• Dahiru Mohammed Agricultural and Bio Environmental Engineering
  • M. M. Maina
  • I. Audu
  • I. Y. Tudunwada
  • N. K. Nasiru
  • N. M. Nasidi
  • S. E. Umar
Keywords: Irrigation, Landsat, Mapping, Saline, Soil


Soil salinization is becoming a more serious issue threatening agricultural production and the sustainable use of land resources. Crop roots are unable to absorb water from the soil when exposed to saline conditions. This study explored the potential of Landsat imagery in detecting and mapping saline soil in the Kano River Irrigation Scheme (KRIS).  Samples of soil were collected from thirty-nine (39) sectors of the KRIS for ground truthing on 20th – 25th April, 2020. Electrical Conductivity (EC) of field samples were correlated with band values of satellite images and salinity indices in order to determine their relationship and assess their effectiveness in predicting soil salinity. Using a geospatial approach, the data was analyzed and maps of salt-affected areas were generated. ArcGIS 10.6 was used as the primary package for modeling and running functions. The result has shown that the EC values over the entire study area are greater than 1.3 dS/m. However, the mean value of EC is approximately 1.91 dS/m. The implication is that, most of the vegetables such as Onion, Carrot, and Beans grown in the KRIS will experience yield reduction without appropriate management practice as their threshold value has been exceeded.


Abbas A. and Khan S (2007) Using remote sensing techniques for appraisal of irrigated soil salinity. In: Oxley, L. and Kulasiri, D., Eds., MODSIM 2007 International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia and New Zealand, 2632-2638.

Azabdaftari, A., & Sunar, F. (2016). Soil salinity mapping using multitemporal landsat data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(June), 3–9. DOI:

Ardahanlioglu, O., Oztas, T., Evren, S., Yilmaz, H., & Yildirim, Z. N. (2003). Spatial variability of exchangeable sodium, electrical conductivity, soil pH and boron content in salt- and sodium-affected areas of the Igdir plain (Turkey). Journal of Arid Environments, 54(3), 495–503. DOI:

Bannari, A., El-Harti, A., Guedon, A. M., Cherkaoui, F. Z., El-Ghmari, A., & Saquaque, A. (2013). Slight and moderate saline and sodic soils characterization in irrigated agricultural land using multispectral remote Sensing. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 34(30), 1–6.

Dehni, A., & Lounis, M. (2012). Remote Sensing Techniques for Salt Affected Soil Mapping : Application to the Oran Region of Algeria. 33, 188–198. DOI:

Douaoui AEK, Nicolas H, Walter C (2006) Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data. Geoderma 134:217–230 DOI:

Farifteh, J., A. Farshad and R. George (2006). "Assessing salt-affected soils using remote sensing, solute modelling, and geophysics." Geoderma 130(3): 191-206. DOI:

Francois, L.E., 1994. Yield and Quality Response of Salt-stressed Garlic. HortScience 29, 1314±1317. DOI:

Jibrin, J. M., Abubakar, S. Z., & Suleiman, A. (2008). Soil fertility status of the Kano River irrigation project area in the Sudan Savanna of Nigeria. Journal of Applied Sciences, 8(4), 692–696. DOI:

Kaledhonkar, M. J., Sharma, D. R., Tyagi, N. K., Kumar, A., & Zee, S. E. A. T. M. Van Der. (2012). Modeling for conjunctive use irrigation planning in sodic groundwater areas. Agricultural Water Management, 107, 14–22. DOI:

Khan A. and Abbas S. (2007). Remote Sensing Based Modelling Applications in Land and Water Management: Using Remote Sensing for Appraisal of Irrigated Soil Salinity. MODSIM 2007. Australia and New Zealand,.

Khan, N. M., Rastoskuev, V. V, Shalina, E. V, & Sato, Y. (2001). Mapping Salt-affected Soils Using Remote Sensing Indicators - A Simple Approach With the Use of GIS IDRISI -. (November), 5–9.

Maas, E.V., 1986. Salt tolerance of plants. Appl. Agric. Res. 1, 12 - 26.

Maas, E.V., 1990. Crop salt tolerance. In: Tanji, K.K. (Ed.), Agricultural Salinity Assessment and Management. ASCE Manuals and Reports on Engineering No. 71, ASCE, New York, pp. 262- 304.

Machado, R. M. A., & Serralheiro, R. P. (2017). Soil salinity: Effect on vegetable crop growth. Management practices to prevent and mitigate soil salinization. Horticulturae, 3(2). DOI:

Maina, M. M., Amin, M. S. M., Aimrun, W., & Asha, T. S. (2012). Evaluation of Different ET 0 Calculation Methods : A Case Study in Kano State , Nigeria. Philipine Agric. Scientist, 95(4), 378–382.

Maina, M. M., Amin, M. S. M., Aimrun, W., & Sani, I. (2012). Soil salinity assessment of Kadawa Irrigation of the Kano River Irrigation Project (KRIP). Journal of Food, Agriculture and Environment, 10(3–4), 1028–1034.

Marchuk, A. G., & Rengasamy, P. (2010). Cation ratio of soil structural stability ( CROSS ). (August), 9–11.

Mohammed D. Maina M.M., Audu I., Tudunwada I.Y and Nasiru N.K. (2021). Remote Sensing Techniques in Mapping Spatial Variability of Salinity in Kano River Irrigation Project (KRIP), Nigeria. Nigerian Journal of Technology, 2021, 40 (4), pp.732 –739. DOI:

Mohammed D, Hassan. A. I. and Amina. A. (2015). Variabilty of Irrigation Water Quality in Kano River Irrigation Project. Journal of Research in National Development, Department of Maritime Management Technology, Federal University of Technology, Owerri, Nigeria.Jorind, 12(2), 337–343.

Mohammed D., Audu I. and Igbadun H. E (2014). Variability of Irrigation Water Quality in Jakara Irrigation Scheme, Kano, A Paper Presented at 16th National Engineering Conference, held on 9th -10th December at Mohammed Dikko LectureTheatre, Kaduna Polytechnic, Kaduna.

Mohammed D., M.M. Maina, I. Audu I. Y Tudunwada, Nasiru N.K and and Umar S. E. (2021). Response Surface Regression Model for Predicting Clay Compsosition and its relationship with Selected Properties at Kano River Irrigation Scheme, Nigeria. Dutse Journal of Pure and Applied Science. Pp 14-26.

Pitt, J. L., & Provin, T. (2001). Managing Soil Salinity. Texas A & M Agrilife Extension, 60, 3–12.7(1)

Salih, S. A. R., Elsheik, M. A. M., & Aydrous, A. E. (2015). Determination of the Effect of Gypsum and Irrigation Water in Reclamation of Sodic Soils in South Khartoum. 55–57.

Sangari, D. U. (2006). An Evaluation of Water and Land Uses in the Kano River Project , Phase I , Kano State. Volume 11(2), 105–111. DOI:

Shahid, S. A. (2016). Salinity Development , 2 Soil Classification , Assessment , and Management in Irrigated Agriculture. (December 2018).

Shannon, M.C. C. and Grieve M.C. (1999). Tolerance of Vegetable Crops to Salinity, Scientia Horticulture 78 (1) 5 – 38. DOI:

Taghadosi, M. M., Hasanlou, M., & Eftekhari, K. (2019). Retrieval of soil salinity from Sentinel-2 multispectral imagery. European Journal of Remote Sensing, 52(1), 138–154. DOI:

Yildirim, A., Gorji, T., Hamzehpour, N., & Sertel, E. (2019). Comparison of Different Soil Salinity Indices Derived From Sentinel-2A Images. International Symposium on Applied Geoinformatics, (1(1)).

Zakari, M.D., Sani N.N, Sabo, A.A., Shanono, N.J., Mohammed, D.,Ahmadu S.E., Ibrahim, A.and Nasidi, N.M.(2022).Effect of Millet Chaff as Organic Ammendment on Rice Yield in Sodic Soil - A Case Study of Thomas Irrigation Scheme in Kano, Nigeria.FUDMA Journal of Sciences, 6(1), pp 68-80. 2022-0601-820. DOI:

Zare, M., Ordookhani, K., Emadi, A., & Azarpanah, A. (2014). Relationship Between Soil Exchangeable Sodium Percentage and Soil Sodium Adsorption Ratio in Marvdasht Plain , Iran. 2(12), 2934–2939.

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