Multiagency Projects:

Multiagency Critical Loads in Virginia and West Virginia

Aquatic Critical Loads and Exceedances in Acid-Sensitive Portions of Virginia and West Virginia - Results of the Southeastern Multiagency Critical Loads Research Project (click to view project results in an interactive web map)
Interactive Web Map for Critical LoadsBackground
The critical load (CL) is the level of sustained atmospheric deposition of S, N, or acidity below which significant harm to sensitive ecosystems does not occur according to current scientific understanding. For the sensitive receptor stream water, the most commonly selected chemical indicator is acid neutralizing capacity (ANC). A number of critical criteria values of ANC have been used as the basis for CL calculations, the most common of which have been 0, 20, 50, and 100 μeq/L. Each is believed to be associated with biological responses. The steady-state CL can be calculated using an empirical model. Results are reported here for a pilot project that explores approaches to CL calculation and mapping for the southeastern United States.

The most commonly used steady-state CL model for aquatic resource protection is the Steady-State Water Chemistry (SSWC) model. In this approach, the CL is calculated as a simple balancing of watershed base cation (BC; e.g., calcium, magnesium, sodium, potassium) inputs and outputs with the atmospheric deposition of strong acids. The watershed supply of BC due to weathering (BCw) is the CL model parameter that generally has the most influence in the CL calculation. Several commonly used regional approaches for estimating BCw are uncertain, in that they are rooted in unsubstantiated assumptions and rely on data that may not be available at appropriate scales for sensitive watersheds. Because the CL is a theoretical construct, its estimation by any model cannot be directly confirmed or validated, at least in the short term.

Estimation of Base Cation Weathering
An important objective of this research was to explore an alternative approach for estimating BCw, arguably the key term for estimating CL using the SSWC model (or any other aquatic steady state CL model). The dynamic model MAGIC (Model of Acidification of  Groundwater in Catchments) was used to estimate watershed-specific values of effective BCw. Based on empirical relationships between simulated BCw and key stream chemistry variables and watershed characteristics, simulated BCw and other spatial variables were extrapolated to the regional population of stream watersheds in acid-sensitive portions of Virginia and West Virginia, allowing regional calculation of CL and CL exceedance using SSWC.

Regression techniques were used to establish equations for BCw prediction across the landscape within each of three study ecoregions (Blue Ridge, Ridge and Valley, and Central Appalachian). MAGIC model estimates of BCw for the calibrated watersheds located throughout the study area were used as modeled weathering rates. Two predictor equations were established for each of the three ecoregions, one using both landscape characteristics and water chemistry parameters for use in the 522 watersheds for which stream chemistry data were available and another using landscape characteristics only. Continuous upslope  averages for each of the landscape predictor variables were calculated for each 30-m grid cell using hydrologically conditioned digital elevation model (DEM) data derivatives. This approach was used because stream chemistry integrates conditions throughout the drainage area.

A total of 92 stream sites were successfully calibrated using MAGIC. BCw estimates for those watersheds were extracted from the model calibration files and used as inputs for regional extrapolations.

Calculation of Critical Load
The stream network generated from the DEM for the pilot project study region was based on a minimum contributing area of 0.5 km2. In other words, the minimum drainage area that was designated as a stream watershed from the flow accumulation analysis was 0.5 km2. The lower boundary of each watershed was determined on the basis of stream tributary junctions. This process resulted in generation of a topographically determined stream network that was intermediate in stream size and density between the 1:100,000 National Hydrography Dataset (NHD) moderate resolution stream network and the high resolution 1:24,000 NHD network. The typical topographically determined watersheds were on the order of 1 km2 in area.

Values for each of the terms in the SSWC model were calculated for every 30-m grid cell in the study region. The SSWC equation was then solved to yield an estimate of CL for each 30-m grid cell. The representative watershed CL value was then calculated for each topographically determined watershed as an average of the CL values calculated at each stream cell (each grid cell intercepted by a topographically determined stream) within the watershed. A regional watershed CL map was prepared for each critical ANC indicator value.

Critical load results were also depicted for the network of streams that flow through these watersheds. Results of the CL calculations for the stream pixels (each 30-m grid cell that intersected a topographically determined stream) were averaged to reflect the CL of the stream reach that flows through that watershed based on the national stream network as represented in the high-resolution NHD database. This process was completed for all watersheds to yield a regional stream coverage that is coded with CL according to the value given to its associated watershed.

For the study area as a whole, about 30% to 40% of the stream length (depending on selection of threshold ANC value) was classified as having CL above 200 meq/m2/yr. The remainder of the stream length had lower calculated CL values, with about one-fourth of the stream length having CL below 100 meq/m2/yr. For most CL classes, there was not much difference in the extent of stream length within the class as influenced by the threshold ANC value selected. For the lowest CL class (less than 50 meq/m2/yr), however, choice of threshold ANC value made a substantial difference to the stream length calculations. The length of stream estimated to have CL ≤ 50 meq/m2/yr across the study area varied by about a factor of four depending on which threshold ANC value was selected.

Critical loads were generally much lower and more heavily influenced by selection of the threshold ANC value for Wilderness streams as compared with non-Wilderness streams. About 70% of the Wilderness stream length had CL less than 100 meq/m2/yr to protect to stream ANC above 50 μeq/L. Nearly half of the Wilderness stream length had CL less than 100 meq/m2/yr to protect to stream ANC above 0 μeq/L. 

Critical Load Exceedance
Watershed-averaged values of total ambient deposition of acidity were overlayed with the CL maps to generate regional estimates of CL exceedance, to identify areas where ambient deposition exceeds the CL.  Broad areas of the study region were found to be in CL exceedance when compared to the 5-year average deposition centered on 2005. Such areas are disproportionately associated with Class I areas and other public lands.

Half of the stream length within the study region was calculated to receive current acidic deposition in exceedance of the CL to protect against stream ANC below 0 μeq/L. That percentage increased to 53% for the threshold ANC value of 20 μeq/L, to 57% for the threshold ANC value of 50 μeq/L, and 63% for the threshold ANC value of 100  μeq/L. Nearly one-fourth of the stream length in the study region was estimated to be receiving acidic deposition that is more than double the CL for protecting stream ANC from going below 50 μeq/L. Exceedance of the CL was most prevalent in the Blue Ridge ecoregion, followed by the Central Appalachian ecoregion.

Temporal Patterns of Response
The CL and CL exceedance values calculated in this project pertain to long-term, steady-state water quality conditions. It may take a long time to reach the steady-state condition with respect to deposition acidity and stream chemistry at a constant loading rate. To address this concern, the dynamic model MAGIC was used to estimate the time to reach steady state at the CL deposition values calculated using the SSWC model. Results showed that:

  • most of the modeled watersheds will not reach steady-state for hundreds of years, and
  • the time period is somewhat longer if the selected threshold ANC value is higher (more protective)

Summary
In summary, the  SSWC steady-state CL model was applied in a regional pilot study to estimate CLs and exceedances for aquatic resources in streams in the southeastern United States. Terms in the SSWC model were derived on a regional landscape basis. Estimates of BC deposition and BC uptake by forests were available from national network databases. A computationally efficient and robust method for estimating weathering on a continuous basis across a regional landscape was developed for this project. It was based on weathering estimates extracted from a well-tested process-based watershed model of drainage water acid-base chemistry and also on features of the landscape that are available as regional spatial data coverages. This approach avoids many of the uncertainties associated with other common methods for estimating BCw for input into SSWC and other steady-state CL models.

Results indicate that more than half of the streams within the study region receive current acidic deposition that is higher than the steady state CLs. Furthermore, results indicate that most of the modeled watersheds will likely not reach the steady-state condition for hundreds of years after continuous constant deposition at the CL levels are established.

It should be noted that CL and exceedance calculations reported here represent examples of one approach to the CL process. No formal uncertainly analysis has been conducted. Therefore, the confidence level associated with these results is not known. Further research is needed to test, evaluate, and refine the approaches used to quantify weathering and CL.

This report is available for downloading here.