Input data measurement-induced uncertainty in watershed modelling |
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| Authors: | Abhijit Patil |
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| Institution: | Department of Civil and Environmental Engineering , Louisiana State University , Baton Rouge , Louisiana , 70803 , USA |
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| Abstract: | Abstract This study presents a new methodology for estimation of input data measurement-induced uncertainty in simulated dissolved oxygen (DO) and nitrate-nitrogen (NO3-N) concentrations using the Hydrological Simulation Program–FORTRAN (HSPF) model and data from the Amite River, USA. Simulation results show that: (1) a multiplying factor of 1.3 can be used to describe the maximum error in temperature measurements; similarly, a multiplying factor of 1.9 was estimated to accommodate the maximum of ±5% error in rainfall measurements; (2) the uncertainty in simulated DO concentration due to positive temperature measurement errors can be described with a normal distribution, N(0.062, 0.567); (3) the uncertainty in simulated NO3-N concentration due to rainfall measurement errors follows a generalized extreme value distribution; and (4) the probability density functions can be utilized to determine the measurement-induced uncertainty in simulated DO and NO3-N concentrations according to the risk level acceptable in water quality management. Editor D. Koutsoyiannis Citation Patil, A. and Deng, Z.-Q., 2012. Input data measurement-induced uncertainty in watershed modelling. Hydrological Sciences Journal, 57 (1), 118–133. |
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| Keywords: | measurement-induced uncertainty dissolved oxygen nitrate-nitrogen temperature rainfall HSPF model |
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