Assessment of soil erosion indicators for maize-based agro-ecosystems in Kenya

Abstract

Measuring soil loss is costly, must cover a range of field situations, is not standardized, and is season dependent. In addition, use of sparse soil loss data (from other studies) compromises the integrity of many erosion models. Easily assessable soil erosion indicators to monitor the cumulative effect of erosion between tillage/weeding and harvesting called eroding clods, flow surfaces, pre-rills, and rills were surveyed directly after the 1995 rainy season in the Taita Taveta district of Kenya, to assessed the utility of each indicator. Their incidences were modeled using CPA. In the area, 70 maize plots in 11 map units, having considerable variation in altitude, land cover, rainfall, and geomorphology, were surveyed. Soil loss was considered variable between plots due to differences in surface soil, land cover, infrastructure (trash lines, grass strips, and Fanya-juu), crop management, slope, and map unit. The eroding clods indicator proved of little significance because the initial clods cover was unknown; the indicator probably relates better to soil erodibility then to soil loss. Flow surfaces, formed during erosive showers, were less present on fields with a higher ground and canopy cover, if the area of eroding clods was high, and if the topsoil had no loam which reduces chances of sealing; no impact of infrastructure, tillage, and weeding were detected. Fewer pre-rills were present where the fraction of groundcover was high, where Pigeon Peas were not grown (they cause micro-relief and concentrated flows), where weeding ended late (time effect), where more flow surfaces occurred, where Fanya-juu was constructed (less steep slopes), where the top-soil contained little sand (less sediment entrainment), and where maize was intercropped with vegetables (positive canopy cover effects). The model was not map unit specific and had an Adjusted R 2 of 67%. The log-linear relationship indicates that combined positive conditions exponentially reduce the occurrence of pre-rills. The “pre-rill” indicator related best to management-affected site conditions and seems to reflect best the cumulative effects of soil loss over time. Rills were found at 18 sites located in drier areas on sandy–clay soils. The model suggested more rills if the topsoil contains no silt; this makes the soil susceptible to compaction, peptisation when wet, and rill formation.