Monitoring and modeling soil moisture to improve runoff forecasting and drought characterization in the Feather River Basin Active

Drought, along with recent wildfires, have had enormous impacts downstream on water quantity and quality. These conditions have greatly impacted the agriculture and the residents of the nearby Central Valley.

For decades, snowpack measurements have been used as a fairly reliable metric to forecast runoff into California reservoirs which store water for later use during the dry summer months. However, after multi-year droughts, it’s believed that dry soils absorb much of the snowmelt before it can runoff into rivers and reservoirs. To confirm this, the USGS in cooperation with DWR has initiated a new study to investigate the role of soil moisture conditions on runoff and attempt to improve reservoir predictions with combined monitoring and modeling.

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One area affected by these dynamics is the Upper Feather River Watershed (UFRW) in Northern California. Unfortunately, there is a lack of soil moisture data being gathered in the UFRW. According to the National Soil Moisture Network, of the 310 soil moisture sensors located in California, none are located in the UFRW.

Expanding monitoring and modeling of both surface water and soil moisture in the UFRW would provide insight into how much snowmelt is being absorbed into the soil. The data gathered will also feed into a watershed model to enhance early drought warning and improve forecasts of runoff into reservoirs. To address this need, the USGS will install soil moisture monitoring (SMM) stations and water-level sensors in the UFRW.

Measuring soil moisture in the UFRW can improve water availability forecasts in both snow-dominated and rainfall-dominated areas. The watershed experiences both mixed rain-snow events and rain-on-snow events. The rain-snow transition zone in the UFRW is also expected to increase due to climate change. In-situ measurements in targeted sub-basins, combined with basin-wide modeling, will improve annual forecasts. The challenge is determining the number and placement of monitoring stations to support basin-wide modeling.
A better understanding of the linkages between soil water storage, drought, and runoff could greatly improve water management and reservoir operations in critical water supply basins in California. Monitoring with soil moisture and streamflow is imperative to collect real-time information, and modeling can be used to extend these point measurements spatially across the watershed. If successful, the sensor network and watershed model in this research could be expanded into other parts of California.

Objectives and Approach

This study will combine in-situ (on-site) monitoring and watershed modeling using the Basin Characterization Model (BCM).
The sensor network used for in-situ monitoring will use a recently developed long-range (LoRa) technology. This will be used to connect with cellular and satellite uplink sites. In addition to its other advantages, this technology will reduce the cost of real-time monitoring.

The project will be divided into four tasks to be performed during federal fiscal years 2022-2024.

Task 1. Sub-basin and sensor site selection and network planning
The USGS will design a network of approximately 15-20 real-time, water-level monitoring sites, 25-40 real-time, soil moisture monitoring (SMM) stations, and 8-10 telemetered uplink sites. 

Each site will use an EnviSense data logger/transmitter, recently developed by Carnegie Mellon University in partnerships with the USGS National Innovation Center (Grimsley, and others, 2022). The EnviSense devices use long range (LoRa) radio telemetry to deliver real-time stream height and soil moisture monitoring (SMM) data. The advantage of this type of network is that each site does not require cellular or satellite communications equipment. Instead, sensors transmit locally, by line-of-sight, to a central uplink site. 

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Task 2. Installation of a) SMM and water-level sensors and b) LoRa-cellular and LoRa-satellite gateway (uplink) sites
The SMM monitoring sites will be selected in areas that best represent soil moisture within different parts of the subbasin. These will be determined by factors such as wildfire history, elevation, geology, and the type of precipitation (rain/snow) typically received. The sites will be co-located with streamgage water level monitoring sites. There will be two SMM sites per streamgage site. 

Water level will be monitored using vented pressure transducers. Water depth data and soil moisture data will be collected at adaptive sampling frequencies based on seasons and changes in conditions. Generally, data will be collected and transmitted at 15-minute or hourly intervals. 

Each sensor site will transmit data to an uplink site using LoRa. The data will then be forwarded to the USGS server.

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This image shows how LoRa sensors at various locations send data to the cellular gateway. The effective operating distance from sensor to the gateway is rated at ~20 kilometers.

Task 3. Server and data management, archival, QC, site maintenance
Soil moisture and water-level data will be recorded in the USGS Aquarius (internal) database. This will made publicly available in real-time through the USGS National Water Dashboard. Data quality will be checked in accordance with technical methods and standards published by United States Department of Agriculture, National Soil Monitoring program, and USGS standards for water-level data.

Task 4. Watershed modeling
The statewide BCM will be refined and calibrated to the UFRW to characterize local water balance processes. Collected soil moisture and streamflow data will be used to calibrate the BCM and extend its drought and flood prediction capabilities for the entire watershed.

Deliverables

Deliverables include water level and soil moisture data, watershed model output, and an interpretive report.

• Sensor data (soil moisture, soil temperature, conductivity, and water level) will be made available through either the USGS National Water Dashboard or ScienceBase. 
• The calibrated BCM watershed model, metadata, and output will be archived in a USGS online model repository.
• A report or journal article will present summary of results and findings from the field data collection and watershed model at the send of this study.
• The USGS may also present a summary of results to DWR through an in-person or online presentation. 

Timeline

Preparation for the project began in October 2021. The final deliverables (above) are anticipated in the spring of 2024.