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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
                   i.nyagumbo@cgiar.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)
So
Soil loss = f (Soil, Cover,Topography, Erosivity)
Effects of soil carbon on soil loss and run-off using laboratory
rainfall 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 measured
from conical tanks and collection
troughs at the lower end of each plot
Tillage Systems tested
1. 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
3. Results and Discussions
Soil Cover changes over time by tillage system over
3 season at Hatcliffe, Harare
CA provided much higher soil cover compared to CMP throughout the cropping
seasons with a significantly different (p<0.001) seasonal mean of 57
compared to 41 %




                                                                 Note:
                                                                 Error bars
                                                                 denote +/-
                                                                 SE of
                                                                 mean
Rainfall energy per unit amount of cover was highest under under CMP
at the start of each season thereby providing an opportunity for
generation of high levels of soil loss and runoff in CMP. The residue
cover in CA dissipated most of this energy
Cumulative soil loss (kg/ha) comparing CA and conventional
mouldboard 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                                                                                                                                         4000
Daily 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 - 21.007
Soil 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
                      Conventional
Estimated             Mouldboard               Conservation        Is CA factor significantly diff
Parameters             ploughing                Agriculture                 from CMP?
                 Est.    t-               Est.    t-
                 Coeff value t-prob       Coeff value tprob
Rainfall
                 0.576   36.91 <0.001     0.055   22.92 <0.001            <0.001            ***
Energy
Soil 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.s


Top 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 = 0.798
Comments:
(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 3
consecutive 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


                                               0




Error bars denote +/- SE of mean

Total seasonal run-off amounted to 7.4,16 and 8.1 % of seasonal rainfall for CMP
compared to 0.5, 0.8 and 0.6 % for CA over the 3 seasons
Runoff multiple regression summary
                                                 Run-off
Estimated            Conventional Mouldboard                                     Is CA factor significantly diff
Parameters                   ploughing           Conservation Agriculture                 from CMP?
                    Est. Coeff t-value t-prob Est. Coeff t-value tprob
Constant                  0.07 0.16 0.871           -0.027 -0.22 0.828                 0.916            n.S
Rainfall 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.s
Top soil moisture
content               -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.
Thank you!

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Contribution of rainfall erosivity, sil cover and organic carbon to soil loss and run-off under CA in Zimbabwe. Isaiah Nyagumbo

  • 1. 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 i.nyagumbo@cgiar.org World Congress On Conservation Agriculture Brisbane, Australia 26-29th September 2011
  • 2. 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) So Soil loss = f (Soil, Cover,Topography, Erosivity)
  • 3. Effects of soil carbon on soil loss and run-off using laboratory rainfall simulation (Elwell, 1986)
  • 4. 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
  • 5. 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
  • 6. 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 measured from conical tanks and collection troughs at the lower end of each plot
  • 7. Tillage Systems tested 1. Conventional mouldboard ploughing Only involved reduced soil disturbance and permanent soil 2.Conservation Agriculture ( Mulch Ripping) cover. Rotation not practised 7
  • 8. 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
  • 9. 3. Results and Discussions
  • 10. Soil Cover changes over time by tillage system over 3 season at Hatcliffe, Harare CA provided much higher soil cover compared to CMP throughout the cropping seasons with a significantly different (p<0.001) seasonal mean of 57 compared to 41 % Note: Error bars denote +/- SE of mean
  • 11. Rainfall energy per unit amount of cover was highest under under CMP at the start of each season thereby providing an opportunity for generation of high levels of soil loss and runoff in CMP. The residue cover in CA dissipated most of this energy
  • 12. Cumulative soil loss (kg/ha) comparing CA and conventional mouldboard 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 4000 Daily 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
  • 13. 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 - 21.007 Soil 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)
  • 14. Soil loss multiple regression summary Soil loss Conventional Estimated Mouldboard Conservation Is CA factor significantly diff Parameters ploughing Agriculture from CMP? Est. t- Est. t- Coeff value t-prob Coeff value tprob Rainfall 0.576 36.91 <0.001 0.055 22.92 <0.001 <0.001 *** Energy Soil 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.s Top 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 = 0.798 Comments: (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
  • 15. Effects of CA and Conventional Mouldboard Ploughing on cumulative runoff in 3 consecutive 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 0 Error bars denote +/- SE of mean Total seasonal run-off amounted to 7.4,16 and 8.1 % of seasonal rainfall for CMP compared to 0.5, 0.8 and 0.6 % for CA over the 3 seasons
  • 16. Runoff multiple regression summary Run-off Estimated Conventional Mouldboard Is CA factor significantly diff Parameters ploughing Conservation Agriculture from CMP? Est. Coeff t-value t-prob Est. Coeff t-value tprob Constant 0.07 0.16 0.871 -0.027 -0.22 0.828 0.916 n.S Rainfall 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.s Top soil moisture content -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.
  • 17. 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)
  • 18. 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!
  • 19. 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.
  • 20. 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
  • 21. 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.