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Drought monitoring using a Soil Wetness Deficit Index (SWDI) derived from MODIS satellite data

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  • Keshavarz, Mohammad Reza
  • Vazifedoust, Majid
  • Alizadeh, Amin

Abstract

Soil moisture is considered a key index of agricultural drought monitoring systems due to its importance for plant growth and biological interactions. In this research, a Soil Wetness Deficit Index (SWDI) was developed based on a Soil Wetness Index to evaluate soil moisture deviation as an indicator of agricultural drought. The Soil Wetness Index is derived using a triangle space concept between the land surface temperature (LST) and vegetation index (NDVI). To acquire the triangle space concept, 8-day-products of land surface reflectance and LST derived from MODIS satellite data over Isfahan were used. The data was collected in the period of 2000–01 (dry year) and 2004–05 (wet year) on an 8-day time step. The results indicated that the SWDI index has the capability of mapping the spatial distribution of areas affected by drought, as well as the drought intensity. The estimated cumulative number of dry days (with −4

Suggested Citation

  • Keshavarz, Mohammad Reza & Vazifedoust, Majid & Alizadeh, Amin, 2014. "Drought monitoring using a Soil Wetness Deficit Index (SWDI) derived from MODIS satellite data," Agricultural Water Management, Elsevier, vol. 132(C), pages 37-45.
    • Handle: RePEc:eee:agiwat:v:132:y:2014:i:c:p:37-45
    DOI: 10.1016/j.agwat.2013.10.004
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    References listed on IDEAS

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    1. Akbari, Mehdi & Toomanian, Norair & Droogers, Peter & Bastiaanssen, Wim & Gieske, Ambro, 2007. "Monitoring irrigation performance in Esfahan, Iran, using NOAA satellite imagery," Agricultural Water Management, Elsevier, vol. 88(1-3), pages 99-109, March.
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    1. Lingkui Meng & Ting Dong & Wen Zhang, 2016. "Drought monitoring using an Integrated Drought Condition Index (IDCI) derived from multi-sensor remote sensing data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(2), pages 1135-1152, January.
    2. Zhihui Yang & Jun Zhao & Jialiang Liu & Yuanyuan Wen & Yanqiang Wang, 2021. "Soil Moisture Retrieval Using Microwave Remote Sensing Data and a Deep Belief Network in the Naqu Region of the Tibetan Plateau," Sustainability, MDPI, vol. 13(22), pages 1-19, November.
    3. Omolola M. Adisa & Muthoni Masinde & Joel O. Botai & Christina M. Botai, 2020. "Bibliometric Analysis of Methods and Tools for Drought Monitoring and Prediction in Africa," Sustainability, MDPI, vol. 12(16), pages 1-22, August.
    4. Chen, Xinguo & Li, Yi & Yao, Ning & Liu, De Li & Javed, Tehseen & Liu, Chuncheng & Liu, Fenggui, 2020. "Impacts of multi-timescale SPEI and SMDI variations on winter wheat yields," Agricultural Systems, Elsevier, vol. 185(C).
    5. Yang, Huicai & Wang, Huixiao & Fu, Guobin & Yan, Haiming & Zhao, Panpan & Ma, Meihong, 2017. "A modified soil water deficit index (MSWDI) for agricultural drought monitoring: Case study of Songnen Plain, China," Agricultural Water Management, Elsevier, vol. 194(C), pages 125-138.
    6. Hong, Minki & Lee, Sang-Hyun & Lee, Seung-Jae & Choi, Jin-Yong, 2021. "Application of high-resolution meteorological data from NCAM-WRF to characterize agricultural drought in small-scale farmlands based on soil moisture deficit," Agricultural Water Management, Elsevier, vol. 243(C).
    7. Dejene W. Sintayehu & Asfaw Kebede Kassa & Negash Tessema & Bekele Girma & Sintayehu Alemayehu & Jemal Yousuf Hassen, 2023. "Drought Characterization and Potential of Nature-Based Solutions for Drought Risk Mitigation in Eastern Ethiopia," Sustainability, MDPI, vol. 15(15), pages 1-22, July.
    8. Abdollahzadeh, Gholamhossein & Sharifzadeh, Mohammad Sharif & Sklenička, Petr & Azadi, Hossein, 2023. "Adaptive capacity of farming systems to climate change in Iran: Application of composite index approach," Agricultural Systems, Elsevier, vol. 204(C).
    9. Małgorzata Biniak-Pieróg & Mieczysław Chalfen & Andrzej Żyromski & Andrzej Doroszewski & Tomasz Jóźwicki, 2020. "The Soil Moisture during Dry Spells Model and Its Verification," Resources, MDPI, vol. 9(7), pages 1-27, July.
    10. Lingkui Meng & Ting Dong & Wen Zhang, 2016. "Drought monitoring using an Integrated Drought Condition Index (IDCI) derived from multi-sensor remote sensing data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(2), pages 1135-1152, January.
    11. Xiao Liu & Ping Guo & Qian Tan & Fan Zhang & Yan Huang & Youzhi Wang, 2021. "Drought disaster risk management based on optimal allocation of water resources," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 285-308, August.
    12. Wei Shangguan & Ruqing Zhang & Lu Li & Shulei Zhang & Ye Zhang & Feini Huang & Jianduo Li & Wei Liu, 2022. "Assessment of Agricultural Drought Based on Reanalysis Soil Moisture in Southern China," Land, MDPI, vol. 11(4), pages 1-16, March.

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