Assessment of agricultural water management in Punjab, India, using bayesian methods

Tess Alethea Russo, Naresh Devineni, Upmanu Lall

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

The success of the Green Revolution in Punjab, India, is threatened by a significant decline in water resources. Punjab, a major agricultural supplier for the rest of India, supports irrigation with a canal system and groundwater, which is vastly overexploited. The detailed data required to estimate future impacts on water supplies or develop sustainable water management practices is not readily available for this region. Therefore, we use Bayesian methods to estimate hydrologic properties and irrigation requirements for an under-constrained mass balance model. Using the known values of precipitation, total canal water delivery, crop yield, and water table elevation, we present a method using a Markov chain Monte Carlo (MCMC) algorithm to solve for a distribution of values for each unknown parameter in a conceptual mass balance model. Model results are used to test three water management strategies, which show that replacement of rice with pulses may be sufficient to stop water table decline. This computational method can be applied in data-scarce regions across the world, where integrated water resource management is required to resolve competition between food security and available resources.

Original languageEnglish (US)
Title of host publicationSustainability of Integrated Water Resources Management
Subtitle of host publicationWater Governance, Climate and Ecohydrology
PublisherSpringer International Publishing
Pages147-162
Number of pages16
ISBN (Electronic)9783319121949
ISBN (Print)9783319121932
DOIs
StatePublished - Sep 4 2015

Fingerprint

water management
canal
water table
mass balance
irrigation
green revolution
Markov chain
food security
crop yield
management practice
rice
replacement
water supply
water resource
groundwater
resource
method
water
test
distribution

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)
  • Environmental Science(all)

Cite this

Russo, T. A., Devineni, N., & Lall, U. (2015). Assessment of agricultural water management in Punjab, India, using bayesian methods. In Sustainability of Integrated Water Resources Management: Water Governance, Climate and Ecohydrology (pp. 147-162). Springer International Publishing. https://doi.org/10.1007/978-3-319-12194-9_9
Russo, Tess Alethea ; Devineni, Naresh ; Lall, Upmanu. / Assessment of agricultural water management in Punjab, India, using bayesian methods. Sustainability of Integrated Water Resources Management: Water Governance, Climate and Ecohydrology. Springer International Publishing, 2015. pp. 147-162
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Russo, TA, Devineni, N & Lall, U 2015, Assessment of agricultural water management in Punjab, India, using bayesian methods. in Sustainability of Integrated Water Resources Management: Water Governance, Climate and Ecohydrology. Springer International Publishing, pp. 147-162. https://doi.org/10.1007/978-3-319-12194-9_9

Assessment of agricultural water management in Punjab, India, using bayesian methods. / Russo, Tess Alethea; Devineni, Naresh; Lall, Upmanu.

Sustainability of Integrated Water Resources Management: Water Governance, Climate and Ecohydrology. Springer International Publishing, 2015. p. 147-162.

Research output: Chapter in Book/Report/Conference proceedingChapter

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Russo TA, Devineni N, Lall U. Assessment of agricultural water management in Punjab, India, using bayesian methods. In Sustainability of Integrated Water Resources Management: Water Governance, Climate and Ecohydrology. Springer International Publishing. 2015. p. 147-162 https://doi.org/10.1007/978-3-319-12194-9_9