2002 Progress Report: Development and Implementation of a Comprehensive Lake and Reservoir Strategy for Nebraska as a Model for Agriculturally Dominated EcosystemsEPA Grant Number: R828635
Title: Development and Implementation of a Comprehensive Lake and Reservoir Strategy for Nebraska as a Model for Agriculturally Dominated Ecosystems
Investigators: Holz, John C. , Bogardi, Istvan , Fritz, Sherilyn C. , Gitelson, Anatoly A. , Hoagland, Kyle D. , Merchant, James W. , Rundquist, Donald C.
Institution: University of Nebraska at Lincoln
EPA Project Officer: Packard, Benjamin H
Project Period: January 1, 2001 through December 31, 2003 (Extended to December 31, 2004)
Project Period Covered by this Report: January 1, 2002 through December 31, 2003
Project Amount: $1,224,706
RFA: Development of National Aquatic Ecosystem Classifications and Reference Conditions (2000) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Water , Ecosystems
The overall objective of this research project is to develop a dynamic lake classification system for agricultural ecosystems, utilizing the innovative and state-of-the-art approaches of a unique combination of disciplines. The three major objectives that are critical to achieving this goal are to: (1) establish a protocol for aggregating lakes and reservoirs in agriculturally dominated ecosystems into appropriate classification strata and identifying reference conditions for these lake classes; (2) establish the role of remote sensing and geographic information systems (GIS) in a lake and reservoir classification strategy; and (3) establish a dynamic technology transfer link between the proposed classification system and the end users.
Establish a Protocol for Aggregating Lakes and Reservoirs in Agriculturally Dominated Ecosystems Into Appropriate Classification Strata and Identifying Reference Conditions for These Lake Classes. During the course of this project, water bodies are classified using combinations of rule-based and data-based hierarchical approaches. The first tier of classification was established and it separates water bodies on the basis of physical characteristics known to influence water quality in this region (i.e., natural Sand Hill lakes, sandpit lakes, reservoirs). During Year 2 of the project, 83 water bodies (18 natural Sand Hill lakes, 9 sandpit lakes, and 56 reservoirs) were sampled for numerous limnological parameters to fill data gaps in our current database and to provide representative spatial coverage of the state. All water bodies were sampled at one deep water site monthly from May through September and analyzed for total phosphorus, total dissolved phosphorus (TP), dissolved orthophosphorus, total nitrogen, total nitrate + nitrite, pH, alkalinity, conducivity, temperature, dissolved oxygen, turbidity, Secchi disk transparency, total suspended solids (TSS), chlorophyll a, atrazine, metolachlor, alachlor, and maximum depth. Phytoplankton and zooplankton samples also were collected and are currently being enumerated to species.
Nine reservoir classes were defined by first performing an ANOVA on each water quality parameter for each reservoir to test for temporal (both between and within-year) differences. This analysis showed very few temporal differences. A factor analysis was then performed and significant factors were plotted to identify five groups of lakes with similar water quality characteristics. The factor analysis revealed three significant factors explained over 69 percent of the variability of the data, with alkalinity, conductivity, chlorophyll a, nitrate plus nitrite, Secchi disk depth, TSS, orthophosphate, total phosphorus, and total nitrogen loading significantly into the three factors. Water clarity/nutrients was the most important factor and, after separating the lakes based on this factor, they could be further classified by factor 2 (alkalinity and conductivity) and factor 3 (chlorophyll a). Additional analyses showed that the U.S. Environmental Protection Agency (EPA) suggested classification parameters of TN, TP, Secchi depth, and chlorophyll a did not adequately characterize the variability among reservoir classes. However, the addition of alkalinity substantially improved the model's performance. These reservoir groups also were compared to Omernik's rule-based Level IV Ecoregions for Nebraska. The Level IV Ecoregions based on soil type, native vegetation cover, topography, and geology do not accurately represent water quality in this region, likely due to the unusually large impact of agricultural land use practices on water quality.
Historic reference conditions for these reservoir classes were estimated using a modified version of EUTROMOD to predict in-lake TP, assuming the entire watershed was returned to native vegetation. This simple and preliminary analyses of 18 representative watersheds/reservoirs suggests that eutophic conditions may be the "natural" state of most of the regions reservoirs.
Reference Condition Development Using Sediment Core Analyses. The aim of the paleolimnological portion of the project is to use sediment cores from selected Nebraska lakes to determine the stability of lake diatom communities during the last approximately 150 years and to infer the stability of limnological conditions over this period. These data will be used to evaluate the stability of the lake classification system developed from contemporary data. Diatom communities in contemporary lakes, reservoirs, and sand pits will be compared with limnological data from these lakes (chemical and morphometric characteristics) to determine the major variables that are correlated with regional diatom distribution. These data, together with other published ecological information on diatom ecology, will be used to infer the nature of limnological change over time from changes in diatom assemblages in sediment cores from individual lakes.
Samples to determine contemporary diatom distribution in both natural and manmade Nebraska lakes were taken from 27 lakes, 22 reservoirs, and 16 sand pits. Particularly, in some of the natural lakes that are shallow or have high alkalinity, diatom preservation or abundance was poor, and therefore, the lakes were unsuitable for further diatom analysis. Thus, diatoms have been analyzed from 15 natural lakes, 19 reservoirs, and 12 sand pits (46 total). Statistical comparison of these diatom data with measured limnological variables is currently underway, using multivariate techniques. Transfer functions to reconstruct past limnological conditions may be generated from these data for limnological variables that have a statistically significant and independent influence on modern diatom assemblages.
Long sediment cores have been taken from four natural lakes and were dated with 210Pb analysis to determine the age of sediment layers, as well as changes in sedimentation rates. Diatoms have been analyzed in contiguous samples in each of these cores spanning back at least 150 years. These four cored lakes include three of the five natural lake reference classes, as determined from the modern data set. In addition, undated sediment sequences were obtained from four additional natural lakes. From these lakes, both the core tops, which represent modern conditions and the core bottoms, which represent presettlement samples, were analyzed for sedimentary diatoms to determine limnological stability with time. Sediment accumulation rates, derived from 210Pb dating of the four cores, show a similar pattern among the four dated sites. Sedimentation rates are low and relatively constant (ranging from 0.01 to 0.04 g cm-2 yr-1) until the mid-1900s. Values increase abruptly in all cores around 1960 and peak near the present day at rates that are 3-10 times those in the 1800s. In terms of diatom assemblages in the dated lake sequences, all of the lakes show some stratigraphic variation over time.
Establish the Role of Remote Sensing and GIS in a Lake and Reservoir Classification Strategy. There are two componenets to the establishment of the role of remote sensing and GIS in a lake and reservoir classification system: GIS and remote sensing.
GIS Database Development: Delineating Watersheds. An accurate representation of Nebraska lakes is necessary to delineate their watershed boundaries and to develop management criteria based on potential impacts of the watersheds on lake water quality. A digital map (i.e., lake coverage) was therefore developed and the coverage is a culmination of a process in which initially all water features from the latest version of U.S. Department of Agriculture/National Resources Conservation Service Soil Survey Geographic Database (SSURGO) were extracted and used as baseline water features. The dataset was updated using other data sources, including the U.S. Geological Survey (USGS) National Hydrologic Dataset, USGS National Land Cover Data, and Census Bureau TIGER data to fill gaps in counties where there are currently no SSURGO data available. Previous efforts to delineate lake watersheds were limited by artifacts of county-based digital elevation models (DEMs) such as seams. The USGS Elevation Derivatives for National Applications (EDNA) datasets now provide us with a unique opportunity to delineate the lake watershed boundaries. The EDNA datasets are comprehensive and seamless for the conterminous United States. The EDNA datasets, obtained from the Earth Resources Observation System (EROS) Data Center (EDC), include Pfafstetter subcatchments, modified hydrologic unit coverage (HUC) boundaries, synthetic (i.e., DEM generated) streamlines, flow direction data, and shaded relief data for all areas that drain into water bodies of Nebraska. The EDNA datasets were used in ArcView GIS to delineate the watersheds of 224 sampled Nebraska lakes. Watershed boundaries of these lakes were delineated using an ArcView script together with the "hydro" tool extension. This process identifies a lake’s watershed based on stream network, stream flow direction, and subcatchment information available in the EDNA dataset. The watershed boundaries were overlaid on shaded relief data and were found to acceptably conform to the terrain.
GIS Database Development: Derivation of Watershed Characteristics Data. Available spatial data on environmental characteristics that affect sedimentation and eutrophication of lakes have been added to our existing GIS database including watershed area, watershed slope and relief, soil erodibility, soil infiltration rate, soil organic matter, soil reaction (pH), soil cation exchange capacity, and soil carbonate. Watershed boundaries of the 185 sampled lakes were used to extract the watershed characteristics from State Soil Geographic (STATSGO) and Digital Elevation Model (DEM) datasets. Watershed boundary coverage was overlaid on raster (or grid) layers for each watershed characteristic. A summary of "zonal" statistics of each watershed characteristic (e.g., maximum, minimum, and mean values) were generated for the respective lake watershed boundaries using ArcMap GIS. These summary statistics were then appended to the watershed boundary dataset and the resultant information was converted into spreadsheets for additional statistical analyses.
Relationship Between Land Use and Reservoir Water Quality. Anthropogenic influences on the reservoir watersheds in agriculturally dominated ecosystems tend to change the natural eutrophication process of these reservoirs as a function of alterations in the land use and land cover (LULC) types. The associations between four water quality parameters (i.e., chlorophyll a, total nitrogen, phosphorus, and Secchi depth) and proportion of LULC (i.e., cropland, rangeland, wetland, urban, and forests) in 56 selected reservoir watersheds were examined using correlation analyses. The first set of the analysis was used to assess the relationship between seasonal mean concentrations of phosphorous and LULC types. Generally, the correlations between the proportions of LULC types in the reservoir watersheds and seasonal mean phosphorus concentrations were low. These correlations were not statistically significant, except for the correlations of wetland with spring phosphorus and summer phosphorus. The correlations between the proportions of LULC and summer mean concentrations of phosphorus, chlorophyll a, Secchi depth, and total nitrogen were on average lower than expected. Only the correlation between wetland and summer mean concentrations of phosphorus was statistically significant. The results pointed to the important role of wetlands in reservoir watersheds. These analyses provided some useful insights into the nature of anthropogenic impacts on watersheds and reservoir water quality.
Remote Sensing. The goal of this part of the research project is to establish remote sensing techniques for lake classification and a dynamic technology transfer link between the proposed remote sensing system and the end-users. The second year of the project was dedicated primarily to:
· Developing a technique for remote quantification of phytoplankton pigment concentrations and composition as biological indicators of water quality in lakes with various eutrophic status and with wide ranges of total suspended matter, dissolved organic matter, and nonliving organic matter.
· Developing a technique for remote quantification of total suspended matter, turbidity, and Secchi depth.
· Assessing temporal and spatial variability of biophysical characteristics estimated remotely in selected reservoirs and lakes by means of an airborne hyperspectral imaging spectrometer (AISA) and comparing them among sample dates within a year to ascertain the sensitivity of the remote sensing approach for detecting the changes.
· Assessing the time frame within which an individual lake/reservoir remains in a certain lake water quality category.
· Assessing to what extent algal indicators reflect temporal variation relative to other endpoints.
· Validating an algorithm for remote quantification of chlorophyll concentration in mesotrophic to hypereutrophic water bodies by means of close range remote sensing.
Close Range Remote Sensing. A dual-fiber Ocean Optics radiometric system was used in boat field campaigns to measure downwelling irradiance and upwelling water radiance of water in the range from 350 to 900 nm. This system was used in 14 field campaigns to develop and validate algorithms for assessing chlorophyll concentration. Reflectance spectra together with ancillary data (Secchi depth, turbidity, total suspended matter, dissolved organic matter, chlorophyll concentrations) were taken at 129 stations. To establish a relationship between remotely measured reflectance and water quality characteristics, we conducted in situ reflectance measurements in as wide as possible range of constituent concentration and composition. The sand pit lakes and reservoirs sampled ranged from mesotrophic to hypereutrophic, and exhibited chlorophyll a concentrations and turbidity values varying by a factor as high as 25; absorption coefficients at 440 nm by colored dissolved organic matter (CDOM) and tripton varied three- and fivefold, respectively. The dominant groups of algae encountered were Cyanophyta, Chlorophyta, and Crysophyta.
The data were used to validate the model, which has been developed for estimating of chlorophyll concentration in productive turbid waters. The model relates remotely measured reflectance R in three spectral bands, X = (R660-670 -1 - R720-730 -1)*R740-750 with chlorophyll concentrations: chlorophyll a = 28.3*X2+161.0*X+56.7. The coefficient of determination was r2 = 0.94 and p <0.0001. The established model was used to predict the chlorophyll a concentrations in the model-validation data set, taken in 2002. Predicted chlorophyll a values were compared to measured ones; the Root Mean Square Error of chlorophyll a prediction was lower than 13 µg L-1. To the best of our knowledge, it is the best prediction of chlorophyll concentration in productive turbid waters with such a wide range of variation of optically active constituent concentrations.
An airborne AISA hyperspectral imaging spectrometer was used to study temporal and spatial distributions of water quality in representative lakes and reservoirs. As a result of these overflights, temporal and spatial distributions of phytoplankton in water bodies were studied and the time frame within which an individual lake/reservoir remains in a certain water quality category was determined.
Establish a Dynamic Technology Transfer Link Between the Proposed Classification System and the End Users (e.g., State and Federal Water Resource Managers). Specifically, this objective aims at developing an integrated decision support system (DSS) to: (1) visualize the lake classification scheme through an interactive computer hierarchy; and (2) facilitate the decisionmaking process by allowing water quality managers both to vary DSS variables to ask "what if" questions relative to each end point, as well as to examine the implications of adding other parameters such as esthetic or economic factors. According to the project schedule of Year 2 of the project, the objectives included the: (1) development of a prototype for a GIS-enhanced DSS; (2) evaluation of a methodology for integrating results of remote sensing and GIS analyses in overall lake classification strategy; (3) incorporation of data variability into DSS; and (4) application of DSS to combinations of traditional, remote sensing, and GIS data.
We have accomplished the objectives for Year 2 of the project by developing the DSS; by completing Lake Classifier, a DSS that ranks lakes without considering uncertainties; and by developing the methodology of Lake Classifier under Uncertainty, a DSS that ranks lakes under uncertain information and variability.
In Year 3, we plan to: (1) classify sandpits using a combination of rule and data-based approaches; (2) complete comparison of other landscape stratification approaches to ecoregions as a priori lake classes; (3) generate at least two complete dated diatom sequences spanning the last 150 years from each of the natural lake reference classes, as well as complete sequences from at least two reservoirs; (4) complete the development of phytoplankton and zooplankton bioindicators; (5) validate developed algorithms using the airborne hyperspectral imaging; (6) estimate the accuracy of chlorophyll estimation using aircraft imaging spectrometer; (7) validate algorithms for estimation of blue-green algae distribution; (8) apply watershed classification procedures to an expanded number of watersheds besides the sampled lakes; (9) improve the validation process for developing an interactive GIS-based lake classifier; (10) determine the subset of watershed characteristics that are essential to the watershed classification process; (11) test Lake Classifier and complete the DSS with detailed help; (12) develop, test, and complete the DSS Lake Classifier under Uncertainty including a detailed help file; and (13) provide an Internet linkage by which users can download and apply the two DSS.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
|Other project views:||All 13 publications||2 publications in selected types||All 2 journal articles|
||Bulley HNN, Merchant JW, Marx DB, Holz JC, Holz AA. A GIS-based approach to watershed classification for Nebraska reservoirs. Journal of the American Water Resources Association 2007;43(3):605-621.||
||Bulley HNN, Marx DB, Merchant JW, Holz JC, Derksen CP. A comparison of Nebraska reservoir classes estimated from watershed-based classification models and ecoregions. Journal of Environmental Informatics 2008;11(2) 90-102.||