4.7 Article

The impact of fog on soil moisture dynamics in the Namib Desert

期刊

ADVANCES IN WATER RESOURCES
卷 113, 期 -, 页码 23-29

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2018.01.004

关键词

Drylands; Ecohydrology; Fog; Gobabeb; Soil moisture; Stochastic modeling

资金

  1. U.S. National Science Foundation [IIA-1427642, EAR-1554894]
  2. Division Of Earth Sciences
  3. Directorate For Geosciences [1554894] Funding Source: National Science Foundation

向作者/读者索取更多资源

Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate. and average depth a (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.

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