Literature DB >> 32325580

Optimize the spatial distribution of crop water consumption based on a cellular automata model: A case study of the middle Heihe River basin, China.

Liuyue He1, Jianxia Bao2, Andre Daccache3, Sufen Wang4, Ping Guo5.   

Abstract

Globally, agriculture is by far the largest water consuming sector and in areas where water is scarce, the spatial optimization of crop water consumption used to improve irrigation benefits becomes critical for regional water management. The spatial heterogeneity of environmental parameters brings great challenge to spatial optimization. Therefore, cellular automaton (CA), crop suitability (CS), spatial distributed crop water consumption model and optimization model were integrated and applied on the middle reaches of Heihe River basin, northwest of China. The cellular automata based Water Consumption Optimization (CA-WCSO) model is not only a spatial dynamic optimization model for crop water consumption, but also a decision support tool that reflects the interaction between water consumption at field level and management regulations at regional level. Six optimization paths: i) forward progressive (FP), ii) forward interlacing (F-IL), iii) forward interpolation (F-IP), iv) reverse progressive (R-P), v) reverse interlacing (R-IL) and vi) reverse interpolation (R-IP) of crop water consumption for the baseline year and the planning year were applied on the study site. Results for baseline year (2015) demonstrate that the six optimization paths can slightly reduce the water consumption (>1.4%) but significantly improve the irrigation benefits of the region by 20.56%. Using CA-WCSO model, decision makers can modify model's constraints and select appropriate optimization path to get the optimized crop planting patterns and make future regional water allocation plans.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Conversion rule; Crop suitability; Crop water consumption; Dynamic optimization; Spatial distribution; Water management

Year:  2020        PMID: 32325580     DOI: 10.1016/j.scitotenv.2020.137569

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Integrated strategic planning and multi-criteria decision-making framework with its application to agricultural water management.

Authors:  Ahmad Radmehr; Omid Bozorg-Haddad; Hugo A Loáiciga
Journal:  Sci Rep       Date:  2022-05-19       Impact factor: 4.996

2.  The influence of immune individuals in disease spread evaluated by cellular automaton and genetic algorithm.

Authors:  L H A Monteiro; D M Gandini; P H T Schimit
Journal:  Comput Methods Programs Biomed       Date:  2020-08-18       Impact factor: 5.428

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.