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Multiple indices based agricultural drought assessment in Tripura, northeast India

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Abstract

Precise and timely information regarding the beginning of the drought, its extent, intensity, and severity is a basic necessity to cope and mitigate climate-induced natural hazards like drought. Agriculture, one of the most sensitive sectors to drought as it has serious implications for the agriculture sector, which is heavily reliant on rainfall. Information can help reduce casualties and human suffering as well as a hamper on the economy and the environment. In this present study, RS and GIS methods were employed to assess the agricultural drought in Tripura, NE India. The standardized precipitation index (SPI) was used to identify meteorological drought. To analyze and describe the soil moisture conditions and agricultural drought, intense drought years, were examined among the drought years. The satellite image–based indices were created to estimate soil moisture levels and the severity of agricultural drought. To evaluate soil moisture conditions, the temperature-vegetation dryness index (TVDI) was employed. NDVI (normalized difference vegetation index), temperature condition index (TCI), vegetation condition index (VCI), and vegetation health index (VHI) were the indicators used to determine agricultural drought. These indicators were generated using moderate-resolution imaging spectroradiometer (MODIS) data from the chosen years 2001–2013. The meteorological drought assessment according to SPI at 6 months time frame concluded with an average of 10 drought events throughout the study period. The years 2005, 2006, 2007, and 2012 were most severe among the drought years observed. Observations for agricultural drought as a result of the progress of the above meteorological drought were in harmony with the indicators depicting the geographical variation and intensity of agricultural droughts. Drought’s influence on agriculture has been considerably increased despite the development of irrigation in the region. Hence, the uplift of irrigation potential in the region is the best viable option to mitigate the increasing drought hazard on agriculture.

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References

  • AghaKouchak A, Farahmand A, Melton FS, Teixeira J, Anderson MC, Wardlow BD, Hain CR (2015) Remote sensing of drought: progress, challenges, and opportunities. Rev Geophys 53(2):452–480

    Article  Google Scholar 

  • Bento VA, Trigo IF, Gouveia CM, DaCamara CC (2018) Contribution of land surface temperature (TCI) to vegetation health index: a comparative study using clear sky and all-weather climate data records. Remote Sens 10(9):1324

    Article  Google Scholar 

  • Choi M, Jacobs JM, Anderson MC, Bosch DD (2013) Evaluation of drought indices via remotely sensed data with hydrological variables. J Hydrol 476:265–273

    Article  Google Scholar 

  • Curtis S, Adler R, Huffman G, Nelkin E, Bolvin D (2001) Evolution of tropical and extratropical precipitation anomalies during the 1997–1999 ENSO cycle. Int J Clim 21:961–971

    Article  Google Scholar 

  • Deng Y, Wang S, Bai X, Tian Y, Wu L (2018) Relationship among land surface temperature and LUCC, NDVI in typical karst area. Sci Rep 8:1–12

    Google Scholar 

  • Dinpashoh Y, Shafaei S (2018) Analysis of drought characteristics of Tabriz (1951–2015). Water Soil Sci 28(3):117–130

    Google Scholar 

  • Drori R, Dan H, Sprintsin M, Sheffer E (2020) Precipitation-sensitive dynamic threshold: a new and simple method to detect and monitor forest and woody vegetation cover in sub-humid to arid areas. Remote Sens 12:1231

    Article  Google Scholar 

  • Dutta D, Kundu A, Patel N, Saha S, Siddiqui A (2015) Assessment of agricultural drought in Rajasthan (India) using remote sensing derived vegetation condition index (VCI) and standardized precipitation index (SPI). Egypt J Remote Sens Space Sci 18:53–63

    Google Scholar 

  • Ekhtiari S, Dinpashoh Y (2019) Application of effective drought index (EDI) in characterizing drought periods (case study: Tabriz, Bandar-e Anzali and Zahedan stations). Sustainable Water Resour Manage 5(4):1723–1729

    Article  Google Scholar 

  • Gitelson AA, Viña A, Arkebauer TJ, Rundquist DC, Keydan G, Leavitt B (2003) Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophys Res Lett 30:1–4

    Article  Google Scholar 

  • Gu Y, Brown JF, Verdin JP, Wardlow B (2007) A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophys Res Lett 34:L06407. https://doi.org/10.1029/2006GL029127

    Article  Google Scholar 

  • Hao Z, Singh VP, Xia Y (2018) Seasonal drought prediction: advances, challenges, and future prospects. Rev Geophys 56(1):108–141

    Article  Google Scholar 

  • Hollins S, Dodson J (2013) Drought. In: Bobrowsky P.T. (eds) Encyclopedia of natural hazards. Encyclopedia of Earth Sciences Series. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4399-4_98

  • IPCC (2021) Climate Change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, pp 7–71

  • Ji L, Peters AJ (2003) Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sens Environ 87:85–98

    Article  Google Scholar 

  • Khajeh SE, Negahban F, Dinpashoh Y (2019) Comparing univariate and multivariate indices in drought monitoring. J Water Soil Sci 23(2):433–446

  • KIRAN, Knowledge Innovation Repository of Agriculture in the Northeast. Web. http://www.kiran.nic.in/statistics.html Assessed on 17th August 2021.

  • Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15(11):91–100

    Article  Google Scholar 

  • Kogan FN (1997) Global drought watch from space. Bull Am Meteorol Soc 78(4):621–636

    Article  Google Scholar 

  • Kogan FN (2002) World droughts in the new millennium from AVHRR-based vegetation health indices principles of a new algorithm. EOS TRANSACTIONS 83(48):3–7

    Article  Google Scholar 

  • Kumar K, Rajagopalan B, Can M (1999) On the weakening relationship between the Indian monsoon and ENSO. Science 284:2156–2159

    Article  Google Scholar 

  • Maybank J, Bonsal B, Jones K, Lawford R, O’Brien EG, Ripley EA, Wheaton E (1995) Drought as a natural disaster. Atmos Ocean 33(2):195–222

    Article  Google Scholar 

  • McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology. Pp. 79- 183, January 17–22, 1993. Boston, MA, USA

  • Mishra A, Liu SC (2014) Changes in precipitation pattern and risk of drought over India in the context of global warming. J Geophys Res Atmos 119:7833–7841. https://doi.org/10.1002/2014JD021471

    Article  Google Scholar 

  • Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391(1–2):202–216

    Article  Google Scholar 

  • Moulin S, Kergoat L, Viovy N, Dedieu G (1997) Global-scale assessment of vegetation phenology using NOAA/AVHRR satellite measurements. J Clim 10:1154–1170

    Article  Google Scholar 

  • Mushore TD, Dube T, Manjowe M, Gumindoga W, Chemura A, Rousta I, Odindi J, Mutanga O (2019) Remotely sensed retrieval of Local Climate Zones and their linkages to land surface temperature in Harare metropolitan city, Zimbabwe. Urban Clim 27:259–271

    Article  Google Scholar 

  • Parida BR, Oinam B (2015) Unprecedented drought in North East India compared to Western India. Curr Sci 10:2121–2126

    Article  Google Scholar 

  • Quesada-Montano B, Wetterhall F, Westerberg IK, Hidalgo HG, Halldin S (2018) Characterizing droughts in Central America with uncertain hydro-meteorological data. Theoret Appl Climatol 137:2125–2138

    Article  Google Scholar 

  • Rhee J, Im J, Carbone GJ (2010) Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sens Environ 114:2875–2887

    Article  Google Scholar 

  • Rojas O, Vrieling A, Rembold F (2011) Assessing drought probability for agricultural areas in Africa with coarse resolution remote sensing imagery. Remote Sens Environ 115:343–352

    Article  Google Scholar 

  • Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with the El Nino/Southern Oscillation. ˜ Monthly Weather Review 115:1606–1626

    Article  Google Scholar 

  • Ropelewski CF, Halpert MS (1989) Precipitation patterns associated with the high index phase of the Southern Oscillation. J Clim 2:268–284

    Article  Google Scholar 

  • Rouse J, Haas R, Schell J, Deering D (1974) Monitoring vegetation systems in the Great Plains with ERTS. NASA Spe Publ 351:309

    Google Scholar 

  • Running SW, Loveland TR, Pierce LL, Nemani RR, Hunt ER Jr (1995) A remote sensing based vegetation classification logic for global land cover analysis. Remote Sens Environ 51:39–48

    Article  Google Scholar 

  • Sandholt I, Rasmussen K, Andersen J (2002) A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sens Environ 79(2–3):213–224

    Article  Google Scholar 

  • Sheffield J, Wood EF (2012) Drought: past problems and future scenarios. Routledge, London

    Book  Google Scholar 

  • Sheffield J, Goteti G, Wen F, Wood EF (2004) A simulated soil moisture based drought analysis for the United States. J Geophys Res Atmos 27:109(D24)

  • Sparavigna AC, Marazzato R (2015) Recurrence plots of geolocated time series from satellite maps of NOAA STAR vegetation health index. Int J Sci 4(12):47–54

  • Sruthi S, Aslam MAM (2015) Agricultural drought analysis using the NDVI and land surface temperature data; a case study of Raichur District. Aquatic Procedia 4:1258–1264

    Article  Google Scholar 

  • Tamaddun KA, Kalra A, Bernardez M, Ahmad S (2017) Multi-scale correlation between the western U.S. snow water equivalent and ENSO/PDO using wavelet analyses. Water Resour Manag 31:2745–2759

    Article  Google Scholar 

  • Tate EL, Gustard A (2000) Drought definition: a hydrological perspective. Drought and drought mitigation in Europe. Springer, Dordrecht, pp 23–48

    Chapter  Google Scholar 

  • Vyas SS, Bhattacharya BK, Nigam R, Guhathakurta P, Ghosh K, Chattopadhyay N, Gairola RM (2015) A combined deficit index for regional agricultural drought assessment over a semi-arid tract of India using geostationary meteorological satellite data. Int J Appl Earth Obs Geoinf 39:28–39

    Article  Google Scholar 

  • Wilhite DA (2000) Drought as a natural hazard: concepts and definitions. In Wilhite, D. A. (ed.), Drought: a global assessment. London: Routledge, Vol. 1, pp. 3–18

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Correspondence to Aribam Priya Mahanta Sharma.

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Responsible Editor: Zhihua Zhang

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Sharma, A.P.M., Jhajharia, D., Gupta, S. et al. Multiple indices based agricultural drought assessment in Tripura, northeast India. Arab J Geosci 15, 636 (2022). https://doi.org/10.1007/s12517-022-09855-0

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