Soil Erosion in Mauritius

Transcription

1 Soil Erosion in Mauritius & its mitigation by sugar cane cultivation By Suman Seeruttun & Daniel Ah Koon 5 December 2006

2 - Introduction - Soil erosion - processes & Universal Soil Loss Equation - Project - establishment of erosion Plots - Results - Soil loss - Effect of rainfall factor (R) - Effect of soil factor (K) D. Ah Koon - Effect of sugar cane - Use of data and model - Conclusion

3 SOIL EROSION a dynamic and natural process but man s activities can accelerate the process which will result in severe soil losses. a process of detachment and transport of soil particles by erosive agents. Ellison, 1944 Erosive agents: - Raindrop impact - Overland flow or surface runoff from rainfall

4 DETACHMENT Removal of soil particles from soil surface Sediment Transport Detachment (Sediment + suspended load) Soil θ

5 Deposition DEPOSITION Sediment Transport (Sediment + suspended load) Soil θ

6 TYPES OF EROSION Interrill and rill (sheet-rill) Ephemeral gully Permanent, incised (classical) gully Stream channel Mass movement Geologic

7 EROSION PREDICTION AS A TOOL Tool: Soil loss equation (USLE/RUSLE) Guide management decisions - Change in land use - EIA Evaluate impact of erosion Inventory soil erosion Conservation planning - In farm planning ( aménagement )

8 SOIL LOSS EQUATIONS USLE/RUSLE: the most widely used erosion model for agricultural land (Renard et al., 1997) Empirical Universal Soil Loss Equation (USLE): a simplified expression of a complex set of interacting variables, developed by USDA A = R K L S C P (Wischmeier and Smith, 1965 & 1978) Revised-USLE (RUSLE1): disseminated by the USDA, Agricultural Research Service (ARS) and USDA-National Resources Conservation Service (NCRS) in 1992 New version (RUSLE2): available as from January 2005 from the USDA-ARS

9 USLE/RUSLE FACTORS A = R K L S C P Average annual soil loss = tonne per hectare per year R Rainfall erosivity K - Soil erodibility L - Slope length S - Slope steepness C - Cover-management P - Supporting practices

10 EROSIVITY (R) Erosivity is: the potential ability of a rainfall to cause erosion expressed as an index based on the kinetic energy of the rain Single storm Energy x 30 minute intensity Annual-sum of daily values

11 SOIL ERODIBILITY (K) Soil erodibility factor: - the soil-loss rate per erosion index for a specified soil as measured on a standard plot standard unit plot condition: - a 72.6 ft (22.1 m) length of uniform 9% slope in continuous clean tilled fallow, up and down hill tillage

12 Slope Length Factor (LS) Length factor: a ratio which compares the soil loss with that from a field of specified length of 22.1 m Slope steepness factor: a ratio which compares the soil loss with a field of specified slope (9% slope) Detachment proportional to slope length LS (topographic) factor

13 Cover-Management (C) Cover or cropping-management factor: - the ratio of soil loss from an area with specified cover and management to soil loss from an identical area in tilled continuous fallow Examples of factors influencing C: - Vegetative community - Crop - Crop rotation - Conservation tillage - Application of surface and buried materials (mulch, manure) - Increasing random roughness

14 SUPPORTING PRACTICES (P) Conservation or support practice factor: the ratio of soil loss with a support practice to soil loss with straight-row farming up and down the slope Examples of support factors influencing P: Contouring Strip systems - Buffer, filter, strip cropping, barriers Terracing

15 RUSLE FACTORS Unit Plot Concept: A = RK LSCP RK - Unit plot soil loss (dimensions) LSCP - Adjusts unit plot soil loss (dimensionless) Standard unit plot condition (erosion plots): 72.6 ft (22.1 m) long uniform 9% slope continuous clean fallow up and down hill tillage ft ft (22.1 (22.1 m) m) Tillage Tillage Slope = 9%

16 SOIL EROSION & SUGAR CANE Sugar cane fields : > 80% of our arable land Erosion efficiently controlled due to its perennial characteristics of the crop and agronomic practices? Changes during the last decades: fields being ploughed more intensively and frequently, surface rocks removed and longer cane rows With reduction in price of sugar, some sloping lands may no longer be cultivated and land use shifted to other crops or activities??

17 HOW TO PREDICT IMPACT OF ABOVE CHANGES?? No previous work on soil erosion in Mauritius except some data for one site (Valetta) through the MSIRI/ACIAR/QDNRM project Study of soil erosion : one of the priority projects in R & D Programme Project approved by the Mauritius Research Council (MRC) for partial funding under the Unsolicited Research Grant Scheme in 2000 (Award No. MRC/RUN 008)

18 MEASUREMENT OF SOIL EROSION IN MAURITIUS & VALIDATION OF RUSLE UNDER LOCAL CONDITIONS Main objectives : - to measure soil loss in the five major soil groups (where erosion is known to occur) - to estimate values of the different parameters influencing soil erosion (e.g. soil erodibility and erosivity factors) under local conditions and validation of the RUSLE - to quantify soil erosion from sugar cane fields

19 SITES FOR EROSION PLOTS AND THEIR SOIL GROUPS Legend Isohyet (mm) Lakes/Reservoirs Other soils Soil types Latosolic Brown Forest (B) Grey Hydromorphic Soils (D) Humic Ferruginous Latosols (F) Sans Souci (F1) Humic Latosols (H) Low Humic Latosols (L1/L2) Low Humic Latosols (L3/L4) 3600 Dark Magnesium Clay (M) Latosolic Reddish Prairie (P1) Mountain Slope Complexes (S) Lithosols (T3, T4) Etoile (H2) ) 1600 Bel Ombre (L2) St Felix (S/B1) Le Val (B2)

20 CHARACTERISTICS OF THE FIVE SITES Site Soil group* Altitude (m) Average annual Rainfall (mm) Cane variety planted Date of planting Bel Ombre L R Sans Souci F M 3035/ Le Val B M 52/ St Felix S/B R Etoile H M 3035/ * Source: Parish and Feillafé (1965)

21 MEAN MONTHLY RAINFALL DISTRIBUTION (mm) AT THE FIVE SITES Rainfall (mm) ( ) Bel Ombre St Felix Le Val Sans Souci Etoile 0 Jan Feb M ar Apr M ay Jun Jul Aug Sep Oct Nov Dec Months

22 RAINFALL RUNOFF AT BEL OMBRE Rainfall Cane Plot Runoff Bare Plot Runoff Rainfall (mm) Runoff (mm) / / / /9 2-7/ / /1 1-7/3 8-12/ / /6 0 Dates

23 RUNOFF AND SOIL LOSS AT BEL OMBRE Soil loss (tha -1 ) Runoff (mm) Date Soil loss Run off

24 RUNOFF AND SOIL LOSS AT SANS SOUCI Soil loss (t/h (tha -1 ) Runoff off (mm) Date Soil loss Run off

25 RUNOFF AND SOIL LOSS AT LE VAL Soil loss Soil (tha loss -1 )(t/h Runoff (mm) off (mm 1-7/07/ /09/ /01/ /03/ /04/ /06/ /02/ /03/ /04/ /12/ /03/ /03/2005 Date Soil loss Run off

26 RUNOFF AND SOIL LOSS AT ST FELIX Soil loss Soil (tha loss -1 (t/h ) Runoff (mm) off (mm 1-6/01/ /01/ /02/ /02/ /12/ /03/ /03/2005 Date Soil loss Run off

27 RUNOFF AND SOIL LOSS AT ETOILE Soil loss (tha -1 ) Soil loss (t/h 3 2,5 2 1,5 1 0, /01/ /02/ /04/04 Date 0,4 0,3 0,2 0,1 0 Runoff (mm) Run off (mm Soil loss Run off

28 NUMBER OF MAJOR (SOIL EROSION) EVENTS AT THE FIVE SITES Periods Bel Ombre Sans Souci Le Val St Felix Etoile July June July June July June July June July June

29 Cyclone CYCLONIC EVENTS CAUSING SOIL LOSS AT THE DIFFERENT SITES Date Bel Ombre Sans Souci Le Val St Felix Etoile Cyprien 1 2 Jan 02 * * * Dina Jan 02 * * * * * Ikala Mar 02 * Gerry 8-15 Feb 03 * * * * * Kalunde 8-16 Mar 03 * * * Manou 3-10 May 03 * * * Darius 2 Jan 04 * * Hennie 24 Mar 05 * * * * Diva * Soil loss 3-5 Mar 06 * * * N/a N/a

30 ANNUAL SOIL LOSS FROM BARE PLOTS (t ha-1 yr-1) Periods Bel Ombre Sans Souci Le Val St Felix Etoile July 01- June July 02- June July 03- June July 04- June July 05- June * Mean ** * soil loss relatively low as weeds were present during major event ** Mean of four years ( )

31 AMOUNT OF SOIL EROSION AS SUSPENDED LOAD (% OF TOTAL SOIL LOSS) Periods Bel Ombre Sans Souci Le Val St Felix Etoile July 01-June July 02-June July 03- June July 04- June Mean

32 AMOUNT OF SOIL EROSION ASSOCIATED WITH CYCLONIC EVENTS (% OF TOTAL LOSS) Periods Bel Ombre Sans Souci Le Val St Felix Etoile July June July June July June July June July June

33 EFFECT OF RAINFALL FACTOR (R) ON SOIL EROSION The erosivity of a rainstorm is a function of its intensity and duration. According to Wischmeier and Smith (1978), KE = log 10 I where KE = kinetic energy (J/m 2 /mm) I = rainfall intensity (mm/hr) 1. Energy per minute = KE x amount of rain (per minute) 2. Total amount of energy for storm = Σ1 3. Determine I 30 ; highest intensity in a 30 minutes period 4. Erosivity index (EI 30 ) = 2 x 3 5. Sum individual storm EI 30 to obtain annual value

34 EROSIVITY INDICES CALCULATED FROM ENERGY VALUES OF RAINFALL DURING EVENTS Periods Bel Ombre Sans Souci Le Val St Felix Etoile July June July June July June July June Mean

35 RAINFALL INTENSITY AND AMOUNT JULY 2001 TO JUNE 2002 Rainfall (mm Rainfall (mm) Bel ombre Sans souci Le Val St felix Etoile < >76 intensity (m m/hr)

36 INFLUENCE OF CYCLONES ON EROSIVITY INDEX Site Non cyclonic Cyclonic Bel Ombre Sans Souci Le Val St Felix Etoile

37 SOIL CLASSIFICATION Mature soils (Latosols) Low Humic Immature soils (Latosolic) Reddish Prairie INCREASING RAINFALL Humic Humic Ferruginous Brown Forest INCREASING AGE

38 ERODIBILITY Erodibility: resistance of the soil to both detachment and transport Erodibility varies with: Soil texture Aggregate stability Shear strength Infiltration capacity Organic and mineral content

39 SIMPLE INDEX FOR ERODIBILITY K value of the USLE Represents the soil loss per unit of EI 30, as measured in the field on a standard bare soil plot, 22.1 m long and of 9% slope

40 Determination techniques Technique USLE nomograph Remark Estimation Rainfall simulator Measurement under artificial conditions Erosion plot Measurement under field conditions

41 THE USLE NOMOGRAPH TECHNIQUE K factor estimated using: Particle size distribution Organic matter content Soil structure Permeability

42 1. Enter scale at left: % silt + very fine sand 2. Proceed to point representing % sand 3. Move up to point representing % SOM 4. Move across to soil structure class 5. Finish with permeability class 6. Estimated K value The USLE nomograph technique

43 NOMOGRAPH K VALUES Site Bel Ombre Sans Souci Le Val St Félix Etoile Soil group L2 F1 B2 S/B1 H2 K value

44 Maximum SOM = 4%

45 Site Bel Ombre Sans Souci Le Val St Félix Etoile SOM CONTENT Soil group L2 F1 B2 S/B1 H2 % OM Only Bel Ombre soil within range

46 Nomograph overestimates K values because SOM content of soils are much higher than maximum nomograph value of 4%

47 THE RAINFALL SIMULATOR TECHNIQUE Produce storms of known intensity and duration Can be repeated on demand Most important design requirement: - drop-size distribution - drop velocity at impact - intensity of natural rainfall with uniform spatial distribution

48 RAINFALL SIMULATOR Tests conducted on bare plots after the end of the rainy season Tests possible only at three sites: Bel Ombre, Sans Souci and Le Val Application intensities varied between about 50 and 200 mm/hr

49 K VALUES WITH RAINFALL SIMULATOR Site Bel Ombre Sans Souci Le Val K value

50 EROSION PLOT K value: calculated on annual basis from rainfall erosivity & soil erosion data A = R x K x LS x C x P A = R x K K = A R

51 ANNUAL SOIL LOSS FROM BARE PLOTS (t ha -1 yr -1 ) Periods Bel Ombre Sans Souci Le Val St Felix Etoile July 01- June July 02- June July 03- June July 04- June July 05- June * Mean ** * soil loss relatively low as weeds were present during major event ** Mean of four years ( )

52 EROSIVITY INDICES CALCULATED FROM ENERGY VALUES OF RAINFALL DURING EVENTS Periods Bel Ombre Sans Souci Le Val St Felix Etoile July June July June July June July June Mean

53 K VALUE FROM EROSION PLOTS Period Bel Ombre Sans Souci Le Val St Félix Etoile 7/01 6/ /02 6/ /03 6/ /04 6/ Weighted average

54 K VALUE FROM DIFFERENT TECHNIQUES Bel Ombre Sans Souci Le Val St Félix Etoile Nomograph Rainfall simulator Erosion plot

55 CONCLUSIONS (SOIL ERODIBILITY) 1. Erodibility is site-specific and varies according to soil group 2. Most reliable erodibility values are those obtained from erosion plots 3. Erodibility highest in L soil at Bel Ombre (0.14) on account of its low OM content

56 SOIL LOSS FROM THE CANE PLOT AT 5 SITES Annual Soil Loss (t/ha) Periods Bel Ombre Sans Souci Le Val St Felix Etoile Jul 01 Jun Jul 02 Jun Jul 03 Jun Jul 04 Jun Jul 05 Jun Mean % of Bare Plot

57 COVER-MANAGEMENT FACTOR (C) FOR SUGAR CANE A = R K LS C P A = R K C C = A / RK

58 COVER-MANAGEMENT FACTOR (C) FOR SUGAR CANE AT FIVE SITES Periods Bel Ombre Sans Souci Le Val St Felix Etoile July June July June July June July June Mean

59 USE OF USLE/RUSLE MODEL Example 1 : Predict soil erosion Standard Erosion Plot Site : Bel Ombre Variety : - Row length : 22.1 m Field slope : 9 % Soil erodibility K : 0.14 Erosivity index R : 277 Cover-mang. C : bare Support pract. P : 1 Field Situation Site : Bel Ombre Variety : R 570 Row length : 60 m Field slope : 20 % Soil erodibility K : 0.14 Erosivity index R : 277 Cover-mang. C : 0.07 Support pract. P : contour planting A = R x K x LS x C x P = 277 x 0.14 x 1 x 1 x 1 = 38.8 t ha -1 yr -1 A = R x K x LS x C x P = 277 x 0.14 x 5.9 x 0.07 x 0.8 = 12.8 t ha -1 yr -1

60 Use of USLE/RUSLE model Example 2 : Change in cane row length Site : Sans Souci Variety : M 3035/66 Site : Sans Souci Variety : M 3035/66 Row length : 100 m Field slope : 8 % Soil erodibility K : 0.05 Erosivity index R : 245 Cover-mang. C : 0.21 Row length : 300 m Field slope : 8 % Soil erodibility K : 0.05 Erosivity index R : 245 Cover-mang. C : 0.21 A = R x K x LS x C x P = 245 x 0.05 x 1.8 x 0.21 x 1 = 4.6 t ha -1 yr -1 A = R x K x LS x C x P = 245 x 0.05 x 3.2 x 0.21 x 1 = 8.2 t ha -1 yr -1

61 Use of USLE/RUSLE model Example 3 : Change in land use; e.g. palm Sugar Cane Site : Bel Ombre Variety : R 570 Row length : 60 m Field slope : 20 % Soil erodibility K : 0.14 Erosivity index R : 277 Cover-mang. C : 0.07 Support pract. P : 0.8 Palm (with cover crop) Site : Bel Ombre Variety : Row length : 60 m Field slope : 20 % Soil erodibility K : 0.14 Erosivity index R : 277 Cover-mang. C : Support pract. P : A = R x K x LS x C x P A = R x K x LS x C x P = 277 x 0.14 x 5.9 x 0.07 x 0.8 = 277 x 0.14 x 5.9 x 0.1 x 1 = 12.8 t ha -1 yr -1 = 18.8 t ha -1 yr -1 C for pineapple = , bananas =

62 OTHER APPLICATIONS OF MODEL 1. Modelling, using GIS, to identify high erosion risk areas; e.g. to develop an erosion risk map for Mauritius 2. To design soil conservation measures where soil loss exceeds soil loss tolerance value 3. Training of stake-holders (farmers, extension officers, operators of land preparation equipment, etc) 4. Indicate the need for any legislation w.r.t. soil erosion and conservation practices; fines for non-respect of good practices

63 Conclusions Soil erosion varied significantly across sites and year. Highest soil loss (bare plots) recorded at Bel Ombre and followed by Sans Souci, Le Val, St Félix and Etoile with a mean of 37.6, 14.3, 9.5, 4.1 and 0.5 t ha -1 yr -1 respectively. Irrespective of year, the worst erosion measured from bare plot was at Bel Ombre (59 t ha -1 ) recorded during the period July 2004 and June 2005 Soil erosion associated with cyclonic events varied between 45% and 68% depending on sites The most important factors influencing erosion were soil erodibility and rainfall erosivity. Rainfall erosivity factor (R) varied across sites. Bel Ombre and Sans Souci have an erosivity factor of approximately 250, Le Val and St Félix of about 150, and Etoile with 41. A R-value of 300 (worst-case scenario) may be used to predict soil erosion in other parts of the island

64 Conclusions (contd.) Calculated soil erodibility factors (K) : 0.14, 0.05, 0.08, 0.03 and 0.01 for Bel Ombre, Sans Souci, Le Val, St Félix and Etoile respectively The use of nomograph & a rainfall simulator to determine the soil erodibility (K) factor was found inappropriate Sugar cane reduced soil erosion by 80% to 99% depending on cane varieties and their stage of growth. Var R 570 more effective than var M 3035/66 Main factors determined in this project may be used to predict and minimise soil erosion in Mauritius through development and adoption of good conservation practices.

65 Acknowledgements - MRC for partial funding of project - Sugar Estates: Bel Ombre, FUEL, Rose Belle, St Felix and Beau Champ - MSIRI: - Director - Mr. M. Rughoo - Colleagues of COWA and Irrigation Depts. - Workshop and Field Officers