Numerical and artificial intelligence models for predicting the water advance in border irrigation

Emamgholizadeh, Samad; Seyedzadeh, Amin; Hadi, Syamsul; Maroufpoor, Eisa; Karami, Gholamhosein

doi:10.1007/s10668-021-01453-6

Cited by 5 publications

(1 citation statement)

References 47 publications

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“…Concerning the irrigation processes, the advances in basins [14], border [15], and furrows [13,16] have been recorded. As for the optimization of the on-farm system management, progress has been made, both in conventional methodologies [8,15,17,18] and within the application of artificial intelligence resources [19][20][21]. Presently, the problem of the water savings in surface irrigation systems focuses on the challenges of the practical implementation of innovative measures; aiming for economic and environmental sustainability is a priority.…”

Section: Introductionmentioning

confidence: 99%

Water-Saving Techniques and Practices for On-Farm Surface Irrigation Systems

Gonçalves

Miao

2021

The 1st International Electronic Conference on Agronomy

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As surface irrigation systems are one of the most used water management techniques in the world, often working with high water losses, there is an urgency to their improvement. Modern methods that provide water savings and labour reduction require adequate design, management knowledge, and technical decision support. This study aims to improve water saving techniques for on-farm systems through an example of the decision-aid process being applied as a methodology based on the field experimentation and modelling of modern surface irrigation technologies in the Hetao (China) and Lower Mondego (Portugal) case studies. The performance indicators of irrigation water productivity (IWP) and the economic water productivity ratio (EWPR) were applied to compare the performance of several project solutions. The results obtained include a complete description of the latest irrigation solutions at the level basin, graded border, and graded furrows, which are adaptable to those case studies. The results revealed the benefits of a level-basin solution. For example, in Hetao, replacing the traditional system with a 100 m or 200 m long level basin, resulted in an increase in IWP by 40% and 3%, respectively, and in EWPR by 23% and 67%, respectively. The effect of a longer basin enables the reduction in operative costs, with a slight increase in distribution uniformity. In Lower Mondego, the IWP increased by 65% and the EWPR increased by 82%, by adopting graded furrows with 1.0‰ slopes and 200 m lengths. The main drivers of development of these surface irrigation systems were determined, namely, the runoff reuse and the system design and management. The issue that the local markets with equipment and consulting services should be available for farmers is also relevant to the development. It was proven that the effectiveness of modern surface water systems must adapt the solutions of the projects to the local characteristics of plot size and slope, soil type, and water supply.

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Section: Introductionmentioning

confidence: 99%

Water-Saving Techniques and Practices for On-Farm Surface Irrigation Systems

Gonçalves

Miao

2021

The 1st International Electronic Conference on Agronomy

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Water depth and cross‐sectional area relationships in sloping surface irrigation systems

Seyedzadeh,

Panahi,

Maroufpoor

2024

Irrigation and Drainage

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The equations governing variations in water depth and cross‐sectional area along a field are crucial for solving the Saint‐Venant equations and determining surface water volume via the volume balance method to determine other hydraulic parameters of surface irrigation systems. Various researchers have proposed different formulations for this equation based on varying assumptions. In many investigations, the flow depth profile has been assumed to be parallel to the furrow bottom or modelled as an elliptical relationship. This study explored four different forms of equation to analyse changes in the water depth profile and to refine its mathematical representation. The coefficients of these equations were derived as functions of the surface storage coefficient. Using field data, the surface storage coefficient values and, consequently, the coefficients of the proposed relationships were determined. The calculated values of the flow cross‐sectional area along the field and the water surface storage volume were compared with the measured values using the established relationships. The most accurate relationship for estimating the flow depth profile was identified through this analysis.

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Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region

Krishnamoorthy,

Lakshmanan

2024

Environ Sci Pollut Res

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Numerical and artificial intelligence models for predicting the water advance in border irrigation

Cited by 5 publications

References 47 publications

Water-Saving Techniques and Practices for On-Farm Surface Irrigation Systems

Water-Saving Techniques and Practices for On-Farm Surface Irrigation Systems

Water depth and cross‐sectional area relationships in sloping surface irrigation systems

Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region

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