在河流健康评估中使用现有数据在河流健康评估中使用现有数据

澳大利亚澳大利亚 Chris Gippel Chris Gippel 博士博士

项目完工研讨会项目完工研讨会

Ministry of Water ResourcesMinistry of Water Resources

2012 February 232012 February 23

River health assessment

Key drivers•Hydrology

•Water quality

•Physical form

•Riparian vegetation

Indicators help informmanagers how to act

Indicators reflect management performance

•Social– Production of goods– Recreation– Drinking water– etc.

Key responses•Biological

– Fish– Macroinvertebrates– Algae

All indicator groups are useful

Data gathering programs already existData gathering programs already exist

Benefits / limitations of using existing data

Benefits

Low cost

System will continue to provide data

Quality control and staff training systems established

Data collected frequently

Historical data available

Limitations

Site location is pre-determined

Few sites in each catchment

Most sites are on main stems and large tributaries

Data have to be obtained from the program owner

For water quality, data might not contain the desired parameters

How to incorporate existing data

Hydrology and water quality station

River health monitoring site

Using the historical recordsW

ater

qu

ality

Years

Bio

logy

Years

Hyd

rolo

gy

Years

Begin riverhealth program

Using the historical recordsW

ater

qu

ality

Years

Bio

logy

Years

Hyd

rolo

gy

Years

Began e-flow Begin riverhealth program

Converting hydrology data to indicator scores

No e-flows study• Assume monthly data

available

• Assume data available before regulation - “reference” hydrology

• Calculate ecologically meaningful indicators

• Score from 0 - 1

E-flows study done• Assume daily data available

• E-flows recommended components define the “reference” hydrology

• Measure the compliance of the flow with the e-flows components

• Score from 0 - 1

Flow Health – monthly data

Taizihe – LiaoyangHigh disturbance太子河 -辽阳 , 人类干扰很大

0

100

200

300

400

500

600

700

800

Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct

Mo

nth

ly f

low

(m

3

106)

50th percentile in reference period

25th percentile in reference period

Year 1999/2000

Persistently low (PLF)and persistentlyvery low (PVL)

Persistentlyhigh (PHF)

High f low season volumegreatly reduced (HFV)

Low f low season volumegreatly reduced (LFV)

Seasonality altered (SFS)

Lowest monthly f lowgreatly reduced

from reference (LMF)

Highest monthly f lowmoderately reducedfrom reference (HMF)

Flow Health – monthly data

0

200

400

600

800

1000

1200

Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

Mo

nth

ly f

low

(m

3

106)

50th percentile in reference period

25th percentile in reference period

Year 2007/2008

Persistently lowreduced (PLF)

Persistentlyhigh OK (PHF)

High f low seasonvolume OK (HFV)

Low f low season volumeslightly reduced (LFV)

Seasonality intact (SFS)

Lowest monthlyf low OK (LMF)

Highest monthlyf low OK (HMF)

Persistently verylow OK (PVL)

Guijiang – Guilin Low disturbance桂江 -桂林，干扰较小

Score relative to reference

75th

percentile25th

percentileMaximumMinimum

Fre

qu

en

cy

of

ob

ser

va

tio

ns

in

re

fere

nc

e p

eri

od

High flow season hydrological attribute value

75th

percentile25th

percentileMaximumMinimum

Fre

qu

en

cy

of

ob

ser

va

tio

ns

in

re

fere

nc

e p

eri

od

Low flow season hydrological attribute value

V large V small

Deviation from reference range of variationSmall

ModerateLarge

Very small

Reference rangeof variation

Small

Score = 1Score = 1

Score = 0 Score = 0

Converting water quality data to indicator scores

Percent of time target met• Set a target grade (I – V)

• Calculate grade for each month

• Calculate percent of months reaching target grade

• Percent of time at target =score from 0 - 1

Weighted grade method• Weight each water quality grade (I =

1.0….V = 0.0)• Calculate grade for each month• Calculate percent of months

reaching each grade• For each grade, calculate percent of

time X weighting• Add the weighted scores =

score from 0 - 1

Summary

• Existing water quality and hydrology data help to tell the history of river health

• Using existing data is inexpensive• Existing data can be combined with data from a site monitoring

program• The indicator score calculations are very easy