Comparative study of different exponential smoothing models in simulation of meteorological drought : A study on Purulia district, West Bengal, India
Article Main
Abstract
Drought is a burning issue in India and hence needs serious attention of researchers to develop rigorous plan and management. Areas that belong to various plateaus, e.g., Chottanagpur plateau, Deccan plateau, etc., are mostly affected by drought in India. In the past decade, Purulia District of West Bengal, which belongs to northeast part of Chottanagpur plateau, faced severe drought several times. But the assessment of drought in this area was far from a decesive proclamation till date. In this research, an attempt was made to compare the Holt-Winter additive and Holt-Winter multiplicative model in simulation (at 1 month lead time) of meteorological drought (using Standardized Precipitation Index (SPI) of Purulia District, West Bengal, India. The additive model showed better performance than the multiplicative model with minimized Root Mean Squared Error (RMSE) and higher correlation coefficient value (R2). The spatial assessment drought at pre-monsoon, monsoon and post-monsoon phase indicated that severe drought had occurred in post monsoon and premonsoon phase at the eastern portions of the study area.
Article Details
Article Details
Keywords
Additive Model, Multiplicative model, Standardized Precipitation Index (SPI)
References
Baidya, T. K. (2015). Archean metallogeny and crustal evolution in the East Indian Shield. Earth Sciences, 4(4), 1. https://doi.org/10.11648/j.earth.s.2015040401.11.
Basist, A., Bell, G. D. & Meentemeyer, V. (1994). Statistical relationships between topography and precipitation patterns. J. Climate, 7(9), 1305-1315. https://doi.org/10.1175/1520-0442(1994)007%3C1305:SRBTAP%3E2.0.CO;2.
Chatterjee, S., Khan, A., Akbari, H. & Wang, Y. (2016). Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901–2002), West Bengal, India. Atmos. Res., 182, 54–75. https://doi.org/10.1016/j.atmosres.2016.07.010.
Dey, A., Nandy, S., Mukherjee, A. & Modak, B. K. (2020). Sustainable utilization of medicinal plants and conservation strategies practiced by the aboriginals of Purulia district, India: a case study on therapeutics used against some tropical otorhinolaryngologic and ophthalmic disorders. Environment, Development and Sustainability, 1-38. https://doi.org/10.1007/s10668-020-00833-8.
Dhar, O. N., Rakhecha, P. R. & Mandal, B. N. (1981). Influence of tropical disturbances on monthly monsoon rainfall of India. Mon. Weath. Rev., 109(1), 188-190. https://doi.org/10.1175/1520-0493(1981)109%3C0188:IOTDOM%3E2.0.CO;2.
Dogan, S., Berktay, A. & Singh, V. P. (2012). Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey .J. Hydrol., 470-471, 255–268. https://doi.org/10.1016/j.jhydrol.2012.09.003.
Dolui, G., Das, N., Guchhait, S. & Roy, S. (2021). Multi-criteria Decision-Making Approach Using Remote Sensing and GIS for Assessment of Groundwater Resources. Geostatistics and Geospatial Technologies for Groundwater Resources in India, 59-79. https://doi.org/10.1007/978-3-030-62397-5_4
Douglas, E. M., Niyogi, D., Frolking, S., Yeluripati, J. B., Pielke Sr, R. A., Niyogi, N. & Mohanty, U. C. (2006). Changes in moisture and energy fluxes due to agricultural land use and irrigation in the Indian Monsoon Belt. Geophys. Res. Lett., 33(14). 1-5. https://doi.org/10.1029/2006GL026550
Drumond, A., Gimeno, L., Nieto, R., Trigo, R. M. & Vicente-Serrano, S. M. (2017). Drought episodes in the climatological sinks of the Mediterranean moisture source: The role of moisture transport. Global. Planet. Change., 151, 4-14. https://doi.org/10.1016/j.gloplacha.2016.12.004
Durdu, Ö. F. (2010). Application of linear stochastic models for drought forecasting in the Büyük Menderes river basin, western Turkey. Stoch. Env. Res. Risk. A., 24(8), 1145-1162. https://doi.org/10.1007/s00477-010-0366-3
Edwards, D. C. & McKee, T. B. (1997). Characteristics of twentieth century drought in the United States at multiple time scales. Department of Atmospheric Sciences, Colorado State University, Climatology Report, (97-2).
Elmunim, N. A., Abdullah, M., Hasbi, A. M. & Bahari, S. A. (2015). Comparison of Statistical Holt-Winter Models for Forecasting the Ionospheric delay using GPS Observations. Indian J. Radio Space. 28-34.
Granger, C.W.J. & Newbold, P. (1986) Forecasting Economic Time Series, 2nd edn (New York, Academic Press). https://doi.org/10.1016/C2013-0-10756-8.
Hagenlocher, M., Meza, I., Anderson, C., Min, A., Renaud, F. G., Walz, Y. & Sebesvari, Z. (2019). Drought vulnerability and risk assessments: state of the art, persistent gaps, and research agenda. Environ. Res. Lett.. https://doi.org/10.1088/1748-9326/ab225d.
Hazra, S., Roy, S. & Mitra, S. (2017). Enhancing Adaptive Capacity and Increasing Resilience of Small and Marginal Farmers of Purulia and Bankura Districts, West Bengal to Climate Change. DRCSC Report. 1-114.
Hyndman, R. J. & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts. 1-504.
Kamari, A., Khaksar-Manshad, A., Gharagheizi, F., Mohammadi, A. H. & Ashoori, S. (2013). Robust model for the determination of wax deposition in oil systems. Industrial & Engineering Chemistry Research, 52(44), 15664-15672. https://doi.org/10.1021/ie402462q.
Kripalani, R. H., Kulkarni, A., Sabade, S. S. & Khandekar, M. L. (2003). Indian monsoon variability in a global warming scenario. Nat. Hazard.., 29(2), 189-206. https://doi.org/10.1023/A:1023695326825.
Kumar, K. K. (1999). On the Weakening Relationship Between the Indian Monsoon and ENSO. Science, 284(5423), 2156–2159. https://doi.org/10.1126/science.284.5 423.2156.
Kundu, S. K. & Mondal, T. K. (2019). Analysis of long-term rainfall trends and change point in West Bengal, India. Theor. Appl. Climatol., 138(3), 1647-1666. https://doi.org/10.1007/s00704-019-02916-7.
McKee, T. B., Doesken, N. J. & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, No. 22, pp. 179-183). Boston, MA: American Meteorological Society.
Mukherjee, I. & Singh, U. K. (2018). Groundwater fluoride contamination, probable release, and containment mechanisms: a review on Indian context. Environ. Geochem. Hlth.. https://doi.org/10.1007/s10653-018-0096-x.
Nag, S. K. & Kundu, A. (2016). Delineation of groundwater potential zones in hard rock terrain in Kashipur block, Purulia district, West Bengal, using geospatial techniques. Int. J. Waste. Resour., 6(201), 1-13. https://doi.org/10.4172/2252-5211.1000201.
Nair, U. S., Lawton, R. O., Welch, R. M. & Pielke Sr, R. A. (2003). Impact of land use on Costa Rican tropical montane cloud forests: Sensitivity of cumulus cloud field characteristics to lowland deforestation. J. Geophys. Res. -Atmos., 108(D7).1-13. https://doi.org/10.1029/2001JD0 01 135.
Razali, S. N. A. M., Rusiman, M. S., Zawawi, N. I. & Arbin, N. (2018). Forecasting of water consumptions expenditure using Holt-Winter’s and ARIMA. In Journal of Physics: Conference Series (Vol. 995, No. 1, p. 012041). IOP Publishing. https://doi.org/10.1088/1742-6596/995/1/012041.
Rossi G. (2003). Requisites for a drought watch system. In: Rossi G, Cancelliere A, Pereira LS, Oweis T, Shatanawi M, Zairi A (eds) Tools for drought mitigation in Mediterranean regions. Springer, Dordrecht, 147–157. https://doi.org/10.1007/978-94-010-0129-8_9.
SAFE (2011). Community-ecosystem approach for adaptive watershed management in drought-prone tribal areas of West Bengal. www.resourceaward.org.
Singh, G.R., Jain, M.K. & Gupta, V (2019). Spatiotemporal assessment of drought hazard, vulnerability and risk in the Krishna River basin, India. Nat. Hazards. 99, 611–635. https://doi.org/10.1007/s11069-019-03762-6.
Sönmez, F. K., Koemuescue, A. U., Erkan, A. & Turgu, E. (2005). An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Nat. Hazards., 35(2), 243-264. https://doi.org/10.1007/s11069-004-5704-7.
Stagge, J. H., Kohn, I., Tallaksen, L. M. & Stahl, K. (2015). Modeling drought impact occurrence based on meteorological drought indices in Europe. J. Hydrol., 530, 37–50. https://doi.org/10.1016/j.jhydrol.2015.09.039.
Suryanarayana, T. M. V & Mistry, P. B. (2016). Principal component regression for crop yield estimation. Springer Singapore. https://doi.org/10.1007/978-981-10-0663-0.
Thom, H. C. S. (1958). A note on the gamma distribution, Monthly. Weather. Rev., 86, 117–122. https://doi.org/10.1 175/1520-0493(1958)086%3C0117:ANOTGD %3E2.0.CO;2.
Wichitarapongsakun, P., Sarin, C., Klomjek, P. & Chuenchooklin, S. (2016). Rainfall prediction and meteorological drought analysis in the Sakae Krang River basin of Thailand. Agriculture and Natural Resources, 50(6), 490–498. https://doi.org/10.1016/j.anres.2016.05.003.
Yves, T., Koutroulis, A., Samaniego, L., Vicente-Serrano, S. M., Volaire, F., Boone, A. & Polcher, J. (2020). Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth-Science Reviews, 103348. https://doi.org/10.1016/j.earscirev.20 20.1 03348.
Zarch, M. A. A., Sivakumar, B. & Sharma, A. (2015). Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI). J. Hydrol.., 526, 183-195. https://doi.org/10.1016/j.jhydrol.2014.09.071.
Basist, A., Bell, G. D. & Meentemeyer, V. (1994). Statistical relationships between topography and precipitation patterns. J. Climate, 7(9), 1305-1315. https://doi.org/10.1175/1520-0442(1994)007%3C1305:SRBTAP%3E2.0.CO;2.
Chatterjee, S., Khan, A., Akbari, H. & Wang, Y. (2016). Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901–2002), West Bengal, India. Atmos. Res., 182, 54–75. https://doi.org/10.1016/j.atmosres.2016.07.010.
Dey, A., Nandy, S., Mukherjee, A. & Modak, B. K. (2020). Sustainable utilization of medicinal plants and conservation strategies practiced by the aboriginals of Purulia district, India: a case study on therapeutics used against some tropical otorhinolaryngologic and ophthalmic disorders. Environment, Development and Sustainability, 1-38. https://doi.org/10.1007/s10668-020-00833-8.
Dhar, O. N., Rakhecha, P. R. & Mandal, B. N. (1981). Influence of tropical disturbances on monthly monsoon rainfall of India. Mon. Weath. Rev., 109(1), 188-190. https://doi.org/10.1175/1520-0493(1981)109%3C0188:IOTDOM%3E2.0.CO;2.
Dogan, S., Berktay, A. & Singh, V. P. (2012). Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey .J. Hydrol., 470-471, 255–268. https://doi.org/10.1016/j.jhydrol.2012.09.003.
Dolui, G., Das, N., Guchhait, S. & Roy, S. (2021). Multi-criteria Decision-Making Approach Using Remote Sensing and GIS for Assessment of Groundwater Resources. Geostatistics and Geospatial Technologies for Groundwater Resources in India, 59-79. https://doi.org/10.1007/978-3-030-62397-5_4
Douglas, E. M., Niyogi, D., Frolking, S., Yeluripati, J. B., Pielke Sr, R. A., Niyogi, N. & Mohanty, U. C. (2006). Changes in moisture and energy fluxes due to agricultural land use and irrigation in the Indian Monsoon Belt. Geophys. Res. Lett., 33(14). 1-5. https://doi.org/10.1029/2006GL026550
Drumond, A., Gimeno, L., Nieto, R., Trigo, R. M. & Vicente-Serrano, S. M. (2017). Drought episodes in the climatological sinks of the Mediterranean moisture source: The role of moisture transport. Global. Planet. Change., 151, 4-14. https://doi.org/10.1016/j.gloplacha.2016.12.004
Durdu, Ö. F. (2010). Application of linear stochastic models for drought forecasting in the Büyük Menderes river basin, western Turkey. Stoch. Env. Res. Risk. A., 24(8), 1145-1162. https://doi.org/10.1007/s00477-010-0366-3
Edwards, D. C. & McKee, T. B. (1997). Characteristics of twentieth century drought in the United States at multiple time scales. Department of Atmospheric Sciences, Colorado State University, Climatology Report, (97-2).
Elmunim, N. A., Abdullah, M., Hasbi, A. M. & Bahari, S. A. (2015). Comparison of Statistical Holt-Winter Models for Forecasting the Ionospheric delay using GPS Observations. Indian J. Radio Space. 28-34.
Granger, C.W.J. & Newbold, P. (1986) Forecasting Economic Time Series, 2nd edn (New York, Academic Press). https://doi.org/10.1016/C2013-0-10756-8.
Hagenlocher, M., Meza, I., Anderson, C., Min, A., Renaud, F. G., Walz, Y. & Sebesvari, Z. (2019). Drought vulnerability and risk assessments: state of the art, persistent gaps, and research agenda. Environ. Res. Lett.. https://doi.org/10.1088/1748-9326/ab225d.
Hazra, S., Roy, S. & Mitra, S. (2017). Enhancing Adaptive Capacity and Increasing Resilience of Small and Marginal Farmers of Purulia and Bankura Districts, West Bengal to Climate Change. DRCSC Report. 1-114.
Hyndman, R. J. & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts. 1-504.
Kamari, A., Khaksar-Manshad, A., Gharagheizi, F., Mohammadi, A. H. & Ashoori, S. (2013). Robust model for the determination of wax deposition in oil systems. Industrial & Engineering Chemistry Research, 52(44), 15664-15672. https://doi.org/10.1021/ie402462q.
Kripalani, R. H., Kulkarni, A., Sabade, S. S. & Khandekar, M. L. (2003). Indian monsoon variability in a global warming scenario. Nat. Hazard.., 29(2), 189-206. https://doi.org/10.1023/A:1023695326825.
Kumar, K. K. (1999). On the Weakening Relationship Between the Indian Monsoon and ENSO. Science, 284(5423), 2156–2159. https://doi.org/10.1126/science.284.5 423.2156.
Kundu, S. K. & Mondal, T. K. (2019). Analysis of long-term rainfall trends and change point in West Bengal, India. Theor. Appl. Climatol., 138(3), 1647-1666. https://doi.org/10.1007/s00704-019-02916-7.
McKee, T. B., Doesken, N. J. & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, No. 22, pp. 179-183). Boston, MA: American Meteorological Society.
Mukherjee, I. & Singh, U. K. (2018). Groundwater fluoride contamination, probable release, and containment mechanisms: a review on Indian context. Environ. Geochem. Hlth.. https://doi.org/10.1007/s10653-018-0096-x.
Nag, S. K. & Kundu, A. (2016). Delineation of groundwater potential zones in hard rock terrain in Kashipur block, Purulia district, West Bengal, using geospatial techniques. Int. J. Waste. Resour., 6(201), 1-13. https://doi.org/10.4172/2252-5211.1000201.
Nair, U. S., Lawton, R. O., Welch, R. M. & Pielke Sr, R. A. (2003). Impact of land use on Costa Rican tropical montane cloud forests: Sensitivity of cumulus cloud field characteristics to lowland deforestation. J. Geophys. Res. -Atmos., 108(D7).1-13. https://doi.org/10.1029/2001JD0 01 135.
Razali, S. N. A. M., Rusiman, M. S., Zawawi, N. I. & Arbin, N. (2018). Forecasting of water consumptions expenditure using Holt-Winter’s and ARIMA. In Journal of Physics: Conference Series (Vol. 995, No. 1, p. 012041). IOP Publishing. https://doi.org/10.1088/1742-6596/995/1/012041.
Rossi G. (2003). Requisites for a drought watch system. In: Rossi G, Cancelliere A, Pereira LS, Oweis T, Shatanawi M, Zairi A (eds) Tools for drought mitigation in Mediterranean regions. Springer, Dordrecht, 147–157. https://doi.org/10.1007/978-94-010-0129-8_9.
SAFE (2011). Community-ecosystem approach for adaptive watershed management in drought-prone tribal areas of West Bengal. www.resourceaward.org.
Singh, G.R., Jain, M.K. & Gupta, V (2019). Spatiotemporal assessment of drought hazard, vulnerability and risk in the Krishna River basin, India. Nat. Hazards. 99, 611–635. https://doi.org/10.1007/s11069-019-03762-6.
Sönmez, F. K., Koemuescue, A. U., Erkan, A. & Turgu, E. (2005). An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Nat. Hazards., 35(2), 243-264. https://doi.org/10.1007/s11069-004-5704-7.
Stagge, J. H., Kohn, I., Tallaksen, L. M. & Stahl, K. (2015). Modeling drought impact occurrence based on meteorological drought indices in Europe. J. Hydrol., 530, 37–50. https://doi.org/10.1016/j.jhydrol.2015.09.039.
Suryanarayana, T. M. V & Mistry, P. B. (2016). Principal component regression for crop yield estimation. Springer Singapore. https://doi.org/10.1007/978-981-10-0663-0.
Thom, H. C. S. (1958). A note on the gamma distribution, Monthly. Weather. Rev., 86, 117–122. https://doi.org/10.1 175/1520-0493(1958)086%3C0117:ANOTGD %3E2.0.CO;2.
Wichitarapongsakun, P., Sarin, C., Klomjek, P. & Chuenchooklin, S. (2016). Rainfall prediction and meteorological drought analysis in the Sakae Krang River basin of Thailand. Agriculture and Natural Resources, 50(6), 490–498. https://doi.org/10.1016/j.anres.2016.05.003.
Yves, T., Koutroulis, A., Samaniego, L., Vicente-Serrano, S. M., Volaire, F., Boone, A. & Polcher, J. (2020). Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth-Science Reviews, 103348. https://doi.org/10.1016/j.earscirev.20 20.1 03348.
Zarch, M. A. A., Sivakumar, B. & Sharma, A. (2015). Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI). J. Hydrol.., 526, 183-195. https://doi.org/10.1016/j.jhydrol.2014.09.071.
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)
How to Cite
Comparative study of different exponential smoothing models in simulation of meteorological drought : A study on Purulia district, West Bengal, India . (2021). Journal of Applied and Natural Science, 13(2), 504-511. https://doi.org/10.31018/jans.v13i2.2637
