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Satellite-based (2000–2015) drought hazard assessment with indices, mapping, and monitoring of Potohar plateau, Punjab, Pakistan

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Abstract

Drought is one of the deadly natural disasters that leave tearstained faces and broken dreams in its wake. Lifecycle as we know it comes to a halt during a dry season in a region. The purpose of this study was to observe the temporal and spatial variation of droughts in the rain-fed area of Potohar plateau (22,254 km2), Punjab, Pakistan, from 2000 to 2015, through remotely sensed satellite data, available at the database of Google Earth Engine. Potohar consists of four major districts of the country; Chakwal, Attock, Rawalpindi, and Jhelum. From 2000 to 2015, indices calculated were: standard precipitation index (SPI), standard precipitation evapotranspiration index (SPEI), vegetation condition index (VCI), precipitation condition index (PCI), soil moisture condition index (SMCI), and temperature condition index (TCI). In this study, SPI and SPEI pointed out meteorological droughts in 2000, 2001, 2002, 2004, 2009, 2010, and 2012, which were taken as base years for drought in the study. The study concluded that the main factor involved in the drought severity is not one, but rather a combined accumulation of temperature, precipitation, and soil moisture. Soil moisture and precipitation affect the vegetation in the area more so than the temperature of the land surface. Soil moisture was heavily influenced by the amount of precipitation. The land surface temperature was seasonal dependent. The surface temperature was warmest in Chakwal and Attock, while Rawalpindi had the coldest land surface temperature. Soil moisture increased with precipitation. Soil moisture was high in Rawalpindi and Attock during drought years.

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References

  • Abatzoglou JT, Dobrowski SZ, Parks SA, Hegewisch KC (2018) TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958 to 2015. Sci Data 5:170191

    Article  Google Scholar 

  • Agnew CT (2000) Using the SPI to identify drought. Drought Netw News 12(1):5–12. http://digitalcommons.unl.edu/droughtnetnews/1/

    Google Scholar 

  • Ahmad S, Hussain Z, Qureshi AS, Majeed R, Saleem M (2004) Drought mitigation in Pakistan: current status and options for future strategies. IWMI. https://doi.org/10.3910/2009.267

    Article  Google Scholar 

  • Akhtar IH (2014) Identification of drought events from multi years temporal SPOT NDVI data for potohar region in Pakistan. Int J Remote Sens GIS 3(3):39–52

    Google Scholar 

  • APP (2017) Climate change to significantly affect wheat, rice crop yields. The NEWS, 2017. https://nation.com.pk/26-Jun-2017/climate-change-to-significantly-affect-wheat-rice-crop-yields

  • Asian Development Bank, A (2008) Pakistan: country environmental analysis. ADP, ADP

    Google Scholar 

  • Ayehu G, Tadesse T, Gessesse B, Yigrem Y (2019) Soil moisture monitoring using remote sensing data and a stepwise-cluster prediction model: the case of Upper Blue Nile Basin, Ethiopia. Remote Sens 11(2):125

    Article  Google Scholar 

  • Beguería S, Vicente-Serrano SM, Reig F, Latorre B (2014) Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int J Climatol 34(10):3001–3023

    Article  Google Scholar 

  • Belayneh A, Adamowski J, Khalil B, Ozga-Zielinski B (2014) Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models. J Hydrol 508:418–429

    Article  Google Scholar 

  • Bhuiyan C (2008) Desert vegetation during droughts: response and sensitivity. Int Arch Photogram Remote Sens Spat Inf Sci 21:907–912

    Google Scholar 

  • Bonaccorso B, Bordi I, Cancelliere A, Rossi G, Sutera A (2003) Spatial variability of drought: an analysis of the SPI in Sicily. Water Resour Manag 17(4):273–296

    Article  Google Scholar 

  • Chaudhry QUZ (2017) Climate change profile of Pakistan (ASIAN DEVELOPMENT BANK). https://doi.org/10.22617/TCS178761

  • Chaudary FR, Khan MFU, Qayyum M (2007) Prevalence of haemonchus contortus in naturally infected small ruminants grazing in the Potohar area of Pakistan. Pak Vet

  • Dai A, NCFARSE (2017) The climate data guide: Palmer Drought Severity Index (PDSI). From https://climatedataguide.ucar.edu/climate-data/palmer-drought-severity-index-pdsi

  • Didan K (2015) MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006. 2015, distributed by NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MOD13Q1.006

  • Eco-Business (2014) Pakistan’s farmers counter climate change with beekeeping. Eco-Business. https://www.eco-business.com/news/pakistans-farmers-counter-climate-change-beekeeping/

  • Elhag KM, Zhang W (2018) Monitoring and assessment of drought focused on its impact on Sorghum yield over Sudan by using meteorological drought indices for the period 2001–2011. Remote Sens 10(8):1231

    Article  Google Scholar 

  • Ghani MW, Arshad M, Shabbir A, Shakoor A, Mehmood N, Ahmad I (2013) Investigation of potential water harvesting sites at potohar using modeling approach. Pak J Agric Sci 50(4):723–29

    Google Scholar 

  • Gorelick N (2013) Google earth engine. AGU Fall Meet Abs 15:11997. http://adsabs.harvard.edu/abs/2013AGUFM.U31A..04G

    Google Scholar 

  • Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R (2017) Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18–27

    Article  Google Scholar 

  • Grillakis MG (2019) Increase in severe and extreme soil moisture droughts for Europe under climate change. Sci Total Environ 660:1245–1255

    Article  Google Scholar 

  • Haroon MA, Zhang J, Yao F (2016) Drought monitoring and performance evaluation of MODIS-based drought severity index (DSI) over Pakistan. Nat Hazards 84(2):1349–1366

    Article  Google Scholar 

  • Heim RR Jr (2002) A review of twentieth-century drought indices used in the United States. Bull Am Meteorol Soc 83(8):1149–1165

    Article  Google Scholar 

  • Jain VK, Pandey RP, Jain MK, Byun H-R (2015) Comparison of drought indices for appraisal of drought characteristics in the Ken River Basin. Weather Clim Extrem 8:1–11

    Article  Google Scholar 

  • Jay LD (2000) Probability and statistics for engineering and sciences. Brooks/Cole Publishing Company, California

    Google Scholar 

  • Kazmi DH, Rasul G (2012) Agrometeorological wheat yield prediction in rainfed Potohar region of Pakistan. Agric Sci 03(02):8

    Google Scholar 

  • Khan I (2016) Environmental degradation costs Pakistan Rs1 billion a day. The NEWS, May 13, 2016. https://www.thenews.com.pk/print/119575-Environmental-degradation-costs-Pakistan-Rs1-billion-a-day

  • Khan KS, Joergensen RG (2006) Microbial C, N, and P relationships in moisture-stressed soils of Potohar, Pakistan. J Plant Sci Soil Sci 169(4):494–500

    Google Scholar 

  • Kogan F, Gitelson A, Zakarin E, Spivak L, Lebed L (2003) AVHRR-based spectral vegetation index for quantitative assessment of vegetation state and productivity. Photogram Eng Remote Sens 69(8):899–906

    Article  Google Scholar 

  • Kumar L, Mutanga O (2018) Google Earth engine applications since inception: usage, trends, and potential. Remote Sens 10(10):1509

    Article  Google Scholar 

  • Kurosaki T (2015) Vulnerability of household consumption to floods and droughts in developing countries: evidence from Pakistan. Environ Dev Econ 20(2):209–235

    Article  Google Scholar 

  • Hansen K, Lindsey R (2002) NASA’s earth observatory: a decade of earth science on display. NASA. https://www.nasa.gov/topics/earth/features/EO_decade.html

  • Mckee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the ninth conference on applied climatology. American metereological society, Anaheim, California, pp 179–184. http://www.droughtmanagement.info/literature/AMS_Relationship_Drought_Frequency_Duration_Time_Scales_1993.pdf

    Google Scholar 

  • Memon N (2012) Disasters in South Asia—A regional perspective. Karachi: Pakistan institute of labour education and research PILER centre, ST-001, Sector X, Sub-Sector V Gulshan-e-Maymar, Karachi. http://www.ndma.gov.pk/Publications/DisastersinSouthAsia,Regionalperspective.pdf

  • Moore RT, Hansen MC (2011) Google earth engine: a new cloud-computing platform for global-scale earth observation data and analysis. American Geophysical Union, Fall Meeting, Abstract #IN43C-02 2011: IN43C-02. http://adsabs.harvard.edu/abs/2011AGUFMIN43C..02M

  • Moreira EE, Paulo AA, Pereira LS, Mexia JT (2006) Analysis of SPI drought class transitions using loglinear models. J Hydrol 331(1–2):349–359

    Article  Google Scholar 

  • NIST/SEMATECH e-Handbook of statistical methods (2003). http://www.itl.nist.gov/div898/handbook

  • Palmer WC (1965) Meteorological drought. U.S. Weather Bureau, Res. Pap. No. 45

  • Pani P, Alahacoon N, Amarnath G, Bharani G, Mondal S, Jeganathan C (2016) Comparison of SPI and IDSI applicability for agriculture drought monitoring in Sri Lanka. In: 37th Asian conference on remote sensing. Colombo, Sri Lanka. https://www.researchgate.net/publication/311303722_COMPARISON_OF_SPI_AND_IDSI_APPLICABILITY_FOR_AGRICULTURE_DROUGHT_MONITORING_IN_SRI_LANKA

  • Park S, Seo E, Kang D, Im J, Lee M-I (2018) Prediction of drought on pentad scale using remote sensing data and MJO index through random forest over East Asia. Remote Sens 10(11):1811

    Article  Google Scholar 

  • Patel NN, Angiuli E, Gamba P, Gaughan A, Lisini G, Stevens FR, Tatem AJ, Trianni G (2015) Multitemporal settlement and population mapping from Landsat using Google Earth Engine. Int J Appl Earth Obs Geoinf 35:199–208

    Article  Google Scholar 

  • Paulo AA, Pereira LS (2007) Prediction of SPI drought class transitions using Markov chains. Water Resour Manag 21(10):1813–1827

    Article  Google Scholar 

  • PMD (2018) Drought bulletin of Pakistan April-June 2018. Islamabad. http://www.ndmc.pmd.gov.pk/quater218.pdf

  • Rashid K, Rasul G (2011) Rainfall variability and maize production over the potohar plateau of Pakistan. Pak J Meteorol 8(15):63–74

    Google Scholar 

  • Roy S, Kogan F (2003) Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India AU - Singh, Ramesh P. Int J Remote Sens 24(22):4393–4402

    Article  Google Scholar 

  • Saad-Ul-Haque, Ghauri B, Khan MR (2013) Short term drought monitoring using remote sensing technique: a case study of potohar region, Pakistan. In: ICASE 2013—Proceedings of the 3rd international conference on aerospace science and engineering. IEEE, pp 137–44. https://doi.org/10.1109/ICASE.2013.6785571

  • Sheikh AT (2019) Can Climate change Pakistan? Dawn. January 20, 2019. https://www.dawn.com/news/1458694

  • Stagge JH, Tallaksen LM, Gudmundsson L, Van Loon AF, Stahl K (2015) Candidate distributions for climatological drought indices (SPI and SPEI). Int J Climatol 35(13):4027–4040

    Article  Google Scholar 

  • Svoboda M, Hayes M, Wood D (2012) Standardized precipitation index user guide. World Meteorological Organization, Geneva

    Google Scholar 

  • Thenkabail PS, Gamage MSDN, Smakhtin VU (2004) The use of remote sensing data for drought assement and monitering in Southwest Asia. IWMI Research Report 085. https://doi.org/10.3910/2009.086

  • Umar M, Mansha M, Khan MS, Javed MN, Gao H, Farhan SB, Iqbal I, Abdullah S (2018) Assessment of drought conditions using HJ-1A/1B data: a case study of Potohar region, Pakistan AU - Aziz, Adnan. Geom Nat Hazard Risk 9(1):1019–1036

    Article  Google Scholar 

  • Umran Komuscu A (1999) Using the SPI to analyze spatial and temporal patterns of drought in Turkey. Drought Netw NEWS 1994–2001:49

    Google Scholar 

  • Urban M, Berger C, Mudau TE, Heckel K, Truckenbrodt J, Onyango Odipo V, Smit IPJ, Schmullius C (2018) Surface moisture and vegetation cover analysis for drought monitoring in the Southern Kruger National Park using sentinel-1, sentinel-2, and landsat-8. Remote Sens 10(9):1482

    Article  Google Scholar 

  • Vicente-Serrano SM, Beguería S, Lorenzo-Lacruz J, Camarero JJ, López-Moreno JI, Azorin-Molina C, Revuelto J, Morán-Tejeda E, Sanchez-Lorenzo A (2012) Performance of drought indices for ecological, agricultural, and hydrological applications. Earth Interact 16(10):1–27

    Article  Google Scholar 

  • Wan Z, Hook S, Hulley G (2015) MOD11A1 MODIS/Terra Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid V006. 2015, distributed by NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MOD11A1.006

  • Wang Y, Yang J, Chang J, Zhang R (2019) Assessing the drought mitigation ability of the reservoir in the downstream of the Yellow River. Sci Total Environ 646:1327–1335

    Article  Google Scholar 

  • Wilhite DA, Glantz MH (1985) Understanding: the drought phenomenon: the role of definitions. Water Int 10(3):111–20. https://doi.org/10.1080/02508068508686328

    Article  Google Scholar 

  • Yu L, Gong P (2012) Google Earth as a virtual globe tool for Earth science applications at the global scale: progress and perspectives. Int J Remote Sens 33(12):3966–3986

    Article  Google Scholar 

  • Zargar A, Sadiq R, Naser B, Khan FI (2011) A review of drought indices. Environ Rev 19(NA):333–349

    Article  Google Scholar 

  • Zhang L, Jiao W, Zhang H, Huang C, Tong Q (2017) Studying drought phenomena in the Continental United States in 2011 and 2012 using various drought indices. Remote Sens Environ 190:96–106

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute of Space Technology, Islamabad, Pakistan

    Ramla Khan, Hammad Gilani & Imran Shahid

  2. Pakistan Council of Research in Water Resources, Islamabad, Pakistan

    Naveed Iqbal

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  1. Ramla Khan
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  2. Hammad Gilani
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  3. Naveed Iqbal
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  4. Imran Shahid
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Contributions

Ramla Khan and Dr. Hammad Gillani did the processing in Earth Engine and wrote the draft of the paper. Dr. Naveed Iqbal and Dr. Imran Shahid gave pointers on different processes involved in drought monitoring.

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Correspondence to Hammad Gilani.

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Khan, R., Gilani, H., Iqbal, N. et al. Satellite-based (2000–2015) drought hazard assessment with indices, mapping, and monitoring of Potohar plateau, Punjab, Pakistan. Environ Earth Sci 79, 23 (2020). https://doi.org/10.1007/s12665-019-8751-9

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