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Monitoring drought pattern for pre- and post-monsoon seasons in a semi-arid region of western part of India

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Abstract

Drought has become a regular phenomenon in the western semi-arid regions of India, where severe drought occurs once in 8–9 years. Therefore, two drought indices, namely temperature condition index (TCI) and vegetation condition index (VCI), were prepared from using Landsat datasets to appraise and monitor of drought pattern for the pre- and post-monsoon seasons between 1996 and 2016 in the Latur district, the north-western part of India. Additionally, the average frequency layers (AFL) of all drought and land use indices were prepared to analyse the correlation between them. The results show a substantial increase in the area under high, very high and severe drought classes both pre- and post-monsoon seasons during the study period. The highest increase was noticed from the high drought class from 2532.45 to 4792.49 sq. km and 1559.84 to 3342.32 sq. km for pre- and post-monsoon season, respectively, based on the TCI and 1269.81 to 1787.77 sq. km in very high drought class for the post-monsoon season using the VCI. The correlation analysis showed that there exists a significant relationship between the land use indices and drought indices. However, the spatial pattern of correlation was heterogeneous for both pre- and post-monsoon seasons. The results of this research can help in the drought management and mitigation planning in the study area. In addition, a similar approach may be applied to analyse drought patterns in other places with similar geographic characteristics as both VCI and TCI are cost-effective and less time-consuming methods and produce reliable outcomes.

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All the datasets generated during this research work are included in this manuscript.

References

  • AghaKouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M. C., Wardlow, B. D., & Hain, C. R. (2015). Remote sensing of drought: Progress, challenges and opportunities. Reviews of Geophysics, 53(2), 452–480.

    Article  Google Scholar 

  • Artis, D. A., & Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12(4), 313–329.

    Article  Google Scholar 

  • Banerjee, S., & Pandey, A. C. (2021). Catchment-level agricultural drought hazard vulnerability analysis of Ganga Basin (India) using spectral indices. Arabian Journal of Geosciences, 14(17), 1–22.

    Article  Google Scholar 

  • Barbosa, M. L. F., Delgado, R. C., Teodoro, P. E., Pereira, M. G., Correia, T. P., de Mendonça, B. A. F., & de Ávila Rodrigues, R. (2019). Occurrence of fire foci under different land uses in the State of Amazonas during the 2005 drought. Environment, Development and Sustainability, 21(6), 2707–2720.

    Article  Google Scholar 

  • Bhardwaj, K., Shah, D., Aadhar, S., & Mishra, V. (2020). Propagation of meteorological to hydrological droughts in India. Journal of Geophysical Research: Atmospheres, 125(22), e2020JD033455.

  • Borro, M., Morandeira, N., Salvia, M., Minotti, P., Perna, P., & Kandus, P. (2014). Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data. Journal of Hydrology, 512, 39–52.

    Article  Google Scholar 

  • Cao, Y., Chen, S., Wang, L., Zhu, B., Lu, T., & Yu, Y. (2019). An agricultural drought index for assessing droughts using a water balance method: A case study in Jilin Province. Northeast China. Remote Sensing, 11(9), 1066.

    Article  Google Scholar 

  • Chahal, M., Singh, O., Bhardwaj, P., & Ganapuram, S. (2021). Exploring spatial and temporal drought over the semi-arid Sahibi river basin in Rajasthan. India. Environmental Monitoring and Assessment, 193(11), 1–25.

    Google Scholar 

  • Chandrasekara, S. S., Kwon, H. H., Vithanage, M., Obeysekera, J., & Kim, T. W. (2021). Drought in South Asia: A review of drought assessment and prediction in South Asian countries. Atmosphere, 12(3), 369.

    Article  Google Scholar 

  • Cheng, C. H., Nnadi, F., & Liou, Y. A. (2015). A regional land use drought index for Florida. Remote Sensing, 7(12), 17149–17167.

    Article  Google Scholar 

  • Cook, B. I., Smerdon, J. E., Seager, R., & Coats, S. (2014). Global warming and 21st century drying. Climate Dynamics, 43(9–10), 2607–2627.

    Article  Google Scholar 

  • Dai, A. (2013). Increasing drought under global warming in observations and models. Nature Climate Change, 3, 52–58.

    Article  Google Scholar 

  • Dai, A. (2011). Drought under global warming: A review. Wires Climatic Change, 2, 45–65.

    Article  Google Scholar 

  • Dhawale, R., & Paul, S. K. (2018). A comparative analysis of drought indices on vegetation through remote sensing for Latur region of India. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, XLII-5, 403–407.

  • Dorjsuren, M., Liou, Y. A., & Cheng, C. H. (2016). Time series MODIS and in situ data analysis for Mongolia drought. Remote Sensing, 8(6), 509.

    Article  Google Scholar 

  • Du, T. L. T., Bui, D. D., Nguyen, M. D., & Lee, H. (2018). Satellite-based, multi-indices for evaluation of agricultural droughts in a highly dynamic tropical catchment. Central Vietnam. Water, 10(5), 659.

    Google Scholar 

  • Dutta, D., Kundu, A., Patel, N. R., Saha, S. K., & Siddiqui, A. R. (2015). Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI). The Egyptian Journal of Remote Sensing and Space Science, 18(1), 53–63.

    Article  Google Scholar 

  • Ganguli, P., & Reddy, M. J. (2014). Evaluation of trends and multivariate frequency analysis of droughts in three meteorological subdivisions of western India. International Journal of Climatology, 34(3), 911–928.

    Article  Google Scholar 

  • Garrido, A., & Gómez-Ramos, A. (2000). Socio-economic aspects of droughts. In Drought and drought mitigation in Europe (pp. 197–207). Springer, Dordrecht.

  • GOI (2019). National Crisis Management Plan for Drought. Ministry of Agriculture and Farmers Welfare (Department of Agriculture, Cooperation and Farmers Welfare). Government of India. https://agricoop.nic.in/sites/default/files/CRISIS-MANAGEMENT-PLAN-2019.pdf

  • Hao, Z., Singh, V. P., & Xia, Y. (2018). Seasonal drought prediction: Advances, challenges, and future prospects. Reviews of Geophysics, 56(1), 108–141.

    Article  Google Scholar 

  • Hollins, S., Dodson, J., Drought. (2013). In: Bobrowsky P.T. (eds) Encyclopedia of Natural Hazards. Encyclopedia of Earth Sciences Series. Springer, Dordrecht., pp. 189–197.

  • Huang, J., Li, Y., Fu, C., Chen, F., Fu, Q., Dai, A., & Wang, G. (2017). Dryland climate change: Recent progress and challenges. Reviews of Geophysics, 55(3), 719–778.

    Article  Google Scholar 

  • India Today. (2016). Latur: The great thirst. 2016. https://www.indiatoday.in/magazine/special-report/story/20160411-latur-water-crisis-drought-marathwada-the-great-thirst-828694-2016-03-30

  • Islam, A. R. M., Shen, S., Hu, Z., & Rahman, M. A. (2017). Drought hazard evaluation in boro paddy cultivated areas of western Bangladesh at current and future climate change conditions. Advances in Meteorology, 2017, Article ID 3514381.

  • Ji, L., & Peters, A. J. (2003). Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sensing of Environment, 87(1), 85–98.

    Article  Google Scholar 

  • Jiang, R., Liang, J., Zhao, Y., Wang, H., Xie, J., Lu, X., & Li, F. (2021). Assessment of vegetation growth and drought conditions using satellite-based vegetation health indices in Jing-Jin-Ji region of China. Scientific Reports, 11(1), 1–18.

    CAS  Google Scholar 

  • Jin, S., & Sader, S. A. (2005). Comparison of time series tasseled cap wetness and the normalized difference moisture index in detecting forest disturbances. Remote Sensing of Environment, 94(3), 364–372.

    Article  Google Scholar 

  • Joshi, K. (2019). The impact of drought on human capital in rural India. Environment and Development Economics, 24(4), 413–436.

    Article  Google Scholar 

  • Kamruzzaman, M., Kabir, M. E., Rahman, A. S., Jahan, C. S., Mazumder, Q. H., & Rahman, M. S. (2018). Modeling of agricultural drought risk pattern using Markov chain and GIS in the western part of Bangladesh. Environment, Development and Sustainability, 20(2), 569–588.

    Article  Google Scholar 

  • Katalakute, G., Wagh, V., Panaskar, D., & Mukate, S. (2016). Impact of drought on environmental, agricultural and socio-economic status in Maharashtra State. India. Natural Resources and Conservation, 4(3), 35–41.

    Article  Google Scholar 

  • Khalili, N., Arshad, M., Farajzadeh, Z., Kächele, H., & Müller, K. (2021). Does drought affect smallholder health expenditures? Evidence from Fars Province. Iran. Environment, Development and Sustainability, 23(1), 765–788.

    Article  Google Scholar 

  • Kogan, F. N. (1995). Application of vegetation index and brightness temperature for drought detection. Advances in Space Research, 15(11), 91–100.

    Article  Google Scholar 

  • Kriegler, F. J., Malila, W. A., Nalepka, R. F. & Richardson, W. (1969). Preprocessing transformations and their effects on multispectral recognition. Remote sensing of environment, VI, 97.

  • Kulkarni, A., Gadgil, S., & Patwardhan, S. (2016). Monsoon variability, the 2015 Marathwada drought and rainfed agriculture. Current Science, 111(7), 1182–1193.

    Article  Google Scholar 

  • Kumar, K. C. A., Reddy, G. O., Masilamani, P., Turkar, S. Y., & Sandeep, P. (2021). Integrated drought monitoring index: A tool to monitor agricultural drought by using time-series datasets of space-based earth observation satellites. Advances in Space Research, 67(1), 298–315.

    Article  Google Scholar 

  • Kumari, B., Tayyab, M., Ahmed, I. A., Baig, M. R. I., Khan, M. F., & Rahman, A. (2020). Longitudinal study of land surface temperature (LST) using mono-and split-window algorithms and its relationship with NDVI and NDBI over selected metro cities of India. Arabian Journal of Geosciences, 13(19), 1–19.

    CAS  Google Scholar 

  • Li, Z., Han, Y., & Hao, T. (2020). Assessing the consistency of remotely sensed multiple drought indices for monitoring drought phenomena in continental China. IEEE Transactions on Geoscience and Remote Sensing, 58(8), 5490–5502.

    Article  Google Scholar 

  • Liang, L., Sun, Q., Luo, X., Wang, J., Zhang, L., Deng, M., ... & Liu, Z. (2017). Long‐term spatial and temporal variations of vegetative drought based on vegetation condition index in China. Ecosphere, 8(8), e01919.

  • Liou, Y. A., Le, M. S., & Chien, H. (2018). Normalized difference latent heat index for remote sensing of land surface energy fluxes. IEEE Transactions on Geoscience and Remote Sensing, 57(3), 1423–1433.

    Article  Google Scholar 

  • Liou, Y. A., & Mulualem, G. M. (2019). Spatio–temporal assessment of drought in Ethiopia and the impact of recent intense droughts. Remote Sensing, 11(15), 1828.

    Article  Google Scholar 

  • Mahmud, T., Sifa, S. F., Islam, N. N., Rafsan, M. A., Kamal, A. M., Hossain, M. S., & Chakraborty, T. R. (2021). Drought dynamics of Northwestern Teesta Floodplain of Bangladesh: A remote sensing approach to ascertain the cause and effect. Environmental Monitoring and Assessment, 193(4), 1–19.

    Article  Google Scholar 

  • Mallya, G., Mishra, V., Niyogi, D., Tripathi, S., & Govindaraju, R. S. (2016). Trends and variability of droughts over the Indian monsoon region. Weather and Climate Extremes, 12, 43–68.

    Article  Google Scholar 

  • McFeeters, S. K. (1996). The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425–1432.

    Article  Google Scholar 

  • Mishra, V., Thirumalai, K., Jain, S., & Aadhar, S. (2021). Unprecedented drought in South India and recent water scarcity. Environmental Research Letters, 16(5), 054007.

  • Mishra, A., & Liu, S. C. (2014). Changes in precipitation pattern and risk of drought over India in the context of global warming. Journal of Geophysical Research: Atmospheres, 119(13), 7833–7841.

    Article  Google Scholar 

  • Mulualem, G. M., & Liou, Y. A. (2020). Application of artificial neural networks in forecasting a standardized precipitation evapotranspiration index for the Upper Blue Nile basin. Water, 12(3), 643.

    Article  Google Scholar 

  • Naikoo, M. W., Rihan, M., Peer, A. H., Talukdar, S., Mallick, J., Ishtiaq, M., & Rahman, A. (2022). Analysis of peri-urban land use/land cover change and its drivers using geospatial techniques and geographically weighted regression. Environmental Science and Pollution Research, 1–19.

  • Niaz, M. A., Faiz, M. A., & Yongxia, W. (2021). Development of an integrated weighted drought index and its application for agricultural drought monitoring. Arabian Journal of Geosciences, 14(6), 1–12.

    Article  Google Scholar 

  • Ogunjo, S., Ife-Adediran, O., Owoola, E., & Fuwape, I. (2019). Quantification of historical drought conditions over different climatic zones of Nigeria. Acta Geophysica, 67(3), 879–889.

    Article  Google Scholar 

  • Oloruntade, A. J., Mohammad, T. A., Ghazali, A. H., & Wayayok, A. (2017). Analysis of meteorological and hydrological droughts in the Niger-South Basin, Nigeria. Global and Planetary Change, 155, 225–233.

    Article  Google Scholar 

  • Panu, U. S., & Sharma, T. C. (2002). Challenges in drought research: Some perspectives and future directions. Hydrological Sciences Journal, 47(S1), S19–S30.

    Article  Google Scholar 

  • Patel, P. M., Saha, D., & Shah, T. (2020). Sustainability of groundwater through community-driven distributed recharge: An analysis of arguments for water scarce regions of semi-arid India. Journal of Hydrology: Regional Studies, 29, 100680.

  • Patel, N. R., Parida, B. R., Venus, V., Saha, S. K., & Dadhwal, V. K. (2012). Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data. Environmental Monitoring and Assessment, 184(12), 7153–7163.

    Article  CAS  Google Scholar 

  • Praveen, B., Talukdar, S., Mahato, S., Mondal, J., Sharma, P., Islam, A. R. M. T., & Rahman, A. (2020). Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches. Scientific Reports, 10(1), 1–21.

    Article  CAS  Google Scholar 

  • Qaiser, G., Tariq, S., Adnan, S., & Latif, M. (2021). Evaluation of a composite drought index to identify seasonal drought and its associated atmospheric dynamics in Northern Punjab, Pakistan. Journal of Arid Environments, 185, 104332.

  • Rossi, G. (2000). Drought mitigation measures: A comprehensive framework. In Drought and drought mitigation in Europe (pp. 233–246). Springer, Dordrecht.

  • Rousta, I., Olafsson, H., Moniruzzaman, M., Zhang, H., Liou, Y. A., Mushore, T. D., & Gupta, A. (2020). Impacts of drought on vegetation assessed by vegetation indices and meteorological factors in Afghanistan. Remote Sensing, 12(15), 2433.

    Article  Google Scholar 

  • Shahfahad., Naikoo, M. W., Islam, A. R. M. T., Mallick, J., & Rahman, A. (2022). Land use/land cover change and its impact on surface urban heat island and urban thermal comfort in a metropolitan city. Urban Climate, 41, 101052.

  • Shahfahad., Kumari, B., Tayyab, M., Hang, H. T., Khan, M. F., & Rahman, A. (2019). Assessment of public open spaces (POS) and landscape quality based on per capita POS index in Delhi. India. SN Applied Sciences, 1(4), 1–13.

    Google Scholar 

  • Shen, Q., Liang, L., Luo, X., Li, Y., & Zhang, L. (2017). Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010. Environmental Monitoring and Assessment, 189(9), 1–14.

    Article  CAS  Google Scholar 

  • Shewale, M. P., & Kumar, S. (2005). Climatological features of drought incidences in India. Meteorological Monograph (Climatology 21/2005), National Climate Centre, Indian Meteorological Department. https://imdpune.gov.in/hydrology/Drought/drought.pdf. Accessed December 2021.

  • Shojaei, S., & Rahimzadegan, M. (2020). Improving a comprehensive remote sensing drought index (CRSDI) in the Western part of Iran. Geocarto International, 1–19.

  • Shukla, P., & Parishwad, O. (2017). Mitigating Water Crisis by Prioritization Sub -Watershed Areas for Resource Management- A Case Study of Latur India. International Journal on Emerging Technologies, 8(1), 635–641.

  • Smirnov, O., Zhang, M., Xiao, T., Orbell, J., Lobben, A., & Gordon, J. (2016). The relative importance of climate change and population growth for exposure to future extreme droughts. Climatic Change, 138(1), 41–53.

    Article  CAS  Google Scholar 

  • Sun, W., Wang, P. X., Zhang, S. Y., Zhu, D. H., Liu, J. M., Chen, J. H., & Yang, H. S. (2008). Using the vegetation temperature condition index for time series drought occurrence monitoring in the Guanzhong Plain, PR China. International Journal of Remote Sensing, 29(17–18), 5133–5144.

    Article  Google Scholar 

  • Tian, M., Wang, P., & Khan, J. (2016). Drought forecasting with vegetation temperature condition index using ARIMA models in the Guanzhong Plain. Remote Sensing, 8, 690.

    Article  Google Scholar 

  • Todmal, R. S. (2019). Droughts and agriculture in the semi-arid region of Maharashtra, western India. Weather, Climate, and Society, 11(4), 741–754.

    Article  Google Scholar 

  • Turner, A. G., & Annamalai, H. (2012). Climate change and the South Asian summer monsoon. Nature Climate Change, 2(8), 587–595.

    Article  Google Scholar 

  • Udmale, P., Ichikawa, Y., Manandhar, S., Ishidaira, H., & Kiem, A. S. (2014). Farmers׳ perception of drought impacts, local adaptation and administrative mitigation measures in Maharashtra State, India. International Journal of Disaster Risk Reduction, 10, 250–269.

    Article  Google Scholar 

  • Uddin, M. J., Hu, J., Islam, A. R. M. T., Eibek, K. U., & Nasrin, Z. M. (2020). A comprehensive statistical assessment of drought indices to monitor drought status in Bangladesh. Arabian Journal of Geosciences, 13(9), 1–10.

    Article  Google Scholar 

  • Vyas, S. S., & Bhattacharya, B. K. (2020). Agricultural drought early warning from geostationary meteorological satellites: Concept and demonstration over semi-arid tract in India. Environmental Monitoring and Assessment, 192(5), 1–15.

    Article  Google Scholar 

  • Waseem, M., Ajmal, M., Ahmad, I., Khan, N. M., Azam, M., & Sarwar, M. K. (2021). Projected drought pattern under climate change scenario using multivariate analysis. Arabian Journal of Geosciences, 14(7), 1–13.

    Article  Google Scholar 

  • Wei, W., Zhang, J., Zhou, L., Xie, B., Zhou, J., & Li, C. (2021). Comparative evaluation of drought indices for monitoring drought based on remote sensing data. Environmental Science and Pollution Research, 28(16), 20408–20425.

    Article  Google Scholar 

  • Wentz, E. A., Anderson, S., Fragkias, M., Netzband, M., Mesev, V., Myint, S. W., & Seto, K. C. (2014). Supporting global environmental change research: A review of trends and knowledge gaps in urban remote sensing. Remote Sensing, 6(5), 3879–3905.

    Article  Google Scholar 

  • Wilhite, D. A., Sivakumar, M. V., & Pulwarty, R. (2014). Managing drought risk in a changing climate: The role of national drought policy. Weather and Climate Extremes, 3, 4–13.

    Article  Google Scholar 

  • Wilhite, D. A., & Glantz, M. H. (1985). Understanding: The drought phenomenon: The role of definitions. Water International, 10(3), 111–120.

    Article  Google Scholar 

  • Xie, F., & Fan, H. (2021). Deriving drought indices from MODIS vegetation indices (NDVI/EVI) and land surface temperature (LST): Is data reconstruction necessary? International Journal of Applied Earth Observation and Geoinformation, 101, 102352.

  • Zhang, H., Ali, S., Ma, Q., Sun, L., Jiang, N., Jia, Q., & Hou, F. (2021). Remote sensing strategies to characterization of drought, vegetation dynamics in relation to climate change from 1983 to 2016 in Tibet and Xinjiang Province China. Environmental Science and Pollution Research, 28(17), 21085–21100.

    Article  Google Scholar 

  • Zhang, X., Obringer, R., Wei, C., Chen, N., & Niyogi, D. (2017). Droughts in India from 1981 to 2013 and implications to wheat production. Scientific Reports, 7(1), 1–12.

    CAS  Google Scholar 

  • Zhang, Y., Li, Y., Ge, J., Li, G., Yu, Z., & Niu, H. (2018). Correlation analysis between drought indices and terrestrial water storage from 2002 to 2015 in China. Environmental Earth Sciences, 77(12), 1–12.

    Article  Google Scholar 

  • Zhao, M., Huang, S., Huang, Q., Wang, H., Leng, G., & Xie, Y. (2019). Assessing socio-economic drought evolution characteristics and their possible meteorological driving force. Geomatics, Natural Hazards and Risk, 10(1), 1084–1101.

    Article  Google Scholar 

  • Zou, L., Cao, S., & Sanchez-Azofeifa, A. (2020). Evaluating the utility of various drought indices to monitor meteorological drought in tropical dry forests. International Journal of Biometeorology, 64(4), 701–711.

    Article  Google Scholar 

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Acknowledgements

The authors are thankful to the United States Geological Survey (USGS) for giving the free access to the satellite data. The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Research Group under grant number RGP2/169/43. The authors are also thankful to the Ministry of Science and Technology of Taiwan for supporting this work under the codes 109-2923-E-008-004-MY2, 108-2111-M-008-036-MY2 and 108-2923-M-008-002-MY3. Finally, the authors are indebted to the anonymous reviewers for their scholarly comments which helped in improving the manuscript.

Funding

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Research Group under grant number RGP2/169/43. The authors are also thankful to the Ministry of Science and Technology of Taiwan for supporting this work under the codes 109–2923-E-008–004-MY2, 108–2111-M-008–036-MY2 and 108–2923-M-008–002-MY3.

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Shahfahad, Talukdar, S., Ali, R. et al. Monitoring drought pattern for pre- and post-monsoon seasons in a semi-arid region of western part of India. Environ Monit Assess 194, 396 (2022). https://doi.org/10.1007/s10661-022-10028-5

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