An Attempt to Utilize a Regional Dew Formation Model in Kenya

Water

Laura Alakukku¹  Juuso Tuure¹  Petri Pellikka²  Dariush Rahimi³  Timo Vesala⁴  Tareq Hussein⁴  MarthaA. Zaidan⁴  Markku Kulmala⁴  Henri Vuollekoski⁴  Nahid Atashi⁴  Matti Räsänen⁴ 

[1] Department of Agricultural Sciences, University of Helsinki, P.O. Box 28 Koetilantie 5, FI-00014 Helsinki, Finland;Department of Geosciences and Geography, University of Helsinki, P.O. Box 64 Gustaf Hällströmin Katu 2a, FI-00014 Helsinki, Finland;Department of Physical Geography, Faculty of Geographical Science and Planning, University of Isfahan, Isfahan 8174673441, Iran;Institute for Atmospheric and Earth System Research (INAR/Physics), Faculty of Science, University of Helsinki, FI-00014 Helsinki, Finland;

关键词: dew yield;    spatial and temporal;    cluster analysis;    dew formation zones;    arid;    semi-arid;   

DOI  :  10.3390/w13091261

来源: DOAJ

【 摘 要 】

Model evaluation against experimental data is an important step towards accurate model predictions and simulations. Here, we evaluated an energy-balance model to predict dew formation occurrence and estimate its amount for East-African arid-climate conditions against 13 months of experimental dew harvesting data in Maktau, Kenya. The model was capable of predicting the dew formation occurrence effectively. However, it overestimated the harvestable dew amount by about a ratio of 1.7. As such, a factor of 0.6 was applied for a long-term period (1979–2018) to investigate the spatial and temporal variation of the dew formation in Kenya. The annual average of dew occurrence in Kenya was ~130 days with dew yield > 0.1 L/m²/day. The dew formation showed a seasonal cycle with the maximum yield in winter and minimum in summer. Three major dew formation zones were identified after cluster analysis: arid and semi-arid regions; mountain regions; and coastal regions. The average daily and yearly maximum dew yield were 0.05 and 18; 0.9 and 25; and 0.15 and 40 L/m²/day; respectively. A precise prediction of dew occurrence and dew yield is very challenging due to inherent limitations in numerical models and meteorological input parameters.

【 授权许可】

Unknown