The effects of subsurface drainage design and water management system on soil desalination in the Canadian Prairies.
Bibliographic record
Abstract
The use of electromagnetic induction to map and monitor the salinity levels of soil and other soil properties such water content has been an important tool of modern agriculture for decades. The present study used an electromagnetic induction (EMI) sensor (i.e EM-38 meter) to conduct surveys at two locations in Manitoba in order to assess the salinity levels and distribution of the soils in these locations. These study sites are Prairies East Sustainable Agriculture Initiative (PESAI) at Arborg, and a research farm Hespler commercial farms in Winkler Southern Manitoba, Canada. At PESAI, the study investigated the impact of drain spacing on the salinity levels of heavy clay soil. At the Winkler site, we investigated the impact on soil salinity of four water management system designs which include irrigation and drainage. At the PESAI research site, drain tiles were installed at a depth of 0.9 m to 1.1 m in the north north-south direction with drain spacing from 15 ft (4.57m), 30 ft (9.14m) and 45 ft (13.72m). The control plot had no drain tiles installed. Similarly, at the Winkler research site, the research area was divided into four water management systems in order to characterize better the effects of these water management systems on the salinity of the soil. These water management systems included no drainage with no irrigation (NDNI), free drainage with overhead irrigation (FDIR), controlled drainage with subirrigation (CDSI), and no drainage with overhead irrigation (NDIR). The irrigation and drainage on these plots started in 2009 and irrigation was stopped in 2013. A total of 2648 ECa data were surveyed from Arborg whereas Winkler had total ECa 11,715. A total of 165 soil samples were taken from 33 separate locations in the two study sites and were taken to the laboratory for further soil analysis. The apparent electrical (ECa) data from the Arborg study was corrected for departure from low induction number (LIN) response. No LIN correction was required for Winkler ECa data because the ECa values were low. The ECa result from both sites showed variations that did not correspond to the individual treatments. Careful examination of both ECa results indicated a large-scale, irregularly-shaped conductive and resistive region that crossed the boundaries of individual treatments. In both studies, the EC of the saturated paste extract (ECe) from all the 165 soil samples were depth weighted using horizontal mode (H-H) and vertical mode (V-V). There was a high correlation between ECa and ECe. Both studies yielded a high Pearson r2 correlation coefficient with Arborg exceeding 0.82 for H-H and 0.74 for V-V, while Winkler H-H was 0.84 and 0.62 for V-V. Although the volumetric water content (VWC) was relatively uniform at both study sites, there was also a weak correlation between VWC and ECa. The laboratory measured ECe is important as it is used to convert ECa from the field to ECe. It was observed that the Arborg calibration equation had a large positive intercept for both H-H and V-V mode. This indicated undissolved ECe source which was gypsum. High clay content of the study area and gypsum rich soil could be the main controlling factors acting on the ECe of the soil. To establish the effects of treatments, one way ANOVA design was applied to H-H and V-V ECe data in Arborg. The results revealed that the control drainage was least conductive compared to the other treatments. ANOVA result for Winkler study site revealed a trend of decreasing salinity in the plotset with time for plotset with irrigation and drainage. There was evidence of a decreasing salinity when mean of the plotset were ranked within May and June 2021. Within the year 2021, CDSI and FDIR were least conductive when compared with NDIR and NDNI. Similarly, in 2009, NDIR and NDNI were least conductive compared with CDSI and FDIR. The result from the Winkler study area showed that the drains tiles were effective in reducing salinity of the soil.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".