Optimizing the Use of Land and Water Resources for Maximizing Farm Income by Mitigating the Hydrological Imbalances

Singh, Ajay

doi:10.1061/(asce)he.1943-5584.0000924

Cited by 41 publications

(10 citation statements)

References 86 publications

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“…The results of this study are in agreement with the reported results of Owji and Nikkami (2012); Han et al (2016) and Tajbakhsh et al (2018) on the reduction of surface runoff generation through land‐use allocation optimization; and the findings of Sadeghi et al (2009); Nikkami et al (2009); Owji, Nikkami, Mahdian, et al (2012); Sunandar et al (2014); Shaygan et al (2014); Han et al (2016); Lazoglou et al (2016); Sokouti and Nikkami (2017) and Tajbakhsh et al (2018) on the reduction of soil erosion and sediment loads. Moreover, our results are consistent with the reported results of Benli and Kodal (2003); Sadeghi et al (2009); Nikkami et al (2009); Hongrui et al (2010); Owji, Nikkami, Mahdian, et al (2012); Sunandar et al (2014); Yuan et al (2014); Singh (2014); Shaygan et al (2014); Zhou et al, (2015); Mohammadi et al (2015); Lazoglou et al (2016); Sokouti and Nikkami (2017), García et al(2017) and Tajbakhsh et al (2018) on increasing economic returns, and also in agreement with the findings of Shaygan et al (2014) denoting an increase of land use suitability index.…”

Section: Resultssupporting

confidence: 93%

Land use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)

Sheikh

Salmani

Mahiny

et al. 2021

Natural Resource Modeling

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This study aims to present an efficient methodology for land use optimization based on minimization of runoff and sediment and maximization of economic benefits, occupational opportunities, and land use suitability in the Tilabad watershed in northeast of Iran. The land use map of the area was prepared using the Landsat satellite images and field surveys. The amounts of runoff and sediment were estimated via SWAT model. The TOPSIS multicriteria decision‐making (MCDM) approach was applied on the results of the multiobjective optimization (MOO) based on non‐dominated sorting genetic algorithm II (NSGA II) to choose the final optimal solution among the Pareto solutions front generated by MOO. The results indicated that the area of agriculture and rangelands should decrease, and the area of forests should increase to achieve the defined objectives. Overall, results indicated that integration of MOO and MCDM provides an efficient procedure for land use optimization in a complex watershed. Recommendations for Resource Managers The optimization of land use allocation across a complex watershed requires the combined application of several models and techniques to achieve a sustainable decision‐making process. By optimization of land use patterns according to the final solution, the surface runoff and sediment load of the watershed will decline, while the economic profit and land use suitability will improve. Despite using a maximization objective function, the land‐based job opportunities might decrease across a watershed by optimization of land use allocation, but this can be considered as an opportunity for provision of manpower to other socioeconomic sectors.

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Section: Resultssupporting

confidence: 93%

Land use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)

Sheikh

Salmani

Mahiny

et al. 2021

Natural Resource Modeling

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“…The burgeoning global population is facing the critical challenge of water shortage for fulfilling its growing domestic, industrial and agricultural demands. The issue will be more serious in coming decades as the per capita availability of fresh water is projected to contract to 50% of its present level in 2025 (Singh, 2014c(Singh, , 2014d. The conjunctive use (COU) of diverse water sources can solve the water shortage issue to some degree by developing water use efficiency (Cheng et al, 2009;Liu et al, 2013;Singh, 2016d).…”

Section: Conjunctive Water Usementioning

confidence: 99%

Salinization and drainage problems of agricultural land

Singh

2020

Irrigation and Drainage

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The extension of irrigated agriculture is essential to fulfilling the mounting demand for food and fibre from a growing population which is anticipated to reach about 10 billion individuals in 2050. Lacking the necessary drainage, this extension can bring about salinization issues in irrigated regions. Continuous irrigation over many years with no adequate drainage services has led to huge agricultural regions becoming unproductive. Salinization problems linked to poor drainage are widespread in agricultural zones over the world. The aforementioned drainage-related salinization issues in agricultural land have been solved by using various methods and techniques. This paper presents an assessment of some non-conventional methods and strategies utilized for dealing with salinization and drainage issues of irrigated land. An indication of the drainage and salinization issues of irrigated areas and the significance of the study are given. Reasoning and foundation of the issues are presented. Numerical and analytical solutions of the problems are described. The drainage water management technique for managing nutrient losses from a drainage system is discussed. The analysis revealed that conjunctive water use with an increased groundwater proportion can to some extent manage the salinization and root-zone submergence problems of irrigated areas. K E Y W O R D S agricultural sustainability, conjunctive water use, drainage of irrigated land, drainage water management, land salinization Résumé L'extension de l'agriculture irriguée est essentielle pour répondre aux demandes croissantes de nourriture et de fibres pour la population croissante qui devrait contacter une dizaine de milliards d'individus en 2050. Sans des conditions de drainage adaptées, cette extension peut entraîner des problèmes de salinisation dans les régions irriguées. L'irrigation continue pendant de nombreuses années sans services de drainage adéquats a provoqué l'impossibilité à produire pour de vastes régions agricoles. Les problèmes de salinisation liés au mauvais drainage sont répandus dans les zones agricoles du monde entier. Les problèmes de salinisation des terres agricoles liés au * Problèmes de salinisation et de drainage des terres agricoles

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“…Because of easy formulation and application, the use of LP-based optimization models is very common in the management of water-resource problems (Bender et al 1984;Suryavanshi and Reddy 1986;Kumar and Pathak 1989;Ahlfeld and Heidari 1994;Vedula and Kumar 1996;Khare et al 2007;Azamathulla et al 2008;Lu et al 2011;Singh 2014e). However, NLP models have not been widely used because of rigorous mathematics involved in its development and the high computation time and memory required.…”

Section: Optimization Modelingmentioning

confidence: 99%

Review: Computer-based models for managing the water-resource problems of irrigated agriculture

Singh

2015

Hydrogeol J

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Irrigation is essential for achieving food security to the burgeoning global population but unplanned and injudicious expansion of irrigated areas causes waterlogging and salinization problems. Under this backdrop, groundwater resources management is a critical issue for fulfilling the increasing water demand for agricultural, industrial, and domestic uses. Various simulation and optimization approaches were used to solve the groundwater management problems. This paper presents a review of the individual and combined applications of simulation and optimization modeling for the management of groundwater-resource problems associated with irrigated agriculture. The study revealed that the combined use of simulation-optimization modeling is very suitable for achieving an optimal solution for groundwater-resource problems, even with a large number of variables. Independent model tools were used to solve the problems of uncertainty analysis and parameter estimation in groundwater modelling studies. Artificial neural networks were used to minimize the problem of computational complexity. The incorporation of socioeconomic aspects into the groundwater management modeling would be an important development in future studies.

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Optimizing the Use of Land and Water Resources for Maximizing Farm Income by Mitigating the Hydrological Imbalances

Cited by 41 publications

References 86 publications

Land use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)

Land use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)

Salinization and drainage problems of agricultural land

Review: Computer-based models for managing the water-resource problems of irrigated agriculture

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