Spatio-temporal variations in effects of participatory irrigation management (PIM) reform in India: A panel data analysis

• Published in: Agricultural water management Vol. 222; pp. 48 - 61
• Main Authors: Ghosh, Souvik, Kolady, Deepthi Elizabeth, Das, Usha, Gorain, Subrato, Srivastava, Shivendra Kumar, Mondal, Bitan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-08-2019
• Subjects: Agricultural scenario; India; Irrigation management transfer; Irrigation scenario; Agricultural scenario; Irrigation management transfer; India; Irrigation scenario
• ISSN: 0378-3774; 1873-2283
• DOI: 10.1016/j.agwat.2019.05.042

•Several states in India have been implementing the PIM reform; however, empirical evidence on its effect is lacking that is addressed in present study.•It is the first empirical study using panel data set of 20 years (10 years each before and after the PIM enactment) for irrigation and agriculture variables that examines the impact of PIM.•Feasible Generalized Least Squares regression models are worked out to understand the impact of PIM reform on food grain productivity.•Results from descriptive analysis suggest spatio-temporal variations in the impact of PIM on agriculture and irrigation scenario showing betterment in both during post-PIM decade.•The regression model revealed positive and significant effect of PIM on food grain productivity in three out of six states studied in India.
After a decade of implementation of participatory irrigation management (PIM) policy in India, the impact of PIM on agricultural and irrigation scenario is studied in six states (Andhra Pradesh, Karnataka, Tamil Nadu, Madhya Pradesh, Odisha, and Rajasthan) implementing the PIM reform. In case of each state, district level panel data of 10 years each before and after the PIM enactment is analyzed for the variables depicting agricultural and irrigation scenario. The decadal mean values calculated before and after implementation of PIM indicate that increased share of net irrigated area to net sown area (3–12%), increased productivity of major crops (11–20%), increased food grain productivity (8–39%) with decreased share of food grain crops area to gross sown area (1–3%), increased area under high yielding varieties in three states (13–54%), increased cropping intensity in five states (3–12%) and increased fertiliser consumption (21–80%) during post PIM period. Net irrigated area has shown an increase from 6 to 38 percent that is because of relatively more increase in groundwater irrigated area (16–63%) as compared to canal irrigated area after PIM (-16 to 31%). District wise agricultural development index (ADI) and irrigation development index (IDI) are derived showing betterment in both after PIM reform. Feasible Generalized Least Squares (FGLS) regression models are worked out that revealed variations in impact of PIM in the states of India. The PIM has made significant impact on food grain productivity as evident from the significant coefficient value for interaction term between year and PIM dummy in case of Karnataka, Odisha and Rajasthan. In case of other three states, the impact of PIM is not significantly visible.