Irrigation Development as an Instrument for Economic Growth in Saskatchewan: An Economic Impact Analysis
Bibliographic record
Abstract
Allocation decisions in Saskatchewan of water are needed because of the limited nature of the resource in the province. Timely allocation of water can impact crop production, and through that economic development in the province, which may result through the value of the improved crop production as well as the economic linkages within the economy. Irrigation can be seen as a tool for economic growth as it decreases the reliance on natural factors which are critical for crop production in the province. The provincial government has committed, among its various agricultural initiatives, to develop tools to reach economic development goals. A study of the economic importance of irrigation in Saskatchewan is important to understand its contribution provincially and regionally as a possible tool for this economic development. The economic impacts of irrigation extend beyond farm-level impacts and understanding how it contributes to the entire economy at a provincial and regional level is information needed by decision makers. The purpose of this study is to provide the contributions of the irrigation sector on the provincial and regional economy. The Saskatchewan Irrigation Impact Analyzer (SIIA) model was built as a part of this study. The SIIA was based on a regionalized rectangular input-output model of the irrigation sector. Base data for the model were obtained from Statistics Canada Transaction Tables for 2011. The model was regionalized into: The Lake Diefenbaker Development Area (LDDA) and the other regions of Saskatchewan. The original data for agriculture production were disaggregated into irrigated and dryland production, each further disaggregated to crop and livestock production sectors. The model was further augmented with an employment model. Two scenarios of irrigation development were tested in the study: First, irrigation development that occurred during 2011-2016; Second, new irrigation development through infill expansion. In addition, the marginal contribution of the irrigation activity on the lake Diefenbaker Development Area region was also undertaken, which required a survey of producers. The study found that the total economic impacts of irrigation development during 2011-2016, enabling an additional 8,472 acres of irrigated production, amounted to $200.83 million in output (sales) generating $86.60 million in GDP contributions at market prices. This resulted in 1,179 full-time equivalent (FTE) employment years and $62.48 million in household income contributions. These estimates are based on a simulation of irrigation over a twenty-year period. With respect to potential irrigation expansion, the study found that if the 32,250-remaining infill-acres (that have been identified as offering irrigation potential) were to be developed and under production for a twenty-year period, the total economic impacts to the province of Saskatchewan would be $603.70 million in output (sales) responsible for 2,908 FTE employment years. This would amount to $181.12 million in household income contributions and $240.89 million in gross domestic product (GDP) contributions at market prices, at 2011 dollars. The study also found that regionally, irrigation provides an impetus for economic development. During the 2011 year, the marginal contribution of irrigation production, over and above the alternative of dryland production, was created through purchases of higher amounts of farm inputs, as well as spending of additional household income. These two avenues resulted in total economic impacts of $116.53 million in output (sales) which generated $78.47 million in GDP contributions at market prices. In the region, $58.72 million in household income gains also were incurred as a result of the 1,323 FTE employment years generated. The study found the economic impacts of irrigation, currently and potentially, to be extensive in each scenario and offering considerable regional impacts over and above the dryland production alternatives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".