The Upper Feather River Watershed is one of California’s regions of highest precipitation. Its runoff provides the majority of water delivered by the State Water Project, an average 3.2 million-acre feet each year feeding into Lake Oroville.
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.
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.
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.
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.
Next Generation Stream Gaging
New Technologies for Mapping Surface Soil Moisture Over Wildfire-Prone Landscapes
Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California
Improving Forecasting for California's Snow Melt Water Supply
Development of Precipitation-Runoff Modeling System (PRMS) for the Yuba River Basin, Northeastern California, with application for streamflow predictability and flood forecasting
Experiences in LP-IoT: EnviSense deployment of remotely reprogrammable environmental sensors
The basin characterization model—A regional water balance software package
A multi-scale soil moisture monitoring strategy for California: Design and validation
Runoff Estimates for California
Streams, rivers, lakes and reservoirs are important natural resources for irrigation, public supply, wetlands and wildlife. Excess precipitation that flows into these sources is called runoff, and it's an important drought indicator. The California Water Science Center tracks both monthly and annual runoff.
- Overview
The Upper Feather River Watershed is one of California’s regions of highest precipitation. Its runoff provides the majority of water delivered by the State Water Project, an average 3.2 million-acre feet each year feeding into Lake Oroville.
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.
Map of Upper Feather River Watershed Study Area (click to enlarge) 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.
LoRa-cellular gateway (left) at Beale Air Force Base (AFB), non-contact stage sensor with EnviSense data logger/transmitter (right) at Upper Blackwelder Lake, Beale AFB 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.
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. 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.
- Science
Next Generation Stream Gaging
USGS scientists and partners have developed and deployed a low-cost, low-power stream gage system that could meet California’s next generation water needs. The system is now in experimental deployment in Sonoma County, addressing post-wildfire runoff threats and is being developed for the Upper Feather River watershed in northern California - a primary source of the state's water supply. This...New Technologies for Mapping Surface Soil Moisture Over Wildfire-Prone Landscapes
A partnership between the USGS, Pepperwood Preserve, and Black Swift LLC aims to map soil and fuel moisture over wildfire-prone landscapes.Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California
Soil moisture is a critical variable for understanding the impacts of drought on ecological, hydrological, and agricultural systems, as soil moisture content has a direct affect on runoff amounts. Runoff occurs as the result of precipitation (both rainfall and snowfall) that is in excess of the demands of evaporation from land surfaces, transpiration from vegetation, and infiltration into soils...Improving Forecasting for California's Snow Melt Water Supply
California's Sierra Nevada snowpack accounts for much of the water supply in many parts of the state. The snowpack retains large amounts of water in the winter that is then released as temperatures rise in the spring and summer. The snowpack also keeps the Sierra soil moist by covering it longer into spring and summer. Soil moisture influences the onset of wildfires, as well as wildfire prevalence...Development of Precipitation-Runoff Modeling System (PRMS) for the Yuba River Basin, Northeastern California, with application for streamflow predictability and flood forecasting
Reservoirs in the Yuba River Basin are operated by the US Army Corps of Engineers (USACE) as part of the Feather-Yuba Forecast Coordinated Operations Program, and play an important role in flood management, water quality, and the health of fisheries as far downstream as the Sacramento-San Joaquin Delta. The basin has been developed for hydropower and irrigation diversions, so that measured... - Multimedia
- Publications
Experiences in LP-IoT: EnviSense deployment of remotely reprogrammable environmental sensors
The advent of Low Power Wide Area Networks (LPWAN) has improved the feasibility of wireless sensor networks for environmental sensing across wide areas. We have built EnviSense, an ultra-low power environmental sensing system, and deployed over a dozen of them across two locations in Northern California for hydrological monitoring applications with the U.S. Geological Survey (USGS). This paper detAuthorsReese Grimsley, Mathieu D. Marineau, Robert A. IannucciThe basin characterization model—A regional water balance software package
This report documents the computer software package, Basin Characterization Model, version 8 (BCMv8)—a monthly, gridded, regional water-balance model—and provides detailed operational instructions and example applications. After several years of many applications and uses of a previous version, CA-BCM, published in 2014, the BCMv8 was refined to improve the accuracy of the water-balance componentsAuthorsLorraine E. Flint, Alan L. Flint, Michelle A. SternA multi-scale soil moisture monitoring strategy for California: Design and validation
A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐mAuthorsJennifer Curtis, Lorraine E. Flint, Michelle A. Stern - Web Tools
Runoff Estimates for California
Streams, rivers, lakes and reservoirs are important natural resources for irrigation, public supply, wetlands and wildlife. Excess precipitation that flows into these sources is called runoff, and it's an important drought indicator. The California Water Science Center tracks both monthly and annual runoff.
- Partners