Abstract
Climate change is the major global challenge facing water resources managers. Drought is a natural hazard temporarily affecting almost every region in the world. In this study, the climate change in term of rainfall fluctuation in the northern part of Iraq (Mosul, Kirkuk and Salah Al-Din) has been investigated using a set of data containing monthly precipitation for the period from 1980 to 2010, and the MODIS time series images for the period from 2000 to 2010. All data series have been used to calculate standardized precipitation index (SPI) and Normalized Difference Vegetation Index (NDVI). Monthly rainfall data from 12 stations were used to derive the SPI at several time scales (3, 6 and 12-months), the analysis was carried out for the period from 1980 to 2010. Results of the SPI analyses showed that the year 2007–2008 was an extremely drought year for the whole study governorates (Mosul, Kirkuk and Salah Al-Din) with the lowest SPI-12 values −2.67, −2.07 and −2.0 for the three above mentioned governorates, respectively. The results also pointed to the importance of using short time scales in detecting and monitoring the agricultural drought during the crop growing season. The multiple time scales analyzed in this study reflected a clearer picture of the severity and frequencies of drought events, which happened in the study area. The NDVI results were analyzed to get the agricultural drought risk map. The highest NDVI values were 0.33 in 2001, 0.39 in 2003 and 0.20 in 2001 for Mosul, Kirkuk and Salah Al-Din, respectively. While the lowest NDVI values were 0.10 in, 0.19 and 0.13 in 2008 for the three above mentioned governorates respectively. This study emphasized the use of Remote Sensing and GIS in the field of drought risk evaluation. The results showed that the NDVI is an efficient way to monitor changes in vegetation conditions (weekly or daily) during the growing season, and can be used as simple and cost-efficient drought index to monitor agricultural drought at a small or large scale. The NDVI and rainfall were found to be highly correlated 0.83, 0.70 and 0.72 for Mosul, Kirkuk and Salah Al-Din, respectively. Therefore, the temporal variations of NDVI are closely linked with precipitation. Results of statistical correlation analysis between NDVI and SPI (3, 6 and 12-months) time scales showed that the highest correlation coefficients were between NDVI and SPI-6, which verified that the short time scales could be related closely to soil moisture. It was observed that the studied indices (NDVI & SPI) could be effectively used for monitoring and assessing agricultural productions and in that way, proper agricultural policies can be adopted to mitigate drought impacts.
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References
Agnew CT (2000) Using the SPI to identify drought. National Drought Mitigation Center, vol 12, no 1
Almamalachy YS, Al-Quraishi AMF, Moradkhani H (2019) Agricultural drought monitoring over Iraq utilizing MODIS products. In: Al-Quraishi AMF, Negm AM (eds) Environmental Remote Sensing and GIS in Iraq. Springer Water
Al-Quraishi AMF, Qader SH, Wu W (2019) Drought monitoring using spectral and meteorological based indices combination: a case study in Sulaimaniyah, Kurdistan region of Iraq. In: Al-Quraishi AMF, Negm AM (eds) Environmental Remote Sensing and GIS in Iraq. Springer Water
Boken VK, Cracknell AP, Heathcote RL (eds) (2005) Monitoring and predicting agricultural drought. Oxford University Press, Oxford, 472 pp
Borg DS (2009) An application of drought indices in Malta, case study. Eur Water (EWRA) 25:25–38
Bot A, Benites J (2005) The importance of soil organic matter: key to drought-resistant soil and sustained food production. FAO Soils Bull 80:94
Bussay A, Szinell C, Hayes M, Svoboda M (1998) Monitoring drought in Hungary using the standardized precipitation index. Annales Geophysicae, Supplement 11 to vol 16, Abstract Book of 23rd EGS General Assembly, C450, Nice, France Apr 1998
Cancelliere A, Mauro GD, Bonaccorso B, Rossi G (2007) Drought forecasting using the standardized precipitation index. Water Resour Manage 21(5):17–22
Chopra P (2006) Drought risk assessment using remote sensing and GIS, a case study in Gujarat, M.Sc. thesis, Dept. of Geo-information Science and Earth Observation, ITC, Netherlands
Corti T, Muccione V, Köllner-Heck P, Bresch D, Seneviratne SI (2009) Simulating past droughts and associated building damages in France. Hydrol Earth Syst Sci 13(9):1739–1747
Dracup JA, Lee KS, Paulson JEG (1980) On the definition of drought. Water Resour Res 16:297–302
Eastman JR, Sangermano F, Ghimire B, Zhu HL, Chen H, Neeti N et al (2009) Seasonal trend analysis of image time series. Int J Remote Sens 30:2721–2726
Edwards DC, McKee TB (1997) Characteristics of 20th century drought in the United States at multiple timescales. Colorado State University: Fort Collins. Climatology Report No. 97-2
Fadhil AM (2009) Land degradation detection using geo-information technology for some sites in Iraq. J Al-Nahrain Univ Sci 12(3):94–108
Fadhil AM (2011) Drought mapping using geoinformation technology for some sites in the Iraqi Kurdistan region. Int J Digital Earth 4(3):239–257
Fadhil AM (2013) Sand dunes monitoring using remote sensing and GIS techniques for some sites in Iraq. In: Proceedings SPIE 8762, PIAGENG 2013: intelligent information, control, and communication technology for agricultural engineering, p 876206. https://doi.org/10.1117/12.2019735
FAO (2003) Special Report: FAO Iraq crop production, 16 Jan 2003
Fensholt R, Proud SR (2012) Evaluation of earth observation based on long term vegetation trends—comparing GIMMS and MODIS global NDVI time series. Remote Sens Environ 119:131–147
Fensholt R, Rasmussen K (2011) Analysis of trends in the Sahelian ‘rain-use efficiency’ using GIMMS NDVI, RFE and GPCP rainfall data. Remote Sens Environ 115:438–451
Fern RR, Elliott AF, Andrea B, Michael LM (2018) Suitability of NDVI and OSAVI as estimators of green biomass and coverage in a semi-arid rangeland. Ecol Ind 94:16–21
Ghulam A, Qin Q, Kusky T, Li ZL (2008) A re-examination of perpendicular drought indices. Int J Remote Sens 29:6037–6044
Ghulam A, Qin Q, Teyip T, Li ZL (2007) Modified perpendicular drought index (MPDI): a real-time drought monitoring method. ISPRS J Photogrammetry Remote Sens 62:150–164
Goebel M-O, Bachmann J, Reichstein M et al (2011) Soil water repellency and its implications for organic matter decomposition—is there a link to extreme climatic events? Glob Change Biol 17:2640–2656
Gutman GG (1991) Vegetation indices from AVHRR data: an update and future prospects. Remote Sens Environ 35:121–136
Haheen A, Baig MA (2011) Drought severity assessment in Arid Area of Thal Doab using remote sensing and GIS. Int J Water Resour Arid Environ 1(2):92–101
Hayes MHB, Swift RS (2011) Progress towards understanding aspects of composition and structure of humic substances. HIS, University of Adelaide, Australia
Hayes M, Svoboda M, Wilhite D, Vanyarkho O (1999) Monitoring the 1996 drought using the standardized precipitation index. Bull Am Meteor Soc 80(3):429–438
Heidorn KC (2007) Drought: the silent disaster. The Weather Doctor’s Weather Almanac [Online]. URL: http://www.islandnet.com/~see/weather/almanac/arc2007/alm07. Accessed 12 June 2011
Hisdal HB, Clausen A, Gustard E, Peters, Tallaksen LM (2004) Events definitions and indices. In: Tallaksen LM, Van Lanen HAJ (eds) Hydrological drought—processes and estimation methods for streamflow and groundwater, developments in water science, vol 48, Elsevier Science B.V., Amsterdam, pp 139–198
Hueso S, Brunetti G, Senesi N, Farrag K, Hernandez T, Garcia C (2012) Semi-arid soils submitted to severe drought stress: influence on humic acid characteristics in organic-amended soils. J Soil Sediments 12:503–512
Huschke RE (ed) (1959) Glossary of meteorology. American Meteorological Society, Boston, 638 p
IAU Report (2010) Inter-Agency Information and Analysis Unit (October 2010), Water in Iraq fact sheet
Jain SK, Keshri R, Goswami A, Sarkar A, Chaudhry A (2009) Identification of drought-vulnerable areas using NOAA-AVHRR data. Int J Remote Sens 30(10):2653–2668
Jain SK, Keshri R, Goswami A, Sarkar A (2010) Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India. Nat Hazards 54:643–656
Ji L, Peter AJ (2003) Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sens Environ 87(1):85–98
Justice CO, Townshend J (2002) Special issue on the moderate resolution imaging spectroradiometer (MODIS): a new generation of land surface monitoring. Remote Sens Environ 83(1):1–2
Kogan FN (1990) Remote sensing of weather change impact on vegetation index in non-homogenous areas. Int J Remote Sens 11:1405–1421
Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15:91–100
Kogan FN (1997) Global drought watch from space. Bull Am Meteorol Soc 78:621–636
Kogan FN, Sullivan J (1993) Development of global drought-watch system using NOAA/AVHRR data. Adv Space Res 13:219–222
Komuscu AU (1999) Using the SPI to analyze spatial and temporal patterns of drought in Turkey. Drought Netw News 11:7–13
Kutson C, Hayes M, Philips T (1998) How to reduce drought risk. Western Drought Coordination Council
Labedzki L (2007) Estimation of local drought frequency in central Poland using the Standardized Precipitation Index SPIy. Irrig Drain 56:67–77. www.interscience.wiely.com
Lal R (2009) Soil degradation as a reason for inadequate human nutrition. Food Sec 1:45–57
Legesse G (2010) Agricultural drought assessment using remote sensing and GIS techniques, M.Sc. thesis, Addis Ababa University
Li B, Tao V et al (2002) Relations between AVHRR NDVI and ecoclimatic parameters in China. Int J Remote Sens 23(5):989–999
Martiny N, Camberlin P, Richard Y, Philippon N (2006) Compared regimes of NDVI and rainfall in semiarid regions of Africa. Int J Remote Sens 27:5201–5223
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th conference on applied climatology. American Meteorological Society, Boston, pp 179–184
Murad H, Saiful Islam AKM (2011) Drought assessment using remote sensing and GIS in north-west region of Bangladesh. In: 3rd international conference on water and flood management (ICWFM)
Murthy CS, Seshasai MVR, Chandrasekar K, Roy PS (2009) Spatial and temporal responses of different crop-growing environments to agricultural drought: a study in Haryana state, India using NOAA AVHRR data. Int J Remote Sens 30:2897–2914
NDMC (2006) Defining drought: overview. National Drought Mitigation Center, University of Nebraska–Lincoln
Okorie FC (2003) Studies on drought in the sub-Saharan Region of Nigeria using remote sensing and precipitation data, JNCASR-Costed Fellowship Programme, University of Hyderabad, India, January–April
Persendt FC (2009) Drought risk analysis using remote sensing and GIS in the Oshikoto—Region of Namibia, M.Sc. thesis, Dept. of Environment and Development, University of KwaZulu-Natal, Pietermaritzburg
Prince SD (2002) Spatial and temporal scales of measurement of desertification//Stafford-Smith M, Reynolds JF, Global desertification: do humans create deserts? Dahlem University, Berlin
PRT/USAID/RTI (2007) Strategic planning of Kirkuk province. Approved by provincial council of Kirkuk province, the future vision of Kirkuk province, government of Iraq, Sept 2011
Qin Q, Ghulam A, Zhu L, Wang L, LI J, Nan P (2008) Evaluation of MODIS derived perpendicular drought index for estimation of surface dryness over northwestern China. Int J Remote Sens 29:1983–1995
Quiring SM, Ganesh S (2010) Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas. Agric For Meteorol 150:330–339
Rathore MS (2004) State level analysis of drought policies and impacts in Rajasthan, India, Working paper 93, Drought Series. Paper 6, International Water Management Institute, India
Reich P, Eswaran H (2004) Soil and trouble. Science 304:1614–1615
Rosenberg NJ (1979) Drought in the Great Plains—research on impacts and strategies. In: Proceedings of the workshop on research in Great Plains drought management strategies, University of Nebraska, Lincoln, Water Resources Publications, Littleton, Colorado, 225p, 26–28 Mar 1979
Rouse JW et al (1974) Monitoring the vernal advancement and retrogradation (greenwave effect) of natural vegetation. NASA/GSFCT Type III Final report. Greenbelt, MD, USA
Shahabfar A, Eitzinger J (2011) Agricultural drought monitoring in semi-arid and arid areas using MODIS data. J Agric Sci 149:403–414
Singh RP, Roy S, Kogan F (2003) Vegetation and temperature condition indices from NOAA-AVHRR data for drought monitoring over India. Int J Remote Sens 24(22):4393–4402
Smakhtin VU, Hughes DA (2004) Review, automated estimation and analyses of drought indices in South Asia, IWMI Working Paper N 83—Drought Series Paper N 1. IWMI: Colombo, p 24
Szalai S, Szinell C (2000) Comparison of two drought indices for drought monitoring in Hungary—a case study. In: Vogt JV, Somma F (eds) Drought and drought mitigation in Europe. Kluwer, Dordrecht, pp 161–166
Tabrizi AA, Khalili D, Kamgar-Haghighi AA, Zand-Parsa SH (2010) Utilization of time-based meteorological droughts to investigate occurrence of streamflow droughts. Water Resour Manage 24:4287–4306
Tallaksen LM, Van Lanen HAJ (eds) (2004) Hydrological drought—processes and estimation methods for streamflow and groundwater. In: Developments in water sciences, vol 48, Elsevier B.V., Amsterdam
Tate EL, Gustard A (2000) Drought definition: a hydrological perspective. In: Vogt JV, Somma F (eds) Drought and drought mitigation in Europe. Kluwer Academic Publishers, Dordrecht, pp 23–48
Thavorntam W, Mongkolsawat C (2006) Drought assessment and mitigation through GIS and remote sensing
Tsakiris G (2010) Towards an adaptive preparedness framework for facing drought and water shortage. Economic of drought and drought preparedness in climate change context. Options Méditerranéennes, no 95
Tsakiris G, Tigkas D, Vangelis H, Pangalou D (2007) Regional drought identification and assessment—case study in Crete. In: Rossi G, Vega T, Bonaccorso B (eds) Methods and tools for drought analysis and management. Springer, The Netherlands, pp 169–191
Tsakiris G, Spiliotis M (2011) Planning against long term water scarcity: a fuzzy multicriteria approach. Water Resour Manage 25(4):1103–1129
Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150
United Nations Development Programme UNDP (2010) Drought impact assessment, recovery and mitigation framework and regional project design in Kurdistan region (KR), Dec 2010
URL: http://www.gisdevelopment.net/application/natural_hazards/drought/ma
USDA foreign agricultural service (2008) IRAQ: drought reduces 2008/09 winter grain production. Commodity Intelligence Report, 9 May 2008
Vicente-Serrano SM, López-Moreno J I (2005) Hydrological response to different time scales of climatological drought: an evaluation of the standardized precipitation index in a Mountainous Mediterranean Basin. Hydrol Earth Syst Sci Discussions 2:1221–1246
Wessels KJ, Prince SD, Frost PE, Van Zyl D (2004) Assessing the effects of human-induced land degradation in the former homelands of northern South Africa with a 1 km AVHRR NDVI time-series. Remote Sens Environ 5(9):47–67
Wilhite DA (2009) Defining drought: the challenges for early warning systems. In: Inter-regional workshop on indices and early warning systems for drought, Nebraska-USA
Wilhite DA, Glanz MH (1985) Understanding the drought phenomenon: the role of definitions. Water Int 10(3):111–120
World Meteorological Organization WMO (2006) Drought monitoring and early warning: concepts, progress and future challenges. WMO-No. 1006
Wu H, Hayes MJ, Welss AHUQ (2001) An evaluation the standardized precipitation index, the china-z index and the statistical z-score. Int J Climatol 21:745–758
Wuest M, Bresch D, Corti T (2011) The hidden risks of climate change: an increase in property damage from soil subsidence in Europe. Swiss Reinsurance Company Ltd. Zurich, Switzerland. http://www.fao.org/ag/agl/aglw/aquastat/main/index.stm
Xue J, Su B (2017) Significant remote sensing vegetation indices: a review of developments and applications. Hindawi J Sens 2017 (Article ID 135691)
Yagci AL, Deng M (2014) The influence of land cover-related changes on the NDVI-based satellite agricultural drought indices. In: 2014 IEEE international geoscience and remote sensing symposium (IGRASS). IEEE, pp 2054–2057
Yan W, Yang L, Merchant JM (1998) An assessment of AVHRR/NDVI ecoclimatological relations in Nebraska, USA. Int J Remote Sens 18(10):2161–2180
Yunjun Y, Qin Q, Fadhil AM, Li Y, Zhao S, Liu S, Sui X, Dong H (2011) Evaluation of EDI derived from the exponential evapotranspiration model for monitoring China’s surface drought. Environ Earth Sci 63(2):425–436
Yevjevich V, Hall WA, Salas JD (1977) Drought research needs. In: Proceedings of the conference on drought research needs, Colorado State University, Fort Collins, Colorado, 276 p, 12–15 Dec 1977
Zhang Z, Kang H, Yao Y, Fadhil AM, Zhang Y, Jia K (2017) Spatial and decadal variations in satellite-based terrestrial evapotranspiration and drought over inner Mongolia autonomous region of China during 1982–2009. J Earth Syst Sci 126(8)
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Al-Hedny, S.M., Muhaimeed, A.S. (2020). Drought Monitoring for Northern Part of Iraq Using Temporal NDVI and Rainfall Indices. In: Al-Quraishi, A., Negm, A. (eds) Environmental Remote Sensing and GIS in Iraq. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-030-21344-2_13
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