The model simulation is a simplification of the field processes. In metekel zone understanding how much and when to irrigate their crops is proplems of farmers. Therefore, this study was conducted to determine the crop water requirement and irrigation scheduling of pepper for the study area to solve the problem. Crop, soil physical and chemical, collected long-term daily climatic and irrigation water quality data, used for crop water requirement and irrigation scheduling using CropWat and AquaCrop models. The result revealed that maximum Crop water requirementof pepper (799.9 mm) was estimated in Guba and minimum ETc pepper (632.2 mm) was estmimated in Bullen using CropWat Model. However, using AquaCrop model the maximum ETc of pepper (779.5 mm) and minimum ETc of pepper (591.3mm) was estimated in Wembera. Moreover, it observed that the irrigation scheduling with a fixed interval criterion for pepper 7 days with 21 irrigation events, has been determined. Among the performance indicators, root mean square error normalized values of pepper was 3.2%, and nash-sutcliffe efficiency index values of pepper was 0.99 and prediction error values of pepper were 0.02, -0.08, -0.06, 0.03, -0.07, in Pawe, Mandura, Guba, Bullen, Wembera respectively. This show that AquaCrop model used to simulate crop water requirements of pepper with relatively similar results as CropWat in Metekel zone.
Published in | Advances (Volume 2, Issue 3) |
DOI | 10.11648/j.advances.20210203.13 |
Page(s) | 50-63 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2021. Published by Science Publishing Group |
CropWat, Aquacrop Crop, Water Requirement, Climate Data
[1] | Doorenbos, J. and Pruitt, W. O. 1977. Guidelines for predicting crop water requirements. FAO Irrigation and Drainage Paper No. 24. FAO, Rome, Italy, 179 p. http://www.fao.org. |
[2] | Ines, A. V. M.; P. Droogers; I. W. Makin; and A. Das Gupta. 2001. A schematized overview of the modeled system in SWAP (Van Dam et al. 1997). https://www.researchgate.net. |
[3] | Raes, D. 2002. BUDGET – a soil water and salt balance model. Reference manual. K. U. Leuven, Department Land Management, Leuven, Belgium. http://iupware.be/?page_id=820. |
[4] | FAO (Food and Agricultural Organization). 2013. Yield response to water: the original FAO. http://www.fao.org. |
[5] | Rodriguez, Y., Depestre, T., Gomez, O. 2008. Efficiency of selection in pepper lines (Capsicum Anjum), from four sub-populations, in characters of productive interest. Ciencia Investigation Agraria, 35 (1): 29-40. |
[6] | CSA (Central Statistical Authority). 2005. Report on the preliminary results of area, production and yield of temporary crops. Part I. Ethiopian Agricultural ample enumeration, 2001/2002 (1994 E.C). Addiss Ababa, Ethiopia. |
[7] | Yibekal Alemayahu, 2009. Managing the soil water balance of hot pepper (capsicum annuum. L.) to improve water productivity. PhD. Thesis, University of Pretoria, South Africa. |
[8] | FAO (Food and Agriculture Organization). 2012. Coping with water scarcity - an action framework for agriculture and food security. Rome, Italy. http://www.fao.org. |
[9] | Raes, D. 2009. ETo Calculator: a software program to calculate evapotranspiration from a reference surface. FAO Land Water Division: Digital Media Service, (36). http://www.fao.org. |
[10] | Henry. E. Igbadun. 2012. Irrigation Scheduling Impact Assessment MODel (ISIAMOD): A decision tool for irrigation scheduling. Indian Journal of Science and Technology, Vol. 5 No. 8 (August 2012) ISSN: 0974- 6846. https://indjst.org. |
[11] | Solomon Zewdu Altaye, Binyam Kassa, Bilatu Agza, Ferede Alemu and Gadisa Muleta. 2014. Smallholder cattle production systems in Metekel zone, Northwest Ethiopia. Research Journal of Agriculture and Environmental Management. Vol. 3 (2), pp. 151-157. https://businessdocbox.com. |
[12] | Abebaw Assaye, Adane Melak, Birhanu Ayalew, Dessalegn Teshale, Yalew Mazengia. 2015. Assessment of Seed Systems in North Western Ethiopia; With Special Emphasis on Community Based Seed Multiplication Scheme. World Scientific News 12 (2015) 100-110. https://www.researchgate.net. |
[13] | Ashebir Haile and Demeke Tamene. 2017. Determination of Optimum Irrigation Scheduling and Water Us Efficiency for Maize Production in North-West Ethiopia. Journal of Natural Sciences Research, volume. 7. no. 21. PP 22-27. https://www.researchgate.net. |
[14] | Singh, V. P. 1994. Elementary Hydrology. Prentice Hall of Idia: New Delhi. https://academicjournals.org. |
[15] | Bouyoucos, G. J. 1962. Hydrometer method improved for making particle size analysis of soils. Agronomy Journal 54: 464-465. https://onlinelibrary.wiley.com. |
[16] | US Salinity Laboratory Staff. 1954. Diagnosis and improvement of saline and alkaline soil. US Department agric. Handbook No 60. pp 160. https://www.scirp.org. |
[17] | Richards LA. 1954. Diagnosis and improvement of saline and alkali soils. USDA Agricultural Handbook No. 60, US Department of Agriculture, Washington DC. 160 pp. https://www.scirp.org. |
[18] | Loague, K. and Green, R. E. 1991. Statistical and graphical methods for evaluating solute transport models: Overview and application. J. Contam. Hydrol, 7: 51-73. https://www.sciencedirect.com. |
[19] | Yibrah G, Araya B, Amsalu N. 2015. Performance of AquaCrop Model in Predicting Tuber Yield of Potato (Solanum tuberosum L.) under Various Water Availability Conditions in Mekelle Area, Northern Ethiopia. Journal of Natural Sciences Research www.iiste.org ISSN 2224-3186 (Paper) ISSN 2225-0921 (Online) Vol. 5, No. 5. https://www.cabdirect.org. |
[20] | Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50 (3), 885-900. https://elibrary.asabe.org. |
[21] | Allen, R. G., Periera, L. S., Raes, D. and Smith, M. 1998. Crop evapotranspiration. Guidelines for computing crop water requirements (FAO Irrigation and Drainage Paper no. 56, p. 300). Rome. https://www.eea.europa.eu. |
[22] | JOHN B. ZAYZAY, Jr. 2015. validation of the FAO AquaCrop model for irrigated hot pepper (capsicum frutescens var legon 18) in the coastal savannah ecological zone of Ghana. A Thesis Submitted to the Department of Agricultural Engineering, School of Agriculture, College of Agriculture and Nature Sciences, University of Cape Coast. |
[23] | Wondimagegn Habte. 2011. Determination of Evapotranspiration and Crop Coefficient of Hot Pepper (Capsicum Annuum L.) at Melkassa, Ethiopia. A Thesis Submitted to The School of Natural Resources Management and Environmental Sciences, School of Graduate Studies Haramaya University. |
[24] | Jamieson, P. D., Porter, J. R., & Wilson, D. R. 1991. A test of computer simulation model ARC-WHEAT 1 on wheat crops grown in New Zealand. Field Crops Research, https://agris.fao.org › agris-search. |
APA Style
Demeke Tamene Mitku. (2021). Application of Aquacrop and CropWat Models for Estimating Crop Water Requirements and Irrigation Scheduling for Hot Pepper in Metekel Zone. Advances, 2(3), 50-63. https://doi.org/10.11648/j.advances.20210203.13
ACS Style
Demeke Tamene Mitku. Application of Aquacrop and CropWat Models for Estimating Crop Water Requirements and Irrigation Scheduling for Hot Pepper in Metekel Zone. Advances. 2021, 2(3), 50-63. doi: 10.11648/j.advances.20210203.13
@article{10.11648/j.advances.20210203.13, author = {Demeke Tamene Mitku}, title = {Application of Aquacrop and CropWat Models for Estimating Crop Water Requirements and Irrigation Scheduling for Hot Pepper in Metekel Zone}, journal = {Advances}, volume = {2}, number = {3}, pages = {50-63}, doi = {10.11648/j.advances.20210203.13}, url = {https://doi.org/10.11648/j.advances.20210203.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.advances.20210203.13}, abstract = {The model simulation is a simplification of the field processes. In metekel zone understanding how much and when to irrigate their crops is proplems of farmers. Therefore, this study was conducted to determine the crop water requirement and irrigation scheduling of pepper for the study area to solve the problem. Crop, soil physical and chemical, collected long-term daily climatic and irrigation water quality data, used for crop water requirement and irrigation scheduling using CropWat and AquaCrop models. The result revealed that maximum Crop water requirementof pepper (799.9 mm) was estimated in Guba and minimum ETc pepper (632.2 mm) was estmimated in Bullen using CropWat Model. However, using AquaCrop model the maximum ETc of pepper (779.5 mm) and minimum ETc of pepper (591.3mm) was estimated in Wembera. Moreover, it observed that the irrigation scheduling with a fixed interval criterion for pepper 7 days with 21 irrigation events, has been determined. Among the performance indicators, root mean square error normalized values of pepper was 3.2%, and nash-sutcliffe efficiency index values of pepper was 0.99 and prediction error values of pepper were 0.02, -0.08, -0.06, 0.03, -0.07, in Pawe, Mandura, Guba, Bullen, Wembera respectively. This show that AquaCrop model used to simulate crop water requirements of pepper with relatively similar results as CropWat in Metekel zone.}, year = {2021} }
TY - JOUR T1 - Application of Aquacrop and CropWat Models for Estimating Crop Water Requirements and Irrigation Scheduling for Hot Pepper in Metekel Zone AU - Demeke Tamene Mitku Y1 - 2021/09/30 PY - 2021 N1 - https://doi.org/10.11648/j.advances.20210203.13 DO - 10.11648/j.advances.20210203.13 T2 - Advances JF - Advances JO - Advances SP - 50 EP - 63 PB - Science Publishing Group SN - 2994-7200 UR - https://doi.org/10.11648/j.advances.20210203.13 AB - The model simulation is a simplification of the field processes. In metekel zone understanding how much and when to irrigate their crops is proplems of farmers. Therefore, this study was conducted to determine the crop water requirement and irrigation scheduling of pepper for the study area to solve the problem. Crop, soil physical and chemical, collected long-term daily climatic and irrigation water quality data, used for crop water requirement and irrigation scheduling using CropWat and AquaCrop models. The result revealed that maximum Crop water requirementof pepper (799.9 mm) was estimated in Guba and minimum ETc pepper (632.2 mm) was estmimated in Bullen using CropWat Model. However, using AquaCrop model the maximum ETc of pepper (779.5 mm) and minimum ETc of pepper (591.3mm) was estimated in Wembera. Moreover, it observed that the irrigation scheduling with a fixed interval criterion for pepper 7 days with 21 irrigation events, has been determined. Among the performance indicators, root mean square error normalized values of pepper was 3.2%, and nash-sutcliffe efficiency index values of pepper was 0.99 and prediction error values of pepper were 0.02, -0.08, -0.06, 0.03, -0.07, in Pawe, Mandura, Guba, Bullen, Wembera respectively. This show that AquaCrop model used to simulate crop water requirements of pepper with relatively similar results as CropWat in Metekel zone. VL - 2 IS - 3 ER -