Transcript Multi-parameter Water-Quality Probes (YSI/Hydrolab) Lecture 5 Retrieval • Rinse in freshwater (fill sensor cup). • If heavy fouling add 1-2% bleach • Do post calibration.

Multi-parameter Water-Quality
Probes (YSI/Hydrolab)
Lecture 5
Retrieval
• Rinse in freshwater (fill sensor cup).
• If heavy fouling add 1-2% bleach
• Do post calibration next day BEFORE
cleaning thoroughly.
• Download data file to EcoWatch software.
• Export to XL or stats package
EcoWatch software
Data problems
• Check battery voltage – no power, no data
• Conductivity cell – fouling causes salinity
to decrease over time
• NTU and CHL sensors fouling over optic
window. Bubbles cause SPIKES.
• Clark DO probe fails under prolonged
hypoxia (10-14 days) as all KCl used up.
• pH well buffered, should not change much
• Low tides may cause air exposure…
Summary statistics
• Min and Max (good for weeding out
obviously bad data (e.g. neg salinity)
• Range (=max – min)
• Mean (=average)
• Standard deviation (=stdev) – msr of
variability
• Coeff Variation (=stdev/mean*100) – msr
of variation as percentage of mean. 5% is
generally accepted in lab work.
Set data in biological context
• Min-Max of range (optimal, lethal)
• # days in suitable range
• Periodicity of optimal, suboptimal
conditions – stress:recovery
• NEED TO KNOW ABOUT YOUR
ORGANISM!
Lab
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Clean YSI retrieved from Pier
Download data
Explore data in Ecowatch
Export data as *.csv file
Import data into Excel
Check for errors/bad data – flag these
Calculate summary statistics
GCRL pier data
http://sites.google.com/site/drcgrass/home/water-quality-monitoring
Data analysis – using ArcGIS
spatial analyst for mapping
The problem
• Time series data – high frequency, but few
points.
• Need to create a “map” – very easy for
humans to interpret (even non-scientists!)
• Spatial Interpolation – a geostatistical
method.
• Spatial Interpolation
• Interpolation is defined as the method of
predicting values for a whole surface based on
sample point values. The assumptions are that
the values occur on the whole surface, i.e. they
are continuous and not discrete, and that they
are spatially related to the surface properties.
Spatial interpolation is used to estimate a value
of a variable at an unsampled location from
measurements made at other sites within a
defined area. Interpolation is based on the
principle of spatial dependence which measures
the degree of dependence between near and
distant objects.
Monitoring
Upper
• Turbidity/Color gradient
• 3 regions along gradient
Middle+Lower region has seagrass
• 3 Stns per region
Sampled 1 day/mo.
Water - chl a/TSS/C-DOM
LiCor+YSI profile (0.5m inc.)
Secchi depth
• 1 “Permanent” Stn per region
Sample each quarter for a month
Mar., Jun., Sept, Dec 2003.
LiCor (5min) and YSI (30min) @
1m depth.
Middle
Zostera &
Halodule
Lower
Salinity Spline and Additional Pts
High Low
Client tools!
Table 1: Threshold concentrations for three
water-quality components, calculated from
measured optical properties in North River,
NC in 2003.
Depth
(m)
Chl a
(ug/L
TSS
(mg/L)
CDOM
(1/m)
0.5
340.3
171.3
28.1
1.0
156.8
73.8
11
1.5
96.6
44
5.83
2.0
61.1
30.1
3.55
3.0
38.8
17.1
1.66
Clients will include federal, state and
local environmental agencies and
water quality monitoring organizations
with an interest in protecting seagrass
as EFH. Can also include research
and education organizations.
Summary
• Need to check data – manually or develop
routines (macros).
• Generate summary statistics – compare to
species of interest / threshold criteria
• Map data if enough points exist.
• Map regions of concern based on criteria.