Page 1 Decision Support System for Water Pollution Reduction of Lake Chao, China Decision Support...

Decision Support System for Decision Support System for Water Pollution Reduction of Water Pollution Reduction of

Lake Chao, ChinaLake Chao, ChinaGünter Meon and Fucai YinGünter Meon and Fucai Yin

Leichtweiss-Institute of Hydraulic Engineering and Water Leichtweiss-Institute of Hydraulic Engineering and Water Resources, University of Braunschweig, GermanyResources, University of Braunschweig, Germany

Anhui Environmental Protection Bureau Anhui Environmental Protection Bureau

IFAT China 2008IFAT China 2008

1. Problem

2. Objectives and Approach

3. Ecohydrologic Model for

Catchment

4. Lake Model for Water Quality

5. Decision Support System

6. Conclusions

ContentsContentsProblemstellung

Untersuchungsgebiet

Strategien

Modellierung

Anwendung

Project “Minimization of Eutrophication in Lake Project “Minimization of Eutrophication in Lake Chaohu” Chaohu” • Project Duration

! 2 phases, 4 years until end of 2009

• Coordinator– Dept. of Hydrology, Water Resources Management and Water

Protection, Leichtweiss Institute, University of Braunschweig

• Partners– Anhui Environmental Protection Bureau, Province Anhui, PR China– Leibnitz-Institute for Water Ecology and Inland Fishery, Berlin

(IGB)– Institute for Waste Water and Environmental Engineering,

University of Braunschweig– Ecotech Company, Bonn

• Funded by– German Ministry of Education and Research BMBF– Chinese Ministry of Science and Technology MOST

South China Sea

B ay of B engal

Hai lar

Qiqihar

Yant ai

Dalian

Qingdao

Xiamen

Cho ngqing

Golm ud

Yumen

Kashi

Yining

Karamay

Shiquanhe

Zh anjiang

Kao hsiun g

Macau (Portugal)

Lianyungang

Burqi n

Hong Kong (U.K. )

Urumqi

Lhasa

Xining Lanzhou

Yinchuan

Xi'an

Chengdu Wuhan

Guiyang

Zhengzhou

Shijiazhuang

Tianjin

Hohhot

Taiyuan Jinan

Hefe i

Nanjing

Shanghai

Hangzhou

Nanchang

Changsha

Fuzhou

Guangzhou

Nanning

Kunming

Shenyang

Changchun

Harbin

Haikou

Beijing

Russia

Mongolia

Pak.

India

Nepal Bhutan

Ban gladesh

Myanmar (Burma)

Thailand

Laos

Vietnam

Ph ilippines

North Korea

South Korea

Cambodia

China

0 500 k m

0 500 m i

1996 MAGELLAN GeographixSMSanta Barbar a, CA (805) 685-3100

Chao-hu

1 1 ProblemProblem

Lake Chao and catchment Lake Chao and catchment

Shanghai

Lake Chao and catchment Lake Chao and catchment 1 1 ProblemProblem

• Lake Chao– 5th largest freshwater lake of

China; part of Yangtze River system.

– located in Anhui Province length: 53 km from east to west

22 km from south to north shore: 188 km

– surface: 760 km²– used for (fresh) water supply,

irrigation, shipping, fishery, tourism, etc.

• Catchment – 14.000 km² with 3 large cities

including Hefei City (capital of Anhui Province) and Chaohu City

– Population 10 Mio (16% of Anhui Province)

Eutrophication of Lake ChaoEutrophication of Lake Chao

• Completely mixed shallow lake, mean depth 3 m • Regulated outflow (water level)• In catchment: intensive agriculture, chemical fertilizers• Domestic and industrial wastewater (only few treatment plants)

Lake water pollution from point and non point sources

1 1 ProblemProblem

Extreme pollution

Strong pollution

Cyanobacterial bloom in Lake Chao, August 2005

1 1 ProblemProblem

Eutrophication of Lake ChaoEutrophication of Lake Chao

• During summer: often blooms of blue algae

(dominated by cyanobacteria)

• Cyanobacteria produce toxins

(microcystines <-> nerve system, cancer)

Objectives and approachObjectives and approach

• Analyse and model the water balance and nutrient budget of the catchment – lake system

• Quantify the anthropogenic effects on water quality in the catchment – lake system

• Develop a concept for waste water treatment in the catchment

• Develop a decision support system “DSS Chaohu” (incl. economic and ecologic performance indices and ranking procedures)

• Perform experiments for removal of microcystines in the lake water during algae blossom (short to medium term measures); design of large scale ecotechnical measures

• Operate DSS under AEPB

• With DSS: develop strategies for reduction of eutrophication to an acceptable level (medium to long term measures)

2 2 ApproachApproach

DSS CHAOLWI and AEPB

Objectives and approach – Project Phase 2 Objectives and approach – Project Phase 2 2 2 ApproachApproach

incl. models

Experiments 1

Ecotechnical ponds at landsideEnclosures inside lake

-> Microcystines in lake sediment-> Toxicity analyses

IGB, LWI and AEPB


DSS and experiments – Project Phase 2DSS and experiments – Project Phase 2


incl. models

Experiments 2

Biofiltration of lake waterBiofiltration in laboratory tests

ISWW and AEPB

Experiments 1



IGB, LWI and AEPB




incl. models

Experiments 2


ISWW and AEPB

Experiments 1



IGB, LWI and AEPB

Design Concepts

for large scale structures for ecotechnical lake water treatment

LWI and AEPB




incl. models

Experiments 2


ISWW and AEPB

Experiments 1


-> Microcystines in lake sediment-> Toxicity analysis

IGB, LWI and AEPB

Design Concepts


LWI and AEPB

Concepts

for waste water sanitationof point emissions in catchment

ISWW and AEPB




incl. models

Experiments 2


ISWW and AEPB

Experiments 1



IGB, LWI and AEPB

Design Concepts


LWI and AEPB

Concepts

for waste water sanitationof point emissions in catchment

ISWW and AEPB




incl. models

Rice terraces and runoff processesRice terraces and runoff processes

Source: Shan, 2001, Ambio, Vol. 30 No. 60

Source: Brinck, 2005, LWI

3 3 Eco-Hydrol. Eco-Hydrol. ModelModel

Input data for eco-hydrologic model NAXOS Input data for eco-hydrologic model NAXOS

Drainage network and subcatchments

Land use

Soil groups

DTM

3 3 Eco-Eco-Hydrol. Hydrol. ModelModel

Sub-catchments (hydrological units) of eco-hydr. Sub-catchments (hydrological units) of eco-hydr. modelmodel3 3

Subcatchment Fengle River, Taoxi StationSubcatchment Fengle River, Taoxi Station

3 3 Eco-Hydrol. Eco-Hydrol. ModelModel

Subcatchment Fengle River, Taoxi Subcatchment Fengle River, Taoxi Station Station - observed and simulated discharge - - observed and simulated discharge - 20032003

33Eco-Hydrol. M.Eco-Hydrol. M.

Multipond-systems in lake catchmentMultipond-systems in lake catchment

Source: Shan, B. et al., 2002

33Eco-Hydrol. M.Eco-Hydrol. M. Example: Liuchahe

River (C. Yin and B. Shan, Research Center for Eco-Environmental Sciences, Beijing 2001)

Factors influencing daily nutrient budgetFactors influencing daily nutrient budget

• Triple cropping system: - Early rice (May - Aug) - Late rice (Aug - Nov)- Wheat / rape (Nov - April)

• Irrigation water provided by ponds or partially by Lake Chao is enriched by nutrients

• Use of chemical and organic fertilizers (1 - 2 times per cropping season = 3 - 6 times per year)

• Waste water of rural households (non-treated); 4.5 Mio people in the countryside (0.6 g P, 10 g N/capita x day)

33

Nutrient modeling for Lake Chao catchmentNutrient modeling for Lake Chao catchment

tDNDP eCC 0,

PP, DP, PN, DN Conc. In Irrigation Water (NCIN,P)

Read TFL

Land Use = Paddy

Rice Season1.05.-30.07.

Or1.08.-1.11.

Yes

Soil Loss [SL]:

SL = R x K x LS x EPF x C

No

P24h < 25mm

Yes

Pad

dy

(hig

hlan

d, m

ount

ain

, pla

in)

Fo

rre

st /S

hru

bber

y La

nd/G

rass

land

Ara

ble

La

nd

Roc

k

Min

ing

Urb

an A

reas

Rur

al A

reas

Land Use

Wat

er

Land UseLand Use

Sediment Input [SED]:

SED = SL x SDRSDR

Load of PP / PN in Surface Runoff [LPP / PN] :

LPP / PN = SED x ER x SNCN,P x UF

ER

Industrial Discharge [ID]:

IDTP, DP, TN, DNIDQ

Waste Water Treatement Plant [WWTP]:

WWTPTP, DP, TN, DN

WWTPQ

PDiffuseNPNPoPN LLRL ,,int.

NutrientRetention

SL

- River Load [kg/d]- Nutrient Conc. [mg/l]

PNPDiffuseNPNPoPN RLLNIL ,,,int.

25mm ≤ P24h ≤ 60mm

No

P24h ≥ 60mm

No

Continuous Flow

Nutrient Retention in Multipond-System

[RPN,P]

- Paddy Load [kg/d]- Nutrient Conc. [mg/l]

PP, DP, PN, DN

No

Soil Nutrient Content [SNCN,P]:

SNCN,P = SNCini + PIS/NIS – POS/NOS

P-/N-Input of Soils [PIS / NIS]:

PIS / NIS = Inorg. Fert + Org. Fert. + Atm. Depostion + SPN,P

P-/N-Output of Soils (POS / NOS):

POS = HarvestNOS = Denitrifi + Volatiliz. + Harvest

SNCini

i

iiGWIntSurf A

ACDNDP

)(, ,,

GWIntSurfDNDP ,,,

No Outflow

Discontinuous Flow

Paddy Nutrient Content [PNC]:

Soil Loss [SL]:

SL = R x K x LS x EPF x C

PP / PN in Surface Runoff from Ponds [PPP/ PNP]:

LPP / PN = SED x ER x Psoil / Nsoil x UF

Yes

Yes

Tile Drainage [TDDN,DP] :

TDDN,DP =ADR x qDR x CDN,DP

P-/N-Input of Paddy [PIP / NIP]:

PIP / NIP = Inorg. Fert + Org. Fert. + Atm. Depostion

P-/N-Output of Paddy [POP / NOP]:

POP = Harvest

NOP = Denitrifi + Volatiliz. + Harvest

Sediments to adjacent soils

[SPN,P ]

LPP / PN

River LoadNutrient Input

into Lake

Particulate Nutrient Emissions

by Landuse

Dissolved Nutrient

Emissions by

Landuse

Dissolved and Particulate Nutrient Emissions

by Paddies and

Nutrient Storage by

Multipondssystem

Landuse:

Paddy or no

Paddy

Point Source Emssions

33Rice FieldsOther Land-

Uses

Nutrient modeling in Lake Chao catchmentNutrient modeling in Lake Chao catchment

33

Consequences for hydro-ecological modelingConsequences for hydro-ecological modeling

- Water cycle in Lake Chao watershed is strongly influenced by anthropogenic actions

- Retention of discharge is increased through multipond-systems

- Multipond-systems retain particle-bound nutrients

- Nutrients are partially recycled within the catchment

Challenge: combining natural processes and the effects of human interference in modeling

33

Water quality model for Lake ChaoWater quality model for Lake Chao

• deterministic dynamic model of the lake

(modified CE-QUAL model), combined with

catchment model

• simulation of hydrologic and

hydrodynamic processes

• simulation of dynamics of ecosystem:

suspended load, primary production,

algae,..

• Simulation of scenarios for different

nutrient imports and their influence on

algae bloom

4 4 Lake ModelLake Model

Lake model: temperatureLake model: temperature

Temperature in the Lake

0

5

10

15

20

25

30

35

40

0 30 60 90 120 150 180 210 240 270 300 330 360

Time (d)

Tem

per

atu

re (

°C)

Mittel im See

Modell

4 4 Lake ModelLake Model

Lake model: DO for western and eastern Lake Lake model: DO for western and eastern Lake

ChaoChao4 4 Lake ModelLake Model

DO

Experimental ecotechnical pond 1 - Experimental ecotechnical pond 1 - operatingoperating

DSS Chaohu: decision process workflowDSS Chaohu: decision process workflow

5 5

DSS-Chaohu: possible measures (scenarios)DSS-Chaohu: possible measures (scenarios)

Change of land-use

Optimisation of fertilization

Pre-Dams

Waste water treatment plants

Cultivation of water plants

Lake water treatment by ecotechnical plants

5 5

Restore multipond systems

ConclusionsConclusions

Strategien

Water quantity and water quality could be modelled fairly well; development of DSS is underway

Models had to be modified to deal with available data and simulate reasonable scenarios of the project

Ecotechnical plants reduce microcystines very efficiently

Combination of modelling, DSS and experiments is a useful and promising way to meet the demands of the project

Continuous and close cooperation with our Chinese partners

6 6

Pilotprojekt Chao-SeePilotprojekt Chao-SeeThank you ! [email protected]

Page 1 Decision Support System for Water Pollution Reduction of Lake Chao, China Decision Support...

Documents

Transcript of Page 1 Decision Support System for Water Pollution Reduction of Lake Chao, China Decision Support...