Wet weather water quality monitoring and urban flood analysis in Hue Citadel area Hiroaki Furumai Professor Research Center for Water Environment Technology Department of Urban Engineering The University of Tokyo
Canal-pond network and Huong river • The Hue Citadel area is located at 12km upstream from the Huong river mouth. Area: 5.21km 2 Population: 63,638 • The inner canal is linked with the outer canal which is connected with Huong river. • In rainy season, inundation occurs Citadel area several times a year. Le Thanh Ton Street N 1km Inundation situation on Nov. 16 th 2013 2 GEOSS/AWCI: May 27, 2014
Research Objectives 1. To investigate the characteristics of water pollution focusing on fecal contamination in the canals and ponds during dry and wet weather periods 2. To assess the influence of river water inflow and wastewater discharge on water flow and water pollution in canals by continuous monitoring with water depth and EC sensor 3. To develop urban inundation model considering river water level change 3 GEOSS/AWCI: May 27, 2014
Water sampling and Continuous monitoring Water sampling (16 points) :Canal ( B,C ) B 3 was conducted during dry and wet :Pond ( P ) weather in 2012. :Street （ S ） Water quality parameters : are E.coli , Total coliform, COD, NH4- S 2 C 3 C 2 N, EC etc. P 5 P 4 S 3 Continuous monitoring (13 points) S 1 P 3 P 7 was conducted by water depth S 4 and EC sensors during a rainy season, Sep. to Dec. in 2012. B 2 Vinyl pipe P 1 N C 1 EC sensor * Measured P 2 Water water depth depth sensor B 1 1km *JICA(2006), **Lieu et al(Hue University) 4 GEOSS/AWCI: May 27, 2014
Fecal contamination in canals, ponds, and inundated water 100000 10 5 Total Coliform (CFU/100mL) 10000000 10 7 P7 (Sep.) E.coli (CFU/100mL) 1000000 10 6 10 4 10000 C2 (Sep.) 100000 10 5 1000 10 3 QCVN:B2 10000 10 4 100 QCVN:B2 10 2 1000 10 3 Dry weather Wet weather N.D. DL N.D. 10 100 10 2 Canal Pond Street Canal Pond Street (Dry weather sample) {9, 10, 0} {9, 10, 0} n ＝ n ＝ (Wet weather sample) {4, 4, 4} {4, 4, 4} • E.coli and Total coliform (TC) concentrations of most samples exceeded the standard values (23 and 24 out of 27 samples (85 and 89%), respectively) • E.coli and TC concentrations were higher in many samples than the regulation values (5 and 8 out of 8 samples, respectively). • Inundated water samples at streets also showed high E.coli concentration. 5 GEOSS/AWCI: May 27, 2014
Use of EC as pollution indicator and EC monitoring in canal EC vs TDS 69 96 300 72 250 129 142 TDS (mg/L) 200 187 150 427 450 241 264 100 50 y = 0.529x + 9.2894 396 R² = 0.9976 135 234 0 0 200 400 600 352 EC (μS/cm) EC vs NH 4 -N EC vs Total coliform 190 56 Total coliform (log(CFU/100mL)) 1.6 5.5 163 1.4 5 1.2 NH 4 -N (mg/L) 158 152 EC ( μS /cm) 1 4.5 400 0.8 QCVN:B2 135 4 N 300 0.6 y = 0.002x + 3.997 200 0.4 3.5 R² = 0.4735 y = 0.0026x + 0.04 0.2 100 R² = 0.8096 58 3 0 0 1km 0 0 200 200 400 400 600 600 EC (μS/cm) EC (μS/cm) 6 GEOSS/AWCI: May 27, 2014
Inundation simulation in Hue City Model simulation has been conducted in the Hue Citadel area to explain the inundation situation. We plan to conduct model simulation under climate change and discuss on possible effective countermeasures for river flood and urban inundation control. Simulation results Past inundation record GEOSS/AWCI: May 27, 2014 7
Required data for model simulation 1) Drainage system data ・ Sewer system ・ River, channel and pond 2) Ground elevation and surface data ・ Ground elevation ・ Land use 3) Meteorological data ・ Rainfall 4) Hydrological data ・ Water level of river, channel or pond 5) Data for model calibration ・ Inundation depth and area ・ Water quality of inundated water 8 GEOSS/AWCI: May 27, 2014
Flowchart of urban inundation model development and Scenario analysis For model construction Model construction Data collection - Drainage system Data processing by GIS software - Land use - Ground elevation For parameters of calculation Inundation simulation Data collection - Rainfall data - Water level and quality of river - Water level and quality of channels and ponds in urban area - Flow and quality of wastewater Model calibration Checking the model performance Data collection For calibration - Record of inundation area, depth Scenario analysis - Water quality of inundated water Predicted future rainfall data and river flow data Possible measures for under climate change flood and pollution control 9 GEOSS/AWCI: May 27, 2014
Inundation simulation with water level rise 2year-2day rainfall (interval 60 minutes) Simulation condition: 80 Rainfall intensity(mm/hr) Total: 164mm 70 61.1mm/hr 60 Return period 2 years -2 days rainfall 50 40 Maximum rainfall intensity: 61.1mm/hr 30 20 10 Total rainfall: 164mm 0 1 5 9 13 17 21 25 29 33 37 41 45 Duration (hours) Water level 2.0m Water level 1.0m Freefall ： inundation area = 232ha ： inundation area = 167ha : inundation area = 172ha Inundation depth(m) 0.5 0.2 0.1 Inundation area expands with increasing the river water level. Therefore, it is very important to consider river water level to evaluate urban inundation situation. 10 GEOSS/AWCI: May 27, 2014
Increase of heavy rainfall event in Hue - GCM model prediction on rainfall - - 5 GCM models : GFDL, MIROC_H, MIROC_M, MIUB, GISS - Model calculation (1981-2000) and prediction (2046-2065) - Average frequency of 5 models during rainy season (Sep-Dec) 1981-2000 2046-2065 [days] [days] 10 10 7.66 8 8 6.83 6 6 4 4 2.40 2.28 2 2 0.76 0.54 0 0 > 50mm/d > 100mm/d > 200mm/d > 50mm/d > 100mm/d > 200mm/d 11 GEOSS/AWCI: May 27, 2014
Conclusions and future task • Fecal pollution : Most of the canals and ponds are fecally contaminated during both dry and wet weather periods. • EC usage as an indicator of water flow : EC value indirectly indicates pathogenic pollution level. EC sensor is very effective tool to know continuous change of water flow as well as water pollution in urban canal which is affected by wastewater and river water inflow. • Urban inundation simulation: The developed sewerage model linked with river water level is useful to estimate the detailed inundation characteristics in the Citadel area. In the next step, it is necessary to conduct model estimation of pathogenic pollution during rainy season and to propose effective measures for flood and health risk management under climate change. 12 GEOSS/AWCI: May 27, 2014
Thank you for your attention Hiroaki FURUMAI Professor, Research Center for Water Environment Technology, Graduate School of Engineering, University of Tokyo furumai@env.t.u-tokyo.ac.jp River flood Inland flood (Inundation) 13 GEOSS/AWCI: May 27, 2014
Key Points of Inter-linked Research in Hue Adaptation to Climate Change => Understanding and assessing climate change-related risk • 3 Risks : flood risk, inundation risk, health risk Hydrological model --- Watershed scale Inundation & runoff quality model --- Drainage scale Health risk model --- Community/Human scale Multi-scale analysis • 3 M : Modeling, Monitoring, and Management Data collection for Modeling Model calibration and validation Sampling and Monitoring work Scenario development and analysis for Management Inter-linked research 14 GEOSS/AWCI: May 27, 2014
Inter-linked Cooperative Research in Huong River Basin Research Steps and Final Goal WEB-DHM model --- Watershed scale (River flood risk) 1) Evaluation of river flow/floods at the Hue city using the watershed hydrological model. U rban inundation model --- Drainage scale (Inundation risk) 2) Evaluation of inundation characteristics using the urban inundation model considering the output of 1) . WQ Monitoring ---- Drainage scale (Water quality risk) 3) Evaluation of pathogenic pollution during flooding based on the output of 2) and water quality monitoring. Dose-response relationship --- Community/human scale (Health risk) 4) Estimation of human health risk during flooding. How to manage river flood, urban inundation, and flood-related health risk under climate change? 15 GEOSS/AWCI: May 27, 2014
16 GEOSS/AWCI: May 27, 2014
River flood Inland flood River flooding in Hue city at Nov. 8 th , 2013. http://talkvietnam.com/2013/11/hue-city- hydropower-dams-open-districts-submerged/) Inland flood (inundation) in Hue city at Sep. 4 th , 2009. http://tropical.way-nifty.com/blog/2009/09/rainy- season-ha.html) 17 GEOSS/AWCI: May 27, 2014
Research Background - flood and water-born diseases - • Frequent urban flooding and its damage during rainy season in Southeast Asia • High occurrence rate of water- Inland flood (inundation) in Hue on Sep. 4 th , 2009. born diseases during and after Epidemic period urban flood Schwartz et al., 2006 of cases per week Mean number Flooded period 90 % percentile Flood starts Weeks 18 GEOSS/AWCI: May 27, 2014
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