Precision Ag vs. Hydrology: Different Problems, Same Solutions

Precision agriculture has provided farmers with a multitude of tools to manage and optimize crop production. However, there are many different approaches out there to do the same thing, which at the end of the day creates a lot of conflicting information and ideas. So how can we distinguish the signal from the noise at the end of the day? One approach is to look at other disciplines to see how they have handled common problems.

Meet Phillip Harder, Research Director and Hydrological Scientist
Before I started at Croptimistic, I spent 16 years doing academic hydrological research (in different roles from grad student to research associate at the University of Saskatchewan) so it’s been fascinating to explore some of the common challenges faced by both the precision ag industry and the hydrological research community. Here are a few key items that I’ve learned:

1. People Use The Tools They Know

There are many different hydrological models that have different purposes, but hydrologists used the models that they were familiar with or were developed by themselves or their colleagues. Therefore, a lot of hydrological research may be based on using the most convenient model (tool) rather than the best one for the job. Humans tend to stick to habit and often run out of time to try new things, so we often end up using the same tools that we know. There is value in using tools that you know well, but that does not mean that you should use a high lift farm jack for everything. All tools, whether they are hydrological models or precision ag approaches, have a built-in bias to solve a particular problem. We need to be careful not to apply tools outside of their intended use so that we don’t inadvertently end up with broken jaws.

Case Study: How hydrologists make their choice of model (Addor and Melsen, 2019)

2. Quantifying Spatial Variability in Landscapes

The goal of quantifying spatial variability may vary (hydrologists want to know how much streamflow a basin will produce whereas a farmer is more interested in how a crop will respond to specific management actions), but in the end it’s the same question. In practise this leads to differences in approaches like grid versus zone-based management strategies in precision agriculture (Figure 1), which are similar to fully distributed and hydrological response unit-based approaches in hydrology (Figure 2). A hydrological response unit (HRU) is an area of equivalent hydrological response defined by landscape and soil attributes. A grid or fully distributed approach often treats the landscape as a grid/raster at a high resolution and every location/grid point needs to have data.

Figure 1 shows a SWAT MAP with a 2-acre grid superimposed on top and it is apparent that this level of gridding does not approach the resolution needed to capture the spatial patterns of the SWAT MAP. A gridded representation of a watershed (bottom left in Figure 2) has significantly more grid elements, which break the landscape up into squares and which all need numbers, versus an HRU equivalent representation which only needs a single set of numbers for each HRU that align with the landscape elements (bottom right in figure 2). In the SWAT zone delineation process we are using the interpretation of electrical conductivity and topographic data, to produce the HRU equivalent but in this case for areas of consistent and stable SWAT properties that will affect crop productivity in similar ways.

There is a long-standing debate in how to think about and divide a landscape in hydrology that reflects what is happening in many precision agriculture discussions. Is the uncertain and indirect information found everywhere (e.g., remote sensing of NDVI) valuable enough to make better decisions as opposed to detailed point scale observations that are required for each grid point?

Figure 1: SWAT zone representation of a field with a 2-acre grid superimposed over top in black lines.




Figure 2: Representation of a watershed that defines hydrological response units (bottom right) from the intersection of land use, soil type, slope and sub basins data layers and the equivalent gridded representation (bottom left) (Figure from Johnson et al 2023).

3. Making Decisions Amid Uncertainty

The underlying question in this landscape representation debate is, how can we make good decisions when everything is uncertain? Hydrologists have some experience with this. We often have insufficient information and limited data for every variable, and sometimes we need to provide answers in data-scarce situations (a common hydrological example is the prediction of streamflow in an arctic river where there are no stream gauges or weather stations for thousands of kilometers). The same challenge occurs in agriculture, where measuring every relevant soil and fertility variable at every 0.25m grid cell, for every 10 cm soil layer depth, over a field is not economically feasible, but we still want to spatially adjust our inputs to optimize production. So how can we improve our decisions with incomplete information?

There are two primary approaches to do this in hydrology:

1. Empirical Models: A hydrologist puts together a conceptual or statistical model of how a hydrological system works and then defines factors to describe the interactions. There is no requirement for any of this to be connected to reality, because with enough data, anything can be calibrated to give a “good” answer. This is a data-driven approach that assumes that the available data can capture all the variability and relationships of interest. The problem is that this approach may not work when conditions are outside the range of the calibration datasets. This is the typical case where correlation works well, but correlation does not imply causation.

Just because some predictor (like NDVI) shows a correlation with the four years of yield data that we may have, it does not mean that the next year will have the same spatial pattern in yield. For example, we may get a drought where the kochia thrives while the crop fails. Our remote sensing NDVI, that cannot differentiate between kochia and crop, will not capture the significant yield drop.

2. “Process-Based” Approach: I will state my bias that this is my preferred option. Basically, in this approach, we try to go back to first principles and build a model to focus on physical processes (things that can be described by physics) that we know are true. So, using the same Kochia example, if we know from our SWAT MAP the water holding capacity of a SWAT zone (Figure 3) and weather conditions, we can calculate the amount of crop available water with the SWAT WATER model. Because crop water use efficiency is relatively stable, we can more realistically anticipate the yield in year 5, even if we do not have any data for similar weather conditions. Not only can we better anticipate and manage for a different outcome, but we will be able to understand why this is occurring which is information to help us do better next time.

Figure 3: Spatial variability of the soil field capacity from SWAT WATER (left), yield (middle), and NDVI (normalised difference vegetation index).

The SWAT MAPS Approach

We can learn from the similarities between hydrological and precision ag challenges. We should use tools that are suitable for our challenges, not just familiar ones, and base our decisions on process-level understanding, not more irrelevant data. The SWAT MAPS approach follows this principle. It is true that "you can't manage what you don't measure", but we also need to avoid "managing what we measure". Yield is the final agronomic goal, but we do not manage yield directly. NDVI shows biomass patterns, but it may not relate to yield, so we can be led astray. What we manage are inputs, and how their response potential varies with soil, water, and topography. So, focusing on the static soil properties that SWAT MAPS use, and managing them accordingly, gives us the process-based understanding to quantify and manage the spatial variability of crop production.

REFERENCES

Addor, Nans Melsen, L.A.. (2019). Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models. Water Resources Research. 10.1029/2018WR022958.

Johnson et al 2023.https://topsoil.nserl.purdue.edu/~flanagan/erosymp2023/Presentations/23507-Billy_Johnson.pdf

Understanding Terms Used to Discuss Soil Moisture Variability

Introduction

Water is the physical mechanism by which plants take up nutrients. Water is the mechanism through which nutrients are extracted from the soil and relocated to where the plant needs it most – roots, stalk, leaf, flower, and seed. Once present, water becomes the way in which roots can extend to access more moisture and additional nutrients found deeper in the soil. It is a balancing act of right moisture conditions resulting in optimum growth, deeper roots, more moisture – and the cycle continues. Considering the importance of water and the increase in short- and medium-term droughts in agriculture – what can growers do to manage effectively for soil moisture variability? Better understand your soil moisture variability across your field and through the season.

Soil Moisture Definitions

Volumetric moisture content, available water, plant available water, soil texture, permanent wilting point, temporary wilting point as well as a host of units mm, mm/m, %, mm/unit depth etc. are all terms that can become quite overwhelming.

In the development of SWAT WATER, a product of SWAT MAPS, the objective has been to provide three relatively simply datasets for users to interpret and drive management decisions e.g., how can my variable rate fertilizer application be adjusted to account for soil moisture variability. Volumetric Moisture Content (VMC), Plant Available Water (PAW) and Days until Wilting Point were developed to provide SWAT WATER users with an indication of when and where a crop is going to show moisture related stress.

Volumetric Moisture Content (VMC)

The Manitoba Department of Agriculture uses a fantastic “gas tank” analogy to describe soil moisture. In simple terms how much fuel is stored in your gas tank right now, is a very simple way to understand soil moisture.

  1. Saturation – your tank is overflowing.
  2. Field Capacity – your tank is full; add anymore fuel and it will overflow.
  3. Temporary Wilting Point – your fuel warning light is on.
  4. Permanent Wilting Point – Your tank is empty.

In simple terms volumetric moisture content (VMC) is the level of your gas tank right now. This could be any one of the levels described above or somewhere in-between, which is normally the case.

Plant Available Water (PAW)

For agricultural crops, the volume of water that is of most importance is the moisture that the crop can access and use. Using the fuel tank analogy, if you were to put a sponge into your fuel tank, your car would only be able to use the fuel that is liquid. Once the tank is empty, any fuel absorbed by the sponge cannot be used by your car.

  • Available Water – In simple terms this would be the current level of fuel in your tank, less the amount of fuel that is held by the sponge and cannot be accessed by your car. In agricultural crops, this is commonly referred to as Plant Available Water (PAW). In the same way as fuel held by the sponge cannot be used by your car, soil particles hold onto some soil moisture so tightly that it cannot be accessed by the crop.

Plant Available Water, in simple terms, is the total volume of fuel in your cars tank less the amount that your car cannot access in the sponge. If you were to squeeze the sponge in your fuel tank – there would be a certain amount of fuel that would come out. In soils this point is described as the Permanent Wilting Point (PWP) i.e., there is fuel/water but because it is held under pressure by the sponge(soil) your car (crop) cannot access it. This amount of fuel/water needs to be ignored and cannot be used.

Volumetric Moisture Content (VMC) includes the amount of fuel/water held in the sponge/soil; Plant Available Water (PAW) excludes the water that the crop cannot access. As you can see – the most important dataset for crop production is Plant Available Water (PAW) as this is the moisture that drives yield or productivity.

Soil Variability (Texture)

Using the gas tank analogy, soil variability affects how large the tank is, and how many sponges are in it. In simple terms, although the fuel tanks may hold the same amount of fuel, there will be more fuel withheld by the tank with five sponges then the tank with one sponge. Ultimately your soils sand, silt and clay percentage behave much like a sponge does in your fuel tank.

Sand – A high sand percentage is like having a small fuel tank but no sponges in the tank. In other words when the tank is empty there is no or very little fuel/water withheld.

Clay – A high clay percentage is like having a large fuel tank with lots of sponges in the tank. Although we all know there is fuel in the tank, because of the number of sponges there will always be a fair amount of fuel in the tank that your car/crop cannot access.

The illustration above shows how different sand silt and clay percentages affect how much water is freely available to your crop. As you can see clay soils tend to hold a large amount of water but much of this water is held in the sponge/soil and cannot be accessed by the crop. At the other end of the soil spectrum, sandy soils hold very little water even when they are overflowing or saturated. A soils sand, silt, and clay percentage acts much like a sponge or several sponges in your cars fuel tank.

Understanding Soil Moisture Variability – Why it Matters?

Applications of the SWAT MAPS variable rate technology has shown that Zone 1s, which are generally made up of coarser textured soils, tend to store less water and stress more often, while Zone 8 through 10 tend to stress more from too much water. Interestingly Zone 1s are quite frequently low on potassium (K) and almost always low on Sulphur (S), while the opposite is true for Zones 8-10. Hydrology plays a significant role on Sulphur distribution in your field. Being a mobile nutrient, water collecting areas in a field can typically have high Sulphur levels, while water shedding areas are often deficient. Drought prone parts of your field can, through variable rate applications of Sulphur, be managed to provide your crop with appropriate nutrition, sufficient to mitigate the impact of soil moisture stress.

A fair amount of research suggests the importance of potassium (K) and magnesium (Mg) in reducing plant stress associated with drought in wheat. Results from European research trials in wheat, included in the chart below, which compared potassium fertilization in a wet season compared to a dry season, show a 20% to 40% yield loss difference between dry and wet years for the same soil, depending on the rate of potassium applied.

The chart below illustrates estimated yield loss due to potassium limitations in wheat trials undertaken by the Institute of Plant Nutrition – Faculty of Agricultural Sciences Goettingen.

The current research suggests that plants, not limited in potassium, can store excess carbohydrates in the stem of the plant for energy use later in the season. In the event of moisture stress, the plant can access these stem reserves to continue growth and in so doing limit the effect of moisture stress on yield. Potassium shortages have also shown shallower rooting depths which would have the effect of increasing drought stress. In a similar way Sulphur (S) has been shown to improve crop recovery after a drought event. Keeping in mind that soil moisture is quite often available at depth, but your crop needs to be given the opportunity to get its roots down into the plant available moisture.

Secondary to a fertility program that increases your crops’ ability to manage water stress and still yield appropriately is the consideration that denitrification is significantly increased in those parts of your field that are poorly drained or are wet. The SWAT MAPS process has often identified these areas to be found in areas with high clay content. In fact, the relationship between sand, silt and clay content is a significant driver of soil moisture variability and as a result should be a key consideration in any variable rate fertility program. The SWAT WATER program allows farmers to easily identify soil variability by the SWAT MAP Mapping process but secondly measure and provides tools to monitor soil moisture conditions, crop stress point and days to wilting point at 4 rooting depths. These tools provide the grower with a mechanism to apply split applications of nitrogen applications in locations that have high soil moisture content and or are poorly drained. Considering that nitrogen fertilization rates are a major economic as well as ecological consideration, applying the right rate in different parts of the field is key to reducing economic losses through overapplication and potential leaching, without compromising on yield.

References

Franzen, D., & Grant, C. A. (2008). Sulphur response based on crop, source, and landscape position. Sulphur: A missing link between soils, crops, and nutrition, 50, 105-116. 

Panhwar Q A, Ali A, Naher U A & Memon M Y (2019). Organic Farming – Global Perspectives and Methods. Chapter 2 – Fertilizer Management Strategies for Enhanced Nutrient Use Efficiency and Sustainable Wheat Production, 17 – 39.

Manitoba dept of Agriculture. Agriculture – Soil Management Guide, Water Use and Moisture Management. Accessed 6 July 2021 https://www.gov.mb.ca/agriculture/environment/soil-management/soil-management-guide/water-use-and-moisture-management.html

Metwally. S. Y, Pollard A. G. (1959) Journal of the Science of Food and Agriculture/ Volume 10, Issue 11. Effects of soil moisture conditions on the uptake of plant nutrients by barley and on the nutrient content of the soil solution. P 632 – 636. https://doi.org/10.1002/jsfa.2740101109

Precision Soil Moisture Management: SWAT WATER

February 9, 2021 – Naicam, Saskatchewan – The newest development in leading-edge variable-rate technology is here: SWAT WATER maps for precision soil moisture management. Croptimistic Technology has developed this technology due to demand for better understanding soil moisture variability relative to Soil, Water, and Topography (SWAT) MAPS.

Croptimistic is an international AgTech company that provides SWAT MAPS, a turn-key variable rate process that prioritizes Soil, Water, and Topography factors of fields for the creation of management zones. The all-new SWAT WATER platform will enable the agriculture industry to manage soil moisture variability spatially (by field zone), vertically (through soil profile), and temporally (over time). Additionally, SWAT WATER integrates field surface hydrology, including drainage paths, depressions, and flow accumulation pathways, plus subsurface hydrology. The result is a soil moisture management tool that provides a complete indicative measurement of soil moisture conditions throughout the crop rooting zone. This new tool promises to provide critical information throughout the growing season for crop management decisions such as nitrogen top-dressing, fungicide applications, or variable-rate irrigation.

Jack Seitz, VP of Sales at Croptimistic, says, “SWAT WATER offers growers and their consultants a tool that can be used to guide management decisions for any agricultural practice governed by changes in soil moisture across a field or farm. SWAT WATER provides tremendous value as a risk management and decision-making tool for understanding when and where to top-dress based on changes in soil moisture over time as well as the opportunity for variable-rate irrigation.”

A recorded version of the SWAT WATER launch can be viewed on YouTube at https://www.youtube.com/watch?v=HQr9dc0X19c.

Managing Spatial and Seasonal Soil Moisture Variability with SWAT WATER

Farming in dryland conditions is for the most part governed by the quality and variability of the soil in your field. Good soils, with high organic matter, mitigate both nutrient and moisture stress by buffering the crop against very wet and very dry seasons. The challenge for most growers is understanding where the good areas are versus the poor areas and more importantly, understanding this in the context of the current season’s climatic conditions. For example, wet years may result in areas that produce poorly due to excess moisture, while these same areas may be the most productive in dry years.

Figure 1: Crop stand variability linked to soil moisture variability.

Variable rate technology, such as SWAT MAPS, provides the perfect platform for mapping spatial variability. An understanding of the dynamic nature of soil moisture in response to topography, soil physical characteristics (e.g. texture), crop moisture demand (e.g. crop stage and type) and associated climatic conditions can further guide management decisions with regards to seeding rates and/or fertilizer applications and pest and disease control. For example, topdressing only those locations with yield potential above the estimated/forecast yield potential provided for the fertilizer prescription. The opposite effect would be in wet years, not fertilizing saturated parts of the field in which there is little or no crop due to excess moisture.

Leveraging the SWAT MAPS variable rate technology, Croptimistic Technology Inc. has developed SWAT WATER, a zone-based soil moisture balance aimed at providing volumetric moisture content (VMC) and crop available water daily. SWAT WATER maps enhance SWAT MAPS by incorporating field hydrology such as overland flow characteristics, by identifying which areas will pond and for how long, as well as soil physical characteristics and soil moisture probe data.

Figure 2. Soil moisture variability associated with changes in physical properties (e.g. soil texture).



Figure 3. The purple areas depict flow accumulation lines, extracted from the field-based topography data.



Figure 5: Soil moisture changes over time based on the SWAT WATER model.

For growers, one of the questions which is repeatedly asked is “where should I place my soil moisture probe?" The SWAT MAPS process provides a platform off which probe installations can be guided to ensure the data obtained from soil moisture probes is relevant to the soil and moisture variability of the field. By guiding this process, the SWAT WATER maps are effectively “ground truthed” and soil moisture probes are more effectively used to understand not just a single location, but the relevance of that location to the rest of the field and all zones within a field.

Figure 6: SWAT WATER, zone-based soil moisture balance relative to probe measurements.

Figure 7: Zone-based soil moisture variability relative to zone-based soil moisture probe measurements.

Water is a critical element in steering decision making as it underpins several drivers of crop yield e.g. salinity, organic matter, pest and disease locations, nutrient availability, and nutrient efficiency. Not all the water held within the soil column is available to plants. While SWAT MAPS provides an excellent perspective on intra field variability, SWAT WATER adds tools relevant to the availability of water within the soil column and the changes in the soil moisture availability over time. With the addition of SWAT WATER, agronomists and famers are empowered with tools to understand if and where soil moisture is optimal for plant growth.

It All Comes Down to Water

Water: it’s the critical element for all plant life and I’ve realized over the past 18 months that it is perhaps the most important of the three pillars of a soil, water, and topography map (SWAT MAP). This isn’t meant to minimize the importance of soil and topography, as they are not mutually exclusive! Topography affects water flow - in other words, where water sheds and where it collects. Soil texture and organic matter affect the total soil water holding capacity as well as actual plant available water (which are two different things!), so all three are working simultaneously to affect water and crop variability.

I’ve started to say that everything relates back to water in some way, and here’s some examples:

1. Salinity. To quote soil scientist Les Henry, “Salinity is not a salt problem, it’s a water problem.” Bang on: there are several different types of salinity, but they are all caused by water in some way, whether its subsoil water coming out the side of a hill as a seep, a high water table near the surface causing “bathtub ring” salinity, or some other mechanism causing salinity. If you want to understand more about salinity, I highly recommend reading Les’s book, “Henry’s Handbook of Soil and Water.” It’s easy to read, entertaining, and educational.

2. Organic matter. While some variability in organic matter has certainly occurred over the last century or more due to cultivation and subsequent erosion of topsoil, even mother nature creates differences in organic matter percent and the depth of topsoil that is rich in organic matter. This is often related to long-term (and when I mean long-term I’m talking 1000’s of years) productivity of the landscape position and soil. Think about it as many little soil climatic zones within a square mile, with knolls being dry and always having grown less native grass than lower slope positions that get water runoff from the hill. We also see dramatic changes in organic matter in western Canada as we go north into what we call the grey-wooded soil zone, where soils that were developed under tree cover (luvisols) have less organic matter than soils developed under grasses (chernozems).

Figure 1. Example of typical zone soil test values.

3. Phosphate. Like organic matter, there is a lot of variability in soil phosphate created from decades of farming and erosion, but phosphate is also always moving downslope with water as dissolved P in snowmelt runoff and heavy rains. Water movement also causes particulate-P (phosphate attached to soil particles) to move downslope as well. This movement occurs in both zero-till and conventional till farming systems, although zero-till at least limits particulate-P movement that comes with soil erosion.

4. Sulphur, chloride, and boron. Three of the four mobile nutrients are clearly influenced by water in SWAT soil test data, having some of the most consistent trends of any nutrients no matter what region they are from. We consistently see higher levels of these nutrients in lower SWAT zones (wettest zones) due to higher mineralization rates – again, driven by water – as well as dissolved nutrients moving with water. Choride and sulphur are associated with salts so these nutrients often test in the 1000s of ppm when there is any salinity in zone 10. On the other end of the spectrum, the zone that is often most deficient in these nutrients is zone 1, where mineralization is relatively low and these nutrients leach away.

5. Nutrient use efficiency. Whether nutrient uptake in the root is through mass flow movement with water or by diffusion, water is required. This gets a lot more complex, but to keep it short it is evident to all SWAT agronomists that in areas of the field where water is “just right”, nutrient use efficiency is far better than areas that are always too wet or too dry. In other words, you don’t necessarily need to apply the same amount of nitrogen per bushel of target yield in SWAT zone 5 than you would in zone 1 where it's too dry or zone 10 where it's maybe too wet.

In summary, integrating water into a good management zone map is critical to the success of VR nutrients and seed. A SWAT MAP does this in several ways by delineating zones based on things like topography, soil texture, and integrating water flow paths into the final map. And it’s exactly what gave me my “ah ha” moment 18 months ago when I started working with SWAT MAPS.

If you're dealing with issues on your farm due to any of the water-related examples listed above, consider investing in SWAT MAPS. There is no map that is better equipped for proper zone management than SWAT MAPS. Please contact us if you are interested in this valuable service.