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Ranking of gridded precipitation datasets by merging compromise programming and global performance index: a case study of the Amu Darya basin

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Abstract

Accurate representation of precipitation over time and space is vital for hydro-climatic studies. Appropriate selection of gridded precipitation data (GPD) is important for regions where long-term in situ records are unavailable and gauging stations are sparse. This study was an attempt to identify the best GPD for the data-poor Amu Darya River basin, a major source of freshwater in Central Asia. The performance of seven GPDs and 55 precipitation gauge locations was assessed. A novel algorithm, based on the integration of a compromise programming index (CPI) and a global performance index (GPI) as part of a multi-criteria group decision-making (MCGDM) method, was employed to evaluate the performance of the GPDs. The CPI and GPI were estimated using six statistical indices representing the degree of similarity between in situ and GPD properties. The results indicated a great degree of variability and inconsistency in the performance of the different GPDs. The CPI ranked the Climate Prediction Center (CPC) precipitation as the best product for 20 out of 55 stations analysed, followed by the Princeton University Global Meteorological Forcing (PGF) and Climate Hazards Group Infrared Precipitation with Station (CHIRPS). Conversely, GPI ranked the CPC product the best product for 25 of the stations, followed by PGF and CHRIPS. Integration of CPI and GPI ranking through MCGDM revealed that the CPC was the best precipitation product for the Amu River basin. The performance of PGF was also closely aligned with that of CPC.

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References

  • Ahmad M, Wasiq M (2004). Water resource development in Northern Afghanistan and its implications for Amu Darya Basin: The World Bank

  • Ahmed K, Shahid S, bin Harun S, Wang X-j (2016) Characterization of seasonal droughts in Balochistan Province, Pakistan. Stoch Env Res Risk A 30(2):747–762

    Article  Google Scholar 

  • Ahmed K, Shahid S, Ali R, Bin Harun S, Wang X (2017) Evaluation of the performance of gridded precipitation products over Balochistan Province, Pakistan. Desalin Water Treat 79:73–86 In

    Article  Google Scholar 

  • Ahmed K, Shahid S, Wang X, Nawaz N, Khan N (2019) Evaluation of gridded precipitation datasets over arid regions of Pakistan. Water 11(2):210

    Article  Google Scholar 

  • Babow S, Meisen P (2012). The Water-Energy Nexus in the Amu Darya River Basin: The Need for Sustainable Solutions to a Regional Problem. Global Energy Network Institute

  • Bai L, Shi C, Li L, Yang Y, Wu J (2018) Accuracy of CHIRPS satellite-rainfall products over mainland China. Remote Sens 10(3):362

    Article  Google Scholar 

  • Becker A, Finger P, Meyer-Christoffer A, Rudolf B, Schamm K, Schneider U, Ziese M (2012) A description of the global land-surface precipitation data products of the global precipitation climatology centre with sample applications including centennial (trend) analysis from 1901-present. ESSDD 5(2):921–998

    Google Scholar 

  • Behar O, Khellaf A, Mohammedi K (2015) Comparison of solar radiation models and their validation under Algerian climate–The case of direct irradiance. Energy Convers Manag 98:236–251

    Article  Google Scholar 

  • Beven K, Westerberg I (2011) On red herrings and real herrings: disinformation and information in hydrological inference. Hydrol Process 25(10):1676–1680

    Article  Google Scholar 

  • Bobushev T, Salnikov V (2014) The Impact of Global Climate Change on Environment (In Cause Of Water Use In Central Asia). Reforma 1(61):17–22

    Google Scholar 

  • Brahim HB, Duckstein L (2011). Descriptive methods and compromise programming for promoting agricultural reuse of treated wastewater. In Computational Methods for Agricultural Research: Advances and Applications (pp. 355-388): IGI Global

  • Chevallier P, Pouyaud B, Mojaïsky M, Bolgov M, Olsson O, Bauer M, and Froebrich J (2012). Trends for snow cover and river flows in the Pamirs (Central Asia). Earth Syst. Sci. Discuss 9:29–64. https://doi.org/10.5194/hessd-9-29-2012

  • Despotovic M, Nedic V, Despotovic D, Cvetanovic S (2015) Review and statistical analysis of different global solar radiation sunshine models. Renew Sust Energ Rev 52:1869–1880

    Article  Google Scholar 

  • Dodson J, Betts AV, Amirov S, Yagodin VN (2015) The nature of fluctuating lakes in the southern Amu-dar'ya delta. Palaeogeogr Palaeoclimatol Palaeoecol 437:63–73

    Article  Google Scholar 

  • Duan Z, Liu J, Tuo Y, Chiogna G, Disse M (2016) Evaluation of eight high spatial resolution gridded precipitation products in Adige Basin (Italy) at multiple temporal and spatial scales. Sci Total Environ 573:1536–1553

    Article  Google Scholar 

  • Duethmann D, Bolch T, Farinotti D, Kriegel D, Vorogushyn S, Merz B, Güntner A (2015) Attribution of streamflow trends in snow and glacier melt-dominated catchments of the T arim R iver, Central A sia. Water Resour Res 51(6):4727–4750

    Article  Google Scholar 

  • Erazo B, Bourrel L, Frappart F, Chimborazo O, Labat D, Dominguez-Granda L, Mejia R (2018) Validation of satellite estimates (Tropical Rainfall Measuring Mission, TRMM) for rainfall variability over the Pacific slope and Coast of Ecuador. Water 10(2):213

    Article  Google Scholar 

  • Fan J, Wang X, Wu L, Zhang F, Bai H, Lu X, Xiang Y (2018) New combined models for estimating daily global solar radiation based on sunshine duration in humid regions: A case study in South China. Energy Convers Manag 156:618–625

    Article  Google Scholar 

  • Froebrich J, Kayumov O (2004). Water management aspects of Amu Darya. In Dying and Dead Seas Climatic Versus Anthropic Causes (pp. 49-76): Springer

  • Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Hoell A (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci Data 2: sdata201566. In

  • Gampe D, Ludwig R (2017) Evaluation of gridded precipitation data products for hydrological applications in complex topography. Hydrology 4(4):53

    Article  Google Scholar 

  • Gampe D, Schmid J, Ludwig R (2019) Impact of reference dataset selection on RCM evaluation, bias correction, and resulting climate change signals of precipitation. J Hydrometeorol 20(9):1813–1828

    Article  Google Scholar 

  • Gao F, Zhang Y, Chen Q, Wang P, Yang H, Yao Y, Cai W (2018) Comparison of two long-term and high-resolution satellite precipitation datasets in Xinjiang, China. Atmos Res 212:150–157

    Article  Google Scholar 

  • Gaybullaev B, Chen S-C (2013) Water salinity changes of the gauging stations along the Amu Darya River. J Agric For 62(1):1–14

    Google Scholar 

  • Guo B, Zhang J, Meng X, Xu T, Song Y (2020) Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN. Sci Rep 10(1):1–17

    Google Scholar 

  • Haag I, Jones PD, Samimi C (2019) Central Asia’s changing climate: How temperature and precipitation have changed across time, space, and altitude. Climate 7(10):123

    Article  Google Scholar 

  • Ibrahimzada MW, Sharma D (2012) Vulnerability assessment of water resources in Amu Darya river basin, Afghanistan. Int J Environ Sci 3(2):802–812

    Google Scholar 

  • Immerzeel W, Lutz A, Droogers P (2012) Climate change impacts on the upstream water resources of the Amu and Syr Darya River basins. Wageningen, The Netherlands

    Google Scholar 

  • Jalilov S-M, Amer SA, Ward FA (2013) Reducing conflict in development and allocation of transboundary rivers. Eurasian Geogr Econ 54(1):78–109

    Article  Google Scholar 

  • Jamil B, Irshad K, Algahtani A, Islam S, Ali MA, Shahab A (2020) On the calibration and applicability of global solar radiation models based on temperature extremities in India. Environ Prog Sustain Energy 39(1):13236

    Article  Google Scholar 

  • Jiang S-j, Zhou M, Ren L-l, Cheng X-r, Zhang P-j (2016) Evaluation of latest TMPA and CMORPH satellite precipitation products over Yellow River Basin. Water Science and Engineering 9(2):87–96

    Article  Google Scholar 

  • Kamiguchi K, Arakawa O, Kitoh A, Yatagai A, Hamada A, Yasutomi N (2010) Development of APHRO_JP, the first Japanese high-resolution daily precipitation product for more than 100 years. Hydrological Research Letters 4:60–64

    Article  Google Scholar 

  • Khan N, Pour SH, Shahid S, Ismail T, Ahmed K, Chung ES, Wang X (2019) Spatial distribution of secular trends in rainfall indices of Peninsular Malaysia in the presence of long-term persistence. Meteorol Appl 26(4):655–670

    Article  Google Scholar 

  • Khaydarov M, Gerlitz L (2019) Climate variability and change over Uzbekistan–an analysis based on high resolution CHELSA data. Central Asian Journal of Water Research (CAJWR) Центральноазиатский журнал исследований водных ресурсов 5(2):1–19

    Article  Google Scholar 

  • Kidd C, Becker A, Huffman GJ, Muller CL, Joe P, Skofronick-Jackson G, Kirschbaum DB (2017) So, how much of the Earth’s surface is covered by rain gauges? Bull Am Meteorol Soc 98(1):69–78

    Article  Google Scholar 

  • Kure S, Jang S, Ohara N, Kavvas M, Chen Z (2013) Hydrologic impact of regional climate change for the snow-fed and glacier-fed river basins in the Republic of Tajikistan: Statistical downscaling of global climate model projections. Hydrol Process 27(26):4071–4090

    Article  Google Scholar 

  • Li D, Christakos G, Ding X, Wu J (2018) Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China). J Hydrol 556:1139–1152

    Article  Google Scholar 

  • Lioubimtseva E (2014). Impact of climate change on the Aral Sea and its basin. In The Aral Sea (pp. 405-427): Springer

  • Liu X, Yang T, Hsu K, Liu C, Sorooshian S (2017) Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau. Hydrol Earth Syst Sci 21(1):169–181

    Article  Google Scholar 

  • Lutz AF, Immerzeel WW, Gobiet A, Pellicciotti F, Bierkens MF (2013) Comparison of climate change signals in CMIP3 and CMIP5 multi-model ensembles and implications for Central Asian glaciers. Hydrol Earth Syst Sci 17(9):3661–3677

    Article  Google Scholar 

  • Malsy M, aus der Beek T, Flörke M (2015) Evaluation of large-scale precipitation data sets for water resources modelling in Central Asia. Environ Earth Sci 73(2):787–799

    Article  Google Scholar 

  • Matsuura K, Willmott C.J (2012). Terrestrial precipitation: 1900-2010 gridded monthly time series. WWW document] URL http://climate.geog.udel.edu/~climate/html_pages/Global2011/Precip_revised_3,2

  • Mergili M, Müller JP, Schneider JF (2013) Spatio-temporal development of high-mountain lakes in the headwaters of the Amu Darya River (Central Asia). Glob Planet Chang 107:13–24

    Article  Google Scholar 

  • Muhammad MKI, Nashwan MS, Shahid S, Ismail T b, Song YH, Chung E-S (2019) Evaluation of empirical reference evapotranspiration models using compromise programming: a case study of Peninsular Malaysia. Sustainability 11(16):4267

    Article  Google Scholar 

  • Mukherjee S, Mishra A, Trenberth KE (2018) Climate change and drought: a perspective on drought indices. Current Climate Change Reports 4(2):145–163

    Article  Google Scholar 

  • Musie M, Sen S, Srivastava P (2019) Comparison and evaluation of gridded precipitation datasets for streamflow simulation in data scarce watersheds of Ethiopia. J Hydrol 579:124168

    Article  Google Scholar 

  • Nashwan MS, Shahid S (2019) Symmetrical uncertainty and random forest for the evaluation of gridded precipitation and temperature data. Atmos Res 230:104632

    Article  Google Scholar 

  • Nashwan MS, Shahid S (2020) A novel framework for selecting general circulation models based on the spatial patterns of climate. Int J Climatol 40:4422–4443

    Article  Google Scholar 

  • Nashwan MS, Shahid S, Wang X (2019a) Assessment of satellite-based precipitation measurement products over the hot desert climate of Egypt. Remote Sens 11(5):555

    Article  Google Scholar 

  • Nashwan MS, Shahid S, Wang X (2019b) Uncertainty in estimated trends using gridded rainfall data: a case study of Bangladesh. Water 11(2):349

    Article  Google Scholar 

  • New M, Hulme M, Jones P (2000) Representing twentieth-century space–time climate variability. Part II: Development of 1901–96 monthly grids of terrestrial surface climate. J Clim 13(13):2217–2238

    Article  Google Scholar 

  • Nezlin NP, Kostianoy AG, Lebedev SA (2004) Interannual variations of the discharge of Amu Darya and Syr Darya estimated from global atmospheric precipitation. J Mar Syst 47(1-4):67–75

    Article  Google Scholar 

  • Normatov PI, Normatov IS (2018). Monitoring of Meteorological, Hydrological Conditions and Water Quality of the Main Tributaries of the Transboundary Amu Darya River. Achievements and Challenges of Integrated River Basin Management, 149

  • Novikov, V., Simonett, O., Beilstein, M., Bournay, E., Berthiaume, C., Kirby, A., Rajabov, I. (2009). Climate change in Central Asia—a visual synthesis. Swiss Federal Office for the environment (FOEN), Zoı Environment Network.

  • Punkari M, Droogers P, Immerzeel W, Korhonen N, Lutz A, Venäläinen A (2014). Climate change and sustainable water management in Central Asia

  • Raju KS, Sonali P, Kumar DN (2017) Ranking of CMIP5-based global climate models for India using compromise programming. Theor Appl Climatol 128(3-4):563–574

    Article  Google Scholar 

  • Rashid M, Shaofeng J, Zhu W (2019). Analysis of climate variability, trends, and prediction in the most active parts of the Lake Chad basin, Africa. Scientific Reports (Nature Publisher Group), 9(1)

  • Roca R, Alexander LV, Potter G, Bador M, Jucá R, Contractor S, Cloché S (2019) FROGS: a daily 1∘× 1∘ gridded precipitation database of rain gauge, satellite and reanalysis products. Earth System Science Data 11(3):1017–1035

    Article  Google Scholar 

  • Salman SA, Shahid S, Ismail T, Ahmed K, Wang X-J (2018) Selection of climate models for projection of spatiotemporal changes in temperature of Iraq with uncertainties. Atmos Res 213:509–522

    Article  Google Scholar 

  • Salman SA, Shahid S, Ismail T, Al-Abadi AM, Wang X-j, Chung E-S (2019) Selection of gridded precipitation data for Iraq using compromise programming. Measurement 132:87–98

    Article  Google Scholar 

  • Samal RK, Kansal ML (2015). Sustainable development contribution assessment of renewable energy projects using AHP and compromise programming techniques. Paper presented at the 2015 International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

  • Savoskul O, Shevnina E (2015) Irrigated crop production in the Syr Darya Basin: climate change rehearsal in the 1990s. Climate Change and Agricultural Water Management in Developing Countries 8:176

    Google Scholar 

  • Schneider U, Becker A, Finger P, Meyer-Christoffer A, Ziese M, Rudolf B (2014) GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor Appl Climatol 115(1-2):15–40

    Article  Google Scholar 

  • Shen Y, Xiong A (2016) Validation and comparison of a new gauge-based precipitation analysis over mainland China. Int J Climatol 36(1):252–265

    Article  Google Scholar 

  • Shibuo Y, Jarsjö J, Destouni G (2007) Hydrological responses to climate change and irrigation in the Aral Sea drainage basin. Geophys Res Lett 34(21)

  • Sun Q, Miao C, Duan Q, Ashouri H, Sorooshian S, Hsu KL (2018) A review of global precipitation data sets: Data sources, estimation, and intercomparisons. Rev Geophys 56(1):79–107

    Article  Google Scholar 

  • Tan X, Ma Z, He K, Han X, Ji Q, He Y (2020) Evaluations on gridded precipitation products spanning more than half a century over the Tibetan Plateau and its surroundings. J Hydrol 582:124455

    Article  Google Scholar 

  • Tanarhte M, Hadjinicolaou P, Lelieveld J (2012) Intercomparison of temperature and precipitation data sets based on observations in the Mediterranean and the Middle East. J Geophys Res Atmos 117(D12)

  • Tapiador F, Navarro A, Levizzani V, García-Ortega E, Huffman G, Kidd C, Petersen W (2017) Global precipitation measurements for validating climate models. Atmos Res 197:1–20

    Article  Google Scholar 

  • Törnqvist R (2013). Basin-scale change in water availability and water quality under intensified irrigated agriculture. Department of Physical Geography and Quaternary Geology, Stockholm University

  • Try S, Tanaka S, Tanaka K, Sayama T, Oeurng C, Uk S, Han D (2020) Comparison of gridded precipitation datasets for rainfall-runoff and inundation modeling in the Mekong River Basin. PLoS One 15(1):e0226814

    Article  Google Scholar 

  • Unger-Shayesteh K, Vorogushyn S, Farinotti D, Gafurov A, Duethmann D, Mandychev A, Merz B (2013) What do we know about past changes in the water cycle of Central Asian headwaters? A review. Glob Planet Chang 110:4–25

    Article  Google Scholar 

  • White CJ, Tanton TW, Rycroft DW (2014) The impact of climate change on the water resources of the Amu Darya Basin in Central Asia. Water Resour Manag 28(15):5267–5281

    Article  Google Scholar 

  • Wu P, Christidis N, Stott P (2013) Anthropogenic impact on Earth’s hydrological cycle. Nat Clim Chang 3(9):807–810

    Article  Google Scholar 

  • Yadav SS, Hegde V, Habibi AB, Dia M, Verma S (2019). Climate change, agriculture and food security. Food Security and Climate Change; Yadav SS, Redden RJ, Hatfield JL, Ebert AW, Hunter D, Eds

  • Yang X, Lu Y, Tan ML, Li X, Wang G, He R (2020) Nine-Year Systematic Evaluation of the GPM and TRMM Precipitation Products in the Shuaishui River Basin in East-Central China. Remote Sens 12(6):1042

    Article  Google Scholar 

  • Yatagai A, Kamiguchi K, Arakawa O, Hamada A, Yasutomi N, Kitoh A (2012) APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull Am Meteorol Soc 93(9):1401–1415

    Article  Google Scholar 

  • Zandler H, Haag I, Samimi C (2019) Evaluation needs and temporal performance differences of gridded precipitation products in peripheral mountain regions. Sci Rep 9(1):1–15

    Article  Google Scholar 

  • Zeleny M (1973). Compromise Programming, Multiple Criteria Decision Making, Edited by JL Cochrane and M. Zeleny. In: University of South Carolina Press, Columbia, South Carolina

  • Zhang W (2003) A compromise programming method using multibounds formulation and dual approach for multicriteria structural optimization. Int J Numer Methods Eng 58(4):661–678

    Article  Google Scholar 

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Acknowledgements

The authors thank the Ministry of Energy and Water of Afghanistan and the National Centers for Environmental Information of NOAA for providing the station observation data of the Amu Darya River basin. The authors are also thankful to the National Center for Atmospheric Research (USA), Climate Hazard Group (University of California, USA), Climate Prediction Center of NOAA, Deutscher Wetterdienst (Germany), Princeton University (USA), and University of Delaware (USA) for making the gridded precipitation data available through their data portal.

Code availability

The codes used for the processing of data can be provided on request to the corresponding author.

Funding

This study was financially supported by the Universiti Teknologi Malaysia (UTM) through grant no. Q.J130000.2451.09G07.

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Authors and Affiliations

  1. School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia

    Obaidullah Salehie, Tarmizi Ismail & Shamsuddin Shahid

  2. Faculty of Environment, Kabul University, Kabul, Afghanistan

    Obaidullah Salehie

  3. Faculty of Water Resources Management, Lasbela University of Agriculture, Water and Marine Sciences, Uthal, Pakistan

    Kamal Ahmed

  4. Dept of Civil Engineering, TKM College of Engineering, Kollam, India

    S Adarsh

  5. Department of Engineering, School of Digital, Technologies and Arts, Staffordshire University, ST4 2DE, Stoke-on-Trent, UK

    Md Asaduzzaman

  6. Spatial Sciences Discipline, School of Earth and Planetary Sciences, Curtin University, Perth, WA, 6102, Australia

    Ashraf Dewan

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  1. Obaidullah Salehie
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  4. Kamal Ahmed
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  5. S Adarsh
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Contributions

All the authors contributed to the conceptualization and design phases of the study. The data were gathered by Obaidullah Salehie and Kamal Ahmed; the programming code was written by Shamsuddin Shahid and Md Asaduzzaman; an initial draft of the paper was prepared by Obaidullah Salehie and S Adarsh; individual revisions and the final version were provided by Tarmizi bin Ismail and Ashraf Dewan.

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Correspondence to Tarmizi Ismail.

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Salehie, O., Ismail, T., Shahid, S. et al. Ranking of gridded precipitation datasets by merging compromise programming and global performance index: a case study of the Amu Darya basin. Theor Appl Climatol 144, 985–999 (2021). https://doi.org/10.1007/s00704-021-03582-4

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