North Temperate Lakes
US Long-Term Ecological Research Network

WSC - The Influence of Legacy P on Lake Water Quality

Abstract
Using a suite of numerical models, we investigated the influence of legacy P on water quality in the Yahara Watershed of southern Wisconsin, USA. The suite included Agro-IBIS, a terrestrial ecosystem model; THMB, a hydrologic and nutrient routing model; and the Yahara Water Quality Model which estimates water quality indicators in the Yahara chain of lakes. Using five alternative scenarios of antecedent P storage (legacy P) in soils and channels under historical climate conditions, we simulated outcomes of P yield from the landscape, lake P loading, and three lake water quality indicators. Data and code may also be found in https://github.com/SRCarpen/Yahara2070LakeModel_Fits2data.git
Core Areas
Dataset ID
384
Date Range
-
Methods
We developed a watershed modeling framework that can simulate an array of ecosystem services, including land-to-lake flows of water, sediment, and nutrients, and surface water quality (Figure 1). The framework includes process-based representation of natural and managed ecosystems (Agro- IBIS), hydrologic routing of water, sediment, and nutrients through the surface hydrologic network (THMB), and prediction of Secchi disk depth (a measure of lake transparency), summertime lake total phosphorus (TP) concentration, and the probability of hypereutrophy in each lake (Yahara Water Quality Model).
for detailed description of modeling approach please see:
Motew, M., Chen, X., Booth, E.G. et al. The Influence of Legacy P on Lake Water Quality in a Midwestern Agricultural Watershed. Ecosystems 20, 1468–1482 (2017). https://doi.org/10.1007/s10021-017-0125-0
Related Sites
Version Number
1

LAGOS - Lake nitrogen, phosphorus, and stoichiometry data and geospatial data for lakes in a 17-state region of the U.S.

Abstract
This dataset includes information about total nitrogen (TN) concentrations, total phosphorus (TP) concentrations, TN:TP stoichiometry, and 12 driver variables that might predict nutrient concentrations and ratios. All observed values came from LAGOSLIMNO v. 1.054.1 and LAGOSGEO v. 1.03 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 54 different sources of data were compiled for this dataset and were mostly generated by government agencies (state, federal, tribal) and universities. Here, we compiled chemistry data from lakes with concurrent observations of TN and TP from the summer stratified season (June 15-September 15) in the most recent 10 years of data included in LAGOSLIMNO v. 1.054.1 (2002-2011). We report the median TN, TP and molar TN:TP values for each lake, which was calculated as the grand median of each yearly median value. We also include data for lake and landscape characteristics that might be important controls on lake nutrients, including: land use (agricultural, pasture, row crop, urban, forest), nitrogen deposition, temperature, precipitation, hydrology (baseflow), maximum depth, and the ratio of lake area to watershed area, which is used to approximate residence time. These data were used to identify drivers of lake nutrient stoichiometry at sub-continental and regional scales (Collins et al, submitted). This research was supported by the NSF Macrosystems Biology program (awards EF-1065786 and EF-1065818) and by the NSF Postdoctoral Research Fellowship in Biology (DBI-1401954).
Dataset ID
332
Methods
See Soranno, P.A., Bissell, E.G., Cheruvelil, K.S., Christel, S.T., Collins, S.M., Fergus, C.E., Filstrup, C.T., Lapierre, J.F., Lottig, N.R., Oliver, S.K., Scott, C.E., Smith, N.J., Stopyak, S., Yuan, S., Bremigan, M.T., Downing, J.A., Gries, C., Henry, E.N., Skaff, N.K., Stanley, E.H., Stow, C.A., Tan, P.-N., Wagner, T., and Webster, K.E. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse. Gigascience 4: 28. doi: 10.1186/s13742-015-0067-4 for details on how the observed values were obtained.
See Collins et al. Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales, Submitted to Ecological Applications, for details on data filtering and relationships between nutrient chemistry and landscape characteristics
Version Number
12

North Temperate Lakes LTER Yahara Lakes District Lake Watersheds

Abstract
This zip archive contains six separate shapefiles. One each for the lake watersheds of Mendota, Monona, and Wingra basins.Yahara_Basin: This polygon shapefile is the full Yahara River watershed delineated using LIDAR elevation data for Dane County and a 10m DEM from the USGS for Columbia and Rock counties. In addition, sewersheds from the city of Madison and a field-checked basin map from Dane Co LWRCD was used.Yahara_subBasins: This is the same as Yahara_Basin except with all of the major sub-basins delineated as well.Yahara_intBasins: This polygon shapefile consists of the internally-drained basins in the Yahara Basin. These were determined using the same elevation sources as in Yahara Basin. [These areas do not have a natural outlet (except during very large flood events...e.g., some overflowed in 2008)]
Creator
Dataset ID
323
Data Sources
Date Range
LTER Keywords
DOI
10.6073/pasta/48c4f52a43e5ad706da1359963048486
Maintenance
completed
Metadata Provider
Methods
See abstract for detailed description of datasources used. Processed with ArcGIS.
NTL Themes
Short Name
NTLSP046
Version Number
16

North Temperate Lakes LTER Northern Highlands Lake District Watersheds

Abstract
Watershed boundaries for 52 individual lakes in the NTL-LTER Northern Highlands Lake District, merged into a single GIS layer.
Dataset ID
145
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Watershed boundaries for 52 individual lakes in the NTL-LTER Northern Highlands Lake District, merged into a single GIS layer in ArcGIS from several layers from the Wisconsin Department of Natural Resources watersheds dataset.
Purpose
<p>Delineation of watershed boundaries.</p>
Short Name
NTLSP012
Version Number
23
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National Science Foundation | LTER Network | Center for Limnology        

This material is based upon work supported by the National Science Foundation under Cooperative Agreement #DEB-2025982, NTL LTER (ROR: 04gq8q482). Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.