Indiana University-Purdue University Indianapolis (IUPUI) / Soil moisture is a key variable in dryland ecosystems. Knowing how and to what extent soil moisture is influenced by rainfall and non-rainfall waters (e.g., dew, fog, and water vapor) is essential to understand dryland dynamics. The hyper-arid environment of the Namib Desert with its frequent occurrence of fog events provides an ideal place to conduct research on the rainfall and non-rainfall effects on soil moisture dynamics. Rainfall and soil moisture records was collected from three locations (gravel plain at Gobabeb (GPG), sand dune at Gobabeb (SDG), and gravel plain at Kleinberg (GPK)) within the Namib Desert using CS655 Water Content Reflectometer and tipping-buckets, respectively. The fog data was collected from the FogNet stations. Field observations of rainfall and soil moisture from three study sites suggested that soil moisture dynamics follow rainfall patterns at two gravel plain sites, whereas no significant relationships was observed at the sand dune site. The stochastic modeling results showed that most of soil moisture dynamics can be simulated except the rainless periods. Model sensitivity in response to different soil and vegetation parameters was investigated under diverse soil textures. Sensitivity analyses suggested that soil hygroscopic point (sh), field capacity (sfc) were two main parameters controlling the model output. Despite soil moisture dynamics can be partially explained by rainfall, soil moisture dynamics during rainless period still poorly understood. In addition, characterization of fog distribution in the Namib Desert is still lacking. To this end, nearly two years’ continuous daily records of fog were used to derive fog distribution. The results suggested that fog is able to be well - characterized by a Poisson process with two parameters (arrival rate and average depth). Field observations indicated that there is a moderate positive relationship between soil moisture and fog at GPG and the relationship tend to be less significant at the other two sites. A modified modeling results suggested that mean and general patterns of soil moisture can be captured by the modeling. This thesis is of practical importance for understanding soil moisture dynamics in response to the rainfall and fog changing conditions.
Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/14008 |
Date | 07 1900 |
Creators | Li, Bonan |
Contributors | Wang, Lixin |
Source Sets | Indiana University-Purdue University Indianapolis |
Language | English |
Detected Language | English |
Type | Thesis |
Rights | Attribution-NonCommercial-NoDerivs 3.0 United States, http://creativecommons.org/licenses/by-nc-nd/3.0/us/ |
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