Integrated Physical and Ecological Management of the East River

Integrated physical and ecological management of the Supply Water Technology: & Science Water East River

J.H.W. Lee*, Z.Y. Wang** , W. Thoe* and D.S. Cheng* *Department of Civil Engineering, The University of Hong Kong, Hong Kong, China (E-mail: [email protected]; [email protected]; [email protected]) **Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China (E-mail: [email protected])

Abstract We present an independent assessment of the health and water sustainability of the East River (Dongjiang) in South China, which is the source of nearly 80% of Hong Kong’s water supply. Field measurements show that the water quality in the upper and middle reaches is generally good and well exceeds the drinking quality standard, with high bio-diversity. The streamflow of the East River Basin is satisfactorily simulated using both the distributed MIKE-SHE model and the lumped HSPF model. With an 81–91 pp 2 No 7 Vol average streamflow of 760 m3/s, the River is able to satisfy the current water demand. Using the HSPF model, the water quality is found to have deteriorated in recent years. In addition to water supply, the River also supports a variety of needs such as hydro-power generation, waste assimilation, navigation, habitat for aquatic life, and expulsion of sea water intrusion. Using the projected need of 150 m3/s for water supply, the instream flow requirement based on hydrological and water quality simulation is estimated to be 467 m3/s in 2010. This suggests that the water sustainability of the East River requires alternative strategies, which may include integrated water resources management, provision of better wastewater treatment, and water and Q soil conservation. 2007 Publishing IWA Keywords Bio-diversity; East River; instream water requirement; integrated river management; sustainability; water quality modelling

Introduction East River (Dongjiang) is one of the three main tributaries of the Pearl River (Zhujiang) system, the fourth largest river system in China. It is 562 km long and has a drainage area of 35,340 km2, with an annual average precipitation of 1,750 mm and runoff of 32.4 billion m3 (Figure 1(a)). The water resources in the East River has been harnessed through three major reservoirs: Xinfengjiang, Fengshuba and Baipenzhu, which are of great importance to the ﬂood control, power generation, irrigation, navigation, and water supply of the Guangdong province. The river is the main source of water supply for Hong Kong, Shenzhen, Dongguan, and Guangzhou. Currently, the East River provides approximately 80% of the potable water supply in Hong Kong. The population in the East River Basin has increased from about 7 million in 1985 to 10 million in 2004, and is projected to reach 12 million in 2020 (Figure 1(b)). The population growth and associated anthropogenic activities have led to drastic changes in both demand and supply of water in the region. Problems such as deterioration in water quality have been reported in both the main stream as well as their associated tributaries (Wang and Zhou, 1999; Zhang and Wu, 1999; Ho and Hui, 2001). The East River Basin is dominated by forests and woodland (Figure 1(c)); urban and agricultural land use are concentrated in the middle and lower reaches, where water pollution has been associated with an increase in industrial and domestic sewage discharges (Hills et al., 1998). Total wastewater discharge in the East River is predicted to increase from 109 t/a in 1998 to about 2.3 £ 109 t/a in doi: 10.2166/ws.2007.043 81 ...Lee J.H.W. tal. et

Figure 1 The East River Basin: (a) location of key cities and hydrological stations; (b) population and wastewater loading; and (c) land use pattern in 2000

2020. The sustainability of the water resources in the East River Basin is of foremost importance to the development of Hong Kong and the Pearl River Delta. And yet, as far as we are aware, this issue has hitherto not been addressed in a comprehensive scientific investigation; field data on bio-diversity has also not been reported. In this paper we per- form an independent assessment of the river health and water sustainability based on field studies, distributed hydrological modeling using MIKE-SHE, and lumped water quality modeling using HSPF.

Environmental and ecological assessment During 2004–2006, nine ﬁeld investigations to the East River Basin have been carried out. The water quality is measured along the mainstream in both the dry season (April 2006) and the wet season (July 2005). In each investigation, the common water quality parameters (DO, pH, conductivity, temperature) are measured on site, and samples are taken for subsequent analysis for nutrients, suspended solids, and bio-diversity using standard methods. Figure 2 shows the distribution of dissolved oxygen (DO), ammonia nitrogen

(NH4), nitrate (NO3), and phosphate (PO4) along the river. In general, the water quality in the East River is better than other large rivers in China. In the dry season, it can be seen that the water quality in the upper and middle reaches (e.g. above Heyuan) is generally good and well exceeds the drinking water quality (Chinese National Water Quality Grade II) standard. The DO is close to saturation and the ammonia nitrogen is negligibly small compared to the drinking water quality standard of 0.5 mg/L. Towards the river mouth, below Boluo, however, there is notable organic pollution; the DO deceases with signiﬁcant increase of ammonia nitrogen and phosphate. The same spatial trend is observed in the wet

season; the higher NH4 concentrations measured may be contributed by non-point pollution sources brought to the river by rainfall and overland ﬂow. Also, DO concentration is

about 1 to 2 mg/L lower in the wet season. NO3 and PO4 concentrations are low in both seasons. An aggregate measure of river health can be provided by a Water Quality Index (WQI, Sˇtambuk-Giljanovic´, 2003). The WQI ranges from 0 to 100, and is based on the

measured values of temperature, DO, pH, conductivity, NH4 þ NO3,PO4 and TSS. 82 For each parameter, a score is given and the scores are aggregated by a weighting factor ...Lee J.H.W. tal. et

Figure 2 Measured water quality along the mainstream of the East River P 2 to obtain the river health index WQI ¼ð1=100Þð WiQiÞ , where Q ¼ score, and W ¼ weighting factor. Details of the calculation method can be found in Fan et al. (2005). In addition to water quality, the algal and benthic macro-invertebrate bio-diversity are investigated on November 2004 and July 2006 respectively for examining the impact of anthropogenic activities on river health. Figure 3(a) shows the location of the sampling sites. Among these, four sites are selected to study the species composition of epilithic diatoms (attached to rocks and stones) and their suitability for river health assessment. These include the Xinfengjiang (XFJ) and Baipuhe (BPH) near Heyuan, as well as Simeizhou (SMZ) and Xizhijiang (XZJ) near Huizhou. Figure 3(b) shows the measured WQI and the algal community diversity in terms of the Shannon-Wiener index (H; based on the number of individuals in each species). It can be seen the WQI is generally around

Figure 3 (a) Location of sampling sites; (b) measured algal bio-diversity 83 80 near Heyuan but decreases to around 50 in the downstream reaches near Huizhou. However, the WQI and the algal bio-diversity do not appear to be correlated. The Shannon-Wiener diversity index falls within the typical range of 1.5–3.5; at the XFJ site below the Xinfengjiang Reservoir, the low bio-diversity is believed to be related to the reservoir operation. Further details on the algal bio-diversity measurement can be found in Fan et al. (this volume). Aquatic macro-invertebrates have been used as indicators of ...Lee J.H.W. stream and riparian health (Wright et al., 1989; Chutter, 1998; Karr, 1999; Smith et al., 1999). Thirteen sites have been surveyed from upstream tributaries to the lower reaches of the East River to collect benthic invertebrates and environmental data. A total of forty-

tal. et one insect families have been found. Figure 4 shows the taxon richness (total number of species) at each of the sites. The highest benthic bio-diversity is measured at two relatively pristine stations upstream; the lowest diversity is recorded at the most downstream sampling station which is characterized by high turbidity, poor water quality, silt sub- strate, and lack of insect fauna. The WQI is strongly correlated with the benthic diversity along the East River.

Hydrological modelling of the East River basin In view of the scarcity of streamflow data, a physically-based distributed model, MIKE- SHE, is employed to study the spatial and temporal variation of streamflow; this is the first time that such a distributed model has been applied to the East River. MIKE-SHE incorporates the topography of the basin derived from Digital Elevation Model (DEM) and uses the spatially distributed rainfall and potential evapo-transpiration as model inputs (Abbott et al., 1986a,b). The hydrological data from eleven precipitation stations, eleven streamflow stations, and eight stations for potential evapo-transpiration are used for model calibration (1969–1973) and validation (1974–1978). The daily averaged streamflow at eleven hydrological stations is predicted; Table 1 shows the accuracy of the hydrological 2 simulationP as evaluatedP by statistical indices including the Nash-StucliffeP coefficientP R ¼ n 2= n 2 n 2= n 2 1 2 i¼1ðPi 2 OiÞ i¼1ðOi 2 OÞ and CD ¼ i¼1ðOi 2 OÞ i¼1ðPi 2 OÞ respectively, where CD ¼ coefficient of determination, and Oi and Pi ¼ daily averaged observed and predicted streamflow respectively, and O ¼ mean observed streamflow. R 2 measures the goodness of fit, while CD measures the scatter of the predicted andP observed = n values around the mean of observation. The percentage bias ð%Bias ¼ð1 nÞ i¼1ðOi 2 PiÞ=OiÞ is also calculated. Ideally, the parameters in a physically-based model can be roughly estimated based on the physical characteristics of the watershed. Due to the limited data, the model parameters are determined by calibration against the streamflow data through parameter optimization. Based on extensive simulations, the MIKE-SHE model

84 Figure 4 Measured taxon richness and water quality along the East River, April 2006 Table 1 Summary of MIKE-SHE streamﬂow simulation of the East River Basin

Period Calibration Validation

Heyuan Lingxia Boluo Heyuan Lingxia Boluo

3 Qobs (m /s) 400 568 704 590 716 841 3 Qsim (m /s) 431 633 754 580 772 918

% bias 7.6 11.4 7.1 21.6 7.9 9.1 Lee J.H.W. R 2 0.61 0.71 0.81 0.15 0.6 0.81 CD 1.02 1.38 1.76 0.43 0.63 1.1 tal. et prediction is judged to be most sensitive to: (i) the saturated zone hydraulic conductivity in both vertical and horizontal direction, (ii) the unsaturated zone hydraulic conductivity in the vertical direction and (iii) the Manning’s roughness for overland flow. These three parameters control the rate of base flow generation, the rate of infiltration and the rate of surface flow generation respectively. A test application of MIKE-SHE for a river basin in Hong Kong where detailed precipitation and runoff data is available has demonstrated that the predicted streamflow is in excellent agreement with data, with R 2 ¼ 0.97 and CD ¼ 0.98 for validation runs (Thoe, 2007). Figures 5 and 6 show the predicted and measured daily averaged streamflow at Heyuan, Lingxia and Boluo – corresponding roughly to the upper, middle and lower reach (Figure 1). The predicted daily averaged streamflow agrees well with data in Lingxia and Boluo. R 2 are 0.71 and 0.6 in Lingxia, and 0.81 and 0.81 in Boluo respectively for the calibration and validation periods (Table 1). Both peak flows and base flows are satisfactorily predicted in these two stations. However, the flow prediction at a station immediately below a reservoir (e.g. Heyuan downstream of Xinfengjiang and Fengshuba Reservoirs, Figure 1) is less satisfactory, and is believed to be related to reservoir

Figure 5 Comparison of predicted and measured daily averaged streamﬂow (1969–1973, calibration) 85 ...Lee J.H.W. tal. et

Figure 6 Comparison of predicted and measured daily averaged streamﬂow (1974–1978, validation)

operation (e.g. Fengshuba reservoir started operation in 1974). The effect of the reservoir operations diminishes with distance downstream, and is not notable in Lingxia and Boluo. Overall, good water balance is achieved in most mainstream stations, with a percentage bias within 10%. Details of the calibrated model parameters can be found in Thoe (2007). Key modeling issues of MIKE-SHE such as scale effect, the mutual interactions between model parameters, and parameter transferability to different sub-basins have also been studied (Yeh et al., 2004). It is judged the ﬂow prediction can be further improved as knowledge about the reservoir operation becomes available.

Water quality modelling of the East River basin An empirically based lumped parameter model, HSPF (Hydrological Simulation Program Fortran, Bicknell et al., 2001), is employed to predict water quality of the East River. The emphasis is on key organic pollutant concentrations of relevance to drinking water quality

(Biochemical Oxygen Demand BOD5, and ammonia nitrogen NH4); the Chinese water quality standard (Grade II) for drinking water is 3 mg/L and 0.5 mg/L for BOD5 and NH4 respectively. The lower East River Basin (from Heyuan to Qiaotou) is modeled (Figure 1). The study area (Figure 7(a)) includes all the major urbanized and developed cities in the non-tidal portion of the river; pollution loads outside of the study area are relatively insignif- icant. Qiaotou is located immediately downstream of Boluo, where the East River diversion scheme to Hong Kong starts. Based on the locations of the hydrological and water quality sampling stations, the study area is further divided into ﬁfteen sub-basins; Figure 7(b) shows the schematization of sub-basin linkage. The HSPF study area (9,630 km2) covers key cities including Heyuan, Huizhou, Dongguan, Shenzhen, and their associated counties. HSPF simpliﬁes a catchment into a tank-and-link system; water and pollutant mass bal- ances are carried out individually in each tank and routing is performed afterwards through links from headwater to basin outlet. HSPF requires as input the grid data (DEM, land use) 86 and the hydro-meteorological data – precipitation, potential evapo-transpiration, air (a) (b)

13 14 916

Inflow from Heyuan 2 3 8 Lee J.H.W.

9 1 4 12 15 10 11 1

14 al. et 3 4 Outflow to 2 7 Qiaotou 12 5 10 15 6 5 7 11 8 16

Figure 7 Water quality modeling of East River: (a) lower East River Basin; (b) HSPF sub-basin linkage temperature, dew point temperature, solar radiation, wind speed and cloud cover. The model is well suited to provide robust daily streamflow and water quality predictions when there is extremely limited data for model calibration and validation. The model is used to predict streamflow and water quality for 1985–2006; model parameters are calibrated against water quality data in 1998. Due to the scarcity of data, the streamflow input from outside of the study area is predicted by MIKE-SHE; at the upstream boundary a constant value is prescribed for pollutant concentrations which are relatively low (PRWRPB, 2000). Based on demographic and pollution data in government reports (PRWRPB, 2000), the point source (PS), non point source (NPS) and wet deposition pollution loads (kg/d) from (i) agricultural, (ii) domestic and (iii) industrial sources can be estimated for each county (from the county loads and percentage area of each county in the sub-basin). NPS loading from (i) urban, (ii) agriculture and (iii) forest areas is brought to the river by overland flow through an accumulation-washoff scheme. NPS loading for different land uses can be estimated using an “export coefficient” (t/km2/a) approach (Fok et al., 2004). Wet deposition from precipitation is represented by a constant concentration. More details of the HSPF modeling can be found in Thoe (2007).

The predicted monthly-averaged streamflow and pollutant (BOD5 and NH4) concentrations at Boluo and Qiaotou are shown in Figure 8. Predicted concentrations are of the same order of the limited available data (PRWRPB, 2000), and are consistent with our field investigations. Normally both BOD5 and NH4 concentrations are below the Chinese National Grade II water quality threshold. However, in recent years, due to the rapid economic and population growth, and the inadequate sewage treatment in the region, a consider- able increase of pollutant concentration is predicted. Also, there is a sharp increase in pollutant concentrations when passing from Boluo to Qiaotou. This phenomenon can be attributed to the tributary Shimahe (lies in sub-basin 11, Figure 7(a)), which enters the mainstream of the East River at Qiaotou. With a drainage area covering the developed Dongguan city, the Shimahe tributary is expected to contribute about 70% of the total pollution loading to Qiaotou. Mainstream usually shows less environmental problems when compared to tributaries; the large mainstream flow generally affords a very high assimilative capacity. The seasonal variation of water quality of the East River can be illustrated for three years with distinct hydrological characteristics. May 2001–April 2002 represents a normal year; May 2004–April 2005 represents an exceptionally dry year while May 2005– April 2006 is an exceptionally wet year. The annual average streamflow at Qiaotou is 87 ...Lee J.H.W. tal. et

Figure 8 Predicted monthly-averaged streamﬂow and water quality at Qiaotou (1985–2006)

987 m3/s, 430 m3/s and 1,511 m3/s for these three years respectively. Figure 9 shows the daily averaged pollutant concentration at Qiaotou for each year. It is clear that the water quality is signiﬁcantly worse in a “dry year”. The differences in pollutant concentration for normal and wet years are not very obvious. It can also be seen that the drinking water standard is likely to be violated during the dry months at Qiaotou. In 2004, the predicted

averaged BOD5 and NH4 concentrations are 5.16 mg/L and 1.39 mg/L respectively; the corresponding monthly flow is 114 m3/s. If Grade II water quality standard is to be met at Qiaotou, a streamflow of 196 m3/s and 317 m3/s would be required. A minimum streamflow of 317 m3/s is hence required for satisfactory waste assimilation in the East River.

Water sustainability assessment The East River supports a variety of needs including drinking water supply, agriculture and industry, navigation, hydro-power generation, waste assimilation, and habitat for aquatic life. Based on the foregoing hydrological and water quality modeling, a quantitat- ive assessment of river health and water sustainability can be made. First, based on socio-economic growth, the annual water supply demand from the East River increases to 47.3 £ 108 m3 in 2010, and the pumping rate for water supply can be estimated to be 3 about Qs ¼ 150 m /s (PRWRPB, 2000). Second, based on the water quality model, the 3 minimum streamflow required for Category II water is Q1 ¼ 317 m /s. To support aquatic habitat, the ecological base flow can be estimated using the “Montana method” based on historical records of discharge. Tennant (1976) concluded that 10% of the average annual flow is the minimum instantaneous flow needed to sustain short-term survival. A flow of 30% of the average annual flow is required to maintain good habitat for aquatic life. The corresponding minimum and desirable ecological base flows can then be determined to 3 be about Q2 ¼ 76 and 230 m /s respectively. Third, based on a minimum depth of 1 m 88 for navigation, and the average width and bottom slope near Qiaotou, the minimum ...Lee J.H.W. tal. et

Figure 9 Predicted daily averaged streamﬂow and water quality at Qiaotou

3 streamflow for navigation can be estimated to be Q3 ¼ 210 m /s. Finally, in dry years, sea water intrusion into the East River can be a significant problem. Based on field data on the extent of sea water intrusion defined by the 0.5 ppt salinity contour, the minimum river flow to arrest the saline intrusion below Qiaotou has been estimated to be 3 Q4 ¼ 150 m /s (Wu et al., 2001). In summary, the minimum river flow to sustain and support the different functions can be calculated as:

3 MWR ¼ Max{Q1; Q2; Q3; Q4} þ Qs ¼ Maxð317; 230; 210; 150Þþ150 ¼ 467 m =s where MWR is the minimum in-stream water requirement. The frequency distribution of daily averaged ﬂow at Qiaotou shows this ﬂow requirement of 467 m3/s is associated with an exceedance frequency of around 55 percent (Figure 10).

Figure 10 Daily averaged streamflow distribution at Qiaotou (1955–1987) 89 Conclusion A study of the health and water sustainability of the East River Basin has been carried out using hydrological and water quality models, and field investigations. The field data show that the water quality is generally good in the upper and middle reaches, and well exceeds drinking water quality standards. Due to anthropogenic activities, the water quality deterio- rates in the downstream reaches towards the river mouth. Benthic macro-invertebrate

...Lee J.H.W. diversity is correlated with water quality. The water quality along the East River is satisfactorily predicted through the application of the distributed MIKE-SHE hydrological model and the lumped parameter HSPF model. It is shown that the significant increase in pollu- tal. et tant concentration from Boluo to Qiaotou is due to the pollution loading from the Shimahe tributary near Dongguan. By considering the needs of the East River for waste assimilation, water supply, navigation, prevention of seawater intrusion, and ecological preser- vation, it is estimated that the required minimum flow for water sustainability is 467 m3/s; this daily streamflow is only exceeded in the East River with a frequency of 55%. Since the water sustainability requirements cannot be comfortably met by the streamflow alone, the present sustainability assessment suggests that alternative strategies including integrated water resources management (reservoir operation to increase emphasis on flood control and in-stream water requirement), provision of better and more effective wastewater treatment, and water and soil conservation should be considered.

Acknowledgements The study is supported by a NSFC/RGC joint research project (50838003 and HKU747/03). The assistance of P.J.F. Yeh, Y.X. Zhang, L. Fok, K. Fan, A.W. Jayawar- dena, A. Koenig, at different stages of the project are gratefully acknowledged. The support of the Pearl River Water Resources Commission in the ﬁeld studies is deeply appreciated.

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