As we face today's large-scale agricultural issues, the need for robust methods of agricultural forecasting has never been clearer. Yet, the accuracy and precision of our forecasts remains limited by current tools and methods. To overcome the limitations of process-based models and observed data, we iteratively designed and tested a generalizable and robust data-assimilation system that systematically constrains state variables in the APSIM model to improve forecast accuracy and precision. Our final novel system utilizes the Ensemble Kalman Filter to constrain model states and update model parameters at observed time steps and incorporates an algorithm that improves system performance through the joint estimation of system error matrices. We tested this system at the Energy Farm, a well-monitored research site in central Illinois, where we assimilated observed in situ soil moisture at daily time steps for two years and evaluated how assimilation impacted model forecasts of soil moisture, yield, leaf area index, tile flow, and nitrate leaching by comparing estimates with in situ observations. The system improved the accuracy and precision of soil moisture estimates for the assimilation layers by an average of 42% and 48%, respectively, when compared to the free model. Such improvements led to changes in the model's soil water and nitrogen processes and, on average, increased accuracy in forecasts of annual tile flow by 43% and annual nitrate loads by 10%. Forecasts of aboveground measures did not dramatically change with assimilation, a fact which highlights the limited potential of soil moisture as a constraint for a site with no water stress. Extending the scope of previous work, our results demonstrate the power of data assimilation to constrain important model estimates beyond the assimilated state variable, such as nitrate leaching. Replication of this study is necessary to further define the limitations and opportunities of the developed system.
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http://dx.doi.org/10.1016/j.scitotenv.2022.153192 | DOI Listing |
Sensors (Basel)
December 2024
Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
Understanding the factors that contribute to slope failures, such as soil saturation, is essential for mitigating rainfall-induced landslides. Cost-effective capacitive soil moisture sensors have the potential to be widely implemented across multiple sites for landslide early warning systems. However, these sensors need to be calibrated for specific applications to ensure high accuracy in readings.
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December 2024
PROEPLA, Higher Polytechnic School of Engineering, Campus Terra, Universidade de Santiago de Compostela, 27002 Lugo, Spain.
Weather and soil water dictate farm operations such as irrigation scheduling. Low-cost and open-source agricultural monitoring stations are an emerging alternative to commercially available monitoring stations because they are often built from components using open-source, do-it-yourself (DIY) platforms and technologies. For irrigation management in an experimental vineyard located in Quiroga (Lugo, Spain), we faced the challenge of installing a low-cost environmental and soil parameter monitoring station composed of several nodes measuring air temperature and relative humidity, soil temperature, soil matric potential, and soil water content.
View Article and Find Full Text PDFSensors (Basel)
December 2024
CommSensLab-UPC, Universitat Politècnica de Catalunya-BarcelonaTech, 08034 Barcelona, Spain.
Interferometric radiometers operating at L-band, such as ESA's SMOS mission, enable crucial Earth observations providing high-resolution measurements of soil moisture, ocean salinity, and other geophysical parameters. However, the increasing electromagnetic spectrum utilization has led to significant Radio Frequency Interference (RFI) challenges, particularly critical given the sensors' fine temperature resolution requirements of less than 1 K. This work presents the hardware implementation of an advanced RFI detection and mitigation algorithm specifically designed for interferometric radiometers, targeting future L-band missions.
View Article and Find Full Text PDFPolymers (Basel)
December 2024
Hunan Mine Carbon Sequestration and Sink Enhancement Engineering Technology Research Center, Changsha 410151, China.
As is widely accepted, cumulative strain and improvement mechanisms of stabilized soil are critical factors for the long-term reliable operation of expressways and high-speed railways. Based on relevant research findings, xanthan gum biopolymer is regarded as a green and environmentally friendly curing agent in comparison to traditional stabilizers, such as cement, lime, and fly ash. However, little attention has been devoted to the cumulative strain and improvement mechanisms of soil reinforced by xanthan gum biopolymer under traffic loading.
View Article and Find Full Text PDFPlants (Basel)
December 2024
Botany Unit, Faculty of Pharmacy, Complutense University of Madrid, 28040 Madrid, Spain.
The relationships between environmental characteristics and species richness in the grasslands of the Colombian Orinoquia are presented and analyzed using an ordinal logistic regression model. Ordinal and scale covariates were included, and their bivariate significance was assessed using Spearman's rho and Kendall's Tau-b. The covariates that showed statistical significance with the weighted richness thresholds (WRT) and defined the model were the soil depth and the soil moisture regime, both of which had positive correlations.
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