L-THIALong-Term Hydrological Impact Assessment (land use computer model)
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Test 1 (R2 = 0.85, MAE = 0.52) produced the highest positive correlation between observed (USGS) and predicted (L-THIA) direct runoff values followed by test 4 (R2 = 0.68, MAE = 0.75).
An analysis of the difference between the predicted (L-THIA) and observed (USGS) mean values of runoff, and a test of significance using t-test were used.
This study presents the development and testing of a simple calibration approach based on observed direct runoff values derived from readily available stream-gauge data available over the Internet; no complicated processing is required in the calibration process and, other than the stream-gauge data, no additional information is required beyond that used in an L-THIA model run.
L-THIA model predictions are found to be approximately 50 percent lower than actual observed direct runoff for the LEC watershed.
If the pace of land-use change or intensification is not captured in the available data, then L-THIA results should underpredict observations during periods of urbanization.
A thorough analysis of the causes of L-THIA underprediction is beyond the scope of this paper.
In a GIS application, L-THIA can handle the computationally intensive task of distributing runoff calculations for numerous land use polygons over space.
Initial applications of L-THIA involved assessing the impact of land use change on groundwater recharge, and of suburbanization on runoff into a wetland in northeast Ohio (Harbor, 1994; McClintock et al, 1995).
Recent applications of L-THIA include Minner's (1998) analysis of variations in urban sprawl impacts for the major climate regions of the U.S., her assessment of the relative hydrologic impacts of conservation subdivision design versus traditional use patterns, and the Minner et al.
In addition to CNs from soil and land use coverages, L-THIA runoff calculations require a long-term precipitation data set.
Runoff depth calculations were performed using L-THIA for each of the rainfall data sets.
The significant contribution of roadway areas to total runoff demonstrates that they are important areas to define in L-THIA analyses.