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Synoptic Assessment of the White River

 

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Wetlands in Arkansas In 1997 and 1998, CAST performed a multi-scalar synoptic assessment of riparian sedimentation in the White River watershed, Arkansas. This research was funded by the U.S. Environmental Protection Agency's National Health and Environmental Effects Research Laboratory, Western Ecology Division, in Corvallis, Oregon, through cooperative agreement CR824447-01-0 to the University of Arkansas in Fayetteville.

The synoptic approach (Leibowitz et al. 1992) has most frequently been used for small-scale, landscape-based studies, with the intent of maximizing limited time and resources. Typically, the goal is to find the highest risk areas, as the result of cumulative impacts, across a region or state. With the availability of improved, higher resolution data and current computer technology, it is possible to assess impacts both at a coarse regional level and at a finer local level, providing additional information that may have a separate audience than that of the traditional synoptic approach. The required time and computing costs for this extra output can be insignificant relative to the entire cost of the study. In this study of the White River watershed within the Mississippi River alluvial valley (also known as the delta), the goal was to expand the potential of the synoptic approach while still meeting its original objectives.

Agricultural runoff appears to be the biggest problem facing the delta wetlands. The Arkansas Department of Pollution Control and Ecology (now the Arkansas Dept. of Environmental Quality) assesses waters for six different use types: fish consumption, aquatic life, swimming, secondary contact, drinking supply, and agriculture and industry. The primary cause of rivers and streams not supporting all uses in Arkansas is siltation/turbidity, with 2,864 assessed stream miles suffering major impact, and another 228 assessed stream miles suffering moderate/minor impact. The primary source affecting these use impacts is agriculture (ADPCE 1996). The synoptic approach seems a reasonable means to rapidly and inexpensively assess the impact of agricultural runoff, and to identify specific areas for improvement.

Previous synoptic wetland assessments can be described as coarse-scale approaches. The primary focus of these studies was typically a rapid assessment of the threats to wetlands within large watersheds, and recommendations were made on how best to remediate these threats. Landscape units in these studies have typically been U.S. Geological Survey (USGS) hydrologic cataloging units, with an average size of around 750,000 acres. These large units were often used because the complex interactions of wetland ecosystems require large amounts of data to be defined and the inter-relationships of these interactions have yet to be fully discovered. Geographic information systems (GIS) allow for cheap storage, retrieval, and manipulation of large amounts of data and provide an ideal environment to perform synoptic wetland assessments at finer scales.

Analyses for this project were conducted at three distinct spatial scales. U.S. Geological Survey (USGS) hydrologic cataloging units were the coarsest scale of analysis and allow for cross comparisons with synoptic wetland assessments previously studied. Sub-basin (10,000-40,000 acres) analysis was the second tier of analysis, focusing on intra-watershed analysis of the source and transport of suspended sediments. Individual contiguous patches of wetland areas were the finest scale of analysis, and each patch was analyzed within each sub-basin according to the outcomes of the source and transport modules.

The first set of indices used in the model are centered around identifying the location and quantity of sediment in runoff. To tie the various indicators together, we used the Revised Universal Soil Loss Equation (RUSLE) (USDA NRCS 1995a). RUSLE is an erosion model designed to predict in a generalized manner the average soil loss and temporal average soil loss per unit area and is defined by the equation

A = R * K * L * S * P

where A is typically expressed in tons/acre/year, and R is a rainfall-runoff erosivity factor, K is a soil erodibility factor, L is a slope length factor, S is a slope steepness factor, C is a cover-management factor, and P is a support practice factor. For this study, all estimates of these parameters were obtained from the U.S. Department of Agriculture's Natural Resources Conservation Service (NRCS) bulletins (1994 & 1995).

Results/Conclusions

It appears that direct agricultural runoff is the largest source of siltation and turbidity in the waters of the study area. Generalizing the results of our model to the sub-basin level, we can examine the direct inflow of runoff from two different perspectives. First, we may simply want to know which sub-basins have the highest amounts of sediment runoff into non-vegetated streams and rivers, weighting each sub-basin by its area. These results may be compared to land cover maps to confirm what one might guess: areas of high agricultural land use generate high quantities of sediment runoff. In particular, there is a notable correlation between high runoff and a high percentage of soybeans within a sub-basin.

Although this information is useful, it doesn't tell the entire story. Given the same amount of runoff sediment, two different sub-basins could have quite different water quality depending upon the density of the stream network. In other words, what is the concentration of the runoff entering the streams? We can easily rank the sub-basins by this criteria as well. Although there is some similarity between this map and the one showing total sediment run-off, there is also a lot of difference. For example, while there are quite a few sub-basins in Phillips county that have a high quantity of sediment runoff per acre, there are only a couple of sub-basins that have a high concentration of sediment runoff into their streams, and only one of these is shared with the first group.

Geographic information systems have been shown to be a useful tool for identification and prioritization of wetlands in the Arkansas delta (Williamson et al. 1994; Foti 1996). Most of these earlier efforts have centered on relatively small study areas, working at spatial resolutions suitable for local analysis. The synoptic approach brings with it the potential to quickly and efficiently assess larger regions, such as the entire delta within the state of Arkansas. The results of this project show that it is also possible to use the synoptic approach to drive a more detailed, multi-scalar analysis of a large region, thereby satisfying a greater audience of potential users.

By breaking down the typically large watersheds of synoptic studies to their sub-basins, a much more detailed picture of ecological function emerges. Although it is certainly important to be able to assess the overall state of the large landscape units, the ability to isolate problem spots offers the land manager the opportunity to better focus his efforts and money. By taking the process one step further, within the individual sub-basin, it is even possible for the individuals responsible for field-based restoration work to have a better idea of the kind of problems they will be facing.

 

The full report for this project was submitted to the U.S. Environmental Protection Agency's National Health and Environmental Effects Research Laboratory, Western Ecology Division, in Corvallis, Oregon.

Literature cited

Arkansas Department of Pollution Control and Ecology (ADPCE). 1996. Water quality inventory report 1996. State of Arkansas Department of Pollution Control and Ecology, Little Rock, Arkansas.

Foti, T. 1996. The standard GIS methodology for wetland analysis. Internal report for Arkansas Multi-Agency Wetland Planning Team, Little Rock, Arkansas. 

Leibowitz, S. G., B. Abbruzzese, P. R. Adamus, L. E. Hughes, and J. T. Irish. 1992. A synoptic approach to cumulative impact assessment: A proposed methodology. EPA/600/R-92/167. U. S. EPA Environmental Research Laboratory, Corvallis, Oregon. 

USDA Natural Resources Conservation Service (NRCS). 1994. State Soil Geographic (STATSGO) Data Base: Data Use information. U.S. Dept. of Agriculture - Natural Resources Conservation Service, National Soil Survey Center. Miscellaneous Publication Number 1492.

USDA Natural Resources Conservation Service (NRCS). 1995. Arkansas Predicting Soil Loss Handbook. U.S. Dept. of Agriculture - Natural Resources Conservation Service, Little Rock, Arkansas.

Williamson, M. D., W. F. Limp, and J. C. Gillam. 1994. Spatial based methods for the development of a state digital wetlands mapping and prioritization program. Report prepared for Arkansas Natural Heritage Commission, Little Rock, Arkansas.