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Flood frequency under changing climate in the upper Kafue River basin, southern Africa: a large scale hydrological model application

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Abstract

The projected impacts of climate change and variability on floods in the southern Africa has not been well studied despite the threat they pose to human life and property. In this study, the potential impacts of climate change on floods in the upper Kafue River basin, a major tributary of the Zambezi River in southern Africa, were investigated. Catchment hydrography was delineated using the Hydro1k at a spatial resolution of 1 km. The daily global hydrological model WASMOD-D model was calibrated and validated during 1971–1986 and 1987–2001 with the simple-split sample test and during 1971–1980 and 1981–1990 with the differential split sample test, against observed discharge at Machiya gauging station. Predicted discharge for 2021–2050 and 2071–2100 were obtained by forcing the calibrated WASMOD-D with outputs from three GCMs (ECHAM, CMCC3 and IPSL) under the IPCC’s SRES A2 and B1 scenarios. The three GCMs derived daily discharges were combined by assigning a weight to each of them according to their skills to reproduce the daily discharge. The two calibration and validation tests suggested that model performance based on evaluation criteria including the Nash–Sutcliffe coefficient, Pearson’s correlation coefficient (r), Percent Bias and R 2 was satisfactory. Flood frequency analysis for the reference period (1960–1990) and two future time slices and climate change scenarios was performed using the peak over threshold analysis. The magnitude of flood peaks was shown to follow generalised Pareto distribution. The simulated floods in the scenario periods showed considerable departures from the reference period. In general, flood events increased during both scenario periods with 2021–2050 showing larger change. The approach in our study has a strong potential for similar assessments in other data scarce regions.

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References

  • Alcamo J, Döll P, Henrichs T, Kaspar F, Lehner B, Rösch T, Siebert S (2003) Development and testing of the WaterGAP 2 global model of water use and availability. Hydrol Sci J 48(3):317–337

    Google Scholar 

  • Alemaw BF, Chaoka TR (2003) A continental scale water balance model: a GIS-approach Approach for southern Africa. J Phys Chem Earth 28(20–27):957–966

    Article  Google Scholar 

  • Alemaw BF, Chaoka TR (2006) The 1950–1998 warm ENSO events and regional implication to river flow variability in southern Africa. Water SA 32:459–463

    Google Scholar 

  • Allasia DG, Da Silva BC, Collischonn W, Tucci CEM (2006) Large basin simulation experience in South America. In: Predictions in ungauged basins: promise and progress (Proceedings of symposium S7 held during the Seventh IAHS Scientific Assembly at Foz do Iguaçu, Brazil, April 2005). IAHS Publ. 303

  • Andersson L, Samuelsson P, Kjellström E (2011) Assessment of climate change impact on water resources in the Pungwe river basin. Tellus A 63:138–157

    Article  Google Scholar 

  • Arnell NW (1999a) Climate change and global water resources. Glob Environ Chang 9:S31–S49

    Article  Google Scholar 

  • Arnell NW (1999b) A simple water balance model for the simulation of stream flow over a large geographic domain. J Hydrol 217:314–335

    Article  Google Scholar 

  • Arnell NW (2003) Effects of IPCC SRES emissions scenarios on river runoff: a global perspective. Hydrol Earth Syst Sci 7:619–641

    Article  Google Scholar 

  • Arnell NW (2004) Global change and global water resources: SRES emissions and socio economic scenarios. Glob Environ Chang 14:31–52

    Article  Google Scholar 

  • Bartman AG, Landman WA, De W, Rautenbach CJW (2003) Recalibration of General Circulation Model output to austral summer rainfall over. Int J Climatol 23:1407–1419

    Article  Google Scholar 

  • Bates BC, Kundzewicz ZW, Wu S, Palutikof JP (eds) (2008) Climate change and water. Technical Paper of the Intergovernmental Panel on Climate Change, IPCC Secretariat, Geneva, 210 pp

  • Beck L, Bernauer T (2011) How will combined changes in water demand and climate affect water availability in the Zambezi river basin? Glob Environ Chang 21:1061–1072. doi:10.1016/j.gloenvcha.2011.04.0

  • Booij MJ, Tollenaar D, vav Beek E, Kwadijk JCJ (2011) Simulating impacts of climate change on river discharges in the Nile basin. Phys Chem Earth 36:696–709

    Article  Google Scholar 

  • Cloke HL, Hannah DL (2011) Large-scale hydrology: advances in understanding processes, dynamics and models from beyond river basin to global scale. Hydrol Process 25:991–995. doi:10.1002/hyp.8059

    Google Scholar 

  • Cole S (2001) An introduction to statistical modelling of extreme values. Springer, London

    Google Scholar 

  • Cunderlik JM, Simonovic SP (2005) Hydrological extremes in a southwestern Ontario river basin under future climate conditions. Hydrol Sci J 50(4):631–654

    Article  Google Scholar 

  • Di Baldassarre G, Montanari A (2009) Uncertaninity in river discharge observations: a quantitative analysis. Hydrol Earth Syst Sci 13:913–921

    Article  Google Scholar 

  • Döll P, Kaspar F, Alcamo J (1999) Computation of global water availability and water use at the scale of large drainage basins. Math Geol 4:111–118

    Google Scholar 

  • Döll P, Kaspar F, Lehner B (2003) A global hydrological model for deriving water availability indicators: model tuning and validation. J Hydrol 270:105–134

    Article  Google Scholar 

  • Döll P, Berkhoff K, Bormann H, Fohrer N, Gerten D, Hagemann S, Krol M (2008) Advances and visions in large-scale hydrological modeling: findings from the 11th workshop on large-scale hydrological modeling. Adv Geosci 18:51–61

    Article  Google Scholar 

  • Engeland K, Hisdal H, Frigessi A (2004) Practical extreme value modeling in hydrological floods and droughts: a case study. Extremes 7:5–30

    Article  Google Scholar 

  • Fauchereau N, Trzaska S, Rouault M, Richard Y (2003) Rainfall variability and changes in during the 20th century in the global warming. Nat Hazards 29:139–154

    Article  Google Scholar 

  • Gain AK, Immerzeel WW, Sperna Weiland FC, Bierkens MPF (2011) Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modeling. Hydrol Earth Syst Sci 15:1537–1545

    Article  Google Scholar 

  • Ghosh S, Resnick S (2010) A discussion on mean excess plots. Stoch Process Appl 120:1492–1517

    Article  Google Scholar 

  • Gong L, Widén-Nilsson E, Halldin S, Xu C-Y (2009) Large-scale runoff routing with an aggregated network-response function. J Hydrol 368:237–250

    Article  Google Scholar 

  • Gong L, Halldin S, Xu CY (2011) Global scale river routing—an efficient time delay algorithm based on HydroSHEDS high resolution hydrography. Hydrol Process 25(7):1114–1128

    Article  Google Scholar 

  • Gottschalk L, Krasovskaia I (2002) L-moment estimation using annual maximum (AM) and peak over threshold (POT) series in regional analysis of flood frequencies, Norsk Geografisk Tidsskrift. Nor J Geogr 56(2):179–187

    Google Scholar 

  • GRDC (2010) Global Runoff Data Centre, Koblenz, Germany

  • Hagemann S, Chen C, Haerter JO, Heinke J, Gerten D, Piani C (2011) Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models. J Hydrometerol 12:556–578

    Article  Google Scholar 

  • Heyns PSVH, Patrick MV, Turton AR (2008) Transboundary water resource management in : meeting the challenge of joint planning and management in the orange river basin. Int J Water Res Dev 24(3):371–383

    Google Scholar 

  • Hirabayashi Y, Kanae S, Emori S, Oki T, Kimoto M (2008) Global projections of changing risks of floods and droughts in a changing climate. Hydrol Sci J 54(4):754–772

    Article  Google Scholar 

  • Hosking JRM (1990) L-moments: analysis and estimation of distributions using linear combinations of order statistics. Royal Stat Soc Lond 52:105–124

    Google Scholar 

  • Hosking JRM, Wallis JR (1997) Regional frequency analysis: an approach based on L-moments. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Hughes DA (1995) Monthly rainfall-runoff models applied to arid and semi-arid catchments for water resources estimation purposes. Hydrol Sci J 40(6):751–769

    Article  Google Scholar 

  • Hughes DA (1997) Southern Africa “FRIEND”. The application of rainfall-runoff models in the SADC region. Water Research Commission Report No. 235/1/97, Pretoria, South Africa

  • Hughes DA (2002) The development of an information modelling system for regional water resource assessments. In: Proceedings of the 4th International Conference on FRIEND. IAHS Publ. No. 274, pp 43–49

  • Hughes DA (2004) Incorporating ground water recharge and discharge functions into an existing monthly rainfall-runoff model. Hydrol Sci J 49(2):297–311

    Article  Google Scholar 

  • Hughes D, Görgens A, Middleton B, Hollingworth B (2002) Regional water resource assessment in the SADC region. In: Proceedings of the Fourth International FRIEND Conference, Cape Town, South Africa, March 2002. IAHS Publ. No. 274, 2002, pp 11–18

  • Hughes DA, Andersson L, Wilk J, Savenije HHG (2006) Regional calibration of the Pitman model for the Okavango River. J Hydrol 331:30–42

    Article  Google Scholar 

  • Hughes DA, Kapangaziwiri E, Baker K (2010a) Initial evaluation of a simple coupled surface and ground water hydrological model to assess sustainable ground water abstractions at the regional scale. Hydrol Res 41(1):1–12

    Article  Google Scholar 

  • Hughes DA, Kapangaziwiri E, Sawunyama T (2010b) Hydrological model uncertainty assessment in southern Africa. J Hydrol 387(3–4):221–232

    Article  Google Scholar 

  • Jung G, Wagner S, Kunstmann H (2012) Joint climate–hydrology modeling: an impact study for the data-sparse environment of the Volta Basin in West Africa. Hydrol Res 43(3):231–248

    Article  Google Scholar 

  • Jury MR, Pathack BMR (1993) Composite climatic patterns associated with extreme modes of summer rainfall over Southern Africa: 1975–1984. Theor Appl Climatol 47:137–145

    Article  Google Scholar 

  • Kaspar F (2004) Development and uncertainty analysis of a global hydrologic model. PhD Dissertation, University of Kassel, Kassel, Germany

  • Klemes V (1986) Operational testing of hydrological simulations models. Hydrol Sci J 31:13–24

    Article  Google Scholar 

  • Lang M, Ourda TBMJ, Bobee B (1999) Towards operational guidelines for over-threshold modeling. J Hydrol 225:103–117

    Article  Google Scholar 

  • Layberry R, Kniveton DR, Todd MC, Kidd C, Bellerby TJ (2006) Daily precipitation over : a new resource for climate studies. J Hydrometeor 7(1):149–159

    Article  Google Scholar 

  • Li L, Ngongondo C, Xu C-Y, Gong L (2012) Comparison of two global datasets of TRMM and WFD based on Large-scale hydrological modelling in southern Africa. Hydrol. Res. (accepted)

  • Liu T, Willems P, Pan XL, Bao An M, Chen X, Veroustraete F, Dong Q-H (2011) Climate change impact on water resource extremes in a headwater region of Tarim basin, China. Hydrol Earth Syst Sci 15:3511–3517

    Article  Google Scholar 

  • Madsen H, Rasmussen PF, Rosbjerg D (1997) Comparison of annual maximum series and partial duration series methods for modeling extreme hydrologic events. 1. At-site modeling. Water Res 33(4):737–757

    Google Scholar 

  • Mason SJ, Joubert AM (1998) Simulated changes in extreme rainfall over Southern Africa. Int J Climatol 17:291–301

    Article  Google Scholar 

  • Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ (2008) Stationarity is dead: whither water management? Science 319:573–574

    Article  CAS  Google Scholar 

  • Mkhandi SH, Kachroo RK, Gunasekara TAG (2000) Flood frequency analysis of southern Africa : II. Identification of regional distributions. Hydrol Sci J 45(3):449–466

    Article  Google Scholar 

  • Moore RJ (1985) The probability distributed principle and runoff production at point and basin scales. Hydrol Sci J 30(2):263–297

    Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans Am Soc Eng 50(3):885–900

    Google Scholar 

  • Mwelwa EM (2004) The application of the monthly step Pitman Rainfall–Runoff Model to the Kafue River Basin of Zambia. MSc thesis, Rhodes University, South Africa

  • Nakicenovic N, Swart R (2000) Special Report on emissions scenarios: A special report of working group III of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, 599 pp. http://www.grida.no/climate/ipcc/emission/index.htm. Accessed 10 May 2012

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models: part I—a discussion of principles. J Hydrol 10(3):282–290

    Article  Google Scholar 

  • Obrdlik P, Mumeka A, Kasonde JM (1989) Regulated rivers in Zambia-the case study of the Kafue River. Regul Rivers Res Manag 3:371–380

    Article  Google Scholar 

  • Petrow T, Merz B (2009) Trends in flood magnitude, frequency and seasonality in Germany in the period 1951–2002. J Hydrol 371:129–141

    Article  Google Scholar 

  • Piani C, Haerter JO, Coppola E (2010a) Statistical bias correction for daily precipitation in regional climate models over Europe. Theor Appl Climatol 99:187–192

    Article  Google Scholar 

  • Piani C, Weedon GP, Best M, Gomes SM, Viterbo P, Hagemann S, Haerter JO (2010b) Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. J Hydrol 395:199–215. doi:10.1016/j.jhydrol.2010.10.02

    Article  Google Scholar 

  • Pitman WV (1973) A mathematical model for generating river flows from meteorological data in South Africa. Report No. 2/73, Hydrological Research Unit, University of the Witwatersrand, Johannesburg

  • Reynard N, Andrews A, Arnel N (1997) The derivation of a runoff grid for southern Africa for climate change impact analyses. In: FRIEND ‘97—regional hydrology: concepts and models for sustainable water resource management IAHS Publ vol 46, pp 23–30

  • Robinson A, Reed D (1999) Flood estimation hand book: statistical procedure for flood frequency estimation, vol 3. Institute of Hydrology, Wallingford

    Google Scholar 

  • Rosbjerg D, Madsen H (2004) Advanced approaches in PDS/Modeling of extremes hydrological events. Hydrol 1:217–220

    Google Scholar 

  • Rustomji P, Bennett N, Chiew F (2009) Flood variability east of Australia’s great dividing range. J Hydrol 374:196–208

    Article  Google Scholar 

  • Samaniego L, Kumar R, Jackisch C (2011) Predictions in a data-sparse region using a regionalized grid-based hydrologic model driven by remotely sensed data. Hydrol Res 42(5):338–355

    Article  Google Scholar 

  • Sawunyama T, Hughes DA (2008) Application of satellite-derived rainfall estimates to extend water resource simulation modelling in South Africa. Water SA 34(1):1–9

    Google Scholar 

  • Shongwe ME, Landman WA, Mason SJ (2006) Performance of recalibration systems for GCM forecasts for southern Africa. Int J Climatol 17:1567–1585

    Google Scholar 

  • Sperna Weiland FC, van Beek LPH, Weerts AH, Bierkens MFP (2012) Extracting information from an ensemble of GCMs to reliably assess future global runoff change. J Hydrol 412–414:66–75. doi:10.1016/j.jhydrol.2011.03.047

    Article  Google Scholar 

  • Strupczewski WG, Kochanek K, Markiewicz I (2011) On the tails of distributions of annual peak flow. Hydrol Res 42(2–3):171–192

    Article  Google Scholar 

  • Strzepek K, McCluskey A (2006) District level hydro-climatic time series and scenario analysis to assess the impacts of climate change on regional water resources and agriculture in Africa. Centre for Environmental Economics and Policy in Africa (CEEPA), Pretoria

    Google Scholar 

  • Svensson C, Kundzewicz ZW, Maurer Th (2005) Trend detection in river flow series: 2 flood and low-flow index series. Hydrol Sci J 50(5):811–824

    Article  Google Scholar 

  • Tanaka S, Takara K (2002) A study on threshold selection in POT analysis of extreme floods. In: The extremes of the extremes: extraordinary floods (Proceedings of a symposium held at Reykjavik. Iceland.July 2000). IAHS IS Publ. No. 271

  • Taye MT, Ntegeka V, Ogiramoi NP, Willems P (2011) Assessment of climate change impact on hydrological extremes in two source regions of the Nile River Basin. Hydrol Earth Syst Sci 15:209–222

    Article  Google Scholar 

  • Turton AR, Meissner R, Mampane PM, Seremo O (2004) A hydropolitical history of South Africa’s international river basins. Report to the Water Research Commission WRC Report No. 1220/1/04

  • USGS (US Geological Survey) (1996a) HYDRO1K Elevation Derivative Database. In: Earth resources observation and science (EROS) Data Center (EDC), Sioux Falls, South Dakota, USA. http://edc.usgs.gov/products/elevation/gtopo30/hydro/index.html. Accessed May 2012

  • USGS (US Geological Survey) (1996b) GTOPO30 (Global 30 Arc-Second Elevation Data Set). In: Earth resources observation and science (EROS) Data Center (EDC), Sioux Falls, South Dakota, USA. http://edc.usgs.gov/products/elevation/gtopo30/gtopo30.html. Accessed May 2012

  • UNEP and ICRAF (2006) Climate change and variability in the: impacts and adaptation strategies in the agricultural sector. http://www.worldagroforestrycentre.org. Accessed May 2012

  • Unganai LS, Kogan FN (1998) Drought monitoring and corn yield estimation in Southern Africa from AVHRR data. Remote Sensing Environ 63:219–232

    Google Scholar 

  • Uppala SM, Kållberg PW, Simmons AJ, Andrae U, Bechtold VDC, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X et al (2005) The ERA-40 re-analysis. Quart J Royal Meteorol Soc 131(612):2961–3012

    Article  Google Scholar 

  • Vogel RM, Fennessey NM (1994) Flow-duration curves. 1: new interpretation and confidence-intervals. J Water Res Pl-Asce 120:485–504

    Article  Google Scholar 

  • Vörösmarty CJ, Moore B (1991) Modelling basin-scale hydrology in support of physical climate and global biogeochemical studies: an example using the Zambezi River. Studia Geophys 12:271–311

    Google Scholar 

  • Vörösmarty CJ, Moore B, Grace AL, Gildea MP, Melillo JM, Peterson BJ, Rastetter EB, Steudler PA (1989) Continental scale models of water balance and fluvial transport: an application to South America. Glob Biogeochem Cycle 3:241–265

    Article  Google Scholar 

  • Vörösmarty CJ, Willmott CJ, Choudhury BJ, Schloss AL, Stearns TK, Robeson S.M. Dorman TJ (1996) Analyzing the discharge regime of a large tropical river through remote sensing, ground-based climatic data, and modelling. Water Resour Res 32:3137–3150

    Google Scholar 

  • Vörösmarty CJ, Sharma KP, Fekete BM, Copeland AH, Holden J, Marble J, Lough JA (1997) The storage and aging of continental runoff in large reservoir systems of the world. Ambio 26:210–219

    Google Scholar 

  • Vörösmarty CJ, Federer CA, Schloss AL (1998) Potential evaporation functions compared on US watersheds: possible implications for global-scale water balance and terrestrial ecosystem modelling. J Hydrol 207:147–169

    Article  Google Scholar 

  • Wang QJ (1991) The POT model described by the generalized Pareto distribution with Poisson arrival rate. J Hydrol 129:263–280

    Article  Google Scholar 

  • Wang Z, Darren L, Ficklin L, Zhang Y, Zhang M (2012) Impact of climate change on streamflow in the arid Shiyang River basin of northwest China. Hydrol Process 26(18):2733–2744. doi:10.1002/hyp.8378

    Google Scholar 

  • Weedon GP, Gomes S, Viterbo P, Österle H, Adam JC, Bellouin N, Boucher O, Best M (2010) The WATCH forcing data 1958–2001: a meteorological forcing dataset for land surface-and hydrological—Rep., WATCH Tech. Rep. 22, pp 41. http://www.eu-watch.org/publications/technical-reports. Accessed 10 May 2012

  • Weedon GP, Gomes S, Viterbo P, Shuttleworth W, Blyth E, Österle H, Adam J, Bellouin N, Boucher O, Best M (2011) Creation of the WATCH Forcing Data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J Hydrometeor 12(5):823–848

    Article  Google Scholar 

  • Westerberg I, Younger P, Guerrero J, Beven K, Seibert J, Halldin S, Xu C-Y (2011) Calibration of hydrologic models using flow-duration curves. Hydrol Earth Syst Sci 15:2205–2227

    Article  Google Scholar 

  • Widen-Nilsson E, Haldin S, Xu C-Y (2007) Global water-balance modelling with WASMOD-M: parameter estimation and regionalization. J Hydrol 340:105–118

    Article  Google Scholar 

  • Wilk J, Hughes DA (2002) Calibrating a rainfall-runoff model for a catchment with limited data. Hydrol Sci J 47(1):3–17

    Article  Google Scholar 

  • Wilk J, Kniveton D, Andersson L, Hughes DA, Layberry R, Todd MC (2006) Rainfall, water balance and land use of the Okavango basin upstream the delta. J Hydrol 331:18–29

    Article  Google Scholar 

  • Wolski P (2009) The Okavango TDA assessment of the hydrological effects of the climate change effects of climate change in the Okavango basin. In: The permanent Okavango River Basin Water Commission. http://iwlearn.net/iw-projects/842/reports/environmental-flow-assessment-reports/assessment-of-hydrological-effects-of-climate-change-in-the-okavango-basin.pdf. Accessed 16 Feb 2012

  • Xu C-Y (1999) From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches. Progress Phys Geogr 23(2):229–249

    Google Scholar 

  • Xu C-Y (2002) WASMOD—the water and snow balance modeling system. In: Singh VP, Frevert DK (eds) Mathematical models of small watershed hydrology and applications. Water Resources Publications LLC, Highlands Ranch, Colorado, pp 555–590 (Chapter 17)

  • Yang T, Xu C-Y, Shao Q-X, Chen X (2010) Regional flood frequency and spatial patterns analysis in the Pearl River Delta region using L-moments approach. Stoch Environ Res Risk Assess 24:165–182

    Article  Google Scholar 

  • Yang C, Yu Z, Hao Z, Zhang J (2012) Impact of climate change on flood and drought events in Huaihe River Basin, China. Hydrol Res 43(1–2):14–22

    Article  CAS  Google Scholar 

  • Zhu T, Ringler C (2010) Climate change implications for water resources in the Limpopo River basin. IFPRI Discussion Paper 00961

Download references

Acknowledgments

This study was supported by the project Capacity Building in Water Sciences for the Better Management of Water Resources in (NUFUPRO-2007) funded by the Norwegian Programme for Development, Research and Education (NUFU) and the Environment and Development Programme (FRIMUF) of the Research Council of Norway, project 190159/V10 (SoCoCA). The second author was also supported by The Research Council of Norway (RCN) with project number 171783 (FRIMUF), and by the Programme of Introducing Talents of Discipline to Universities—the 111 Project of Hohai University. We gratefully thank the E.U funded Watch Project for availing to us the WFD and the GCM future scenarios data as well as their technical support with data retrieval. The GRDC is gratefully acknowledged for kindly providing the discharge data for the Kafue River at Machiya station.

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  1. Department of Geosciences, University of Oslo, P.O. Box 1047, Blindern, Oslo, Norway

    Cosmo Ngongondo, Lu Li, Lebing Gong & Chong-Yu Xu

  2. Department of Geography and Earth Sciences, University of Malawi, Chancellor College, P.O. Box 280, Zomba, Malawi

    Cosmo Ngongondo

  3. Department Physical Geography and Quaternary Geology, Bert Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden

    Lebing Gong

  4. Department of Geology, University of Botswana, Pr. Bag UB00704, Gaborone, Botswana

    Berhanu F. Alemaw

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Correspondence to Cosmo Ngongondo.

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Ngongondo, C., Li, L., Gong, L. et al. Flood frequency under changing climate in the upper Kafue River basin, southern Africa: a large scale hydrological model application. Stoch Environ Res Risk Assess 27, 1883–1898 (2013). https://doi.org/10.1007/s00477-013-0724-z

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