Developing a strategy for the national coordinated soil moisture monitoring network

Abstract

Soil moisture is a critical land surface variable, affecting a wide variety of climatological, agricultural, and hydrological processes. Determining the current soil moisture status is possible via a variety of methods, including in situ monitoring, remote sensing, and numerical modeling. Although all of these approaches are rapidly evolving, there is no cohesive strategy or framework to integrate these diverse information sources to develop and disseminate coordinated national soil moisture products that will improve our ability to understand climate variability. The National Coordinated Soil Moisture Monitoring Network initiative has developed a national strategy for network coordination with NOAA's National Integrated Drought Information System. The strategy is currently in review within NOAA, and work is underway to implement the initial milestones of the strategy. This update reviews the goals and

Using soil moisture information to better understand and predict wildfire danger: a review of recent developments and outstanding questions

“…The International Soil Moisture Network (ISMN) houses publicly available data from nearly 2700 in situ soil moisture monitoring stations across 65 networks worldwide, a number that is steadily growing (Dorigo et al 2021). The United States has an especially prolific collection of in situ soil moisture monitoring networks, and the ongoing National Coordinated Soil Moisture Monitoring Network (NCSMMN) initiative aims to produced harmonised data products from in situ soil moisture measurements from approximately 2000 sites across the nation (Cosh et al 2021). One of the longest running and densest large-scale soil moisture monitoring networks in the US, and in the world, is the Oklahoma Mesonet (McPherson et al 2007;Ochsner et al 2013).…”

“…3). Finally, these datasets are often of limited duration, generally spanning less than 20 years (Cosh et al 2021;Dorigo et al 2021), which can make it challenging to use them for soil moisture-wildfire modelling. Therefore, there is a clear need for supplemental strategies for quantifying soil moisture, which include remotely sensed and modelled soil moisture information.…”

<em>In situ</em> Soil Moisture Sensors in Undisturbed Soils

“…Longer tines integrate a larger volume of soil; however, they can be more difficult to insert and are more subject to signal loss in soils with clay and higher bulk electrical conductivity (BEC). Manufacturers report SWC measurement errors of 0.02-0.03 m 3 m −3 , while users typically find these to be significantly larger 23 .…”

“…11. Record station metadata, the data behind the data 23 NOTE: Document metadata at installation and each site visit (see Table 1). Consistent metadata reporting supports the growing community of practice and is critical to ensure data and network integrity.…”

Machine learning based estimation of field-scale daily, high resolution, multi-depth soil moisture for the Western and Midwestern United States

“…Previous efforts have also relied on interpreting soil moisture directly from RS products ( e.g ., NASA’s Soil Moisture Active-Passive (SMAP) Mission), which can cover a wide spatial range with relatively fine temporal resolution but is still lacking the finer spatial resolution details needed for decision making ( Moran et al, 2000 ; Hunt et al, 2003 ; Velpuri, Senay & Morisette, 2016 ). Combining high-quality RS datasets, modeling techniques, and in-situ soil moisture measurements from national databases through data fusion can help generate high resolution gridded soil moisture products needed for agricultural monitoring ( Peng et al, 2017 ; Cosh et al, 2021 ); however, land managers are still faced with the difficulty of retrieving and processing data derived from RS products without spending extensive resources on obtaining advanced technical support and expert knowledge. Soil moisture monitoring is particularly challenging for rangeland management considering that ranches commonly encompass a great number of land cover types such as grasses, hay, pasture, and shrubs which are associated with high heterogeneity in soil moisture dynamics.…”