A framework for the use of decision-support tools at various spatial scales for the management of irrigated agriculture in West-Africa


The Kou watershed, situated in the Southwestern part of Burkina Faso, has succumbed since a couple of decades in a typical theater play of anarchistic water management. With its 1800 km2, this small watershed holds the second largest city of Burkina Faso (Bobo-Dioulasso), a former State ran irrigated rice scheme and several informal agricultural zones. Despite the abundance on water resources, most water users find themselves regularly facing to water shortages due to an increase in population and low irrigation efficiencies. Local stakeholders are hence in need of easy-to-use and low-cost decision support tools for the monitoring and exploitation of the water resources at different spatial and user levels. A top-to-bottom string of adapted water management tools has been successfully installed to tackle the problems: from watershed (top) to field level (bottom), passing by the 1200 ha irrigation scheme. Land use maps have been derived from time-series of free satellite images. Combined with data from a network of hydrologic gauging stations, regional water use maps were established. SIMIS was put in place for the public-private management of the regions irrigated rice scheme. Day to day water use on irrigated plots was followed by soil humidity and crop canopy measurements. A simple field-cropwater balance model Aqua Crop was used by extension workers to draft optimal irrigation charts. Each tool was applied independently, requiring only limited data; but their combined results contributed to an improved integrated water management.

Share and Cite:

Wellens, J. , Traoré, F. , Diallo, M. and Tychon, B. (2013) A framework for the use of decision-support tools at various spatial scales for the management of irrigated agriculture in West-Africa. Agricultural Sciences, 4, 9-15. doi: 10.4236/as.2013.48A002.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] FAO (2002) World agriculture: Towards 2015/2030. Food and Agriculture Organization, Rome.
[2] Urama K.C. (2005) Land-use intensification and environmental degradation: Empirical evidence form irrigated and rain-fed farms in south eastern Nigeria. Journal of Environmental Management, 75, 199-217.
[3] Victoria, F.B., ViegasFilho J.S., Pereira, L.S., Teixeira, J.L. and Lanna, A.E. (2005) Multi-scale modelling for water resources planning and management in rural basins. Agricultural Water Management, 77, 4-20. dx.doi.org/10.1016/j.agwat.2004.09.037
[4] Bergez, J.E., Leenhardt, D., Colomb, B., Dury, J., Carpani, M., Casagrande, M., Charron, M.H., Guillaume, S., Therond, O. and Willaume, M. (2012) Computer-model tools for a better agricultural water management: Tackling managers’ issues at different scales—A contribution form systemic agronomists. Computer and Electronics in Agriculture, 86, 89-99. dx.doi.org/10.1016/j.compag.2012.04.005
[5] Wellens, J., Sawadogo, I., Diallo, M., Dakouré, D., Compaoré, N.F., Traoré, F. and Tychon, B. (2007) Recensement exhaustif des activités hydro-agricoles du Bassin du Kou. http://www.ge-eau.org/recensement.html
[6] Lillesand, T.M., Kiefer, R.W. and Chipman, J.W. (2004) Remote sensing and image interpretation. Wiley, New York.
[7] Wellens, J., Midekor, A., Traore, F. and Tychon, B. (2013) An easy and low-cost method for preprocessing and matching small-scale amateur aerial photography for assessing agricultural land use in Burkina Faso. International Journal of Applied Earth Observation and Geoinformation, 23, 273-278. dx.doi.org/10.1016/j.jag.2012.09.007
[8] Foody, G.M. (2004) Estimation sub-pixel land cover classification accuracy assessment. Remote Sensing of Environment, 26, 469-478.
[9] Wang, Z., Hu, G. and Yao, S. (2007) Decomposition mixed pixel of remote sensing image based on tray neural network model. In: Kang, L., Liu, Y. and Zeng, S., Eds., Advances in Computation and Intelligence, Springer, Heidelberg, 305-309. dx.doi.org/10.1007/978-3-540-74581-5_33
[10] Ozdogan, M. and Gutman, G. (2008) A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental US. Remote Sensing of Environment, 112, 3520-3537. dx.doi.org/10.1016/j.rse.2008.04.010
[11] Heller, E., Rhemtulla, J.M., Lele, S., Kalacska, M., Badiger, S., Sengupta, R. and Ramankutty, N. (2012) mapping crop types, irrigated areas, and cropping intensities in heterogeneous landscapes of southern India using multitemporal medium-resolution imagery: Implications for assessing water use in agriculture. Photogrammetric Engineering and Remote Sensing, 78, 815-827.
[12] Zhou, Q., Li, B. and Sun, B. (2008) Modelling spatiotemporal pattern of landuse change using multitemporal remotely sensed imagery. ISPRS Congress Beijing, 3-11 July 2008, Beijing, 729-734.
[13] Foody, G.M. (2002) Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80, 185-201. dx.doi.org/10.1016/S0034-4257(01)00295-4
[14] Congalton, R.G. and Green, K. (2009) Assessing the accuracy of remotely sensed data: Principles and practices. CRC/Taylor & Francis, Boca Raton.
[15] Manandhar, R., Odeh, I. and Ancev, T. (2009) Improving the accuracy of land use and land cover classification of landsat data using post-classification enhancement. Remote Sensing, 1, 330-344.dx.doi.org/10.3390/rs1030330
[16] World Bank (2007) Emerging Public-private partnerships in irrigation development and management. Water Sector Board Discussion Paper Series, Paper No. 10, The World Bank, Washington DC.
[17] Molden D.J. and Gates, T.K. (1990) Performances measures for evaluation of irrigation water delivery systems. Journal of Irrigation and Drainage, 116, 804-823. dx.doi.org/10.1061/(ASCE)0733-9437(1990)116:6(804)
[18] Wellens, J., Nitcheu, M., Traore, F. and Tychon, B. (2013) A public-private partnership experience in the management of an irrigation scheme using decision-support tools in Burkina Faso. Agricultural Water Management, 116, 1-11. dx.doi.org/10.1016/j.agwat.2012.09.013
[19] Lozano, D. and Mateos, L. (2008) Usefulness and limitations of decision support systems for improving irrigation scheme management. Agricultural Water Management, 95, 409-418. dx.doi.org/10.1016/j.agwat.2007.11.003
[20] Sargardoy, J.A., Pastore, G., Yamashita, I. and LópezCortijo, I. (2001) SIMIS: Scheme irrigation management information system. Version 2.0 for Windows. FAO Land and Water Digital Media Series No. 6. FAO, Rome, Italy. http://www.fao.org/nr/water/infores_cdroms.html
[21] Mateos, L., Lopez-Cortijo, I. and Sagardoy, J.A. (2002) SIMIS: The FAO decision support system for irrigation scheme management. Agricultural Water Management, 56, 193-206. dx.doi.org/10.1016/S0378-3774(02)00035-5
[22] Geerts, S. and Raes, D. (2009) Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas. Agricultural Water Management, 96, 1275-1284. dx.doi.org/10.1016/j.agwat.2009.04.009
[23] Steduto, P., Hsiao, T.C., Raes, D. and Fereres, E. (2009) AquaCrop—The FAO crop model to simulate yield response to water. I. Concepts and underlying principles. Journal of Agronomy, 101, 426-437. dx.doi.org/10.2134/agronj2008.0139s
[24] Hsiao, T.C., Heng, L., Steduto, P., Rojas-Lara, B., Raes, D. and Fereres, E. (2009) AquaCrop—The FAO crop model to simulate yield response of water: III. Parameterization and testing for Maize. Agronomy Journal, 101, 448-459. dx.doi.org/10.2134/agronj2008.0218s
[25] Raes, D., Steduto, P., Hsiao, T.C. and Fereres, E. (2009) AquaCrop—The FAO crop model to simulate yield response to water. II. Main algorithms and software description. Journal of Agronomy, 101, 438-447. dx.doi.org/10.2134/agronj2008.0140s
[26] Geerts, S., Raes, D. and Garcia, M. (2010) Using AquaCrop to derive deficit irriation schedules. Agricultural Water Management, 98, 213-216. dx.doi.org/10.1016/j.agwat.2010.07.003
[27] Wellens, J., Raes, D., Traore, F., Denis, A. and Djaby, B. (2013) Performance assessment of the FAO AquaCrop model for irrigated cabbage on farmer plots in a semi-arid environment. Agricultural Water Management, 127, 40-47. dx.doi.org/10.1016/j.agwat.2013.05.012
[28] Hu, Z., He, F., Yin, J., Lu, X, Tang, S., Wang, L. and Li, X. (2007) Estimation of fractional vegetation cover based on digital camera survey data and a remote sensing model. Journal of China University of Mining and Technology, 17, 116-120. dx.doi.org/10.1016/S1006-1266(07)60025-X
[29] Raes, D., Sahli, A., Van Looij, J., Ben Mechlia, N. and Persoons, E. (2000) Charts for guiding irrigation in real time. Irrigation and Drainage Systems, 14, 343-352. dx.doi.org/10.1023/A:1006412031535
[30] Hill, R.W. and Allen, R.G. (1996) Simple irrigation calendars: a foundation for water management. In: Food and Agricultural Organization of the United Nations (FAO), Ed., Irrigation Scheduling: From Theory to Practice, Rome, 69-74.
[31] Traoré, F., Cornet, Y., Denis, A., Wellens, J. and Tychon, B. (2013) Monitoring the evolution of irrigated areas with Landsat images using backward and forward change detection analysis in the Kou watershed, Burkina Faso. Geocarto International. www.tandfonline.com
[32] Ouédraogo, M. (2010) Social economical study on the agricultural use of the water resources of the river Kou: Case study of the agricultural region situated between Nasso and Diaradougou. GEeau, Bobo-Dioulasso, Burkina Faso.
[33] Traoré, F. (2012) Optimizing the use of water resources for agriculture in the Kou watershed. Ph.D. Dissertation, Université de Liège, Liège, Belgium.
[34] Institut International de l’Irrigation (IIMI) (1997) Diagnostic analysis and performance evaluation of five irrigation schemes located next to dams in Burkina Faso. Final Report—Part 1, Irrigation Management Project, Ouagadougou, Burkina Faso.
[35] Aggarwal, R.M. (2000) Possibilities and limitations to cooperation in small groups: the case of group-owned wells in Southern India. World Development, 28, 1481-1497.dx.doi.org/10.1016/S0305-750X(00)00030-9
[36] Bos, M.G. and Nugteren, J. (1990) On irrigation efficiencies. ILRI Publication, Wageningen.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.