Multi-parameter Water-Quality Probes (YSI/Hydrolab)

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

• 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 datahttp://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.

MonitoringUpper

Lower

• 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 &Zostera &HaloduleHalodule

Salinity Spline and Additional Pts

High Low

Client tools!

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

Table 1: Threshold concentrations for three water-quality components, calculated from measured optical properties in North River, NC in 2003.

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.