Main Supervisor: Prof. YAMASHITA Takao

Sub-Supervisors: a. Prof. HIGO Yasushib. Assoc. Prof.

KAWAMURA Kensuke

BATINCILA GlennM102607

Philippines

1

ydrological Modeling of the Agusan River Basin in

Mindanao with Projected Climate Change and

Land Use Change Scenarios

H

Outline

1. Background

2. Objectives of the Study

3. Methodology

4. Data Sources

5. Results

6. Conclusion

2

- Agricultural production, availability of water supply and many

other hydrological processes are likely to be impacted by climate change (Gleick, 1987, Revelle and Waggoner,1983)

- The Philippines is one of the most disaster prone countries in the

world (World Bank and National Disaster Coordination Council (NDCC), 2004).

- 20 typhoons hit the country annually (WB).

Background

- Projections from the IPCC show significant global warming and

alterations in frequency and amount of precipitation from year 2000 to 2100 (Hengeveld, 2000; Le Treut et al., 2007; Mearns et al.,2007)

- Understanding changes in spatial and temporal variations of runoff in a large river basin is important to develop measures for mitigating potential negative impacts.

3

http://en.wikipedia.org/wiki/File:Tropical_cyclones_1945_2006_wikicolor.png

Scenario AIB Scenario B1

4

2011 January 04

2011 February 02

5

January 04, 2011 Gage Height

February 02, 2011 Gage Height

1968 January 17, Gage Height =6.68 m

6

Butuan City: Area - Total 817.28 km2, Population (2010) - 309,709 (379/km2)

West Bank Flood Wall –Completed CY 1999 West Bank Flood Wall –Completed 2007

29 of 35

Tributary Contribution

Point SourceNon-Point Source

Withdrawal

Spillway

Inflows:TributariesPoint sourcesNonpoint source

Spillways

Withdrawal

Hydrological Simulation Program - Fortran (HSPF)

1. To create a watershed hydrological model

2. To investigate streamflow responses at

various

climate change and land use change

scenarios

Objectives of the Study

3. To help policy makers and planners assess

and

manage the impacts of climate and land

use change.

…In the Agusan River Basin

Methodology

1. Data Preparation for Hydrological Model

2. Model Generation and Calibration

3. Future Scenarios Generation

4. Analysis of Impact and

Vulnerability

+ Recommendation

9

Data Sources

1. Physical watershed-specific data

- Digital Elevation Model from USGS

HydroSHEDS

- Land Cover Data from GlobCover

2. Meteorological Data

- Precipitation data from TRMM satellite

- Observed Temperature data from PAGASA

3. River Discharge Observation Data from the

DPWH– BRS

10

- HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales)- TRMM (Tropical Rainfall Measuring Mission) - PAGASA (Philippine Atmospheric, Geophysical and Astronomical Services Administration)- DPWH-BRS (Department of Public Works and Highways-Bureau of Research and Standards

The Study Area

Provinces : 8 Cities: 3 Municipalities: 23Barangays: 426 Population: 732,359 Popl’n Density: 64 Persons per Sq. km No. of households: 141,894

River Basin Area km2.

　 1. Cagayan

27,712

　 2. Cotabato

20,065

　 3. Agusan

11,979

　 4. Pampanga

9,488

11

1

4

3

2- 45 %

- 18 %

- 37 %

- 0.12 %

- 0.48 %

Digital Elevation Model

Sub-Watersheds, Streams and Observation Stations

- Observation Stations- Streams

Processed by GIS

12

Year mm1999 4,0712000 3,2712001 3,5362002 2,8522003 3,4702004 2,6852005 3,1962006 3,4032007 3,5292008 3,7842009 3,8732010 3,202

Annual Ave ． 3,406

Annual Precipitation Variability (1999-2010) in the Agusan River Basin (mm unit)

MEI – Multi-Variate ENSO Index 　 Red indicates positive (warm) phase while blue indicates negative (cold) phase.

Annual Precipitation, mm

Butuan

Hinatuan

Malaybalay

Davao

(from Philippine Meteorological Stations)

13

1901 1907 1913 1919 1925 1931 1937 1943 1949 1955 1961 1967 1973 1979 1985 1991 1997 2003 2009 2015 2021 2027 2033 2039 2045 2051 2057 20631000

2000

3000

4000

5000

6000

f(x) = 11.3807453161553 x + 2626.52381314561

GPCC 1901-2009NCEP/NCAR NMC reanalysis, 1948-2011PAGASA Hinatuan Station (Observed)NOAA, GFDL CM2.0Linear (NOAA, GFDL CM2.0)

Annual Precipitation from 1901 to 2065 (Models and Observed)

Result: Precipitation is expected to increase by 10% or more a few decades from now.

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 21001,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000

Total Annual Rainfall (mm) from ECHAM5 GCM

14

I. Top 10 years, El Nino II. Top 10 years, La Nina

Year mm1999 38881956 38351945 38021962 37771934 37581963 36922009 35921908 35761926 35711910 3562

a. GPCC

Year mm1941 17521992 20241903 20561940 20771998 21201991 21541983 22241915 22331905 22451914 2252

a. GPCC

Year mm2063 4,729 2001 4,633 2025 4,603 2084 4,515 1980 4,480 2099 4,460 2051 4,410 2007 4,384 1966 4,374 2062 4,370

b. ECHAM5b. ECHAM5

Year mm2043 1,427 1990 1,485 1962 1,936 2057 2,199 1979 2,380 1997 2,431 2083 2,544 2032 2,548 2024 2,612 2073 2,647

15

Land Cover Description Area, Sq. km.Mosaic cropland (50-70%) / vegetation (grassland/shrubland/forest) (20-50%)

4,198

Mosaic vegetation (grassland/shrubland/forest) (50-70%) / cropland (20-50%)

433

Built-up Area 14 Closed to open (>15%) (broadleaved or needleleaved, evergreen) shrubland (<5m)

111

Closed to open (>15%) broadleaved evergreen (>5m) 4,452 Mosaic forest or shrubland (50-70%) / grassland (20-50%) 116 Post-flooding or irrigated croplands (or aquatic) 4 Rainfed croplands 2,087 Water bodies 55 Total Area 11,471

Land Use Description Area, Sq. km.Residential 14 Evergreen Forest Land 5,113 Shrub and Brush Rangeland 4,198 Cropland and Pasture 2,092 Streams and Canals 55

Total Area 11,471

Lad Cover and Land Use Summary Table

16

TRMM RadarPhilippine Meteorological Stations (PAGASA)

Source of Precipitation Data: TRMM and PAGASA96

km

114 km

132 km

164

km

136 km

17

64 Sub-Watersheds

Grouping Sub-Watersheds by Meteorological Segments

18 Meteorological Segments

Intersect Catchment and Drainage with Land Use and Meteorological Data

a. Cropland Areas 63 b. Forest Areas 64 c. Built-up Areas 14 c. Shrub and Brush 64 d. Streams 21

Total 226 operations

18

Graphical and Statistical Results:

19

A. Hydrograph B. Flow Duration Curve

NSE - Nash-Sutcliffe efficiency,  PBIAS - Percent bias, RMSE-observations standard deviation ratio (RSR),r – Correlation coefficient, R Squared – Coefficient of determination

Mean Monthly Discharge Flow (cfs) – Simulated vs. Observed

A. Talacogon

C. Prosperidad D. Sibagat

B. Santa Josefa

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

10,000

20,000

30,000

40,000

50,000

60,000

TALACOGON (Observed) RCH57 (Simulated)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0.00

1,000.00

2,000.00

3,000.00

4,000.00

5,000.00

6,000.00

7,000.00

8,000.00

9,000.00

SANTA JOSEFA (Observed) RCH50 (Simulated)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

PROSPERIDAD (Observed) RCH8 (Simulated)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0.00

500.00

1,000.00

1,500.00

2,000.00

2,500.00

3,000.00

3,500.00

4,000.00

4,500.00

5,000.00

SIBAGAT (Observed) RCH2 (Simulated)

s 20

Sibagat River

21

Agusan River: Poblacion, Talacogon Section

22

Gibong River: Brgy. Maug, Prosperidad Section

23

Lower Maanat River

24

Climate Change and Land Use Change Scenarios

s 25

1. Scenario 1 ( +20% to Precipitation)

2. Scenario 2 ( Scenario 1 with +2 °C to Temp.)

3. Scenario 3 (Precipitation -50%)

4. Scenario 4 (LULC Change)

5. Scenario 5 (Scenario 4 + Scenario 2)

A. Major Irrigation Facilities B. ARB Sub-Watersheds

26

A. Changes on Maximum Flow

Seasonal Average Percent Changes by Scenario

27

C. Changes on Minimum Flow

B. Changes on Mean Flow

1. Scenario 1 ( +20% to Precipitation)

2. Scenario 2 ( Scenario 1 with +2 °C to Temp.)

3. Scenario 3 (Precipitation -50%)

4. Scenario 4 (LULC Change)

5. Scenario 5 (Scenario 4 + Scenario 2)

28

A. Effect on maximum flow per seasonLULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual25% 34% 45% 21% 39% 35%50% 45% 59% 31% 48% 46%100% 60% 77% 43% 51% 58%

　 　 　 　 　 　B. Effect on mean flow per seasonLULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual25% 35% 16% 4% 31% 21%50% 34% 18% 7% 30% 22%100% 31% 7% -7% 24% 14%

　 　 　 　 　 　C. Effect on minimum flow per seasonLULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual25% 12% -13% -3% 19% 4%50% 8% -14% -4% 14% 1%100% 4% -21% -13% 11% -5%

Twenty percent (20%) increase in precipitation combined with two degree Celsius (2°C) increase in temperature and Land use Change

Conclusions and Recommendations

- It is expected that the study will have significant implications on water management and land use planning.

- The ARB is highly vulnerable to climate change and land use change.

- Appropriate water resources policies, management and infrastructures should be adopted to meet the future challenges.

29

- In the future, a more precise discharge data and model validation are expected as advancements to improve the hydrological prediction.

BATINCILA Glennglenn_batincila@yahoo.comNEDANimfa Tiu Bldg., J. Rosales AvenueButuan City PhilippinesTel No. (+6385) – 342-5774

どうも有り難う御座いますMarami pong salamat !

30