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Can Micro-Irrigation Technologies Resolve India’s Groundwater Crisis? Reflections from Dark-Regions in Gujarat Cover

Can Micro-Irrigation Technologies Resolve India’s Groundwater Crisis? Reflections from Dark-Regions in Gujarat

Open Access
|Oct 2019

Figures & Tables

ijc-13-2-888-g1.png
Figure 1

Map of the Study Villages.

Note: this figure not to scale and depict authentic boundaries.

Table 1

Descriptive Statistics of the Variables used in the Analysis.

Sl. No.Dependent VariablesDescriptionMean (SD)
1ΔDWLiΔDepth of Water Level (in feet)11.47 (17.07)
2ΔCPiΔColumn Pipe (in no.)2.09 (4.61)
3ΔPumpiΔPump set HP2.19 (4.16)
Independent Variables
Adoption of MI
4GIAMIiGIA under MI (%)0.76 (0.23)
5YearMIiNo. of years adopted MI4.41 (2.84)
Farm and Tubewell Characteristics
6GIAMIiGross Irrigated Area Before MI adoption6.03 (4.67)
7WRMiWater Recharge Measures0.60 (0.49)
8Ln(DWater)iLn(Depth of water level before MI adoption)4.48 (0.89)
9AgeTubewelliAge of the Tubewell18.09 (9.87)
Water Regulatory Measures
10MeteriMeter Connection (Yes/No)0.35 (0.48)
11(GIAMI*Meter)iGross Irrigated Area under MI*Meter Connection2.31 (4.54)
Tubewell Owners’ Characteristics
12EduOwneriYears of schooling of Tubewell Owner7.13 (4.87)
13AgeOwneriTubewell Owners’ Age51.47 (12.34)
14N430

[i] Note: SD - Standard Deviation.

Source: Authors’ Computation.

Table 2

Tubewell Owners’ Behaviour after adopting MI (Percentage of respondent).

Sl. No.Post Adoption BehaviourMean (SD)
1Increase Gross Irrigated Area (GIA)0.26 (0.44)
2Increase frequency of Irrigation0.80 (0.40)
3Increase Cropping Intensity0.32 (0.47)
4Shifting Water Intensive Crops0.37 (0.48)

[i] Note: SD - standard deviation.

Source: Authors’ table based on the field survey.

Table 3

Impact of MI adoption on Groundwater Extraction at common aquifer level.

Sl. No.Independent VariablesΔDWLiΔCPiΔPumpi
Coef. (Robust SE)Coef. (Robust SE)Coef. (Robust SE)
(i)(ii)(iii)(iv)(v)
Adoption of MI
1GIAMIi–5.08      –0.42      0.59      
(3.43)      (0.91)      (0.81)      
2YearMIi0.38      0.13**  0.05      
(0.24)      (0.06)      (0.05)      
Farm and Tubewell Characteristics
3GIABMIi0.37**  0.09*    0.03      
(0.18)      (0.05)      (0.04)      
4WRMi1.19      0.44      0.04      
(1.81)      (0.51)      (0.46)      
5Ln(DWater)i0.23      0.97**  0.27      
(1.68)      (0.41)      (0.30)      
6AgeTubewelli–0.03      0.01      0.01      
(0.07)      (0.02)      (0.01)      
Water Regulatory Measures
7Meteri–0.08      0.41      –0.44      
(1.96)      (0.45)      (0.43)      
8(GIAMI*Meter)i–0.49**  –0.15***–0.05      
(0.19)      (0.06)      (0.05)      
Tubewell Owners’ Characteristics
9EduOwneri–0.04      –0.00      –0.01      
(0.16)      (0.04)      (0.04)      
10AgeOwneri–0.02      0.01      0.02**  
(0.06)      (0.01)      (0.01)      
11Constant27.79***0.54      4.77***
(9.86)      (2.63)      (1.73)      
12R20.39      0.46      0.46      
13F (19, 410)17.56***9.67***14.92***
14Village EffectsYes      Yes      Yes      
15N430      430      430      
16ModelOLS      OLS      OLS      

[i] Source: Authors’ Computation.

Note: Robust standard errors are in the parentheses; *** p < 0.01, ** p < 0.05 and * p < 0.1 respectively.

DOI: https://doi.org/10.5334/ijc.888 | Journal eISSN: 1875-0281
Language: English
Submitted on: Apr 13, 2018
Accepted on: Feb 2, 2019
Published on: Oct 30, 2019
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Chandra Sekhar Bahinipati, P.K. Viswanathan, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.