A computer analysis of the flow of water and nutrients in agricultural soils as affected by subsurface drainage
Bibliographic record
Abstract
A computer model was developed in order to determine the effects of drainage practices on nutrient losses from level agricultural soils. The model performs a daily simulation of the vertical flow of water, nitrogen, phosphorus, and heat, and of the growth of crops. A water flow submodel calculates the depth of the water table based on daily predictions of evaporation, transpiration, flow to drains and ditches, and deep percolation. An original saturated-unsaturated flow algorithm is used to determine moisture infiltration, redistribution, and upward flow in the soil matrix, as well as bypassing flow in the soil macropores and horizontal flux between the soil matrix and the macropores, and surface runoff. Nutrient movement occurs by mass flow. Heat flow, nutrient biochemical transformations, and crop growth are determined by using well established relations. Field tests were carried out for a period of two years on an experimental site in the Lower Fraser Valley of British Columbia. The water table depth was measured on a continuous basis. Grab samples of drainwater and observation wells were obtained periodically and analyzed for nitrogen (N0₃-N, NH₄-N, and TKN) and phosphorus (P0₄-P and TP). The field results show a decrease in the concentration of all nutrients over the sampling period, and provide evidence that denitrification and bypassing flow are important mechanisms affecting the nutrient balance of this soil. These results were used to calibrate the model. An excellent fit of the observed water table profile and an adequate fit of the observed drain concentration of nitrate were obtained. The simulation revealed that bypassing flow is a very important transfer mechanism in this soil and must be included in order to obtain a satisfactory fit of the experimental data. A sensitivity analysis of the model showed that the patterns of moisture flow have a predominant influence on the rate of nutrient leaching. In particular, it was found that the nutrient concentration in drain water is a strong function of the hydraulic conductivity of the soil matrix and of the horizontal distance between the soil macropores, which control the ratio of moisture flow in the soil matrix to the macropore flow and the lateral diffusion of nutrients between the soil matrix and the macropores. The effects of four different drainage designs on nutrient losses were simulated over a period of two years for three different soils and two different nutrient distributions in the soil. It was found that there is a large difference between the amount of nutrients leached from drainage systems using different drainage coefficients. There was also a large difference in the response of two drainage designs based on the same drainage coefficient but using different depth and spacing of drains. Transient effects, as determined by the initial vertical distribution of the nutrients, were seen to remain dominant over the two year duration of the simulation. The model was found to be useful in explaining the apparent contradictions found in the literature assessing the effects of subsurface drainage on nutrient losses. The results from the model show these effects to be strongly site and condition specific. Furthermore, the model shows that soils and drainage designs that produce similar volumes of drain flow may exhibit very different leaching responses, and that drainage designs equivalent from a hydraulic standpoint can be very dissimilar in their potential for leaching nutrients. The model provides a tool which can be used to determine the appropriateness of different drainage designs in soils where minimizing nutrient losses is critical.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".