Browsing by Subject "arid"

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  • Atashi, Nahid; Tuure, Juuso; Alakukku, Laura; Rahimi, Dariush; Pellikka, Petri; Zaidan, Martha Arbayani; Vuollekoski, Henri; Rasanen, Matti; Kulmala, Markku; Vesala, Timo; Hussein, Tareq (2021)
    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 similar to 130 days with dew yield > 0.1 L/m(2)/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/m(2)/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.
  • Sotunde, Sobowale Adedapo (Helsingfors universitet, 2016)
    In meeting the crop water needs in the arid and semi-arid regions, alternative source of water must be explored, like the harvesting of dew and fog. To estimate the quantity of potential harvestable water in semi-arid Nigeria, a 3-hourly meteorological data from 8 weathers stations across the semi-arid region of Nigeria were analysed. The data; from January to December 2009; was retrieved in June 2015 from the European Center for Medium range Weather Forecasting (ECMWF) database, by the Finnish Meteorological Institute (FMI). The available data includes the wind speed (WS) and direction, air temperature, and the relative humidity (RH). From the available data, the following needed parameters to calculate the potential water harvestable in each area were first calculated; the air saturated vapour pressure, air vapour pressure, absolute humidity, and finally the potential water harvestable through air humidity over 3hours (WH3). Only the RH ≥69% were used in calculating the WH3, at lower values water harvesting isn’t possible. Also, only the WS ≤2 was used, at higher values of WS, evaporation occurs. All the areas showed the possibility of harvesting water from dew and fog. The possibility was however higher during the wet season both in quantity and in frequency in all the areas considered than in the dry season.