Measurement of environmental parameters in polar regions based on a ubiquitous sensor network

To estimate the spatial variation of soil CO2 flux in a permafrost region, major environmental parameters were measured and analyzed using the proposed ubiquitous sensor network-based remote monitoring system (U-RMS). The use of techniques for power-efficient operation and network scalability that enable long-term use of a wireless sensor network (WSN) that can be deployed reliably and widely is described. The temporal and spatial variations in air temperature (Ta) and relative humidity (RH) near the surface at 16 locations and soil temperature (Ts) and soil water content (SWC) at 10 locations were measured to monitor the active permafrost layer in Alaska from September 2012 to January 2013 and from July to September 2013. The temporal variations in environmental parameters in the soil and near the surface depended on the thawing and freezing of the snow cover in the permafrost regions. The spatial patterns of Ts in the three periods were not similar because of the heterogeneous distribution of snow coverage and depth in winter. On the other hand, the spatial patterns of Ts and SWC had a negative relationship during summer. The spatial variations in Ts and SWC showed a high coefficient of variation (CV) that ranged from 20% to 40%, while the CV of Ta and RH was within 5% except in winter due to the spatially heterogeneous snow cover. The relationship between CO2 efflux and Ts or SWC in 2012, which had a high CV, was examined to estimate the soil CO2 efflux in 2013. The Ts explained ~60% (soil CO2 efflux=0.066×exp0.1443×Ts, R2 0.59) of the variation in soil CO2 efflux in a temperature range of 3 to 8°C. Therefore, the soil CO2 efflux in 2013 was estimated in the range of 0.08mgm−2s−1 to 0.47mgm−2s−1, and average CV was 25%. Using the camera sensor, the growth of vegetation and the operating appearance of the remote WSN were also monitored. In the long term, measurement of temporal and spatial variations in environmental parameters, based on U-RMS, is expected to contribute to the understanding of the carbon and water cycles in permafrost.