Welcome to CSI's Database


This database contains water quality results from over 100 locations in the 800 square mile Cayuga Lake watershed in central New York. Seven autonomous groups of volunteers partner with CSI to collect samples at fixed stream locations up to five times a year under base flow and stormwater conditions and transport them to CSI's certified lab for analysis of bacteria, sediment, nutrients and minerals. Volunteer groups sample most streams from their headwaters to their mouths, providing snapshots not only of water quality in different reaches but the pattern of water quality across the stream's entire watershed, as well.



One outcome of volunteer-CSI monitoring partnerships are estimates of the amounts of phosphorus and sediment entering Cayuga Lake from its tributary streams, referred to as "loads". Loads are important because the lake's southern end was placed on the federal government's list of impaired water bodies in 2002. Total Maximum Daily Loads, essentially a "pollution diet", could be imposed at some point. Loads of phosphorus and sediment can be estimated by combining their concentrations in samples collected by volunteers at the mouths of Cayuga Lake tributary streams with flow data from the U.S. Geological Survey. CSI's load estimates show how many tons of pollutants each tributary stream loads to Cayuga Lake in a year. By sampling throughout a stream's watershed, volunteers also help identify where pollutants originate.



How this database is organized 


Monitoring events: The CSI database is used to report the results of monitoring events. Each date on which a sample or set of samples is collected and analyzed is considered a monitoring event. A monitoring event has certain attributes, for example:

  • its date and time

  • whether groundwater or surface water

  • base flow or stormwater

  • synoptic* or partial (*all locations in a monitoring set sampled on same day)

  • Which lab and field analyses are performed

 

The raw data produced by monitoring events are accessed and sorted by means of “filters” built into the database’s Query Interface (see below).

 

Spatial hierarchy: Spatial context is essential for interpreting water quality data. The CSI database is organized according to a 3-tier geographic hierarchy.

Spatial Tier 1: Monitoring region. Only one region, the Cayuga Lake Watershed, is included at present. The scope of the database is being expanded to include the Susquehanna River Basin and other regions.

Spatial Tier 2: Monitoring sets. A monitoring set is a set of fixed locations that are grouped together for monitoring purposes. The locations in a monitoring set are determined, in partnership with CSI and local government agencies, by the community-based volunteers who take responsibility for collecting samples. Monitoring sets may be:

  • fixed locations on a stream

  • drinking water wells belonging to residents in a county who volunteer to publicize their private test results

  • a set of regulated point sources such as sewage treatment plants

Spatial Tier 3: Monitoring location. This tier gives specific information on the location where each individual water sample is collected.

The 3-tier spatial hierarchy facilitates interpretation of water quality data while opening the data collection process to significant input from community volunteers. 


How to access and search raw data 


  1. Click on Search Database at the top of this page to go to the Query Interface. The Query Interface is arranged in columns, each column corresponding to a category of event attributes. You will find several sets of drop-down menus to filter the raw data and select the set of event attributes that interest you.

  2. To access the first set of drop-down menus, hover the cursor over any column heading and click on the arrow that appears. A drop-down menu presents three options:

    • Ascending/descending

      • Ascending/descending is different for each column and orders the entries in that column, for example, by date.

      • Note: Ascending/descending is enabled for some but not all columns.

    • Columns

      • Triggers a drop-down menu which is the same for all columns and allows you to choose which categories of event attributes you want to appear on the page.

    • Filter

      • Prompts a set of drop-down menus, which are different for each column. The Filter menus allow you to select specific event attributes, for example,

        • a date

        • base flow or stormwater conditions

        • a monitoring set

        • a monitoring location within a monitoring set

        • an analyte

      • The Filter menus provide the keys to searching the database.

      • Note: If the Filter menus appear distorted, try changing the pixel setting on your computer display.

 

How to download raw data to MS Excel

 

The purpose of the CSI database is to make scientifically credible water quality monitoring data available for use by the general public, regulators and policy makers. After you have selected the data you’re interested in, you can download it by clicking on the MS Excel icon at the bottom right of the query interface page. It may take a couple of minutes to complete the download, depending on the amount of data. Once the data are in an MS Excel spreadsheet, you can analyze it, store it or do whatever you want with it.

 

Work in progress: Results summaries

 

In addition to raw data searches, the CSI database will offer graphs and maps summarizing results at each of the three tiers of its spatial hierarchy. Work on this part of the database is still in progress. To get a rough idea of how it will look, try the following:

Spatial Tier 2: Maps and results summaries for monitoring sets

 

  1. Click on Monitoring Sets at the top of this page

  2. Click View for the monitoring set of interest.

  3. Select an Analyte from the drop-down menu between the map and the graph to see its average profile across the monitoring set

Spatial Tier 3: Maps and results summaries for monitoring locations

  1. Click View in the list of Monitoring Locations below the graph