1. BMKG
Drought monitoring and mapping in Indonesia under current and future climate conditions
Mamenun1, Ronald Vernimmen2 ,
1 Meteorological Climatological and Geophysiscal Agency of Indonesia (BMKG)
Jl. Angkasa I No. 2 , Jakarta Indonesia
2 Deltares, P.O.Box MH, Delft, the Netherlands
International workshop on the Digitation of Historical Climate Data, the new SACA&D Database and Climate Analysis in the Asian Region, Citeko 2-5 April 2012

2. Outline Background Joint Cooperation Program (JCP)
Drought Monitoring & Mapping
a. Using ground stations
b. Using sattellite observations
Validation TRMM satellite data withground stations
Monthly average
Monthly deficit precipitation
Next steps
Agroclimatic mapping
Drought occurance in the future
Summary
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3. Background

4. Joint Cooperation Programme
21 april 2017
Joint Cooperation Programme
Joint Cooperation Program
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PusAir
KNMI
Deltares
Component A;
General Institutional Development
Component B;
Collborative Development of Customized and Standardized IWRM tools and Approaches
Component C; Supporting the Development of Consistent Datasets
Component D;
Operational Management Support: Drought and Flood Monitoring and Warning
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5. Joint Cooperation Programme
21 april 2017
Joint Cooperation Programme
JCP Framework
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6. Building DEWMS Indonesia
21 april 2017
Building DEWMS Indonesia
System based on Delft-OMS = Delft-FEWS
Open Shell Forecasting System
System for operational forecasting (resilience !)
Fully configurable by users (Open Interface to models and data)
Platform for operational research (Short cycle from research to operations)
Java, PostgreSQL/Oracle, Jboss, XML
Operating system independent, very scalable
Toolbox for development of forecasting systems
Highly modular structure – independent modules provide functionality
Rapid implementation, scalable & flexible
Automatic / manual & stand alone
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7. Building DEWMS Indonesia
21 april 2017
Building DEWMS Indonesia
Concept
Delft-OMS
import
validation
transformation / interpolation
data hierarchy
general adapter
export / report
administration (data, forecasts)
viewing (data, forecasts)
archiving …
data feeds PI
import
models
export &
dessimination
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8. Building DEWMS Indonesia
21 april 2017
Building DEWMS Indonesia
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9. Drought monitoring & mapping
21 april 2017
Drought monitoring & mapping
A. Using Ground Stations
As a pilot, for the Pemali Comal catchment in Central Java, manual ground measurements of rainfall serve as input for calculation of the Standardized Precipitation Index (SPI).
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10. Drought monitoring & mapping
21 april 2017
Drought monitoring & mapping
A key feature of the SPI is the flexibility to measure drought at different time scales.
Short term droughts of 1 month (SPI-01) defined by specific regional climatology;
Agricultural important droughts over 3 to 6 months (SPI-03, SPI-06) resulting in deficits in soil moisture;
Longer term droughts (months to years) have impact on surface and groundwater supplies.
The severity of a drought can be compared to the average condition for a particular station or region. Values range from 2.00 and above (extremely wet) to and less (extremely dry) with near normal conditions ranging from 0.99 to
SPI value;
Drought Category;
2.00 and above
Extremely wet
1.50 to 1.99
Very wet
1.00 to 1.49
Moderately wet
-0.99 to 0.99
Near Normal
-1.00 to -1.49
Moderately dry
-1.50 to -1.99
Severely dry
-2.00 and less
Extremely dry
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11. Drought monitoring & mapping
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Drought monitoring & mapping
Timeseries for individual stations are calculated
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12. Drought monitoring & mapping
SPI-1
SPI-3
SPI-6
SPI-12
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(April 2007)

13. Drought monitoring & mapping
21 april 2017
Drought monitoring & mapping
B. Using Satellite Observations
Validation of TRMM 3B42RT (TMPA) satellite data with ground stations on monthly basis
Location
Rain gauge
TRMM Grid Cell
Jakarta 10 3
Bogor 4
Bandung 13
Banjarbaru 15 6
East Java
Lampung 5
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Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia,
Hydrol. Earth Syst. Sci., 16, , doi: /hess , 2012.

14. Drought monitoring & mapping
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Drought monitoring & mapping
Correction Factor:
TRMMCorr= 3.20 TRMM 0.79
Validation Region
Ground Stations
TMPA
TMPA bias corr P
Avg.diff
Rel. bias
RMSE R2
Jakarta
2010
1865
-145
-7.2
83.8
0.84
1918
-92
-4.6
78.2
Bogor
3056
2944
-112
-3.7
94.9
0.83
2845
-211
-6.9
79.8
Bandung
1723
1936
213
12.3
85.8
1965
242
14.0
71.6
0.86
East Java
2106
1835
-271
-12.8
56.0
0.95
1819
-287
-13.6
49.3
0.96
Banjar Baru
2208
2217 9
0.4
59.6
2303 95
4.3
0.85
Lampung
1946
2191
244
12.6
0.89
2200
254
13.1
63.6
0.90
Annual ground station and TMPA 3B42RT comparison before and after bias correction of TMPA 3B42RT precipitation estimates over the period 2003–2008.
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Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia,
Hydrol. Earth Syst. Sci., 16, , doi: /hess , 2012.

15. Drought monitoring & mapping
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Drought monitoring & mapping
Validation Region
Ground Stations
TMPA
TMPA bias corr P
Avg.diff
Rel. bias
RMSE R2
Jakarta
319
276
-43
-13.5
50.5
0.62
340 21
6.6
51.2
0.65
Bogor
715
539
-176
-24.6
72.9
0.78
604
-111
-15.5
64.1
0.79
Bandung
286
204
-82
-28.7
33.9
0.87
265
-21
-7.3
29.7
East Java
166 75
-91
-55.1
31.8
0.91
114
-52
-31.3
23.6
0.92
Banjar Baru
462
467 5
1.0
36.0
0.85
551 89
19.3
40.2
Lampung
367
255
-121
-30.3
39.9
0.71
336
-8.4
32.2
0.77
Dry season (June–October) ground station and TMPA 3B42RT comparison before and after bias correction of TMPA 3B42RT precipitation estimates over the period 2003–2008.
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Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia,
Hydrol. Earth Syst. Sci., 16, , doi: /hess , 2012.

16. Drought monitoring & mapping
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Drought monitoring & mapping
Validation result
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Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia,
Hydrol. Earth Syst. Sci., 16, , doi: /hess , 2012.

17. Drought monitoring & mapping
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Drought monitoring & mapping
Validation result
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18. Drought monitoring & mapping
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Drought monitoring & mapping
TRMM satellite data are used for improved rainfall monitoring and assessing the current drought status.
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TRMM 3B42RT satellite precipitation (in mm) over Indonesia on 28 March :00 WIB.

19. Drought monitoring & mapping
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Drought monitoring & mapping
TRMM 3B42RT satellite precipitation aggregated to monthly totals are bias corrected using the method described in Vernimmen et al. 2012*, based on validation of TRMM 3B42RT with ground stations.
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Bias corrected TRMM 3B42RT satellite precipitation (in mm) over Indonesia in March 2012.
*Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, , doi: /hess , 2012.

20. Drought monitoring & mapping
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Drought monitoring & mapping
Climatology (monthly average) from corrected TRMM3B42RT
Monthly average on March 2012.
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21. Drought monitoring & mapping
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Drought monitoring & mapping
Climatology of corrected monthly TRMM 3B42RT is used to calculate ‘Sifat Hujan’ (monthly rainfall compared to long-term average).
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‘Sifat Hujan’ March Yellow is normal conditions, orange is drier while green is wetter compared to long-term average

22. Drought monitoring & mapping
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Drought monitoring & mapping
Monthly precipitation deficit is calculated. For evaporation, currently the CGIAR-PET* monthly dataset multiplied with a fixed crop factor of 0.8 is used.
Global CGIAR-PET is a modelled dataset (1 km resolution) using data available from WorldClim Global Climate Data over the period
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Precipitation deficit in March The precipitation deficit needs to be linked to drought indicators for different agricultural crops *

23. Drought monitoring & mapping
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Drought monitoring & mapping
Deficit precipitation on watershed basin (DAS) for java location
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March 2012 *

24. Drought monitoring & mapping
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Drought monitoring & mapping
Next Steps :
Using the TRMM 3B42RT satellite precipitation the following will also be implemented (in progress):
Onset of dry season, defined as 3 consecutive decadal (10-day) periods with precipitation < 50 mm
Similarly, onset of the wet season
3. SPI
4. Peat fire forecasting (through running a peatland water budget model; ground water table depth is a better indicator for fire risk then precipitation alone)
Other suggestions?
ECMWF Seasonal Forecast data will be utilized in the near future as well.
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25. Agroclimatic mapping using satellite observations
Oldeman agroclimatic maps for Indonesia based on corrected monthly TRMM satellite precipitation.
Classification based on number of wet and dry months in a year.
Wet month = long term average > 200 mm
Dry month = long term average < 100 mm
Historical maps (1980’s) based on ground stations measurements and used by ‘Pertanian’ (Ministry of Agriculture)
Oldeman, L. R., Las, I., and Darwis, S. N.: An agroclimatic map of Sumatra, Contributions, Central Research Institute for Agriculture, Bogor, No. 52, 35 pp., 1979.
Oldeman, L. R., Las, I., and Muladi: The agroclimatic maps of Kalimantan, Maluku, Irian Jaya and Bali, West and East Nusa Tenggara, Contributions, Central Research Institute for Agriculture, Bogor, No. 60, 32 pp., 1980.
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26. Oldeman classification
5 main zones
A has more than 9 consecutive wet months. Wetland rice can be cultivated any time of the year.
B has 7-9 consecutive wet months. Two wetland rice crops can be cultivated during this period.
C has 5-6 consecutive wet months. Two rice crops can be cultivated only, if the first rice crop is planted (or sown) as a dry land crop (so-called gogorancah system).
D has 3-4 consecutive wet months. Only one wetland rice crop is generally possible.
E has less than 3 consecutive wet months. Without additional water from irrigation, wetland rice is not recommended.
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27. Oldeman classification
These 5 main zones are subdivided based on length of dry season
1 less than 2 dry months. No restrictions are expected with regard to available water.
2 2-3 dry months. Careful planning is needed to grow crops throughout the year.
3 4-6 dry months. A fallow period is part of the rotation system because of water constraints.
4 7-9 dry months. Only one crop can successfully be cultivated. The remainder of the year is too dry.
5 more than 9 consecutive dry months. Areas in this subzone are generally not suitable for any cultivation of arable crops.
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28. Oldeman map Indonesia Oldeman agroclimatic map based
on bias corrected monthly
TRMM 3B42RT (left) compared to
historical map (right) for Kalimantan
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29. Oldeman map Indonesia
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30. Schmidt-Ferguson Climatic map
Similarly, the Schmidt-Ferguson (1951) climatic map is generated.
Different definition of dry and wet month!
dry: < 60 mm (whereas Oldeman < 100 mm)
wet: > 100 mm (whereas Oldeman > 200 mm)
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31. Drought occurrence in the future
Precipitation datasets from different Global Circulation Models (GCMs) under different IPCC scenario’s will be processed using Delft-OMS and will be used to generate precipitation change, drought occurance, Oldeman maps, etc.
These maps will help create an understanding of future drought vulnerabilities (which areas in Indonesia are vulnerable to climate change?) and will prepare for climate proofing of agricultural and water supply systems.
The following GCM’s will be considered:
Model
Institute
Country
Acronym
BCM2.0
Bjerknes Centre for Climate Research
Norway
BCCR
CGCM3.1
Canadian Centre for Climate modelling and Analysis
Canada
CCCMA
CGCM2.3.2
Meteorological Research Institute
Japan
CGCM
CSIRO-Mk3.0
Commonwealth Scientific and Industrial Research Organisation
Australia
CSIRO
ECHAM5
Max Planck Institute
Germany
ECHAM
ECHO-G
Freie Universität Berlin
Berlin
ECHO
GFDLCM 2.0
Geophysical Fluid Dynamics Centre
USA
GFDL
GISS ER
Goddard institute for Space Studies
GISS
IPSL CM4
Institute Pierre Simon Laplace
France
IPSL
MIROC3.2
Center of Climate System Research
MIROC
NCAR PCMI
National Center for Atmospheric Research
NCAR
HadGEM2
Met Office’s Hadley Centre for Climate Prediction UK
HADGEM
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32. Summary
Drought monitoring and mapping both using ground stations and validated sattellite observation has been made as part of the development of Drought Early Warning and Mapping System
The average monthly and characteristic of climatology (sifat hujan), deficit rainfall in Indonesia and java’s watershed basin is calculated based on the corrected satellite data
The correction sattellite data will be applied on calculating SPI index, decadal precipitation for wet and dry onset, peat fire forecasting, and climate type
ECMWF Seasonal Forecast data will be utilized in the near future as well.
The climate scenario will be applied to project the drought occurance in the future
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33. 21 april 2017
Thank You
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