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FINAL REPORT Volume III: Annexes

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FINAL REPORT Volume III: Annexes No. Ministry of Agriculture and Fisheries (MAF) Government of the Democratic Republic of Timor-Leste THE STUDY ON COMMUNITY-BASED INTEGRATED WATERSHED MANAGEMENT IN LACLO AND COMORO RIVER BASINS IN THE DEMOCRATIC REPUBLIC OF TIMOR-LESTE FINAL REPORT Volume III: Annexes MARCH 2010 JAPAN INTERNATIONAL COOPERATION AGENCY Nippon Koei Co., Ltd. GED JR 10-039 THE STUDY ON COMMUNITY-BASED INTEGRATED FINAL REPORT WATERSHED MANAGEMENT IN LACLO AND COMORO RIVER March 2010 Volume III: Annexes BASINS IN THE DEMOCRATIC REPUBLIC OF TIMOR-LESTE Community-based Integrated Watershed Management in Laclo and Comoro River Basins in the Democratic Republic of Timor-Leste Composition of Final Report Volume I Main Report Volume II Watershed Management Planning Guidelines Volume III Annexes Community-based Integrated Watershed Management in Laclo and Comoro River Basins in the Democratic Republic of Timor-Leste List of Annexes Annex A Estimation of Erosion Potentials Annex B Result of Market Survey Annex C Typical Designs for Proposed Countermeasures of Slope Protection and Sediment Control Sub-program Annex D Detailed Work Plans for the Sub-programs Annex E Implementation Schedules of the Sub-programs in the Watershed Management Plan Annex F Estimated Costs of the Sub-programs in the Watershed Management Plan Annex G Results of RRA Survey at the Target Villages Annex H Operation Guidelines for the Pilot Project Monitoring Team under the JICA Study Annex I Results of Evaluation of the Pilot Projects Draft Final Report Volume III i Annex‐A Estimation of Erosion Potential Appendix-A Estimation of Erosion Potentials 1. General In order to estimate and compare the potential of the soil surface erosion in the watersheds, the Universal Soil Loss Equation (USLE) method was applied. USLE is a model that predicts long-term average annual rate of erosion on a field slope based on the rainfall pattern, soil type, topography, crop system and management practice. USLE can only predict the amount of the soil loss that results from sheet or rill erosion on a single slope and does not account for additional losses that might occur from gully erosion, wind or tillage erosion. Since data and information required for the USLE was not available in the country, USLE estimation was made on several assumptions. 2. Procedure for Using USLE (1) Formula of USLE The Formula of USLE is shown below: A=R×K×L×S×C×P (unit : t/ha/year) where, A : Average annual soil loss R : Rainfall erosivity factor K : Soil erodibility factor L : Slope length factor S : Slope steepness factor C : Crop and management factor P : Support practice/Erosion Control factor Soil loss was calculated by the formula for each cell of grid of 0.9ha (30m×30m) using the ArcGIS software. (2) Determination of Values for each Factor 1) Rainfall erosivity factor (R) The rain erosivity index (REI) is employed as the rain erosivity factor. The REI was calculated by the following formula used by the Ministry of Forestry in Indonesia. 12 Re = 2.21 × Ri1.36 i1 where, Re: Rain Erosivity Index Ri: Monthly rainfall (cm) i : Month (January to December) The Monthly rainfall data was obtained from the monthly rainfall map complied by ALGIS. 2) Soil erodiblity factor (K) K factor depends on the characteristics of soil. According to the result of the field survey and soil survey conducted by AusAID in 2002-3, that indicates the texture of soil samples A-1 from Aileu district are categorized as sandy loam, clay and clay loam1, the K value for watersheds was determined as 0.22. 3) Slope Length factor (L) Slope Length factor (L) is calculated based on the following equation. L = / 22.1 where, : slope length In this calculation, the slope length was classified into 6 classes based on the present condition as following table. Slope Length for Classified Land Uses Land use Slope Length (m)/Slope (%) (1) Coffee plantation, paddy field and Settlement area a) class-1 8 m / 0-8% b) class-2 8 m / 8-15% c) class-3 4 m / 15-25% d) class-4 3 m / 25-40% e) class-5 2 m / over 40 % (2) Others 50 m Source: JICA Study Team 4) Slope Steepness factor (S) Slope Steepness factor was calculated by the formula as shown below. S = (65.41 sin2θ+ 4.56θ+ 0.065) where, θ: slope steepness Slope steepness data was acquired from the satellite elevation data. The steepness values of 50% in gradient is applied for all the slope with a steepness over 50%. 5) Cover and Management factor (C) Cover and Management factor is based on the type and condition of vegetation and crops. Therefore, the factor was determined in accordance with the categories of the Land-use and vegetation map (shown as Figure 3.8) as shown below. Value of C factor in the watersheds Type of Land use C factor 1. Forests 1-1: Dense forest (natural) 0.01 1-2: Medium forest (natural) 0.50 1-3: Sparse forest (natural) 0.50 2. Shrub land 0.02 3. Grassland (including grazing lands and upland farms） 0.02 4. Coffee plantation 0.01 5. Bare land (including grazing lands and upland farms） 1.00 6. Sandbar/River bed 0.00 7. Paddy field 0.05 8. Settlements 0.10 Source: JICA Study Team 1 Working Report, Mr.Kimio Miura/JICA Agricultural Policy Advisor,2005 A-2 6) Support Practice / Erosion Control factor (P) P factor indicates the effectiveness of soil conservation works (e.g., Terracing work, contour cropping, etc) introduced in the site. Due to the lack of the data, the assumption value was decided by type of Land-use and Vegetation as the following table. Value of P factor in the watersheds Type of Land use P factor 1. Forests 1-1: Dense forest (natural) 1.00 1-2: Medium forest (natural) 1.00 1-3: Sparse forest (natural) 1.00 2. Shrub land 1.00 3. Grassland (including grazing lands and upland farms） 1.00 4. Coffee plantation 0.80 5. Bare land (including grazing lands and upland farms） 1.00 6. Sandbar/River bed 1.00 7. Paddy field 0.02 8. Settlements 1.00 Source: JICA Study Team 3. Result of USLE The average annual soil loss was calculated by using USLE under the above conditions. It is difficult to directly evaluate the values/data of the estimated soil erosion potentials since they are the results of the rough estimation without any field validation and reliable data/value as calculation factors. Therefore, in order to make the relative evaluation of the results of USLE, the values/data of the estimation were classified into five (5) classes, namely, i) severe, ii) high, iii) moderate, iv) low, and v) very low. Five-grading classification method was employed by splitting the total range of the data into five classes as shown below. Criteria for evaluation of potential of soil erosion Potential level Very low Low Moderate High Severe Estimated amount of annual soil loss by USLE calculation 0-250 250-500 500-750 750-1,000 1,000- (t/ha/yr) Source: JICA Study Team In accordance with the result of USLE calculation for grid as shown in the Attachment 1, the erosion potentials is estimated by administrative unit and sub-watershed. Results of the estimation were used for the assessment of soil erosion potentials in the watersheds rather than for the identification of total sediment loads produced. Attachment 2 shows the erosion potential by suco and the following table presents its summary by the sub-watershed. Potentials of Soil Erosion in the Watersheds Watershed Sub- Unit Potential level of soil erosion watershed Very low Low Moderate High Severe Total Comoro Downstream of ha 286 14 21 34 381 737 Comoro % 38.8 1.9 2.8 4.6 51.7 100.0 Bemos ha 2,648 69 94 84 1,495 4,391 % 60.3 1.6 2.1 1.9 34.0 100.0 Balele ha 6,013 213 231 237 2,630 9,325 % 64.5 2.3 2.5 2.5 28.2 100.0 A-3 Watershed Sub- Unit Potential level of soil erosion watershed Very low Low Moderate High Severe Total Buamara ha 2,453 47 60 76 817 3,452 % 71.1 1.4 1.7 2.2 23.7 100.0 Anggou ha 1,826 54 50 45 331 2,307 % 79.2 2.3 2.2 2.0 14.3 100 Subtotal ha 13,225 398 457 477 5,654 20,212 % 65.4 2.0 2.3 2.4 28.0 100 Laclo Downstream of ha 5120 327 254 287 196 6,183 Laclo % 82.8 5.3 4.1 4.6 3.2 100 Sumasse ha 10,911 1,268 965 721 2,901 16,765 % 65.1 7.6 5.8 4.3 17.3 100 Ue Coi ha 5,898 737 414 304 1,424 8,778 % 67.2 8.4 4.7 3.5 16.2 100 Lihubani ha 10,033 908 834 754 4,437 16,966 % 59.1 5.4 4.9 4.4 26.2 100 Lohun ha 9,652 1,093 871 704 4,841 17,161 % 56.2 6.4 5.1 4.1 28.2 100 Noru ha 6,872 279 353 418 4,930 12,852 % 53.5 2.2 2.7 3.3 38.4 100 Eraibanaubere ha 6,505 335 412 459 5,817 13,528 % 48.1 2.5 3.0 3.4 43.0 100 Laclo Malikan ha 3261 123 141 159 1,947 5,630 % 57.9 2.2 2.5 2.8 34.6 100 Daisoli ha 6,735 510 554 553 4,134 12,487 % 53.9 4.1 4.4 4.4 33.1 100 Monofunihun ha 6,298 588 636 705 6,089 14,316 % 44.0 4.1 4.4 4.9 42.5 100 Manotahe ha 3,748 193 202 214 2,092 6,450 % 58.1 3.0 3.1 3.3 32.4 100 Subtotal ha 75,031 6,362 5,635 5,279 38,810 131,117 % 57.2 4.9 4.3 4.0 29.6 100 Total ha 88,256 6,760 6,092 5,756 44,464 151,329 % 58.3 4.5 4.0 3.8 29.4 100 Source: JICA Study Team As shown in the table above, about 28 % of the Comoro watershed and 30 % of the Laclo watershed are considered highly susceptible to surface soil erosion.
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