Abstract
Many studies have shown that isotope data are valuable for hydrological model calibration. Recent developments have made isotope analyses more accessible but event sampling still involves significant time and financial costs. Therefore, it is worth to study how many isotope samples are needed for hydrological model calibration and what the most informative sampling times are. In this study, we used synthetic data to investigate how systematic errors in the precipitation, streamflow and the isotopic composition of precipitation affect the information content of stream isotope samples for model calibration. The results show that model performance improves significantly when two or three isotope samples are used for calibration and that the most informative samples are taken on the falling limb. However, when there are errors in the rainfall isotopic composition, rising limb samples are more informative. Data errors caused the most informative samples to be more clustered and to occur earlier in the event compared to error free data. These results provide guidance on when to sample events for model calibration and thus help to reduce the cost and effort in obtaining useful data for model calibration.
Highlights
Changes in the chemistry and isotopic composition of stream water during rainfall events are frequently used to study runoff generation processes [1]
We focus on systematic errors in precipitation intensity (P), the isotopic composition of precipitation (CP ), and streamflow (Q)
The effect of the observation errors on model validation performance was larger for the small event than for the medium and large event (Figure 4), which suggests that model calibration for events with a slow response is more sensitive to data errors than the calibration for large events with larger changes in the amount of streamflow and the isotopic composition of streamflow during the event
Summary
Changes in the chemistry and isotopic composition of stream water during rainfall events are frequently used to study runoff generation processes [1]. These water quality data can be used to test and improve hydrological and hydrochemical models [2,3,4]. The respondents that identified themselves as field hydrologists would collect more samples for model calibration than those who identified themselves as modellers (e.g., 35% of the field hydrologists vs 22% of the modellers would take 6 to 20 samples). Seven percent of the respondents would take many more samples and highlighted the need for continuous sampling (hourly or sub-hourly). While continuous isotope measurements are possible [10], these data are still not widely available and most studies rely on data from a few samples
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