Inverse modeling of dissolved O2 and δ18O-DO to estimate aquatic metabolism, reaeration and respiration isotopic fractionation: effects of variable light regimes and input uncertainties

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Abstract

A transient model, hereafter referred to as ROM-TM, was developed to quantify river ecosystem metabolic rates and reaeration rates from field observation of changes in dissolved O2 (DO) and the ratio of 18O to 16O in DO (δ18O-DO). ROM-TM applies an inverse modeling approach and is programmed using MATLAB. Parameters describing photosynthesis, ecosystem respiration, gas exchange, and isotopic fractionation, such as maximum photosynthetic rate (P m ), photosynthetic efficiency parameter (a), respiration rate at 20 °C (R 20 ), gas exchange coefficient (K), respiration isotopic fractionation factor (a R ), and photorespiration coefficient (β R ), can be abstracted by minimizing the sum of square errors between the fitted data and the observed field data. Then DO and δ18O-DO time series can be reconstructed using estimated parameters and input variables. Besides being capable of teasing apart metabolic processes and gas exchange to provide daily average estimates of metabolic parameters at the ecosystem scale, ROM-TM can be used to address issues related to light including light saturation phenomena at the ecosystem level, the effect of cloud cover on the metabolic balance, and photorespiration. Error and uncertainty analysis demonstrates that ROM-TM is stable and robust for the random errors of DO time series. The photosynthetic parameters P m and a are more sensitive than other parameters to lower-resolution time series data.