Infrastructure effects on floods in the Mekong River Delta in Vietnam

HYDROLOGICAL PROCESSES Hydrol. Process. 22, 1359– 1372 (2008) Published online 11 March 2008 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/hyp.6945

Infrastructure effects on floods in the Mekong River Delta in Vietnam Le Thi Viet Hoa,1 * Haruyama Shigeko,2 Nguyen Huu Nhan3 and Tran Thanh Cong3 1 2

Institute of Natural Environmental Studies, Graduate School of Frontier Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan Institute of Natural Environmental Studies, Graduate School of Frontier Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan 3 National Hydro-Meteorological Center, Ministry of Natural Resource and Environment, 8 Mac Dinh Chi, Ho Chi Minh, Viet Nam

Abstract: The Mekong River Delta (MRD) is one of two primary rice-growing areas in Vietnam. Flooding in the Mekong River is a recurrent event and is not only one of the most destructive natural disasters but also a natural resource in this area. The cultivated surface soil layer in the Mekong Delta has a thickness of only about 50 cm, and is heavily polluted by acidic water infiltrating from deeper soil layers during the dry season. The annual floods carry fertile silt to farmland and fresh water to wash away the acidic water and provide the water needed to grow vast rice fields. The flood water carries with it various fish species that facilitate aquaculture development in the area. The floods also wash away polluted water and provide the whole delta with clean water. Owing to these different factors, the flooding in this area has a positive impact on agriculture and a negative impact on regional planning. Recent infrastructural changes designed to mitigate flood damage and protect crops and residents’ lives make the inundation regime more complicated. To understand the role of infrastructure in the flood regime in this area as well as the mechanism of the flood regime, it is necessary to apply an integrated method of study including numerical modelling, a geographic information system (GIS), and statistical analyses. This study includes a brief presentation of the measured data analysis of flood variation trends over the 43-year period from 1961 to 2004 and an analysis of the hydrological effects of infrastructure changes associated with human activities in the period from 1996 to 2001 based on the integrated hydraulic model known as HydroGis. Copyright  2008 John Wiley & Sons, Ltd. KEY WORDS

Mekong River Delta; numerical model; flood; topography; simulation

Received 26 December 2006; Accepted 08 April 2007

INTRODUCTION The Mekong River Delta (MRD) in Vietnam is located at the downstream end of the Mekong River basin. It is flat and low-lying with an area of only 11% of the entire Mekong River basin. Vast amounts of water from the entire basin area must flow through it, causing severe floods in this area annually. Almost all Vietnamese living in this region suffer from the inundations caused by upstream flows, tides, storm surges, storm rainfall, and marine salinity intrusion. The flooded area in the delta is estimated to be from approximately 1Ð2–1Ð8 million ha in high flood years, and flooding lasts from 2 to 6 months with water depths between 0Ð5 and 4Ð0 m (MRC, 2001). In the dry season, the delta is also impacted by salinity intrusion and tides (Truong et al., 1996). However, the loss of life and property from flooding is offset by benefits to agriculture from the washing away of acidic and salty water and from soil fertilization by the deposition of sediment. This being so, as nonstructural measures, the simulation of floods, * Correspondence to: Le Thi Viet Hoa, Institute of Natural Environmental Studies, Graduate School of Frontier Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. E-mail: [email protected] Copyright  2008 John Wiley & Sons, Ltd.

timely flood forecasting, and warnings may be regarded as key steps towards significant reductions in flood damage and human suffering. Thus, to find solutions that mitigate flood-disaster-related damage and enhance environmental management for the lower MRD, it is urgent to study the hydrological regime, the propagation of flood waves, and the patterns of inundation in lowlying areas. These studies require the application of numerical models. Development and application of numerical models based on the Saint Venant equations for rivers and floodplains to simulate inundation extent for different purposes are common worldwide (Cunge, 1975; Daluz Vieira, 1983; Abbott et al., 1986; Chow et al., 1988; Bates et al., 1996; Harvouet and Van Haren, 1996; Moussa and Bocquillon, 1996; Romanowicz et al., 1996; Keskin and Agiralioglu, 1997; Dutta et al., 2000, 2003; Horritt and Bates, 2001; Werner et al., 2005; Howes et al., 2006). In the MRD, the flood propagation in rivers and floodplains with models solving the equations of Saint Venant were developed. Most are packaged in the form of such computer software as SOGREAH (France), MIKE 11 (Denmark), ISIS (UK), Master model (Holland), etc. The application of these software models to the Vietnamese situation presents certain problems related to

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database standards, data management, model modification and rationalization, and local experience, and for these reasons the effectiveness of their application in Vietnam is insufficient. In Vietnam, since 1978, topographical and hydraulic data on the delta have been updated and various one-dimensional hydraulic models have been developed, e.g. SOGREAH (ordered by UNESCO and now no longer applied in the delta), SAL, VRSAP, and KOD (Truong, 2006). These local models produce good hydrodynamic simulations (Dac, 1996; Nien, 1996; Dong, 2000; Thuy and Dac, 2000); they differ in their numerical algorithms and simulation schematizations. However, without geographic information system (GIS) linking, most are ‘unfriendly’ and difficult to operate and present data management problems. Drawing on previous basic studies and oriented towards application in Vietnamese conditions, the software HydroGis was developed at the National Hydro-Meteorological Center to model flood control, salinity, and mass transport in low river systems and river mouths (Nguyen et al., 2002; Nguyen and Tran, 2003). The combination of hydraulic models and GIS in HydroGis has the advantage of simulating flooding in a large river delta such as the MRD (Nguyen et al., 2002, 2005; Nguyen and Tran, 2003; Le et al., 2005, 2007). The purpose of this study is to apply the software HydroGis to simulate flooding in the Vietnamese part of the MRD. Verification of model accuracy proved that such results as hourly water level, discharge volume, inundation depth, and inundation time can be used to evaluate the hydrological effects of infrastructure changes associated with human activities. The model was calibrated and validated using observed stream flow data for both 2000 and 2001, which were abnormal, with two big peaks, and with flood data (Le, 2002) and topographical data for these 2 years. In addition, flood variation trends since 1961 were analysed to understand more about the flood regime in this area. The effect on flooding of the engineering structures that were constructed during the period 1996–2002 is studied.

STUDY AREA The 4800 km long Mekong River is the longest river in Southeast Asia and it drains an area of 0Ð795 ð 106 km2 (Gagliano and McIntire, 1968). The river discharge into the MRD (Figure 1(a)) varies seasonally between typically 2100 m3 s1 in April (the low-flow season) and 40 000 m3 s1 in September (the high-flow season; Figure 1, Wolanski et al., 1996, 1998). The MRD is located downstream of Kompong Cham, Cambodia, and covers a total area of 4Ð95 million ha, of which 3Ð9 million ha or 74% is located in Vietnam and the remaining 26% in Cambodia. (Figure 1(a)). The MRD in Vietnam is affected by two tidal sources, regular semidiurnal tides from the South China Sea and irregular diurnal tides from the Gulf of Thailand. The effect of the former, whose highest amplitude of Copyright  2008 John Wiley & Sons, Ltd.

fluctuation is approximately 3Ð5–4 m, is stronger than that of the latter, whose amplitude is 0Ð8–1 m. In Vietnam’s MRD, the land is flat and low and the natural river system together with a man-made canal system form a dense water channel network. Since 1996, the infrastructures have been upgraded to protect crops and human life in this region. In Long Xuyen quadrant, the main flood control constructions include the following: (1) rubber dams named Tha La and Tra Su, which are designed to prevent floods until the end of August in the Long Xuyen quadrant and can be opened after harvesting most of the Summer–Autumn crop; (2) spillways in Xuan To and the extended Vinh Te canal to drain flood water to the Gulf of Thailand via the Ha Tien quadrant by a drainage system; (3) digging of drainage canals named T4, T5, and T6 connecting the Vinh Te canal and the Rach Gia-Ha Tien canal; (4) expansion of drainage gates through Road 80 and the digging and dredging of 20 canals to drain flood water to the Gulf of Thailand; and (5) construction of sewers for salinity prevention. In Dong Thap Muoi, the main flood control constructions included only, until the flood of 2000, dredging the Tan Thanh-Lo Gach canal, raising its embankment, re-constructing five bridges on the road along this canal, dredging such canals as 2–9, Khang Chien, Binh Thanh, and Thong Nhat, and the expansion or new construction of bridges along National Road 30 and National Road 1 (along the Mekong River). Road number 1 from My Tho to An Huu was raised. After 2000, some hydraulic construction took place and roads continued to be upgraded or maintained, some canals were dredged, and many residential areas were built up. Thus, during the period 2000–2002, a number of structures continued to be constructed in Long Xuyen quadrant: (1) dredging and digging of about 20 canals for flood drainage canals through Road 80 such as Tuan Thong and Lung Lon; (2) completing the salinity prevention sewers along the Gulf of Thailand coastline; (3) upgrading Road 80 and building sluices under the dykes; and (4) upgrading embankments along canals in Chau Thanh district, An Giang province. In Dong Thap Muoi, the flood situation is more complicated; until the year 2000 flood season, mainly dredging and digging of canals was carried out. Upstream of Dong Thap Muoi, Tan Thanh-Lo Gach not only irrigated the northern part of Hong Ngu but also played a delaying role in the propagation of floods into Dong Thap Muoi and steered a portion of floods towards the Vam Co river. After the flood season in 2000, various flood control works were carried out during the 2000–2002 period: (1) dredging the Tan Thanh-Lo Gach canal and raising the embankments from 5Ð5 to 6Ð5 m; (2) completing and constructing such bridges as Ca Giao, 2–9, Khang Chien, Binh Thanh, and Thong Nhat; (3) expanding and constructing the bridges in Tu Thuong; (4) dredging four canals such as 2–9, Khang Chien, Binh Thanh, and Thong Nhat to drain into the Mekong River; (5) dredging the Song Trang-Ca Rung and Hong Ngu-28 canals to drain floods into the Vam Co river; (6) upgrading Road Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

INFRASTRUCTURE EFFECTS ON FLOODS IN THE MEKONG RIVER DELTA IN VIETNAM

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Figure 1. Mekong river delta: (a) study area; (b) hydro-meteorological network; (c) computation network

1 from My Tho to An Huu over the flood 2000 level, along which all the bridges were constructed or expanded; (7) upgrading Road 30 from An Huu to Hong Ngu and from Hong Ngu to Dinh Ba over the flood 2000 level; (8) upgrading roads such as Roads 62, 50, 3, 54, 57, 60, 61, and 63 over the flood 2000 level; and (9) building embankments along canals in the northern part of the Vinh An canal. The region affected by these changes is sketched in Figure 2. Copyright  2008 John Wiley & Sons, Ltd.

HYDROGIS MODEL DESCRIPTION The basic equations Interactions between cross-sections are modelled by the Saint Venant system of equations and equations of mass balance as follows: ∂A ∂Q C D qc ∂t ∂x

1 Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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(a)

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Figure 2. The region having infrastructure change in Mekong River delta in Vietnam: (a) during 1996– 2000; (b) after 2000

∂Q ∂ C ∂t ∂x

∂Z gAQjQj Q2 C gA Cw BWWx C A ∂x K2

∂Z Q ∂S C S C qc cos ˛ D 0 ∂x ∂x A ∂S ∂ ∂S ∂S L R CU Es D [qout C qout S ∂t ∂x ∂x ∂x gAR

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L R SL C qin SR ]/A C qin ∂C ∂ ∂C ∂C L R CU Ec D [qout C qout C ∂t ∂x ∂x ∂x

3

L R C qin CL C qin CR ]/A C source - sink

4

R qc D qL C qR , qR D qin qRout ,

Copyright  2008 John Wiley & Sons, Ltd.

Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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A2 R4/3 n2 ES D EC D E0 C CE Ax2/3 U x , L qLout , K2 D qL D qin

E0 D 0Ð5 1Ð0m2 /s, CE D 0Ð01

5

are modelled by equations of energy, momentum, and mass balance as follows:

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dVi D Qo-o C Qc-o C P E C QW š Inf, dt o in o out C in C out Qji Qij , Qc-o D qci qic Qo-o D

where Q is discharge, m3 /s; A is wet area of cross-section, m2 ; qc is total lateral discharge per unit of length, m2 /s; q with indexL,R is lateral discharge from cells placed on the left and right sides of the river per unit of length, m2 /s; q with indexin,out is discharge per unit of length to/from the river by interaction with linked cells placed on the left and right sides of the cross-section, m2 /s; B is width at river surface, m; S is salinity in river, g/l; S with index is salinity of left/right linked cell to the cross-section, g/l; R is hydraulic radius, m; ˛ is angle of lateral flow to river axis, radian; Cw is wind friction coefficient; Es is salinity dispersion coefficient, m2 /s; W, Wx are wind speed and component of wind direction to river axis; Ec is mass dispersion coefficient, m2 /s; T is half-life of substance; Sink is rate of substance decay by biochemical/physical effects, mg/l/s; Source is rate of substance induction by biochemical/physical effects, mg/l/s; N is the Manning coefficient; K is the discharge coefficient; U is cross-section average flow velocity, m/s; C is concentration of substance in river, ml/l; C with index is concentration of substance in the cell, ml/l; D8Ð02105 m3 /kg is experimental coefficient; Cw D2Ð6105 is experimental coefficient of wind stress. The changes in water volume (V), salt mass (VS ), and substance mass (VC ) by processes: 1. Total water and mass flows between cell and river: Qco0 QSco , QCco ; 2. Total water and mass flows between cells: Qoo Q So o , QCoo ; 3. Rainfall and its impact on mass balances: P, (PS), and (PC); 4. Evaporation and its impact on mass balances: (E), (ES ), and (EC ); 5. Infiltration/groundwater flows: š Inf; 6. Bio-chemical/physical loading of mass: source; 7. Bio-chemical/physical decay of mass: sink; 8. Incoming mass source: Qw, Qs, Qc Copyright  2008 John Wiley & Sons, Ltd.

jD0

jD0

cD0

cD0

7 dVi Si S C QS P S C ES C Q , D Qo-o i i i S c-o dt o in o out c in S D S D Qo-o Qji Sj Qij Si , QC-O qci S jD0

jD0

c out

cD0

qic Si

8

cD0

dVi Ci C C QC P C C EC C sink D Qo-o i i i i c-o dt C sourcei C QC , C D Qo-o

o in

Qji Cj

jD0

o out jD0

c out

qic Ci

C D Qij Ci , Qc-o

c in

qci C

cD0

9

cD0

where Si , Ci are salinity and concentration of substances in cell i; Sj , Cj are salinity and concentration of substances in cell j; Qij is total discharge from cell i to cell j; Qji is total discharge from cell j to cell i; qci is total discharge from cross-section to cell i linked with it; qic is total discharge from cell i to cross-section linked with it; o in is total number of cells flowing into cell i; o out is total number of cells flowing out from cell i; c in is total number of cross-sections flowing into cell i; c out is total number of cross-sections flowing out from cell i; The cell grids and river segments are sketched in Figure 3. The components Qij , Qji , qci , qic in Equations (7), (8), (9) are the sum of two components: overflows of the cell’s border heads and flows through sewers, sluices, and dikes breaking at the cell and river borders. The value and direction of overflows and flows through cell and river structures were modelled by the Bernoulli or Manning formulas independent of flow properties (full free, shallow submerged or deep submerged flow). The parameters related to the Equations (7), (8), (9) are average water level in cell , cell area at a given water Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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Cross-section Cn River/canal River/canal

The numerical solution

Cell Cell jn t C 1 Cell

C2 Cell i

Cell j1

parameters as tidal water level and storm surge water level. Thus HydroGis can be used in both simulating and forecasting.

Cell jn--1

Cell j2

Figure 3. Schematic figure of the river segments and cells

level, water depth in cell, height, width and length of borders, radius between linked cells and cross-section, geometry and hydraulic parameters of hydro-technical constructions, cell land cover surface properties, etc. The system of Equations (1) and (2) is closed, with four variables: Q, , S, and C for all river cross-sections and floodplain cells in the network. The above described model is nonlinear. The initial conditions are given values of all arrays Q, , S, and C for all river cross-sections and floodplain cells in the network. The boundary conditions are as follows: ž At a downstream node of river network (river mouths): t D Zs t; St D Ss t when flow is directed to the river; Ct D Cs t when flow is directed to the river. ž At an upstream node of the river network (inflow of water and waste): Qt D Qo t; St D Co t when flow is directed to the river; Ct D Co t when flow is directed to the river.

The above system of equations with included conditions is solved numerically by iteration cycles. The Saint Venant equations are discretized using the four point implicit Preissmann scheme. Zeidel’s iteration method is used for the approximate solution of the system of equations. The maximum number of iteration cycles usually depends on the time step and the resolution of the river network. t and x are chosen to satisfy the Courant–Friedrich–Lewy criterion (CFL) as well as to optimize the computation time. However, the number of iterations will increase if t or x, or both, increase. Hence, for each case under study, the user must experiment with different numbers to find optimal t and x. HydroGis has an option that facilitates this.

METHODOLOGY AND DATA With urbanization, the flood regime undergoes a certain variation. First, a simple statistical trend analysis of measured data for the 43-year period is considered. The HydroGis model is then applied for flood simulation to evaluate the impact of infrastructure change on the flood regime. All available data in the MRD are updated and input to the hard boundary database and the hydrometeorological database for each flood in 2000 and 2001. The model was verified by correcting the parameters and input. After validation of the model, hourly runoff, inundation depth, inundation time, and other variables at any point were found for our study. To examine the hydrological effect of infrastructure changes, it is necessary to analyse such components of simulated floods as water level at main stations, inundation depth, inundation area, inundation time, and inflow to Vietnam, on the supposition that the flood in 2000 occurred under different topographical conditions to those of 1996, 2000, 2001, and 2002. In order to evaluate the impact of infrastructure change, three comparisons between scenarios were considered in this study:

Water level is the same for all joint cross-sections of the river at this node; Algebraic sum of incoming and outcoming water flows will equal 0; Algebraic sum of incoming and outcoming mass flows will equal 0.

1. The results when the model was run with the hydrometeorological data of the 2000 floods under the topographical conditions of 2000 and 1996 (case 1) 2. The results when the model was run with the hydrometeorological data of the 2000 floods under the topographical conditions of 2000 and 2001 (case 2) 3. The results when the model was run with the hydrometeorological data of the 2000 floods under the topographical conditions of 2000 and 2002 (case 3)

The model HydroGis provides the option to set boundary databases using either traditional tools for importing measured data to the boundary databases or using modelling tools for predicting such hydro-meteorological

Figure 4 shows the flowchart of the study process. With an acceptable error, the model results can be used for analysis of the impact of human activities on the inundation regime in this region.

ž At a joint node of the river network:




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hydro-meteorological condition of the flood 2000

Scenario1:Hard boundary database in 2000 Comparing 1 and 2 (case 1)

Difference in WL in August

Comparing 3 and 1 (case 2)

Difference in WL in flood season

Comparing 4 and 1 (case 3)

Difference in the inundation time

Scenario 2: Hard boundary database in1996

Scenario 3: Hard boundary database in 2001

Scenario 4: Hard boundary database in 2002

Figure 4. Flowchart of the study (b) 500 Peak at Chau Doc, cm

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L. T. V. HOA ET AL.

Figure 6. Observed and simulated hydrograph of water level in Mekong river delta in 2000 and 2001

In this study, cross-sectional hydraulic data approximating the river–canal network were digitized from hydrometric readings; planning data from 1990 to 2000 were supplied by the Vietnamese Ministry of Transportation’s inland waterway administration. Elevation data for the floodplain cell network in the MRD are based on a digital elevation model with a resolution of 100 ð 100 m obtained from the Mekong River Commission. The embankment elevation is based on the map of the MRD obtained from the Southern Institute of Hydraulic Science. Hydrological data were obtained from the National Hydro-meteorological Center of Vietnam. Information about changes in dikes and embankment elevations was obtained from local offices. The detailed computation scheme for the MRD includes 2535 flood cells, 13 262 cross-sections, and 467 sewers, bridges, and sluices (Figure 1(c)). There are 82 downstream boundaries located at estuaries in which water level data were measured hourly, and 7 upstream discharge boundaries were used. The data on rainfall, evaporation, infiltration, and wind were input from archives of 24 hydrometeorological stations in the MRD including some stations in Cambodia such as Phnom Penh, Kratie, and Siem Riep. Copyright  2008 John Wiley & Sons, Ltd.

RESULTS AND DISCUSSION Flood trends in the Mekong River Delta On the basis of the hydrological variables from 1961 to 2004 at stations along the Mekong River, at Dong Thap Muoi and the Long Xuyen quadrant, the trend of variation in the maximum water level at some stations is shown in Figure 5. This figure shows that the maximum water level in the main river at Tan Chau and Chau Doc is almost unchanged, but at other stations, this trend has increased in recent years and increases with progression downstream. This can be explained as follows: (1) the infrastructures in Dong Thap Muoi and the Long Xuyen quadrant have become more developed and embankments have been raised, blocking the overflows and reducing drainage in these regions; (2) the infrastructural development in the downstream part of the MRD (including Dong Thap Muoi and the Long Xuyen quadrant) have decreased the flood-regulating role of floodplain cells during peak-time periods, increasing water levels in rivers downstream of this region. Annual maximum flows in Dong Thap Muoi and the Long Xuyen quadrant reveal a significant increasing trend with time and with progression downstream. The Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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14000 12000 10000 8000 6000 4000 2000 0

To DTM To LX quadrant To middle part 2000

8-Dec

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Figure 7. Comparison of simulated and observed inflow to Vietnam through the boundary

maximum flow acceleration downstream can be explained because embankments to protect crops and residents’ lives become obstacles to flood drainage. In order to understand the flood mechanism in more detail, the HydroGis model was applied to simulate the 2000 and 2001 floods, the two biggest floods occurring in this century. Application of the HydroGis model for flood simulation In order to simulate these floods, the topographical and hydro-meteorological data, including information on infrastructure changes each year, were separately updated for the floods of 2000 and 2001. Observed and simulated hydrographs of water levels at all stations in this region during these floods are shown in Figure 6. The figures show water level fluctuations in the hydrographs of some downstream stations at the beginning of the flood season. In the dry season, water levels in the canals are very low and waste is deposited in the canals. They obstruct the water flow in the early flood season and cause a reduction of tide effects, making accurate simulation of these effects in the model difficult. This is the reason why the tide effects cause water level fluctuations in the model results at such downstream stations as Long Xuyen and Kien Binh in the early flood season. Except for this fluctuation, the hydrographs at the stations in the main rivers, Dong Thap Muoi and the Long Xuyen quadrant, show good agreement between the HydroGis model’s result (Hsim) and observed water level (Hobs). Table I shows the differences between simulated and observed flood peak values. The inflows from Cambodia to Vietnam through the boundary were calculated and compared with the observed flood data. The comparison was done for all Copyright  2008 John Wiley & Sons, Ltd.

the inflow and outflow discharges in Dong Thap Muoi and the Long Xuyen quadrant. Figure 7 shows the hydrographs of the simulated versus observed inflow for the floods of 2000 and 2001. Generally, the observed data of overflow discharge along the Vietnam–Cambodia boundary have a margin of error of 15–17%, thus the differences between observed and simulated values about or less than 20% are acceptable and the validated results can be used for analysis of inundation characteristics in this area. Analysis of infrastructure change impact on inundation regime After validating the model, all the results were used for comparisons of three scenarios. The model results for the year 2000 flood, using the year 2000 hard boundary condition are called scenario 1 and are used to test the response of the flood waves to three scenarios in Figure 4. Scenario 2 corresponds to the year 2000 flood with the hard boundary condition of 1996. Scenario 3 and scenario Table I. Comparison of simulated and maximum observed water levels Number

1 2 3 4 5 6 7 8 9

Station

Tan Chau Chau Doc Moc Hoa Hung Thanh Kien Binh Xuan To Tri Ton Tan Hiep Vam Nao

2000

2001

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506 490 327 358 266 468 298 185 373

507 486 326 350 276 462 300 182 372

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476 449 292 321 251 428 287 164 354

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(a)

(b)

(c)

Figure 8. Comparison of the simulated maximum water level in August of the flood 2000 between: (a) hard boundary of 2000 and 1996; (b) hard boundary of 2001 and 2000; (c) hard boundary of 2002 and 2000

4 correspond to the year 2000 flood with the infrastructure further modified by changes after the flood 2000. Comparisons between the model’s water levels for the floods simulated using the different hard boundary conditions of these scenarios show the infrastructure change effect on the flood regime from 1996 to 2002 (Figures 8–10). The inundation depths, computed by subtracting the land elevation of flood cells from water levels, are used to produce maps of the spatial distributions of monthly maximum inundation depths. Case 1: The infrastructure change from 1996 to 2000 decreased the inundation in August by approximately 10–40 cm in Long Xuyen quadrant, Copyright  2008 John Wiley & Sons, Ltd.

but increased it by approximately 10–20 cm upstream of the Dong Thap Muoi area. However, water drainage into the Gulf of Thailand increased, causing an increase in inundation in the Ha Tien area (Figure 8(a)). The profiles of the maximum water level in August in Figure 9 show that water levels increased upstream of the Dong Thap Muoi area limited by the Dong Tien canal and the Hoa Binh canal. In August, downstream of Dong Thap Muoi, water levels in the flood cell were unchanged, but in the Long Xuyen quadrant, they were significantly decreased by 5–30 cm at the beginning of the flood season. Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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n Do g

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co

r

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riv

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Hong Ngu

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Hung Thanh Xuan To

er

co T Moc Hoa ay riv er

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in topography 2000

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Maximum water level in August, m

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e Bassac riv

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in topography 1996 in topography 2001 An Binh Canal

in topography 2002

Hoa Binh Canal

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Tan An

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Chau Doc in topography 2000

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AN GIANG

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in topography 1996

My Tho My Thuan Cho Lach

KIEN GIANG

Hoa Binh

BEN TRE

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Tan Hiep Rach Gia

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riv

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in topography 2001

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in topography 2002

Tri Ton canal Muoi Chau Phu canal Mac Can Dung canal Ba The canal

2.0 Kien Hao canal Rach Gia-Long Xuyen canal Tron canal Cai San canal

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940000

Nam Can

0.0 0 440000

490000

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20

40

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Distance from Chau Doc to Rach Gia, km

Figure 9. The profile of water level differences in floodplain: (a) in Dong Thap Muoi area from Tan Chau to Tan An; (b) in Long Xuyen quadrant from Chau Doc to Road 80

This implies that timely flood protected embankments and the drainage canal system in Long Xuyen quadrant affected, to some extent, the inundation in August. The maximum water level in the flood season in Dong Thap Muoi increased 10–30 cm (Figure 10(b)). Case 2: The infrastructure change from 2000 to 2001 decreased inundations in almost all areas by approximately 10 cm in August, except in Long An province (Figure 8(b)). The profiles of the maximum water levels in August in Figure 9 show that, from August, large amounts of floodwater propagated to Dong Thap Muoi, causing an increase in water level. This increased by approximately 5–20 cm upstream from Dong Thap Muoi, but decreased in Long Xuyen quadrant, especially by approximately 0Ð5 m in the middle of Long Xuyen quadrant. The Copyright  2008 John Wiley & Sons, Ltd.

differences in annual maximum water levels increased 10–20 cm in Ha Tien, Kien Giang province, and Long Khot to Tan Hung-Vinh Hung, downstream of Dong Thap Muoi in Long An province, and downstream of Dong Thap Muoi towards the Vam Co river (Figure 10(b)). In the region between two Mekong tributaries, western and southwestern Dong Thap and An Giang and southeastern Kien Giang provinces, where the embankments were raised, the water levels decreased by 10–20 cm. Flood propagation from Long Xuyen quadrant to west of the Hau river decreased. The duration of the flood increased from 2 to 5 days (Figure 11(b)). Case 3: The infrastructure change during 2001 to 2002 continued to decrease water levels in Long Xuyen quadrant, while water levels increased by 10–30 cm in Long An and downstream of Dong Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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(a)

(b)

(c)

Figure 10. Comparison of the simulated maximum water level of the flood 2000 between: (a) hard boundary of 2000 and 1996; (b) hard boundary of 2001 and 2000; (c) hard boundary of 2002 and 2000

Thap Muoi towards the Vam Co river. The profile of water levels shows that flood propagation to Dong Thap Muoi was earlier and inundation was higher (Figure 9). However, in Long Xuyen quadrant, inundation decreased. The difference in annual maximum water levels increased by 10–20 cm in Ha Tien, Kien Giang province and Long Khot to Tan Hung-Vinh Hung, downstream of Dong Thap Muoi in Long An province, and downstream of Dong Thap Muoi towards the Vam Co river (Figure 10(c)). Flood flowing from Long Xuyen quadrant to the West of Copyright  2008 John Wiley & Sons, Ltd.

the Hau river decreased. In Dong Thap Muoi, the duration of the flood increased from approximately 5 to 10 days, while elsewhere the flood duration remained at approximately 2–5 days (Figure 11(c)).

CONCLUSION AND RECOMMENDATION The model introduced in this study was applied to simulate and assess the hydrological impact of infrastructure changes due to human flood prevention activities. It is Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp


(a)

1371

(b)

(c)

Figure 11. Comparison of the simulated maximum inundation duration of the flood 2000 between: (a) hard boundary of 2000 and 1996; (b) hard boundary of 2001 and 2000; (c) hard boundary of 2002 and 2000

particularly suitable to the vast MRD with its complicated flood regime. The model results still have a certain margin of error, but analysis based on these results shows the following: 1. On the basis of the available topographical, hydrological, and field survey flood flow data, this model simulates well the flood flows in the MRD, which are very large and have a complicated flood regime; the model generates acceptable results and provides valuable information for more detailed study of floods in this area. Copyright  2008 John Wiley & Sons, Ltd.

2. Under scenarios 2–4, the model suggests that the infrastructure changes during the period 1996–2002 had effects on the flood regime. Such infrastructure changes as dredging the canals, raising the embankment systems along canals, upgrading roads to protect residents’ lives, and protecting crops can prevent floods by slowing flood propagation to paddy fields early in the season, but cause inundations to last approximately 5–10 days longer and to be 0Ð2–0Ð3 m deeper in some regions near or between high embankment systems (such as the region between the Tan ThanhLo Gach and Hong Ngu canals, south of the Hong Hydrol. Process. 22, 1359– 1372 (2008) DOI: 10.1002/hyp

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Ngu canal and upstream of the Long Xuyen quadrant). The model results show that the recent engineering structures decreased inundation in those regions where the embankments were raised, and caused the flood wave to propagate to other regions where flooding is worsened in peak flood height and duration. Flood flow propagation to Dong Thap Muoi increased, causing higher inundation. Especially downstream of Dong Thap Muoi towards the Vam Co river, the inundation lasted longer and was deeper during big floods such as the flood of 2000; this may be because the structures obstruct flood drainage. 3. The high embankments in the region between two tributaries and along the Vinh Te canal boundary confined runoff propagation from Cambodia and overflow towards the downstream part of the Mekong River, causing a significant decrease in maximum water level. This is a change in flood propagation in the delta as compared to the natural regime. Long Xuyen quadrant was protected from early flooding, but flooding propagated faster from Cambodia to Long An in Dong Thap Muoi and Ha Tien quadrant, almost in synchrony with flooding in the main river at Tan Chau and Chau Doc. 4. These changes decrease overbank inflow to Vietnam and increase waterflow in the canals. This is consistent with the above analysis of variation trends based on the flood data from 1961 to 2004: flood peaks tend to increase with progression downstream. The evaluation in this study and the model results could be useful in understanding the mechanism of the flood regime and assessing the potential effects of future planning for flood prevention in this region.

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