Water (Apr 2019)
Dew Yield and Its Influencing Factors at the Western Edge of Gurbantunggut Desert, China
Abstract
Dew is a significant water resource in arid desert areas. However, information regarding dew is scarce because it is difficult to measure due to the harsh environment of locations such as Gurbantunggut Desert, China. In this study, a non-destructive field experiment was conducted from 2015 to 2018 at a desert test station located in the western edge of the Gurbantunggut Desert, using a calibrated leaf wetness sensor (LWS) to measure dew yield. The results are as follows: (1) Dew formed after sunset with the atmospheric temperature gradually dropping and evaporated after sunrise with the temperature increasing in the second morning. (2) Dew was featured as ‘high frequency and low yield’. The average daily dew yield during dew days was 0.10 mm with a daily maximum of 0.62 mm, while dew days accounted for 44% of the total monitoring days, with a monthly maximum of 25 days. Compared with rainfall, dew days were two times as frequent as rainy days, while the average annual dewfall (12.21 mm) was about 1/11th of the average annual rainfall (134.6 mm), which indicates the dew contribution to regional water balance is about 9%. (3) March–April and October–November are the main periods of dew occurrence in this region because accumulated snow begins to melt slowly in March–April, providing sufficient vapor for dew formation, and the air temperature difference between day and night in October–November is the highest in the year, meaning that the temperature drops rapidly at night, making it easier to reach the dewpoint for vapor condensation. (4) Daily dew yield (D) was positively correlated to relative humidity (RH) and the difference between soil temperature at 10 cm below the ground and surface soil temperature (Tss), and negatively correlated to wind speed (V), air temperature (Ta), surface soil temperature (Ts), cloud cover (N), dewpoint temperature (Td) and the difference between air temperature and dewpoint temperature (Tad). It should be noted that the measured values of all factors above were the average value of the overnight period. The multivariate regression equation, D = −0.705 + 0.011 × RH − 0.006 × N − 0.01 × V, can estimate the daily dew yield with the thresholds of the parameters, i.e., RH > 70%, N < 7 (oktas) and V < 6 m/s.
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