Final Country Report - Climate Change

8/6/2019 Final Country Report - Climate Change

1/79

INDONESIA COUNTRY REPORT

CLIMATE VARIABILITY AND

CLIMATE CHANGES, AND THEIR

IMPLICATION

GOVERNMENT OF REPUBLIC OF INDONESIA

JAKARTA

2007


2/79

INDONESIA COUNTRY REPORT

CLIMATE VARIABILITY AND

CLIMATE CHANGES, AND THEIR

IMPLICATION

GOVERNMENT OF REPUBLIC OF INDONESIA

JAKARTA

2007


3/79

ii

Published by:

Ministry of EnvironmentRepublic of IndonesiaJl. D. I. Panjaitan Kav. 24

Jakarta Timur 13410Indonesia

Ministry of Environment, 2007

Any part of this publication may be produced and quoted with a proper quotationsuggested below.

Suggested Quotation:

MoE. 2007. Indonesia Country Report: Climate Variability and Climate Change,

and their Implication. Ministry of Environment, Republic of Indonesia, Jakarta.

A catalog record of this publication is available from Perpustakaan Nasional

Indonesia.

ISBN: 978-979-8362-92-7

Coordinating Lead Authors:

Rizaldi Boer, Sutardi and Dadang Hilman


4/79

iii

FOREWORD FROM

NATIONAL FOCAL POINT TO THE UNFCCC

The Intergovernmental Panel on Climate Change (IPCC) concludes that globalwarming over the past 50 years was mainly caused by human activities that have

increased atmospheric concentrations of greenhouse gases. Over recent years, it isquite clear that the El Nio events have become more frequent as the global

temperature anomalies associated with each El Nio continue to increase. Thismeans that the extreme regional weather and climate anomalies associated with El

Nio are being exacerbated by increasingly higher temperatures.

Extreme weather and climate events cause serious floods, drought and wild fires in

Indonesia. Many reports showed that these events have caused serious impact onIndonesian economy and human living. Wild fire occurred in El-Nino 1997 has

caused huge economic loss and damaged peoples livelihoods increasing povertyrates by one-third or more. Drought occurred in 1972 has also impacted millions of

people. Flood occurred in early February 2007 which lasted for about 22 days alsoaffected thousands of people and destroyed about 1,500 houses. Flood hazards have

become common in many part of Indonesia regions. In the period 2001-04, about

530 floods were reported, occurring in almost all provinces. The scale of damage is

also increasing.

This country report describes impact of climate variability and climate change on

various sectors in Indonesia and be considered as one of official document ofGovernment of Indonesia that contains the most updated information related to

climate variability and climate change. Part of this report has been presented in theInternational Workshop on Water and Climate on 23-24 May 2007 at HotelKemang, Jakarta which was organized by the State Ministry of Environment and the

Ministry of Public Works of Republic of Indonesia supported by the Dutch

government and in partnership with among others, i.e. Partners for Water(Netherlands), Wetlands International, World Bank, UNESCO and WMO.

This report has been prepared with support from many agencies. On behalf of theGovernment of Indonesia I would like to welcome and endorse this report to wider

audience. Feedback and comments will definitely be appreciated in order to improveand updated this report in the future. Let me take this opportunity to extend my

sincere gratitude and thanks to authors, reviewers, contributors of this report, whohave made the publication possible.

Special thanks are extended to Ton Bresser from UNESCO-

IHE Institute for Water Education, BertJan Heij from Netherlands EnvironmentalAssessment Agency and Hank van Schaik from Co-operative Programme on Water

and Climate who have assisted in editing this report. Acknowledgement alsoextended to Bayu Krisnamurti, R.W. Triweko, Guy Alaerts, Raymond Kemur, andJan Verhagen who have provided written comments and inputs for the improvement

of the report, and to all participants of the Joint International Water and ClimateWorkshop for their valuable comments. Finally, our appreciation to the United


5/79

iv

Nations Development Program (UNDP) who has provided fully support in the

process of finalizing and producing the report.

Finally, it is hoped that this report can be one of references showing to the global

community how climate variability and climate change has impacted developingcountries and what would be the implication if no serious efforts are taken from now

to adapt to climate change.

Jakarta, December 2007

Masnellyarti Hilman

Deputy Minister III for the Minister of Environment

National Focal Point to the UNFCCC


6/79

v

FOREWORD FROM THE

Ministry of Environment, Republic of Indonesia

Understanding the historical interactions between society and climate hazards,

including adaptations that have evolved to cope with these hazards is a critical firststep in developing adaptations to manage future climate risks. Past experiences and

lessons learned in addressing climate risks need to be documented as thisinformation is important in developing successful adaptation strategies to climate

change. Adaptation will be more successful if it accounts for both current and futureclimate risks. Even if future adaptation strategies would need to be very differentfrom those currently in use, todays adaptation strategies will allow us to refine the

approaches needed in the future. Starting with adaptation to current climatevariability with building in additional safety margins for future climate changes is a

cost-effective and no regrets approach.

Long historical climate data record as well as reliable information on impacts of pastand present variable climates is essential for developing adaptation plans. Studiesand analysis to understand how the current system behaves to past and present

climate variability and what changes should be done and planned to the system to

increase the coping range of the system to future climate, are the urgent actions indeveloping the adaptation programs.

This country report is one of important references that provide information onimpact of climate variability and climate change on a number of major sectors in

Indonesia.

Last but not least, I hope this report can provide a glance how climate variability has

impacted Indonesia and how future climate may look like and its implication on

sectors. And the information contained in this report could meet our current needson information based on scientific activities that is still lacking in this country.


Minister of Environment,

Republic of Indonesia

Rachmat Witoelar


7/79

vi

FOREWORD FROM THE

Ministry of Public Works, Republic of Indonesia

Water is fundamental to human well-being, socio-economic development and thehealthy evolution of ecosystems. In many countries, including Indonesia, water

access and management is a constant challenge. Climate variability and/or climatechange is likely to pose an additional burden on water resources and their

management, especially in areas where water resources are already under stress dueto meteorological and upper-watershed conditions and demand pressure from

society. Increased intensity and frequency of storms, drought and flooding, alteredhydrological cycles and precipitation variance have implications for future wateravailability for various uses and sectors, i.e., water supply, agriculture, human

health, human settlements, industry, hydro power, fishery, tourism, environmental,etc. In addition to that, the increased of number infrastructure and property damages

as well as human injured and loss due to water related disasters are observed for thelast ten years. To address these challenges and adapt water management to changing

climatic conditions, it is necessary to ensure that the current meteorological trendsand information on the future water availability and demands are taken into accountin the process of water resources management and policy development. This

information ideally should be synthesized in a country report.

This country report which was developed by the Inter-sectoral Working Group thatwas formed by The Minister of Public Works Decree No: 239/KPTS/M/2007, dated27 April 2007 was intended to be a reference document that provide information on

the extend of climate hazards, their impacts and their trends of impact in the futureto related sectors for the participants of the Joint International Water and Climate

Workshop in May 2007 in Jakarta. During the workshop the country report waspresented in order to receive comments and inputs for its improvement. The finalversion of the country report which already have accommodated most of the

comments and the inputs for improvement and finalized through intensive

discussion within the Inter-sectoral Working Group is intended to be a formalreference document on the impacts of climate change and adaptation measures in

coping with climate change on the water sector and this document will be up datedin each two (2) years in order to accommodate the recent development of the currentmeteorological trends and their adaptation measures.

I hope this country report will serve as a complementary document for the NationalAction Plan for Mitigation and Adaptation to Climate Change (RAN-MAPI) and

also for inputs on the development the Second National Communication forMitigation and Adaptation for climate change.


Minister of Public Works

Republic of Indonesia

Djoko Kirmanto


8/79

vii

CONTENTS

Preface (Acknowledgement)

Content

List of Tables

List of FiguresForeword from the Ministry of Environment

Foreword from the Ministry of Public Work

I. Introduction 1

II. Climate Hazards in Indonesia 3

2.1 Type of Climate Related Hazards in Indonesia 3

2.2 Detecting Changes in Frequency and Intensity of Climate Hazards 3

III. Impact of Extreme Climate Events 5

3.1 Changes in rainfall 5

3.2 Impact on Water Reservoirs, Electricity Generation andDrinking Water 6

3.3 Impact on Agriculture 7

3.4 Impact on Land and Forest Fires 12

3.5 Impact on Coastal Zones and Fishery 14

3.6 Impact on Health 14

IV. Past and Future Climate Change 16

4.1 Past Global Climate Changes 16

4.2 Past Changes in Climate, Hydrology an Sea Level 17

4.3 Future Global Climate Change and Sea Level Rise 28

4.4 Indonesian Climate in the 21st Century 29

V. Implication of Climate Changes and Sea Level Rise in Indonesia 35

5.1 Impact of Climate Changes 35

5.2 Impact of Sea Level Rise 40

VI. Knowledge Gap and Adaptation Programs 44

References

Appendix


9/79

viii

LIST OF TABLES

1. Percent change of rain relative to normal rainfall by provinces 52. Percentage of young plants killed due the long dry season 10

3. Total economic loss nationally due to fires in 1997 El Nio year (inmillion USD) 14

4. Relative sea level rise in a number of observation stations 275. List of small islands that serve as baseline for Indonesian sea territorial 41

6. Plan for adaptation to climate change in nine sectors

LIST OF FIGURES

1. Degree of exposure to natural hazards and percentage of area affected 22. Global surface mean temperature anomalies during the top 10 El Nio

events in this century 43. Number of floods occurred in Indonesia during the period of 2001-2004 4

4. Average volume of water at the main water storage in Java during La- Nia, El-Nio, and normal years 6

5. Anomaly of electricity production from 1992-2006 6

6. Impact of El-Nio on rice and secondary crops 7

7. National food crops production in the period 1980-1997. Arrows indicateEl-Nio years

9

8. January-April rice production in relation to monsoon onset 9

9. Drought index and rice production loss by district 1110. Variation ofwerengattack during a period of 1989 to 2005 in Indonesia 12

11. Yield of Palm Oil with age 1212. CO2 emission from South East Asia in period of 1991 to 2001. Dashed

and solid lines show different degrees of smoothing of the bariability 1313. Number of incidence rate and affected cities and districts by dengue 15

14. Annual trend of dengue incidence rate by districts in Java 1515. (a) Anomaly of mean globa sea-land and (b) 2001-2005 mean surface

temperature relative to 1951-1980 measured at meteorologicalstations and ship and satellite SST measurements 16

16. Observed changes in global average sea level rise from tide gauges (blue)

and satellite (red) data and (c) Northern Hemisphere snow cover forMarch-April. All changes are relative to responding averages for the

period 1961-1990 17 Annual rate of maximum (a) and minimum temperature (b) changes over

33 stations in Indonesia 1818 Disappearance of snow cover at the Jaya Wijaya Mount at Irian Jaya,

Indonesia (left) and melting of glacier at Upsala Argentina (right) 1919. Significant decreasing annual rainfall trend in Bengkulu of Sumatra and

Ketapang of Kalimantan 2020. Annual changes of wet season (a) and dry season rainfall (b) over 30

stations in Indonesia 2121. Number of extreme dry month (


10/79

ix

22. The changes in onset of wet season and onset of dry season in Sumatra

Island 2223. The changes in onset of wet season and onset of dry season in Java Island 2324. Percentage of rivers which have minimum flows that potentially cause

drought (a) and flood problems (b). 2325. The change in peak flow and its relationship with flood volume in the 12

rivers in West Java 2326. Decreasing trend in base flows (m3/s) of Ciliwung (a), Barito (b) and

Larona (c) rivers. 2527. Water inflow from local rivers to the three cascade dams of Citarum

Watershed (Cirata, Saguling and Jatiluhur) 2628. Water quality at Tarum Barat Canal used for drinking water supply at

DKI Jakarta 26

29. Existing operational Sea Level Monitoring Stations in Indonesia 2730. Model projections of global mean warming compared to observed

warming 2831. The change in mean temperature and seasonal rainfall in Indonesia under

the two emission scenarios for the five GCM models. 3032. Changes in JJA seasonal rainfall for 20702099 relative to 19011960

(mm day-1) from six of the oceanatmosphere climate models, for the

Special Report on Emissions Scenarios A2 global warming scenario.

Contour line colors correspond to different models. 3233. Precipitation trend for JJA of the multimodel ensemble median from 1979

to 2099. Shading indicates_99%significance by the Spearman-rho test.

The black line gives the 4 mmday_1 contour from the medianclimatology (19001999 average) of the models to indicate a typical

boundary of the convection zones. 3234. Summed precipitation for AprilJune (AMJ) and JulySeptember (JAS)

for the present climate (dashed line) and for the future predicted climate,

using the A2 scenario 33

35. Likelihood of exceeding the 30-day monsoon threshold in 2050 for thethree EDMs applied to all GCMs for each scenario (15 GCMs for

SRESA2 and 19 GCMs for SRESB1. 3336. Likely rainfall pattern in Java and Bali 3437. Status of clean water availability in 2015 by districts 37

38. Projection of water status by sub-district at Citarum watersheds with nochange in rainfall and water extraction of 10% 38

39. Projection of water status by sub-district at Citarum watersheds with nochange in rainfall and water extraction of 20% using baseline demandscenario 39

40. Area being inundated in 2050 under different sea level rise and land

Subsidence scenarios. 4241. Example oflong-term plan for adaptation for agriculture sector 45


11/79


12/79

1

I. INTRODUCTION

In the past four decades, climate related hazards such as floods, droughts, storms,landslides and wild fires have caused major loss of human lives and livelihoods, the

destruction of economic and social infrastructures as well as environmental damages.In many parts of the world, the frequencies and intensities of these hazards tend to

increase (Sivakumar, 2005; ADRC, 2005). Floods and windstorms accounted for70% of total disasters and the remaining 30% of the total disasters are accounted for

by droughts, landslides, forest fires, heat waves and others. Within the period of2003-2005 alone, there were about 1,429 disaster incidences in Indonesia. About

53.3 percent were hydro-meteorological disasters (Bappenas and Bakornas PB,2006). Of this figure, floods occur most often (34%), followed by landslides at 16%.It is likely that global warming will lead to greater extremes of drying and heavy

rainfall which will in turn lead to higher risk of climate hazards (Trenberth andHoughton, 1996; IPCC, 2007). A report from UN-OCHA (2006) indicates that

Indonesia is one of the vulnerable countries to climate related hazards (Figure 1).

In the future, a changing climate brought about by global warming is expected tocreate new patterns of risk, and higher risks generally. Sea level rise due to meltingglaciers and polar ice and thermal expansion will contribute to the increase of

coastal flooding. Increasing intensity of tropical cyclones observed in recent decades

may be tied to increasing sea surface temperatures. By impacting the hydrologiccycle, global warming is expected to alter climatic ranges, shift regional climaticaverages, resulting in shifting of climate zones, and lead to a higher frequency and

amplitude of weather events. Climate variability and change occurring against abackdrop of increasing global population and globalization of economic processes

may be expected to lead to increased competition over resources and newvulnerabilities. With the increase of climate risk, many countries, particularly leastdeveloped and developing countries, may have difficulties to achieve the

Millennium Development Goals related to poverty, hunger and human health.

This country report describes briefly the type of climate hazards in Indonesia and

their impact on various sectors, trends of climate change in the past and climatechange scenarios in the future as well as their implication on the sectors. Views fromsectors on how to address this climate change impact are summarized in the last

chapter. The country report was developed based on data and information providedby sectors, reviewed journal articles and project reports. Scientific explanations are

not discussed in detail, however, where relevant, short notes on the methodologyused for data analysis are provided as foot notes.


13/79


14/79


15/79

4

in all provinces of Indonesia. A rising trend of flood occurrence was also observed

in this short period of observation (Figure 3).

Figure 2. Global surface mean temperature anomalies during the top 10 El Nio events inthis century (1914/15, 1917/18, 1940/41, 1957/58, 1965/66, 1972/73, 1982/83,1986/87, 1991/92, and 1997/98. Source: NCDC/NOAA)

Figure 3. Number of floods occurred in Indonesia during the period of 2001-2004 (Source:Provided by the Ministry of Public Works, 2007)

0

50

100

150

200

NumberofF

loodEvents

2001/2002 2002/2003 2003/2004


16/79

5

II. IMPACT OF EXTREME CLIMATE EVENTS

3.1. Changes in rainfall

As discussed in Chapter II, many of the extreme climate events in Indonesia,particularly droughts, were associated with ENSO. This was primarily due to the

significant decrease in rainfall. The impact of the 1982 and 1997 El-Nio events(the two strongest El-Nio years in the last 25 years) on rainfall over Indonesia, has

been documented by Irawan (2002). His analysis was based on monthly rainfalldata in 1970-1997 by province and the impact was measured based on the

percentage of changeof seasonal rainfall relative to the rainfall means during the period. It was found that all provinces had lower seasonal rainfall in these years.Sumatra, Java and Sulawesi consistently showed a decrease of seasonal rainfall, in

particular of dry season rainfall (Apr-Sep or May-Oct depending upon the pattern ofmonthly rainfall of each province, Table 1). The average decrease in dry season

(Apr-Sep or May-Oct) and wet season (Oct-Mar or Nov-Apr) Indonesian rainfall in1997s El-Nio was about 62% and 32% respectively while those in 1982s El-Nio

was about 47% and 19% respectively. These results indicate that the effect ofENSO on DS rainfall is stronger than on WS rainfall.

Table 1. Percentage of change of rainfall by province, relative to normal rainfall (average

of 1970-1997)

Source: Irawan (2002)

Furthermore, ENSO influences on inter-annual rainfall variability in Indonesiareveal that (USDA, 1984; ADPC, 2000; Yoshino et al., 2000; and Kirono and

Partridge, 2002): (i) the end of the dry season occurs later than normal during ElNio and earlier during La Nia years, (ii) the onset of the wet season is delayedduring El Nio and advanced during La Nia years, (iii) a significant reduction of

dry season rainfalls could be expected during El Nio and significant increaseduring La Nia years, (iv) long dry spells occur during the monsoon period,

particularly in Eastern Indonesia.

1997 1982Island

Oct-Mar orNov-Apr

Apr-Sep orMay-Oct Annual

Oct-Mar orNov-Apr

Apr-Sep orMay-Oct Annual

Sumatra -35 -47 -38 -21 -32 -24

Java -34 -80 -41 -11 -85 -23

Bali/Nusa Tenggara -26 -82 -31 -26 -75 -32

Kalimantan -33 -57 -40 -5 -36 -16

Sulawesi -28 -67 -39 -35 -33 -30

Maluku/Ambon -13 -53 -40 -5 -27 -20

Indonesia -32 -62 -38 -19 -47 -24


17/79

6

3.2. Impact on Water Reservoirs, Electricity Generation and Drinking Water

The decrease and increase in rainfall has significant impact on water storage inreservoirs (Figure 4). Significant changes in water volume in the reservoirs (dams)

occurred during dry seasons, in particular in dry season II (June-September). Manyof these dams have functions for electricity generation and for providing irrigation

water and drinking water.

Figure 4. Average volume of water at the main water reservoirs in Java during La-Nia, El- Nio, and normal years. WS: wet season, DS: dry season Source: Las et al.(1999)

The occurrence of ENSOs that caused significant decrease of water levels in the

reservoirs has caused serious impact on electricity generation. Data from eightDams (four small dams and four big dams in Java) indicated that in El-Nio years of1994, 1997, 2002, 2003, 2004 and 2006 most of the power plants operated in the

eight dams produced less electricity than normal (long-term means; Figure 5). The

interesting feature was that during the 1994 El-Nio, the four big dams (Cirata,Saguling, Brantas and Jatiluhur) were still able to produce electricity above the longterm means, but not in El-Nio years of 1997 onwards.

Figure 5. Anomaly of electricity production from 1992-2006 (Drawn from data provided byPLN., Electricity State Company, 2007).

0

20

40

60

80

100

120

140

Volum

eAir(%

dariNorm

al)

La-Nina El-Nino La-Nina El-Nino

Jatiluhur Kedung Ombo

Okt-Jan (MH)Feb-Mei (MK I)

Jun-Sep (MK II)

Volumeofwater(%f

rom

ct- anFeb-May

Jun-Sep

-100

-80

-60

-40

-20

0

20

40

60

80

100

1992 1994 1996 1998 2000 2002 2004 2006

ElectricityProductionAnomaly

(%f

roml

ongtermm

ean)

Area 1

Area 2

Area 3

Area 4

Cirata

Saguling

Brantas

Jatiluhur


18/79

7

The shortage of water in the reservoirs during extreme dry years will also influence

the availability of drinking water, especially in urban/metro areas. For example,Jakarta, the capital city of Indonesia, gets drinking water from the Citarum Dam.Under extreme drry years, the water level at Citarum Dam may go down to a level of

less than 75 m. Under this condition, the water pump at the dam can not be operatedand supply of water to processing the plant will stop. On the other hand, in extreme

wet years, the flood will damage the processing plant and contaminate the water.Floods occurred in February 2007 have caused damage in the production installation

which amounted to about 2.2 million USD. Heavy rainfall also increases theturbidity and this will increase the cost of water processing. Current technology for

water processing is still conventional and it can tolerate the turbidity of between 500and 2000 NTU. Under emergency, the plant still can be operated even though theturbidity has increased up to 8.000 NTU, but the cost for the processing will increase

significantly. If the turbidity goes beyond 8,000 NTU, the plant can not be operated.

3.3. Impact on Agriculture

Significant decrease in rainfall in dry seasons has significant impact on food cropsproduction. From historical data, it was shown that, in general, the area affected bydrought significantly increased during El Nio years (Figure 6). However, from

national production statistics the impact of El Nio, apart from 1982, is not distinct,

except for rice (Figure 7). This condition appears due to a number of reasons(Suryana and Nurmalina, 2000; Meinke and Boer, 2002): (i) the statistics are basedon calendar years rather than El Nio years, (ii) not all regions of the nation are

affected by drought simultaneously, (iii) shortage of water may force a farmer toswitch crops from rice to secondary crops, (iv) restricted water supply may reduce

the area planted under irrigation but yield of crops may increase due to higher solarradiation, and (v) production may be affected in the year following an El Nio eventas farmers have less money to spend on fertilizers or insecticides.

Figure 6. Impact of El-Nio on rice and secondary crops (Drawn from Data provided byDirectorate of Plant Protection, Boer and Subbiah, 2005).

0

1020

30

40

50

60

70

80

90

Dr

oughtArea(thousandha)

1990 1991 1992 1993 1994 1995 1996 1997

Maize

Completely damageLightly-heavily affected

0

100

200

300

400

500

600

700

800

900

D

roughtArea(thousandha)

1990 1991 1992 1993 1994 1995 1996 1997

Rice

Completely damage

Lightly-heavily affected

0

5

10

15

20

25

30

35

DroughtArea(thousandha)

1990 1991 1992 1993 1994 1995 1996 1997

Soybean


0

5

10

15

20

25

DroughtArea(thousandha)

1990 1991 1992 1993 1994 1995 1996 1997

Peanut



19/79

8

Delay in onset of the rainy season during El-Nio years will also reduce the

production of wet season rice (January-April Production; Figure 8). It is suggestedthat a 30-day monsoon delay will reduce January-April rice production inWest/Central Java by about 6.5% and in East Java/Bali 11.0%.

Data of historical impacts of El-Nio events on national rice production indicate that

the national rice production system is vulnerable to extreme climate events.Whenever El-Nio occurred, the rice productions loss due to drought increased

significantly (Figure 9), and the total loss also tended to increase. On average, theproduction loss due to drought in the period 1991-2000 was three times higher than

that, occurring in the period of 1980-1990 (Boer and Las, 2003). This seems toindicate that the national rice production system becomes more vulnerable toextreme climate events.

The occurrence of ENSO also has indirect effects on crops. There was an indication

that the brown plant hopper (wereng coklat) population increased significantly inLa-Nia years probably due to higher rainfall amounts. Wereng attack in West Java,

the main rice growing area of Indonesia, increased significantly in years when La-Nia occurs, i.e. 1998 and 2005 (Figure 10). In addition, types of major crop pestand diseases have shifted recently. For example in the past pink rice stem borer

(Sesamia inferens) was only minor problem in Java (e.g. Indramayu, Magelang,

Semarang, Boyolali, Kulonprogo, and Ciamis) compare to yellow rice stem borer(Scirpophaga incertulas), and white rice stem borer (Scirpophaga innnotata).

Nowadays this disease become dominant (Nastari Bogor and Klinik Tanaman IPB,

2007). According to Kalshoven (1981), regions with distinct dry seasons arefavorable for pink rice stem borer. Bacterial leaf blight(Xanthomonas oryzaepv.Oryza) in the last three years is also dominant diseases for rice crop while before thisdisease is not important so that research on this diseases is still limited. Saddler(2000) stated that optimal temperature for this disease to grow in around 30oC.

Similar phenomena is also observed in non-rice crops. For example, twistingdisease caused byFusarium oxysporum before 1997 is not important disease for red

onion crop, but now this becomes very important disease not only in lowland butalso in the highland areas. In the last two years, this diseases attack seriously red

onion crops in a number of onion production centre such as Brebes (Wiyono, 2007).From laboratory research, this crop when being exposed to high temperature, it

become more is less resistant to this disease (Tondok, 2003).

The phenomenal example is the appearance of Gemini disease in chili in the last fiveyears in all main chili and potato production centre of Java (Bogor, Cianjur, Brebes,

Wonosobo, Magelang, Klaten, Boyolali, Kulonprogo, Blitar, dan Tulungagung;Nastari Bogor dan Klinik Tanaman IPB, 2007). This disease caused by virus which

is transmitted to the crops by kutu kebul (Bemisia tabaci). Up to know, research onthis disease is still limited. However initial findings suggests that temperature is the

main triggering factor for this disease as indicated by the significant increase inBemisia tabaci population on tomato when temperature was increased from 17 to 30

C (Bonaro et al.., 2007). The explosion of this virus under elevated temperature

has been predicted by Boland et al., (2004) in Canada. These above findings may


20/79


21/79

10

Long dry seasons in El-Nio years affect significantly not only annual crops but also

perennial crops. Based on field observation, a long dry season in general destroysyoung plants. On average, the percentage of young plants (age of less than 2 years)die back due to the long dry season of the El_Nio year 1994 is presented in Table

2.

Table 2. Percentage of young plants killed due the the long dry season of the 1994 El Nioyear

crop type Percent Die Back

Tea about 22

Rubber Between 4 and 9

Cacao about 4

Cashew nut Between 1.5 and 11

Coffee about 4

Coconut Between 5 and 30

Source: Based on data provided by the Directorate General of Plantation, Ministry of Agriculture.

The impact of severe drought on some plantation crops such as coconut and palm oilmay not occur during years of drought events but it may be observed a few monthslater. Hasril et al. (1998) found that the impact of long dry spell on the production

of palm oil is significant after 4-9 months (Figure 11).


22/79

11

Figure 9. Drought index and rice production loss by district (Drawn from data provided byDirectorate of Plant Protection, Boeret al. 2002)

1991 1992

1993 1994

1995 1996

1997


23/79

12

Figure 10. Variation ofwerengattack during the period of 1989 to 2005 in Indonesia. Source:

Drawn from data provided by Directorate of Plant Protection (2007)

Figure 11. Yield of Palm Oil with age (Hasan et al., 1998)

3.4. Impact on Land and Forest Fire

The extent of land and forest fires in Indonesia is also closely related to ENSOevents. In El-Nio years, the total area of land and forest being burnt by fires

increased significantly and this lead to much of the increase in levels of atmospheric

CO2. For example in the 1991/92, 1994/95 and 1997/98 El-Nio years, the carbonemission from fires measured in 97 monitoring stations across South East Asiancountries increased significantly (Schimel and Baker 2002). Wildfires in Indonesia

were responsible for much of the increase (Page et al. 2002). Most of the carbonemission from fire in Indonesia during 1997/98 came from peat fire. Total area of

0

2000

4000

6000

8000

10000

12000

14000

71978

101980

131981

161983

191984

221986

251987

281989

311990

341992

371994

401995

Age (Semester and Year)

Freshfruit(kg/ha)

El-Nio years were 82/92, 91/92, and 94/95

0

10000

2000030000

40000

50000

60000

70000

80000

90000

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Year

Atta

ckedareas(Ha)

NAD North Sumatra South Sumatra Lampung

West Java Central Java DI Yogyakarta East Java

Bali West Nusa Tenggara West kalimantan South kalimantan

South Sulawesi Banten


24/79


25/79

14

Table 3. Total economic loss due to fires nationally in the 1997 El-Nio year (in MillionUSD)

Sectors MoE and UNDP (1998) WWF & EEPSEA (1998)

1 Agriculture 88.6 130.7

2 Forestry 508.2 640.6

3 Health cost 43.8 256.7

4 Transmigration 0.2 0.05 Transportation 13.6 4.9

6 Tourism 4.9 19.6

7 Fire cost control 3.2 3.3

TOTAL 662.4 1055.6

3.5. Impact on Coral Ecosystems

The increase in sea temperature during the 1997 El-Nio year has caused serious

problems for the coral ecosystems. Wetland International (Burke et al., 2002)reported that the 1997 El-Nio has damaged about 18% of the coral ecosystems inSouth East Asia. Coral bleaching was observed in many places such as in the

eastern part of Sumatra, Java, Bali, and Lombok. In thousands islands (north of theJakarta coast), about 90-95% of the corals located 25 m below sea surface has been

bleached.

3.6. Impact on Health

Extreme weather related to ENSO may also contribute to the outbreak of humandiseases such as malaria, dengue, diarrhea, cholera and other vector borne diseases.In Dhaka, Bangladesh the cholera cases correspond significantly to local maxima in

ENSO, and this climate phenomenon accounts for over 70% of disease variance

(Rodo et al., 2002). In Africa, malaria disease outbreak was triggered by theoccurrence of above normal rainfall (Moji et al., 2002). This finding has been used

as one of the indicators to warn the possibility of malaria outbreak. In Indonesia

Dengue cases are also found to increase significantly in La-Nia years (Figure 13)when seasonal rainfall increased above normal. A significant increasing trend in the

number of dengue cases was also observed in Java. Based on data of dengueincidence rate from 1992 to 2005, it was found that in many big cities, especially in

Java, the incidence rate of dengue increased consistently from year to year (Figure14) peaking in La-Nia years.


26/79

15

Figure 13. Number of incidence rate of dengue histogram and of affected cities and districts

line in Indonesia (Source: Depkes RI dalam www.tempointeraktif.com). Note:1973, 1988 and 1998 are La-Nia years.

Figure 14. Annual trend of dengue incidence rate in districts in Java (cases/100,000 people).Source: (drawn from data provided by Depkes, 2007).

IncidenceRateper100.000

Numberofaffected

Between -6 and -3Between -3 and 0Between 0 and 3Between 3 and 6

Between 6 and 9

Between 9 and 12Between 12 and 15Between 15 and 18Between 18 and 21

Between 21 and 24


27/79


28/79

17

4.2. Past Changes in Climate, Hydrology, and Sea Level in Indonesia

Temperature. Based on trend analysis of maximum and minimum temperature data

of 1980-2002 for 33 stations, a significant increase in maximum and minimumtemperature was observed in most of the stations. The rate of change varied from

one station to another station (Figure 17). The highest rate of minimum temperatechanges was observed in Polonia-Medan (0.172oC per year) while that of maximum

temperature changes was observed in Denpasar (0.087oC per year). On average therate of changes in minimum and maximum temperature over the 33 stations was

0.047oC and 0.017oC per year respectively.

Figure 16. Observed changes in global average sea level rise from tide gauges (blue) andsatellite (red) data and Northern Hemisphere snow cover for March-April. Allchanges are relative to corresponding averages for the period 1961-1990 (IPCC,

2007).

The locations of the stations that monitor the air temperature are mostly in urbanareas. The increase in population, industries and transportation activities in these

areas may contribute partly to the increase of the temperature. It is quite difficult toquantify the single effect of the increase of the GHG concentration on site-specific

temperatures t. However, there is much evidence that global warming is occurring.For example, much snow that covers the Jayawijaya Mount of Irian Jaya in the pasthas disappeared already. Similar feature was also observed in other country such as

in melting of glaciers in the Upsala Mount of Argentina (Figure 18).


29/79

18

Figure 17. Annual rate of maximum (a) and minimum temperature (b) changes over 33stations in Indonesia (significant at 5% level; rate of changes < 0.04oC; between0.04 and 0.07oC ; and > 0.07oC;. Source: Data provided by BMG and analysed

by Boeret al. (2007).

(a)

(b)


30/79

19

Figure 18. Disappearance of snow cover at the Jaya Wijaya Mount at Irian Jaya, Indonesia(left) and melting of glacier at Upsala Argentina (right)

Rainfall. Based on a record of historical annual rainfall data with a length of about

43 years, from 63 stations (period of record varied from the earliest year 1950 andthe latest 1974 until 1997), it was found that all stations show a decreasing trend of

annual rainfall depth during the last decades, except for stations in the Lesser SundaIslands and the eastern coast of Java and the northern part of Indonesia (e.g.Sumatra) (Aldrian, 2007)1. The decrease varies among stations. It was found that in

the period of 1968 and 1997, the large significant decrease of trends were observedin Bengkulu, Sumatra and Ketapang, Kalimantan, i.e. 71.79 and 29.71 mm/yearrespectively (Figure 19). A similar study conducted by Boer et al. (2007) also

showed that there was a significant decreasing trend in both seasonal rainfalls (rainyand dry seasons). Most of the wet season rainfall of stations located in the southern

part of Indonesia (South Sumatra, Java and Eastern Indonesia) tended to increase

(Figure 20a) while that of dry season rainfall tended to decrease (Figure 20b).

Whereas in the stations located in the northern part of Indonesia (e.g. Sumatra),rainfall in both seasons showed a slight increase.

Furthermore, Aldrian and Djamil (2006) also studied the change of rainfall pattern in

the Brantas Catchment Area based on 40 daily rainfall stations from 1955 to 2002.They found that number of extreme dry months that was increasing for the last fivedecades, particularly in areas near to the coast. In coastal areas, the number of

extreme dry months increased to 4 months in the last ten years and in 2002 it

reached 8 months which was considered as the longest dry season for the whole fivedecades (Figure 21). In the mountain areas, amount of dry months in about 1-2

1Trend analysis was done using the Mann Kendall trend test (Gilbert, 1987) and the linear

regression of Sens estimate (Salmi et al., 2002).


31/79

20

months for the last ten years with maximum number of 4 months (Figure 21). Thus

there was a decrease in monsoonal strength and the shifted balances between the wetseason and dry season during the last five decades. This study suggests that thelowland areas are more susceptible to the climate change.

Figure 19. Significant decreasing annual rainfall trend in Bengkulu of Sumatra and Ketapangof Kalimantan (Reconstructed from Aldrian, 2007)

The shifted balances between the wet and dry seasons will lead to the shifted onsetof seasons. Based on mean data of onset of the rainy and dry season in the period of1961 to 1990 and that of 1991 and 2003, it can be indicated that the onset of the

seasons have changed in a number of regions of Sumatra and Java islands (Figure 22

and 23). In most of the Sumatra region, the onset of the wet season delayed between1 and 2 dekads (one dakad equal to 10 days), while the onset of dry seasonsadvanced between 1 and 6 dekads, except in some of areas in the eastern part of

Sumatra. A similar feature was also observed in Java.

Hydrology. Changes in stream flow are not only due to changes in rainfall but alsodue to changes in land use and land cover and water use. Many studies suggest that

the fluctuations of stream flow will increase with the decrease in forest cover.Recent studies indicated that the actual forest cover of Indonesia in 2000 was about81.6 millions ha. With a deforestation rate of around 1.6 millions ha per year

(Kartodihardjo, 1999), almost three times the deforestation rate in the eighties(600.000 ha/year), it is presumed that the forest cover in Indonesia in the year 2008could be 68.8 millions ha only, or almost 53% of the forest cover of Indonesia in1990 (Rosalina et al., 2003).

The high rate of deforestation has caused serious problems in many watersheds in

Indonesia Based on data from 52 rivers in Indonesia, it was found that the number ofrivers in which the minimum flow potentially would cause drought problems hasincreased significantly. Similarly, the number of rivers in which the peak flow

potentially causes flooding also increased quite significantly (Figure 24). Based on

two year observations at 12 rivers in West Java, it was also found that peak flow inthe 12 rivers in 1999 has increased significantly compare to that of 1981 (Figure 25).

The increase in peak flow will increase flood volume. These findings suggest that

the risk of drought and flood will definitely increase under the changing climate, if

0

1000

2000

3000

4000

5000

6000

7000

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

AnnualRainfall(m

m) Bengkulu: Y=-71.8X + 5451

Ketapang: Y=-29.7X + 4010

Formatted: F

Roman, 8 pt

Formatted: F

Roman, 8 pt


32/79

21

no significant efforts are going to be undertaken to increase forest cover, particularly

in regions with high rainfall such as Sumatra and Java.

Figure 20. Annual changes of wet season (a) and dry season rainfall (b) over 30 stationsin Indonesia (significant at 5% level). Source: Data provided by BMG andanalysed by Boeret al. (2007)

Between 0 and 3 mm/yr


Between 6 and 9 mm/yrBetween 9 and 12 mm/yr







Between -21 and -24 mm/yr



Between -9 and -12 mm/yrBetween -6 and -9 mm/yr


Between 0 and -3 mm/yr


33/79

22

Figure 21. Number of extreme dry month (


34/79

23

Figure 23. The changes in onset of wet season and dry season in Java Island. One dekadequal to 10 days. Source (BMG, 2004)

Figure 24. Percentage of rivers which have minimum and peak flows that potentially causedrought (a) and flood problems (b). Source: Loebies (2001).

Figure 25. The change in peak flow and its relationship with flood volume in 12 rivers inWest Java (Reanalyzed based on data from Pawitan, 2002)

0

20

40

60

80

100120

140

Ciliw

ung

Midd

leCiliw

ung

UpperCiliw

ung

Ciluar

Ciseuseupa

n

Lowe

rCiliw

ung

Katulam

paTu

gu

Ciesek

Cisukabir

us

Cisarua

Cibo

go

PeakFlow(m3/s).

19811999

0

500

1000

1500

2000

2500

0 25 50 75 100 125 150

Peak Flow (m3/s)

FloodVolume(1000m

3) 1981

1999

(a) Wet season

No ChangeAdvanced 1-2dekadsAdvanced 3-4

No Change

Advanced 1-2dekadsAdvanced 3-4dekads

(b) Dry season

Percentofriverwith

minimum

flowpotentiallycauseddrought

Percentofriverwithmaximum

flowpotentiallycausedflood

Year Year

(a) (b)


35/79

24

Based on stream flow data from 1990 to present, a decreasing trend in base flows

has been observed in a number of stations of major rivers in Indonesia such as theUlar river (North Sumatra), Tondano River (North Sulawesi), Citarum river (WestJava), Brantas (East Java), Ciliwung-Katulampa (West Java), Barito-Muara Teweh

(Central Kalimantan), Larona-Warau (South Sulawesi). A significant decrease inthe base flow was observed in some of these rivers (Figure 26). These significant

decreases were caused partly by the increase in water use and the decrease in forestcover in the upper part of the river basins, particularly in the Ciliwung River.

From long historical data of water inflow from local rivers to the three cascade dams

of the Citarum watershed (Cirata, Saguling and Jatiluhur), it was found that themaximum, mean and minimum water inflow from the local rivers decreasedsignificantly (Figure 27). The rate of decrease is more pronounced for peak flow,

i.e. 6.5 m3

s-1

year-1

. A similar decreasing pattern was also observed in rainfall.Pawitan (2002) found that the annual rainfall in the upper Citarum stations

decreased at a rate of about 10 mm per year (based on rainfall data in the period of1896-1994).

The quality of water in the Citarum watershed also decreased significantly.Observations at station B.Tb.49 located at Tarum Barat Canal showed that a rapid

change in turbidity occurred after 1997 (Figure 28). A similar pattern was observed

in some other monitoring stations. The decrease in the water quality will increasecost for processing the water.


36/79

25

Figure 26. Decreasing trend in base flows (m3/s) of Ciliwung (a), Barito (b) and Larona (c)rivers. Source: Puslitbang Air Bandung (2007).

1

20

40

60

81

900101 25.days/mm 9301 9401 9501 9601 9701 9801 9901 0001 0101 YYYMM

A

A

A site 2120102 020120102 Ciliwung at Ciliwung-Katulampa Debit m3/det .734units/mm Origin 1

0

2 0 0 0

4 0 0 0

6 0 0 0

6 9 3 0

7 7 0 1 0 1 8 0 0 1 8 3 0 1 8 6 0 1 8 9 0 1 9 2 0 1 9 5 0 1 9 8 0 1Y Y M M

A

A

A s i te 3 2 7 0 0 0 1 0 3 0 2 7 0 0 0 1 S B A r i to a t S B a r it o -M T e w e h

0

100

200

300

400

500

610

760101 7701 7801 7901 8001 8101 8201 8301 8401 8501 YYMM

A

A

A site 4570006 040570006 S Larona at S Larona-Warau Debit m3/det


37/79


38/79

27

Figure 29. Existing operational Sea Level Monitoring Stations in Indonesia

Table 4. Relative sea level rise in a number of observation stations

Stations Location Sea Level Rise(mm/year)

Source

Cilacap 1.30 Hadikusuma, 1993

Belawan 7.83 ITB, 19904.38 ITB, 1990Jakarta

7.00 Based on data from 1984-20063

9.37 ITB. 1990Semarang

5.00 Based on data from 1984-2006

Surabaya 1.00 Based on data from 1984-2006

Sumatra 5.47 ITB, 1990

Panjang, Lampung 4.15 P3O-LIPI, 1991

A phenomenon called ROB, inundation of coastal areas during spring tide, has beenobserved in Demak since 1995. This phenomenon has affected more than 650 ha of

coastal areas in six villages, i.e. Sriwulan, Bedono, Timbul Seloka, Surodadi,Babalan and Beran Wetan. It also damages infrastructures such as roads and

railways. During these bad conditions, those infrastructures are failed to functionand create problems for transportation and economy. Responding to the impacts, the

Ministry of Marine Affairs and Fishery together with the local government, has beenimplementing a number of activities, i.e. rehabilitation of mangrove areas, coastal

sediment stabilization, and construction of pile-houses. Impact of this phenomenonis enhanced as the land subsidence continues. Problems of land subsidence has

been observed in a number of cities mainly due to overexploitation of ground water.

3 The derived water levels are a combination of changes in the sea level and the vertical land motion at the

location of the gauge. Therefore, the trends derived are relative MSL trends and can be considered validonly for a region near the gauge with uniform vertical land motion.


39/79

28

4.3. Future Global Climate Change and Sea Level Rise

Global Temperature Rise. Due to the increase in human activities in

consuming energy and forest conversion, the concentration of greenhouse gases inthe atmosphere will continuously increase. Scientific evidence shows that during

the course of the 21st century the global-average surface temperatures are likelyincreasing by 2.0-4.5oC as the concentration of greenhouse gases in the atmosphere

increase.

The first problem in assessing future climate change is how to estimate the likelychange in greenhouse gases emissions in the future. Many trajectories might occur

as the level of emissions is closely related to population growth, socio-economicdevelopment, and technology changes. Implementation of climate policy or GHGemission targets by developed countries as stated in the Kyoto Protocol may also

affect the rate of the GHG emissions. Therefore, in estimating future emissions theIPCC has developed a number of scenarios (IPCC 2000) using several assumptions

of the driving forces. The scenarios provide alternative images of how the futuremight unfold and are an appropriate tool with which to analyze how the drivingforces may influence future emission outcomes and to assess associated

uncertainties. Figure 30 provides likely changes in global temperature when

emission scenarios follow SRESB1, SRESA1B, SRESA2 and commitment underthe Kyoto Protocol.

Figure 30. Model projections of global mean warming compared to observed warming.Observed temperature anomalies are shown as annual (black dots) and decadalaverage values (black line). Source: 4th AR of IPCC (2007)

Sea Level Rise. The increase in temperature in the future will cause sealevel rise as a result of the thermal expansion of seawater as it warms and melting of

glaciers and the ice sheets of Greenland and Antarctica. It was estimated that the

volumes of the Greenland and Antarctic Ice Sheets are equivalent to approximately


40/79

29

7 m and 57 m of sea level rise, respectively (IPCC, 2007). In the period of 1961-

2003, mass loss of glaciers and ice caps (excluding those around the ice sheets ofGreenland and Antarctica) is estimated to be 0.50 0.18 mm per year in sea levelequivalent (SLE), and in the period of 1991-2003 it was about 0.77 0.22 mm per

year. These estimates have a high degree of confidence (Figure 31). Based onclimate models, it was indicated that thermal expansion is expected to continue to

contribute substantially to sea level rise over the next 100 years (IPCC, 2007).

Projection of sea level rise to 2020 under scenario of SRES A1B in the ensemble ofAOGCMs4, the rate of thermal expansion is projected to be 1.3 0.7 mm per year,

and is not significantly different under the A2 or B1 scenarios. These projected ratesare within the uncertainty of the observed contribution of thermal expansion for

1993 to 2003 of 1.6 0.6 mm per year (IPCC, 2007). Since deep oceantemperatures change only slowly, thermal expansion would continue for manycenturies even if atmospheric concentrations of greenhouse gases were stabilized

(IPCC, 2007).

4.4. Indonesian Climate in the 21stCentury

Global warming may lead to changes in regional climate, like changes in

precipitation (amount of heavy rainfall) and in climate extremes such as number ofhot days, and number of long dry spells. Salinger (2005) stated that the effect ofglobal warming will be superimposed on decadal climate variability, such as that

caused by the inter decadal or Pacific Decadal Oscillation, and on inter annualfluctuations caused by the ENSO and the North Atlantic Oscillation. All this may

lead to a century of increasing climate variability and change, expected to beunprecedented in the history of human settlement and agrarian activities.

Boer and Faqih (2005) assessed the impact of increase in GHG concentration under

the two scenarios (SRESA2 and SRESB2)5. The assessment was conducted basedon five GCMs, i.e. GCMs, CCSR-NIESS, CGCM1, CSIRO, ECHAM4 and

HadCM3. The monthly data of the GCMs outputs from the two scenarios weretaken from the Data Distribution Center. Mean temperature and rainfall changesover the Indonesian region in 2020, 2050 and 2080 were calculated based on grids

data in the areas of between 17 N-17 S and 90 E-147 E. The results of the analysisshowed that the Indonesian temperature means will increase at a rate of about

4 AOGCM or Atmospheric-Ocean General Circulation Model is a numerical representation of the climate

system based on the physical, chemical and biological properties of its components, their interactions and

feedback processes, and accounting for all or some of its known properties. The atmosphere and oceangeneral circulation model components are three-dimensional, time-dependent models that include arepresentation of the equations of motion on a sphere. In addition to atmosphere and ocean components,

the term AOGCM is often applied to computer models that include land surface and sea ice model

components. The model components are coupled, in the sense that fluxes are regularly exchanged between the different model components as they march forward in time (Source:

http://data1.gfdl.noaa.gov/nomads/forms/deccen/glossary/glossary.html)5 Concentration of GHG in the atmosphere in 2025, 2050 and 2100 under the SRESA2 would be about440, 535, 825 ppm respectively and under the SRESB2 about 425, 480, and 600 ppm respectively.


41/79

30

0.0344 oC per year for SRESA2 and about 0.0211oC per year for SRESB2 (Figure

31).

Figure 31. The change in mean temperature and seasonal rainfall in Indonesia under the two

DJF_SRESA2

-20

-15

-10

-5

0

5

10

15

20

0 .0 0 .5 1 .0 1 .5 2 .0 2 .5 3 .0 3 .5 4 .0

Temperature change (oC)

RainfallCh

ange(%)

CCSR

CGCM1

CSIROECHAM4

HadCM3

DJF_SRESB2

-20

-15

-10

-5

0

5

10

15

20

0 .0 0 .5 1 .0 1 .5 2 .0 2 .5 3 .0 3 .5 4 .0


RainfallCh

ange(%)

CCSR

CGCM1

CSIROECHAM4

HadCM3

JJA_SRESA2

-20

-15

-10

-5

0

5

10

15

20

0. 0 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0


RainfallChange(%

)

CCSR

CGCM1

CSIRO

ECHAM4

HadCM3

JJA_SRESB2

-20

-15

-10

-5

0

5

10

15

20

0. 0 0 .5 1 .0 1. 5 2. 0 2 .5 3 .0 3. 5 4. 0


RainfallChange(%

)

CCSR

CGCM1

CSIRO

ECHAM4

HadCM3

MAM_SRESA2

-20

-15

-10

-5

0

5

10

15

20

0. 0 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0


RainfallChange(%

)

CCSR

CGCM1

CSIRO

ECHAM4

HadCM3

MAM_SRESB2

-20

-15

-10

-5

0

5

10

15

20

0. 0 0 .5 1 .0 1 .5 2. 0 2. 5 3. 0 3. 5 4. 0


RainfallChange

(%

)

CCSR

CGCM1

CSIRO

ECHAM4

HadCM3

SON_SRESA2

-20

-15

-10

-5

0

5

10

15

20

0. 0 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0


RainfallChange(%

)

CCSR

CGCM1

CSIRO

ECHAM4

HadCM3

SON_SRESB2

-20

-15

-10

-5

0

5

10

15

20

0 .0 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0


RainfallChange(%

)

CCSR

CGCM1

CSIRO

ECHAM4

HadCM3


42/79

31

emission scenarios for the five GCM models. The data points in the left representdata for 2020, the middle for 2050 and the right for 2080 (Boer and Faqih, 2005).

The impact of the increased GHG concentration on rainfall also varied betweenGCM models and between the scenarios (Figure 31). The CCSR and CSIRO

models suggested that the seasonal rainfall would increase consistently in the periodbetween 2020 and 2080 under both scenarios, except for SON (Sep-Nov) rainfall.

Whereas, for ECHAM4 and CGCM1, the rainfall would decrease consistently. ForHadCM3, the impact was not consistent. For example the DJF (Dec-Feb) rainfallmight not change up to 2020, but it would increase up to 2.5% from the baseline in

2050 and then it decreased up to 2% from the baseline in 2080. Regions withdecreasing rainfall might be exposed to high drought risk (long dry spell), while

those with increasing rainfall might be exposed to high flood risk. The return period

of such extreme events might also increase. This study indicates that the impact ofglobal warming on rainfall in Indonesia could not be generalized.

A study conducted by Neelin et al. (2006) in tropical region using a multimodelensemble of global warming simulations indicates that most of models agree on theoverall amplitude of the precipitation decreases that occur at the margins of the

convective zones, with percent error bars of magnitude similar to those for the

tropical warming

6

(Figure 32). Focusing in Indonesia, it is quite clear that in regionsof the southern part of the equator line (South of Sumatra, Java and most of eastern

part of Indonesia) more models suggest the decreasing trend in JJA rainfall(indicated by darker shading) than in regions of the northern part of the equator line

(Central and North Sumatra and northern part of Kalimantan). Further analysis alsosuggests that the precipitation median trend for JJA decreases in the regions of thesouthern part of equator, but it increases in the regions of the northern part of the

equator (Figure 33).

More detail study conducted by Naylor et al. (2007) using more GCMs and

empirical downscaling models7 indicates that under the SRESA2 scenario total AMJrainfall in Java and Bali is expected to increase relative to the current pattern by

6

To provide a measure of amplitude growth, Neelin et al. (2006) project each models precipitationchange field onto spatial patterns that are constant in time and are chosen to reflect each models typical

precipitation response for dry and wet regions (negative and positive anomalies), respectively. The

two spatial patterns for each model are defined by the precipitation change for 20702099 (relative to the19011960 base period) in the tropics (lat 23S to lat 23N). This pattern is divided into negative and

positive anomalies, each normalized by their respective spatial residual means square. The late-21st-century precipitation change is used to characterize each models preferred pattern.7Projections of rainfall change was done using 15 different GCMs and three empirical downscaling

models (EDMs). Predictors used in the EDM1 were 850-mb specific humidity, EDM2 850-mb specific

humidity and sea-level pressure and EDM3 [850-mb used specific humidity, upper (200-mb)- and lower(850-mb)-level zonal winds. The 850-mb specific humidity represents possible changes in the

hydrological cycle that arise as a result of mean warming. Sea level pressure variations are stronglyrelated to the dynamical circulation in the tropics (e.g., ENSO and the Walker circulation) and the

seasonal cycle. Zonal winds represent the monsoon shear line and therefore correspond very strongly tovariations in monsoon onset date. As the monsoon sets in, the surface winds shift from easterly to

westerly, and winds aloft shift from westerly to easterly. Thus, upper- and lower-level winds may capturechanges in monsoon onset and retreat (Naylor et al., 2007).


43/79

32

about 10% on average, but to decrease in JAS by about 1025%. The decline in

JAS rainfall could be up to 50% in West/Central Java and 75% in East Java/Bali atthe tail end of the distributions. In East Java/Bali, some models projected that totalrainfall would drop close to zero for the JAS (Figure 34). Under SRESB1, the

projection of changes is similar to those of SRESA2 until 2050. Furthermore, theonset of the rainy season in Java and Bali may also delay under a changing climate.

However, the uncertainty is quite high as illustrated by the wide range of resultsamong GCMs for a given EDM (Figure 35). Nevertheless, it is clear that a 30-day

delay in monsoon onset is very likely to occur more frequently in 2050 than it doestoday (Figure 35). Based on these two findings, it is very likely that the rainfall

pattern in Java and Bali will change in the future. The pattern of change is quitesimilar to what has happened in the past (see section 4.2). The onset of the rainyseason will delay, while the onset of the rainy season will advance. This means that

the length of rainy season will shorten.

Figure 32. Changes in JJA seasonal rainfall for 20702099 relative to 19011960 (mm day-1)from six of the oceanatmosphere climate models, for the Special Report onEmissions Scenarios A2 global warming scenario. Contour line colors correspondto different models. Shading denotes precipitation decreases exceeding 0.5 mmday-1, with darker shading where these regions overlap for more than one of the

three models shown on each panel. The dashed black contour gives the observedclimatological 4 mm day-1 contour, which typifies the shape of the meanconvection zones. Source: Neelin et al. (2006)

Figure 33. Precipitation trend for JJA of the multimodel ensemble median from 1979 to 2099.Shading indicates_99%significance by the Spearman-rho test. The black line gives


44/79

33

the 4mmday_1 contour from the median climatology (19001999 average) of themodels to indicate a typical boundary of the convection zones. Source: Neelin etal. (2006)

Figure 34. Summed precipitation for AprilJune (AMJ) and JulySeptember (JAS) for thepresent climate (dashed line) and for the future predicted climate, using the A2

scenario (Nayloret al., 2007)

Figure 35. Likelihood of exceeding the 30-day monsoon threshold in 2050 for the threeEDMs applied to all GCMs for each scenario (15 GCMs for SRESA2 and 19GCMs for SRESB1. The thick rectangle shows the middle tercile, and thehorizontal lines on either side show the lower and upper terciles. The arrowsindicate the mean future probability for all GCMs. The vertical lines show theobserved probability for 19832004 (Nayloret al., 2007).

The interesting findings are that the results of the above different studies are quite

consistent and future wet and dry season rainfall trend follows the past trends. This

means that the trend of change occurring in the past may continue to the future,


45/79


46/79

35

V. IMPLICATION OF CLIMATE CHANGES AND SEA LEVEL RISE IN

INDONESIA

Based on historical evidences, it is quite clear that past emissions cause someunavoidable warming in the future (delayed effects) even if atmospheric greenhouse

gas concentrations remain at 2000 levels (IPCC, 2007). In Indonesia, a significantincreasing trend of air temperature is observed in many parts of the region (see

Figure 13). Onset of the rainy season and the dry season delayed or advanceddepending on locations (see Figure 22 and 23). Rainfall patterns also change. In

most of the area of Java, Bali and South Sulawesi, the depth of rainfall in the rainyseason tended to increase while that in the dry season tended to decrease, while other

parts show an opposite pattern (see Figure 17). The length of the rainy season in

some parts also shortens or lengthens. Under elevated CO2 concentrations thesechanges may continue and may bring the country into higher climate risks. In Java

and Bali, the length of the rainy season may be shorter, and its rainfall depth willincrease whereas dry season rainfall may decrease (see Figure 34-35).

The connection between global warming and the change in inter-annual climatevariability is not clear yet. However, there is strong historical evidence showing

that El Nio events have become more frequent and stronger as the global

temperature anomalies associated continue to increase as suggested by Figure 2.This means that the extreme regional weather and climate anomalies associated withEl Nio are being exacerbated by increasingly higher temperatures. Thus, in the

future the intensity and the frequency of extreme weather and climate events mayincrease.

Furthermore, the sea level rise may also continue due to thermal expansion of theocean even if atmospheric concentrations of greenhouse gases were stabilized (IPCC,

2007). These changes can slow the pace of progress toward sustainable

development either directly through increased exposure to adverse impacts orindirectly through erosion of the capacity to adapt to the changes. The following

paragraphs discuss briefly the implications of climate changes and sea level rise in anumber of sectors.

5.1. Impact of Climate Change

Changes in rainfall pattern and length of the rainy season will have seriousimplications for the agriculture sector. The current cropping pattern might not be

practicable anymore in the future. At present, the cropping pattern used in most of

the rice growing areas of Indonesia is rice-rice. The second planting depends

heavily on irrigation water. Under extreme drought years, the availability ofirrigation water is becoming very limited and this normally will cause huge rice

production loss (see Figure 9). Under a changing climate, the occurrence of extremeclimate events (drought) will be more frequent than the current climate and there is a

possibility that the dry season will persist for longer periods. Keeping this cropping

pattern in the future may expose Indonesian farmers to more frequent crop failures.Thus, in areas where the pattern of rainfall changes into this direction farmers should


47/79

36

alter their cropping pattern from rice-rice to rice-non rice. If the rice-rice pattern is

maintained, development or improvement of water storage and irrigation facilitieswill be required for balancing increased rainfall in AMJ with decreased rainfall inJAS so that irrigation water is still available during the dry season. More efforts to

create new short maturing rice varieties should also be in place to anticipate theshorter wet season.

The increase in temperatures and CO2 concentrations will also affect rice yields.

Some studies showed that for every 1C increase in the minimum temperature, riceyields decrease by 10% (Peng et al., 2004). At a global scale, increased CO2

concentrations may have a positive impact on crop yields. However, recent studiesindicated that the fertilization effect from elevated CO2 on crop yields issignificantly smaller than previously predicted (Long et al., 2006). Global models

that combine precipitation, temperature, and CO2 effects for the A2 scenariogenerally show reduced yields in the tropics (Amien et al., 2004).

The increase in temperature and the changes in rainfall pattern and length of seasons

may also trigger the development of crop pests and diseases. For example, BPH(Brown Plant Hopper) population normally increases when rainfall in thetransitional season increases compared to normal (see Figure 10). The changes in

cropping patterns as part of adaptation efforts to climate change may also alter crop

pests and diseases problems in the regions. Invasion of new races of pests anddiseases may likely occur in a changing climate. In addition, change in temperatureand rainfall may also change the domination of certain crop pest and diseases

(Wiyono, 2007). Field observations in a number of districts of Java such asIndramayu, Magelang, Semarang, Boyolali, Kulonprogo, and Ciamis provide the

evidence of this phenomena (see section 3.3).

New initiatives to anticipate the scarcity of water due to climate change and the

increase on water demand, especially in urban areas, as a result of increasing

population and industrial activities should be in place. Inter basin transfer of watermay be one of the potential options to anticipate to the scarcity of water in the

future. In Indonesia many basins are surplus in water resources, even in the ultimatestage of development, while others face serious shortages, especially during extremedrought years. Creation of storages and inter-basin transfer of water from surplus to

deficit regions could therefore be an option for achieving more equitable distributionof our water wealth and its optimal utilization. Projection of water availability for

drinking water from Directorate General of Human Settlement indicates that in2010-2015, many districts in Indonesia may face problems of clean water shortage(Figure 37).


48/79

37

Figure 37. Status of clean surface water availability in 2015 per district (Drawn from dataprovided by Cipta Karya, 2007)

A study to assess the impact of climate change at watershed level has beenconducted at the Citarum watershed. This watershed supplies about 7650 millioncubic meters (MCM) per year, i.e. about 5750 MCM from the tree dams (Saguling,

Cirata and Jatiluhur) and 1950 million cubic meters from other rivers (Perum Jasa

Tirta, 2003). Under a changing climate, water scarcity problems in this watershedmay occur more frequently. Under the present climate, most of the sub-districts will

have water scarcity problems if water extraction from the watershed is limited toabout 10% of the annual flow (Figure 38). The level of water deficit in these sub-

districts would be more than 60 million cubic meters (MCM) per year. Byincreasing the level of water extraction from 10% to 20%, the status of the water

balance in a number of sub-district of Sukabumi and Purwakarta would be surplus

(Figure 39). However, based on historical observed inflow data (1986-2002), it wasfound that the chance to have minimum flow of less than 10% (of the mean) wasabout 10% for Saguling, 15% for Cirata and 25 % for Jatiluhur, and in most cases

these conditions occurred in El-Nio years. This indicates that if minimum flowcould not reach 10% of the mean flow, many sub-districts would have more severe

water deficit problems.

No data

Safe

Quite Prone

Prone


49/79

38

Figure 38. Projection of water status by sub-district at Citarum watersheds with no change inrainfall and water extraction of 10% (Boer et al., 2005). Note: Assuming noground water extraction.

Scenarios:Water supply: Normal rainfallWater extraction: 10% of totaldischarge

Water demand: Base line

2005 2010 2020

2050 2080


50/79

39

Figure 39. Projection of water status by sub-district at Citarum watersheds with no change inrainfall and water extraction of 20% using baseline demand scenario (Boer et al.,2005). Note: Assuming no groundwater extraction.

Under a changing climate, the frequency to have this condition in the future mightincrease as suggested by a number of GCM models such as ECHAM and CGCM(CRU, 1999). Historical data also show significant decreasing trend in annual

rainfall in this watershed. The annual rainfall in the Citarum watershed hasdecreased at a rate of 10 mm/year. In the early 1900s the mean annual rainfall wasabout 2800 mm per year and in the 1990s it decreased to about 2350 mm (Pawitan,

2002).

The decrease in rainfall and length of wet season will directly reduce soil water

availability. A number of studies have indicated that in tropical countries the projected depletion of soil moisture would likely caused reduction forest

productivity (IPCC, 1996). In India for example teak productivity would declinefrom 5.40 to 5.07 m3/ha/year and moist deciduous forests could decline from 1.8 to1.5 m3/ha/year (Achanta and Kanetkar, 1996). In Indonesia, forest productivity is

between 9 and 13 m3/ha/year. With the change in rainfall, the productivity of forestin regions with decreased rainfall will have lower forest productivity by 4m3/ha/year, while in those with increased rainfall will have higher forest

productivity by about 2 m3/ha/year (Boer et al., 1999). Change in forest productivitywill have implication on logging regulation for example length of concession period.

To anticipate this change, policy response is required.

2005 2010 2020

2050 2080Scenarios:Water supply: Rainfall +20%

Water extraction: 20% of total dischargeWater demand: Baseline


51/79

40

5.3. Impact of Sea Level Rise

Natural changes in sea level can be very large. For example, during the last glacialera, which ended about 10,000 years ago, the ocean was 120 m lower than it is now.

Global mean sea level rises can occur due to an increase in the volume of water inthe oceans. During the 20th and 21st centuries this is likely to be the result of

thermal expansion of sea water and the melting of and glaciers and changes in themass of the Antarctic and Greenland ice sheets. The process of thermal expansion is

characterised by a long delay after a temperature increase, meaning that it isnecessary to look several centuries ahead. The sea level change at a given locality,

also termed the relative sea level change, depends on yet more factors:

x regional variations, including those caused by non-uniform patterns of

temperature and salinity changes in the ocean. These can cause deviations(by up to 100%) from the world mean sea level rise

x vertical movements of the land surface caused, for example, by tectonics,and land subsidence due to large-scale water extraction or compaction of

peatlands

As an island country, Indonesia has a very long coast, i.e. about 81.000 km. In1997, it was reported that about two million people live in coastal areas with an

elevation of between 0 and 2 m asl. Also, many industries and sectors operate in

these coastal areas such as oil and gas exploration, transportations, fisheries(approximately 400,000 ha ponds), settlements, agriculture and tourisms. These

economic activities contribute to about 25% of the gross domestic product and

absorb about 15% of employment (Dahuri dan Dutton, 2000). The increase in sealevel will result in devastating impacts on socio-economic activities and sustainabledevelopment.

The impact of sea level rise will be more severe when coastal erosion can not be

minimized or stopped. In recent years, the number of severely eroded coasts inIndonesia has increased rapidly. There are at least five factors causing suchsituation. The first is the interruption of the continuous along shore sand transport

by various structures built along the shorelines, massive jetties, and harbour breakwaters (Reclamation of Bali Airport, Pulau Baai harbour Breakwater). The

second relates to the formation of circulating currents induced by seawalls. The thirdrelates to the decrease of sediment supply from rivers, because many dams ordiversion channels were built in the upstream regions (Krueng Aceh river mouth).The fourth cause relates to coral or sand mining, which not only reduces sediment

supply from the updrift side but also disturbs the equilibrium of the beach profile(Tanjung Pasir Tangerang, west Java). The fifth is due to deforestation of mangrove

forests (East Lampung, Northern Coast of Java). Now, there are more than hundredcoastal sites in seventeen provinces that are facing significant erosion (Subandono etal., 2001).

With a sea level rise of about 1 m, it was estimated that about 405,000 ha of coastalland including small islands will be flooded. The impacts might be severe in certain

coastal areas such as the north coast of Java, the east coast of Sumatra, and the southcoast of Sulawesi (Subandono, 2002). The disappearance of small islands due to sea


52/79

41

level rise will have serious implications for the Indonesian state border. Recent

studies indicate that at least 8 of 92 outmost small islands that serve as a baseline forthe Indonesian sea territory are very vulnerable to sea level rise (Table 4). Surveyconducted from 29 Juli 7 Agustus 2004 at Nipah Island (Riau Province) by BPPT,

BRKP, Pemda Riau and Universities showed that the island is almost inundated bysea water during high tide. During low tide the total area of Nipah island is about

73.6 ha, and during high tide only 1.8 ha (Hendiarti, 2007).

Table 5. List of small islands that serve as baseline for Indonesian sea territory

Province Island Coastal Type Border with

East Kalimantan Pulau Kepala Mud withmangrove

Malaysia

Central Sulawesi Pulau Dolangan Mud Malaysia

North Sulawesi Pulau Manterawu Mud withmangrove

Philippine

Papua Pulau Fani High wave Palau

Papua Pulau Fanildo Sandy Palau

Papua Pulau Brass Sandy Palau

Papua Pulau Laag Sandy and

wetland

Australia

Riau Nipah Sandy SingaporeSource: Hydro-oceanography, Indonesian Navy 2003, LAPAN (2003), Hendiarti (2007).

Sea level rise in combination with water flow reduction from upstream during dry

seasons will also accelerate the saline water intrusion to the inland. Coastal waterswill become more saline and soil salinity will increase, even the ground water

aquifers will also bear the brunt of salinity intrusion. The problem of waterintrusion has been observed in a number of metro cities near the coast such as

Jakarta, Surabaya and Semarang. For example in Jakarta, such problems have beenoccurring since the 1960s. The shallow groundwater of the coastal areas was

brackish before major groundwater development took place. The brackish wateroccurred under the aquifer less than 100 m deep, as a result of direct contact

between the aquifer and the sea bottom. The saltwater intrusion in the shallow and

deep aquifer had reached to 10 15 km from the coastline in Jakarta. Over-exploitation of ground water, causing land subsidence, has exacerbated the

problem8. Penetration of salt water in the deeper aquifer (40 140 m) has gone up to5 13 km inland such as in the area of the Soekarno Hatta airport, and 8 10 km in

the areas of Cengkareng, Grogol and Kelapa Gading.

Rate of land subsidence in Jakarta varied between locations and times. Maximumsubsidence was found in the northwestern and central eastern parts of Jakarta, while

minimum subsidence was found in the southern part. In general the estimatedsubsidence rates are around 1 to 10 cm per year. The rate of land subsidence in

8At present about 60% of the population and about 90% of industries, hotels and business centres rely onthe groundwater due to the limitations of the pipe water supply.


53/79

42

several locations of Jakarta basin usually has a positive correlation with the

registered abstraction volume of groundwater in those locations (Abidin et al.,2004).

Sea level rise in combination with land subsidence due to over exploitation ofground water will definitely move the coastal line to the inland, with an associated

higher risk of floods . A study conducted by Pusat Pengembangan Kawasan Pesisirdan Laut, Institut Teknology Bandung (2007) showed that at a sea level rise of about

0.25, 0.57 and 1.00 cm per year the total area of north Jakarta being inundated byflood in 2050 would be about 40, 45 and 90 km2 respectively, and this will increase

further if land subsidence continues (Figure 40). A similar study conducted byDasanto and Istanto (2007) also indicated that when sea level increases by about 0.5

m and land subsidence continues, parts of six sub-districts of North Jakarta andBekasi will be permanently inundated. In North Jakarta the sub-districts includeKosambi, Penjaringan and Cilincing, and in Bekasi they are Muaragembong,

Babelan and Tarumajaya.

Figure 40. Area being inundated in 2050 under different sea level rise and land subsidencescenarios. Land subsidence is about 0.8 cm per year (Source: PusatPengembangan Kawasan Pesisir Dan Laut ITB, 2007)

SLR: 0.25 cm/year no



SLR: 0.25 cm/year with




54/79


55/79

44

take a huge effort to fill in this gap. May be a concentrated action in the most

vulnerable and valuable nature areas is a way to start. From this report it is clearthat information on the historical impact of climate variability is still limited andstudies on the implications on climate change are only available for a limited

sectors. For example, the implication of climate change on the water quality are yetunknown. Effects on tourism, a serious source of income in Indonesia are also

unknown. Thus many research activities are needed to fill the gaps and to increaseour understanding on climate variability and climate changes and their implications

on sectors.

6.2. Adaptation programs

Climate change is evident in both a change in average temperature and rainfall, as

well as changes in the frequency and severity of extreme weather events, such asfrosts, heat waves, droughts and floods (IPCC 2001). It is considered likely that

continued greenhouse gas emissions at or above current rates will result in furtherglobal warming in this century. Moreover, even if the atmospheric concentrations of

all greenhouse gases and aerosols are stabilized at 2000 levels, global temperaturesare projected to continue rising (IPCC 2007). While measures to reduce the growthof greenhouse gas emissions are an important response to the threat of climate

change, adaptation to climate change will also form a necessary part of the response.

In this context, adaptation refers to strategies that act to reduce the adverse impactsof climate change and also to make benefit from it.

Historical data shows that the Indonesian climate has already changed. Thedirection of change in the future may vary between regions. In Java and Bali, the

pattern of change is similar to changes that occurred in the past. It is very likely thatthe length of the rainy season in these two islands will shorten and the depth ofrainfall in this season tends to become higher than that of the current climate, while

the depth of the dry season rainfall tends to decrease. In addition, the frequency of

extreme climate events associated with ENSO may also increase under globalwarming. Figure 2 suggests that extreme regional weather and climate anomalies

associated with El Nio are being exacerbated by i

Documents

Final Country Report - Climate Change