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By: R.D. Doi Department of Geography University of Rajasthan JAIPUR-302 004

Land Degradation and Water Scarcity Challenge to Sustainability of Agrarian Society in Semi-Arid Environ of Rajasthan. By: R.D. Doi Department of Geography University of Rajasthan JAIPUR-302 004. INTRODUCTION

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By: R.D. Doi Department of Geography University of Rajasthan JAIPUR-302 004

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  1. Land Degradation and Water Scarcity Challenge to Sustainability of Agrarian Society in Semi-Arid Environ of Rajasthan By: R.D. Doi Department of Geography University of Rajasthan JAIPUR-302 004

  2. INTRODUCTION • The basic principle for sustainable land use is that it must provide sufficient food, fodder and fuel for its own directly dependent population and this supply must continue for generations to come. • Micro level land degradation assessment in respect to ravine land including water resource and other basic requirements provide insights based on objective and primary data. • The term water scarcity describes a situation where users are in competition for access to water. • Agrarian societies are increasingly becoming vulnerable due to land degradation an depletion of water resource. • Now-a-days sustainability is the watchword for any of the land development and rational land use planning. • Primary data provide insights of sustainability such as land holding size and operations, cooking fuel supply, drinking water supply, water potential and water table status, watershed wise crop yield status and reasons for low crop yields, occupational status, animal wealth, expenditure pattern, per capita expenditure and deficit as well as soil-water conservation measures. • Test of a hypothesis is the proof of a hypothesis.

  3. OBJECTIVES • To assess gap between the annual expenditure in different heads and the market value of crops produced at household level in the study area. • To comprehend reasons for low crop yield at micro level • To judge suitability of RS data in assessment of land degradation at village level. • To collect primary data through structured schedule pertaining to water resource scarcity and its impact on agricultural production • To investigate ground realities about the soil-water conservation efforts as needed at micro level and peoples outlook and their awareness on such issues. • To establish relationship between land degradation and population density

  4. Table 1 RS Data Products Used

  5. HYPOTHESES • The existing agricultural land use is not capable to support the population of the villages affected by the ravine hazard in the study area for a long period. • Gullied and degraded lands are likely to be further degraded and are ultimately converted into ravine land under the existing practices/measures of soil-water conservation in the study area.

  6. SATELLITE DATA (IRS-1D LISS-III) RAW DIGITAL IMAGE (KHARIF CROP SEASON OCTOBER 2001) LOADING IMAGE + SCANNING BASE MAP SATELLITE DATA (IRS-1D LISS-III) RAW DIGITAL IMAGE (RABI CROP SEASON JANUARY 2002) FLOW DIAGRAM OF METHODOLOGY RECTIFIED/GEOCODED BASE MPA USING PCI GCP WORKS RECTIFIED RABI SEASON IMAGE RECTIFIED KHARIF SEASON IMAGE SUPERVISED IMAGE CLASSIFICATION USING PCI IMAGE WORK MODEL FIELD CHECKS STAGE-1 BITMAP GENERATION BITMAP GENERATION “MAP” CLASSIFIED KHARIF MAP CLASSIFIED RABI MAP “MAP” CONTD...

  7. CHANNEL=2 VALUE CODE = ? CHANNEL=1 VALUE CODE = ? COMPLEX LOGIC (TEXT FILE) OUTPUT CHANNEL=3 (NEW VALUE) AGGREGATE LAND USE/ LAND COVER CLASSIFICATION GROUND TRUTH STAGE-2 FOR DOUBTFUL CLASS (SELECTED TRAINING SITES) FINAL AGGREGATE LAND USE / LAND COVER CLASSES (2001-2002) MASK 49 SUB WATERSHEDS USING GEOMATICA CREATION OF BITMAP CLASSES CROSS CONTD...

  8. AREA STATISTICS FOR 49 SUB WATERSHEDS VECTORIZATION OF RANINOUS CLASS USING ArcGIS VILLAGE BOUNDARY CROSS VILLAGE LEVEL RAVINOUS CLASS RE-GROUPING OF VILLAGE USING Z-SCORE VALUE RAVINOUS INTENSITY IN EACH VILLAGE Fig 2 ***

  9. Fig 5 a & b

  10. S. no. % ravinous land to the total village geographical area Class description No. of villages % of villages to the total civic units Area covered (Km2 ) 1. 0 unaffected 68 4.19 44.12 2 <1 very slight/negligible 114 7.02 73.92 3 1-18 slight to moderately affected 797 49.07 516.73 4 18-36 moderate to highly affected 394 24.27 255.57 5 36-54 very highly affected 187 11.51 121.20 6 54-72 severely affected 53 3.26 34.33 7 >72 very severely affected 11 0.68 7.16 Total 1624 100.00 1053.03 Table 2 Ravinous land intensity at village level in The Morel river basin (2001-2002)

  11. b - Middle c - Lower Photo plates a, b, c : Ravine Depth Measurements in Morel river basin a - Upper

  12. Ravine Intensity No. Of Villages Landless (0 hact) Small (Up to 4 hact) Medium (4-10 hact) Large (10-15 hact) Big (>15 hact) Slight to Moderately Affected 19 9.06 65.26 18.57 6.69 0.40 Moderate to Highly Affected 10 11.59 75.37 12.17 - 0.87 Very Highly Affected 6 8.52 66.43 22.96 - 2.08 Severely Affected 5 10.54 69.94 16.88 2.68 - Total 40 10.00 69.25 17.64 2.34 0.73 Table 3: Ravine land intensity and farmers’ categories in the ravine-affected villages during 2003-04 Hact = hectare Source: Computed and complied by the author

  13. Ravine Intensity No. of Villages Animal Dung Kero- sene Local Fuel- Wood Biogas LPG Others Slight to Moderately Affected 19 4.40 1.05 94.18 - - 0.35 Moderate to Highly Affected 10 2.0 0.2 96.45 - 1.35 - Very Highly Affected 6 2.08 - 95.83 - 2.08 - Severely Affected 5 6.4 2.14 90.94 - - - Total 4.0 3.72 0.90 94.40 - 0.90 0.08 Table 4: Ravine Land Intensity and Average Number of Household Depending on Fuel Source Supplies during 2003-04 in the Morel Sub-catchment Source: Computed and complied by the author

  14. Ravine Intensity No. Of Villages Self Well Village Well Tap Water Self Tube well Hand Pump Others Slight to Moderately Affected 19 42.71 1.95 3.25 3.90 43.25 4.1 Moderate to Highly Affected 10 21.82 0.67 - 7.89 64.57 4.2 Very Highly Affected 6 34.58 6.87 9.93 7.23 55.5 - Severely Affected 5 24.94 - - 0.8 75.58 1.34 Total 4.0 31.00 2.37 3.29 4.95 59.72 2.41 Table 5: Ravine Land Intensity and Average Number of Households Depending on Drinking Water Supply Sources during 2003-04 in the Morel Sub-catchment Source: Computed and complied by the author

  15. S. No. Ravine Intensity No. of Villages Own Wells Panchayat Wells Pre- monsoon Post- monsoon Average Pre- monsoon Post- monsoon Average 1 Slight to Moderately Affected 19 29.01 23.57 26.29 36.96 25.55 31.25 2 Moderate to Highly Affected 10 22.16 20.08 21.12 23.74 20.71 22.22 3 Very Highly Affected 6 25.22 22.82 24.02 30.02 27.82 28.92 4 Severely Affected 5 28.92 25.80 27.36 39.53 36.14 37.83 Total 40 26.33 23.07 24.70 32.56 27.55 30.05 Table 6: Ravine Intensity and Water Table (Metres) during 2003-04 in the Morel Sub-catchment Source: Compiled by the author based on householdss

  16. Watershed Code Yield Status Reasons for Poor Yield 0 1 2 3 0 1 2 2D2A1 10.2 70.4 19.4 – 3.14 16.13 42.90 2D2A2 10.7 83.5 5.8 – 5.24 18.00 68.90 2D2A3 13.0 80.0 7.0 – 14.2 6.48 76.92 2D2A4 17.0 80.2 2.8 – 2.55 31.40 57.00 2D2A5 23.7 54.6 20.6 1.0 12.4 11.30 68.80 Total 14.73 73.75 11.12 0.2 7.5 16.70 63.00 Table 7: Watershed-wise Average Number of Respondents (%) Reporting Yield Status and Reasons for Poor Yield during 2003-04 in the Morel River Basin

  17. Watershed Code Reasons for Poor Yield 3 4 5 6 7 8 2D2A1 6.40 2.20 25.27 2.60 1.35 – 2D2A2 1.43 – 1.43 – 0.57 2.57 2D2A3 0.84 – – – – 1.56 2D2A4 6.56 1.44 – – – 1.08 2D2A5 5.50 2.00 – – – – Total 4.15 1.20 5.40 0.55 0.40 1.10 Source: Computed and complied by the author Yield Status: 0. No Response 1. Poor 2. Normal 3. High Reasons for Poor Yield: 0. No response 1. No irrigation means 2. Water scarcity 3. Poor soil 4. Mite problem 5. Badland (ravinous/ gullied) 6. Poor water quality 7. Damage due to cold wave 8. Infected

  18. Table 8: Per Capita Requirement of Expenditure in Different Items and Per Capita Price of All Crops Produced in Sample Villages in the Morel Sub-catchment (2003-04) S.No. Village Name Family Size Requirement of (Rs.) per Capita Expenditure Market Value (Rs.) of per Capita Produced Crops % Deficit/Surplus 1 Lauhara + Kelagaon 8.52 2425 856 -64.70 2 Edalpur 7.71 3861 2916 -24.47 3 Manda Meenapura 11.00 7746 6171 -20.33 4 Ekat 5.68 2543 1040 -59.10 5 Garhi Ka Gaon 10.20 2180 295 -86.47 6 Hadoti 6.53 4423 3824 -13.54 7 Malikpur 9.20 2339 2169 -7.27 8 Amarwa 9.26 3167 1111 -64.92 9 Kuagaon 8.00 4356 2808 -35.53 10 Kakrala 11.00 2760 4464 +61.74 11 Naneta Khera 16.00 6083 3464 -43.05 12 Gujar Koleta 11.90 4716 2265 -51.97 13 Salempur 6.36 4273 3490 -18.32

  19. 14 Kunkata Khurd 7.00 4463 5355 +19.99 15 Thikariya 8.96 5256 788 -85.00 16 Delari 11.00 3977 5865 +47.47 17 Bidarkha 8.07 5685 3212 -43.50 18 Ramnagar Rewari 9.67 2715 1428 -47.40 19 Dholawas 11.00 2774 2151 -22.46 20 Torda 12.25 6748 2991 -55.67 21 Lakhanpur 7.10 2562 437 -82.94 22 Gurha Meena 13.73 3175 1029 -67.60 23 Chandlai 7.45 5760 876 -84.80 24 Salagrampura 11.25 4932 381 -92.27 25 Dahar 5.71 2634 22 -99.16 26 Majheola 7.85 3100 978 -68.45 27 Tapri (Malarna Doongar) 10.83 4617 8755 +89.62 28 Shamoli 6.59 2092 975 -53.53 29 Lunera 14.50 2802 4225 +50.78 30 Kayamnagara Basri 10.83 1739 334 -80.80 31 Seesiyawas 12.00 3798 1528 -59.77 32 Chorwara 13.88 4297 2373 -44.77 33 Roopa Ki Nangal 8.70 3037 281 -90.75 34 Malpura Doongar 6.00 7012 664 -90.53 35 Mukandpura 11.40 12654 4116 -67.47 36 Bisori 8.20 5767 4409 -23.55 37 Kolyana 6.64 4095 472 -88.47 38 Chak Chainpura 9.80 7805 4727 -39.43 39 Sau 11.53 3658 2732 -25.31 40 Khori 8.80 2849 75 -97.37 x = 9.55 x = 4272 x = 2400 x Deficit = -43.82

  20. Table 9: Number of Respondents Reporting Existence of Soil-Water Conservation Measures in the Sample Villages of the Morel Sub-catchment (2003-04) Ravine Intensity No. Of Total Respondents LSD SSD AC MW Yes No Yes No Yes No Yes No Slight to Moderately Affected 192 0 192 17 175 90 102 0 192 Moderate to Highly Affected 162 0 162 0 162 116 46 0 162 Very Severely Affected 58 0 58 0 58 25 33 0 58 Severely Affected 92 0 92 0 92 35 57 25 67 Chi-Square 28.59 Chi-Square 35.92 Chi-Square 135.29

  21. BT CB CT GP GS PD Yes No Yes No Yes No Yes No Yes No Yes No 0 192 0 192 15 177 0 192 0 192 0 192 0 162 0 162 5 157 0 162 0 162 0 162 17 41 0 58 0 58 0 58 0 58 0 58 0 92 0 92 0 92 0 92 0 92 0 92 Chi-Square 13..97

  22. AF SF CVH WC RG AO Yes No Yes No Yes No Yes No Yes No Yes No 0 192 0 192 0 192 0 192 0 192 0 192 0 162 0 162 0 162 0 162 0 162 0 162 0 58 0 58 0 58 0 58 0 58 0 58 0 92 25 67 0 67 0 67 0 67 0 67 Chi-Square 117.80 Source: Computed and complied by the author

  23. Description: LSD Loose Stone Check Dam BT Bench Terracing SSD Silt Detension Dam CB Contour Bunding AC Anicut Construction CT Contour Trenching MW Masonary Work GP Gully Ploughing GS Gabion Structure CVH Contour Vegetative Hedge PD Pasture Development WC Wild Cropping AF Agro Forestry RG Ration Grazing SFSocial ForestryAOAny Other

  24. CONCLUSION • Ravine-affected villages are having main dependence on agriculture (77.31%) and inhabited predominated by the ST followed by the OBC categories. • People are aware of the problem of land degradation and some of the half-hearted measures taken by the Government agencies as well as some NGOs but gross lack of Users' Groups. • The maximum of 797 villages fall under the categiry of slight to moderat affect • More than 70% households belong to the category of small farmers (upto 16 bighas) followed by the medium category (16-40 bighas) sharing 13.92%. • There is not even a single farmer belonging to the big category (>15 hectares or 60 bighas). The average size of owned land holding size is 2.23 hectares in the surveyed villages of the study area. Self-operated holdings are found predominately in the surveyed villages. • Heavy dependence of more than 96% households on local fuel wood for their cooking requirement is implying stress on the local vegetative cover. Nearly 55% households depend on hand pumps for drinking water in the surveyed villages.

  25. Working population constitutes about 47.54% of the total population of the 40 villages. The agricultural working population varies between 67.16% (watershed 2D2A1) and 83.21% (watershed 2A2A2) to the total working population. • Occupational multiplicity (9.8%) reveals that a single occupation is not sufficient to support families for their livelihood. • About 74% (of the total 504) households have reported poor yield status of crop produce. The maximum of 63% households had reported water scarcity as one of the reasons for poor crop yields. • Among the 10 heads of expenditure in the surveyed villages, the irrigation head of expenditure ranks first (Rupees 5064 per household). The first three ranking expenditures are heads irrigation; clothing and animal feed which together share 50% of the total annual expenditure per household in the surveyed villages of the Morel sub-catchment. • There is a significant high deficit in percent terms (-43.82), which is an indicative of gloomy future for most of the people living in rural segment solely depending on agriculture in ravine infested villages of the study area. Hence the occupational multiplicity is a must to fulfill the basic needs of household population. The validity of the above hypothesis has been strengthened by the findings that 9.8 percent of the total 504 household respondents are exhibiting occupational multiplicity in the study area.

  26. The r-value is (-0.15), which is significant at the 0.01 levels between ravine land intensity in terms of extent (% area to the total geographical area of respective civic unit) and density of population during the years 2001-02 and 2001 respectively. It also supports the hypothesis one that ‘’ the existing agricultural/crop land use is not capable to support the population of the villages affected by the ravine hazard in the project area for a long period.” • Data pertaining to 16 measures of soil-water conservation have been gathered from each of the household head (referred as respondent). The Chi-Square Test is only applicable in case of Anicut Construction (AC). At the degree of freedom 3, the calculated value of Chi -Square calculated value is 35.92, which is very significantly higher than the tabulated value of 7.81. It means that the hypothesis number two also holds good that " gullied and degraded lands are likely to be further deteriorated and are ultimately converted into ravine land if the existing practices/measures of soil-water management continues without introduction of site specific need based suitable measures". The hypothesis is further validated by the preponderance of negative responses pertaining to other measures of soil water conservation. The above analysis suggests that land degradation and water scarcity challenge to sustainability of agrarian society in semi-arid environ of Rajasthan. 

  27. ACKNOWLEDGEMENTS I am grateful to the UGC, New Delhi for providing funds to purchase RS data and avail consultancy. Remote Sensing Division of B.M. Birla Science and Technology Centre, Statue Circle, Jaipur deserves special appreciation for allowing me to avail DIP facilities and Geomatica V 9.0 software at reasonable charges and timely help..

  28. THANK YOU

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