Joint Modelling of Drought Severity and Duration using Copula Theory: A Case Study of Ghana
Tóm tắt
Analysing and understanding the occurrence and development of droughts is of great significance in mitigating drought impacts. This study assessed the possible changes in the joint distribution of drought duration and severity in two major cities of Ghana, Accra and Yendi. The duration and severity of droughts, estimated using the Standardized Precipitation Index (SPI), were determined based on run theory. The best-fitted Copula models were used to combine the drought duration and severity to analyse the drought return period. The gamma, lognormal and Weibull distributions were considered to select the marginal distributions for the duration and severity, while the normal, t, Gumbel, Joe, Clayton and Frank copulas to select the best-fit Copula model. Bias corrected climate simulations of six Global Climate Models (GCMs) of the CMIP6 were used to project drought characteristics for the near and far futures. The results showed the Clayton and Frank copulas as the most suitable for fitting the joint distribution of drought duration and severity at Accra and Yendi, respectively. Lognormal and Weibull distributions were the most suitable for the marginal distributions of severity and duration, respectively. The joint return periods of droughts showed almost no change in the future compared to the historical period in Accra with a historical mean of 11.36 and a near and far future mean of 12.26 and 10.30 respectively but significantly reduced return periods in the future in Yendi with a near and far future means of 1.47 and 2.13 respectively compared to a historical mean of 17.40. The drought risks estimated for different future periods can provide useful information in planning, management, and assessing the adequacy of the water structures in the region.
Tài liệu tham khảo
Ajayi V, Llori W (2020) Projected drought events over West Africa using RCA4 regional climate model. Earth Systems and Environment 4(2):2–18, DOI: https://doi.org/10.1007/s41748-020-00153-x
Akhtar M, Ahmad N, Booij MJ (2008) The impact of climate change on the water resources of Hindukush-Karakorum-Himalaya region under different glacier coverage scenarios. Journal of Hydrology 355:2–16, DOI: https://doi.org/10.1016/j.jhydrol.2008.03.015
Alamgir M, Mohsenipour M, Homsi R, Wang X, Shahid S, Shiru MS, Alias NE, Yuzir A (2019) Parametric assessment of seasonal drought risk to crop production in bangladesh. Sustainability 11:1442, DOI: https://doi.org/10.3390/su11051442
Ayantobo OO, Li Y, Song S, Javed T, Yao N (2018) Probabilistic modelling of drought events in China via2-dimensional joint copula. Journal of Hydrology 559:373–391, DOI: https://doi.org/10.1016/j.jhydrol.2018.02.022
Bambangi S (2007) Population and socioeconomic development in Ghana: Socioeconomic development or population management?. Ghana Journal of Development Studies 4:6–11, DOI: https://doi.org/10.4314/gjds.v4i1.35049
Ganguli P, Reddy MJ (2012) Risk assessment of droughts in Gujarat Using bivariate copulas. Water Resource Management 26:3301–3327, DOI: https://doi.org/10.1007/s11269-012-0073-6
Genest C, Favre A (2007) Everything you always wanted to know about copula modelling but were afraid to ask. Journal of Hydrology 12:347–368, DOI: https://doi.org/10.1061/(ASCE)1084-0699
Hartmann H, Ziegler W, Kolle O, Trumbore S (2013) Thirst beats hunger-declining hydration during drought prevents carbon starvation in Norway spruce saplings. New Phytologist 200:340–349, DOI: https://doi.org/10.1111/nph.12331
Hay LE, Wilby RL, Leavesley GH (2000) A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. Journal of the American Water Resources Association 36(2):387–397, DOI: https://doi.org/10.1111/j.1752-1688.2000.tb04276.x
Hui-Mean F, Yusof F, Yusop Z, Suhaila J (2019) Trivariate copula in drought analysis: A case study in peninsular Malaysia. Theoretical and Applied Climatology 138:65–671, DOI: https://doi.org/10.1007/s00704-019-02847-3
International Panel on Climate Change (IPCC) (2013) The physical science basis. contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC) In: Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535
Karavitis CA, Alexandris DE, Tsesmelis and Athanasopoulos (2011) Application of the standardized precipitation index (SPI) in Greece. Water 3:787–805, DOI: https://doi.org/10.3390/w3030787
Khan N, Sachindra D, Shahid S, Ahmed K, Shiru MS, Nawaz N (2020) Prediction of droughts over Pakistan using machine learning algorithms. Advances in Water Resources 139:103562, DOI: https://doi.org/10.1016/j.advwatres.2020.103562
Lee T, Modarres R, Ouarda TBMJ (2013) Data-based analysis of bivariate copula tail dependence for drought duration and severity. Hydrological Processes 27:1454–1463, DOI: https://doi.org/10.1002/hyp.9233
Massey FJ (1951) The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association 46:68–78, DOI: https://doi.org/10.2307/2280095
Mirabbasi R, Fakheri-Fard A, Dinpashoh Y (2012) Bivariate drought frequency analysis using the copula method. Theoretical and Applied Climatology 108:191–206, DOI: https://doi.org/10.1007/s00704-011-0524-7
Mishra AK, Singh VP (2010) A review of drought concepts. Journal of Hydrology 391:202–216, DOI: https://doi.org/10.1016/j.jhydrol.2010.07.012
Montaseri M, Amirataee B, Rezaie H (2018) New approach in bivariate drought duration and severity analysis. Journal of Hydrology 559: 166–181, DOI: https://doi.org/10.1016/j.jhydrol.2018.02.018
Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resource Management 23:881–897, DOI: https://doi.org/10.1007/s11269-008-9305-1
Piani C, Weedon GP, Best M, Gomes SM, Viterbo P, Hagemann S, Haerter JO (2010) Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. Journal of Hydrology 395:199–215, DOI: https://doi.org/10.1016/j.jhydrol.2010.10.024
Requena AI, Mediero L, Garrote L (2013) Bivariate return period based on copulas for hydrologic dam design: Comparison of theoretical and empirical approach. Hydrology and Earth System Sciences Discussions 10:557–596, DOI: https://doi.org/10.5194/hessd-10-557-2013
Saghafian B, Mehdikhani H (2014) Drought characterization using a new copula-based trivariate approach. Natural Hazards 72:1391–1407, DOI: https://doi.org/10.1007/s11069-013-0921-6
Sehgal V, Lakhanpal A, Maheswaran R, Khosa R, Sridhar V (2018) Application of multi-scale wavelet entropy and multi-resolution volterra models for climatic downscaling. Journal of Hydrology 55: 1078–1095, DOI: https://doi.org/10.1016/j.jhydrol.2016.10.048
Shiau JT (2006) Fitting drought duration and severity with two-dimensional copulas. Water Resource Management 20:795–815, DOI: https://doi.org/10.1007/s11269-005-9008-9
Shiau JT, Modarres R (2009) Copula-based drought severity-duration-frequency analysis in Iran. Meteorological Applications 16:481–489, DOI: https://doi.org/10.1002/met.145
Shiru MS, Shahid S, Alias N, Chung ES (2018) Trend analysis of droughts during crop growing seasons of Nigeria. Sustainability 10(3):871, DOI: https://doi.org/10.3390/su10030871
Shiru MS, Shahid S, Chung ES, Alias N, Scherer L (2019) An MCDM-based framework for selection of general circulation models and projection of spatio-temporal rainfall changes: A case study of Nigeria. Atmospheric Research 225:1–16, DOI: https://doi.org/10.1016/j.atmosres.2019.03.033
Sklar A (1959) Fonctions de repartition an dimensions et leurs marges. Publications de l’institut statistique de l’Universite de Paris: Paris, France 8:229–231
Song YH, Chung ES, Shahid S (2021) Spatiotemporal differences and uncertainties in projections of precipitation and temperature in South Korea from CMIP6 and CMIP5 general circulation models. International Journal of Climatology 41(13):5899–5919, DOI: https://doi.org/10.1002/joc.7159
Song YH, Chung ES, Shahid S (2022) Differences in multi-model ensembles of CMIP5 and CMIP6 projections for future droughts in South Korea. International Journal of Climatology 42(5):2688–2716, DOI: https://doi.org/10.1002/joc.7386
Sun FB, Roderick ML, Lim WH, Farquhar GD (2011) Hydro climatic projections for the Murray-Darling Basin based on an ensemble derived from Intergovernmental Panel on Climate Change AR4 climate models. Water Resources 47:2–20, DOI: https://doi.org/10.1029/2010WR009829
Sung JH, Ryu Y, Chung ES (2022) Multivariate frequency analysis for streamflow drought having different time resolution using archimedean copula functions. KSCE Journal of Civil Engineering 26(4):2013–2021, DOI: https://doi.org/10.1007/s12205-022-1634-8
Sylla MB, Nikiema PM, Gibba P, Kebe I, Klutse NAB (2016) Climate change over west africa: Recent trends and future projections. In Adaptation to Climate Change and Variability in Rural West Africa; Yaro, J.A., Hesselberg, J., (eds). Springer International Publishing: Berlin/Heidelberg, Germany 3:25–40
Twisa S, Manfred FB (2019) Seasonal and annual rainfall variability and their impact on rural water supply services in the Wami River Basin, Tanzania. Water 11(10):2055, DOI: https://doi.org/10.3390/w11102055
Yevjevich V (1967) Objective approach to definitions and investigations of continental hydrologic droughts. Hydrology Papers 23; Colorado State University: Fort Collins, CO, USA
Yusof F, Hui-Mean F, Suhaila J, Yusof Z (2013) Characterisation of drought properties with bivariate copula analysis. Water Resource Management 27:4183–4207, DOI: https://doi.org/10.1007/s11269-013-0402-4
Wang L, Zhang X, Wang S, Salahou MK, Fang Y (2020) Analysis and Application of Drought Characteristics Based on Theory of Runs and Copulas in Yunnan, Southwest China. International Journal of Environmental Research and Public Health 28;17(13):4654, DOI: https://doi.org/10.3390/ijerph17134654