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Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka

Author

Listed:
  • Niranga Alahacoon

    (Department of Physics, University of Colombo, Colombo 00300, Sri Lanka
    International Water Management Institute (IWMI), 127, Sunil Mawatha, Pelawatte, Colombo 10120, Sri Lanka)

  • Mahesh Edirisinghe

    (Department of Physics, University of Colombo, Colombo 00300, Sri Lanka)

  • Manjula Ranagalage

    (Department of Environmental Management, Faculty of Social Sciences and Humanities, Rajarata University of Sri Lanka, Mihintale 50300, Sri Lanka)

Abstract

For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and meteorological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is ≥30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and meteorological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.

Suggested Citation

  • Niranga Alahacoon & Mahesh Edirisinghe & Manjula Ranagalage, 2021. "Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka," Sustainability, MDPI, vol. 13(6), pages 1-28, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3427-:d:520544
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    Cited by:

    1. Joko Prihantono & Takashi Nakamura & Kazuo Nadaoka & Anindya Wirasatriya & Novi Susetyo Adi, 2022. "Rainfall Variability and Tidal Inundation Influences on Mangrove Greenness in Karimunjawa National Park, Indonesia," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    2. Soleman Imbiri & Raufdeen Rameezdeen & Nicholas Chileshe & Larissa Statsenko, 2021. "A Novel Taxonomy for Risks in Agribusiness Supply Chains: A Systematic Literature Review," Sustainability, MDPI, vol. 13(16), pages 1-24, August.
    3. Jeewanthi Sirisena & Denie Augustijn & Aftab Nazeer & Janaka Bamunawala, 2022. "Use of Remote-Sensing-Based Global Products for Agricultural Drought Assessment in the Narmada Basin, India," Sustainability, MDPI, vol. 14(20), pages 1-21, October.
    4. Sujith S. Ratnayake & Lalit Kumar & Punchi B. Dharmasena & Harsha K. Kadupitiya & Champika S. Kariyawasam & Danny Hunter, 2021. "Sustainability of Village Tank Cascade Systems of Sri Lanka: Exploring Cascade Anatomy and Socio-Ecological Nexus for Ecological Restoration Planning," Challenges, MDPI, vol. 12(2), pages 1-23, September.

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