What Does SMAP Mean for In Situ Soil Water Content Measurement?
With the recent news coverage of the SMAP (Soil Moisture Active Passive) satellite launch, researchers may wonder: what does remote sensing mean for the future of in situ measurements? We asked two scientists, Drs. Colin Campbell and Chris Lund, for answers to this complex question. Here’s what they had to say:
What is SMAP?
SMAP is an orbiting earth observatory that estimates soil moisture content in the top 5 cm of soil over the entire earth. The mission is three years long with measurements taken every 2-3 days. This will allow seasonal changes around the world to be observed over time, improving our ability to manage water resources and better parameterize land surface models. SMAP determines the amount of water found between the minerals, rocky material, and organic particles found in soil by measuring the ability of radar to penetrate the soil. The wetter the soil is, the less the radar will penetrate. SMAP has two different sensors on the platform: an L band aperture radar with a resolution of about a kilometer when it’s looking straight down (the pixel size is about 1 km by 1 km), combined with a passive radiometer with about 40 km of resolution. This combination creates a synthetic product that takes advantage of the sensitivity of the radiometer.
What does SMAP mean for in situ soil water content measurement?
It’s all about scale: In some ways, comparing in situ to SMAP measurements is like comparing apples to…well…mountain-sized apples. The two forms of measurement use vastly different scales. In situ soil moisture sensors measure water content at the volume of several liters of soil, maximum. Even the sensor with the largest field of sensitivity, the neutron probe, can only integrate a volleyball-sized volume. On the other hand, SMAP measures at a resolution of 1 km2, which is larger than the size of a quarter section, a large field for many farmers. Global soil moisture maps will allow scientists using SMAP to look at big picture applications like weather, climate and hydrological forecasting, drought, and flooding, while more detailed in situ measurements will tell a farmer when it’s time to water, or help researchers discover exactly why plants are growing in one location versus another. The difference in spatial scale makes the two forms of measurement useful for very different research purposes and applications. However, there are applications where the two measurements can be complementary. Most notably, in situ measurements are often temporally rich while being spatially poor. But, SMAP can be used to scale in situ measurements to areas where in situ measurements are absent. In situ measurements can also be used as a source of validation data for SMAP-derived values for any location where both in situ and SMAP measurements overlap. Thus, there is opportunity for synergy when pairing SMAP and in situ measurements.
What can SMAP do that in situ measurement can’t?
Scientists say they’ve seen a relationship between the top 5 cm of soil moisture and some factors related to climate change and weather. Because in situ soil sensors sample across a spatial footprint of a few meters, it can be very difficult to use their data to say anything about processes occurring across broad spatial scales; two liters of soil is not going to tell you anything about weather or flooding. SMAP can help us better understand the interaction between the land surface and atmosphere, improving our understanding of the global water cycle as well as regional and global climate. This will help with forecasting crop yield, pest pressure, and disease…that’s big picture research.
The productivity of a forest also may depend on the general soil moisture measured by SMAP. For instance, if we got an idea of the soil moisture and greenness of a forest, we could tie together the approximate water availability and the resulting biomass accumulation with incoming solar radiation. Better biomass accumulation models could lead to better validation of global carbon cycle models.
SMAP will also be able to detect dry areas across the U.S. and challenges they might present. Surface runoff that leads to flooding could also be predicted as scientists will be able to see where soils reach saturated conditions.
In other applications, people working on global water or energy budgets have to parameterize the land surface in terms of how wet or dry it is. That’s the big advantage of SMAP’s relatively new data sets. Any time you’re running a regional climate model you have to parameterize what the soil moisture is in order to partition surface heat flux into sensible and latent heat flux. If there’s a lot of available water, it’s weighted more toward evaporation and less toward sensible heat flux. In areas where there’s little available water and low evaporation, you get high surface temperatures and sensible heat flux. So SMAP will be important for model parameterization as we haven’t had a good global data set for soil moisture until now.
What can in situ sensors do that SMAP can’t?
In irrigated agriculture, farmers need to know when and how much to irrigate. In situ sensors give them this information by showing how much water was lost from the root zone and what is still left. SMAP is unable to tell you what’s down in the root zone; it only reaches to 5 cm. Additionally, 1 km resolution is larger than most irrigation blocks. These factors mean that it will be difficult to make irrigation decisions from SMAP alone.
Scientists using in situ sensors are concerned with the soil moisture available in a local area because their time resolution is excellent and they have the ability to resolve what’s happening in particular conditions related to crops or natural systems. Natural systems are often heterogeneous, meaning there may be adjacent areas with different types of vegetation including trees, shrubs, and grass. Tree roots may grow deep while grass roots are shallow. Being able to look over all these different areas without averaging them together, as SMAP does, is critical in some applications.
What about geotechnical applications? Literature suggests SMAP output can help predict landslides. It is more likely that it can only see when the soil is generally saturated and generate a warning. But in slopes that are at risk of landslides, in situ monitoring with sensors such as tensiometers to measure positive pore water pressure may be more useful for determining when a slide is imminent.
SMAP, like in situ water content measuring systems, is also limited by the fact that it measures the amount, not the availability, of water. If it measures 23% water content in a certain area, that measurement may not tell us what we want to know. A clay soil at 23% VWC will be close to wilting point while a sand would be above the plant optimal range. SMAP doesn’t measure the energy status of water (water potential), so even if SMAP tells us a field has water content, that water might not be readily available. Water availability must be determined through a pedo-transfer function or moisture release curve appropriate for a specific soil type (It is possible to overlay SMAP data on soil type data to estimate energy state, but this might not be fine enough resolution to be useful).
How do SMAP and in situ instruments work together? The key is ground truthing in situ soil moisture measurements with SMAP type satellites and vice versa. Ground-based measurements at specific locations can be matched with satellite information to extrapolate over a field and gain confidence in the small continuous scale alongside the larger infrequent scale. It’s analogous of a video camera recording one plant continuously while a single shot camera snaps whole-field pictures every day. With the SMAP “single-shot” we can say, something changed from time A to time B, but we don’t know what happened in the middle (rain event, etc.). In situ measurements will tell us the details of what happened in between each snapshot. Putting both data sets together and matching trends, we can show correlation and complete the soil moisture picture. Basically, In situ measurements provide temporally rich information about soil moisture from a postage stamp-sized area of earth’s surface (driven by highly localized conditions), whereas SMAP gives us the ability to monitor broad scale spatiotemporal patterns across all of earth’s surface (driven by synoptic conditions).
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