Evaluation of wireless sensor networks (WSNs) for remote wetland monitoring: design and initial results

Here, we describe and evaluate two low-power wireless sensor networks (WSNs) designed to remotely monitor wetland hydrochemical dynamics over time scales ranging from minutes to decades. Each WSN (one student-built and one commercial) has multiple nodes to monitor water level, precipitation, evapotranspiration, temperature, and major solutes at user-defined time intervals. Both WSNs can be configured to report data in near real time via the internet. Based on deployments in two isolated wetlands, we report highly resolved water budgets, transient reversals of flow path, rates of transpiration from peatlands and the dynamics of chromophoric-dissolved organic matter and bulk ionic solutes (specific conductivity)—all on daily or subdaily time scales. Initial results indicate that direct precipitation and evapotranspiration dominate the hydrologic budget of both study wetlands, despite their relatively flat geomorphology and proximity to elevated uplands. Rates of transpiration from peatland sites were typically greater than evaporation from open waters but were more challenging to integrate spatially. Due to the high specific yield of peat, the hydrologic gradient between peatland and open water varied with precipitation events and intervening periods of dry out. The resultant flow path reversals implied that the flux of solutes across the riparian boundary varied over daily time scales. We conclude that WSNs can be deployed in remote wetland-dominated ecosystems at relatively low cost to assess the hydrochemical impacts of weather, climate, and other perturbations.

[1]  S. Loheide A method for estimating subdaily evapotranspiration of shallow groundwater using diurnal water table fluctuations , 2008 .

[2]  Kenneth Y. Kaneshiro,et al.  Integration of Wireless Sensor Networks into Cyberinfrastructure for Monitoring Hawaiian “Mountain-to-Sea” Environments , 2008, Environmental management.

[3]  Timothy K. Kratz,et al.  Long-term dynamics of lakes in the landscape : long-term ecological research on north temperate lakes , 2006 .

[4]  H. Hemond Biogeochemistry of Thoreau's Bog, Concord, Massachusetts , 1980 .

[5]  J. Canadell,et al.  Peatlands and the carbon cycle: from local processes to global implications - a synthesis , 2008 .

[6]  Peter Arzberger,et al.  New Eyes on the World: Advanced Sensors for Ecology , 2009 .

[7]  W. N. White A method of estimating ground-water supplies based on discharge by plants and evaporation from soil--results of investigations in Escalante Valley, Utah , 1932 .

[8]  Thomas C. Winter,et al.  Dynamics of water-table fluctuations in an upland between two prairie-pothole wetlands in North Dakota , 1997 .

[9]  J. Holden,et al.  Hydrological studies on blanket peat: the significance of the acrotelm‐catotelm model , 2003 .

[10]  Yu Hen Hu,et al.  A temperature compensation method for CDOM fluorescence sensors in freshwater , 2011 .

[11]  Deborah Estrin,et al.  Habitat monitoring with sensor networks , 2004, CACM.

[12]  T. Kratz,et al.  Spatial and temporal patterns in the hydrogeochemistry of a poor fen in northern Wisconsin , 1990 .

[13]  P. Gerla,et al.  The relationship of water-table changes to the capillary fringe, evapotranspiration, and precipitation in intermittent wetlands , 1992, Wetlands.

[14]  S. Carpenter,et al.  Integrating aquatic and terrestrial components to construct a complete carbon budget for a north temperate lake district , 2011 .

[15]  M. Lomas,et al.  The MILLENNIA peat cohort model: predicting past, present and future soil carbon budgets and fluxes under changing climates in peatlands , 2010 .

[16]  K. Davis,et al.  Environmental drivers of evapotranspiration in a shrub wetland and an upland forest in northern Wisconsin , 2007 .

[17]  Scott D. Bridgham,et al.  The carbon balance of North American wetlands , 2006, Wetlands.

[18]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[19]  Paul J.M. Havinga,et al.  A new wireless underground network system for continuous monitoring of soil water contents , 2009 .

[20]  David Bruce Lewis,et al.  Making Sense of the Landscape: Geomorphic Legacies and the Landscape Position of Lakes , 2005 .

[21]  Paul L. G. Vlek,et al.  An appraisal of global wetland area and its organic carbon stock , 2005 .

[22]  Timothy K. Kratz,et al.  Effects of climate variability on lake evaporation: Results from a long-term energy budget study of Sparkling Lake, northern Wisconsin (USA) , 2005 .

[23]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.

[24]  K. Ewel,et al.  Effect of the 1997–1998 ENSO-related drought on hydrology and salinity in a micronesian wetland complex , 2001 .

[25]  H. Ingram,et al.  Size and shape in raised mire ecosystems: a geophysical model , 1982, Nature.

[26]  D. Naugle,et al.  Vulnerability of Northern Prairie Wetlands to Climate Change , 2005 .

[27]  Qi Han,et al.  On Integrating Groundwater Transport Models with Wireless Sensor Networks , 2010, Ground water.

[28]  Stefano Chessa,et al.  Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards , 2007, Comput. Commun..

[29]  S. Carpenter,et al.  Filling holes in regional carbon budgets: Predicting peat depth in a north temperate lake district , 2010 .

[30]  Jennifer C. Hou,et al.  Wireless sensor networks , 2004, IEEE Wirel. Commun..