Contribution of rainfall erosivity, sil cover and organic carbon to soil loss and run-off under CA in Zimbabwe. Isaiah Nyagumbo
Contribution of Rainfall Erosivity, Soil Cover and Organic Carbon to Soil loss and Run-off under Conservation Agriculture in Zimbabwe Isaiah Nyagumbo CIMMYT: Conservation Agriculture Programme Southern Africa Regional Office, Harare firstname.lastname@example.org World Congress On Conservation Agriculture Brisbane, Australia 26-29th September 2011
1. Introduction● Soil Erosion is generally known to be a function of 4 physical factors:● Vegetation (cover amount and type)● Soil (erodibility itself a function of texture, depth, carbon, infiltration etc.)● Topography (slope and slope length)● Climate (Rainfall erosivity)SoSoil loss = f (Soil, Cover,Topography, Erosivity)
Effects of soil carbon on soil loss and run-off using laboratoryrainfall simulation (Elwell, 1986)
Introduction cont’d....● Due to the high cost and large time scales associated with establishing the importance of these factors soil loss models are often used such as the USLE (Wischmeier, 1976) and in Southern Africa the Soil loss estimation Model for Southern Africa (SLEMSA ) is used Z= KCX Where K is the soil erodibility factor, C is the crop cover sub-model, X is the topographic factor● Soil loss targets for Zim: 3-5t/ha/yr● Unfortunately few studies in Southern Africa have attempted to quantify the influence of these erosion factors in a CA system
Objective● To evaluate the relative importance of rainfall energy (erosivity), soil cover and soil organic carbon on annual soil loss and run-off under conventional mouldboard ploughing and Conservation Agriculture systems on a Fersiallitic Red clay soil in Zimbabwe
2. Materials and Methods● Studies carried out at the Institute of Agric Eng, Hatcliffe, Harare over 3 seasons on rectangular plots 30x 10 m at 4.5% slope● Soils: Deep well drained red clay Fersiallitic soils● Rainfall erosivity determined from rainfall intensities (autographic raingauge) using Hudson Index● KE = 29.8 – 127.5/I I= 10-min rain intensity and KE> 25 (only storms with intensities greater than 25 mm/hr considered) Total storm KE= KE* Rainfall amount● Soil loss and run-off measuredfrom conical tanks and collectiontroughs at the lower end of each plot
Tillage Systems tested1. Conventional mouldboard ploughing Only involved reduced soil disturbance and permanent soil 2.Conservation Agriculture ( Mulch Ripping) cover. Rotation not practised 7
Methods cont’d● 2 treatments implemented in a completely randomized design with 3 replicates● Measurements conducted over 3 consecutive seasons 93/4 to 95/6.● Data analysed using ANOVA and multiple regression statistical tools
Soil Cover changes over time by tillage system over3 season at Hatcliffe, HarareCA provided much higher soil cover compared to CMP throughout the croppingseasons with a significantly different (p<0.001) seasonal mean of 57compared to 41 % Note: Error bars denote +/- SE of mean
Rainfall energy per unit amount of cover was highest under under CMPat the start of each season thereby providing an opportunity forgeneration of high levels of soil loss and runoff in CMP. The residuecover in CA dissipated most of this energy
Cumulative soil loss (kg/ha) comparing CA and conventionalmouldboard ploughing over 3 seasons at Hatcliffe, Harare Av CMP-cum.soil loss (kg/ha) MR-avg-cum.soil loss (kg/ha) 120 6000 Total rainfall = 481 mm Total rainfall = 957 mm Total rainfall = 774 mm Total Erosivity = 9694 J/m2 Total Erosivity = 13 919 J/m2 Total Erosivity = 9647 J/m2 100 5000 80 4000Daily rainfall (mm) soil loss target= 3.5t/ha/yr 60 3000 40 2000 20 1000 0 0 10-Oct-93 10-Jan-94 10-Apr-94 10-Jul-94 10-Oct-94 10-Jan-95 10-Apr-95 10-Jul-95 10-Oct-95 10-Jan-96 10-Apr-96 Date
Effects of Rainfall erosivity on Soil loss (kg/ha)at Hatcliffe, Harare under CA and CMP systems over 3 cropping seasons NB: Relationships significantly different (p<0.001) 1200 CMP-Soil loss kg/ha MR-Soil loss kg/ha 1000 800 Z (CMP)= 0.5691x - 21.007Soil loss (kg/ha) N= 567; R² = 0.7988 **** 600 400 200 Z (MR) = 0.0512x - 2.9053 N=567; R² = 0.5961 *** 0 0 200 400 600 800 1000 1200 1400 1600 Rainfall erosivity (J/m2)
Soil loss multiple regression summary Soil loss ConventionalEstimated Mouldboard Conservation Is CA factor significantly diffParameters ploughing Agriculture from CMP? Est. t- Est. t- Coeff value t-prob Coeff value tprobRainfall 0.576 36.91 <0.001 0.055 22.92 <0.001 <0.001 ***EnergySoil Cover % -1.10 -7.62 <0.001 -0.12 -6.33 <0.001 <0.001 ***Soil carbon 0.5 0.01 0.99 1.50 0.13 0.893 0.987 n.sTop soil moist 1.63 2.92 0.004 -0.04 -0.42 0.675 0.003 ** Overall Multiple regression: Significant at p<0.001; R2 = 0.798Comments:(1) Soil loss mostly influenced by Rainfall Energy and soil cover for both CMP and CA(2) Top Soil Moisture content significant for CMP but not for CA and a signifcant difference in behaviour between the two is observed. For CMP soil loss increased with increase in moisture but not for CA.(3) In both cases Soil Organic Carbon (ranged 9.9 to 12mg-C/g soil) did not
Effects of CA and Conventional Mouldboard Ploughing on cumulative runoff in 3consecutive seasons at Hatcliffe 120 Total rainfall 774 mm Total rainfall 481 mm Total rainfall 956 mm Rainfall (mm)Cummulative run-off or Daily Rainfall (mm) 100 Av CMP-cum.runoff(mm) Av-MR-cum.runoff(mm) 80 60 40 20 0Error bars denote +/- SE of meanTotal seasonal run-off amounted to 7.4,16 and 8.1 % of seasonal rainfall for CMPcompared to 0.5, 0.8 and 0.6 % for CA over the 3 seasons
Runoff multiple regression summary Run-offEstimated Conventional Mouldboard Is CA factor significantly diffParameters ploughing Conservation Agriculture from CMP? Est. Coeff t-value t-prob Est. Coeff t-value tprobConstant 0.07 0.16 0.871 -0.027 -0.22 0.828 0.916 n.SRainfall Energy 0.009 65.87 <0.001 0.0006 27.25 <0.001 <0.001 ***Soil Cover % -0.0075 -5.83 <0.001 -0.001 -7.29 <0.001 <0.001 ***Soil org. carbon 0.266 0.67 0.501 0.047 0.47 0.64 0.779 n.sTop soil moisturecontent -0.0196 -3.96 <0.001 0.0004 0.50 0.619 0.004 ** Overall Multiple regression: Significant at p<0.001; R2 = 0.862 Comments: (1) Runoff followed same trend as soil loss being mostly influenced by Rainfall Energy and soil cover for both CMP and CA (2) Top Soil Moisture content also significant for CMP and not significant for CA (3) In both systems Soil Organic carbon did not significantly influence runoff.
Discussion● Dissipation of rainfall energy due mulching in CA systems contributes to taming the erosive power of tropical rainstorms● In the presence of a good residue cover, soil moisture status and organic carbon become irrelevant or unimportant drivers for soil loss and runoff in CA but remain important determinants for run-off and soil loss in Conventional ploughing.● Although few studies compare the relative importance of these factors, similar reductions in soil loss and runoff from CA are widespread in literature (Contill, 1998) and more recently from Ethiopia (Araya, et al, 2011)
Discussion cont’d.....● This suggests that with application of a good residue cover, degradation on soils with low organic carbon may be effectively controlled although SOC remains important in other soil quality attributes such as soil water storage (Nyagumbo,2002).● From a conservation point of view the results obtained also emphasize the importance of residue cover even in clay soils in contrast to Chivenge, et al 2007 who suggest that optimization of SOC and sustainability can be focussed more on reduced soil disturbance and less on C inputs in clay soils!
4. Conclusion & Recommendations● The most important soil loss and run-off factors were rainfall erosivity, soil cover and antecedent soil moisture. In CA this erosivity is easily dissipated by the mulch cover.● The presence of a good mulch cover in CA overrides and nullifies the contribution of other erosion factors such as SOC and moisture to soil loss and run-off.● In contrast to CA, significant amounts of sheet erosion in conventional systems occur at the start of the season and still progressively continue with time even if the crop builds up appreciable canopy cover.
Conclusion & Recommendations cont’d● Results obtained here re-emphasize the need for developing innovative ways for soil cover provision in CA systems under these tropical conditions given the challenges of livestock competition for residues and low biomass production
5. Acknowledgements● GTZ for the financial support to this research work● Government of Zimbabwe for the research sites and personnel manning the station throughout the study period● Victor Mateveke (a University of Zimbabwe student) who assisted in the initial data capturing and compilations.