Sustainable intensification opportunities for Alfisols and Vertisols landscape of the semi-arid tropics

Kh Anantha, Kaushal K. Garg, Venkataradha Akuraju, Gajanan Sawargaonkar, Naveen K. Purushothaman, Bhabani Sankar Das, Ramesh Singh and Ml Jat

Agricultural Water Management, 2023, vol. 284, issue C

Abstract: Land and water management interventions are key to achieving sustainable intensification in the drylands. This study explores opportunities for doing so in Vertisols and Alfisols using 34-year (1976–2009) long-term experimental data. Four cropping systems were evaluated in each soil types with two land form management interventions, i.e., raised beds and flat beds. Surface runoff generated and soil water content in each system were monitored along with crop yields. In Vertisols, maize-chickpea sequential cropping and sorghum+pigeon pea intercropping on raised beds representing an improved practice was followed for 34 years (1976–2009). Sole chickpea and sole sorghum were grown on flat beds as a traditional system during the same period. In Alfisols, groundnut/pigeon pea intercrop and sole sorghum were grown for 5 years (2002–2006) and sorghum/pigeon pea intercrop and sole castor were grown for 3 years (2007–2009) under raised bed and flat bed conditions, respectively. The use of improved practices in Vertisols produced 3–5 times higher yield compared to traditional practices with net returns estimated at US$ 800–1300/ha/year compared to US$ 90–350/ha/year under the traditional practice. Despite growing an additional crop, chickpea yield under the improved practice was close to the yield obtained from the traditional practice. In Alfisols, raised beds improved crop yields by 15–20% compared to the flat bed method, leading to an additional net return of US$ 80–100/ha/year. Sorghum/pigeon pea intercrop was found to be superior followed by sole castor, groundnut/pigeon pea intercrop and sole sorghum in Alfisols. Hydrological monitoring revealed opportunities to harvest surface runoff, especially in Alfisols, by building low-cost rainwater harvesting structures that can provide life-saving irrigation during dry spells. An interpretive machine learning (IML) approach was used to estimate four response variables (Sorghum equivalent yield; Net Income; Technical Water Productivity, and Economic Water Productivity) using five different predictor variables (i.e., cropping systems, land form, soil order, effective rainfall (Reff= rainfall-runoff), and water regimes (dry, wet, and normal). Results showed that cropping system is the highest mean feature importance for all the productivity parameters followed by effective rainfall. This paper also discusses soil water dynamics, production functions and technical and economic water productivity which could aid in resource optimization and in developing strategies for land, water and crop management interventions with the aim of bridging yield gaps in the semi-arid tropics.

Keywords: Surface runoff; Effective rainfall; Cropping systems; Net returns; Raised bed (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:284:y:2023:i:c:s037837742300197x

DOI: 10.1016/j.agwat.2023.108332

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