Testing the hydrological landscape unit classification system and other terrain analysis measures for predicting low-flow nitrate and chloride in watersheds.
Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use-elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification scheme.
Poor
Cara J
CJ
Department of Civil and Environmental Engineering, Washington State University, 118 Sloan Hall, Pullman, WA 99164-2910, USA. cpoor@wsu.edu
McDonnell
Jeffrey J
JJ
Bolte
John
J
D000383:Agriculture; D002712:Chlorides / Q000032:analysis*; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D005843:Geography; D009566:Nitrates / Q000032:analysis*; D009922:Oregon; D045483:Rivers; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014881:Water Supply / Q000032:analysis*
D002712:Chlorides; D009566:Nitrates; D014874:Water Pollutants, Chemical