Posts Tagged ‘water quality’

Quality of “The Lake”

Friday, December 13th, 2013

Early View article:Geospatial and Temporal Analysis of a 20-Year Record of Landsat-Based Water Clarity in Minnesota’s 10,000 Lakes,” Leif G. Olmanson, Patrick L. Brezonik, and Marvin E. Bauer.

This one is close to my heart. For just about every summer of his long life, my late father in law, from St. Paul, would gather his buddies for a fishing trip up to “The Lake.” (Doesn’t matter which one, they’re all called “The Lake.”) I have his records, so I know a lot has changed. This article quantifies some of the changes. (I also learned Minnesota, “Land of 10,000 Lakes,” actually has ~12,000 of 4 ha or larger.)

[Abstract] “A large 20-year database on water clarity for all Minnesota lakes ?8 ha was analyzed statistically for spatial distributions, temporal trends, and relationships with in-lake and watershed factors that potentially affect lake clarity. The database includes Landsat-based water clarity estimates expressed in terms of Secchi depth (SDLandsat), an integrative measure of water quality, for more than 10,500 lakes for time periods centered around 1985, 1990, 1995, 2000, and 2005. Minnesota lake clarity is lower (more turbid) in the south and southwest and clearer in the north and northeast; this pattern is evident at the levels of individual lakes and ecoregions. Temporal trends in clarity were detected in ~11% of the lakes: 4.6% had improving clarity and 6.2% had decreasing clarity. Ecoregions in southern and western Minnesota, where agriculture is the predominant land use, had higher percentages of lakes with decreasing clarity than the rest of the state, and small and shallow lakes had higher percentages of decreasing clarity trends than large and deep lakes. The mean SDLandsat statewide remained stable from 1985 to 2005 but decreased in ecoregions dominated by agricultural land use. Deep lakes had higher clarity than shallow lakes statewide and for lakes grouped by land cover. SDLandsat decreased as the percentage of agriculture and/or urban area increased at county and catchment levels and it increased with increasing forested land.”

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Estimating loads

Monday, December 9th, 2013

Early View article:Load Estimation Method Using Distributions with Covariates: A Comparison with Commonly Used Estimation Methods,” by Sébastien Raymond, Alain Mailhot, Guillaume Talbot, Patrick Gagnon, Alain N. Rousseau, and Florentina Moatar.

[Abstract] Load estimates obtained using an approach based on statistical distributions with parameters expressed as a function of covariates (e.g., streamflow) (distribution with covariates hereafter called DC method) were compared to four load estimation methods: (1) flow-weighted mean concentration; (2) integral regression; (3) segmented regression (the last two with Ferguson’s correction factor); and (4) hydrograph separation methods. A total of 25 datasets (from 19 stations) of daily concentrations of total dissolved solids, nutrients, or suspended particulate matter were used. The selected stations represented a wide range of hydrological conditions. Annual flux errors were determined by randomly generating 50 monthly sample series from daily series. Annual and interannual biases and dispersions were evaluated and compared. The impact of sampling frequency was investigated through the generation of bimonthly and weekly surveys. Interannual uncertainty analysis showed that the performance of the DC method was comparable with those of the other methods, except for stations showing high hydrological variability. In this case, the DC method performed better, with annual biases lower than those characterizing the other methods. Results show that the DC method generated the smallest pollutant load errors when considering a monthly sampling frequency for rivers showing high variability in hydrological conditions and contaminant concentrations.

Hydrocarbons in aquifers

Thursday, October 24th, 2013

Early View article:Statistical Evaluation of Variables Affecting Occurrence of Hydrocarbons in Aquifers Used for Public Supply, California,” by Matthew K. Landon, Carmen A. Burton, Tracy A. Davis, Kenneth Belitz, and Tyler D. Johnson.

The variables affecting the occurrence of hydrocarbons in aquifers used for public supply in California were assessed based on statistical evaluation of three large statewide datasets; gasoline oxygenates also were analyzed for comparison with hydrocarbons. Benzene is the most frequently detected (1.7%) compound among 17 hydrocarbons analyzed at generally low concentrations in groundwater used for public supply in California; methyl tert-butyl ether (MTBE) is the most frequently detected (5.8%) compound among seven oxygenates analyzed. At aquifer depths used for public supply, hydrocarbons and MTBE rarely co-occur and are generally related to different variables; in shallower groundwater, co-occurrence is more frequent and there are similar relations to the density or proximity of potential sources.

Multiple lines of evidence indicate that benzene and other hydrocarbons detected in old, deep, and/or brackish groundwater result from geogenic sources of oil and gas. However, in recently recharged (since ~1950), generally shallower groundwater, higher concentrations and detection frequencies of benzene and hydrocarbons were associated with a greater proportion of commercial land use surrounding the well, likely reflecting effects of anthropogenic sources, particularly in combination with reducing conditions.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Alum in reservoirs

Tuesday, October 8th, 2013

Early View article:Mobilization and Toxicity Potential of Aluminum from Alum Floc Deposits in Kensico Reservoir, New York,” by Charles T. Driscoll, Ashley Lee, Mario Montesdeoca, David A. Matthews, and Steven W. Effler.

Alum sometimes is applied to reservoirs to control turbidity during high-flow events. Is this something to worry about for the biota?

The authors report on the results of field measurements, laboratory sediment release experiments, and chemical equilibrium calculations conducted to evaluate the potential for the mobilization of Al from alum floc deposits in sediments of Kensico Reservoir, New York. Under ambient water quality conditions, mobilization of sediment Al is not a noteworthy concern at Kensico Reservoir. However, under experimental conditions of low pH, low acid neutralizing capacity (ANC), and low temperature, the inorganic fraction of monomeric Al can be mobilized from Kensico sediments to concentrations that would likely impair the health of aquatic organisms (>2 ?mol/l).

Fortunately, the prevailing conditions in Kensico Reservoir differ greatly from those necessary for such mobilization. Specifically, the prevailing pH and ANC are substantially above and concentrations of complexing anions are greatly below levels of concern. Extreme and unforeseen changes in water chemistry would be necessary for sediment release of Al sufficient to result in toxic conditions.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Chespeake Bay TMDLs and “Gray Literature”

Thursday, September 5th, 2013

Bay Bridge at Sunset, by Steve Droter. Image courtesy of the Chesapeake Bay Program.

NOW APPEARING IN EARLY VIEW! In the October 2013 issue, we are pleased to present one of our most ambitious Featured Collections to date: Chesapeake Bay TMDLs. The Chesapeake Bay Program, a state-federal partnership founded in 1983, has coordinated a huge scientific effort to learn more about this irreplaceable natural resource touching parts of seven States. Guest Editors Lewis Linker, Richard Batiuk, and Carl Cerco put together this Featured Collection to document the enormous effort to establish nutrient and sediment TMDLs for the Bay and its surrounding watershed.

A very large part of research and data collection for Chesapeake Bay was done under cooperative agreements with states and universities, interagency agreements with federal agencies, and contracts. The resulting reports reside in the Program’s Bay Resource Library. The papers in the Featured Collection draw upon this and other resources to describe the various elements for determining TMDLs: the data collection, the hydrodynamic models, the water-quality models, and the public involvement. In effect, the Featured Collection serves as a gateway and introduction to a treasure trove of information on Chesapeake Bay, much of which is not found in peer-reviewed journals. Reliance on “gray literature” presented some unique challenges and opportunities to JAWRA.

“Gray literature” often is used in a pejorative sense to imply a lack of quality compared to peer-reviewed journals. But, many agency, university, and contractor reports are not the type of article that belongs a research journal. Data collection reports, critical though they may be, rarely make it into journals unless they include analysis as well. Ditto for summaries of public meetings, which are so informative for understanding the basis for decisions.

Some “gray” reports, such as those reporting how models were developed and tested, are pretty strong science in their own right. Modeling efforts for Chesapeake Bay often underwent extensive review processes far beyond what a journal would impose, including independent expert panels and public comments. Nevertheless, the reports lack the “gold standard” of anonymous peer review required for journals, and typically don’t score well in scholarly search rankings.

Agency libraries play a critical role in preserving these vital records. Regrettably, search engines like Google Scholar™ sometimes do not index non-peer-reviewed supporting material, so one must rely on specialized sites like to serve this function. (I served on the founding committee for and can confirm one of the main goals was exposure of unclassified contractor reports.)

For this Featured Collection, the authors and guest associate editors had to walk a fine line between describing what the models show and justifying the models themselves. Like most journals, JAWRA does not have the resources for the latter: We would not, for example, expect a volunteer reviewer to set up and rerun a model. Our emphasis, therefore, was on description, accurately reporting on the process of setting the TMDLs. By describing what data and models were used, and pointing to the original “gray literature” materials upon which the TMDLs are based, we hope to give the readers a head start in making their own evaluations.

Streambed E. coli

Wednesday, August 28th, 2013

Early View article:Assessing the Impacts of E. coli Laden Streambed Sediment on E. coli Loads over a Range of Flows and Sediment Characteristics,” by Pramod K. Pandey and Michelle L. Soupir.

In this study, the authors demonstrated the impacts of streambed on total in-stream E. coli loads. The model was developed to calculate the total in-stream E. coli load. The inclusion of streambed sediment E. coli resulted in increased levels of E. coli. For example, when neglecting the streambed sediment E. coli concentrations, the average E. coli load was 107 (CFU/s); however, when streambed sediment E. coli concentrations were included in the model, the predictions ranged from 1010 to 1014 (CFU/s). The model predictions are verified using field data and the model skill (mskill) and NSE coefficient values were 0.78 and 0.55, respectively. Results of this study suggest that monitoring streambed sediment E. coli concentrations is required to improve the assessment of in-stream E. coli concentrations.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Estimating concentrations

Saturday, August 24th, 2013

Early View article:An Optimization Method for Estimating Constituent Mean Concentrations in Base Flow-Dominated Flow,” by Laurent Ahiablame, Bernard Engel, and Indrajeet Chaubey.

A method for characterizing base flow quantity and quality for different land uses was explored using inverse modeling with two optimization techniques (a least square method and a genetic algorithm [GA] optimization), land use information, and streamflow quantity and quality data. The proposed method has the potential to effectively estimate constituent mean concentrations for pollutant load determination in gauged and ungauged watersheds, albeit more analysis with larger and more robust datasets is desirable to further refine and validate the accuracy of the approach.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.] – See more at:

TMDL balance

Tuesday, June 18th, 2013

Early View article:TMDL Balance: A Model for Coastal Water Pollutant Loadings,” by Stephanie L. Johnson, David R. Maidment, and Mary J. Kirisits

The application highlights an example of distributing bacterial sources spatially based on land use data. The authors developed a TMDL Balance model using a steady state, mass balance, GIS-based model for simulating pollutant loads and concentrations in coastal systems. The model uses plug-flow reactor and continuously-stirred tank reactor equations to route spatially distributed point and nonpoint source loads through a watershed via overland flow, non-tidal flow, and tidal flow, decaying the loads via first-order kinetics. In this paper, they explain the development of the watershed loading portion of the TMDL Balance model, demonstrating the methodology through a case study: computing bacterial loads in the Copano Bay watershed of southeast Texas.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Quality of water from rain barrels

Friday, June 7th, 2013

Early View article:Assessment of Residential Rain Barrel Water Quality and Use in Cincinnati, Ohio,” by William D. Shuster, Dennis Lye, Armah De La Cruz, Lee K. Rhea, Katharine O’Connell, and Amanda Kelty.

Water from rain barrels can have a lot of uses, but drinking it is not one of them. In this study, rainwater reuse and levels of select microbial indicators were monitored for six residential rain barrels located in the Shepherd Creek watershed of Cincinnati, Ohio. Water from rain barrels typically had poor microbial quality and was used for watering indoor and outdoor plants. Water from rain barrels typically had poor microbial quality and was used for watering indoor and outdoor plants. Rain barrel water chemistry was slightly acidic, exhibited wide ranges in conductivity, turbidity, and total organic carbon (TOC) concentrations and gave no evidence of the presence of cyanobacterial microcystin toxins. Selected microbial water-quality indicators indicated that counts of total coliform and enterococci were consistently above U.S. Environmental Protection Agency standards for secondary recreational contact water-quality standards.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]

Documenting BMPs

Monday, April 29th, 2013

Early View article: Locating Existing Best Management Practices Within a Watershed: The Value of Multiple Methods,” by Caitlin A. Grady, Adam P. Reimer, Jane Frankenberger, and Linda Stalker Prokopy.

There is an increasing need to document the impacts of conservation-related best management practices (BMPs) on water quality within a watershed. However, this impact analysis depends upon accurate geospatial locations of existing practices, which are difficult to obtain. This study demonstrates and evaluates three different methods for obtaining geospatial information for BMPs. This study was focused on the Eagle Creek Watershed, a mixed use watershed in central Indiana. We obtained geospatial information for BMPs through government records, producer interviews, and remote-sensing aerial photo interpretation. Aerial photos were also used to validate the government records and producer interviews. This study shows the variation in results obtained from the three sources of information as well as the benefits and drawbacks of each method. Using only one method for obtaining BMP information can be incomplete, and this study demonstrates how multiple methods can be used for the most accurate picture.

[Please note: I have quoted and paraphrased freely from the article, but the interpretation is my own.]