From Field to Model: Determining EROSION 3D Model Parameters for the Emerging Biomass Plant Silphium perfoliatum L. to Predict Effects on Water Erosion Processes
Abstract
:1. Introduction
2. Materials and Methods
2.1. Site Characteristics and Site Management
2.2. Rainfall Simulator Experiment for Model Calibration
- an automated sprinkler to generate and distribute water droplets;
- a tripod to elevate the sprinkler with an adjustable height of up to 3 m;
- a pump to supply the system with water from a tank;
- a water tank supplying the system with water.
2.3. Natural Runoff and Soil Erosion Measurement
2.4. Model Background
2.5. Determining Input Parameters from Experimental Data
2.6. Validation of the Model Performance
2.7. Model Simulation to Explore Management Effects on Soil Erosion Using Experimentally Determined Parameters
- The first “worst case” scenario represents conventional maize cultivation across the entire field. This scenario serves as a baseline for comparison, reflecting typical farming practices for bioenergy cropping.
- In the second scenario, maize would be cultivated without tillage (no-till).
- In a third scenario, established cup plant stands would grow on the test sites.
- The fourth scenario combines conventional maize cultivation with a buffer strip (30 m width) cultivated with cup plant for water retention and soil protection.
- Lastly, the fifth scenario combines no-till maize with the same buffer strip.
3. Results
3.1. Rainfall Simulation for Model Calibration
3.2. Natural Precipitation Events for Model Validation
3.3. Case Study on the Application of Cup Plant Parameters to Model Cultivation Strategies and Their Impact on Soil Erosion
4. Discussion
4.1. Rainfall Simulation for Skinfactor Calibration
4.2. Validation of Skinfactor Values
4.3. Case Study
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Input Parameter | Unit | Data Source |
---|---|---|
Altitude DEM | (m) | Digital elevation model with a resolution of 1 m (Landesamt für Geoinformation und Landesvermessung Niedersachsen LGLN © 2024) |
Soil cover | % | Field measurement |
Bulk density | kg/m3 | Field measurement according to DIN ISO 11272 (available online: https://www.dinmedia.de/de/norm/din-en-iso-11272/263368180 (accessed 2 September 2024)) |
Soil organic carbon content | % | Field measurement according to DIN ISO 10694 (available online: https://www.dinmedia.de/de/norm/din-iso-10694/2799936 (accessed 2 September 2024)) |
Grain size distribution | % | Field measurement according to DIN ISO 11277 (available online: https://www.dinmedia.de/de/norm/din-iso-11277/53934894 (accessed 2 September 2024)) |
Skinfactor | - | Rainfall experiment |
Surface roughness | s/m1/3 | Rainfall experiment |
Initial soil moisture * | % | Field measurement/Parameter catalogue EROSION 3D |
Erosion resistance | N/m2 | Parameter catalogue EROSION 3D |
Rainfall intensity | mm/min | Field measurement (rain gauge) |
Erosion Event | Date | Rainfall Erosivity * (EI30, N/h−1) | Rainfall Intensity (I30, mm/h) | Duration (min) | Rainfall (mm) | Soil Cover (%) | ||
---|---|---|---|---|---|---|---|---|
Cup Plant | Maize No-Till | Maize Conv. | ||||||
E1 | 24 June 2022 | 180.0 | 124.8 | 260 | 64.6 | 95 | 66 | 70 |
E2 | 8 September 2022 | 8.2 | 15.2 | 405 | 27.6 | 5 | 5 | 5 |
September 2022 * | June 2023 | |||
---|---|---|---|---|
Treatment | Skinfactor (-) | Surface Roughness (s/m1/3) | Skinfactor (-) | Surface Roughness (s/m1/3) |
Cup plant | 0.72 | 0.431495 | 11.5 | 0.491129 |
Maize conv. | 0.16 | 0.144314 | 1.2 | 0.091000 |
Maize no-till | 0.21 | 0.319425 | 3.6 | 0.120144 |
E1 | E2 | ||||
---|---|---|---|---|---|
Crop | Replication | (Runoff (L); Sediment (kg)) | |||
Observed | Modeled | Observed | Modeled | ||
1 | (455; - *) | (580; 0.2) | (15; 0) | (17; 0) | |
Cup plant | 2 | (413; - *) | (488; 0.3) | (18; 0.012) | (16; 0) |
3 | (-; - *) | (1280; 5.1) | (16; 0.028) | (15; 0) |
Scenario | Sediment Budget per Pixel Cell (kg/m2) | |||
---|---|---|---|---|
Median | Mean | Standard Deviation | Erosion Reduction (%) | |
Maize conv. | −0.4 | −10.5 | 68.2 | - |
Maize no-till | 0.0 | −5.1 | 153.7 | 51.6 |
Cup plant | 0.0 | −0.7 | 23.6 | 92.6 |
Maize conv. + buffer strip cup plant | −0.2 | −9.5 | 68.8 | 9.7 |
Maize no-till + buffer strip cup plant | 0.0 | −4.4 | 131.2 | 58.3 |
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Koch, T.; Aartsma, P.; Deumlich, D.; Chifflard, P.; Panten, K. From Field to Model: Determining EROSION 3D Model Parameters for the Emerging Biomass Plant Silphium perfoliatum L. to Predict Effects on Water Erosion Processes. Agronomy 2024, 14, 2097. https://doi.org/10.3390/agronomy14092097
Koch T, Aartsma P, Deumlich D, Chifflard P, Panten K. From Field to Model: Determining EROSION 3D Model Parameters for the Emerging Biomass Plant Silphium perfoliatum L. to Predict Effects on Water Erosion Processes. Agronomy. 2024; 14(9):2097. https://doi.org/10.3390/agronomy14092097
Chicago/Turabian StyleKoch, Tobias, Peter Aartsma, Detlef Deumlich, Peter Chifflard, and Kerstin Panten. 2024. "From Field to Model: Determining EROSION 3D Model Parameters for the Emerging Biomass Plant Silphium perfoliatum L. to Predict Effects on Water Erosion Processes" Agronomy 14, no. 9: 2097. https://doi.org/10.3390/agronomy14092097