Evaluating the Impacts of Land Degradation on the Quality of Soils and Their Variations between Different Clusters in Mosiro Irrigation Scheme, Narok County, Kenya
Edward Mare Muya *
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
Violet Kirigua
Kenya Agricultural and Livestock Research Headquarters, P.O.Box 57811-00800, Nairobi
Victor Wasike
Kenya Agricultural and Livestock Research Headquarters, P.O.Box 57811-00800, Nairobi.
Leonard Simiyu Nafuma
KARLO-Njoro, P.O. Njoro, Kenya.
Esther Macharia
KARLO-Njoro, P.O. Njoro, Kenya.
Elias Gitonga Thuranira
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
Peter Onyango Owenga
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
Haron Goro
Small Scale Horticultural Development Project, Ministry of Agriculture, Livestock and Fisheries, P.O.Box 30028-00200, Nairobi, Kenya.
Benard Kariuki Waruru
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
Alla Lusi Chek
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
Jeremiah Kimigo
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
Peter Mbindio Maingi
Kenya Agricultural and Livestock Research Organization (KARLO), Food Crop Research Institute, P.O.Box 14733, Nairobi, Kenya.
*Author to whom correspondence should be addressed.
Abstract
Aims: To study the impact of land degradation on soil quality
Study Design: Comparative analysis of soil quality indicators in year 2002 and 2013 in Mosiro Irrigation Scheme.
Methodology: Changes in soil indicators determined in 2002 and 2013 were analyzed using ANOVA at 95% confidence level through Genstat Computer Software. The same indicators were applied to identify and characterize different clusters whose degree of variations were analysed using the same statistical method.
Results: The results showed that all the soil quality attributes changed in the range of 21.4 and 79.1%. The greatest change was recorded in potassium which decreased by 79.1%, followed by phosphorous (60% decrease).
The increase in sodium by 47% had a negative implication in terms of its increased potential to cause soil structural deterioration, while the increase of soil pH from 6.74 to 8.18 implied increased tendency of soil to fix most of the nutrients rendering them unavailable to plants. The soil organic carbon, nitrogen, phosphorous and potassium decreased by over 20%, which is much higher than the permissible threshold of 5% in ten years. The variations in soil characteristics between the five clusters identified were found to be significant for: cation exchange capacity (P=0.002), magnesium (P=0.003) and bulk density (P=0.01). There was no significant difference for calcium (P=0.147). All the textural characteristics of soil vary significantly with the highest being clay content (P=0.001), followed by silt (P=0.0018) and sand (P=0.008). For the micro-nutrients, the variation of manganese (P<0.001), zinc (P=0.003), copper (P=0.008) and iron (P=0.031) between different clusters was found to be significant.
Conclusion: Because the variations between different clusters in terms of both physical and chemical soil quality attributes was found to be significant except for calcium, each cluster must have different irrigation schedules and fertilizer inputs (except for calcium). This should form an important consideration in designing the irrigation water supply scheduling for all the clusters. Similarly, the prescription of the quantity of the micro-nutrients to apply should be clusters-specific. This is because the blanket recommendations across the clusters, where variations in terms of the levels of micro-nutrients are significant, would result into lower fertilizer use efficiency.
Keywords: Land degradation, soil quality, clusters and productivity