Department of Conservation and Recreation
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Department of Conservation and Recreation
DCR has evaluated the potential for water quality degradation due to nonpoint sources (NPS) of pollution biennially since 1986 on a per hydrologic unit basis, also taking into account indicators of where such degradation might have its greatest negative impact.
Results can be found in the 2022 NPS Assessment Report, which is derived from the 2022 Virginia Water Quality Assessment (305b) Report published by the Virginia Department of Environmental Quality (DEQ).
For the 2022 NPS Pollution Assessment, estimations of the NPS pollutant loads of Nitrogen (N), Phosphorus (P) and Sediment (S) by the sixth-level hydrologic units of the National Watershed Boundary Dataset (NWBD) have been calculated using a NPS load simulation model and data developed by the DCR, DEQ and the Virginia Polytechnic Institute and State University (Virginia Tech) Department of Biological Systems Engineering (BSE).
The voluminous statewide data requirements of the model include:
Much of this data was gathered in very small units - in either small cells of less than a quarter acre or as coordinate pairs (x,y) - and then aggregated into hydrologic unit level data. For the 2020 NPS Pollution Assessment and Prioritization Study, data was developed and loads calculated for 1,240 of the 1,251 sixth-level hydrologic units of the Virginia NWBD (11 units were open-water only).
Loadings were developed using the above data as well as additional data layers and a host of modeling factors (i.e. build-up rates, curve numbers, uptake rates, evapo-transpiration, dissolved pollutant factors, etc.) in the NPS load computer model. The model replicated many of the NPS pollutant producing processes and created additive estimated NPS pollutant loads from each. Those processes (load components) are:
The load estimates by detailed hydrologic units as calculated above for N, P and S were separately calculated for agriculture, urban, forest and barren land use classes as well as for non-sewered development and channel erosion. A total NPS load per hydrologic unit per pollutant is calculated by summing these NPS load components.
Best management practices (BMPs) from the Virginia Agricultural BMP Cost-Share Program (VACS), as well as from the USDA NRCS and others, were used by DEQ to reduce the estimated loads initially calculated by the model per hydrologic unit in Virginia.
Modeling performed in the 2020 NPS pollution assessment is edge-of-stream modeling. This differs from the CBPO loading estimates, which are to the fall line of each river system, and from the load reductions calculated in the Virginia Agricultural BMP Cost-Share program, which are loadings to the edge of a field.
As part of each NPS Pollution Assessment, the estimated loads per pollutant per hydrologic unit are divided by the land area of the hydrologic unit to create a unit area load (UAL) per pollutant per hydrologic unit. For the purpose of targeting NPS pollutant reduction activities, hydrologic units are ranked per NPS pollutant (nitrogen, phosphorus, sediment and total) based on the UAL values of each into three categories:
Estimated loads, UALs and rankings can be obtained from DCR’s NPS databases. Results are reported and mapped in the 305(b) water quality report.
Aside from the ranking of the UALs above, other NPS pollution measures can be useful for prioritizing NPS reduction activities. In the 2022 study, two biological assessments were also reported – an evaluation of public surface water protection needs and a modified index of biological integrity (mIBI). Likewise, two measures of the extent of impaired waters in a HU were calculated – percent of river miles impaired and percent of lakes/reservoirs acres impaired. Combined with other relevant NPS measures, evaluations of NPS conditions can help planners and decision-makers target which hydrologic units should be given primary consideration for the implementation of NPS pollution control measures. Attention should be directed to those units with higher rankings in the prioritization categories as well as those units downstream of polluting conditions.
The mIBI was produced by the Virginia Commonwealth University Center for Environmental Studies. The mIBI values are derived from more than 162,000 stream-dependent records maintained by the DCR Division of Natural Heritage, the Virginia Department of Wildlife Resources and VCU. The academically established process for determining IBI scores can be found in the 2022 NPS Assessment Report.
To evaluate the effect to the human population that depends on surface water for drinking that NPS pollution can have on a hydrologic unit basis, sources (intakes) of public surface water supplies and the population they each serve were obtained from the VDH, which has also established a standard zone of protection from these sites. This is the area where activities likely to cause water quality degradation are most likely to affect the surface water supply. This area likely differs from the area of the population served. The process for ranking the various protection zones or overlapped portions of zones scores can also be found in the NPS Chapter of the 305b Report.
The impaired waters percentages were derived from impaired waters determinations made by DEQ and reported in their 2020 303d report. Impairments were evaluated to isolate those that had a nonpoint source measure and only those impairments were used in calculating the percentage of miles or acres impaired within each HU.
Prioritization component values and rankings can also be obtained from DCR’s NPS databases.
Various state programs have relied on specific products from past assessments in evaluating program conditions and targeting activities and funding. In general, DCR attempts to maximize limited resources and funds by targeting the high-load high-priority ranked units for NPS pollution reduction activities. However, different programs may target using different rankings. The rankings table of the NPS Chapter of the 305(b) Report contains a small set of flagged conditions. Other customized targeting methods can be developed by combining various ranked components in a way that meets program-specific targeting needs. For example, the Virginia Agricultural BMP Cost-Share Program (VACS) uses a customized Agricultural Nonpoint Source Assessment Ranking that uses an agricultural UAL per hydrological unit (loads/ag land) per NPS pollutant to target NPS BMP recruitment.
