# Presentation: 228679

## Real-Time Continuous In-Stream Monitoring to Measure and Estimate Water-Quality Concentrations and Loads

***Andy Ziegler***
*** ******USGS Kansas Water Science Center***
***with contributions from Teresa Rasmussen***
***Trudy Bennett, Casey Lee, Pat Rasmussen, Xiaodong Jian,***
***Vicki Christensen, Walt Aucott, Tim Cohn,  Bob Hirsch, and many others ***

**National Water-Quality Monitoring Council Conference **
**San Jose, California, May 9, 2006**

## Why monitor water quality continuously? 

**Improves our understanding of hydrology and water quality and can lead to more effective resource management**
**Captures seasonal, diurnal, and event-driven fluctuations **
**Provides warning for water supply and recreation**
**Improves concentration and load estimates with defined uncertainty (8,760 hourly values per year)**
**Optimizes the collection of samples**

## Types of continuous water-quality monitors

**Electrometric**
**Gage height, temperature, pH, DO, SC**
**Electromagnetic spectrum**
**Streamflow, turbidity, chlorophyll, nitrate**
**In-stream analyzers (bench chemistries)**
**Nitrate, silicate,  phosphorus, chloride, ....**
**Labs in field at gage house**
**Aqualab (TCEQ), GC/MS- ORSANCO, etc...**

## Improved tools now are available--In-stream continuous monitors...

- pH
- Water Temperature
**Dissolved Oxygen**
- Specific Conductance
**Turbidity**
- ORP
- Fluorescence
- PAR
- Nitrate, ammonia, etc.
- New gizmos every year

## USGS streamflow network of 7,000+

- http://water.usgs.gov/waterwatch/

## Where is USGS operating continuous  “turbidity”?

**211 sites.  Most sites are in Oregon (34), Georgia (34), Kansas (17), and 10 each in California, Kentucky, and Virginia**

## http:// ks.water.usgs.gov/Kansas/rtqw/

## Approach:

**Approach:**

**Add water-quality monitors at streamgages and transmit data “real” time**
**Collect water samples over the range of  hydrologic and chemical conditions **** **
**Develop site-specific regression models using samples and sensor values**** **
**Estimate concentrations and loads**
**Publish regression models **** **
**Display estimates, uncertainty, and probability on the Web**
**Continued sampling to verify**

**Little Arkansas River near Sedgwick, Kansas**

**http://ks.water.usgs.gov/Kansas/rtqw/**

## http:// ks.water.usgs.gov/Kansas/rtqw/

| Directly measured |  Estimated |
| --- | --- |
| Gage Height/Stage | Streamflow (discharge) |
| Specific Conductance | Chloride, alkalinity, fluoride, dissolved solids, sodium, sulfate, nitrate, atrazine |
| Turbidity | Total suspended solids, suspended sediment, fecal coliform, E. coli, total nitrogen, total nitrogen, total phosphorus, geosmin |

**http:// ks.water.usgs.gov/Kansas/rtqw/**

## Turbidity estimates E. Coli reliably

- Turbidity estimates *E. Coli ***reliably**

**Rasmussen, Ziegler, and Rasmussen, 2005**

## Bacteria frequently exceed water-quality standards

- 2,358

- 262

**Bacteria frequently exceed water-quality standards**

## E.Coli densities generally largest at Topeka. 

***E.Coli *****bacteria, col/100mL**

***E.Coli***** densities generally largest at Topeka.**

***E.Coli *****bacteria, col/100 mL**

**During the spring, the primary contact criterion was exceeded 80% of the time and the secondary contact criterion was exceeded 25% of the time.**

**Rasmussen, Ziegler, and Rasmussen 2005**

## Turbidity to estimate probability of exceeding E. coli criteria

**Turbidity, FNU, YSI 6026 sensor**

**Turbidity to estimate probability of exceeding E. coli criteria**

**Probability of exceedance, percent**

**Rasmussen and Ziegler, 2003**

## Kansas River TMDL incorporates continuous turbidity data.  When turbidity > 350 FNU, E. coli criteria likely to be exceeded.

** ****Establishes TMDL goals that incorporate continuous data**** - less than 10% of estimated geometric means are to exceed primary criterion and exceedences occur at flows exceeded less than 20% of the time.**

**Kansas River TMDL incorporates continuous turbidity data.****  When turbidity > 350 FNU, *****E. coli***** criteria likely to be exceeded.**

**(Figure from KDHE, *****E.Coli***** Bacteria TMDL for Kansas-Lower Republican Basin, 2005)**

## Streamflow relation to water quality is complex and variable

**78 events (flow exceeded 100 cfs)—comprised 99 percent of the load for the 6-year period**
**Largest event was 8 percent of the load for the 6-year period and occurred over 8 days (0.3 percent of time)**
**Only 5 events exceeded the 2-year flood**
**Average event --6 days, **
**	****maximum --25 days**

**  ****Turbidity, FNU                        **

**  ****Streamflow                    **

**2-Year flood                    **

## 90 percent of the load occurs in 7 percent of the time

**Little Arkansas River nr. Halstead  1999-2004**

**Percentage of time load is equaled or exceeded**

**Percentage of load from 1999-2004**

## Continuous data is necessary to understand the water-quality response to streamflow

- Mill Creek April 28-29, 2006 hysteresis

- 0

- 1

- 2

- 3

**0. Q inc. within 15 min.**

**1. source limit reached**

**2. new trib or bank collapse**
** ****source**

**3. response to precip and **
**new tribs**

## Geosmin was detected in a near shore surface accumulation of cyanobacteria, but not in open water samples
The model predicted the elevated geosmin levels that occurred in the surface accumulation of cyanobacteria; had the accumulation not been sampled, the model would have appeared to give an incorrect estimation of geosmin concentration
Spatial (both vertical and horizontal) changes in the distribution of cyanobacteria may substantially influence the occurrence of taste and odor episodes

- The model predicted the elevated geosmin levels that occurred in the surface accumulation of cyanobacteria; had the accumulation not been sampled, the model would have appeared to give an incorrect estimation of geosmin concentration
- Spatial (both vertical and horizontal) changes in the distribution of cyanobacteria may substantially influence the occurrence of taste and odor episodes

**Future: Real-time estimation of geosmin in Cheney Reservoir (2005)**

- http://ks.water.usgs.gov/Kansas/rtqw/sites/07144790/htmls/ytd/p62719_ytd_all_uv.shtml

**log10(geosmin)=7.2310-1.0664log10(turbidity)-0.0097(conductivity)**
** ****r2=0.71**

## Benefits of Real Time Water Quality

**Improve our understanding of the hydrology and water quality of streams**
**Identify source areas and evaluate trends for NPDES, BMPs and TMDLs**
**Provide notification of changes in water-quality conditions for water treatment and recreation in real time**
**Comparison to water-quality criteria **
**Continuously measure water quality in real time like streamflow**
**Better estimate selected constituent concentrations and loads with defined uncertainty**
**Optimize timing of sample collection**

## Future Challenges for Continuous Water Quality

**Detection of water-quality trends and BMPs effectiveness**
**More installations nationwide to better understand variability **
**Need more direct measurement sensors**
**Reduce O&M costs/time**
**Ice and shallow water installations **
**Continued sampling to document that relations remain representative**
**Improve ways to estimate and communicate uncertainty**

## Real-time continuous concentrations and loads on the Web— 

**http://ks.water.usgs.gov/Kansas/rtqw/**

**Real-time continuous concentrations and loads on the Web— **

- Andy Ziegler
- aziegler@ usgs.gov