CHAPTER V ANALYSIS OF IRRIGATION SURVEY CHAPTER V ANALYSIS OF IRRIGATION SURVEY
5.1 General 128
5.2 Economic Survey 130
5.2.1 Major Crops 131
5.5.2 Agriculture Income 142
5.2.30ther Income 143
5.2.4 Fertilizers 144
5.2.5 Energy Sources 145
5.2.6 Agricultural Facilities 146
5.3 Village Wise Soil Moisture Comparison 147
5.5.1 Village Wise Soil Moisture Content 148
5.3.2 Soil Moisture Difference 158
5.3.3 Season Wise Soil Moisture 161
5.4 Population Analysis 162
5.4.1 Age Group 163
5.4.2 Occupation 164
5.4.3 Dependent Population on Agriculture 164
5.5 Water Management 165
5.5.1 Irrigation Sources 165
5.5.2 River lifts irrigation 167
5.5.3 Well Irrigation 167
5.5.4 Canal Irrigation 168
5.5.5 Water Conservation 169
5.5.6 Water Collection from Distance 170 5.6 Water Requirement 172
5.7 Irrigation 175
5.7.1 Methods of Agriculture 175
5.7.2 Types of Irrigation 176
5.8 Problems of Agriculture 179
5.9 Testing of Hypotheses 181
5.9.1 Hypothesis No. 1: (Chi-Square) 181
5.9.2 Hypothesis No. 2: ('Z' Test) 182
5.9.3 Hypothesis No. 3: ('Z' Test) 183
5.9.4 Hypothesis No. 4: (Correlation) 185
5.9.5 Hypothesis No. 5: ('Z' Test) 186
5.9.6 Income Per Hectare 188
5.10 Nilwande Dam Canal Site Sutablity 188
5.10.1 Suitable Canal Site No. 1 188
5.10.2 Suitable Canal Site No. 2 189
5.11 The Analytic Hierarchy Process (AHP) 190
5.12 Resume 205 CHAPTER V ANALYSIS OF IRRIGATION SURVEY
5.1 General
Survey involves collection of primary and secondary data about the village. Information about this basic data is very essential in a country like India, where almost 75% of the population live in the villages. Secondly, such surveys also help in understanding the socioeconomic structure of the villages. The field survey provides ideas for the emerging geographers to fiirther take up the study of large area at a greater level and forms a base for the regional planning at national level. One has to be introducing all the aspects of field study and survey. Due to this reason field survey of a village we are getting proved information about study area.
The selection of the villages is done on the basis of random sampling techniques. In field studies, a village is selected because it is the basic administrative unit reflecting the characteristics of the areas in terms of its socioeconomic and physical conditions. The village is said to be the basic geographical unit because number of villages constitute a taluka similarly, a number of talukas combine to form district and several districts together constitute the state, which with other states forms a country.
The main aim of the village survey is to know about the physical, social and economic features of the place and to collect the first hand information and to know the nature of the interaction of man and environment. Firstly, the physical, geographical aspects of the village are studied; secondly, the socioeconomic conditions are studied; thirdly, the land area is evaluated and lastly, the demographic characteristics and settlement pattern are studied.
128 Table 5.1 Selected Villages for Agricultural Irrigation Survey 2014-2015
Villages Frequency Percentage
Mhaladevi 41 10.2
Dhokari 34 8.5
Gardhani 51 12.7
Nilwande 24 6
Rumbodi 37 9.2
Bahirwadi 27 6.7
Kalas Bk. 42 10.4
Parkhatpur 24 6
Dhumalwadi 41 10.2
Sugaon Bk. 25 6.2
Rede 21 5.2
Unchkhadak Kh. 35 8.7
Total 402 100
Source: The field Survey (2015).
The above table 5.1 covers 12 villages for agriculture survey using technique of Salant and Dillman. It show that Gardani is highest percentage and lowest household in Rede village. This sample survey depended on population size.
129 5.2 Economic Survey
Table 5. 2 Agricultural Area (in ha.)
Area Horticulture Arable
(in ha.) Frequency Percentage Frequency Percentage
below 1 256 63.6 381 94.8
1.01 to 2 103 25.6 16 4
2.01 to 3 23 5.7 1 0.2
3.01 to 4 9 2.2 3 0.7
4.01 to 5 4 1 0 0
Above 5 7 1.7 1 0.2
Total 402 100 402 100
Source: The field Survey (2015).
The above table 5.2 shows that accumulation of population is more in irrigated area than arable area. Approximately about 63.6% populations are having less than Iha. area while maximum house holder having less than 5ha. land. It is also show that in the arable area absence of land above 4ha. this is under land scarcity.
130 5.2.1 Major Crops
Table 5.3 Cultivated Crops
Sr.No Name of Crops Frequency Percentage Cumulative Percentage
1. Cora 43 3.23 3.23
2. Bajara 246 18.51 21.74
3. Wheat 222 16.76 38.5
4. Sugarcane 174 13.09 51.59
5. Soyabean 45 3.38 54.97
6. Onion 255 19.18 74.15
7. Groundnut 13 0.97 75.12
8. Gram 88 6.62 81.74
9. Pomegranate 49 3.68 85.42
10. Tomato 93 6.99 92.41
11. Fodder Crops 60 4.51 96.92
12. Other 41 3.08 100
Total 1329 100 -
Source: The field Survey (2015).
131 • Corn
• Bajara
• Wheat
• Sugarcane
• Soyabean
• Onion
• Groundnut
• Gram
• Pomegranate
• Tomato
Graph 5. 1 Cultivated Crops
In study area there are two main agricultural seasons i.e. Rabbi or the season of winter crops and the Kharif or the season of summer crops. Rabbi crops are the crops which is grown in the period of October - November to February - March with the help of stored monsoon water, soil moisture and dew, the main crop which are grown during the season are Wheat, Gram, Pulses (Masur), Green peas etc. Kharif crops are usually sown with the beginning of the first rain in July, during the south - west monsoon season i.e. Rice, Vare, Pulses (Udid), Tomato etc. In study area was observed the more percentage of up to Iha. land.
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138 Table 5.4 Major Crops in the Study Area (in ha.)
c c re n k- 0) u Village re u '(5 •o re re '(5* o 00 > CO 2 3 o
Agar 3 0 28 0 27 0
Agastinagar (N.V.) 67 0 12 0 3 2
Akole 30 1 14 0 11 14
Ambad 31 1 9 0 6 30
Ambevangan 0 74 0 21 0 0
Ambikanagar (N.V.) 77 0 6 0 11 0
Aurangpur 12 0 9 1 27 40
Babhul Wandi 17 24 0 54 0 0
Bahirwadi 38 2 12 1 21 3
Bari 0 74 0 13 0 0
Bhandardara 0 26 0 54 0 0
Bhojadarawadi (N.V.) 10 13 0 36 1 4
Chichondi 0 78 0 14 0 0
Chitalwedhe 36 5 5 6 25 14
Deogaon 0 26 0 65 0 0
Dhamangaon Awari 47 1 10 0 2 25
Dhokri 31 0 22 0 25 4
Dhumalwadi 32 1 18 0 7 32
Digambar 16 8 0 70 0 0
Dongarwadi 19 25 0 47 0 0
Gardani 84 0 2 1 6 6
Ghatghar 0 30 0 58 0 0
Guhire 0 31 0 55 0 0
Indori 1 0 10 0 51 13
Jahagirdarwadi 0 66 0 16 0 0
Jamgaon 4 15 1 42 6 15
139 Kalas Bk. 57 0 2 10 8 0
Kalas Kh. 84 0 0 0 5 0
Katalapur 0 33 0 59 0 0
Kelungan 1 47 0 41 0 1
Khanapur 19 2 0 57 5 5
Khirvire 1 39 0 55 0 0
Kodani 0 73 0 20 0 0
Kohandi 3 32 0 39 0 0
Koltembhe 0 20 0 61 0 0
Kombhalne 7 13 0 68 0 2
Kumbhefal 47 0 11 2 18 9
Ladagaon 0 24 0 67 0 0
Malegaon 2 34 0 41 0 0
Manhere 0 59 0 37 0 0
Manoharpur 54 0 7 0 7 20
Mehenduri 8 1 3 0 64 2
Mhaladevi 33 4 0 0 35 5
Murshet 0 79 0 17 0 0
Muthalane 44 10 0 45 0 0
Mutkhel 0 14 0 71 0 0
Navalewadi 23 0 24 0 22 15
Nilwande 23 15 12 0 21 22
Nimbral 24 9 15 0 24 20
Nirgudwadi (N.V.) 20 24 0 45 0 0
Pabhulwandi 0 26 0 57 0 0
Panjare 0 41 0 49 0 0
Parakhatpur 26 0 38 0 16 5
Pendshet 0 65 0 25 0 0
Pimpalgaon Nakvinda 39 20 0 19 0 1
Pimparkane 15 24 0 46 0 0
Poparewadi 9 13 0 71 0 0
140 Rajur 0 13 0 40 0 1 Randha Bk. 0 73 0 24 0 0 Randha Kh. 7 72 0 12 0 0 Ratanwadi 0 21 0 58 0 0 Rede 27 0 13 0 32 2 Rumbhodi 17 6 6 22 18 6 Samrad 0 23 0 67 0 0 Sarowar (N.V.) 0 52 0 25 0 0 Senit Kh. (N.V.) 0 21 0 69 0 0 Shelvihire 0 23 0 64 0 0 Shendi 0 72 0 9 0 0 Shenit Bk. 0 19 0 74 0 0 Sherankhel 18 13 0 32 0 0 Shinganwadi 0 33 0 53 0 0 Sugaon Bk. 11 1 27 0 32 9 Sugaon Kh. 51 0 10 0 12 9 Sultanpur 77 0 0 0 6 0 Takali 52 0 13 0 14 4 Tambhol 83 0 0 0 1 6 Terungan 0 32 0 43 0 0 Titavi 1 11 0 85 0 0 Udadawane 0 23 0 69 0 0 Unchkadak Kh. 5 0 9 0 43 21 Unchkhadak Bk. 21 0 5 0 44 2 Vashere 67 0 8 0 2 2 Vithe 10 12 6 28 19 13 Waki 0 59 0 35 0 0 Waranghushi 0 52 0 42 0 0 Total 1541 1854 370 2406 677 386 Source: Agriculture Department, Akole 2011.
141 Total 1541 1854 370 2406 677 386 MIN 0 0 0 0 0 0 MAX 84 79 38 85 64 40 MEAN 18 22 4 28 8 5 STDV 24 24 8 27 13 8
MEAN-STDEV -6 -2 -3 2 -5 -4 MEAN 18 22 4 28 8 5 MEAN+lstSTDEV 42 46 12 55 21 13 MEAN+2nd STDEV 66 70 20 81 35 21 MEAN+3rd STDEV 90 94 27 108 48 29 Source; : Agricu ture Department, Akole 2011.
This study area is mostly dominated by fodder, In addition to that rice covers 1854ha. area, Bajara 1341 ha, Sugarcane 677ha. and Maize 370ha. farmers grow these crops with the help of very less water supply. So they have chosen crops which can survive with scarcity of water like Bajara, Maze, Soyabin. If hill side area is irrigated through canal they can take other cash crops also.
5.5.2 Agriculture Income
Table 5. 5 Agriculture Income
Valid Cumulative Income (Rs.) Frequency Percentage Percentage Percentage
None 6 1.5 1.5 1.5
1-50000 250 62.2 62.2 63.7
50001-100000 104 25.9 25.9 89.6
100001- 12 3 3 92.5 150000 Valid 150001- 16 4 4 96.5 200000
200001- 5 1.2 1.2 97.8 250000
Above 250001 9 2.2 2.2 100
Total 402 100 100 -
142 Source: The field Survey (2015).
Above table 5.5 shows the income from agriculture of total questionnaires (people). 250 questionnaires (people) having Rs. 1 to 50,000 from agriculture and their valid percentage are 62.2 whereas the cumulative percentage of this questionnaire is 63.7%. Annual income Rs.5000/- to 100000 is of 104 people (frequency) valid percentage is 299 and cumulative percentage is 89.6. 12 farmers having annual income from agriculture are 100001 to 150000 and their percentage is 3 and cumulative percentage is 92.5. Like this Rs. 150001 to 200000 their percentage is 16 .Only five farmers having agricultural income of Rs.200001 to 450000 their percentage is 1.2 very low whereas only 9 farmers have annual agricultural income is more than above 250001 and their percentage is 2.2.
5.2.3 Other Income
Table 5. 6 Other Income
Valid Cumulative Income (Rs) Frequency Percentage Percentage Percentage
None 336 83.6 83.6 83.6
1-50000 53 13.2 13.2 96.8
50001-100000 13 3.2 3.2 100
Total 402 100 100
Source: The field Survey (2015).
The other income source through which people earning income Rs. 1 - 50,000
IS earned by 53 and their percentage valid percentage and cumulative percentage is 83.6 whereas 13 are earning Rs. 50001 to 100000 annually. Most of population engaged in agriculture their income is low.
143 5.2.4 Fertilizers
Table 5. 7 Distribution of used Fertilizers
Sr. No Particulars Frequency Percentage Cumulative Percentage
1. Organic 291 43.43 43.43
2. Chemical 369 55.08 98.51
3. Other 10 1.49 100
Total 670 100 -
Source: The field Survey (2015).
55% 43% • Organic
I Chemical
I Other
Graph 5. 2 Distribution of used fertilizers
The fertilizers used in the field organic fertilizers used by 291 farmers and their shares in using fertilizers are 43.43%. Chemical fertilizers are used by 369 farmers and the share of chemical fertilizers is 55.08%, whereas other fertilizers are used by 10 farmers which shares 1.49%.
144 5.2.5 Energy Sources
Table 5. 8 Energy Sources
Sr. No Particulars Frequency Percentage Cumulative Percentage
1. Electricity 374 93.5 93.5
2. Diesel Pump 06 1.5 95
3. Solar Energy 03 0.75 95.75
4. others 17 4.25 100
Total 400 100 -
Source: The field Survey (2015).
• Electricity
• Diesel Pump
I Solar Energy
I Others
Graph 5. 3 Energy Sources
Table and pie diagram shows that the energy resources used in study area 93.5% people having electric supply and its frequency is 374. Only 6 peoples are using diesel pump and their percentage is 1.5. Whereas very little frequency is of solar energy resources, i.e. 0.75%. Whereas other energy sources covered 4.25% shares i.e. frequency of 17.
145 5.2.6 Agricultural Facilities
Table 5. 9 Agricultural Facilities
Sr. No Particulars Frequency Percentage Cumulative Percentage
1. Water 336 42.80 42.80
2. Electricity 79 10.06 52.86
3. Fertilizer 355 45.22 98.09
4. Other 15 1.91 100
Total 785 100 -
Source: The field Survey (2015).
^^ • Water
^^^^ • Electricity ^^^^^^B ^^^^H ^^^^P ^^H ^^^H B Fertilizer ^^V • Other
Graph 5. 4 Agricultural Facilities
Table and pie diagram shows about 42.80% farmers have water facilities and their frequency is 336 whereas electrical facilities are used by 79 farmers and it accounts for 10.06%, fertilizers are used by 355 farmers and their share is 45.22%. Whereas 15 are having other agricultural facilities and they share only 1.97% part. In the study area increaseof the agricultural facilities.
146 5.3 Village Wise Soil Moisture Comparison
Any agricultural study should issues related to soil moisture. Geographers are generally assess soil moisture availability using Thorn wait model in specially in dry areas like Karjat tahsil saptarshi (1993) and purandar tahsil (Bhagat,2001) at the advent of RS technique many scholars have done exercise to evaluate soil moisture based on the principal that reflectively of different bands depends upon moisture content of soil surface (Rao, 2010, saptarshi, 2010, Bhagat, 2005) studies in the past have used Landsat ETM+. The present study has used more software technique as data for reflectance for 7 bands have been analytical using are GIS software weekly data can give specific signature for soil moisture contest. Such signature have been observed in the field and systematic ground truthing has given clarity regarding
Indicate dry soils, low, medium, high, very high soil moisture and water bodies. It is also observe that pixels 'Very High' soil moisture has shone the depth of to go can during ground truthing. Dry pixels have shown filled soil moisture less than 5% the image analysis has given results as given in the following table.
147 ft '"'-f' Q landBjanlS.wrtncis img Value Fil« EOii _ H19I1 2S0OJ6 LOM: -11833 Tasseled Cap - LandsatS - Wetness D-llJ30--«.«70drY • ^.>fB - -3J33 !«> B-3,232 --1,997 med.uir INPUT RASTER • -1,996 - -703.7 hi|h • -nii - 3642 vcv hi|)i • 364J-2jaO ..u,
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Table 2. TCT ccKfficients for Landsat 8 at-satellite reflectance.
Landsat 8 (Blue) ((jrecn) (Red) (MR) (SWIRl) (SWIR2) TCT Band 2 Band 3 Band 4 Band 5 Band 6 Band 7
Brijjihtnfss 0.3029 0.2786 0.4733 0.5599 0.508 0.1872 (irccnness -0.2941 -0.243 -0.5424 0.7276 • 0.0713 -0.1608 1 Wetness (I.1.>11 0.1973 0,3^!^.*^ 0.3407 0.7117 0.45 <
Source: OLI and TRS Landsat 8 Satellite Image (2015).
In the present study used geocoded OLI TRS Landsat 8 satellite image for soil moisture measurement.
It is useflil to improve the agro-economy of the population which having less income in Akole tahsil. Additionally, it will provide water to dry areas where water situation is deficit. Stored rainwater in Nilwande dam will be useful to insured food security by conjunctive use of canal.
5.5.1 Village Wise Soil Moisture Content
January month -
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150 Table 5.10 Soil Moisture in January 2015
Wetness area (in ha.)
Village Name Very Grand Dry High Low Medium Water High Total
Agar 0 18 1 7 8 1 35
Agastinagar (N.V.) 2 144 52 107 78 12 396
Akole 1 426 14 122 314 69 947
Ambad 51 341 150 257 215 28 1043
Ambevangan 62 198 160 234 44 2 701
Ambikanagar 118 23 92 43 4 0 281 (N.V.)
Aurangpur 0 130 3 18 124 16 292
Babhul Wandi 272 120 272 228 30 3 924
Bahirwadi 6 79 21 54 80 14 253
Ban 42 196 110 196 78 8 629
Bhandardara 6 218 49 158 112 104 646
Bhojadarawadi 27 74 68 86 11 0 265 (N.V.)
Chichondi 47 266 148 328 77 18 885
Chitalwedhe 17 125 41 62 100 13 357
Deogaon 74 118 165 179 22 1 558
Dhamangaon Awari 65 554 330 504 329 58 1841
Dhokri 29 184 43 76 147 25 506
151 Dhumalwadi 0 171 9 81 158 29 448
Digambar 158 53 178 120 28 231 769
Dongarwadi 72 56 128 130 4 0 390
Gardani 118 316 354 333 175 29 1327
Ghatghar 111 313 433 343 355 286 1840
Guhire 9 116 46 95 37 10 313
Indori 1 142 3 17 238 39 440
Jahagirdarwadi 27 112 121 165 21 2 447
Jamgaon 64 109 117 139 38 2 469
Kalas Bk. 29 417 100 149 349 79 1123
Kalas Kh. 16 . 115 110 103 58 9 411
Katalapur 42 180 157 224 59 15 678
Kelungan 86 234 188 251 48 6 812
Khanapur 3 117 36 72 46 6 280
Khirvire 143 21 167 76 10 3 420
Kodani 21 94 80 127 32 37 391
Kohandi 54 99 153 157 24 103 589
Koltembhe 46 313 113 214 394 234 1314
Kombhalne 261 9 110 32 2 0 413
Kumbhefal 27 291 187 201 153 18 877
Ladagaon 45 109 109 158 20 0 442
Malegaon 99 34 140 128 13 50 465
152 Manhere 34 235 142 309 38 2 760
Manoharpur 16 114 36 69 65 6 306
Mehenduri 193 184 265 128 158 32 960
Mhaladevi 65 132 185 115 88 13 598
Murshet 135 94 160 174 30 199 792
Muthalane 459 74 747 243 10 0 1535
Mutkhel 47 333 109 225 305 404 1424
Navalewadi 0 46 2 25 34 11 119
Nilwande 68 75 98 55 51 37 384
Nimbral 18 150 79 85 140 14 486
Nirgudwadi (N.V.) 5 47 51 75 7 1 185
Pabhulwandi 115 107 190 149 25 3 589
Panjare 380 228 384 326 100 113 1532
Parakhatpur 2 176 15 47 99 10 350
Pendshet 20 174 58 137 108 9 506
Pimpalgaon 338 284 405 320 116 28 1491 Nakvinda
Pimparkane 112 81 263 211 12 46 724
Poparewadi 127 7 102 41 0 277
Rajur 333 258 374 330 61 2 1358
Randha Bk. 10 63 56 109 7 5 251
Randha Kh. 27 142 93 172 18 12 464
153 Ratanwadi 121 278 217 306 258 366 1547
Rede 10 102 43 48 64 8 275
Rumbhodi 33 335 102 151 250 52 924
Samrad 61 159 301 308 136 216 1181
Sarowar (N.V.) 6 101 16 46 55 5 231
Senit Kh. (N.V.) 141 221 201 239 62 2 865
Shelvihire 121 51 209 150 4 11 546
Shendi 6 87 44 102 20 1 260
Shenit Bk. 112 115 139 156 23 3 548
Sherankhel 157 107 270 239 16 3 792
Shinganwadi 153 92 262 151 48 66 772
Sugaon Bk. 6 285 12 53 201 27 584
Sugaon Kh. 8 171 34 70 99 17 399
Sultanpur 1 54 20 27 50 16 167
Takali 59 187 97 93 145 22 603
Tambhol 64 196 201 254 91 19 826
Terungan 47 141 97 155 101 24 564
Titavi 75 88 245 229 14 27 678
Udadawane 331 250 419 336 222 179 1737
Unchkadak Kh. 84 179 117 105 102 11 598
Unchkhadak Bk. 1 128 4 24 110 21 289
Vashere 20 306 91 232 95 8 752
154 Vithe 9 151 67 87 88 12 415
Waki 12 126 76 170 23 8 416
Waranghushi 169 458 367 529 125 6 1654
Grand Total 6566 14011 12221 13580 7911 3641 57929
Source: OLI and TRS Landsat 8 Satellite Image (18 Jan-2015).
Table 5.11 Soil Moisture in May-2015
Wetness area (in ha.)
Village Name Very Grand Dry High Low Medium Water High Total
Agar 1 0 5 16 0 12 35
Agastinagar (N.V.) 104 7 162 101 7 15 396
Akole 78 7 237 393 5 227 947
Ambad 327 44 412 190 37 31 1043
Ambevangan 326 145 119 19 92 0 701
Ambikanagar 129 16 112 8 16 0 281 (N.V.)
Aurangpur 10 0 65 147 0 69 292
Babhul Wandi 392 83 294 79 68 9 924
Bahirwadi 46 2 105 85 2 15 253
Bari 254 153 122 32 66 2 629
Bhandardara 202 44 187 105 32 77 646 Bhqjadarawadi 120 17 101 11 17 0 265 (N.V.)
Chichondi 363 123 200 97 79 22 885
Chitalwedhe 71 11 72 127 10 68 357
Deogaon 252 94 132 34 47 1 558
Dhamangaon Awari 769 60 776 138 92 6 1841
155 Dhokri 77 2 191 170 3 62 506 Dhumalwadi 60 2 218 147 4 19 448 Digambar 206 74 170 50 41 227 769 Dongarwadi 177 29 138 18 25 2 390
Gardani 321 6 705 253 11 31 1327
Ghatghar 472 127 337 366 125 415 1842
Guhire 97 48 65 55 27 22 313
Indori 5 3 30 213 1 188 440
Jahagirdarwadi 223 93 68 9 57 1 451
Jamgaon 153 84 146 41 42 3 469
Kalas Bk. 116 6 276 530 6 188 1123
Kalas Kh. 55 0 228 106 1 21 411
Katalapur 283 133 169 26 63 4 678
Kelungan 357 159 195 22 80 1 815
Khanapur 38 1 111 107 0 23 280
Khirvire 181 40 137 35 27 2 421
Kodani 110 93 81 43 28 36 391
Kohandi 207 75 118 47 45 97 589
Koltembhe 310 129 332 280 55 208 1314
Kombhalne 229 35 88 22 36 3 413
Kumbhefal 122 2 354 320 5 74 878
Ladagaon 207 92 91 5 46 — 442
Malegaon 150 155 46 12 54 48 465
Manhere 405 135 124 11 85 0 760
Manoharpur 57 3 133 85 5 23 306
Mehenduri 305 28 244 257 40 85 960
Mhaladevi 145 5 214 148 9 78 598
Murshet 178 192 154 66 55 148 792
156 Muthalane 852 123 389 48 123 1 1535
Mutkhel 344 92 438 326 50 176 1425
Navalewadi 9 0 46 58 0 5 119
Nilwande 105 25 85 89 19 62 384
Nimbral 72 3 128 168 7 109 486
Nirgudwadi (N.V.) 87 7 75 6 9 0 185
Pabhulwandi 233 24 187 108 29 8 589
Panjare 354 478 343 186 110 62 1532
Parakhatpur 58 1 84 165 3 38 350
Pendshet 215 78 114 46 47 6 506
Pimpalgaon 536 108 534 207 84 22 1491 Nakvinda
Pimparkane 349 71 176 26 55 47 724
Poparewadi 146 27 68 12 24 1 277
Rajur 483 385 288 50 150 2 1358
Randha Bk. 108 54 35 15 30 9 251
Randha Kh. 123 81 110 84 33 34 464
Ratanwadi 390 264 276 200 95 322 1547
Rede 39 2 66 93 2 74 275
Rumbhodi 144 10 223 368 13 165 924
Samrad 386 220 229 114 100 134 1183
Sarowar (N.V.) 101 27 74 13 15 0 231
Senit Kh. (N.V.) 390 156 178 31 105 6 867
Shelvihire 273 67 130 20 45 11 546
Shendi 80 26 80 47 13 13 260
Shenit Bk. 241 49 181 35 39 3 548
Sherankhel 281 25 350 93 34 10 792
Shinganwadi 220 269 102 66 61 55 772
Sugaon Bk. 25 0 103 334 0 122 584
157 Sugaon Kh. 54 4 99 188 5 49 399
Sultanpur 5 0 52 79 0 32 168
Takali 114 8 212 206 8 56 603
Tambhol 276 9 413 111 13 4 826
Terungan 217 132 106 42 58 10 564
Titavi 303 167 69 21 91 28 678
Udadawane 397 483 241 227 130 261 1738
Unchkadak Kh. 108 21 215 187 11 57 598
Unchkhadak Bk. 4 1 24 125 1 135 289
Vashere 271 5 338 114 19 6 753
Vithe 102 12 105 128 16 52 415
Waki 159 53 96 61 34 13 416
Waranghushi 757 258 422 63 155 2 1657
Grand Total 18099 6380 15746 9582 3381 4764 57951
Source: OLI & TRS Landsat 8 Satellite Image (10 May- 2015).
The above table 5.11 clearly shows village like to Rumbhodi, Indori, Kalas Kh.,Unchkhadak kh., Nimbral, Mhaladevi, Dhokri, Takali, Sugaon Kh., have good soil moisture even in month of May. All the villages has counted under canal irrigation proposals executed. If suggest plan is executed the village like Dhamangaon Awari, Bahirwadi, Mehenduri, Tambhol, Sultanpur, Vashere shorting very low moisture even in May 2015. There is need of the canal irrigation facility. In view of this it is suggest from present research work new canal site should be proposed in government plan for maximum benefit in the study area.
5.3.2 Soil Moisture Difference
Agricultural study should issues related to soil moisture. At the advent of RS technique many scholars have done exercise to evaluate soil moisture based on the principle that reflectively of different bands depends upon moisture content of soil surface. The present study has used more sophisticated techniques as data for
158 reflectance for 7 bands have been analytical using GIS software comparatively January and May 2015 satellite image can give a specific signature for soil moisture.
The present study used geocoded OLI TRS Landsat 8 satellite image and hence soil moisture contents can be observed at difference with village map superimposed.
Table 5.12 Soil Moisture Difference in 2015
Sr. No. SWI Class Jan area (ha.) May area (ha.) Difference (ha.)
1 Dry 6668.12 18219.34 -11551.22
2 Low 12350.73 15791.98 -3441.25
3 Medium 13682.58 11763.56 1919.02
4 High 14074.69 3410.83 10663.86
5 Very High 7963.22 6438.91 1524.31
6 Water 3652.79 2767.51 885.28
Total 58392 58392
Source: OLI and TRS Landsat 8 Satellite Image (2015)
159 Table 5.13 Soil Moisture Difference in 2015
Area Jan 2015 (%) Area May 2015 (%) Difference (%)
11.46 31.31 -19.85
21.22 27.14 -5.92
23.51 20.22 3.29
24.19 5.86 18.33
13.68 11.06 2.62
6.28 4.76 1.52
100 100
Source: OLI and TRS Landsat 8 Satellite Image (2015)
The table shows that as mentioned above village wise areas in different categories have been computed using GIS techniques and tabulated as given below.
160 5.3.3 Season Wise Soil Moisture
Table 5.14 January 2015
Sr. no. SWI Class Area (ha) Area (%)
1 Dry 6668.12 11.46
2 Low 12350.73 21.22
3 Medium 13682.58 23.51
4 High 14074.69 24.19
5 Very High 7963.22 13.68
6 Water 3652.79 6.28
Total 58392 100
Source: OLI and TRS Landsat 8 Satellite Image (18 Jan-2015).
Table 5.15 May 2015
Sr. No. SWI Class Area (ha) Area (%)
1 Dry 18219.34 31.31
2 Low 15791.98 27.14
3 Medium 11763.56 20.22
4 High 3410.83 5.86
5 Very High 6438.91 11.06
6 Water 2767.51 4.76
Total 58392 100
Source: OLI & TRS Landsat 8 Satellite Image (10 May-2015)
161 The above table clearly shows that dry soil moisture percentage is high in month of May. If suggested plan is executed, very low moisture even in may can get irrigation facility with canal. This may be considered that the advanced that suggested canal site the proposed in government plan.
5.4 Population Analysis
Table 5.16 Gender of the Family Members
Cumulative Gender Frequency Percentage Valid percent percent
Male 889 44.72 44.72 44.72
Valid Female 1099 55.28 55.28 100
Total 1988 100
Source: Tlie field Survey (2015).
According to the table, the numbers of female marginally exceed the number of male in the overall study area. It means, it is a very good sex ratio.
The above table shows the frequency and percentage of male and female i.e. sex ratio. The male frequency is 8.89 which covers 44.72%. Proportion of population where female frequency is 1099 which cover of 55.28%. There is a high proportion of women population due to migration of the male population in other places for employment.
162 5.4.1 Age Group
Table 5.17 Age Group of the Family Members
Cumulative Age Frequency Percentage Valid percent Percentage
0-14 233 11.72 11.72 11.72
15-59 1519 76.41 76.41 88.13 Valid Above 60 236 11.87 11.87 100
Total 1988 100 - -
Source: The field Survey (2015).
For socioeconomic survey 12 villages were selected. In this from Gardani village more household sample had been taken. Composition of the population, according to the age group is known as age group structure. This characteristic ofhuman populations is fundamental to understand demographic process of fertility, mortality and migration. It is also used in ecology to determine the overall age distribution of a population an indication of the reproductive capabilities and the likelihood of the continuation of a species. Age composition may be summarized in terms of age groups e.g. 0-14 years, 15-59 years and 60 above.
The age group structure is most commonly used method of population along their characteristics. The bulk of the population is found in the age group of 15-30 and 30-60 years indicating availability of working population. We found less population in the age group of 0-Hand 60 and above years, as there is no medical facility in the village along with unhygienic condition and malnutrition tend to reduce the life expectancy of villagers. While the economic burden of children, awareness about family size and government policies tend to reduce the number of children per family. The age group 0-14 has 233 people, i.e. 11.72%, whereas the age group of 15 to 59 has 1579 people i.e. 76.41%. Remaining 236 people are above 60 years and their share is 11.87%. It means that the adult age group is higher which will be helpful for overall development of the study area in the current situation.
163 5.4.2 Occupation
Table 5.18 Occupation
Agriculture Others
Occupation Percentag Percentag Frequency Frequency e e
Yes 391 97.3 69 17.2
No 11 2.7 333 82.8
Total 402 100 402 100
Source: The field Survey (2015).
The occupational structure of 402 people out of 402 questionnaire 391 people are engaged in agriculture and they are shares 97.3% and other remaining 11 people are not engaged in agriculture, whereas 69 people engage in other occupations and they are not working in another occupation, sharing 2.7%.
5.4.3 Dependent Population on Agriculture
Table 5.19 Dependent Population on Agriculture
Valid Cumulative Family Member Frequency Percentage Percentage Percentage
None 4 1 1 1
lto3 60 14.9 14.9 15.9
4 to 6 288 71.6 71.6 87.6 Valid 7 to 9 46 11.4 11.4 99
10 to 12 4 1 1 100
Total 402 100 100
Source: The field Survey (2015).
164 The agricultural dependency ratio out of 402 family's banders 4 family is not dependent on agriculture. There percentage 1.60 people having rate 1 to 3 and their shares are 14.9 and valid percentage are 14.9 as well as cumulative percentage is 15.9. 4 to 6 valid families are 288 and their percentage is 71.6%. And valid percentage is 71.6. Families with 7 to 9 dependents have 46 frequencies their percentage and vaUd percentage is 11.4 and cumulative percentage is 99.0. And the remaining 10 to 12 questionnaires have 4 frequencies. Their percentage and valid percentage is 1. Due to which cumulative percentage is 100.
5.5Water Management
5.5.1 Irrigation Sources
Table 5.20 Irrigation Sources
Sr.No Particulars Frequency Percentage Cumulative Percentage
1. Well 307 64.76 64.76
2. Tube well 07 1.47 66.23
3. Ponds 12 2.53 68.76
4. River 127 26.79 95.57
5. Others 21 4.43 100
Total 474 100
Source: The field Survey (2015).
165 There are various sources of water in the study area. Out of 100% questionnaires, 64.76% farmers having well irrigation and their frequency are 307. Tube well is irrigation is used by only 7 farmers and their shares is 1.47%, whereas 2.53% farmers are using pond irrigation and frequency is 12. Whereas 26.79% farmers are adopted river based irrigation facilities and the frequency is 127. Whereas other irrigation methods has been adopted by 21 farmers and the percentage is 4.43. Average farmers depend on well, so in this area canal irrigation is mostly required.
• Well BTube well DPonds D River • Others
Graph 5. 5 Irrigation Sources
Table 5. 21 Irrigation Expenditure (per ha.)
Comparative Irrigation Cost Analysis Particulars Well River Canal Digging Expenditure (Rs.) 70200 - - Pipeline, motor and other 24600 395200 - expenditure (Rs.) Electricity Monstrance & Other 20000 30000 - Expenditure (Rs.) (5 HP) (7.5HP) Water Tax (Rs.) - - 2400 Total Cost (Rs.) 114800 425200 2400
Source: Appendix L and M (2015).
166 There are three major sources of water in the study area. Out of 100% farmers, 64.76% farmers having well irrigation because the river distance and cost of water is high. Tube well is irrigation is used shares is 1.47%, whereas 2.53% farmers are using pond irrigation. Whereas 26.79% farmers are adopted river based irrigation facilities. Average farmers depend on well in one season, so in this area canal irrigation is mostly required.
5.5.2 River lifts irrigation
Advantages
1. As assure Pravara river is perennial and its water is distributed in the limited part of the study area
2. The system permits easy installation of drip and sprinkler irrigation. However, it requires additional capital and recurring expenditure.
3. The river water quality is fairly good as TDS, TSS (Total suspended solids) and total desalts salts are less.
Disadvantages
1. The part of the rivers in the study area axis as the canal and hence there is conflicts between the study area those in downstream zone mainly from the villages in Sangmner tahsil.
2. Lift irrigation can be fast, effective for the villages within 2/3 km. away from the river, therefore, the great deals of agronomic disparity between riverside farmer and farmer located on higher side.
3. The tribal villages are consisted with below poverty level. It is ethical to provide sufficient water to the dry people.
5.5.3 Well Irrigation
Advantages-
1. Irrigation is comparatively less than other irrigation sources. 2. It requires average space for construction and maintenance.
167 Disadvantages
1. Water quality is the main issue of well irrigation where large volume of water is brackish in the aquifer which TDS and TSS are more than the limit. 2. TDS and TSS are high mainly because of the use of chemical fertilizers and pesticide in the agricultural area of the basin. 3. Majority of well in dry area in summer season espacilly in February to mid- June. It means the water supply is limited to two cropping season Kharip and Rabbi. 4. Limited aquifer - the tahsil has limited storage of ground water if the planner encourages the well irrigation it may not be sustainable. Here, the study suggests to use well water is a conjunctive manner.
5.5.4 Canal Irrigation
Advantages-
1. The canal irrigation system is nothing but surface water resources which is renewed in each monsoon season. Therefore, sustainability this water resources is more than more irrigation. 2. The water quality is good with TDS and DSS and below the permissible limit.
Disadvantages
1. Canal rotation- canal rotation system is that is availability is periodical. If there is scarcity of water the duration of water increased the field investigation has revaluated that canal rotation is after 4-5 weeks. This is not suitable was crops like vegetables, onion, wheat, etc. this may be one of important reasons why farmers choose sugar cane rather than vegetables. They impact of the sugar cane crop is well known as observed in the studies carried out by Saptarshi (2008), Bhagat (2014), More (2011).
168 5.5.5 Water Conservation
Table 5. 22 Water Conservation
Sr. No Types of Activity Frequency Percentage Cumulative Percentage
1. Social Dam 291 59.38 59.38
2. CCT 90 18.38 77.76
3. Others 109 22.24 100
Total 490 100 -
Source: Tiie field Survey (2015).
• Social Dam
• Flat Groove
H Others
._i
Graph 5. 6 Water Conservation
Above table 5.22 and pie diagram shows that water conservation as a social activity in the study area. Out of 100% social activities for water conservation 59.38% share are accounted as social dams and its frequency is 29%. CCT (Continuous Contour Trenching) is done by 18.38% people having a frequency of 90, whereas 109 farmers have contributed for other methods of conservation of water and it account 22.24%.
169 5.5.6 Water Collection from Distance
Table 5.23 Water Collection from Distance
Valid Cumulative Distance (m.) Frequency Percentage Percentage Percentage
None 161 40.0 40.0 40.0
1-500 101 25.1 25.1 65.2
501-1000 33 8.2 8.2 73.4
Valid 1001-1500 14 3.5 3.5 76.9
1501-2000 18 4.5 4.5 81.3
Above 2500 75 18.7 18.7 100.0
Total 402 100.0 100.0
Source: The field Survey (2015).
Above table 5.23 shows that Pipeline is mainly used system in the study area. 161 farmers have not brought water from any distance, their percentage is 40, from 1 to 500m distance, 101 famers are caring from water and their share is 25.1%. 501 - 1000m. (frequency is 33, 8.2%), 1001 - 1500 m (frequency is 14, 3.5%), 1501 - 2000m. (frequency is 18, 4.5%) and 75 farmers have brought water from more than 2500m distance and they account for 18.7%.
Table 5. 24 Rotation of Water for Crops
Valid Cumulative Days Frequency Percentage Percentage Percentage
0-5 43 10.7 10.7 10.7
6-10 202 50.2 50.2 60.9 Valid 11-15 152 37.8 37.8 98.8
Above 15 5 1.2 1.2 100.0
170 Valid Cumulative Days Frequency Percentage Percentage Percentage
0-5 43 10.7 10.7 10.7
6-10 202 50.2 50.2 60.9 Valid 11-15 152 37.8 37.8 98.8
Above 15 5 1.2 1.2 100.0
Total 402 100.0 100.0
Source: The field Survey (2015).
The above table 5.24 shows that out of 100% farmers, 10.7% farmers providing water to sail before 5 days of the first water and their frequency is 43.50.2% people means 202 frequencies provides water in between 6 to 10 days. 37.8% people that are 152 frequencies provides water to soil in 11-15 days, whereas only 1.2 people provide water to soil above 15 days and their frequency is 5.
171 5.6 Water Requirement
Table 5. 25 Water Requirements for Crops
Current Water Requirement in (mh)
Rain Requirement Sr. TGA Name of village Water of Water Deficit (mh) No. (ha.) (mh) (mh)
1 Agar 35 7 43 -36
2 Agastinagar 396 80 112 -31
3 Akoie 947 192 884 -692
4 Ambad 1042 212 398 -186
5 Ambikanagar 281 57 130 -73
6 Aurangpur 292 59 281 -222
7 Bahirwadi 253 52 253 -201
8 Dhamangaon Awari 1840 374 573 -199
9 Dhokari 506 103 297 -194
10 Dhumalwadi 448 91 270 -179
11 Gardani 1326 269 384 -114
12 Indori 440 89 790 -700
13 Kalas Bk. 410 83 914 -831
14 Kalas Kh. 1122 132 228 -96
15 Khanapur 280 57 134 -77
16 Kumbhephal 877 178 528 -350
172 17 Manoharpur 306 62 138 -75
18 Mehenduri 960 195 664 -469
19 Mhaladevi 598 122 334 -212
20 Nawalewadi 119 24 120 -96
21 Nilwande 384 78 136 -58
22 Nimbral 486 99 401 -302
23 Parkhatpur 350 71 356 -285
24 Rede 275 56 337 -281
25 Rumbhodi 923 188 809 -621
26 Sugaon Bk. 457 93 688 -595
27 Sugaon Kh. 399 81 290 -209
28 Sultanpur 167 34 95 -61
29 Takali 603 123 409 -287
30 Tambhol 825 168 329 -162
31 Unchkhadak Bk. 598 122 525 -404
32 Unchkhadak Kh. 289 59 480 -422
33 Vashere 753 153 335 -182
Total 18988 3762 12667 -8905
Source: Agricultural Department, Akole (2011).
The water requirement for the present agriculture has been computed by multiplying hectarage under different crops by ecological need of water as given by Bhagat (2001). The formula used to compute total water requirement is given below.
173 WR j = V Aij X Ri
1=1
Aij = Area under i* crop in j* village.
Ri= water requirement for i"' crop n= Number of crops grown in the area
WRj== Water requirement for agriculture in a village j.
32 y WRj = Water Requirement of the agriculture in 32 villages.
The map of village wise requirement of the area under study has been prepared using GIS technique. Total requirement of agriculture is 12667m/ha. However, the water from rainfall in the area is 3762m/ha which is the product of rainfall and TGA. As assumed by Saptarshi 1993, Bhagat (2001), More(2011), Patil (2013), etc. available rain water for crops in tropical areas may be considered after 40% loss by way of evaporation and 20% loss by way of percolation. Thus, rain water available for agriculture is
TGA X Rainfall in mm. x 0.4
Rainwater - 20% loss due to runoff and percolation - 40% loss due to evaporation = 0.4 rainfall in m.
This is certainly less than the requirement by 8905m/ha. Therefore, it may be assume that this loss is made up by tapping. The resources from river and wells in the vicinity of the Pravara. The map of distribution of crop clearly indicate that the crops, water requirements of which is high viz. sugarcane, fodder, etc. are concentrated in the vicinity of river.
So far as soil cover is concern there is no significance difference in the villages showing concentration of crops like Jowar, Bajara, Maize, and crops like Sugarcane, Onion, etc. This is to say that actual constructed long the upper contour, these villages can grow crops fetching good income. Thus, the suggested canal site may be justified.
174 Mksladoi \bkr«dari
1.5 0.75 0 1.5 Km I I I
73°57'30"E 74''U'«"E 74°2'3U"E 74°5'U"E
Legend: Sourct: ^M > 2.5 Std. Dev. 11 Survc\ of India (SOI I Topomiips Scali'- 1:5(MKMI 2) Ahmetlnagar Irrigation department ^1.5-2.5Std. Dev. ^0.50-1.5 Std. Dev. I I -0.50 - 0.50 Std. Dev. ^M < -0.50 Std. Dev.
Fig. 5. 9 Rain Water
5.7 Irrigation
5.7,1 Methods of Agriculture
Table 5.26 Methods of Agriculture
Sr. No Particulars Frequency Percentage Cumulative Percentage
1. Modem 288 34.32 34.32
2. Traditional 149 17.75 52.07
3. Others 402 47.93 100
Total 839 100 -
Source: The field Survey (2015).
175 H Modern
• Traditional
• Others
Graph 5.7 Methods of Agriculture
Above table shows that the method of agriculture by the farmer of the study area 288 farmers are adopting modem method of agriculture and its shares are 34.32%, whereas 149 frequencies are using traditional agricultural methods and they are capturing 17.75% shares. But 402 fanners are using other methods of agriculture and their percentage is 47.93%.
5.7.2 Types of Irrigation
Table 5.27 Types of Irrigation
Sr.No Particulars Frequency Percentage Cumulative Percentage
1. Flow Method 375 74.25 74.25
2. Drip 94 18.61 92.86
3. Sprinkler 14 2.77 95.65
4. Others 22 4.35 100
Total 505 100 -
Source: The field Survey (2015).
[76 • Flow Method
• Drip
H Sprinkler
• Others
Graph 5.8 Types of Irrigation
Table 5.28 Changes in Irrigation Method
Cumulative Sr. No Particulars Frequency Percentage Percentage
1. Drip Method 369 66.72 66.72
2. Inner Drip 53 9.58 76.57
3. Sprinicler 93 16.83 93.13
4. Others 38 6.87 100
Total 553 100 -
Source: The field Survey (2015).
Above table shows that the types of irrigation in the study area out of 100%, 74.25% questionnaires are using a flow method and their frequency is 375. Drip irrigation is adopted by 94 questionnaires and the share is 18.61%. If it is consider that use of drip irrigation is suitable 66.72%. People feels that this method should be improve and their frequency is 369. Whereas 53 questionnaires are feeling that water should provide to agricultural land by the inner drip method and their shares are 58%.
177 • Drip Method
• Inner Drip
• Sprinkler
• Others
Graph 5,9 Types of irrigation
Above table shows the types of iirigation in study area according to the circle shown in above pie diagram 2.77% People having sprinkler irrigation, but 16.83% questionnaires feel that it should be get change and their frequency is 93. Whereas 4.35% people frequency 22 having other sources of irrigation but 38 frequency 6.87% people think that it should also get change.
Table 5.29 Arable Land Conversion in Productive Land
Valid Cumulative Frequency Percentage Percentage Percentage
No 25 6.2 6.2 6.2
Vahd Yes 377 93.8 93.8 100.0
Total 402 100.0 100.0
Source: The field Survey (2015).
Above table shows the land converted into productive land through providing water. 93.8% people can convert their land in productive phase if they provide water to the land in time and their frequency is 377. Arable land have been converted in this time period due to rapid access of Pravara river irrigation system.
178 5.8 Problems of Agriculture
Table 5.30 Water Problems in Agriculture
Valid Cumulative Frequency Percentage Percentage Percentage
No 162 40.3 40.3 40.3
Valid Yes 240 59.7 59.7 100.0
Total 402 100.0 100.0
Source: The field Survey (2015).
Table 5.31 Electricity Problems in Agriculture
Valid Cumulative Frequency Percentage Percentage Percentage
No 127 31.6 31.6 31.6
Valid Yes 275 68.4 68.4 100
Total 402 100 100
Source: The field Survey (2015).
Table 5.32 Investment Problems in Agriculture
Valid Cumulative Frequency Percentage Percentage Percentage No 164 40.8 40.8 40.8 Valid Yes 238 59.2 59.2 100 Total 402 100 100
Source: The field Survey (2015).
179 Table 5.33 Others Problems in Agriculture
Valid Cumulative Frequency Percentage Percentage Percentage
No 388 96.5 96.5 96.5
Valid Yes 14 3.5 3.5 100
Total 402 100 100
Source: The field Survey (2015).
Out of 100% people 59.7% are facing the problem of agricultural activities and remaining 40.30% people having permanent sources of water for getting solutions on their problems. The farmers are adopting tankers, drip irrigation along with it they are cultivating ting such crops which required less water.
In the study area out of 100% questionnaires 68.4% that means 275 people are not satisfied with electrical facilities because of due to failure in supply of electricity on time which creates havoc for the crops.
Out of 100% questionaries' 98.3% people didn't feel the need of tankers based on unavailability of water. It means only 1.7% people are using tankers. Water 313 peoples (77.9%), feels that drip irrigation should not be used for agree because if these people consider the structure and texture of soils, slopes and high rainfall water will easily available in the area with very less expenditure only the water will get available through canals or need of water storage dams and 22% people are using drip irrigation and trying to increase mere production from agriculture. Along with it 68.4% farmers take crops which required less water.
59.2% people feels that agro production will increase if there will be investment in the field and remaining 40.8% farmer likely to do agriculture in with own traditional methods.
Along with it time to time they are many problems are created during the cultivation so the farmers are thinking about fodder crops which can help them in the development and improvement in their economic problem. Such type has 3.5%
180 people. Because there is no guarantee of rates for crops, unsuitable climate, natural disasters, pollutions as well as man-made problems effects on the less production. This is not affordable for the farmer of that study area. So some farmers are cultivating their land with less expenditure.
5.9 Testing of Hypotheses
5.9.1 Hypothesis No. 1: (Chi-Square)
Ho: There is no significant association between the type of the soil, depth of the soil and period of providing water to the soil.
HI: There is a significant association between the type of the soil, depth of the soil and period of providing water to the soil.
Table 5.34 Descriptive Statistics
Std. N Mean Minimum Maximum Deviation
Type of soil 402 1.38 0.977 1 6
Period of giving 402 2.3 0.67 1 4 water to soil
Depth of the Soil 402 1.5 0.866 0 6
Source: The field Survey (2015).
Table 5.35Test Statistics
Type of Soil Period of giving Water to Soil Soil Depth
Chi-square 1250.358 252.547 760.358
df 5 3 5
Asymp. sig. 0 0 0
Source: The field Survey (2015).
181 The Chi square calculated value is more than the table value in all the cases (Table Value is 11.070,7.815 and 11.070 respectively). Also the 'P' value is less than 0.05 (p < 0.05), which means that the null hypothesis is rejected and the alternate hypothesis is accepted. Hence it can be concluded that there is a significant association between the type of soil, the depth of the soil and the period of providing water to the soil. The type of the soil and the depth of the soil determine the period of providing water to the soil.
5.9.2 Hypothesis No. 2: ('Z' Test)
Ho: There is no significant difference in the sources of water available in the sample area.
Hi: There is a significant difference in the sources of water available in the sample area.
Table 5.36 One-Sample Statistics
Source of Water N Mean Std. Deviation Std. Error Mean
Well 402 0.76 0.425 0.021
Tube well 401 0.02 0.131 0.007
Farm pond 402 0.03 0.17 0.008
River 401 0.32 0.466 0.023
Others 402 0.05 0.223 0.011
Source: The field survey (2015).
182 Table 5.37 One-Sample Test
Source of Water N Mean Std. Deviation Std. Error Mean
Well 402 0.76 0.425 0.021
Tube well 401 0.02 0.131 0.007
Farm pond 402 0.03 0.17 0.008
River 401 0.32 0.466 0.023
Others 402 0.05 0.223 0.011
Source: The field survey (2015).
The calculated value of 'Z' is more than the table value in all the cases (Table Value is 1.96). Also the 'P' value is less than 0.05 (p < 0.05), which means that the null hypothesis is rejected and the alternate hypothesis is accepted. Hence it can be concluded that there is a significant difference in the sources of water available in the sample area. There are different sources of water available in the sample area and it differs from village to village.
5.9.3 Hypothesis No. 3: ('Z' Test)
HQ: There is no significant difference in the types of crop cultivated in the sample area.
Hi: There is a significant difference in the types of crop cultivated in the sample area.
Table 5.38 One-Sample Statistics
Crop N Mean Std. Deviation Std. Error Mean
Com 402 0.11 0.309 0.015
Bajra 402 0.61 0.488 0.024
Wheat 402 0.55 0.498 0.025
183 Sugarcane 402 0.43 0.496 0.025
Soyabean 402 0.11 0.316 0.016
Onion 402 0.63 0.482 0.024
Ground Nut 402 0.03 0.177 0.009
Gram 402 0.22 0.414 0.021
Pomogranate 402 0.12 0.328 0.016
Tomato 402 0.23 0.422 0.021
Grass 402 0.15 0.357 0.018
Others 402 0.1 0.303 0.015
Source: The field Survey (2015).
Table 5.39 One-Sample Test
Test Value = 0
95% Confidence
Crop Sig.(2- Mean Interval of the z df tailed) Difference Difference
Lower Upper
Com 6.93 401 0 0.107 0.08 0.14
Bajra 25.146 401 0 0.612 0.56 0.66
Wheat 22.239 401 0 0.552 0.5 0.6
Sugarcane 17.494 401 0 0.433 0.38 0.48
Soyabean 7.11 401 0 0.112 0.08 0.14
Onion 26.374 401 0 0.634 0.59 0.68
184 Ground Nut 3.661 401 0 0.032 0.01 0.05
Gram 10.601 401 0 0.219 0.18 0.26
Pomogranate 7.461 401 0 0.122 0.09 0.15
Tomato 10.986 401 0 0.231 0.19 0.27
Grass 8.388 401 0 0.149 0.11 0.18
Others 6.749 401 0 0.102 0.07 0.13
Source: The field Survey (2015).
The calculated value of 'Z' is more than the table value in all the cases (Table Value is 1.96). Also the 'P' value is less than 0.05 (p < 0.05), which means that the null hypothesis is rejected and the alternate hypothesis is accepted. Hence it can be concluded that there is a significant difference in the types of crop cultivated in the sample area. There are different types of crops cultivated in the sample area and it differs from village to village.
5.9.4 Hypothesis No. 4: (Correlation)
Ho: There is no significant association between the total number of family members and the number of family members dependent on agriculture.
Hi: There is a significant association between the total number of family members and the number of family members dependent on agriculture.
Table 5. 40 Descriptive Statistics
Mean Std. Deviation N
Depend - Agriculture 4.64 1.589 402
Total number of family members 4.9453 1.61415 402
Source: The field Survey (2015).
185 Table 5.41 Correlations
Total Number Depend of Family Agriculture Members
Correlation 1 .890'* Coefficient Depend agriculture Sig. (2-tailed) 0
N 402 402 Spearman's Correlation .890** 1 Total number Coefficient of family Sig. (2-tailed) 0 members N 402 402
Source: The field Survey (2015).
**. Correlation is significant at the 0.01 level (2-tailed).
The 'P' value is less than 0.05 (p < 0.05), which means that the null hypothesis is rejected and the alternate hypothesis is accepted. Hence it can be concluded that there is a significant association between the total number of family members and the number of family members dependent on agriculture. Also there is a highly positive correlation among the variables which means that an increase in the number of family members will only lead to an increase in the number of dependents on agriculture.
5.9.5 Hypothesis No. 5: ('Z' Test) Percentage of Agricultural Income in the Total Income of the Respondent.
HQ: There is no significant contribution of the agricultural income in the total income.
Hi: There is a significant contribution of the agricultural income in the total income.
186 Table 5.42 One-Sample Statistics
Std. Std. N Mean Error Deviation Mean
Percentage contribution of 402 93.59 17.99 0.897 agriculture income in total income
Source: The field Survey (2015).
Table 5.43 One-Sample Test
Test Value = 0
95%
Sig. Confidence Mean Interval of the z df (2- Difference tailed) Difference
Lower Upper
Percentage contribution of 104.301 401 0 93.586 91.82 95.35 agriculture income in total income
Source: The field Survey (2015).
The calculated value of 'Z' is more than the table value (Table Value is 1.96). Also the 'P' value is less than 0.05 (p < 0.05), which means that the null hypothesis is rejected and the alternate hypothesis is accepted. Hence it can be concluded that there is a significant contribution of the agricultural income in the total income. If the respondents' agricultural income is affected their total income will also be affected significantly, since there is a significant contribution of agricultural income on total income.
187 5.9.6 Income Per Hectare of Land to be Calculated in Order to Show the Loss Per ha. When the Land is Going Under the Water Canal Project:
Table 5.44 Income per ha. of Agricultural Land
Total Agricultural Income 29431000
Total Agricultural Land (in ha.) 549.01
Income Per ha. 53607.40
Source: The field Survey (2015).
Calculate the hectare of land that will go under the project and multiply it with the income per hectare. The amount derived will be the loss per hectare if the agricultural land is sacrificed for the project.
5.10 Nilwande Dam Canal Site Sutablity
Canal construction work is still uncompleted due to locals public obstruction, therefore researchers have put their observation as follows.
• Canals site should be shift toward the hill side. • Dig the canals at 630 m. depth and circulate the water of Bhandardara and Nilwande jointly for area of Nilwande project under irrigation. There are two objectives of suitable canal site in the study area
a) To conserve acquired fertile and horticulture area. b) To increased the irrigated area fi"om new canal at suitable site. For the fulfillment of above objectives following are the suitable canal sites.
5.10.1 Suitable Canal Site No. 1
Actual sanctioned canal site is 610.40 m. but according to researcher it should be at 620m. from the surface though it will be proceed, some problems will also be persisting. They are as follows:
> Total 558ha. area is required for the canal. Due to which 390ha. fertile and 168 ha. forest area will influence.
188 > The land which is acquired by the government will never be returned to the original owners. There are 175 nalas, this canal will prepare below these nalas due to this canal, maintenance of these nalas become impossible. > Canal maintenance would be impossible due to huge depth. > The basic goals of the suitable canal site would not fiilfiU due to some tribal settlement eliminates by acquisition. > Land owners will obstruct the acquisition of fertile lands. > The forest land acquisition will take long time. 5.10.2 Suitable Canal Site No. 2
Actual sanctioned depth of releaser is 630 m to be drawn row to bottom of hill.
The proposal is fully not technical even if considered, but cost of construction of canals is growing high and more expensive. Akole canal cost is equal to full project cost and some problems will be taken place due to this canal site. They are as follows:
• 750ha. Fertile and 679ha. of forest i.e. total 1429ha. area should newly acquire.
• Land acquired by government will not be return to original owners.
• Maintenance of 230 infrastructures is impossible.
• Maintenance of canals is impossible due to huge depth.
• Canal way is on sloppy area of hills that causes to big fraught of soils but will not endure in high rainfall.
• It effects on power generation which will cause to higher compensation to pay from the government.
• Some tribes home eliminates by acquisition of land, hence there rehabilitation have to accomplish is completed.
• Land owners will obstruct the acquisition of fertile lands.
• The forest land acquisition will take long time.
189 • Bhandardara power house no. 1 and 2 will produce less power which cause to bare big loss and Rs. 637 Crores will have to pay to concerned company as compensation.
• Nilwande dam power generation project will stop to work.
S.llThe Analytic Hierarchy Process (AHP)
The Analytic Hierarchy Process (AHP) is a general theory of measurement and one of the methods of Multi Criterion Decision Making Analysis (MCDMA). This technique used to select most appropriate altemative from multiple criterions. It derived ratio scales from distinct and continuous matching comparisons to get reliable resuhs in the favors of objectives of the study. Pairwise comparison and weighted scale of Saaty's built enough capabilities to portrait most suitable results of the study.
In this study AHP is use to developed proposed canal site suitability. Land suitability for proposed canal site have been generated using basic five criterions (Table 5.45) i.e. LULC, elevation, slope, soil depth, road proximity, etc. Among this criterion each criterion has its own unique identity. This identity makes them different than each other. Though, it's needfiil to assign scores for all criterions as per their importance. Scores assigned using pair-wise comparison matrix (table 5.45) on the basis of Saaty's nine points weight scale (table 3.2). Creation of a pairwise comparison matrix, above mentioned five criterion have been used to create a ratio matrix which taken as input and relative weights are produced as an output. Criterion weights in percentages have estimated for Weighted Overlay Analysis (WOA).
The AHP is a general theory of measurement. It is used to derive ratio scales from both disfinct and continuous matching comparisons.
The given table 5.48 shows the weighted overlay based on AHP. Table 5.48 raster maps are overlaid. These are LULC, Elevation, slope, soil depth and road proximity maps.
Weightages are given from lowest to highest intensity of importance. LULC raster shows that 55.95% influence for those eight classes are analyzed according to those classes. Intensity of importance which is given from 1 to 9 (lowest to highest).
190 Barren land and open scrub land shows highest and moderately high intensity of importance respectively. Other classes show the lowest intensity of importance.
Elevation raster shows 16.15% influence. Two classes are considered for this analysis from which below 630 m. area has highest intensity of importance and above 630 m. area shows the lowest intensity of importance.
Slope maps influence is 14.46% and six classes are taken for this among which gentle and moderate slopes are shows the highest intensity of importance and other shows the lowest importance.
Soil depth raster influences 8.2%). Six classes are studied with that shallow soil class which shows the highest and remaining classes shows the lowest intensity of importance.
Road proximity raster shows the less influence, which is 5.42%). Seven classes are taken into the consideration among them 151-200 and 201-250 classes shows the highest and other classes shows the lowest intensity of importance.
Weighted overlay based on AHP shows the suitable canal site in highest intensity of importance areas, where as LULC influence is more about 56% and road proximity layer shows the less about 5.42%). barren land and open scrub land (LULC), < 630m. (elevation), gentle and moderate slope (Slope), shallow soil (soil depth) and 151-200 and 201-250 (road proximity). These all classes show the highest intensity of importance and remaining all classes shows the lowest intensity of importance.
191 Table 5.45 Pairwise Comparison Matrix Based on AHP
88 ^ e a a. g W) § 1? 1 g s •o-n aw« W I- la W ^ •r « ti a ^ u B P^ Pi >> ua 3 ij 2 ^ M = LULC 1 7 4 8 5 5.6854 0.9206 0.5595
Elevation 0.1429 1 3 1 3 -0.0410 0.2657 0.1615 (m.)
Slope Class 0.25 0.3333 1 4 3 -0.0410 0.2378 0.1446 (degree)
Soil Depth 0.125 1 0.25 1 2 -0.3017 0.1320 0.0802
Road Proximity 0.2 0.3333 0.3333 0.5 1 -0.3017 0.0892 0.0542 (m.)
Source: OLI and TRS Landsat 8 Satellite Image(18 Jan-2015).
Table 5.46 Proposed Canal Statistics
Sr. no. Canal Lengtii (in Icm.)
1 High level left canal 19.37
2 High level right canal 18.31
Table 5.46 shows proposed canal statistics, which has high level left canal (19.37 km) and high level right canal (18.31 km).
192 Table 5.47 Area under Different Suitability Categories
Sr.no. Suitability Categories Area (in ha) Area (inyo)
1 Lowest suitability 15939.70 27
2 Very low suitability 4539.24 8
3 Low suitability 4112.82 7
4 Moderately low suitability 13652.90 23
5 Moderate suitability 2184.12 4
6 Moderate high suitability 11049.20 19
7 High suitability 3520.62 6
8 Very high suitability 950.44 2
9 Highest suitability 2242.98 4
58192 100
Source: OLI and TRS Landsat 8 Satellite Image (18 Jan-2015).
Table 5.47 shows the area under different suitability categories for which nine suitability categories are analyzed. Among the total area, 12% area shows the highest suitability, 46% area shows the moderate suitability and 42% area shows the lowest suitability for the development of the canal.
193 Table 5.48 Weighted Overlay Based on AHP
Sr.no. Raster Influence Field Intensity of Importance 1 Landuse - 55.95% Class Landcover Agriculture 1 (Lowest) Barren land 9 (Highest) Dense forest 1 (Lowest) Open scrub 6 (Moderate high) Rocky / Open space 1 (Lowest) Settlement 1 (Lowest) Sparse vegetation 1 (Lowest) Water bodies 1 (Lowest)
2 Elevation (m.) 16.15% Class
Below 630 9 (Highest) 631 to 1646 1 (Lowest)
3 Slope class 14.46% Class (degree) Gentle 9 (Highest) Moderate 9 ( Highest) Stiff 1 (Lowest) Steep 1 (Lowest) Very Steep 1 (Lowest) Extra Steep 1 (Lowest)
4 Soil depth 8.02% Class High Soil depth 1 (Lowest) Shallow 9 (Highest) Marginal 1 (Lowest) Thin 1 (Lowest)
194 Moderate 1 (Lowest) Water bodies 1 (Lowest)
5 Road proximity 5.42% Class (m.)
0-50 1 (Lowest) 51-100 1 (Lowest) 101-150 1 (Lowest) 151-200 9 (Highest) 201-250 8 (Very high) 251-300 1 (Lowest) >300 1 (Lowest)
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202 Table 5.49 Village wise Saved Land by Acquiring Canal
.Q a u O OS a Agastinagar Right -0.71 -0.66 0.00 0.00 0.00 1.36 0.00 -0.07 (N.V.)
Akole Right 7.83 4.54 0.00 0.00 1.54 3.24 0.00 17.15
Aurangpur Right 4.41 1.98 0.00 0.00 0.00 0.88 0.00 7.27
Bahirwadi Left 3.88 0.47 0.00 0.00 0.64 0.49 0.00 5.49
Dhokri Left 4.61 1.05 0.00 0.00 0.00 1.62 0.00 7.27
Dhumalwadi Right 2.68 -1.24 -0.36 0.00 6.02 -0.32 0.00 6.77
Gardani Left 6.34 0.58 0.00 0.00 0.00 0.95 0.00 7.87
Indori Right 6.45 2.79 0.00 0.00 0.00 1.03 0.00 10.27
Kalas Kh. Right 11.02 11.47 0.00 0.00 0.00 5.45 0.00 27.94
Khanapur Left 1.32 6.20 0.00 0.00 0.00 1.28 0.00 8.80
Kumbhephal Left -0.09 6.06 lAA 6.75 0.00 -0.02 0.00 14.85
Manoharpur Right 0.93 6.80 -0.11 -0.25 0.00 0.68 0.00 8.06
Mehenduri Left 1.22 8.84 0.00 0.00 0.00 1.37 0.00 11.43
Mhaladevi Left 4.22 12.09 0.00 -0.43 -0.58 2.17 0.00 17.47
Right 4.49 -4.29 0.04 1.08 1.67 0.94 0.00 3.93
Navalewadi Right 5.57 0.91 0.00 0.00 1.37 4.30 -0.13 12.15
203 Nilwande Left 0.00 0.69 0.00 0.40 0.00 0.00 0.62 1.58
Nimbral Left 4.84 6.96 0.00 0.00 0.00 2.68 0.00 14.48
Parakhatpur Right 3.90 0.18 0.00 0.00 0.05 0.83 0.00 4.95
Rede Left 0.00 7.16 0.00 0.00 0.00 0.35 0.00 7.51
Rumbhodi Right 8.50 0.20 0.44 3.96 0.12 5.15 0.29 18.66
Sugaon Bk. Right 2.60 5.05 0.00 -0.08 0.00 1.47 0.00 9.04
Sugaon Kh. Left -0.37 2.99 0.00 0.00 0.00 0.53 0.00 3.14
Sultanpur Right -0.57 0.93 0.00 -0.49 0.00 1.81 0.00 1.68
Takali Left 5.78 1.03 0.00 0.00 0.18 0.16 0.00 7.15
Tambhol Left 4.89 15.93 1.23 2.98 0.00 3.10 0.00 28.14
Unchkadak Left 6.14 2.85 0.00 0.00 0.00 4.62 0.00 13.62 Kh.
Unchkhadak Right 1.86 1.38 0.00 0.00 0.00 0.19 0.00 3.43 Bk.
Grand Total 0 101.73 102.94 3.38 13.95 11.00 46.32 0.78 280.04
(source : O LI and TRS Laiidsa t 8 Sa tellite Im age (18. ran-20 15).
The researcher has divided canal land in eight categories which included agriculture, barren land, dense forest, open scrub, rocky space, settlement sparse vegetation, water bodies. After using research formula as shown above in the diagram, we can save 101.73ha. land in agriculture, 103ha. land barren land, 3.39ha. open scrub, 0.77 ha. water bodies.13.95ha. rocky space, llha. Settlement, 40.32ha. sparse vegetation. We are approximately saved 280.04ha. land altogether. We can also save money by using the underground canal in secure areas as it has proved helpftil in Nilwande - Tambhol route having height of 627.40m.from ASL.
204 It is not only convenient, but saves our land and economy. Underground routes, reduce evaporation. Seepage losses water loss and irrigation time management.
5.12 Resume
To strengthen above information I was carried out the field survey considering crop water requirement, irrigation facility, its types, methods, population analysis, water management, soil moisture (Jan and May 2015). It was helped me to prove the requirement of water to the study area. Second objective was to demarcate the suitable canal site excluding cultivated land, forest and settlements which is tested by Saaty's AHP technique. It is also as per our third objective to evaluate the benefits of suggested canal system site. From this overall analysis present research work is suggest the suitable canal site of Nilwande dam for maximum benefits to the agricultural development with sustainable development within the local region.
205