Assessment of Climate Change Impact on Future Turbidity Current Regimes in Soyang Lake with CE- QUAL-W2 Considering SWAT Inflows

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1 SESSION G2: ENVIRONMENTAL APPLICATIONS Amphitheater Shannon, Room U4.6 11:00 12:20 p.m. Assessment of Climate Change Impact on Future Turbidity Current Regimes in Soyang Lake with CE- QUAL-W2 Considering SWAT Inflows 2013.07.18. Ha, Rim J. Y. Park, S. R. Ahn, S. H. Kim, S. J. Kim* Dept. of Civil & Environmental System Eng. Konkuk University South Korea

2 CONTENTS 1 2 3 4 5 6 Introduction Climate Change scenario SWAT Modeling CE-QUAL-W2 Modeling Future Turbidity Current Regimes Summary & Concluding remarks

3 1. Introduction Change of water quality issues in Korea Before 1970s No pollution problems No concern about environmental conservation In 1980s High BOD from sewage Fish farms installed in many reservoirs In 1990s Sewage treatment systems established Active operations of fish farms within reservoirs Eutrophication problems emerged Algal toxins were reported Current issues in 2000s Turbidity and siltation major ecological hazard TMDL of BOD and TP for water quality management - Phosphorus removal from sewage

4 1. Introduction Turbidity problem in reservoirs Turbid water lasts 3 months after summer monsoon in the Han River. Reservoirs are filled with turbid water after monsoon. Large dams prolong the duration of turbid water in downstream. Destroys aquatic ecosystems. SAV is reduced. Fisheries are reduced. Fall: Sediments emerged. In 2006, turbid water in Soyang river aggravated by the typhoon Ewiniar, sustained for over 280 days unlike conventional years, then which interrupted water supply of Chuncheon and Seoul areas.

1. Introduction Turbidity problem in reservoirs Cause of Turbidity problem Highland agriculture area 63% of the total highland agricultural area in South Korea Iuding imprudent development of mountainous area Landslides, Road expansion, washed and road construction for forestry 5

6 1. Introduction Persistent turbidity in reservoirs and their downstream after flood events is an important environmental issues in Korea. One of the most important water management issues of Soyang Lake (located in North Han River in Korea) is a long term discharge of turbid water to downstream during flood season. Water in Soyang river is an essential source for citizens of Chuncheon and Seoul areas. In these situations, it is very urgent to look for the fundamental causes of long term effects by climate change of turbidity in lake, and to also get measures about for such problems. The main goal of this study is to evaluate the future climate change impact on turbidity current regimes for Soyang Lake watershed in South Korea using SWAT watershed model and CE-QUAL-W2 lake water quality model.

7 1. Flowchart of Study Baseline(1990-2010) 2011-2040 2041-2070 2071-2100

2. Climate Change scenario Downscaling 8 IPCC AR4 RCM climate change scenario ECHO-G (GCM) MM5 RCM (Regional Climate Model) Temperature (maximum, minimum) Precipitation Relative humidity 1860 2100 A1B, B1, A2 400 km (~3.75 ) Monthly Dynamic Downscaling EHCO-G (400km) MM5 (27km) MM5 (RCM) 1871 2100 A1B 27 km (~0.243 ) Monthly, Daily Downscaling (Artificial Neural Networks method) Model Country Grid size CONS: EHCO-G Germany / Korea 96 48 SWAT model Typhoon Simulation, Quantile Mapping

9 3. SWAT Modeling Water balance equation SW t = SW 0 + t i=1 (R day - Q surf - E a - W seep - Q gw ) SW t = Final soil water content (mm) SW 0 = Initial soil water content on day i (mm) R day = Amount of precipitation on day i (mm) Q surf = Amount of surface runoff on day i (mm) E a = Amount of evapotranspiration on day i (mm) W seep = Amount of water entering the vadose zone from the soil profile on day i (mm) Q gw = Amount of return flow on day i (mm) Sediments : MUSLE (Modified Universal Soil Loss Equation) Sed = 11.8(Q surf q peak area hru ) 0.56 K C P LS CFRG Sed = Sediment yield on a given day (ton) Q surf = Surface runoff volume (mm/ha) q peak = Peak runoff rate (m3/s) area hru = Area of the HRU (ha) K = USLE soil erodibility factor C = USLE cover and management factor P = USLE support practice factor LS = USLE topographic factor CFRG = coarse fragment

3. SWAT Modeling Multi-purpose Dam Watershed Description Soyang Lake Watershed Study area: 2,694.4 km 2 Forest area ratio: 88.6 % South Korea: 99,373 km 2 The annual average precipitation: 1,153 mm The annual mean temperature: 10.3 The 123 m (404 ft) tall dam withholds a reservoir of 2,900,000,000 m 3 Model Input data Observed data Station Period Soyanggang Dam Dam inflow 1998~2010 Hydrological Naerincheon Stream flow 1998~2010 Water quality TMDL 8day Inbuk A 2004~2010 Soyang B 2004~2010 10

11 3. SWAT Modeling Map data (Land use, soil and elevation data) Spatial resolution : 100 m Landuse : Land cover was classified with 7 categories. Forest (88.6%), Upland Crop (4.4%), Paddy (2.1%) Soil Texture : Most soil cover is Sandy Loam (32.3%), Loam (31.8%), and Silty Loam (21.5%) respectively. Average Elevation : 650 EL.m Land use Soil type DEM Soyang-gang Dam

12 3. SWAT Modeling Streamflow results Calibration : 3 years (2005-2007) / Validation : 3 years (2008-2010) 1 NC located upstream and 2 SD in the watershed outlet 1 Naerin-cheon Calibration R 2 : 0.81 / NSE : 0.78 2 Soyang-gang Dam Validation R 2 : 0.69 / NSE : 0.67

13 3. SWAT Modeling Stream water quality results Sediment R²: 0.68 Sediment R²: 0.75 Total Nitrogen R²: 0.41 Total Nitrogen R²: 0.82 Total Phosphorus R²: 0.21 Total Phosphorus R²: 0.20

3. SWAT Modeling Future hydrologic cycle Baseline 2030s 2060s 2090s PCP (mm) Runoff (mm) S flow (mm) B flow (mm) ET (mm) Scenarios Precipitation (mm) Evapotranspiration (mm) Surface flow (mm) Base flow (mm) Runoff (mm) Baseline 1412.8 515.3 534.8 323.6 856.1 2030s 1563.5 551.2 612.0 357.9 967.3 (2011-2040) (+10.7%) (+7.0%) (+14.4%) (+10.6%) (+13.0%) 2060s 1677.4 564.3 680.9 387.2 1065.3 (2041-2070) (+18.7%) (+9.5%) (+27.3%) (+19.7%) (+24.4%) 2090s (2071-2100) 1959.4 (+38.7%) 586.0 (+13.7%) 897.5 (+67.8%) 423.5 (+30.9%) 1317.9 (+54.0%) 14

15 3. SWAT Modeling Future stream water quality Sediment +22.9% ~ +126.5% Total Nitrogen +11.4% ~ +50.4% Total Phosphorus +2.7% ~ +17.1%

16 4. CE-QUAL-W2 Modeling Model coupling Technique Artificial Neural Network Temperature, Precipitation, Relative humidity Air temp. condition (ATC) CE-QUAL-W2 ATC, IFC, OFC, WTC, WQC Initial ATC and WQC SWAT Runoff, T-N, T-P, SS Runoff HEC-RESSIM Inflow condition (IFC) Water quality condition (WQC) Multiple Regression Analysis Using Temp. and runoff Water temp. condition (WTC) SWAT Output Runoff PO 4 NO 3 NH 4 Chl-a CE-QUAL-W2 Input Inflow PO 4 NO 3 NH 4 Chl-a Dam outflow Dam Outflow condition (OFC) Organic-N OM group Organic-P Water Temperature Dam Outflow

17 4. CE-QUAL-W2 Modeling CE-QUAL-W2 (U.S Army Corps of Engineers, 1986) It has been applied successfully to hundreds of rivers, lakes, and reservoirs around the world. At a reach scale, a long, narrow, pooled river is typically a good candidate for a two-dimensional, laterally averaged model. Useful for metalimnion modeling. Sediment LPOM RPOM Algae Epiphyton CBOD

18 4. CE-QUAL-W2 Modeling Model body Setup Segment boundaries were specified to form 138 active segments in the main river reach from upstream start point of Soyang River to Soyang-gang Dam (branch 1) Water body Branch Segment Layer (maximum) 1 1 138 134 200 180 160 140 120 100 80

19 4. CE-QUAL-W2 Modeling Boundary condition Validation Water level : Observed vs. Simulated Water temperature, Sediment, Water quality Calibration / Validation Model Input Data (Boundary conditions) CE-QUAL-W2 Inflow SWAT outflow CE-QUAL-W2 Outflow : Consider of release for hydropower and spillway Calibration : 2010 Validation : 2006

20 4. CE-QUAL-W2 Modeling Model Input Data (Initial conditions) Inflow water temperature Use of the Multiple Regression Equation (Q~T water ~T dewpint ~T air ) SoyangA station data : Intervals of about 8 days Inflow water turbidity(ss) Use the Multiple Regression Equation (Q~SS) SoyangA station data: Interval of about 8 days Tw = 2.936 + 1.022Td 0.101Ta - 0.037Q WT WT eq 2004~2010 yr SoyangA R²: 0.98

Validation 2006 Calibration 2010 21 4. CE-QUAL-W2 Modeling Temperature SS T-N, T-P, chl-a turnover turnover

22 5. Future Turbidity Current Regimes Select future flow condition 10%(Flood year), 50%(Normal year), 90%(Drought year) 10 % 50 % 90 % Year 2024 2060 2082 2018 2056 2090 2013 2066 2096 Period F.F M.F L.F F.F M.F L.F F.F M.F L.F * F.F : 2011~2040 * M.F : 2041~2070 * L.F : 2071~2100

23 5. Future Turbidity Current Regimes Future Detention Time of SS In the future, the average detention time of SS increased by all period. Year Yearly Dam Inflow (CMS) Detention Time Min.(day) Max.(day) Avg.(day) 10% (Flood year) 2024 F.F 93.2 0.13 510.0 94.5 2060 M.F 106.9 0.48 329.1 94.9 2082 L.F 127.7 0.67 424.4 95.4 50% (Normal year) 2018 F.F 81.5 0.29 241.6 68.4 2056 M.F 87.6 0.20 139.5 36.1 2090 L.F 115.3 0.74 534.6 124.6 90% (Drought year) 2013 F.F 73.3 0.10 165.9 38.5 2066 M.F 75.2 0.30 147.3 37.1 2096 L.F 93.7 0.20 243.4 64.6

24 5. Future Turbidity Current Regimes Statistical summary of the future SS of segment inflow, share of lake inside, and dam outflow Under the future impact on reservoir inflow by SWAT, the future reservoir turbid current will be stayed longer more than present in metalimnion due to thermal stratification. Inflow Lake Share Outflow Class Year SS > 25mg/L Days Max. (mg/l) Days SS > 10 mg/l Max. (%) Avg. (%) SS > 25mg/L Max. Days (mg/l) 2027 F.F 98 166.7 152 100.0 22.9 10 33.8 10% 2058 M.F 120 196.4 184 58.9 12.1 20 32.0 2095 L.F 134 164.7 191 70.4 18.3 19 26.7 2020 F.F 108 155.5 163 98.2 14.6 0 19.6 50% 2047 M.F 127 182.2 155 94.7 20.6 21 37.2 2077 L.F 126 160.5 199 72.4 15.5 8 30.7 2021 F.F 101 137.8 173 75.0 14.4 0 17.3 90% 2048 M.F 120 132.5 155 87.8 15.5 0 12.7 2073 L.F 117 155.6 209 99.1 28.4 4 31.6

25 5. Future Turbidity Current Regimes The future SS of segment inflow, share of lake inside, and dam outflow Lake SS Outflow SS

26 6. Summary & Concluding remarks In this study, watershed model (SWAT) and reservoir water quality model (CE-QUAL-W2) were applied to assess the future climate change impact on turbidity current regimes in Soyang lake. CE-QUAL-W2 using SWAT inflows simulated the features of lake stratification regime, including the formation of a turbid intermediate layer in the reservoir. By the future prediction of lake turbidity current regimes considering SWAT watershed impact, the proper management of both watershed and lake would be possible for Soyang reservoir. This study results may include optimizing certain positive effects of reservoir operation as well as minimizing negative effects to downstream communities.

27 Thank You For further information, please contact: Ha, Rim Ph.D. Candidate, Dept. of Civil & Environmental System Engineering, Konkuk University rim486@konkuk.ac.kr We re on the Web! See us at: http://konkuk.ac.kr/~kimsj/ Earth Information Engineering Laboratory

28 Q & A