Abstract
The increasing demand for food and clean energy, such as biofuel calls for a sustainable food-energy nexus in the agriculture sector. Mixed cropping pattern of food and biofuel crops is a viable strategy to meet the escalating demands of the biofuel production at the cost of food production. The implementation of the proposed solutions of simulation–optimization frameworks, at larger spatial scales, is a challenging task. One of the commonly adopted approaches is to implement the solution initially in critical zones that are sensitive to the land management practices and are critical for achieving the objectives. Despite the different techniques to identify the critical zones, this study proposes a new approach to identify the critical zones within a watershed, where the land use changes are essential to improve the social and physical environment while meeting the concurring demands for food and biofuel production. A decision support system (DSS), utilizing the concept of analytical hierarchy process (AHP) is developed to choose the number of optimal solutions from the Pareto-optimal Front to reduce the uncertainty involved in solution adaption by the decision-maker and identification of the critical zone. The results from the study indicate how solution strategies can influence the objective of optimal balance between crop demand and nutrient minimization using different cases. The proposed land use using the developed framework reduced the Total Nitrogen and Total Phosphorous loads by 29% and 38%, respectively from the watershed by converting about 44% of the baseline land use to different cropping patterns with the restriction on minimal food grain and biomass production. The outcome of the framework indicates that the adaptation of more robust objective function for spatial optimization through the developed DSS can reduce the nutrient load in the downstream water.
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Data is available in public domain.
Abbreviations
- DSS:
-
Decision support system
- AHP:
-
Analytical hierarchy process
- SWAT:
-
Soil and water assessment tool
- Swg:
-
Switchgrass
- Mxg:
-
Miscanthus
- CC30:
-
Continuous corn with 30% stover removal
- CC50:
-
Continuous corn with 50% stover removal
- HRUs:
-
Hydrological Response Units
- APV:
-
Aggregate pollutant value
- Nopt :
-
Nitrate load
- Popt :
-
Phosphorous load
- Nbase :
-
Nitrate loads for the baseline scenario
- Pbase :
-
Phosphorous loads for the baseline scenario
- BPCopt :
-
Optimized biomass production cost
- BPCmisc :
-
Biomass production cost for Miscanthus
- CR:
-
Consistency ratio
- CI:
-
Consistency index
- RI:
-
Random index
- NSE:
-
Nash sutcliffe efficiency
- PBIAS:
-
Percentage bias
- r2 :
-
Coefficient of determination
- MLSOPT:
-
Multi-level spatial optimization technique
- GWLQA:
-
Great lakes water quality agreement
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Acknowledgements
The authors would like to thank P.G. Senapathy Center for Computing Resource, IIT Madras for providing the access of VIRGO Super Cluster for doing all the simulations during experiment.
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All the authors conceived the experiments, Ashish Kumar, Vamsi Krishna Vema and K.P. Sudheer designed the experiment. Ashish Kumar performed the experiment. The experiment data and results were analyzed by Ashish Kumar, Vamsi Krishna Vema, Cicily Kurian and Jobin Thomas. K.P. Sudheer supervised the research as a part of Ashish Kumar’s master’s thesis. Ashish Kumar and Vamsi Krishna Vema prepared the original draft and all the authors contributed to the manuscript revisions.
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Kumar, A., Vema, V.K., Kurian, C. et al. A decision support system for the identification of critical zones in a watershed to implement land management practices. Stoch Environ Res Risk Assess 35, 1649–1664 (2021). https://doi.org/10.1007/s00477-021-01983-5
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DOI: https://doi.org/10.1007/s00477-021-01983-5