Reply to comment by Binayak P. Mohanty and Zhenlei Yang on “A simulation analysis of the advective effect on evaporation using a two‐phase heat and mass flow model”

Abstract

[1] We thank Mohanty and Yang [2013] (hereafter referred to as MY) for their comment on our paper ‘‘A simulation analysis of the advective effect on evaporation using a two-phase heat and mass flow model’’ [Zeng et al., 2011b]. We appreciate the effort by MY to look critically at our paper. We hope that the responses to their comments will help to clarify the issues they raised and to communicate better our approach and contributions to the reader. By reviewing MY’s comments, it is clear to us that we need to provide further clarification on the details of the key aspects of our paper. As shall be seen in following sections, we disagree with all of their objections. Before we issue the point-to-point rebuttal to the two key points MY raised, we want to clarify the approaches we presented in our paper. In such way, we hope to assist the reader to have a systematic view on the key aspects and make definite conclusions on its merits and validity. [2] The main objective of our paper was to identify the controlling mechanism for the advective effect on soil evaporation. When excluding soil airflow, the advective flux can lead to the underestimation of surface evaporative flux [Zeng et al., 2011a, 2011b]. To identify such mechanism, a systematic approach, including both experimental and numerical ones, should be applied. We implemented an in situ experiment and developed a two-phase heat and mass flow model to serve this purpose. With the calibrated two-phase model, the detailed driving force (e.g., matric potential gradient, soil air pressure gradients, and soil temperature gradients) and conductivity fields can be used to investigate and identify what exactly drives the underestimation error. The comparison in the modeled surface fluxes (e.g., evaporative fluxes) with and without soil airflow can identify the underestimation error. The modeled surface flux is a total flux, which is the summation of thermal and isothermal fluxes, and advective fluxes (e.g., when soil airflow being considered). Therefore, it requires a systematic view to decompose the total flux into different components, based on different driving forces. This is what we discussed at the beginning of section 3.3 in our original paper [Zeng et al., 2011b], from where we have analyzed the direct and indirect controlling mechanisms. [3] Based on the diurnal variation pattern of matric potential gradients above the depth of 50 cm, upward during the day and downward during the night, the original paper targets the isothermal flux as the direct driving factor for the underestimation error (e.g., the upward isothermal flux is higher when considering airflow than that without airflow). The inverse variation pattern of soil temperature and soil air pressure gradients, compared to the matric potential one, precludes their direct influence on the underestimation error. However, soil temperature gradient may have an indirect effect on the error (e.g., the downward thermal flux is lower when considering airflow than that without airflow). To verify the above hypothesis, the original paper compares the gradient and conductivity fields by using a normalized scale index (NSI). It is found that the indirect effect of thermal fluxes on the error is invalid because the downward thermal flux with airflow mechanism is larger than that without airflow. This is in contrast to the hypothesis. On the other hand, the original paper verifies the isothermal flux as the direct driving factor accounting for the underestimation error. The upward isothermal flux with airflow mechanism is indeed larger than that without airflow. [4] From Figure 4 of Zeng et al. [2011b], it is obvious that the advective effect is the most significant on day 2, which is chosen for analyzing the controlling mechanism behind the effect. The most significant effect, on day 2, implies the dominance of isothermal fluxes, which can be inferred by comparing the magnitude of different component fluxes [Zeng et al., 2009b]. From day 2 onward, the thermal fluxes start to dominate. As the soil temperature gradient is downward during daytime, it can be inferred that the dominance of thermal fluxes will minify the advective effect. This is because both fluxes (downward thermal and upward isothermal fluxes) will cancel each other out. This can also be inferred from the diurnal patterns of matric potential and soil temperature gradient in Figure 5 of Zeng et al. [2011b]. [5] The further analysis identifies the isothermal hydraulic conductivity as the key factor accounting for the advective effect since it is increased largely when considering airflow. One of the possible mechanisms for such increase Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands.