Simulator” is valued as useful for improving the disaster response capabilities of

local disaster management personnel. It is considered that the current demonstrative proposal, together with the

eventual development of a disaster prevention information sharing platform as shown in Figure 7-1, is necessary

to improve the disaster preparedness of counterpart countries including Indonesia. It can be concluded that such

a platform will have an international competitive edge with the inclusion of “Japan-made Flood-Simulator” as

its core product.

情報収集元 Sources of information to be collected

気象情報 Weather information

予測雨量情報 Predicted precipitation information

実測雨量情報 Measured precipitation information

水文ステーション Hydrological stations

河川水位 River water levels

・降雨量 • Rainfall amounts

漁船 Fishing boats

漁船位置情報 Fishing vessel position information

監視カメラ映像 Surveillance camera videos

河川・洪水画像 River/flood images

住民 Residents

職員 Employees

被害、対策状況報告 Damage and response status reports

他行政機関、関係組織など Other administrative agencies, related organizations, etc.

情報連携 Information sharing

防災情報共有プラットフォーム Disaster prevention information sharing platform

電気、ガス、水道被災状況 Damage status of power, gas, and water lines

公共インフラ会社など Public utility companies, etc.

リアルタイム情報収集・表示・配信システム Real-time information collection, display, and distribution system

洪水シミュレーション Flood simulations

シミュレーション結果情報 Simulation results information

情報配信先 Information distribution destinations

災害情報 Disaster information

避難勧告 Evacuation advice

38

住民（スピーカ） Residents (speakers)

住民（スマホ） Residents (smart phones)

洪水警告通知 Flood warning notification

職員 Employees

Figure 7-1: Conceptual-image of flood simulation-based disaster information sharing platform

(2) Probability of winning orders for “Japan-made Flood-Simulator”

It is estimated that the probability of winning an order will be quite high if we continue lobbying the

Gorontalo Regency government until December 2019, and if as a result the budget for flood simulator

introduction is wedged into the Regency’s fiscal 2020 procurement budget. In addition, seeing the actual

occurrence of a severe earthquake and tsunami damage to Palu in Middle Sulawesi Province, and currently, the

governments of the provinces in Sulawesi Island are strongly interested in disaster management. Hence, Japan’s

experience in the field of disaster management may improve the chance of system sales compared to other

donor countries.

From now on, we intend to start a strong promotional campaign targeting the governments of Gorontalo

and South Sulawesi Provinces neighboring Middle Sulawesi Province on the superiority of Japanese disaster

management technology so that we will stand a better chance of winning orders for “Japan-made Flood-

Simulator.”

7-2. Descriptions and prices of the main materials and equipment expected to be procured from Japan

The assumption is that all materials and equipment necessary for the implementation of the project will be

procured from Japan. Table 7-3 shows the descriptions and prices of the main materials and equipment expected

to be procured from Japan according to Introduction Plan 1. Similarly, Table 7-4 shows the descriptions and prices

of the flood simulator-related items included in Introduction Plan 1b, whose rainfall prediction system-related

portions appear in Table 7-5.

Table 7-3: Main materials, equipment and prices expected to be procured from Japan according to Introduction

Plan 1a

Item Description Cost (before tax) Remarks

Software “Japan-made Flood-Simulator” /Flood

Professional Edition ¥11,000,000

Inclusive of spec PC*

Operator training Cost of the three-day operator training to

be provided in Indonesia ¥3,400,000

Delivery to be made

through NSI

Annual maintenance Annual technical support service via e-mail

(Approx. 20 times per year) ¥1,000,000

* OS - Microsoft® Windows® 7, 8.1, or 10, 64-bit; CPU - Intel® Core™ i5 or higher compatible processor (Intel® Core™ i7

recommended); Memory - 2 GB or more; HDD -100 GB or more free space; Graphics memory - 128 MB or more recommended;

USB terminal - 1 or 2 USB ports required for license key validation

Note: The models of the relevant rivers are not included. If these must be delivered, their development must be ordered at separate

cost.

39


Plan 1b

Item Description Cost (before tax) Remarks

Hardware Server × 2 units ¥4,700,000 One for backup in

case of failure NAS × 2 units ¥400,000

Client × 1 unit ¥250,000

UPS ¥300,000

Rack-related ¥757,000

Peripheral devices (HUB, etc.) ¥30,000

Software “Japan-made Flood-Simulator” /Flood

Enterprise Edition ¥17,000,000

Client software ¥2,500,000 For results display

Model

development

(*1)

Bolango River, Bone River, Alo River,

etc.

¥8,000,000

SE cost Server construction,

on-site commissioning, and

system adjustments (data collection) ¥15,570,000

Sundry

expenses

Transportation costs, travel costs, and

administrative costs ¥3,500,000

Annual

maintenance

(*2)

Annual technical support service via e-mail

(Approx. 20 times per year)

¥2,000,000

Delivery to be

made through NSI

* 1: For detailed information on the hardware, see the list of hardware separately attached.

* 2: The period of the system operation and maintenance contract is one year.


Plan 1b (rainfall prediction system-related)

Item Description Cost (before

tax)

Remarks

Hardware

Server for radar data processing × 1 unit (*1) ¥500,000

Server for numerical rainfall prediction × 1 unit (*1) ¥500,000

System

construction

Radar data conversion system ¥9,000,000 Creation of input

data to flood

simulator rainfall prediction system ¥9,000,000

SE cost Network construction and on-site system adjustment ¥2,000,000

Sundry

expenses

Transportation costs, travel costs, and administrative

costs ¥1,000,000

* 1: Tower type, Linux OS, Xeon 6 core or higher, and HDD free space of 3 TB

40

7-3. Measures necessary to help Japanese enterprises to win orders

As was seen in the 60th diplomatic relations establishment anniversary held in 2017, Panasonic and Gobel

Group play a large role in the Japan-Indonesia relationship. Therefore, an effective infrastructure introduction

scheme would be one coordinated through Mr. Rachmat Gobel, the Chairman of the Gobel Group, or through

economic and political circles associated with him. Incidentally, the flood simulator was recommended for the

first time to Gorontalo Province, home to Mr. Gobel. It should be noted, however, that Indonesia has long been

receiving ODA, World Bank’s funds, etc., to promote its infrastructure improvement; and there are many asking

about the possibility of introduction through ODA of Government of Japan. To help secure orders, the provincial

government must be lobbied, with cooperation from Mr. Gobel, to consider introducing a disaster prevention

system based on BMKG-BPBD collaboration, and proposal activities will be continued to ensure budget allocation

for that system.

Furthermore, focus should not be placed exclusively on simulator-based flood disaster mitigation. Other disaster

management components should also be included in the package to cover earthquakes, tsunamis, volcanic

eruptions, and so on. It will be important to form a Team Japan and make joint efforts to export technologically-

driven disaster management infrastructure in collaboration with JICA, the lead player in the Palu Emergency

Support Scheme.

Also considered effective is lobbying the Regency Governor, the final decision-maker on the purchase, jointly

with the Japanese Embassy, JICA Indonesia Office, and MITI’s staff stationed in Indonesia. Considering the

schedule and budget, it is difficult to make frequent visits to Sulawesi. Therefore, it is planned to keep visiting the

Regency Governor, with cooperation from Gobel Group, at an approximate frequency of once every two to three

months.

41

8. Prospects of fund procurement for the project

8-1. Views of the counterpart country’s government and agencies on fund procurement

As shown in Table 8-1, three methods of fund procurement are under consideration for the implementation of

this project.

As stated in 4-2(2), the likelihood of approval of a yen loan request can be judged low because the loan amount

to be requested will be too small unless the introduction plan includes radars or unless more than one simulator is

introduced at the same time.

Table 8-1: Prospective sources of fund procurement

Item Name of fund Name of

government/agency

Descriptions

Fund 1 Gorontalo Regency

government budget

Gorontalo Regency Gorontalo Regency’s budget (APBD II)

Fund 2

Green Climate Fund (GCF) GCF International fund for supporting the efforts

of developing countries to prevent, reduce,

or absorb (alleviate) GHG emissions and

adapt to climate change effects

Fund 3

Project or Programme

Funding from the

Adaptation Fund

The Adaptation

Fund (AF)

Funding provided to projects or programs

for supporting adaptation of vulnerable

communities in developing countries to

climate change

Option

Project for Supporting the

Development and

Implementation of

Reconstruction Plans for

Middle Sulawesi Province,

Indonesia

JICA JICA technical cooperation project for

developing various reconstruction plans and

supporting their implementation according

to the Basic Reconstruction Plan developed

jointly with the Indonesian Ministry of

National Development Planning

(BAPPENAS)

8-2. Movements of related agencies with regards to fund procurement

Through this study project, discussions are underway with Gorontalo Regency Governor and other interested

parties regarding how to procure funding in the form of Fund 1 “Gorontalo Regency government budget.” We are

aiming to win budget allocation from the Regency’s fiscal 2020 budget.

The total amount of declared donations from developed and developing countries (a total of 43 countries) to

Fund 2 “Green Climate Fund (GCF)” is approximately US$ 10.3 billion, which includes US$ 1.5 billion (approx.

¥154 billion) from Japan. So far, the GCF has granted US$ 1.63 billion to support 93 projects (as of January 2019).

Projects are classified by size into the following four levels: micro-scale projects with a total project cost of US$ 10

million or less; small-scale projects with a total project cost of between US$ 10 and 50 million; medium-scale

projects with a total project cost of between US$ 50 and 250 million; and large-scale projects with a total project

42

cost of over US$ 250 million. If GCF money is made available, our project will be able to introduce C-band radars

as well.

国家指定期間 national designated agency

コーディネート coordinate

監督 supervise

理事会 administrative board

事務局 secretariat

申請 application

資金 fund

ダイレクト・アクセス機関 direct access institute

国際アクセス機関 international access institute

案件形成 project forming

贈与／融資／保証／出資 bestowal／loan／guarantee／financial contribution

プロジェクト／プログラム project／program

民間セクター＆その他関係機関 private sector & other concerned institute

Figure 8-1: Overview of the utilization of GCF funding

Source: MoE “About the Green Climate Fund” (https://www.env.go.jp/earth/ondanka/gcf.html)

Fund 3 “Project or Programme Funding from the Adaptation Fund” is a scheme recommended from the

Indonesian side during this study project. The Adaptation Fund provides financial support for projects or programs

for supporting adaptation of vulnerable communities in developing countries to climate change. Since 2010, the

Adaptation Fund has provided US$ 532 million to 80 adaptation projects (as of February 2019). The Adaptation

Fund is financed with contributions from governmental and private-sector donors and with a 2-percent share of

proceeds from the clean development mechanism (CDM) project activities. The eligible areas of adaptation

projects are as follows: agricultural and coastal land management; disaster risk reduction; food security; forestry;

interdisciplinary projects; rural and urban development; and water resources management.

We intend to ask and check with the relevant agencies about the eligibility of this project for financial support

from the Adaptation Fund.

The Option “Project for Supporting the Development and Implementation of Reconstruction Plans for Middle

Sulawesi Province, Indonesia” is a JICA technical cooperation project aiming to support the reconstruction of the

central region of Sulawesi Island, Indonesia. For this project, a dedicated consultation office was established in

43

Palu, Middle Sulawesi Province, in January 2019. Through a five-party consortium formed by Yachiyo

Engineering Co., Ltd., Oriental Consultants Global Co., Ltd., Nippon Koei Co., Ltd., Pacific Consultants Co., Ltd.,

and Pasco Corporation, this project will implement the following activities, among others: disaster risk

assessment; hazard map development; spatial plan development; disaster resilience enhancement of infrastructure

and public facilities; and livelihood rehabilitation assistance for survivors.

8-3. Prospects of project-related fund procurement, the current status of requests for yen loan, and the

likelihood of its approval

In this research project, Gorontalo Regency government has been lobbied through Gobel Group for budget

allocation. At present, however, there is no positive sign regarding Fund 1 “Gorontalo Regency government

budget.” Aiming to win budget allocation from the Regency’s fiscal 2020 budget, we intend to explore continuous

approaches in fiscal 2019 while also exploring the possibilities of winning orders for ongoing extended projects

from METI.

Preparation is underway for a cross-cutting proposal to Fund 2 “Green Climate Fund (GCF)” for funding for

the combination of the REDD+ project (alleviation) promoted by Kanematsu Corporation jointly with Gorontalo

Province and this project (adaptation). The GCF sets a “50-50 fund allocation to alleviation and adaptation” as the

target to be achieved. This makes it all the more likely that the GCF will adopt cross-cutting proposals for

alleviation-adaptation combination projects. Accordingly, this project is also combined with another into a cross-

cutting proposal to stand a better chance of winning funding.

With regards to Fund 3 “Project or Programme Funding from the Adaptation Fund,” we intend to ask and check

with the relevant agencies about the eligibility of this project for financial support from the Adaptation Fund. The

possibility of us winning funding is unknown.

44

9. Challenges and action plan towards the realization of the project

9-1. Progress in fund procurement efforts including requests for UN-GCF and yen loan

In this study project, a lobbying campaign targeting Gorontalo Regency government has been promoted through

Gobel Group as an effort to procure funding in the form of Fund 1 “Gorontalo Regency government budget.”

As an effort to procure funding in the form of Fund 2 “Green Climate Fund (GCF),” concept note preparation

is underway. The concept note is a document prepared optionally by accredited entities prior to submission of a

proposal for a project. In return for its submission to the GCF Secretariat, feedback and advice will be received.

Meanwhile, selection of an accredited entity (AE) is also underway for this project. A proposal to the GCF must

be submitted through an AE. What makes the GCF unique is that the eligibility to become an AE is not limited to

international organizations and governmental agencies but extends to private financial institutions or non-

governmental organizations (NGOs). In Japan, JICA and Tokyo Mitsubishi UFJ Bank have become AEs (as the

end of March 2018). AE selection is currently underway from two candidates, one of which is JICA while the

other is PT Sarana Multi Infrastruktur (Persero) (a.k.a.: PT SMi), an Indonesian AE.

Assuming that there continue to be open bid opportunities for Fund 3 “Project or Programme Funding from the

Adaptation Fund,” the information to be provided in the proposal is undergoing close scrutiny.

9-2. Measures expected to be necessary for future funding requests for and provision of UN-GCF, yen loan,

etc.

Aiming to win budget allocation from Fund 1 "Gorontalo Regency government budget" for fiscal 2020, we

intend to explore continuous approaches in fiscal 2019 while also exploring the possibilities of winning orders for

ongoing extended projects from METI. While doing so, departments and organizations expected to use “Japan-

made Flood-Simulator” must be identified. At the same time, capacity building of operators will also be necessary.

With regards to Fund 2 “Green Climate Fund (GCF),” AE selection and scrutiny of the content of the concept

note will be initiated upon the completion of the concept note. Along with the scrutiny, it will also be necessary

to consider the modalities of GCF funding support (Table 9-1) and specification approval for the Japanese

technologies and products discussed in this study project.

Moreover, a proposal to the GCF must be submitted with the attachment of a Non Objection Letter issued by

the national designated authority (NDA) of the project-implementing country. In the case of Indonesia, the NDA

is the Ministry of Finance. In the past, Kanematsu has received support for an REDD+ project from the Ministry

of Environment and Forestry. Exploiting this experience, we must receive support from the Ministry of

Environment and Forestry and Gobel Group in order to obtain the Non Objection Letter from the Ministry of

Finance.

45

Table 9-1: Modalities of GCF funding support

Assistance to public sector Assistance to private

sector

Grant 〇〇

Loan aid

〇

〇 (Conditions variable

depending on project)

High-concessionality Low-concessionality

Period 40 years 20 years

Grace period 10 years 5 years

Capital repayment

rate (% of initial

principal)

(11th-20th years) 2%

(21st-40th years) 4%

(6th-20th years) 6.70%

(21st-40th years) N/A

Interest rate 0.25% 0.75%

Commitment fee 0.75% 0.75%

Guarantee 〇 (Conditions variable depending on project) 〇 (Conditions variable


Investment

(equity) ×

〇 (Conditions variable


With regards to Fund 3 “Project or Programme Funding from the Adaptation Fund,” we intend to ask and check

with the relevant agencies about the eligibility of this project for financial support from the Adaptation Fund.

During the process, necessary measures will be taken.

9-3. Specific challenges and action plan towards submission of funding requests for UN-GCF funds, yen

loans, etc.; and other issues including horizontal deployment to other countries

To procure funding in the form of Fund 1 “Gorontalo Regency government budget,” the intention of Gorontalo

Regency Governor is important in the first place. The Governor has already shown a strong interest in introducing

“Japan-made Flood-Simulator.” This is because Gorontalo Regency is frequently hit by floods, partly due to

climate change, and disaster risks are increasing, posing a threat to life in its community. So, a continuous lobbying

campaign must be mounted to have a “Japan-made Flood-Simulator” procurement budget wedged into the

Regency’s fiscal 2020 budget. Consideration should also be given to turning the introduction of “Japan-made

Flood-Simulator” into an established fact by starting basic capacity building ahead of the introduction of “Japan-

made Flood-Simulator” in order to facilitate the budgeting of its introduction.

To procure funding in the form of Fund 2 “Green Climate Fund (GCF),” the content of the concept note does

matter. Accordingly, Kanematsu Corporation intends to complete a concept note in collaboration with Gobel

Group. Its content will be explained to related parties for feedback, based on which the concept note will be

modified as necessary and then will be formally submitted to the GCF for technical evaluation.

To procure funding in the form of Fund 3 “Project or Programme Funding from the Adaptation Fund,”

information on the next bidding opportunity must be obtained as early as possible to make preparations towards

46

adoption simultaneously with preparation for application to the GCF.

With regards to the Option “Project for Supporting the Development and Implementation of Reconstruction

Plans for Middle Sulawesi Province, Indonesia,” Pasco Corporation will act as a go-between for us to approach

the Consortium and JICA about the introduction of “Japan-made Flood-Simulator.” During the process, necessary

measures will be taken.

Horizontal deployment would be targeted at, among other countries, Vietnam and Thailand. In both countries,

frequent floods due to causes such as typhoons are social headaches and there is expected to be high need for

introducing “Japan-made Flood-Simulator” and even weather radars as well. With regards to Vietnam in particular,

as stated in 7-1, “Japan-made Flood-Simulator” has a proven track record of introduction (FY 2013 Private-Sector

Technology Promotion Project for Socio-Economic Development of Developing Countries - ICT-Based

Sustainable Disaster Prevention/Reduction System Promotion Project, JICA). This suggests a high probability of

successful horizontal deployment to Vietnam.

（様式２）

頁図表番号

31 Table 4-1

31 Table 4-2

32 Table 4-332 Table 4-4

43 Table 7-3

43 Table 7-4

44 Table 7-5

Main materials, equipment and pricesexpected to be procured from Japan accordingto Introduction Plan 1bMain materials, equipment and pricesexpected to be procured from Japan accordingto Introduction Plan 1b (rainfall predictionsystem-related)

二次利用未承諾リスト

委託事業名FY 2018 Operational FeasibilityStudy Project towards OverseasDeployment of High-QualityInfrastructure

報告書の題名FY 2018 Operational FeasibilityStudy Project towards OverseasDeployment of High-QualityInfrastructure(Republic of Indonesia: FeasibilityStudy Project for Flood DisasterPreparedness Planning Assuming theUse of Flood Simulator and WeatherRadar in the Province of Gorontalo)Study Report

受注事業者名Kanematsu CorporationJapan Weather Association

Main materials, equipment and pricesexpected to be procured from Japan accordingto Introduction Plan 1a

タイトルRough estimation of introduction cost foreach introduction planProject cost breakdown based onInfrastructure Introduction Plans (unit:\1,000; 1US$ = \110)Specifications for data preparationData preparation cost (unit: \1,000)

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