Technical report: The design and evaluation of a basin‐scale wireless sensor network for mountain hydrology. Issue 5 (15th May 2017)

• Record Type: Journal Article
• Authors: Zhang, Ziran; Glaser, Steven D.; Bales, Roger C.; Conklin, Martha; Rice, Robert; Marks, Danny G.
• Is Part Of: Water resources research. Volume 53:Issue 5(2017)
• Page Start: 4487
• Page End: 4498
• Publication Date: 2017-05-15
• Subjects: wireless‐sensor network -- water‐information system -- snow observation -- mountain hydrology -- Sierra Nevada; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2016WR019619
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: A network of sensors for spatially representative water‐balance measurements was developed and deployed across the 2000 km 2 snow‐dominated portion of the upper American River basin, primarily to measure changes in snowpack and soil‐water storage, air temperature, and humidity. This wireless sensor network (WSN) consists of 14 sensor clusters, each with 10 measurement nodes that were strategically placed within a 1 km 2 area, across different elevations, aspects, slopes, and canopy covers. Compared to existing operational sensor installations, the WSN reduces hydrologic uncertainty in at least three ways. First, redundant measurements improved estimation of lapse rates for air and dew‐point temperature. Second, distributed measurements captured local variability and constrained uncertainty in air and dew‐point temperature, snow accumulation, and derived hydrologic attributes important for modeling and prediction. Third, the distributed relative‐humidity measurements offer a unique capability to monitor upper‐basin patterns in dew‐point temperature and characterize elevation gradient of water vapor‐pressure deficit across steep, variable topography. Network statistics during the first year of operation demonstrated that the WSN was robust for cold, wet, and windy conditions in the basin. The electronic technology used in the WSN‐reduced adverse effects, such as high current consumption, multipath signal fading, and clock drift, seen in previous remote WSNs. Key Points: This first basin‐scale wireless‐sensor network provides reliable, representative measurements in a mountain basin The distributed network better characterizes patterns of key hydrologic variables compared to operational networks Used with spatially explicit modeling and other spatial data, the network offers unprecedented opportunities for improved hydrologic prediction