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b13final-160611140933.pptx

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b13final-160611140933.pptx

  1. 1. 1
  2. 2. 2 The water requirement has been increasing more and more especially in agriculture. The agricultural sector makes use of 75% of the water withdrawn from river, lakes and aquifers. In recent years irrigated land has developed rapidly. Water increasingly often becomes a limiting factor for food production especially in dry climates. In dry climates water sources are very limited since the amount of rain-fall is very low. As the total size of the hot dry areas in the world is about 45-50 million square kilometres which means one third of the total land area of the world. In dry climate the availability of water for irrigation of crops is limited, which restricts the possibility for cultivation of crops. For that reason a lot of research has been done to develop methods to protect water and using less amount of fresh water as far as possible without effects on crops yield, and to increase water use efficiency in irrigation without any negative effects on crop yields. Thus irrigation scheduling is one of the best methods which can help us to realize these aims.
  3. 3.  M. Anadranistakis et al.(1999) :Evapotranspiration was calculated using temperature,humidity,wind speed,root depth,crop height etc using penman monteith method.the results showed a deviation of 8% form the experimental results  A.W. Abdelhadi et al.(1999) :Evapotranspiration was calculated using penman monteith,farbrother method the results for penman monteith method were more accurate than the farbrother method.the farbrother method gave highervalues  J. G. Annandale et al. (2001) :Evapotranspiration was calculated using a short programme named CROPWAT written in delphi and based on penman monteith method.this was widely used by the food and agricultural organization.5 day averages were taken instead of daily averages resulting in moreaccuratepredictions  K H V Durga rao et al. (2001) :using different image processing techniques crop type and their area coverage was calculated for a area in deheradun evapotranspiration was calculated using CROPWAT the current irrigation schedule was proved to be more than necessary thus a revision of the irrigation schedulewas proposed 3
  4. 4. 1. Identify the types of crops and the area occupied by thosecrops using satelliteoraerial images. 2. Estimate the water requirement for the different type of crops during their base period.(sowing to harvesting) 3. The product of the area occupied by the crops and the base period water requirement will give the total waterrequirement for that particular irrigation area. 4
  5. 5.  Efficient use of available water resource & Sustainable watershed management  we can decide the water requirements for suggested cropping pattern by irrigation department)  It helps in thedesign of irrigation project. 5
  6. 6.  Crops have low ref lectance in the visible region and have high reflectance in infrared region.  The crops in the image cannot be distinguished accuratelywith visible spectrumalone.  Hence multispectral images are obtained by using multispectral sensors mounted on satellites  By obtaining the LISS-IV IMAGE , preparing the NDVI Map for a particular region, we can identify the types of cropgrown in thearea. 6
  7. 7. For example Truecolourimage: Thedifferent cropscannot be seen distinctively Falsecolouror infrared image: We can see thecontrast between different crops 7
  8. 8.  But before that we need to know how those crops appear at differenttimesof theyearand theirgrowing season  lastly all the information is processed using a software such as ERDAS and ARC-GIS toobtain thearea undereach crop 8
  9. 9.  Wateris utilized in crops mainly forevapotranspiration  Evapotranspiration (ET) is the sum of evaporation and plant transpiration from the Earth's land and ocean surface to theatmosphere.  Factors that affect evapotranspiration include the plant's growth stage or level of maturity, percentageof soil cover, solarradiation, humidity, temperature, and wind. 9
  10. 10. PENMAN MONTEITH METHOD FOR ESTIMATION OF REFERENCE CROP EVAPOTRANSPIRATION:  this is oneof the mostaccurate methods fortheestimationof evapotranspiration  Referencecropevapotranspiration is defined as the evapotranspiration froma hypothetical cropwithan assumed heightof 0.12m having a surface resistanceof 70 s/m and an albedo of 0.23, closely resembling the evaporation of an extension surface of green grass of uniform height, activelygrowing and adequatelywatered.  Thesoftware CROPWAT 8.0 was used tosimplify thecalculations involved in theestimationof evapotranspiration 10
  11. 11.  Theequation forreferenceevapotranspiration is: given by: where: ETo= Referenceevapotranspiration [mm /day] Rn = Net radiation at thecropsurface [MJ /m2/day] G = Soil heat flux density [MJ/ m2 /day] T = Mean daily air temperature at 2 m height [°C] u2 = Wind speed at 2 m height [m/s] es = Saturation vapour pressure [kPa] ea = Actual vapour pressure [kPa] ∆ = Slopevapour pressure curve [kPa /°C] γ = Psychrometricconstant [kPa/ °C] 11
  12. 12. Thevarious parametersrequired fortheequation are:  Latitude in degree and minutes  Altitude in meters  Maximum temperature  Minimum temperature  Wind velocity  Sunshine hours  Mean temperature 12
  13. 13. DATA USED: The following data products are used for the present study:  Survey of India (SOI) Topomap on 1:50,000 scale (to prepare the base map to get information the command area)  Hydro meteorological Data (Estimation of reference crop evapotranspiration by penman monteith method )  Satellite images ( LISS 3 and LISS 4) (to identify the cropping pattern in the study area)  Cadastral map (to know the area details like Survey Number & Area under irrigation, from Revenue Department & Irrigation Department)  Crop data (as per the suggested cropping pattern from irrigation department) 13
  14. 14. Google image 14
  15. 15. Study area location 15
  16. 16.  The study area is located south west of Davangere city in Davangere district  The study area is supplied by the right bank canal network from the Bhadra reserviour  The study area consists of the command area of the 10th distributary of the Harihara branch canal.  10th distributary having an areaof 38.88sq.km(3888 hectares)  The study area lies between from 75.796 to 75.886 decimal degrees longitudeand from 14.377 to 14.411 decimal degrees latitude LAND COVER  Major portion of the land is used for agriculture, horticulture ,plantationsof areagroundnut, coconut ,water bodies, barren scrubs  Thesoil mainly consistsof red soil followed by black soil THE HARIHAR BRANCH CANAL  The 10th distributary of the harihar branch canal has a design discharge of 1.765cumecs  The 10th distributarytakes off from the Harihar branch canal at 15.3 km 16
  17. 17. METHOD OF DATA ACQUISITION  Field Surveywas carried out using a GPS device  Borewells and wells were taken as reference points, a topomap was developed using arcgis with the helpof the GPS coordinates 17
  18. 18. NDVI map was generated using the LISS-III & LISS IV map Supervised classification was carried out on the NDVI map. The steps taken for supervised classification areas follows: 1. Defining training samples 2. Generate signature file 3. Perform most likelihood classification Filters and corrections were applied to obtain the final classified image 18
  19. 19.  The following weatherdatawasentered into the CROPWAT 8.0 software Month Min TempMax Temp Humidity Wind Sun Rain °C °C % km/day hours mm January 16.3 30.1 66 69 8.5 0 February 18.2 32.8 65 77 8.4 0 March 20.8 35.5 57 34 8.8 21.2 April 22.9 36.5 57 41 9 25.2 May 23 35.2 61 65 7.6 115 June 22.1 30.5 27 49 4 89.2 July 21.5 28.1 75 75 1.9 153.6 August 21.5 28.3 73 79 3.8 99.2 Septemb e 20.8 29.3 72 35 4.6 330.2 October 20.6 30 69 48 5.2 105.2 November 18.3 29.3 67 172 9.8 26.2 December 16.1 29 66 79 3.8 0 19
  20. 20.  The following are thecrop data forsome crops Banana: Maize: 20
  21. 21. 21
  22. 22.  NDVI mapgenerated using the LISS 3 map RESULTS 22
  23. 23.  Classified mapobtained bysupervised classification 23
  24. 24.  After applying filtering and corrections the final classified mapwasobtained 24
  25. 25.  The areal information of the cropping pattern obtained wasas follows: 25 land use area(sqm) area(hectares) sugarcane 1225811.546 122.5811546 single rice 4889876.297 488.9876297 maize 737911.5978 73.79115978 double rice 27445981.8 2744.59818 coconut 841015.4332 84.10154332 built up area 1418468.603 141.8468603 barren land 731838.9495 73.18389495 banana 2004747.776 200.4747776 arecanut 1454758.992 145.4758992
  26. 26.  Reference evapotranspiration ET0 and effective 26 rainfall obtained from CROPWAT for theyear 2015 Month ETo Eff rain mm/day mm January 3.5 0 February 4.11 0 March 4.49 20.5 April 5.03 24.2 May 4.91 93.8 June 3.75 76.5 July 2.95 115.9 August 3.41 83.5 September 3.32 158 October 3.33 87.5 November 4.43 25.1 December 2.73 0 Average 3.83 684.9
  27. 27. sugarcane banana barley maize rice(rabi) rice(khariff) arecanut coconut total irrigation(mm/dec) Jan-01 39.2 30.4 9.9 9.9 36.4 0 33.84 37.92 197.56 Jan-02 42.5 34.1 12.5 10.8 39.5 0 38.07 42.66 220.13 Jan-03 49 40.7 27 18.3 45.9 0 43.3575 48.585 272.8425 Feb-01 46.5 40 38.7 27.1 44.2 0 41.2425 46.215 283.9575 Feb-02 48.5 42.3 45.1 37.9 46.8 0 43.3575 48.585 312.5425 Feb-03 39.6 34.6 36.9 37.2 38.5 0 34.7975 39.005 260.6025 Mar-01 44 39.5 42.4 43.5 44.5 0 40.3725 45.855 300.1275 Mar-02 40.2 38.1 41.1 42.3 43.3 0 38.93 44.54 288.47 Mar-03 44.9 45.2 49 50.3 51.5 0 46.2325 52.735 339.8675 Apr-01 42.7 43.4 41.8 48.9 50.1 0 47.275 53.65 327.825 Apr-02 43.2 43.7 30.1 40.4 50.3 0 49.99 56.62 314.31 Apr-03 30.2 20.1 5.8 17 36.4 0 40.2325 46.735 196.4675 May-01 13.4 0 0 0 0 0 25.5175 31.765 70.6825 May-02 0.7 0 0 0 0 103.9 15.36 21.48 141.44 May-03 1.5 0 0 0 0 161.3 19.7175 25.965 208.4825 27  The decadewise irrigation (mm/decade)forthevarious crops was obtained as follows: Irrigation requirement=ET0×Kc - effectiverainfall Rabi season:
  28. 28. Khariff season 28 sugarcane banana barley maize rice(rabi) rice(khariff) arecanut coconut total irrigation(mm/dec) Jun-01 0 0 0 0 0 19.4 16.6 21.7 57.7 Jun-02 0 0 0 0 0 17.8 15.27 19.86 52.93 Jun-03 0 0 0 0 0 9.7 7.855 12.19 29.745 Jul-01 0 0 0 0 0 0 0 0 0 Jul-02 0 0 0 0 0 0 0 0 0 Jul-03 0 0 0 0 0 0 0 0.62 0.62 Aug-01 0 0 0 0 0 7.9 4.6825 8.635 21.2175 Aug-02 11.1 0 0 0 0 14.9 12.0975 16.305 54.4025 Aug-03 9.1 0 0 0 0 8.3 5.37 9.96 32.73 Sep-01 0 0 0 0 0 0 0 0 0 Sep-02 0 0 0 0 0 0 0 0 0 Sep-03 0 0 0 0 0 0 0 0 0 Oct-01 1.4 0 0 0 0 0 0 1.12 2.52 Oct-02 9 0 0 0 0 0 3.9825 7.935 20.9175 Oct-03 25.3 5.5 0 0 0 0 20.3 25.4 76.5 Nov-01 36.9 16.9 0 0 0 0 31.3725 36.855 122.0275 Nov-02 50.4 29.7 0 0 0 0 43.1025 49.095 172.2975 Nov-03 44.5 28 0 0 0 0 38.9575 44.185 155.6425 Dec-01 37.1 25.5 0 0 3.3 0 32.6825 36.635 135.2175 Dec-02 29 20.9 0 0 114.8 0 25.38 28.44 218.52 Dec-03 36.9 27.5 0 0 181.6 0 31.725 35.55 313.275
  29. 29.  The decadewise irrigation volume requirement obtained was as follows: Irrigationvolume = Irrigation requirement × area undercrop 29 irrigation discharge required(cum/decade) crop arecanut rice khariff rice rabi maize coconut sugarcane banana total discharge(cum/sec) Jan-01 49229.04 0 177991.4972 7305.32474 31891.31 48051.8126 60944.3324 375413.3167 0.434506154 Jan-02 55382.68 0 193150.1137 7969.44517 35877.72 52096.9907 68361.8992 412838.8423 0.477822734 Jan-03 63074.71 0 224445.322 13503.7821 40860.73 60064.76575 81593.2345 483542.5525 0.559655732 Feb-01 59997.9 0 216132.5323 19997.4041 38867.53 57000.23689 80189.9111 472185.5107 0.546511008 Feb-02 63074.71 0 228846.2107 27966.8493 40860.73 59451.85998 84800.8309 505001.199 0.584492129 Feb-03 50621.98 0 188260.2374 27450.3111 32803.81 48542.13722 69364.2731 417042.7421 0.482688359 Mar-01 58732.26 0 217599.4952 32099.1542 38564.76 53935.70802 79187.5372 480118.915 0.555693189 Mar-02 56633.77 0 211731.6437 31213.6603 37458.83 49277.62415 76380.8903 462696.4136 0.535528256 Mar-03 67257.15 0 251828.6293 37116.953 44350.95 55038.93841 90614.5995 546207.2145 0.632184276 Apr-01 68773.73 0 244982.8025 36083.8768 45120.48 52342.15301 87006.0535 534309.0955 0.618413305 Apr-02 72723.4 0 245960.7777 29811.6282 47618.29 52955.05878 87607.4778 536676.6388 0.621153517 Apr-03 58528.59 0 177991.4972 12544.497 39304.86 37019.50869 40295.4303 365684.381 0.423245811 May-01 37121.81 0 0 0 26714.86 16425.87472 0 80262.54273 0.092896461 May-02 22345.1 3359695.66 0 0 18065.01 858.0680821 0 3400963.833 3.936300733 May-03 28684.21 5215773.91 0 0 21836.97 1838.717319 0 5268133.804 6.097377087 Rabi season
  30. 30. Khariff season crop Jun-01 arecanut 24148.9994 rice khariff 627315.647 rice rabi 0 maize coconut 0 18250.03 sugarcane banana 0 0 total 669714.6812 discharge(cum/sec) 0.775132733 Jun-02 22214.16993 575578.274 0 0 16702.57 0 0 614495.0104 0.711221077 Jun-03 Jul-01 0 11427.13195 313657.823 0 0 0 0 0 10251.98 0 0 0 0 0 335336.9335 0 0.388121451 0 Jul-02 0 0 0 Jul-03 0 0 0 Aug-01 6811.909018 255453.279 0 Aug-02 17598.947 481804.286 0 0 0 0 0 0 0 521.4296 0 7262.168 0 13712.76 13606.5082 0 0 0 0 0 521.4295686 269527.3562 526722.4973 0 0.000603506 0.311952959 0.60963252 Aug-03 7812.05583 268387.622 0 0 8376.514 11154.8851 0 295731.0768 0.342281339 Sep-01 0 0 0 0 0 0 0 0 0 Sep-02 0 0 0 0 0 0 0 0 0 Sep-03 0 0 0 0 0 0 0 0 0 Oct-01 0 0 0 0 941.9373 1716.13616 Oct-02 5793.577718 0 0 0 6673.457 11032.3039 0 0 2658.07345 23499.33909 0.003076474 0.027198309 Oct-03 29531.6077 0 0 0 21361.79 31013.0321 11026.11 92932.54459 0.107560815 Nov-01 45639.42673 0 0 0 30995.62 45232.446 33880.24 155747.734 0.180263581 Nov-02 62703.7498 0 0 0 41289.65 61780.9019 59541.01 225315.3134 Nov-03 56673.77374 0 0 0 37160.27 54548.6138 56132.94 204515.5922 Dec-01 47545.16102 0 16136.59178 0 30810.6 45477.6084 51121.07 191091.0298 0.260781613 0.236707861 0.221170173 Dec-02 36921.78342 0 561357.7989 0 23918.48 35548.5348 41899.23 699645.8246 0.80977526 Dec-03 46152.22928 0 888001.5355 0 29898.1 45232.446 55130.56 1064414.873 1.231961659 irrigation discharge required(cum/decade) 30
  31. 31.  Theviolation in cropping pattern isobserved as follows: 31 Crop Notified area(hectares) Actual area(hectares) %violation Rice 62.04 3233.5858 5112.098324 sugarcane 120.21 122.5811 1.972464853 plantations 1262.74 430.0521 65.94294154
  32. 32. 1.Irrigation scheduling is the key element to proper management of irrigation system by applying thecorrectamountof waterat the right time to meet the requirement of water to the plants. 2.From classification we can find huge violation of cropping area and because of that shortage of supplied water in the tailrace. It’s clearly shows that there is proper water management is required in thestudy area. 3.Scheduling efficiency was much lower forall treatmentsduring the rainy summerseason compared to the other drier seasons indicating inaccuracy in determining site specific rainfall. 4.Most crops will recover overnight from temporary wilting if less than 50 percent of the plant availablewater has been depleted. Therefore, theallowable depletion volume generally recommended is maximum 50 percent. However, the recommended volume may range from 40 percent or less in sandy soils to more than 60 percent in clayey soils. 5.Theallowable depletion is alsodependent on the typeof crop, its stageof development, and its sensitivity todrought stress 6.When the irrigation scheduling is designed according to historical climate data or estimated by computer program, it is important to look at the crop in the field for color changeor measuring soil waterstatus to makesure that theestimation is right, because this kind of scheduling does not take intoaccount weatherextremes which aredifferent 32
  33. 33.  The same procedurecould be carried out forother locations facing irrigation problems  Suitable irrigation scheduling can bedeveloped to meet thedeficit irrigation requirements 33
  34. 34. 34

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