Model-Based Estimation of Agronomic Value Responses to Seasonal Forecasts
DOI:
https://doi.org/10.53555/nnfaes.v7i3.936Keywords:
ENSO Phases, Forecast, Rainfall, Maize, Season, YieldAbstract
Projecting crop yields and aggregate production of the region is of the highest interest for maize production markets which is the source of economic development of the farmers. We used Agriculture Production Systems sIMulation (APSIM 7.10) to simulate the maize yield of Nkotsi region of Rwanda for two seasons SOND and MAM. For this simulation, daily meteorological data of the rainfall, Solar radiation, maximum and minimum temperature are inputs of the model. The impact of the ElNi~no-Southern Oscillation(ENSO)phases and the yield is demonstrated, it is found that ElNi~no phase is good for maize and LaNina lead to the small yield. We compared the simulated yield with observed the author realize that they are correlated with R Square of 0.89. We identified cropping practices of profit-maximizing based on climate information. The seasonal rainfall forecasting has been done by Climate
Predictability Tools(CPT15) and WeatherMan Version 4.7, utilizing General Circulation Model (GCM) and Enhancing National Climate Services (ENACTS) data from 1985 to 2019.
Related: https://nnpub.org/index.php/FAES/article/view/1411
References
Douglas R Brown. A review of bio-economic models. Cornell African Food Security and Natural Resource Management (CAFSNRM) Program, 102,2000.
S Coulter, Stan Lalor, Contributors Stephen Alex, Alastair Black, Andy Bol, Jim Burke, Owen T Carton, Brian S Coulter, Noel Culleton, Pat Dillon, et al. Major and micro nutrient advice for productive agricultural crops.2008.
Neil Dawson, Adrian Martin, and Thomas Sikor. Green revolution in subsaharan africa: implications of imposed innovation for the wellbeing of rural smallholders. World Development, 78:204{218, 2016.
James W Hansen. Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges. Agricultural systems, 74(3): 309{330, 2002.
James W Hansen, Andries Potgieter, and Michael K Tippett. Using a general circulation model to forecast regional wheat yields in northeast australia. Agricultural and Forest Meteorology, 127(1-2):77{92, 2004.
James W Hansen, Ashok Mishra, KPC Rao, Matayo Indeje, and Robinson Kinuthia Ngugi. Potential value of gcm-based seasonal rainfall forecasts for maize management in semi-arid kenya. Agricultural Systems, 101 (1-2):80{90, 2009.
Peter Hoefsloot, Amor VM Ines, Jos van Dam, Gregory Duveiller, Francois Kayitakire, and James Hansen. Combining crop models and remote sensing for yield prediction: Concepts, applications and challenges for heterogeneous smallholder environments. 2012.
James W Jones, Gerrit Hoogenboom, Cheryl H Porter, Ken J Boote, William D Batchelor, LA Hunt, Paul W Wilkens, Upendra Singh, Arjan J
Gijsman, and Joe T Ritchie. The dssat cropping system model. European journal of agronomy, 18(3-4):235{265, 2003.
DONALD KABERUKA et al. Rwanda vision 2020. 2000.
Allen C Kelley. The consequences of rapid population growth on human resource development: The case of education. In The impact of population growth on well-being in developing countries, pages 67{137. Springer, 1996.
David A Laird. The charcoal vision: a win{win{win scenario for simultaneously producing bioenergy, permanently sequestering carbon, while improving soil and water quality. Agronomy journal, 100(1):178{181, 2008.
Caroline Lesser and Evdokia Mois´e-Leeman. Informal cross-border trade and trade facilitation reform in sub-saharan africa. 2009.
Ralf Metzler and Joseph Klafter. The random walk’s guide to anomalous diffusion: a fractional dynamics approach. Physics reports, 339(1):1{77, 2000.
Francisco J Meza, James W Hansen, and Daniel Osgood. Economic value of seasonal climate forecasts for agriculture: review of ex-ante assessments and recommendations for future research. Journal of Applied Meteorology and Climatology, 47(5):1269{1286, 2008.
Alphonse Mutabazi. Rwanda country situational analysis. CAMCO Report, Nairobi Kenya, 2011.
H Partow, U Bloesch, G Bouma, N Brown, M Estrella, et al. Rwanda: from post conflict to environmentally sustainable development. United Nat ions Environment Programme, Nairobi, 2011.
AV Pukhovskiy. Ability of mitscherlich-spillman model to estimate critical soil phosphate levels. Int J Nutr Food Sci, 2:45{51, 2013.
William W Riggs, Kynda R Curtis, and Thomas R Harris. Importance & Use of Enterprise Budgets in Agricultural Operations. University of Nevada, Nevada Cooperative Extension, 2005.
O Rojas, Y Li, and R Cumani. An assessment using fao’s agricultural stress index (asi): Understanding the drought impact of el nino on the global agricultural areas. 2014.
FS Royce, JW Jones, and JW Hansen. Model-based optimization of crop management for climate forecast applications. Transactions of the ASAE, 44(5):1319, 2001.
Rwanda. Economic Development and Poverty Reduction Strategy, 2008-2012.
Ministry of Finance and Economic Planning, 2007.
B Searle, R Renquist, and B Bycroft. Agronomic factors affecting the variability of squash fruit weight. Agronomy NZ, 32:27{34, 2003.
Samar R Sen et al. Decision-making and agriculture. In Decision-making and agriculture. Sixteenth International Conference of Agricultural Economics, Nairobi, Kenya, 26th July{4th August, pages 1{14, 1976.
MVK Sivakumar and J Hansen. Climate prediction and agriculture: summary and the way forward. In Climate Prediction and Agriculture, pages 1{13. Springer, 2007.
L Sun and MN Ward. Climate downscaling: assessment of the added values using regional climate models. In Climate Prediction and Agriculture, pages 15{29. Springer, 2007.
Johan FM Swinnen and Hamish R Gow. Agricultural credit problems and policies during the transition to a market economy in central and eastern europe. Food policy, 24(1):21{47, 1999.
V Zanella, BV Ortiz, K Thorp, F Morari, G Mosca, and G Hoogenboom. Combining crop sensing and simulation modeling to assess within-field corn nitrogen stress. In Precision agriculture’15, pages 165{177. Wageningen Academic Publishers, 2015.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Journal of Advance Research in Food, Agriculture and Environmental Science (ISSN: 2208-2417)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
