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Crop Water Requirement Estimation by Using Cropwat Model: A Case Study of Abrajit Earthen Dam Command Area, East Gojjam, Ethiopia

Currently, the Ethiopian government has launched an extensive irrigation system in the country and is constructing various small earthen dams in each woreda. But there is a gap between the water potential that we have and the water needs for the command area that has not been adequately studied. To solve this problem, these researchers are trying to compare the potential of the existing dams and the water needs of the exiting command areas using a CROPWAT model. The main crops cultivated are tefe, wheat, corn, paper, cabbage, corn, etc. However, for this work, the researcher only admitted that the whole area was suitable for wheat because of suitability, need, ease of irrigation and agricultural practice as well of the dominant irrigation type of the community should be used. The gross area of the project area covers a total of 6,456 hectares. Of this, only 4,566 hectares of the command area has been used for agricultural purposes by the villagers of the study area, while 286 hectares of the command area is currently irrigated by Abrajit dams. From the CROPWAT software model analysis consequence we have agreed that the total artificial application of water request for the existing command area in the region at seventeen percent (70%) effectiveness is 179.5 millimeter and a net irrigation requirement of 123.1 millimeter of water. Currently, the irrigation system taking place in the study area is 77.4% of the dam's capacity. There is additional irrigation capacity in the study area that will allow 22.6% of the earth dams to be irrigated in the future without having to build an additional dam.

Irrigation Demand, CROPWAT Model, Reference and Evapotranspiration of Crops, Effective Rainfall, Irrigation Planning

APA Style

Moges Tariku Tegenu. (2023). Crop Water Requirement Estimation by Using Cropwat Model: A Case Study of Abrajit Earthen Dam Command Area, East Gojjam, Ethiopia. Hydrology, 11(3), 43-50. https://doi.org/10.11648/j.hyd.20231103.11

ACS Style

Moges Tariku Tegenu. Crop Water Requirement Estimation by Using Cropwat Model: A Case Study of Abrajit Earthen Dam Command Area, East Gojjam, Ethiopia. Hydrology. 2023, 11(3), 43-50. doi: 10.11648/j.hyd.20231103.11

AMA Style

Moges Tariku Tegenu. Crop Water Requirement Estimation by Using Cropwat Model: A Case Study of Abrajit Earthen Dam Command Area, East Gojjam, Ethiopia. Hydrology. 2023;11(3):43-50. doi: 10.11648/j.hyd.20231103.11

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Abdalla N M, Zhang X J, Ishag A, Gamareldawla H. Estimating reference evapotranspiration using CROPWAT model at Guixi Jiangxi Province. State Key Laboratory of Hydrology and Water Resources and Hydraulic Engineering, Hohai University, China, 2010; 15pp. URL: http://www. paper.edu.cn
2. Adeniran K A, Amodu M F, Amodu M O, Adeniji F A. Water requirements of some selected crops in Kampe dam irrigation project. Australia Journal of Agriculture Engineering, 2010; 1 (4): 119–125.
3. Allen, R. G.; Pereira, L. S.; Raes, D.; Smith, M., (1998): Crop evapotranspiration-guidelines for computing crop water requirements - FAO Irrigation and drainage paper 56, FAO, Rome, Italy, 300p.
4. Araya, A.; Kisekka, I.; Vara Prasad, P. V.; Gowda, P. H., (2017): Evaluating optimum limited irrigation management strategies for corn production in the Ogallala aquifer region. J. Irrig. Drain. Eng., 143, 04017041.
5. Barker, R., (2002): Recent development in irrigation management in Asia and the Pacific. Report of the APO seminar on organizational change for participatory irrigation management. Philippines, (Tokyo: 23-27 October 2000 (SEM-32-00).
6. Broner, I. 2005. Irrigation: Irrigation scheduling. Fact Sheet No. 4.708. Colorado State University Extension –USDA. 2 pp. [Online] Available: http://www.ext.colostate.edu/pubs /crops/04708.pdf
7. Chen, F. W.; Liu, C. W.; Chang, F. J., (2014): Improvement of the agricultural effective rainfall for irrigating rice using the optimal clustering model of rainfall station network. Paddy Water Environ. 12, 393–406.
8. Djaman, K.; Balde, A. B.; Sow, A.; Muller, A. B.; Irmak, S.; N’Diaye, M. K.; Manneh, B.; Moukoumbi, Y. D.; Futakuchi, K.; Saito, K., (2015): Evaluation of sixteen reference evapotranspiration methods under sahelian conditions in the Senegal River Valley. J. Hydrol. Reg. Stud. 3, 139–159.
9. Djaman, K.; Irmak, S., (2013): Actual crop evapotranspiration and alfalfa- and grass-reference crop coefficients of maize under full and limited irrigation and rain fed conditions. J. Irrig. Drain. Eng., 139, 433–446.
10. FAO (2009): CropWat 8.0, edited, land and water development division. Food and Agriculture Organization of the United Nations, Rome.
11. Levidow, L.; Zaccaria, D.; Maia, R.; Vivas, E.; Todorovic, M.; Scardigno, A., (2014): Improving water-efficient irrigation: Prospects and difficulties of innovative practices. Agric. Water Manag., 146, 84–94.
12. Malikian A., Gasemi H., Ahmdian A., (2009): Evaluation of the efficiency of Cropwat8 model for determining plant water requirement in arid region, Zabol University, Iran. http://jdesert.ut.ac.ir/pdf_36341_b5506d9c85fe0387ce84d 4132b117cfa.html
13. Nischelm. J., J. Cordes, B. Riewe and R. Hohm. 2011. Current irrigation management practices study 2007 – 2009. Alberta Agriculture and Rural Development. Lethbridge, AB. 36 pp.
14. Panda RK, Behera SK, Kashyap PS 2004. Effective management of irrigation water for maize under stress conditions. Agric. Watermanag. 2004; 66: 181-203.
15. Peter, J. R., (2004): Participatory irrigation management, international network on participatory irrigation management, (Washington, DC: INWEPF/ SY/2004(06)).
16. Rao BB, Savani MB. Application of PLANTGRO, a water use model for differentially irrigated pearl millet. J Agrometeol. 1999; 1: 65-72.
17. Rathore LS, Nisha Mendiratta, Singh KK. Soil moisture prediction under maize in sandy loam. Annals of Arid Zone. 1998; 37 (1): 47-52.
18. Ritchie Joe T, Gopal Alagarswamy. Model concepts to express genetic difference in maize yield components. Agron. J. 2003; 95: 4-9.
19. Robertson MJ, Carberry P, Chuhan YS, Ranganathan R. Leary O, GJ. Predicting growth and development of pigeoeonpea: a simulation model. Field Crops Res. 2001; 71: 195-210.
20. Zhiming F, Dengwei L and Yuehong Z (2007). Water Requirements and Irrigation Scheduling of Spring Maize Using GIS and CROPWAT model in Beijing-TianjinHebei Region. Chinese Geographical Science 17 (1): 56-63.
21. Zhong S, Zhang W, Lu J, Wei C. Temporal variation of soil water and its influencing factors in hilly area of Chongqing, China. Int J Agric & Biol Eng, 2014; 7 (4): 47–59.