Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data
2.2. Methodology
2.2.1. Standardized Precipitation Evapotranspiration Index
2.2.2. Drought Characteristics
- Spatial extent of drought
- Trends of drought intensity
- Frequency of drought (number of drought events)
- Duration of drought
3. Results
3.1. Spatial Extent of Drought
3.2. Trends of Drought Intensity
3.3. Frequency of Drought
3.4. Duration of Drought
4. Discussion
5. Conclusions
- A drying trend is detected over Iraq with severe to extreme drought conditions governing the first decade of the 21st century.
- The worst drought condition has occurred during 2007–2008 when severe and extreme drought covered about 25% and 60% of Iraq, respectively.
- The intensity of drought has exacerbated during the past decades, with the most aggravation happening in the central regions of Iraq.
- Droughts are found to be more frequent but shorter at the western, central and southeastern parts of Iraq.
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Van Loon, A.F.; Ploum, S.W.; Parajka, J.; Fleig, A.K.; Garnier, E.; Laaha, G.; van Lanen, H.A.J. Hydrological drought typology: Temperature-related drought types and associated societal impacts. Hydrol. Earth Syst. Sci. Discuss. 2014, 11, 10465–10514. [Google Scholar] [CrossRef]
- Amin, M.T.; Mahmoud, S.H.; Alazba, A.A. Observations, projections and impacts of climate change on water resources in Arabian Peninsula: Current and future scenarios. Environ. Earth Sci. 2016, 75, 1–17. [Google Scholar] [CrossRef]
- Ahmadalipour, A.; Moradkhani, H.; Yan, H.; Zarekarizi, M. Remote Sensing of Drought: Vegetation, Soil Moisture and Data Assimilation, Remote Sensing of Hydrological Extremes. In Remote Sensing of Hydrological Extremes; Springer International Publishing: Basel Switzerland, 2017; pp. 121–149. [Google Scholar]
- FAO. Drought Characteristics and Management in Central Asia and Turkey; Food and Agriculture Organization of the United Nations: Rome, Italy, 2017. [Google Scholar]
- Scanlon, B.R.; Ruddell, B.L.; Reed, P.M.; Hook, R.I.; Zheng, C.; Tidwell, V.C.; Siebert, S. The food-energy-water nexus: Transforming science for society. Water Resour. Res. 2017, 53, 3550–3556. [Google Scholar] [CrossRef]
- United Nations Development Programme (UNDP). Impact Assessment, Recovery and Mitigation Framework and Regional Project Design in Kurdistan Region (KR); UNDP: Baghdad, Iraq, 2010; p. 78. [Google Scholar]
- Ahmadalipour, A.; Moradkhani, H. Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment. J. Hydrol. 2017, 555, 557–568. [Google Scholar] [CrossRef]
- Beguería, S.; Vicente-Serrano, S.M.; Reig, F.; Latorre, B. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int. J. Climatol. 2014, 34, 3001–3023. [Google Scholar] [CrossRef]
- Das, P.K.; Dutta, D.; Sharma, J.R.; Dadhwal, V.K. Trends and behaviour of meteorological drought (1901–2008) over Indian region using standardized precipitation-evapotranspiration index. Int. J. Climatol. 2015, 36, 909–916. [Google Scholar] [CrossRef]
- Ahmadalipour, A.; Moradkhani, H.; Svoboda, M. Centennial drought outlook over the CONUS using NASA-NEX downscaled climate ensemble. Int. J. Climatol. 2017, 37, 2477–2491. [Google Scholar] [CrossRef]
- Gao, Z.; Xu, N.; Fu, C.; Ning, J. Evaluating Drought Monitoring Methods Using Remote Sensing: A Dynamic Correlation Analysis between Heat Fluxes and Land Cover Patterns. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 8, 298–303. [Google Scholar] [CrossRef]
- Mishra, A.K.; Ines, A.V.M.; Das, N.N.; Prakash Khedun, C.; Singh, V.P.; Sivakumar, B.; Hansen, J.W. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study. J. Hydrol. 2015, 526, 15–29. [Google Scholar] [CrossRef]
- Nichol, J.E.; Abbas, S. Integration of remote sensing datasets for local scale assessment and prediction of drought. Sci. Total Environ. 2015, 505, 503–507. [Google Scholar] [CrossRef] [PubMed]
- Vicente-Serrano, S.; Cabello, D.; Tomás-Burguera, M.; Martín-Hernández, N.; Beguería, S.; Azorin-Molina, C.; Kenawy, A. Drought Variability and Land Degradation in Semiarid Regions: Assessment Using Remote Sensing Data and Drought Indices (1982–2011). Remote Sens. 2015, 7, 4391–4423. [Google Scholar] [CrossRef]
- Yan, H.; Moradkhani, H.; Zarekarizi, M. A probabilistic drought forecasting framework: A combined dynamical and statistical approach. J. Hydrol. 2017, 548, 291–304. [Google Scholar] [CrossRef]
- Madadgar, S.; Moradkhani, H. A Bayesian Framework for Probabilistic Seasonal Drought Forecasting. J. Hydrometeorol. 2013, 14, 1685–1705. [Google Scholar] [CrossRef]
- Lorenzo-Lacruz, J.; Vicente-Serrano, S.M.; González-Hidalgo, J.C.; López-Moreno, J.I.; Cortesi, N. Hydrological drought response to meteorological drought in the Iberian Peninsula. Clim. Res. 2013, 58, 117–131. [Google Scholar] [CrossRef]
- Barker, L.J.; Hannaford, J.; Chiverton, A.; Svensson, C. From meteorological to hydrological drought using standardised indicators. Hydrol. Earth Syst. Sci. 2016, 20, 2483–2505. [Google Scholar] [CrossRef]
- Van Loon, A.F.; Laaha, G. Hydrological drought severity explained by climate and catchment characteristics. J. Hydrol. 2015, 526, 3–14. [Google Scholar] [CrossRef]
- Ahmadalipour, A.; Moradkhani, H.; Demirel, M.C. A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature. J. Hydrol. 2017, 553, 785–797. [Google Scholar] [CrossRef]
- Zhang, B.; Zhao, X.; Jin, J.; Wu, P. Development and evaluation of a physically based multiscalar drought index: The Standardized Moisture Anomaly Index. J. Geophys. Res. Atmos. 2015, 120, 11575–11588. [Google Scholar] [CrossRef]
- Mo, K.C.; Lettenmaier, D.P. Objective Drought Classification Using Multiple Land Surface Models. J. Hydrometeorol. 2014, 15, 990–1010. [Google Scholar] [CrossRef]
- Rajsekhar, D.; Singh, V.P.; Mishra, A.K. Integrated drought causality, hazard, and vulnerability assessment for future socioeconomic scenarios: An information theory perspective. J. Geophys. Res. Atmos. 2015, 120, 6346–6378. [Google Scholar] [CrossRef]
- Maia, R.; Vivas, E.; Serralheiro, R.; de Carvalho, M. Socioeconomic Evaluation of Drought Effects. Main Principles and Application to Guadiana and Algarve Case Studies. Water Resour. Manag. 2015, 29, 575–588. [Google Scholar] [CrossRef]
- Huang, S.; Huang, Q.; Leng, G.; Liu, S. A nonparametric multivariate standardized drought index for characterizing socioeconomic drought: A case study in the Heihe River Basin. J. Hydrol. 2016, 542, 875–883. [Google Scholar] [CrossRef]
- Carrão, H.; Singleton, A.; Naumann, G.; Barbosa, P.; Vogt, J.V. An optimized system for the classification of meteorological drought intensity with applications in drought frequency analysis. J. Appl. Meteorol. Climatol. 2014, 53, 1943–1960. [Google Scholar] [CrossRef]
- Deo, R.C.; Byun, H.-R.; Adamowski, J.F.; Begum, K. Application of effective drought index for quantification of meteorological drought events: A case study in Australia. Theor. Appl. Climatol. 2016. [Google Scholar] [CrossRef]
- Madadgar, S.; Moradkhani, H. Drought Analysis under Climate Change Using Copula. J. Hydrol. Eng. 2013, 18, 746–759. [Google Scholar] [CrossRef]
- Cook, B.I.; Smerdon, J.E.; Seager, R.; Coats, S. Global warming and 21st century drying. Clim. Dyn. 2014, 43, 2607–2627. [Google Scholar] [CrossRef]
- Dai, A. Drought under global warming: A review. Wiley Interdiscip. Rev. Clim. Chang. 2011, 2, 45–65. [Google Scholar] [CrossRef]
- Mishra, A.K.; Singh, V.P. A review of drought concepts. J. Hydrol. 2010, 391, 202–216. [Google Scholar] [CrossRef]
- Palmer, W.C. Meteorological Drought; US Department of Commerce: Washington, DC, USA, 1965.
- McKee, T.B.; Doeskin, N.J.; Kleist, J. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, Anaheim, CA, USA, 17–22 January 1993; pp. 179–184. [Google Scholar]
- Vicente-Serrano, S.M.; Beguería, S.; López-Moreno, J.I. A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Clim. 2010, 23, 1696–1718. [Google Scholar] [CrossRef] [Green Version]
- Dutra, E.; Wetterhall, F.; Di Giuseppe, F.; Naumann, G.; Barbosa, P.; Vogt, J.; Pozzi, W.; Pappenberger, F. Global meteorological drought-Part 1: Probabilistic monitoring. Hydrol. Earth Syst. Sci. 2014, 18, 2657–2667. [Google Scholar] [CrossRef]
- Mo, K.C.; Lyon, B. Global Meteorological Drought Prediction Using the North American Multi-Model Ensemble. J. Hydrometeorol. 2015, 16, 1409–1424. [Google Scholar] [CrossRef]
- Zhao, T.; Dai, A. The magnitude and causes of global drought changes in the twenty-first century under a low–moderate emissions scenario. J. Clim. 2015, 28, 4490–4512. [Google Scholar] [CrossRef]
- Stagge, J.; Tallaksen, L. Standardized precipitation-evapotranspiration index (SPEI): Sensitivity to potential evapotranspiration model and parameters. Int. Assoc. Hydrol. Sci. 2014, 10, 367–373. [Google Scholar]
- Hoerling, M.; Eischeid, J.; Perlwitz, J.; Quan, X.; Zhang, T.; Pegion, P. On the increased frequency of mediterranean drought. J. Clim. 2012, 25, 2146–2161. [Google Scholar] [CrossRef]
- Gleick, P.H. Water, Drought, Climate Change, and Conflict in Syria. Weather Clim. Soc. 2014, 6, 331–340. [Google Scholar] [CrossRef]
- Lelieveld, J.; Hadjinicolaou, P.; Kostopoulou, E.; Chenoweth, J.; El Maayar, M.; Giannakopoulos, C.; Hannides, C.; Lange, M.A.; Tanarhte, M.; Tyrlis, E.; et al. Climate change and impacts in the Eastern Mediterranean and the Middle East. Clim. Chang. 2012, 114, 667–687. [Google Scholar] [CrossRef] [PubMed]
- United Nations Educational, Scientific and Cultural Organization (UNESCO). Integrated Drought Risk Management—DRM (National Framework for Iraq); UNESCO: London, UK, 2014. [Google Scholar]
- Al-Faraj, F.A.M.; Al-Dabbagh, B.N.S. Assessment of collective impact of upstream watershed development and basin-wide successive droughts on downstream flow regime: The Lesser Zab transboundary basin. J. Hydrol. 2015, 530, 419–430. [Google Scholar] [CrossRef]
- Amini, A.; Zareie, S.; Taheri, P.; Bin, K.; Yusof, W.; Raza, M. Drought analysis and water resources management inspection in Euphrates-Tigris basin. In River Basin Management; InTech: London, UK, 2016. [Google Scholar] [CrossRef]
- Eklund, L.; Seaquist, J. Meteorological, agricultural and socioeconomic drought in the Duhok Governorate, Iraqi Kurdistan. Nat. Hazards 2015, 76, 421–441. [Google Scholar] [CrossRef]
- AL-Timimi, Y.K.; AL-Jiboori, M.H. Assessment of spatial and temporal drought in Iraq during the period 1980–2010. Int. J. Energy Environ. 2013, 2, 653–660. [Google Scholar]
- Robaa, S.M.; Al-Barazanji, Z.J. Trends of annual mean surface air temperature over Iraq. Nat. Sci. 2013, 11, 138–145. [Google Scholar]
- Thornthwaite, C.W. An Approach toward a Rational Classification of Climate. Geogr. Rev. 1948, 38, 55–94. [Google Scholar] [CrossRef]
- The World Bank. Iraq—Country Water Resource Assistance Strategy: Addressing Major Threats to People’s Livelihoods; World Bank: Washington, DC, USA, 2006; pp. 1–97. [Google Scholar]
- Rodell, M.; Beaudoing, H. GLDAS Noah Land Surface Model L4 Monthly 0.25 × 0.25 Degree V2.0. Available online: https://disc.sci.gsfc.nasa.gov/datasets/GLDAS_NOAH025_M_V020/summary (accessed on 10 December 2017).
- Stagge, J.H.; Kohn, I.; Tallaksen, L.M.; Stahl, K. Modeling drought impact occurrence based on meteorological drought indices in Europe. J. Hydrol. 2015, 530, 37–50. [Google Scholar] [CrossRef]
- Allen, R.G.; Pruitt, W.O.; Wright, J.L.; Howell, T.A.; Ventura, F.; Snyder, R.; Itenfisu, D.; Steduto, P.; Berengena, J.; Yrisarry, J.B.; et al. A recommendation on standardized surface resistance for hourly calculation of reference ETo by the FAO56 Penman-Monteith method. Agric. Water Manag. 2006, 81, 1–22. [Google Scholar] [CrossRef]
- Priestley, C. H.B.; Taylor, R.J. On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters. Mon. Weather Rev. 1972, 100, 81–92. [Google Scholar] [CrossRef]
- Hargreaves, G.H.; Samani, Z.A. Reference crop evapotranspiration from temperature. Appl. Eng. Agric. 1985, 1, 96–99. [Google Scholar] [CrossRef]
- Colaizzi, P.D.; Agam, N.; Tolk, J.A.; Evett, S.R.; Howell, T.A.; Gowda, P.H.; Kustas, W.P.; Anderson, M.C. Two-Source Energy Balance Model to Calculate E, T, and ET: Comparison of Priestley-Taylor and Penman-Monteith Formulations and Two Time Scaling Methods. Trans. ASABE 2014, 57, 479–498. [Google Scholar] [CrossRef]
- Mavromatis, T. Drought index evaluation for assessing future wheat production in Greece. Int. J. Climatol. 2007, 27, 911–924. [Google Scholar] [CrossRef]
- Dai, A. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900–2008. J. Geophys. Res. Atmos. 2011, 116. [Google Scholar] [CrossRef]
- Vangelis, H.; Tigkas, D.; Tsakiris, G. The effect of PET method on Reconnaissance Drought Index (RDI) calculation. J. Arid Environ. 2013, 88, 130–140. [Google Scholar] [CrossRef]
- Mohammed, R.; Scholz, M. Impact of Evapotranspiration Formulations at Various Elevations on the Reconnaissance Drought Index. Water Resour. Manag. 2017, 31, 531–548. [Google Scholar] [CrossRef]
- Willmott, C.J.; Rowe, C.M.; Mintz, Y. Climatology of the terrestrial seasonal water cycle. J. Climatol. 1985, 5, 589–606. [Google Scholar] [CrossRef]
- Caporusso, N.B.; Rolim, G.D.S. Reference evapotranspiration models using different time scales in the Jaboticabal region of São Paulo, Brazil. Acta Sci. Agron. 2015, 37, 1–9. [Google Scholar] [CrossRef]
- Hulme, M.; Marsh, R.; Jones, P.D. Global changes in a humidity index between 1931–60 and 1961–90. Clim. Res. 1992, 2, 1–22. [Google Scholar] [CrossRef]
- Stagge, J.H.; Tallaksen, L.M.; Gudmundsson, L.; Van Loon, A.F.; Stahl, K. Candidate Distributions for Climatological Drought Indices (SPI and SPEI). Int. J. Climatol. 2015, 35, 4027–4040. [Google Scholar] [CrossRef]
- Touma, D.; Ashfaq, M.; Nayak, M.A.; Kao, S.-C.; Diffenbaugh, N.S. A multi-model and multi-index evaluation of drought characteristics in the 21st century. J. Hydrol. 2015, 526, 196–207. [Google Scholar] [CrossRef]
- Huang, S.; Huang, Q.; Chang, J.; Zhu, Y.; Leng, G.; Xing, L. Drought structure based on a nonparametric multivariate standardized drought index across the Yellow River basin, China. J. Hydrol. 2015, 530, 127–136. [Google Scholar] [CrossRef]
- Makkonen, L. Plotting positions in extreme value analysis. J. Appl. Meteorol. Climatol. 2006, 45, 334–340. [Google Scholar] [CrossRef]
- Weibull, W. A statistical theory of the strength of materials. R. Swed. Inst. Eng. Res. 1939, 151, 1–45. [Google Scholar]
- Van Loon, A.F. Hydrological drought explained. Wiley Interdiscip. Rev. Water 2015, 2, 359–392. [Google Scholar] [CrossRef]
- McEvoy, D.J.; Huntington, J.L.; Abatzoglou, J.T.; Edwards, L.M. An evaluation of multiscalar drought indices in Nevada and Eastern California. Earth Interact. 2012, 16, 1–18. [Google Scholar] [CrossRef]
- Shubbar, R.M.; Salman, H.H.; Lee, D.I. Characteristics of climate variation indices in Iraq using a statistical factor analysis. Int. J. Climatol. 2016, 37, 918–927. [Google Scholar] [CrossRef]
- Al-Faraj, F.A.M.; Tigkas, D. Impacts of Multi-year Droughts and Upstream Human-Induced Activities on the Development of a Semi-arid Transboundary Basin. Water Resour. Manag. 2016, 30, 5131–5143. [Google Scholar] [CrossRef]
- Longuevergne, L.; Wilson, C.R.; Scanlon, B.R.; Crétaux, J.F. GRACE water storage estimates for the middle east and other regions with significant reservoir and lake storage. Hydrol. Earth Syst. Sci. 2013, 17, 4817–4830. [Google Scholar] [CrossRef] [Green Version]
- Voss, K.A.; Famiglietti, J.S.; Lo, M.; De Linage, C.; Rodell, M.; Swenson, S.C. Groundwater depletion in the Middle East from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region. Water Resour. Res. 2013, 49, 904–914. [Google Scholar] [CrossRef] [PubMed]
Category | SPEI Values |
---|---|
(min–max) | |
Extremely dry | Less than −2 |
Severe dry | −1.99 to −1.5 |
Moderate dry | −1.49 to −1.0 |
Near normal | −1.0 to 1.0 |
Moderate wet | 1.0 to 1.49 |
Severe wet | 1.50 to 1.99 |
Extremely wet | More than 2 |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Hameed, M.; Ahmadalipour, A.; Moradkhani, H. Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment. Geosciences 2018, 8, 58. https://doi.org/10.3390/geosciences8020058
Hameed M, Ahmadalipour A, Moradkhani H. Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment. Geosciences. 2018; 8(2):58. https://doi.org/10.3390/geosciences8020058
Chicago/Turabian StyleHameed, Maysoun, Ali Ahmadalipour, and Hamid Moradkhani. 2018. "Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment" Geosciences 8, no. 2: 58. https://doi.org/10.3390/geosciences8020058
APA StyleHameed, M., Ahmadalipour, A., & Moradkhani, H. (2018). Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment. Geosciences, 8(2), 58. https://doi.org/10.3390/geosciences8020058