6. Discussion (i). Field Data Field assessments were done to identify the erosion level at site. Field visits, interviews etc. and traversing the area along the road network could identify the erosion hazard patches in the study area. After observation of selected area were mapped and it is shown in fig.8. A map based identification of field information systems was found satisfactory. Field identification of land use showed that the major land use in sample areas were in agreement with the field land data. Soils in the area were also checked and compared with the available soil maps and was found to be in agreement. (ii), USLE Parameters The parameters of USLE were extracted from various sources. However other than the land use parameters, the rest had single values on literature. Land use parameters were selected as the minimum recommended value. Soil loss from equation using the minimum land use parameters and the other parameters cited in literature indicated a high annual soil loss. Therefore land use factors were kept at the minimum values stated in publications. Soil erodibility values were taken as the values recommended by Joshua(1977). Rainfall erosivity was relation to mean annual rainfall using the regression equation by Premalal (1988).There parameters used in this study showed an average soil loss value of 33 ton/ha/yr (iii). Aggregating Area Specific Attributes, Area specific attribute LS factor was incorporated into computation of annual soil loss by taking the weighted average of RKCP in the polygons within each similar LS polygon. This could be done using the map dissolve function in the GIS software. Therefore the hazard polygons did not exactly reflect the true hazard potential ,when the LS polygons were too big. As such for better computations the LS polygons need 6-1 to be broken into many smaller ones. However the limitation of breaking into smaller polygons would be the limitation of software to handle large amounts of data. (iv). Level of Soil Erosion. Field observation polygons fitted with the computed annual soil loss polygons from USLE showed to vary with different classifications for soil erosion hazard levels. The best fit was obtained for the trial No. 3, classification.(Table-5.4). Comparing the values it could be stated that land use, erodibility and crop management parameters taken for computations, shows good matching of approximating 85% and a poor matching of the remaining polygons. Therefore if USLE is used with standard efficient in literature for Kegalle district, then an average annual soil loss >45 ton/ha/yr could be Classified As severe, 26< loss <45 ton/ha/yr is moderate soil erosion and <26 ton/ha/yr for no or insignificant soil erosion hazard zones and shown in figure 13. (v). Field Data Collection of Soil erosion, land use, soil types etc. for a project with a spatial extent of this study area ( 230 sq.km.) is quite large. It needs to be based on spatial coverage of which boundaries are foot paths, cart tracts, and gravel roads not the grid base. The spatial details could be easily mapped on to a scale of 1:10,000 using a pre coding methodology. (vi) The land use factors in this study did not influence significantly , because, the major portion ( 76 % ) of the area was Rubber plantation. Therefore it may be necessary to carry out a detail sample area study having a variety of land use. (vii) The comparison of field identified erosion levels with compute erosion level used a trial and error variation of erosion class classification to visually verify the estimation. This proved to be a good method because field identified polygons may not be able to exactly mathematically fit to computations without using a significant number of polygons thus making computer handling a complex issue. F i g u r e / 3 : F ie ld V e r i f i e d E r o s i o n H a z a r d C l a s s i f i c a t i o n - G u r u g o d a W a t e r s h e d 6-2 a 7. Conclusions and Recommendations 7.1 Conclusions i. A soil erosion hazard assessment model using GIS as a tool can successfully model the critical zones for watershed management with a 97% of very good or good comparison. ii. Field verified soil erosion model based on USLE enabled the identification threshold annual soil loss values for erosion hazard zones as indicated below. Annual soil loss Erosion hazard zones <26 ton/ha/yr 26 - 45 ton/ha/yr >45 ton/ha/yr Insignificant Moderate Severe iii. Based on the field verified model the watershed managers can easily apply the USLE rationally selecting the parameters and select the cistical soil erosion zones using the above threshold values as guidelines in selecting the priority area for soil conservation watershed. iv. Actual erosion hazard zones of watershed of this magnitude can easily be recorded using 1:10,000 maps and a pre coded questionnaire. 7-1 7.2 Recommendation. i. The slope class polygons used in this study area quite big and hence proved difficult to match with field observed zones. As such it is necessary to use smaller slope class polygons for better model verifications. ii. The watershed selected was predominant with Rubber plantations. Therefore the effect of land use may not have reflected well in the results. Therefore it may be necessary to carryout further work with different land use for strengthening results from this study. Iii .Measurements of soil loss from plots under different scenario needs to be done for calibration of the parameters used in the USLE. This would enable the comparison of threshold values found from literature with the values obtained from present model. iv. The erosion hazard zoning model indicated that 80% of the watershed was with the threat of moderate or severe soil erosion hazard. This areas are recommended to be implemented for watershed management. References Annual report,(1999).. Central Bank of SriLanka Dahanayaka Kapila,(!998), Live with land slides. Publication of N.D.M.C.Ministry of social services. .De Roo A.P.J.,(1996), Soil Erosion assessment Using GIS, FAO. Conservation Guide (1987), Guidelines for economic appraisal of watershed management projects FAO Rome Glenn O. Schwab,Richard K. Frevert, Taloott W.Edminister, Kenneth K.Barnes(1966),Soil and Water Conservation Engineering. Guideline for construction in Disaster prone Areas (1999),SLUMDMP,Sri Lanka Urban Multi Hazard Disaster Mitigation Project .Gunawardana.E.R.N.,(1995), Importance of natural forest in Sri Lanka for soil conservation and hydrology. .Gunawardana.E.R.N(1997)Participatory Processes for Integrated Watershed Management (Participatory Watershed Management Training in Asia(PWMTA) Henry Gamage,(1998), State of art and status of watershed management in Sri Lanka,(Participatory watershed management training in Asia (PWMTA) Joshua.WD ,(1977); Soil erosive power of rainfall in the different climatic zones in Sri Lanka,In erotion and solid matter transport in Inland water, Keech M.A.(1969), Mondaro Tribal Trust Land Determination of Trend using a air photo analysis, Rhodesia Agricultural Journal 8-1 Kenneth N.Brooks, Peter F. Ffolliott,Hans M.Gregersen,John, L.Thames (1993 ); Hydrology and the management of watersheds , Kharel(1997) Participatory Processes for Integrated Watershed Management (Participatory Watershed Management Training in Asia(PWMTA Lu Shengli(1997) Participatory Processes for Integrated Watershed Management (Participator)' Watershed Management Training in Asia(PWMTA) .Mahadavifar M.R, Masoomeh Rakhsandeh, Piran Veyseh,(2000) : Landslide hazard zonation of Lorestan province in Iran using GIS, (4 t h International Conference on Integrating GIS and Environmental Modeling), Malcolm Newson (1992), Land Water and Development Margot , Gary, 2000 : GIS and Site- Scale Planning: Challenges and opportunities for environmental designers GIS/EM4 (4 t h International Conference on Integrating GIS and Environmental Modeling) McCool,D.K.L.C Brown, G.R.Forter, C.K.Multchler and L.D.Meyer,(1987),revised slope steepness factor for the Universal Soil Loss Equation Millers,(1994), Erosion and sedimentation data ,Hand book for Agrohydrology. Morgan.R.P.C.(1995), Erosion hazard Assessment, soil erosion and conservation Panabokke,C.R. and R.Kannangara,1975 Proc: Section B, Annual Session , Assn .Advancement of Science,Sri Lanka 31 (3):49 Qiming Zhou,(1995); Successful GIS; Paper presented in GIS AM/FM workshop in ASIA' Reddy(1997) Participatory Processes for Integrated Watershed Management (Participatory Watershed Management Training in Asia(PWMTA 8-2 Roose. R.J.(1977), Application of the universal soil loss equation of Wischmeier and Smith in West Africa. In Soil Conservation and management in the humid tropics,eds.D.J.Greenland and Rial, 177-87. Chichester: John Wiley and Sons. Vijay P.Singh, and M.Fiorentino,(1996 ): Geographical Information Systems In Hydrology, Wickramasinha. W,(1993); Evaluation of selected land utilisation types in the estate sector with special reference to the watershed management; Thesis, International Institute for aerospace survey and earth science. Wickramasinha.L. A.,Premalal.R.,( 1988); Development of rainstorm erosivity map for Sri Lanka in land conservation for future generations. Proceeding of the fifth International Soil Conservation Conference. 18-19 Jan 1988, Bangkok,Thailand Wickramasinhe.W.,(1993), Thesis Report ,Evaluation of selected land utilization types in the estate sector with special reference to the watershed management: Wijesekara NTS.,(2000) River basin management, (The National Engineering Conference on "Engineering for the Emerging Millennium"), Wimalasinha,Wijerathna,(1998). Participatory watershed management; Present status and future prospects,(Paper presented at the national conference On "The status and future direction of water research in Sri Lanka" ) 8-3 Appendix 1. Field Data Collection Sheet For Watershed Management - Kegalle District A General 1. District 2. DS.Division 3. A.S.C. Area 4. Village/(G.S. Division).. 5. Name of Recorder 7. Extent of Village Ac 6 . Name of Interviewer 6. i . Male/female, ii Age . . . . B. Land use Description. Ac Land slope classes, (% Average ) If any soil conservatio n practice used 0-7 8-15 16-20 21-30 31 -40 >40 Y/N If yes metho d 1. Total Extend 2. Crop i. Tea ii. Rubber iii. Coconut iv. Forest v. Paddy vi. Scrub vii. Others Y/N Y/N Y/N Y/N Y/N Y/N Y/N if s C. Soil Soil type Depth cm Surface texture ^Ci 1 2 3 4 Al D. Erosion Hazad (type) Yes/No; If yes, where/ when .a Al 1. High 2. Moderate 3. Negligible E. Any land slide experienced surrounding the area ; 1. ? c f #a faDco 5. aOcrarf CD&afesoaaf *»© - . . . 2. « a > 3 © t t - 6. »CD30t$0j ©axoateoxwaJ «>© - . 3. eo:>ec5a> »estafca - 7. tf#/goi» - ©ere - q § 4 . g»@«B@Q:>0 » C D 3 0 o - Setooo 9©® o© o>tp® % 0 - 7 8 - 15 16-20 21 -30 31-40 4 0 > 1. § 4 ) qQ& ©® 9®j«5oo 2. ©CSOcDaJ I. S (q>iOj) ii. ooJ iii. o a o iv. v. «©a>a$ cksj vi. ©g e»£©c vii oBjocOerf •qi. oad nc&a5Qa qi. o > c $ S ^ e o o So® ©00© 1. erf© S j c a > a « S 2. 03©}«B»ac3«rf ©j^aDO « S 3. csjgeSa gq> a>0® a>ja> . tjOO SDKS o i® OJ6CD3 S qjoJe. ©8 /e»jCD i a>8 «D® ©esxstfc. ? . . . ii. «»:>:>©ed£ ? 0 . ®Oa><£ Page A2 Appendix : 3 STATION NAME: DEHIOWITA (DUNEDIN) \ LAT.7.02 LON. 80.28E ELEV.122.0M ELEMEN Precip,Total Mly in Milimeters Missing data values are coded as -9.9M YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL 1983 5.6 9.4 4.2 182 244.0 353.1 300.2 342.4 444.5 256.3 367.4 554.9 3063.6 1984 381.7 199.9 675.3 632 470.7 454.0 718.0 42.4 455.2 219.1 956.1 73.1 5277.9 1985 264.8 285.7 401.6 258 458.7 753.9 209.4 446.6 261.4 660.5 504 208.7 4713.1 1986 215.4 251.9 188.7 329 238.8 169.1 100.3 209.6 501.4 464.0 189.7 253.4 3110.9 1987 41.8 0 73.2 511.0 512.7 390.3 13.4 464.8 336.3 957.3 365.7 115.6 3782.1 1988 61.0 239.0 260.3 343 • 391.0 507.6 565.6 652.7 443.6 193.9 400.1 105.2 4162.8 1989 25.4 0 84.2 280 464.3 796.7 381.2 378.3 310.41 512.7 458.3 -9.9M 3691.4 1990 142.0 7.1 262.5 52.2 481.1 256.0 326.1 41.1 45.1 446.2 539.3 304.0 2902.7 1991 326.6 27.6 155.5 290 466.7 584.9 312.3 139.5 132.6 397.5 361.1 148.8 3342.7 1992 89.7 0 59.7 395.0 453.3 426.7 368.6 205.7 353.0 543.6 365.0 123.5 3383.8 1993 89.0 35.1 163.1 421 493.0 385.2 139.0 128.6 321.4 779.3 492.7 367.3 3814.3 1994 38.7 207.0 187.8 362 464.0 238.6 192.1 134.4 272.6 438.4 582.6 31.6 3149.3 1995 99.6 88.0 47.6 653 579.6 424.9 137.3 388.7 255.2 442.8 348.0 -9.9M 3465.0 1996 94.6 99.6 52.3 295 62.5 391.9 236.0 147.8 566.0 155.4 175.5 28.1 2304.9 1997 34.3 42.7 97.4 249 520.2 177.0 458.4 119.8 667.6 810.0 453.1 316.3 3946.1 1998 232.1 8.1 111.8 334.0 760.9 281.4 451.8 306.0 823.1 509.8 228.6 299.5 4347.1 1999 140.7 184.9 267.2 270 437.3 297.9 235.0 245.3 236.5 581.7 -9.9M -9.9M 2896.6 AVERAGE 134.3 99.2 181.9 344.4 441.1 405.2 302.6 258.5 378.0 492.3 424.2 209.3 3724.0 Page A3 Appendix 4 STATIO NAME :AMBANPITIYA LAT:7.23N LON: ELEV : 201.2M ELEMENT: Precip.Total Mly in Milimeters Missing data values are coded as -9.9M YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL 1983 0 10.9 10.2 57.2 211.1 278.1 103.3 162.8 198.2 132.0 313.4 226.2 1703.4 1984 175.0 122.0 359.8 537 161.1 233.5 343.6 7.5 277.6 164.5 357.5 105.5 2844.2 1985 100.3 99.3 68.8 124 519.5 442.2 236.9 106.3 227.1 414.9 364.4 170.5 2874.1 1986 371.8 139.9 88.9 233 102.6 55.7 58.6 80.4 290.4 334.1 195.8 110.1 2061.4 1987 51.9 0 79.1 380 223.11 200.4 0 254.7 200.7 563.0 95.4 12.6 2061.3 1988 0 195.9 129.5 441.0 265.4 437.1 591.3 429.4 462.8 132.6 385.5 67.0 3537.5 1989 54.2 0 91.6 176 259.6 40.2 295.0 90.5 137.8 196.6 155.7 0.0 1496.9 1990 167.2 38.2 123.5 64.5 252.6 504.9 108.1 27.4 18.7 224.3 146.4 92.0 1767.8 1991 95.1 9.7 149.2 198 111.2 154.0 292.5 65.4 22.2 282.7 394.3 18.2 1792.3 1992 0 0 6.3 157 145.4 144.4 233.0 37.1 126.7 402.1 370.8 28.0 1650.5 1993 0 84.0 69.4 162 241.5 112.2 154.0 138.6 93.2 816.1 599.8 204.9 2675.9 1994 68.0 177.7 40.6 196 255.2 284.4 119.3 86.0 236.8 685.5 435.0 2.0 2586.6 1995 190.0 5 149.5 519 563.9 193.1 96.7 235.5 211.5 286.1 414.5 0 2864.6 1996 75.4 61.1 66.5 353 15.0 133.2 133.2 103.4 440.1 351.0 247.3 17.5 1996.3 1997 0 43.6 178.4 197 401.7 292.3 292.3 57.4 448.1 666.2 459.3 256.1 3292.0 1998 64.2 0.5 53.0 242 401.3 311.7 311.7 307.8 419.3 404.9 300.2 207.3 3024.0 1999 133.1 118.2 67.9 439 427.7 119.6 119.6 122.2 97.1 611.1 -9.9M -9.9M 2255.3 AVERAGE 91.0 65.1 101.9 263.2 268.1 231.6 205.2 136.0 229.9 392.2 327.2 94.9 2423.0 Page A4 Appendix :5 STATION NAME:UNDUGODA (YATADERIYA) LAT:7.1GLON:80 ELEV:*"**M ELEMEN Precip,Total Mly in Milimeters Missing data values are coded as -9.9M YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL 1983 11.4 80.8 14.5 55.1 281.5 336.6 136.2 377.5 281.8 289 431.0 432.9 2,728.3 1984 291.5 126.4 414.1 507 431.0 263.1 522.4 60.9 336.4 168.7 535.0 38.0 3,694.0 1985 67.0 39.5 167.7 205 303.1 738.8 281.1 302.3 218.3 561.9 473.4 266.2 3,623.8 1986 202.8 36.2 143.7 496 185.7 202.5 173.0 200.3 362.9 335.2 162.4 22.0 2,522.5 1987 11.7 0 123.8 336 416.6 368.0 0 400.1 365.3 934.7 290.1 150.8 3,396.6 1988 117.6 207.2 203.0 -9.9M -9.9M -9.9M -9.9M -9.9M -9.9M -9.9M -9.9M -9.9M 527.8 1992 -9.9M -9.9M 10.0 284 380.1 533.0 417.5 227.2 -9.9M 773.1 -9.9M -9.9M 2,624.5 1993 -9.9M -9.9M 136.5 278 398.9 442.5 250.7 140.5 202.5 862.1 598.0 289.7 3,599.2 - AVERAGE 117.0 81.7 151.7 308.4 342.4 412.1 254.4 244.1 294.5 560.7 414.98 199.93 3,381.0 Page A5 Appendix 6. Comparison Using Standard Deviation as Classification-Trial .2 Fi eld Ob se rv at io ns Po ly go n N o. Fi eld Ob se rv at io n Ra nk in g Co m pu te d Ra nk in g M at ch in g Fi eld Ob se rv ati on s Po ly go n N o. Fi eld Ob se rv ati on Ra nk in g Co m pu te d Ra nk in g M at ch in g Fi eld Ob se rv at io ns Po ly go n N o. Fi eld Ob se rv at io n Ra nk in g Co m pu te d Ra nk in g M at ch in g Fi eld Ob se rv at io ns Po ly go n N o. Fi eld Ob se rv at io n Ra nk in g Co m pu te d Ra nk in g M at ch in g 1 1 1 G 17 1 1 G 33 2 1 M 49 1 2 M 2 1 ' G 18 1 P 34 1 1 G 50 1 1 G 1 1 G 19 1 1 G 35 2 1 M 51 1 1 G 4 1 1 G 20 2 1 M 36 2 1 M 52 1 2 M 5 1 1 G 21 2 j M 37 1 1 G 53 2 1 M 6 1 1 G 22 1 1 G 38 2 J M 54 2 1 M 7 2 M 23 1 1 G 39 2 M 55 2 1 M 8 2 M 24 2 2 G 40 1 1 G 56 2 1 M 9 2 M 25 1 1 G 41 1 1 G 57 2 1 M 10 1 2 M 26 1 1 G 42 1 1 G 58 2 1 M 11 1 P 27 1 1 G 43 1 2 M 59 1 1 G 12 1 1 G 28 1 -> P 44 1 1 G 60 2 1 M 13 1 1 G 29 1 1 G 45 2 1 M 61 2 2 G 14 1 1 G 30 1 1 G 46 2 M 62 1 1 G 15 1 1 G 31 1 1 G 47 2 -> M 63 1 1 G 16 1 P 32 2 1 M 48 2 2 M No of G =33 No of M =26 No of P =4 P -Poor matching - 6.3% M Good matching - 41.3% G -V. Good matching - 52.4% A6 Appendix 7. Comparison Using Standard Deviation as Classification-Trial .4 E ; Vi O CV £ : Fi eld Ob se rv at io n Ra nk in g Co m pu te d R an ki ng M at ch in g Fi eld Ob se rv at io ns Po ly go n N o. Fi eld Ob se rv at io n Ra nk in g Co m pu te d Ra nk in g M at ch in g Fi eld Ob se rv at io ns Po ly go n N o. Fi eld Ob se rv at io n Ra nk in g 5 1 2 0 M at ch in g Fi eld Ob se rv at io ns Po ly go n N o. Fi eld Ob se rv at io n Ra nk in g Co m pu te d Ra nk in g M at ch in g 1 1 1 G 17 1 1 G 33 2 1 M 49 1 2 ! M 2 ] 1 G 18 1 3 P 34 I 1 G 50 1 1 G j 1 1 G 19 1 2 M 35 2 1 M 51 1 1 | G 4 1 1 G 20 2 2 G 36 2 j 2 I G 52 1 2 M 5 I 2 M 21 2 *> s> M 37 1 j l JG 53 2 3 M 6 1 1 G 22 1 2 M 38 2 1 J M 54 2 1 M 7 2 3 M 23 1 1 G 39 2 3 M 55 2 1 M 8 2 M 24 2 2 G 40 1 3 P 56 2 1 M 9 2 M 25 1 1 G 41 1 2 M 57 2 1 M 10 1 2 M 26 1 1 G 42 1 1 G 58 2 1 M 11 1 3 P 27 1 1 G 43 1 1 2 M 59 1 1 G 12 1 2 M 28 1 P 44 1 | 2 M 60 2 2 G 13 1 2 M 29 1 1 G 45 2 i 1 i M 61 2 2 G 14 1 1 G 30 1 1 G 46 2 ; 2 l G 62 1 j P 15 1 1 G 31 1 2 M 47 2 -> J ) M 63 1 2 M 16 1 2 M 32 2 1 M 48 2 - i M No of G =26 No of M =32 No of P =5 P -Poor matching - 7.9% M Good matching - 50.8% G -V. Good matching - 41.3% A7 Appendix 8. Comparison Using Standard Deviation as Classification-Trial .3 Fi eld Ob se rv at io ns Po ly go n No . Fi eld Ob se rv ati on s Co mp ut ed Ra nk in g M at ch in g Fi eld Ob se rv at io ns Po ly go n No . Fi eld Ob se rv at io n Ra nk in g J Co m pu te d Ra nk in g M at ch in g Fi eld Ob se rv at io ns Po ly go n No . Fi eld Ob se rv at io n Ra nk in g Co mp ut ed Ra nk in g M l is u R Fi eld Ob se rv at io ns Po lyg on N o. Fi eld Ob se rv at io n Ra nk in g Co m pu te d Ra nk in g M at ch in g 1 1 1 G 17 1 1 G 33 2 1 M 49 1 2 M 2 1 1 G 18 1 2 M 34 1 G 50 1 1 G J 1 1 G 1.9 1 2 M 35 2 1 i M 51 1 1 G 4 1 1 G 20 2 1 M 36 2 1 M 52 1 2 M 5 1 1 G 21 2 2 G 37 1 1 G 53 2 2 G 6 1 1 G 22 1 1 G 38 2 M 54 2 1 M 7 2 -> j M 23 1 1 G 39 2 *> M 55 2 1 M 8 2 2 G 24 2 2 G 40 1 P 56 2 1 M 9 2 2 G 25 1 1 G 41 1 1 G 571 2 1 M 10 1 2 M 26 1 1 G 42 1 1 G 58 2 1 M 11 1 2 M 27 1 1 G 43 1 1 G 59 1 1 G 12 1 1 G 28 1 2 M 44 1 2 M 60 2 1 M 13 1 1 G 29 1 1 G 45 2 1 M 61 2 2 G 14 1 1 G 30 1 1 G 46 2 1 M 62 1 -> P 15 1 1 G 31 1 1 G 47 2 2 G 63 1 1 G 16 1 1 G 32 2 1 M 48 2 M No of G =36 No of M =25 No of P =2 P -Poor matching - M Good matching - G -V. Good matching 3.2% 39.7% 57.1% A8 Appendix. 9 S u m m a r y of c o n s e r v a t i o n p r a c t i c e s for major c r o p s . V i s i t e d G . N . D i v i s i o n T o t a l A rea (Acs ) Map Ma jo r A n y c o n s . No. N a m e H i g h L a n d Paddy Re fe rence C r o p p r a c t i c e Y/N 1 63 Ampe 339 33 3 Scrub/F N Paddy Y Rubber Y 2 62 A r u k g a m m a n a 450 15 3 OP N Rubber Y Coconut N 3 61B Pothuko laden iya 851 45 3 Scrub/F N Rubber Y Coconut N 4 91 Udabage 143 53 1 Tea Y Rubber Y Paddy N OP N 5 93 Maden iya 224 42 1 Tea Y Rubber Y Paddy Y OP N 6. 61C Hapuden iya 388 24 3 Rubber Y Paddy Y coconut N Rubber Y 7 87 Kohombaden iya 248 12 1 Tea Y Rubber Y Scurb N OP N 8 Kinigama 719 56 4 OP, N Rubber Y Coconut N 9 65 Pmden iya 198 20 3 Rubber N Paddy Y OP N 10 69A Dematanpi t iya 496 53 6 OP N Scrub N Forest N Paddy Y A9 11 6 5 B B o y a g o d a 591 50 5 Rubber Y Coconut N paddy Y Scrub N 12 63A Rukgahatenna 262 10 3 OP N Rubber Y Coconut Y 13 K a r a g a l a 777 50 7 O P N Rubber Y Coconut N P a d d y Y 14 6 2 8 Hatnapi t iya 297 5 9 Forest N Rubber Y OP Y 15 55 Talewela 306 10 7 Rubber Y OP N Coconut N 16 57A Eragama 302 55 8 Rubber Y P a d d y Y OP N 17 54 Godigamuwa 198 78 7 OP N Paddy Y Rubber Y 18 43D Udamagamn 327 40 7 Rubber y Paddy Y OP Y 19 48E Madopola 340 32 7 OP N Rubber Y Paddy Y 20 5 5 D Meedeniya South 347 23 7 Rubber Y P a d d y Y OP N 21 54A Walhura 230 65 7 Rubber N Paddy Y OP N 22 55C Meedeniya North 416 120 7 Paddy Y Coconut N OP N 23 58 B Ganthuna Pal legam; 198 48 9 Paddy Y Paddy 24 56B Udugoda 400 18 4 OP Rubber y 25 56C Hungampola 214 60 7 Coconut n Paddy 26 57 Athurupane 190 18 8 Forest OP 27 59 Mabopitiya 140 60 8 OP Paddy Rubber y 28 49.E M i n u w a n q a m u w a 196 4 3 8 OP Rubber n Paddy 29 58A Ganthuna Pa l l egam; 166 46 9 Rubber n Paddy A9 Appendix 1 0 . Field Visit Details D.S. Division : Galigamuwa. Date of Field Visit Persons who met at the field Visited G.N.DIvision No. Name Officers who accompanied visit Total Area High Land (Acs) | Mostly Paddy | Affected Area (Acs Map Ref ere Major Crop 13 14 Yattegoda ASC Area 2 2 / 2 / 2 0 0 0 22/2/2000 3/1/00 K.P.Sunil.P.Ranjith, N. Podinona S.Siyadooris.M .Beebihamy. K.Thilakaratna, M.Abbubaker, K.Priyantha.D.R.M.S.Yaso. S.Wijesiri, S.H.Karunaratna. 63 Ampe D.Dias Gunawardhana .Senior Technical Officer 339 Agriculture Instructor(AI),Divisional Officer(DO) Technical Officer(TA) 62 Arukgammana R.A. Indrani Siriyalatha ,STA 61B Pothukoladeniya K.K. Ranjanee.TA 9 1 Udabage K.P.G.A. Jayatissa,Divisional Officer (DO) .Agriculture Instructor(AI) 3/2/00 .A..Wijekoon. .K.M.Piyaseeli. 61C Hapudeniya R.A.L.Wijesekara .Divisional Officer (DO) .Agriculture Instructor(AI) Technical Officer(TA) 3/9/00 H.H..Gunawardana.,H.A.Jayasena. Kinigama H.H.A.Gunasekara.DO.STA 3/10/00 K.R.Martin, D.M.Hendric 65 Pindeniya S.M.R.T. Kumarihamy.DO.STA Nandani ,STA 3/25/00 P.G.Karunawathi. , L.M.Siyadoris 69A Dematanpitiya D.R. Sanath Kumara.STA 4/28/00 E.P.Hapuwita. ,E.P. Piyadasa. 65B Boyagoda M.A. Ananda Chandrasiri.TA ,DO 4/29/00 P.Sirisoma. .P.R.Nandasena. 63A Rukgahatenna R. Gamini Rajapaksha ,TA , DO 6/9/00 M.Gunasinha., V.Sirisena Karagala E. Somaratne ,TA ,DO 6/10/00 D.M.Samaneris, D.M.Ratnasekara 62B Hatnapitiya M.W. I.S. Mawaththa TO.DO.STA Paragammana ASC Area. 6/20/001K.G.Wimalawathi, K.Dayawathi 55 Talewela L.A. Pathmaseeli .DO.TA 6/29/00 D.Priyantha, L.Chandralal 57A Eragama W.A.S. Wijesinghe.AI.DO.TA 6/30/00 W.M. Gunapala, T.W. Sumanawathi 54 Godigamuwa D. Nayanakanthi ,AI , TA 450 851 143 388 719 198 496 591 262 777 297 306 302 198 33 15 45 53 24 56 20 53 50 10 50 10 55 78 21 34 21 28 10 Scrub/F OP Scrub/F Tea Rubber OP Rubber OP Rubber OP OP Forest Rubber Rubber OP TOTT Appendix 10. 7/7 /00 M.K.Dingiri B a n d a , R.A. Nawara tne 4 3 D U d a m a g a m a M.K.S.D. Bandara 327 4 0 2 7 Rubber 7 /8 /00 H.R. Abeyra tne , P. S is lsoma 4 8 E Madopo la P. Prasanna Path l rana 340 32 3 7 OP 7 /19 /00 J . Joseph, A . B . Perera 5 5 D M e e d e n i y a South W . M . S . Amarath i lake ,TA 347 23 3 7 Paddy 7 /20 /00 M.G. Jayas inhe , J .P . Jayat issa 5 4 A W a t h u r a N.a. Wi jaya K u m a r a ,TA 230 65 8 7 Rubber 8/1 /00 S .P . S imon, M. G u n a p a l a 5 5 C M e e d e n i y a North K.G. A . M . Kiriella , D O , S T A , T A 416 120 5 7 Paddy 8/4 /00 M.L. P remara tne , M.R. Upa l i 58B Ganthuna Pallegarr K.L. D a m m i k a S e n a r a t h n e ,TA,Engineer 198 48 1.5 g Rubber 8/5 /00 L.G. D a s s a n a y a k e , K. Suwar is 56B U d u g o d a N.P. Newtan 400 18 4 4 OP 8 /18 /00 M.P. Piyasisi, P.O. K u m a r a d a s a 56C H u n g a m p o l a R .Asoka Katunathi lake ,DO ,STA,AC 214 68 7 7 Coconut 9 /1 /00 K.Lalitha., M . P o d i m e n i k e , B.Jayantha. 57 Athurupane M.Nimal Jayantha , S T A 190 18 11 8 Forest 9 /2 /00 K.R.'P. Bandara , Upul Ranj i lh 59 Mabopit iya K.R.S. Nilanthi Kumar i , D O 140 6 0 9 8 OP 9 / 1 5 / 0 0 G.B.R. Gunath i lake , G . B . R . N a n d a w a t l 4 9 E M i n u w a n g a m u w a W . W i m a l a d a s a ,TA ,AI , D O 196 43 6 8 OP 9 / 1 6 / 0 0 U. R. w ickramaslnghe , R . M . Jayantha 58A Ganthuna Pallegarr] H. Podira lahami 166 46 5 9 Rubber 9 / 2 2 / 0 0 D. Senevi ra tne , M.A. Karunara tne Pothukoladeniya (N) R.P. Subasinhe ,DO , S T A 279 15 8 3 OP D O Divisional Off icer OP Other Plantation TA -Technical Officer Al _ Agricultural Instructor STA - Seneior Technical Officer Observed Erosion Hazard Location (1:10,000) A 11 Observed Erosion Hazard Location (1:10,000) A 11 3< IJ Appendix 10. Observed Erosion Hazard Location (1:10,000) A 1 1 Appendix^r6Y - — 4 ; r -A /? 5"o vncxi. >-:J;;l^ :;a 5 J .. A d m i n B o u n d r y Severe Moderate Negligible Z 0 1 FEB 2001 f I d e n t i f i e d F i e l d E r o s i o n L e v e l s