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An empirical method to predict initial and minimum streamwater pH for episodic events in central Pennsylvania

Thesis/Dissertation ·
OSTI ID:39166
Two models were developed for central Pennsylvania to predict the episodic initial and minimum pH in streamwater resulting from runoff events and to aid in regional evaluations of stream sensitivity to acidic atmospheric deposition. The IpH model was formulated by multiple regression, using baseflow pH data from Leading Ridge Experimental Watershed One, to predict streamwater initial pH using input parameters of month and 2-day, 7-day, 14-day, 28-day, and 60-day antecedent precipitation. Estimating baseflow pH values for other regional streams require an adjustment of IpH predicted values by high and low baseflow factors to reflect baseflow pH for the {open_quotes}new{close_quotes} stream. The model r{sup 2} was 0.71 and verification results indicated that the model performed well for seven of eight watersheds. IpH model verification resulted in a model efficiency of 0.66. Additional IpH verification using data from four other watersheds found predicted values within 0.3 pH unit of actual values 80% of the time. The EpH model was developed by multiple regression to predict episodic minimum pH using data from eight central Pennsylvania watersheds. The model input parameters are total storm precipitation, initial pH, and the ratio of the In(a/tan{beta}) 80th percentile to the 90th percentile values (In80/90). The index relates topographically, the amount of area draining to a particular watershed point divided by the slope. The In80/90 variable was included to represent differences in hydrologic responsiveness among watersheds. The EpH model had an r{sup 2} of 0.80 and was verified with data from five additional regional watersheds. EpH predicted values for 20 episodes were within 0.3 pH units 75% of the time. The IpH/EpH models appear to be suitable for predicting initial and minimum pH during episodes for headwater streams of central Pennsylvania. The models have demonstrated reasonable accuracy while being easy to apply.
Research Organization:
Pennsylvania State Univ., University Park, PA (United States)
OSTI ID:
39166
Country of Publication:
United States
Language:
English