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Multistage stochastic programming modeling for farmland irrigation management under uncertainty.

ABSTRACT: Farmland management and irrigation scheduling are vital to a productive agricultural economy. A multistage stochastic programming model is proposed to maximize farmers' annual profit under uncertainty. The uncertainties considered include crop prices, irrigation water availability, and precipitation. During the first stage, pre-season decisions including seed type and plant density are made, while determinations of when to irrigate and how much water to be used for each irrigation are made in the later stages. The presented case study, based on a farm in Nebraska, U.S.A., showed that a 10% profit increase could be achieved by taking the corn price and irrigation water availability uncertainties into consideration using two-stage stochastic programming. An additional 13% profit increase could be achieved by taking precipitation uncertainty into consideration using multistage stochastic programming. The stochastic model outperforms the deterministic model, especially when there are limited water supplies. These results indicate that multistage stochastic programming is a promising method for farm-scale irrigation management and can increase farm profitability.

SUBMITTER: Li Q

PROVIDER: S-EPMC7266336 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Multistage stochastic programming modeling for farmland irrigation management under uncertainty.

Li Qi Q Hu Guiping G

PloS one 20200602 6

Farmland management and irrigation scheduling are vital to a productive agricultural economy. A multistage stochastic programming model is proposed to maximize farmers' annual profit under uncertainty. The uncertainties considered include crop prices, irrigation water availability, and precipitation. During the first stage, pre-season decisions including seed type and plant density are made, while determinations of when to irrigate and how much water to be used for each irrigation are made in th ...[more]

PMID: 32484821

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Project description:Hedgerows provide valuable habitats and corridors for many species in farmland, yet a lack of appropriate management may threaten their benefits to biodiversity. Although agri-environment scheme (AES) prescriptions on hedgerow management have the potential to reverse the detrimental effect of over-trimming on wildlife, their effectiveness has rarely been addressed. The aims of the study were to (i) assess moth responses to trimming regimes; and (ii) investigate the influence of the surrounding landscape on moth assemblages. We specifically tested the effectiveness of the trimming regime recommended by the targeted AES that was implemented on farms near greater horseshoe bat (Rhinolophus ferrumequinum) colonies since it represented the most sympathetic hedgerow management option among English AES options. We sampled adult micro- and macro-moths along 64 hedgerows located within 20 English farms using light traps, and classified moths into two guilds reflecting their larval food preferences, namely grass/herb- and shrub/tree-feeders. Our results suggest that reducing trimming has a positive impact on macro-moth species richness as well as on shrub/tree-feeder abundance and species richness. It also benefited four moth species that are significantly declining in Britain. Furthermore, while the proportion of woodland at a large spatial scale (3.0 km radius around the sampling sites) was positively associated with the abundance of macro-moths and grass/herb-feeders, woodland connectivity had a positive effect on the species richness of grass/herb- and shrub/tree-feeders at large and medium (1.5 km radius) scales, respectively. Both the abundance and species richness of macro-moths and the abundance of shrub/tree-feeders were negatively affected by the presence of arable fields adjacent to hedgerows. Overall, these findings reveal the wider biodiversity benefits of targeted AESs focusing on habitat improvement for R. ferrumequinum, and the importance of woodland in the wider landscape. We therefore strongly recommend implementing a multi-scale management approach (i.e. from field to landscape) through the use of adequate AES prescriptions to conserve moths in agricultural landscapes.

Project description:Sewage irrigation has a strong influence on the physical, chemical, and biological properties of soil. However, the effects of sewage irrigation on the pore characteristics of soil are not well understood. This study compares the effects of sewage irrigation and groundwater irrigation on computed tomography (CT)-measured pore parameters and examines the relationships between CT-measured pore parameters and soil physicochemical and microbial properties. Intact soil cores were collected from S1 irrigated with sewage for 25 years, S2 irrigated with sewage for 52 years, and CK irrigated with groundwater. Various soil pore characteristics were determined, including the total pore number, macropore number (>1 mm diam.), coarse mesopore number (0.264?1 mm diam.), total porosity, macroporosity, coarse mesoporosity, and circularity. The results indicated that sewage irrigation significantly affected soil pore number and porosity. Compared with S1 and S2, CK exhibited a higher average total pore number (91), macropore number (40), coarse mesopore number (51), total porosity (2.08%), macroporosity (1.90%), and coarse mesoporosity (0.18%) throughout the 50?350 mm layer. At depths of 200?350 mm, S2 exhibited the lowest average total pore number (33), macropore number (13), coarse mesopore number (21), total porosity (0.42%), macroporosity (0.35%), and coarse mesoporosity (0.07%) among the three sites. In addition, the average pore numbers and porosity at depths of 200?350 mm decreased with increasing sewage irrigation time. There were significant positive correlations between pore features (including pore numbers and porosity) and soil properties (phosphorus content and fungi numbers). Our results suggest that decreased macropore numbers and macroporosity in the sewage-irrigated farmland may strongly intensify the accumulation of metals and nutrients in the upper layer. The findings of this study are useful for understanding the negative effects of sewage irrigation on soil pore structure and are critical for developing sustainable strategies in agriculture.

Dataset Information

Multistage stochastic programming modeling for farmland irrigation management under uncertainty.

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Multistage stochastic programming modeling for farmland irrigation management under uncertainty.

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