Developing soil water potential time series using the Montana Mesonet’s in-situ sensor data and lab-measured soil characteristics

Abstract

As a headwaters state, changes in water across Montana’s landscape can have major implications for nearly two-thirds of the land area of the Conterminous United States to which its two major river basins drain. Monitoring watersheds in Montana provides important metrics for drought detection, agricultural management, and other natural resource management decisions. The Montana Mesonet, a wireless network of 79 meteorological, soil moisture, and groundwater monitoring stations, was created in 2016 to provide monitoring data. This network is supported through federal, state, tribal and private partnerships. Each station records measures at 15-minute intervals, including: soil moisture, soil-water conductivity, precipitation, relative humidity, temperature, wind speed and direction, solar radiation, and groundwater levels. Developing information about soil characteristics will put sensor data into a context applicable for land management decisions. As such, this project-in-progress focuses on the development of soil water retention curves and soil texture characterizations to enhance data collected by the Montana Mesonet. To assess soil characteristics, triplicate soil cores were collected at each station site at four depths. These cores are used for two lab analyses. Soil water retention curves were developed across a moisture gradient using tensiometers, balances, and potentiometers. Lab-measured soil water retention curves allow in-situ soil moisture time series to be converted to soil water potential, a biologically meaningful variable used to assess plant water stress. So far, approximately one-third of sites have soil-water retention curves and soil-water-potential time series generated at all depths. Soil texture will be determined by assessing the particle size distribution of a sample using the integral suspension pressure (ISP) method. The addition of these soil characteristics to the extensive Mesonet data will allow for site-specific historic, near real-time, and forecasted modeling of plant-available water, groundwater recharge, calculations of drought indices, and other practical applications to inform management decisions

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