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A SYSTEM DESIGN OPTIMIZATION MODEL FOR INTEGRATED NATURAL RESOURCE CONSERVATION AND DEVELOPMENT IN AN AGRICULTURAL COMMUNITY

Published online by Cambridge University Press:  27 July 2021

Thomas Barlow ,
Mandappa Biddanda ,
Samarth Mendke ,
Emmanuel Miyingo ,
Anabel Sicko ,
Panos Y. Papalambros ,
Cheng-Chun Chien  and
William O'Neal
Thomas Barlow
Affiliation:
University of Michigan
Mandappa Biddanda
Affiliation:
University of Michigan
Samarth Mendke
Affiliation:
University of Michigan
Emmanuel Miyingo
Affiliation:
Makerere University
Anabel Sicko*
Affiliation:
University of Michigan
Panos Y. Papalambros
Affiliation:
University of Michigan
Cheng-Chun Chien
Affiliation:
University of Michigan
William O'Neal
Affiliation:
University of Michigan
*
Sicko, Anabel, Optimal Design Laboratory, University of Michigan, Mechanical Engineering, United States of America, [email protected]

Abstract

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Integrated Natural Resource Conservation and Development (INRCD) Projects are efforts at worldwide locations to promote economic development of local communities consistent with conservation of natural resources. This umbrella term includes Integration Conservation and Development Projects (ICDPs) introduced by the World Wide Fund to combine social development and conservation s through the use of socio-economic investments, and the Integrated Natural Resource Management (INRM) research and development efforts that have employed a systems approach for quantitative modeling and optimization. In the spirit of the INRCD framework, we describe the development of a system-level agriculture and energy model comprising engineering and economic models for crop, irrigation, and energy subsystem designs for a community in Central Uganda. The model architecture is modular allowing modifications for different system configurations and project locations. We include some initial results and discuss next steps for system optimization, refining model assumptions, and modeling community social benefits as drivers of such projects.

Keywords

OptimisationSustainabilityIntegrated Natural Resource Conservation and Development (INRCD)Integrated Conservation and Development Projects (ICDP)Constraint modelling
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 273 - 282
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

Albert, S (1999). Solving Mixed Integer Linear Programs Using Branch and Cut Algorithm. MS Thesis, Mathematics, North Carolina State University, 1999.Google Scholar
Alvarez, S.R., Oviedo, J.E. and Gil, A.A. (2018). “Hymod: A Software for Hybrid Microgrid Optimal Design.” 15th International Conference on Electrical Engineering, Computing Science and Automatic Control, IEEE, New York City, New York. https://doi.org/10.1109/ICEEE.2018.8533914CrossRefGoogle Scholar
Bekalo, I., Ochola, W.O. and Sanginga, P.C. (2010), Managing natural resources for development in Africa: a resource book. University of Nairobi Press, Nairobi, Kenya.Google Scholar
Brown, G.O. (2012). “The History of the Darcy-Weisbach Equation for Pipe Flow Resistance”, Environmental and Water Resources History, ASCI. Available online: https://ascelibrary.org/doi/10.1061/40650(2003)4.Google Scholar
EPA (2020a). Greenhouse Gases Equivalencies Calculator. Accessed on 8 Dec. 2020. https://www.epa.gov/energy/greenhouse-gases-equivalencies-calculator-calculations-and-referencesGoogle Scholar
EPA (2020b). Watersense: Adding Microirrigation to Your Services: A Mini-Guide for Irrigation Professionals. [online] Available at: https://www.epa.gov/sites/production/files/2018-05/documents/ws-outdoors-microirrigation-prosguide.pdf. (Accessed on 8 Dec. 2020).Google Scholar
FAO (2020a). GIEWS FPMA Tool - monitoring and analysis of food prices. [online] Available at: https://fpma.apps.fao.org/giews/food-prices/tool/public/#/dataset/domestic. (Accessed on 8 Dec. 2020)Google Scholar
FAO (2020b). FAO Penman-Monteith Equation. [online] Available at: http://www.fao.org/3/X0490E/x0490e06.htm#fao penman monteith equation (Accessed on 8 Dec. 2020)Google Scholar
Foster, T., Foster, T., Brozović, N., Butler, A.P., Neale, C.M.U., Raes, D., Steduto, P., Fereres, E., Hsiao, T.C. (2017). “AquaCrop-OS: An open-source version of FAO's crop water productivity model.” Agricultural Water Management, Vol. 181, pp.18–22. https://doi.org/10.1016/j.agwat.2016.11.015CrossRefGoogle Scholar
Fuentes, E., Arce, L. and Salom, J. (2018). “A review of domestic hot water consumption profiles for application in systems and buildings energy performance analysis.” Renewable and Sustainable Energy Reviews, Vol. 81, pp. 1530–1547. https://doi.org/10.1016/j.rser.2017.05.229CrossRefGoogle Scholar
Fungo, B., Grunwald, S., Tenywa, M. M., Vanlauwe, B. and Nkedi-Kizza, P. (2010), “Lunnyu Soils in the Lake Victoria basin of Uganda: Link to Toposequence and Soil type.” Online Journal of Earth Sciences, Vol. 4 No. 2, pp. 63–71. https://doi.org/10.3923/ojesci.2010.63.71Google Scholar
Hughes, R. and Flintan, F. (2001). Integrating conservation and development experience: a review and bibliography of the ICDP literature. International Institute for Environment and Development, London.Google Scholar
Macrotrends (2020). Soybean Prices - 45 Year Historical Chart. [online]. Available at: https://www.macrotrends.net/2531/soybean-prices-historical-chart-data'>Soybean%20Prices%20-%2045%20Year%20Historical%20Chart</a> (Accessed on 8 Dec 2020)Soybean%20Prices%20-%2045%20Year%20Historical%20Chart+(Accessed+on+8+Dec+2020)>Google Scholar
Minai, J. O. (2015). Assessing the spatial variability of soils in Uganda. PhD Dissertation, Purdue University.Google Scholar
Motoma, R.I.P. (2007). Modelling a Water Conserving Tariff for Kampala Uganda. MS Thesis, Loughborough University.Google Scholar
Okello, D., Banda, E. and Mubiru, J. (2011). “Availability of Direct Solar Radiation in Uganda.” ISES Solar World Congress, Kassel, Germany, 2011. https://doi.org/10.18086/swc.2011.24.22CrossRefGoogle Scholar
Owor, M., Tindimugaya, C., Brown, L., Upton, K., Ó Dochartaigh, B.É. and Bellwood-Howard, I. (2018). Africa Groundwater Atlas: Hydrogeology of Uganda. [online] British Geological Survey. Available at: http://earthwise.bgs.ac.uk/index.php/Hydrogeology_of_Uganda (Accessed November 30, 2020.)Google Scholar
Papalambros, P.Y. and Wilde, D.J. (2017). Principles of Optimal Design: Modeling and Computation, Cambridge University Press, Cambridge, England.CrossRefGoogle Scholar
Prathumchai, K., Nagai, M., Tripathi, N. K. and Sasaki, N. (2018). “Forecasting Transplanted Rice Yield at the Farm Scale Using Moderate-Resolution Satellite Imagery and the AquaCrop Model: A Case Study of a Rice Seed Production Community in Thailand.” ISPRS International Journal of Geo-Information, Vol. 7 No.2, p. 73. https://doi.org/10.3390/ijgi7020073CrossRefGoogle Scholar
Prinsloo, G., Dobson, R., and Brent, A. (2016). “Scoping exercise to determine load profile archetype reference shapes for solar co-generation models in isolated off-grid rural African villages.” Journal of Energy in Southern Africa, Vol. 27 No. 3, pp. 11–27. https://doi.org/10.17159/2413-3051/2016/v27i3a1375CrossRefGoogle Scholar
Pumpmakers (2020). PM Pumpmakers GmbH, Sankt Veit an der Glan, Austria. Available at: https://pumpmakers.com/en (Accessed 30 Nov. 2020)Google Scholar
Rajski, P. and Papalambros, P.Y. (2021). “Integrated Natural Resource and Conservation Development Project: A Review of Success Factors from a Systems Perspective.” Proceedings of the Design Society ICED21, Gothenburg, Sweden (this volume).CrossRefGoogle Scholar
Rao, N.H., Sarma, P. and Chander, S. (1988). “Irrigation scheduling under a limited water supply”, Agricultural Water Management, Vol. 15 No. 2, pp.165–175. https://doi.org/10.1016/0378-3774(88)90109-6CrossRefGoogle Scholar
Ruiz, S. (2020). Hymod: A Software for Hybrid Microgrid Optimal Design. Available at: https://www.mathworks.com/matlabcentral/fileexchange/66123-hymod-a-software-for-hybrid-microgrid-optimal-design, MATLAB Central File Exchange. (Accessed 30 Nov. 2020.)Google Scholar
Schienbein, L. A., Balducci, P. J., Nguyen, T. B., Brown, D. R., DeSteese, J. G. and Speer, G. A. (2004). Avoiding Distribution System Upgrade Costs Using Distributed Generation, PennWell Pub., Tulsa, OK.Google Scholar
Schütze, N. and Mialyk, O. (2019). “Deficit Irrigation Toolbox: A new tool to improve crop water productivity and food security under limited water resources.” 21st EGU General Assembly, Vienna, Austria.Google Scholar
Schütze, N., de Paly, M. and Shamir, U. (2012). “Novel simulation-based algorithms for optimal open-loop and closed-loop scheduling of deficit irrigation systems.” Journal of Hydroinformatics, 14 (1): 136–151. https://doi.org/10.2166/hydro.2011.073CrossRefGoogle Scholar
Seidel, S.J., Schütze, N., Fahle, M., Mailhol, J.-C. and Ruelle, P. (2015). “Optimal Irrigation Scheduling, Irrigation Control and Drip Line Layout to Increase Water Productivity and Profit in Subsurface Drip-Irrigated Agriculture.” Irrigation and Drainage, 64, 501–518. https://doi.org/10.1002/ird.1926CrossRefGoogle Scholar
Semenov, M.A. and Barrow, E.M. (2002). LARS-WG: A Stochastic Weather Generator for Use in Climate Impact Studies. User Manual, Hertfordshire, UK, 0-27.Google Scholar
Sprei, F., 2002. Characterization of power system loads in rural Uganda. MS Thesis, Lund University of Technology, Lund, Sweden.Google Scholar
Tinarwo, D., 2009. Design of village power and microgrids for rural areas of Zimbabwe with specific attention to voltage regulation on low voltage meshed distribution grids. Kassel University Press, Kassel, Germany.Google Scholar
UNDP (2015). Sustainable Development Goals. [online] Available at: https://www.undp.org/content/undp/en/home/sustainable-development-goals.html. (Acc. 8 Dec. 2020)Google Scholar
USDA (2020). Natural Resources Conservation Service. Soil Texture Calculator. Available at: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/?cid=nrcs142p2_054167 (Acc. 30 Nov. 2020)Google Scholar
Veenstra, J., Dembe, D., Nsamba, J., Wasko, L., Burras, L., Nonnecke, G., Orum, B., Downie, S. and Cox, R. (2009). “Mapping Soils in Central Uganda.” Soil Survey Horizons, Vol. 50 No. 1, pp. 31–34. https://doi.org/10.2136/sh2009.1.0031CrossRefGoogle Scholar