The document summarizes hydrological modeling studies conducted to evaluate flood control dams in the Marikina River Basin in the Philippines. The studies used the SWATCH rainfall-runoff model to simulate floods from Tropical Storm Ondoy and other return periods. Flood routing studies then analyzed single dams and cascades of dams at various locations. Results showed dams could attenuate flood peaks and volumes, with the cascade alternative providing the most reduction in downstream flooding.

1. HYDROLOGICAL MODELING STUDIES FOR PROPOSED FLOOD-
CONTROL DAMS IN THE MARIKINA RIVER BASIN
Leonardo Q. Liongson
Team Energy Professorial Chair
& Professor, Institute of Civil Engineering and National Hydraulic Research Center, University of the
Philippines, Diliman, Quezon City, Philippines
Abstract
Tropical Storm Ondoy (Ketsana) crossed Metro Manila and the adjacent river basins in a late wet-season
episode of 2009, starting in the evening of September 25, 2009 and continuing into the next day of
September 26, 2009. TS Ondoy brought very intense and heavy rainfall to the region - record amounts of
rains fell over a very short time period of 12 hours to 24 hours, which are estimated to occur at an average
annual frequency of 1 in 100 years or even higher, depending on the measuring location in the region. The
rains generated record-magnitude flood flows and inundation in the Pasig-Marikina River Basin in Metro
Manila, and the Laguna de Bay region. This paper describes the application of the distributed watershed
rainfall-runoff model SWATCH in order to simulate the TS Ondoy floods and other floods of lower return
periods (2 years to 100 years) in the upper Marikina River Basin, using as input the spatially-interpolated
rainfall network data and available topographic, soil/geology and river-geometry data. The SWATCH
model consists of a tree-network of several variable rectangular surface/soil/aquifer storage nodes and
overland/channel flow links, with accounting of soil moisture, evapotranspiration, infiltration, and recharge
to groundwater, and routing of overland and channel flows, interflow and baseflow into aggregated total
streamflows. Using the model-computed inflow flood hydrographs, the options of single or cascade of
flood-control storage dams (with selected reservoir-storage and spillway capacities) for attenuation of
floods peaks and volumes, and downstream flood hazard reduction are initially evaluated by flood-routing
studies.
Introduction
Tropical Storm Ondoy (Ketsana) crossed Metro Manila and the adjacent river basins in a late wet-season
episode of 2009, starting in the evening of September 25, 2009 and continuing into the next day of
September 26, 2009. TS Ondoy brought very intense and heavy rainfall to the region - record amounts of
rains fell over a very short time period of 12 hours to 24 hours, which are estimated to occur at an average
annual frequency of 1 in 100 years or even higher, depending on the measuring location in the region. The
rains generated record-magnitude flood flows and inundation in the Pasig-Marikina River Basin in Metro
Manila, and the Laguna de Bay region. The hydrological and hydraulic aspects of the Ts Ondoy (Ketsana)
extreme event (storm rainfall, floods) were described previously by the author (Liongson, 2010) and the
flood management alternatives were also discussed in the same article.
With the purpose of evaluating the performance of the proposed flood mitigation measure which is a high
Marikina Dam or else a cascase of two or three flood-control dams, the two hydrological modeling
applications for the upper Marikina River Basin were undertaken, as reported in this paper:
(1) The application of the distributed watershed rainfall-runoff model SWATCH in order to simulate the TS
Ondoy floods and other floods of lower return periods (2 years to 100 years) in the upper Marikina River
Basin, using as input the spatially-interpolated rainfall network data and available topographic, soil/geology
and river-geometry data. The SWATCH model consists of a tree-network of several variable rectangular
surface/soil/aquifer storage nodes and overland/channel flow links, with accounting of soil moisture,
evapotranspiration, infiltration, and recharge to groundwater, and routing of overland and channel flows,
interflow and aquifer return flow (baseflow) into aggregated total streamflows;
(2) The flood routing studies wherein, by using the model-computed inflow flood hydrographs, and
selecting the options of single or cascade of flood-control storage dams (with selected reservoir-storage and

2. spillway capacities), the attenuation of floods peaks and flood volumes and the downstream flood hazard
reduction are initially evaluated.
The SWATCH Model
SWATCH is a mathematical distributed watershed model developed by Morel-Seytoux et. al. (1987) to
physically simulate a stream-aquifer system for a storm event. SWATCH utilizes basin division in order to
model spatial variability. Rainfall in different rainfall stations is then distributed to these divisions by
means of weights and runoff is computed through the use of its various modules for runoff computation
such as rainfall, storage, infiltration, excess rainfall, soil moisture storage, evapotranspiration, overland
flow, interflow storage and discharge, groundwater recharge flow, stream-aquifer return flow and channel
flow modules. The sum of overland flow, interflow and aquifer return flow is computed as total lateral
inflow to the river channels (Figure 1).
Figure 1 – Cross-sectional diagram of the watershed hydrologic simulation model SWATCH (1988).
Without going into the mathematical details of the other components of the hydrologic cycle
(evapotranspiration, infiltration, soil moisture storage), a brief summary of the equations for overland flow,
river-channel flow, interflow and aquifer return flow (baseflow) is provided below:
2

3. Kinematic model of overland flow:
∂h ∂  1 5 / 3 1/ 2 
+  h SV  = i − f
∂t ∂x  n V 
(x,t) = distance and time coordinates.
1 5 / 3 1/ 2
q= h SV = overland flow discharge/unit width.
nV
h = water retention depth of overland flow.
i = rainfall intensity on overland surface plain.
f = infiltration rate on overland surface plain.
n V = Manning's roughness coefficient of overland surface plane .
SV = slope of overland surface plain
Kinematic model of river-channel flow:
∂H ∂  1 
B +  BH SR  = q − Bf
5 / 3 1/ 2
∂t ∂x  n R 
1
Q= BH5 / 3S1/ 2 = river-channel discharge.
R
nR
H = water depth of river-channel flow.
B = width of river channel.
q = specific overland flow discharge.
f = bed infiltration rate.
n R = Manning's roughness coefficient of river bed.
SR = slope of river channel bed.
Darcy-flow Kinematic model of interflow or upper saturated zone:
∂h ∂
n I I + [ K I h ISI ] = fex − feff
∂t ∂x
qI = K I h ISI = interflow discharge at river intersection.
h I = saturated depth of interflow or upper saturated zone.
fex = excess infiltration rate from upper unsaturated zone (vadose zone).
feff = effective infiltration rate from interflow or upper saturated zone.
K I = horizontal hydraulic conductivity of interflow zone.
SI = slope of interflow plane.
n I = effective drainable porosity of interflow zone.
3

4. Darcy-flow Groundwater model of aquifer or lower saturated zone:
∂hG ∂  ∂h G 
SG + TG = rG
∂t ∂x   ∂x 

∂h
qG = TG G = groundwater return flow or baseflow at river intersection.
∂x
h G = saturated depth of aquifer or lower saturated zone.
rG = aquifer recharge rate.
SG = effective drainable aquifer porosity.
TG = aquifer transmissivity.
Rainfall Interpolation and Depth-Duration-Frequency Relations
Figure 2 – The map of the Marikina River Basin, showing the sub-basin divisions
and river network of 84 reaches within the watershed.
The rainfall data network used in the study consists of four (4) short-record EFCOS climatic stations (Boso
Boso, Mt. Oro, Aries and Nangka) and one PAGASA Science Garden long-record synoptic stations. The
hourly rainfall data observed at the rainfall stations are used to interpolate point rainfall at the centroids
(x,y) of the 84 sub-basins of the watershed, using the unbiased multiquadric method (Balascio, 2001) as
described below. The T-year annual maximum rainfall depth for Science Garden is represented by the
Extreme Value Type or Gumbel distribution, derived after frequency analysis of the 38 years of annual
maximum records for storm durations ranging from 10 minutes to 48 hours. The result is the so-called
Rainfall-Duration-Frequency or RDF relations. The RDF relation for each short-term EFCOS station is
extended or derived (by transposition) by multiplying the Science Garden RDF value of given duration by
the ratio of maximum storm depths for the same duration, measured during the same TS Ketsana storm
event, at the short-term EFCOS station and the Science Garden synoptic station. The rainfall estimation
equations are presented below.
4

5. Unbiased Multiquadric Method of Rainfall Interpolation:
zo = Do c + b
zo = interpolated rainfall at variable point (x,y).
Do = station (xi ,yi )-to-point (x,y) distance (Nx1) vector = ( (x-xi )2 +(y-yi )2 )
z = Dc + b1
z = (1xN) vector of observed rainfall at station (xi ,yi ) for i=1,2, 3...N.
D = station (xi ,yi )-to-station (x j ,y j ) distance (NxN) matrix =  (xi -x j )2 +(yi -yi )2 
 
1 t D-1 z
b = bias correction = , to satisfy the condition that 1 t c=0 (zero sum of coefficients).
1 t D-1 1
c = (1xN) coefficient vector = D-1 (z-b 1)
1= (1xN) unity vector
Extreme Value Type I or Gumbel Distribution
(Rainfall-Duration-Frequency (RDF) relations):
XT (d) = X(d) + S(d) K T = T-year annual maximum rainfall depth of duration, d.
x k (d)= k-th observed annual maximum rainfall of duration,d.
X(d) = sample mean annual maximum rainfall depth of duration, d.
1 N
= ∑ xk (d)
N k =1
S(d) = sample standard deviation of annual rainfall depth of duration, d.
1/ 2
 1 N 2
= ∑  xk (d) − X(d)  
 N-1 k = N
 

6  T 
KT = - 0.5770 + ln ln    = Gumbel frequency factor.
π 
  T-1  
Station-to-Station RDF Transposition:
 x(i,d,TS Ketsana) 
XT (i, d) =   XT (j, d)
 x(j,d,TS Ketsana) 
XT (i, d) = T-year estimated/extended annual maximum rainfall at short-record station-i
(EFCOS stations) for duration, d.
XT (j, d) = T-year annual maximum rainfall at long-record station-j (Science Garden) for duration, d.
x(i,d,TS Ketsana) = observed TS Ketsana maximum rainfall at short-record station-i for duration, d
x(j,d,TS Ketsana) = observed TS Ketsana maximum rainfall at long-record station-j for duration, d.
The RDF values aree incremented and converted into 48-hour critical storm profiles for all stations and T-
year or TS Ketsana event, using the alternating-block method wherein the maximum rainfall intensity
occurs in the middle of the 48-hours storm and lower intensities occur before and the after the time of peak
intensity. Using the SWATCH model and the spatially interpolated hourly sub-basin rainfall over the 84
sub-basins, the streamflow flood hydrographs are computed for the TS Ketana event and also for return
periods of 2, 5, 10, 25, 50 and 100 years. The simulated flood hydrographs (in terms of water level) are
compared with the observed water level at the river stations of Montalban, Nangka, Sto. Niño (Figure 3, for
example) and Rosario Junction. As examples, the simulated flood hydrographs at Montalban and Sto. Niño
river station during the TS Ketsana storm event are shown in Figure 4.
5

6. Figure 3 – Comparison between SWATCH-computed flood hydrograph (converted from discharge to water
level using the DPWH-JICA discharge rating equations as shown) and the observed water level of Marikina
River at Sto. Niño station, which both reached levels between 12 noon and 4 p.m. on 26 September 2009.
The difference in results can be attributed to the limitation that the kinematic channel flow model used is a
one-dimensional channel flow model which does not include an extensive flood plain (considered in two-
dimensional inundation models) affected by river overflows, floodplain storage and local patterns of
tributary flows.
Figure 4 – Examples of output SWATCH-computed flood hydrographs during the TS Ketsana storm event,
at the locations of the EFCOS Montalban and Sto. Niño station water-level stations.
6

7. Flood Routing for Alternative Flood-control Dam Alternatives.
The alternatives for flood-control dams as flood mitigation measures in the upper Marikina River Basin
have been proposed in three prospective dam locations (as single dams or cascade of two or three dams)
(Figure 5). Using geologic and contour maps, potential locations for a flood mitigation reservoir are located
at the proposed project site of the Marikina Dam, along Wawa River, near the Montalban Bridge and Wawa
dam. The other two are found along Boso-Boso River, near Mt. Tayabasan and Mt. Baytangan,
respectively, in the mountainous regions of the river basin.
Figure 5. Proposed locations of flood-control dams at Marikina Dam A (at Wawa River),
Boso Boso Dam A and Boso Boso Dam B.
The flood routing studies are conducted using the hydrological storage routing method. Given the
SWATCH-computed inflow flood hydrographs into a dam-reservoir, the storage volume capacity of the
reservoir (planimetered from a digital-elevation model or DEM of the river valley and watershed), and the
assumed overflow spillway discharge capacity (parameterized by spillway crest elevation and crest length),
the outflow (release) flood hydrographs are computed. The spillway parameters are selected in order to
maximize the attenuation (reduction) of peak outflow flood discharge and the retained flood volume by
reservoir storage and spillway regulation. The equations are given indicated below:
Reservoir Storage Routing Equations:
dS
= ∑ Qin (t) − Qout (t)
dt in
Qin (t) = inflow discharge to reservoir from each source-in.
Qout (t) = CL ( H(t) − Hc )
3/ 2
= overflow spillway discharge (spillway rating equation).
S = S(H) = reservoir storage volume as a function of H (reservoir capacity equation).
H = H(t) = reservoir water surface elevation above riverbed.
Hc = elevation of spillway crest above riverbed.
L = width of spillway crest.
C = spillway discharge coefficient.
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8. Flood Routing Results
The diagrams and table of results of the flood routing computations are shown below and in the succeeding
pages.
Table 1 – Results of Flood Routing Studies for Single Dam Alternatives
(a) Single Dam – Marikina Dam A..
(b) Single Dam – Boso Boso Dam B.
(c) Single Dam – Boso Boso Dam A
8

9. Figure 6 – Examples of network diagram and flood-routing inflow, outflow,
stage (water surface elevation) and storage hydrographs for Single Marikina Dam A.
Figure 7 – Example of network diagram and flood-routing stage (water surface elevation) hydrographs
for Triple Cascade of Boso Boso Dam B, Boso Boso Dam A and Marikina Dam A.
9

10. Table 2 – Results of Flood Routing Studies for Double Cascade Dam Alternatives
(a) 2-Dam Cascade: Boso Boso Dam A and Marikina Dam A.
(b) 2-Dam Cascade: Boso Boso Dam B and Marikina Dam A.
(c) 2-Dam Cascade: Boso Boso Dam B and Boso Boso Dam A.
10

11. Table 3 – Results of Flood Routing Studies for Triple Cascade Dam Alternative
Discussion of Results
The Upper Marikina River Basin experienced large flows during TS Ketsana in Septemebr 2009 resulting
from the large amounts and high intensity of rainfall over a period of 12 to 24 hours. The updated
SWATCH model applied in this study computed a TS Ketsana peak flood flow of about 5000 m3/s at Sto.
Niño water-level station (slightly lower than the initial NHRC estimate of 5700 m3/s (which was based on
an areally adjusted Science Garden rainfall data and not on EFCOS rainfall network data, as reported
earlier by this author (Liongson, 2010)). This maximum flood discharge greatly exceeded the river bankful
capacity of the river of about 900 m3/s.. There is a need to mitigate, if not prevent, the damage that future
typhoons may bring to the river basin since the Upper Marikina River Basin is contributory to the flooding
of Metro Manila.
Calculations for the best dam design parameters show that the triple cascade dam (Table 3) is the most
viable solution for the river basin, achieving a 6% attenuation to TS Ketsana flood peak inflow (from peak
inflow of 2722 m3/s to peak outflow of 2566 m3/s). Based on the RDF relations derived from historical
rainfall record (as inputs to SWATCH), the succeeding flood routing procedure has shown that the triple
cascade dam can give a 13% attenuation to flood peak for a 100-year return period design flood (from peak
inflow of 3023 m3/s to peak outflow of 2632 m3/s). It is also seen from the Tables 3 that that the selected
best dam/spillway parameters can afford to store only about 3-7% of inflow flood volume. The same
dam/spillway parameters afford a 30.67 m. and 31.13 m maximum water level rise (above the riverbed) for
the TS Ketsana flood and 100-year flood, respectively, for a spillway crest elevation of 5 m. above the
riverbed.
The proposed single dam design (Table 1), Marikina Dam A, is clearly not viable, as it can only give a 1%
attenuation to flood peak (with a peak outflow of 2,855 m3/s), storing only 8% of the inflow flood volume,
and producing a 36.70 m. maximum water level rise (above the riverbed) for TS Ketsana flood, for a
spillway crest elevation of 23 m. above the riverbed.
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12. Recommendations
The created IDF curves for the EFCOS rainfall stations were done only through TS Ketsana-event-
based storm transposition of the rainfall from the long-record Science Garden station. The refinement
of the IDF curves could be better facilitated through the acquisition and processing of more future and
historical rainfall data gathered in both EFCOS climatic and PAGASA synoptic rainfall stations.
From discussions with hydraulic engineers in various fora, the proposed Marikina Dam A can not be
used since it has a limestone foundation. Added to that is the proximity of the location to the Valley
Fault System. A study of the geological properties and possible geotechnical solutions to the
permeability and earthquake risk should be undertaken.
The conclusion in this study regarding the higher values of both inflow and outflow flood discharges of
Marikina Dam A differ with the proposed dam design values indicated in the DPWH report (Gatan,
2009), wherein the dam design may be able to reduce the peak flood discharge of a 100-year storm into
that of a 30-year storm (from 2100 m3/s to 1500 m3/s). The data used by both studies should be
checked to establish a better grasp of the viability of a dam as a solution for the river basin flooding.
Although surveys of the proposed dam locations and other potential dam locations could be undertaken
to refine the dam design parameters (reservoir volume capacity, spillway crest elevation and length) it
is anticipated that the said refinement will only be a small increment over the previously computed
volume capacity based on the DEM. It is strongly recommended that other flood mitigation measures
should be studied in the river basin, since the proposed dam designs are ineffective in reducing peak
flows and store only a small portion of flood volumes for return periods of 25, 50 and 100 years, and
for TS Ketsana event, with the added risk of a huge rise of water levels in areas upstream of the said
dam locations.
Due to the limitation in the ability of the proposed flood-control dams to reduce flood peaks and
volumes, resulting from the low viable reservoir volume capacities in the upper Marikina River Basin,
it is wise to recommend that other feasible mitigation measures be seriously planned and implemented
for the Pasig-Marikina River Basin as a whole: both structural and non-structural, especially
downstream, measures in the populated areas of the basin. These measures include the following:
1. Concerted push to undertake regional-wide and basin-wide typhoon, rainfall and flood monitoring,
modeling, forecasting, warning and community-based action programs. This should include the
well-informed detailed interfacing and connectivity of local drainage works and major river
channel and lakeshore projects, affecting the operations of floodways, control structures such as
flood gates and weirs, and pumping stations.
2. Review, revision, updating and upgrading (if necessary) of the design and plans of ongoing
channel improvement and other river engineering projects (riverbank protection, diking,
floodways, widening and dredging, if ever) in view of the updated hydrological estimates of
extreme rainfall and flood magnitudes.
3. City-level feasibility studies on the adoption and construction of temporary flood detention basins
in open, flat and low areas near river channels (such as parks and wetlands), which will accept
river overflows and, through provision of shaft spillways, divert and store excess flood waters in
underground water cisterns, with added benefit as storage for raw water supply sources.
References
Balascio, C., 2001. Multiquadric Equations and Optimal Areal Rainfall Estimation. Journal of
Hydrologic Engineering, pp.498-505.
Liongson, L., 2010, Flood Mitigation in Metro Manila, Philippine Engineering Journal, June 2010
issue, National Engineering Center, UP Diliman.
Morel-Seytoux et al., 1987. SWATCH: A Multi Process Watershed Model for Simulation of Surface
and Subsurface Flows in a Soil-Aquifer-Stream Hydrologic Syste, Colorado State University.
Gatan, Patrick., 2009. Learning from the Ondoy Flood – A Dialogue with Experts. DPWH. 14 October
2009, Manila, Philippines. Asian Development Bank website:
http://www.adb.org/water/topics/pdfs/OKF-SSantiago.pdf.
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