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Why study mountain hydrology?
This portion of our initiative aims to study California’s water supply at its source, the Sierra Nevada mountains. It is estimated that seasonal snow cover is the primary source of water supply for over 60 million people in the western United States, and that melting snow is responsible for 80% or more of annual water supplies in California. This work is part of a larger monitoring initiative conducted under a collaborative effort with the Sierra Nevada Research Institute and the Critical Zone Observatories. While the study of hydrologic phenomena is a relatively mature field, the hydrologic processes pertaining to water and energy fluxes in mountainous regions, where basins are largely dominated by snowmelt, are yet not well captured by hydrologic models. It is especially not known to what extent, if any, recent trends in climate change will affect mountain hydrology and, specifically, future water supplies. Our project focuses on the deployment of large-scale wireless sensor networks for the study of such phenomena. The data acquired by these networks will allow for a deeper scientific understanding of these natural systems, while providing decision makers with improved forecasting tools. Additionally, it is fun to work in the mountains, as our pictures indicate.
Research Objectives
Wireless Sensor Networks
A sixty-node prototype wireless sensor network (WSN) has been deployed on a 1.5 kilometer transect in a mid-elevation headwater catchment in the Kings River Experimental Watershed. The site is located near Shaver Lake, California. The network is built upon ultra-low-power radio technology developed by Dust Networks. The WSN is self-healing, and self-meshing, allowing it to adapt to changes in environmental conditions to ensure reliable data transfer. The network gathers data from over 300 sensors, measuring temperature, humidity, snow depth, soil moisture, matric potential and solar radiation levels. Measurements are taken on fifteen-minute intervals and real-time data is readily made available via a mobile cell-phone modem at the base station of the network.
Sensor Nodes
Sensor node architecture: (1) mote (wireless component), (2) custom data-logger to interface the sensor array, (3) on-site storage, (4) 12V battery to power sensor array, (5) snow-depth sensor, (6) humidity and temperature sensor, (7) solar radiation sensor, (8) 10W solar panel, (9) external 8dBi antenna, (10) four soil moisture, temperature, and matric potential sensors at varying depths. Readings are taken on 15 minute intervals.
Snow Depth Sensor
Snow depth is the total depth of snow on the ground during a specified time. It is measured, because winter precipitation is stored in the snow pack and released latter in the year as snow melt. Snow depth must be coupled with snow density to determine the quantity of water being stored in the snowpack. The Judd Communications ultrasonic depth sensor works by measuring the time required for an ultrasonic pulse to travel to and from the snow/soil surface. An integrated temperature probe provides an air temperature measurement for properly compensating for the speed of the acoustic signal An embedded micro-controller calculates a temperature compensated distance and performs an error checking routine. Both distance and air temperature are output digitally. Measurement errors are typically within a single centimeter.
Soil Moisture Sensor
Why measure: This sensor measures soil moisture (volumetric water content) and soil temperature. These measurements are taken at different depths to better understand the dynamics of soil storage. Changes in soil water storage over time indicate wetting and drying periods throughout the year and are an important part of the overall water balance . Soil temperature readings indicate if soils are frozen, which significantly affects water movement on the soil surface. The Decagon Devices ECH2O water content/temperature sensor measures the dielectric permittivity of soil to determine water content. Temperature is measured using a thermistor which is attached to the probe prongs. Both soil moisture and temperature are output digitally.
Matric Potential Sensor
The matrix potential , or water potential, is a measure of of how water moves in soil, and from soil to plants. Water potential is used to determine plant water availability and soil stress. Comparing soil water content and matric potential measurements, in situ moisture release curves can be created. The Decagon Devices MPS-1 sensor measures the dielectric permittivity of an internal, porous ceramic disk to infer water potential. A large range of continuous soil water potential measurements can be made without calibration to specific soil types, since the dielectric permittivity of the porous ceramic disk is highly dependent on the amount of water that is present in the pore spaces of the ceramic.
Solar Radiation Sensor
The solar radiation sensor measures global solar radiation, which is the primary energy source for snowmelt processes. Solar radiation varies significantly among regions, season, and time of day. Surrounding terrain elevation, man-made obstructions, and surrounding trees can also cause large variations in locations with a small area. The Li-Cor pyranometer is designed for field measurement of global solar radiation, featuring a silicon photovoltaic detector mounted in a fully cosine-corrected miniature head. The current output is directly related to solar radiation.
Temperature and Humidity Sensor
Humidity readings can be indicators of the rain-snow trnasition zone, a region where percipitation transitions from liquid to solid form. Humidity readings can also be used to determine the effects of in-air water content on WSN communcations. The SHT1x by Sensiron features a version 4 Silicon sensor chip. Besides the humidity and temperature sensors, the chip contains an amplifier, A/D converter, OTP memory and a digital interface. While the sensor is made of a CMOS chip, the sensor housing consists of an LCP cap with epoxy glob top on an FR4 substrate. Electrical properties of various substrates on the sensors help infer humidity and temperature conditions.
Steven Glaser
| Professor, Systems Engineering Civil and Environmental Engineering, UC Berkeley glaser@berkeley.edu |
Roger Bales
| Professor, School of Engineering, UC Merced Sierra Nevada Research Institute rbales@ucmerced.edu |
Branko Kerkez
| Civil and Environmental Engineering, UC Berkeley bkerkez@berkeley.edu |
Matt Meadows
| Sierra Nevada Research Institute mmeadows@ucmerced.edu |
