FAQ


How is BasinScout Platform® different than other tools available now? 

The key benefit of BasinScout Platform is the specificity of its recommended actions. Building a watershed-scale or basin-wide restoration program with BasinScout Platform allows you to target the particular fields that can generate the greatest environmental benefit. In a region with hundreds of thousands of acres, you can hone in on the few dozen fields where conservation actions have the most impact. 

BasinScout Platform occupies a niche between high-resolution precision agricultural models/tools and coarse watershed modeling tools like EPA’s SPARROW. The former highlights where, on a given field, specific actions should be taken and is geared toward a single operator looking to maximize efficiency and profit. The latter highlights which watersheds across an entire region are in trouble and is geared toward high-level policy makers. Neither is the right solution for figuring out how to fix a basin that is in trouble.

BasinScout Platform uses field-specific costs and outcomes of best management practice (BMP) implementation scenarios to prioritize sites based on user-specified criteria. For example, the user can specify that they want to prioritize recruitment based on the reduction in groundwater demand achieved per dollar spent on irrigation upgrades, and BasinScout Platform will provide a list of sites where irrigation upgrades are feasible, ranked in order of cost-efficiency for achieving groundwater demand reductions. 


What is the foundation of the BasinScout Platform?

The BasinScout Platform is based on The Freshwater Trust’s BasinScout methodology, which uses a wide variety of data to assess a watershed at a coarse, mid-range or detailed scale. A BasinScout analysis takes into consideration the environmental needs within the watershed, regulatory requirements or policies, current conditions, restoration actions already implemented, and water quality improvement targets. We are able to graphically represent these watershed assessments and further determine the potential for environmental benefit, or “uplift,” at individual parcels and in entire watersheds. Uplift is achieved through implementation of effective conservation actions and further informed by social and financial considerations. Conservation actions for freshwater resources usually focus on reductions in temperature, nutrient or sediment reductions, or restoration of stream flow. Conservation actions for groundwater usually focus on reductions in water usage and increases in infiltration.


How can BasinScout Platform be used for sustainable groundwater management?

Water agencies and groundwater sustainability agencies in stressed groundwater basins are planning for and will need to implement agricultural management practices that achieve local groundwater sustainability targets. The BasinScout Platform can help achieve this goal by providing:

  • Data and insight on current agricultural conditions in the basin.
  • An assessment of region-specific agricultural practices that can improve conditions.
  • An easy way to build and customize an implementation plan, including known costs and benefits, to achieve sustainability targets.

Specifically, the BasinScout Platform can identify and prioritize the location and timing of on-farm projects, such as improvements to irrigation efficiency, winter flooding and cropping practices, to support water budget goals and groundwater sustainability plans.

We are working with groups to create and compare multiple scenarios for increasing stormwater infiltration on agricultural fields that creates both maximum flexibility for growers and maximum availability of water for the entire basin. The result is a decision-support tool that aligns projects focused on agricultural best management practices with the regulatory requirements of California’s Sustainable Groundwater Management Act.


What data are used in BasinScout Platform?

When analyzing an agricultural area to determine current management practices and agricultural attributes at the field level, we use satellite information from a number of government and private organizations. These earth-observation data are paired with historical data for validation.

When translating those current conditions into conservation actions, we use multiple temperature, nutrient, flow and stream function models. These models pull from a variety of datasets, including publicly available data, such as soil characteristics, climate, topography and land use, as well as geospatial data from LiDAR, elevation models and satellites.


How is machine learning used in BasinScout Platform?

Ground-truthed data about agricultural practices (such as when a field implemented cover cropping) is paired with satellite data captured across the same time period. These two pieces of information, “training data” and “input data”, are the building blocks of a machine learning model. When a large volume of these training and input pairs are provided to a machine learning model, it “learns” to relate the satellite data series to the ground conditions. We then provide the machine learning model with a satellite data series, and it can provide us the probability that it represents a certain ground condition. This process is automated, allowing for the rapid evaluation of an agricultural landscape.


What is the advantage of automation?

A trained crop advisor or extension worker can create a conservation plan for a single field in a matter of days using field-level data and field-level models and tools. But what happens when there are 10,000 fields in a basin, each with a variety of potential conservation actions (or combinations thereof)? How do we know which of those fields are in greatest need of the limited time and resources available for conservation planning? By automating the entire analytical workflow — accessing satellite imagery, using machine learning models to turn that imagery into field-level information for thousands of fields, using that field-level information to run environmental and economic models for various scenarios on each field, and comparing the results basin-wide to find where the best opportunities lie — BasinScout Platform makes possible something that previously would’ve taken years.


How accurate are the models and the results?

Uncertainty is inherent in the modeling and simulation of complex natural systems due to the impossibility of perfectly predicting every influencing factor. For example, while BasinScout Platform can use satellite imagery and machine learning to create a snapshot of what is happening on any given agricultural field, it may not be possible to know exactly how much fertilizer was added to that field, when it was added, or in what form it was added. What we can know, however, is how uniformly healthy the crop looks, which can serve as a proxy for nutrient application. This information, combined with information about recommended nutrient application rates for specific crops, the slope of the field, the underlying soil properties, and locally calibrated and validated physical models that describe the cause-and-effect relationships of these systems, we can confidently paint a picture of the specific environmental impacts of agricultural practices at the field-level.

Moreover, BasinScout Platform is intended to serve as a general roadmap for watershed restoration planning, highlighting the highest risk fields and the actions that are likely to create the biggest positive impact for the lowest cost. As the plan develops, the user may want to refine certain aspects of the input data being used to generate it. For the next iteration of BasinScout Platform, users will be able to update field attributes, re-run environmental and cost models, and re-generate basin plans to improve their confidence in the plan being created.


How are specific field-level recommendations determined?

Working from each field’s current condition, BasinScout Platform determines which BMP or combination of BMPs can be feasibly implemented on each field within the region. BasinScout Platform simulates implementation of each BMP individually, then it simulates every feasible combination of BMPs. This approach ensures that the positive and negative interactions between practices are fully captured. Natural systems are extremely complex, and the way two actions affect one another are highly dependent on the broader cropping and management system they are being applied to.

When creating different scenarios, BasinScout Platform provides the user with the estimated field-specific change in irrigation demand, shallow infiltration, runoff volume, and sediment and nutrient losses. The field-specific economic costs and benefits of implementing the feasible BMPs are also calculated.


What insight is derived from the data?

By combining the specificity of field-scale models with the broader contextual evaluation of a watershed-scale analysis, BasinScout Platform can not only provide insight into what environmental actions can be taken on each field in the basin, but it also compares the cost-effectiveness of every action, and identifies which actions on which fields will allow you to meet your uplift targets at the lowest possible cost. The result is an actionable roadmap that identifies the best ways of making a difference for the watershed.

For example, a wastewater utility was able to winnow 2,200 parcels of land down to 40 key parcels, representing 6,500 acres of prioritized habitat area where recycled water could be applied for maximum environmental benefit.