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Main Supervisor: Prof. YAMASHITA Takao
Sub-Supervisors: a. Prof. HIGO Yasushi
b. Assoc. Prof. KAWAMURA Kensuke
BATINCILA G...
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...
4
January 04, 2011 Gage Height
February 02, 2011 Gage Height
1968 January 17, Gage Height =6.68 m
5
Butuan City: Area - Total 817.28 km2, Population (2010) - 309,709 (379/km2)
West Bank Flood Wall –Completed CY 1999 West B...
29 of 35
Tributary
Contribution
Point Source
Non-Point Source
Withdrawal
Spillway
Inflows:
Tributaries
Point sources
Nonpo...
1. To create a watershed hydrological model
2. To investigate streamflow responses at various
climate change and land use ...
Methodology
1. Data Preparation for Hydrological Model
2. Model Generation and Calibration
3. Future Scenarios Generation
...
Data Sources
1. Physical watershed-specific data
- Digital Elevation Model from USGS HydroSHEDS
- Land Cover Data from Glo...
The Study Area Provinces : 8
Cities: 3
Municipalities: 23
Barangays: 426
Population: 732,359
Popl’n Density: 64 Persons pe...
Digital Elevation Model
Sub-Watersheds, Streams and
Observation Stations
- Observation Stations
- Streams
Processed
by GIS...
Year mm
1999 4,071
2000 3,271
2001 3,536
2002 2,852
2003 3,470
2004 2,685
2005 3,196
2006 3,403
2007 3,529
2008 3,784
2009...
y = 11.381x + 2626.5
1000
2000
3000
4000
5000
6000
GPCC 1901-2009
NCEP/NCAR NMC reanalysis, 1948-2011
PAGASA Hinatuan Stat...
I. Top 10 years, El Nino II. Top 10 years, La Nina
Year mm
1999 3888
1956 3835
1945 3802
1962 3777
1934 3758
1963 3692
200...
Land Cover Description Area, Sq. km.
Mosaic cropland (50-70%) / vegetation (grassland/shrubland/forest)
(20-50%)
4,198
Mos...
TRMM RadarPhilippine Meteorological Stations (PAGASA)
Source of Precipitation Data: TRMM and PAGASA
17
64 Sub-Watersheds
Grouping Sub-Watersheds by
Meteorological Segments
18 Meteorological Segments
Intersect Catchment and Dr...
Graphical and Statistical
Results:
19
A. Hydrograph B. Flow Duration Curve
NSE - Nash-Sutcliffe efficiency, PBIAS - Percen...
Mean Monthly Discharge Flow (cfs) – Simulated vs. Observed
A. Talacogon
C. Prosperidad D. Sibagat
B. Santa Josefa
0
10,000...
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 +...
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 F...
28
A. Effect on maximum flow per season
LULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual
25% 34% 45% 21...
Conclusions and
Recommendations
- It is expected that the study will have significant
implications on water management and...
BATINCILA Glenn
glenn_batincila@yahoo.com
NEDA
Nimfa Tiu Bldg., J. Rosales Avenue
Butuan City
Philippines
Tel No. (+6385) ...
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Agusan River Basin Hydrological Modeling

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In this study, hydrological modeling is conducted for the Agusan River Basin (ARB) in Mindanao, Philippines using the Hydrological Simulation Program-Fortran (HSPF) model. The first major objective is to build the HSPF model and the second investigated the streamflow responses at nineteen (19) critical river outlets subjected to climate change and land use change scenarios.

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  • Greetings – Compliments – Name –Position –Purpose Statement – Signpost – This paper contributes to the scientific understanding of changing hydrology in a large river basin due to climate change and offers baseline information to develop measures for mitigating potential negative impacts
  • My presentation is divided into six (6) sections. Firstly, I’m going to talk about the background of my research followed with the objectives of the study. Then I will discuss about the methodology and data sources. Then I’m going to move on to the results and lastly I’ll focus on the conclusion.
  • The Philippines by virtue of its geographic circumstances is highly prone to natural disasters, such as earthquakes, volcanic eruptions, tropical cyclones and floods, making it one of the most disaster prone countries in the world.On average, the Philippines faces about 20 typhoons annually, with five of them expected to cause major damages to life and property. Typhoons remain the largest killers in the Philippines, followed by earthquakes, volcanoes and floods.Climatic variability combined with human-induced emission of green-house gases result in an increase in global average air and ocean temperatures and alterations in frequency and amount of precipitation from year 2000 to 2100Availability of water supply, reservoir operations, crop production, erosion processes, runoff production and many other hydrological processes are likely to be impacted by climate changeIPCC-DDC 4th Assessment ReportScenario SRA1B. A future world of very rapid economic growth, global population that peaks in mid-century and declines thereafter, and rapid introduction of new and more efficient technologies, with the development balanced across energy sources.Scenario SRB1. A convergent world with the same global population as in the A1 storyline but with rapid changes in economic structures toward a service and information economy, with reductions in material intensity, and the introduction of clean and resource-efficient technologies. Community Climate System Model, version 3.0 (CCSM3) from National Center for Atmospheric Research (NCAR)
  • HSPF is Built on the Stanford Watershed Model (Crawford and Linsley, 1966)HSPF is embedded in the US Environmental Protection Agency’s (EPA) water quality assessment tool, BASINS (Lahlou et al., 1998)The HSPF model mathematically represents the various hydrologic processes as flows and storages.The model consists of three primary modules, PERLND for pervious land, IMPLND for impervious land, and RCHRES for stream reaches, to simulate flow, water quality, and sediment transport in pervious land, impervious land, and streams.The PERLND simulates snow accumulation and melt, the water budget based on interactions among various storages, sediment produced by erosion, and water quality constituents in the dissolved as well as particulate phase.
  • Prediction of probable impacts on water yield from various catchments caused by climate change and land-use change is extremely important for environmental and economic decisions and strategies.In this study, the first major objective is to build a hydrologic model for the ARB watershed and the second major objective is to investigate the streamflow responses at the basin outlet and at the major tributary rivers considering various climate change and land use change scenarios.- The specific objectives of the study are as follows:To delineate the watershed boundary of the Agusan River Basin (ARB). To define a number of sub-basins within the ARB watershed so the hydrologic response to climate change for each of these sub-basins will be used for planning and decision making. To generate streamflow network. To create the land cover and land use map of the ARB for hydrological simulation and to create future land use change scenario. To determine the variability of precipitation intensity within the ARB watershed and its surrounding regions as necessary input for meteorological data. To create the hydrological model of the ARB and define the hydrological streamflow characteristics of the major river (Agusan River) and its major tributary rivers. To create various climate change scenarios and land use change scenario as future conditions of the ARB. To investigate how land-use change or the extension of area affected by man-made intervention, and climate change will affect the hydrological nature in the basin. To provide tools and information to help policy makers, planners and water managers assess and manage the impacts of climate and land use change.
  • Data needs for hydrological simulation is extensive. At a minimum, continuous rainfall records are required to drive the runoff model and additional records of evapotranspiration, temperature, and solar intensity are desirable. The essential geographic information required for simulation are the watershed, the sub-basins, the stream network, the land uses and the ground surface elevations. This information is supplied to the model through GIS.Observed temperature and precipitation data from Tropical Rainfall Measuring Mission (TRMM) with grid increments at 0.25 degrees (27 km) are used as atmospheric forcing.Evapotranspiration data are computed based on daily observed maximum and minimum observed temperature from four (4) observed meteorological stations surrounding the ARBThe digital elevation model is used to delineate the watershed of the ARB and define the river networks.The model is calibrated using four observed sets of river discharge data.The calibrated model is then used to create five (5) projected scenarios based on land use change and probable increase of precipitation intensity and temperature change for future runoff predictions.Significant outputs from the model system for every scenario and for every major stream within the ARB river network are hydrograph, flow duration curves, seasonal flow frequency output, and highest and lowest flow values for a return period of 1, 25, 50, and 100 years. Graphical visualization and statistical analysis are then used to analyze the results.
  • In this study, the DEM is extracted from the USGS HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) which is derived from elevation data of the Shuttle Radar Topography Mission (SRTM) at 3 arc-second resolution.HydroSHEDS has been developed by the Conservation Science Program of World Wildlife Fund (WWF), in partnership with the U.S. Geological Survey (USGS), the International Centre for Tropical Agriculture (CIAT), The Nature Conservancy (TNC), and the Center for Environmental Systems Research (CESR) of the University of Kassel, Germany. Land cover data in the format of GIS shapefile is obtained from the European Space Agency (ESA) GlobCover 2005 project.It is the first 300 m global land cover map for 2005 based on Environmental Satellite Medium Resolution Imaging Spectrometer Instrument (ENVISAT MERIS) launched in 2002 by the European Space Agency (ESA)The existing rain-gauge network over the country is not adequate enough for obtaining accurate spatial rainfall distribution. Therefore, it is necessary to make use of satellite data from TRMM to improve streamflow prediction.The TRMM was launched by the the National Aeronautics and Space Administration (NASA), in cooperation with the Japan Aerospace Exploration Agency (JAXA), in 1997 from the Tanegashima Space Center in Tanegashima, Japan.A series of daily observed temperature from all four meteorological stations, namely, a) Davao City station, b) Butuan City station, d) Malaybalay City station, e) Hinatuan Municipality station, which surrounds the ARB are taken from year 1999 to 2011.
  • - The Agusan River Basin (ARB) is located in Eastern Mindanao and lies at 125°7' E ~ 126°19' E, 7°12' N ~ 9°6' N . It is the third largest river basin in the Philippines and has a total area of 11,979 sq. kilometers. The Agusan River is the third longest river in the Philippines and is the main river which drains the ARB from Compostela Valley area to Butuan City.The river consists of forest headwaters which originate from as high as 2,560 m mountainous environment surrounding the basin and has a total length of 283 km from the mouth of the river to the farthest north streamThe pouring point of the ARB watershed is selected eighteen (18) kilometers upstream from the mouth of the Agusan River so that the hydrological model to be generated will not be influenced by tidal fluctuations.This reduces the study area of the ARB to 11,346 sq. km consisting of sixty seven percent (67%) covered by the province of Agusan del Sur, twenty percent (20%) covered by the province of Compostela Valley.Included in the ARB are three component cities, twenty three municipalities and 426 barangays with a total population of 732,359 persons, 141,894 households and a population density of 64 persons per square kilometers.
  • The DEM from HydroSHEDS is extracted and processed using ArcGIS® hydrology tools and ArcHydro tools and projected at World Geodetic System (WGS) 1984 datum Universal Transverse Mercator (UTM) geographic coordinate system Zone 51N. A spatial analysis was performed to process the digital elevation model and land use/land cover (LULC) in the study area.The watershed boundary is first delineated using the hydrology tool. The pouring point of the watershed is selected approximately twenty (20) kilometres upstream from the shoreline boundary so that tidal influence will not affect the model simulation.The stream network delineation is then processed using ArcHydro tools with 125 square kilometres considered as the river threshold which represents one percent (1%) of the maximum flow accumulation. The DEM shows that the highest elevation of the ARB reaches as high as 2,558 m (8,400 ft) above mean sea level. These mountainous areas can be found at the northern side, western side and the southern side of the watershed. For this research, the ARB is divided into sixty-four (64) sub-basins with 125 square kilometers as the minimum drainage area.The main criteria for selecting these sub-basins are the location of river gauging stations, the resolution of the precipitation data from TRMM, the location of the river gauging stations, and the level of information required at the sub-basin level.
  • Precipitation modelling is included in this study to characterize the precipitation annual distribution within the ARB watershed and its neighbouring region in the entire Mindanao island.A total of 500 TRMM datasets at 0.25° interval for the entire Mindanao area are downloaded and the total annual precipitation for each dataset is computed.Using ArcGIS® spline interpolation tool, the isohyetal map in unit mm is plotted from year 1999 to 2010 to serve as sufficient duration to encompass a range of climatic variations such as El Niño and La Niña condition. The figure reveals that the eastern side of Mindanao, especially the ARB, experiences a relatively high amount of total annual rainfall compared to the western side of Mindanao.On the average, the ARB receives an annual precipitation of 3,400 mm (134 in) for the eleven year period from 1999 to 2010 with 3,200 mm (126 in) during La Niña condition in 2005 and 2010 and as low as 2,700 mm (106 in) in 2004 and with as high as 4,100 mm (160 in) during El Niño condition in year 1999.Precipitation data from the PAGASA stations near the ARB show that region normally experience high precipitation in the months of January and February. This phenomenon is triggered by trade winds blowing from the Pacific Ocean.
  • 42. Evergreen Forest - Areas dominated by trees where 75 percent or more of the tree species `maintain their leaves all year. Canopy is never without green foliage.43. Mixed Forest - Areas dominated by trees where neither deciduous nor evergreen species represent more than 75 percent of the cover present. 51. Shrubland - Areas dominated by shrubs; shrub canopy accounts for 25-100 percent of the cover. Shrub cover is generally greater than 25 percent when tree cover is less than 25 percent. Shrub cover may be less than 25 percent in cases when the cover of other life forms (e.g. herbaceous or tree) is less than 25 percent and shrubs cover exceeds the cover of the other life forms.
  • The hydrological analysis is performed using the EPA BASINS 4 WinHSPF Program.The resulting model is calibrated using four (4) observed sets of river gauging data.Statistical analysis is performed to determine the accuracy of the model.
  • The overall simulation period is run from January 1999 to May 2011.Calibration however is limited from CY2005 to CY2010 depending on the availability of the data on the gauging stationGraphical as well as statistical measures are used to calibrate the modelManual calibration is applied to keep the observed and simulated mean flow values of the reaches as close as possible.Values of various parameters for HSPF calibration are selected based on the guidance provided in a BASINS technical note and on land use, agricultural activity, literature values, and slope and soil characteristicsAs observed data on high flow values has a high degree of uncertainty it is not practical to make use of automatic calibration since it involves comparing the total annual flow values of the observation and simulation results.Hydrographs, flow duration curves and scatter plot are used for graphical visualization of the results.While the model considers hourly data to run, perfectly calibration is entirely impossible since observed values are only measured once daily and the unavailability of sophisticated instrument to accurately/automatically measure streamflow data.
  • This figure shows the comparison between the mean monthly discharges for the periods 1999-2011 in all simulated values and from the period 2005 to 2010 for observed values. Simulated flows are generally larger than observed flows during low-flow conditions, and are smaller than observed values for high-flow conditions.
  • The potential impact of climate change on the occurrence of extreme precipitation change, temperature change and land-use scenarios are investigated Major output include flow duration curves, flow frequency grid statistics and seasonal flow values. Weather scenarios based on IPPC Task Group on Data and Scenario Support for Impacts and Climate Analysis (TGICA) recommendations is used (IPCC-TGICA, 2007)Scenario 1 - Twenty percent (20%) increase in precipitation to simulate extreme wet conditionScenario 2 - Scenario 1 combined with two degree Celsius (2oC) change in temperature to simulate extreme wet condition and global warmingScenario 3 can be justified based on global circulation models - Global Precipitation Climatology Centre (GPCC) and ECHAM 5Land use change scenario adopted in the study consists mainly of the conversion of all forestland to agricultural land. This extreme and worst-case scenario is considered for the study as this condition was experienced by the neighboring region. Another important point to be emphasized in this study is the effectiveness of the forest in regulating streamflows.
  • - All the five scenarios are considered for predicting future streamflow in the four gauging stations and 14 subbasins as rivers in these subbasins are the major source for agricultural production
  • A 20% increase in precipitation will increase the average annual maximum, mean and minimum flow by 33%, 35% and 10%, respectively.Land use change has a much greater impact on the maximum and minimum flow values than on the mean flow.Conversion of all forestland to agricultural land will not significantly alter the streamflow mean value but it will increase the peak flow by as much as 77% of the maximum flow will decrease the minimum flow by as much as 21%.Reduction of precipitation by 50% will result to reduction of maximum, mean and minimum flow from 60% to 80%.Scenario 5 will result in an increase of maximum flow values by almost twice that in Scenario 1 and Scenario 2. Therefore, Scenario 5 is the critical scenario for the assessment of risks associated with the occurrence of floods in the basin. For the analysis of drought situation in the basin, Scenario 3 and Scenario 5 are the critical scenarios.
  • Summary of the Main Points…
  • Transcript of "Agusan River Basin Hydrological Modeling"

    1. 1. Main Supervisor: Prof. YAMASHITA Takao Sub-Supervisors: a. Prof. HIGO Yasushi b. Assoc. Prof. KAWAMURA Kensuke BATINCILA Glenn M102607 Philippines 1 ydrological Modeling of the Agusan River Basin in Mindanao with Projected Climate Change and Land Use Change Scenarios H
    2. 2. Outline 1. Background 2. Objectives of the Study 3. Methodology 4. Data Sources 5. Results 6. Conclusion 2
    3. 3. - 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. 4. 4
    5. 5. January 04, 2011 Gage Height February 02, 2011 Gage Height 1968 January 17, Gage Height =6.68 m 5
    6. 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 6
    7. 7. 29 of 35 Tributary Contribution Point Source Non-Point Source Withdrawal Spillway Inflows: Tributaries Point sources Nonpoint source Spillways Withdrawal Hydrological Simulation Program - Fortran (HSPF)
    8. 8. 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
    9. 9. Methodology 1. Data Preparation for Hydrological Model 2. Model Generation and Calibration 3. Future Scenarios Generation 4. Analysis of Impact and Vulnerability + Recommendation 9
    10. 10. 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
    11. 11. The Study Area Provinces : 8 Cities: 3 Municipalities: 23 Barangays: 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 %
    12. 12. Digital Elevation Model Sub-Watersheds, Streams and Observation Stations - Observation Stations - Streams Processed by GIS 12
    13. 13. Year mm 1999 4,071 2000 3,271 2001 3,536 2002 2,852 2003 3,470 2004 2,685 2005 3,196 2006 3,403 2007 3,529 2008 3,784 2009 3,873 2010 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
    14. 14. y = 11.381x + 2626.5 1000 2000 3000 4000 5000 6000 GPCC 1901-2009 NCEP/NCAR NMC reanalysis, 1948-2011 PAGASA Hinatuan Station (Observed) NOAA, GFDL CM2.0 Linear (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. 1,000 2,000 3,000 4,000 5,000 1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 2022 2025 2028 2031 2034 2037 2040 2043 2046 2049 2052 2055 2058 2061 2064 2067 2070 2073 2076 2079 2082 2085 2088 2091 2094 2097 2100 Total Annual Rainfall (mm) from ECHAM5 GCM 14
    15. 15. I. Top 10 years, El Nino II. Top 10 years, La Nina Year mm 1999 3888 1956 3835 1945 3802 1962 3777 1934 3758 1963 3692 2009 3592 1908 3576 1926 3571 1910 3562 a. GPCC Year mm 1941 1752 1992 2024 1903 2056 1940 2077 1998 2120 1991 2154 1983 2224 1915 2233 1905 2245 1914 2252 a. GPCC Year mm 2063 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 mm 2043 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
    16. 16. 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
    17. 17. TRMM RadarPhilippine Meteorological Stations (PAGASA) Source of Precipitation Data: TRMM and PAGASA 17
    18. 18. 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
    19. 19. 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
    20. 20. Mean Monthly Discharge Flow (cfs) – Simulated vs. Observed A. Talacogon C. Prosperidad D. Sibagat B. Santa Josefa 0 10,000 20,000 30,000 40,000 50,000 60,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec TALACOGON (Observed) RCH57 (Simulated) 0.00 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 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec SANTA JOSEFA (Observed) RCH50 (Simulated) 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec PROSPERIDAD (Observed) RCH8 (Simulated) 0.00 500.00 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 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec SIBAGAT (Observed) RCH2 (Simulated) s 20
    21. 21. Sibagat River 21
    22. 22. Agusan River: Poblacion, Talacogon Section 22
    23. 23. Gibong River: Brgy. Maug, Prosperidad Section 23
    24. 24. Lower Maanat River 24
    25. 25. 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)
    26. 26. A. Major Irrigation Facilities B. ARB Sub-Watersheds 26
    27. 27. 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. 28. 28 A. Effect on maximum flow per season LULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual 25% 34% 45% 21% 39% 35% 50% 45% 59% 31% 48% 46% 100% 60% 77% 43% 51% 58% B. Effect on mean flow per season LULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual 25% 35% 16% 4% 31% 21% 50% 34% 18% 7% 30% 22% 100% 31% 7% -7% 24% 14% C. Effect on minimum flow per season LULC Jan, Feb, Mar Apr, May, Jun Jul, Aug, Sep Oct, Nov, Dec Annual 25% 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
    29. 29. 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.
    30. 30. BATINCILA Glenn glenn_batincila@yahoo.com NEDA Nimfa Tiu Bldg., J. Rosales Avenue Butuan City Philippines Tel No. (+6385) – 342-5774 どうも有り難う御座います Marami pong salamat ! 30
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