Use of ACRU, a distributed hydrological model, to evaluate how errors from downscaled rainfall are propagated in simulated runoff in uMngeni catchment, South Africa

References

• Acocks, J.P.H., 1988. Veld types of South Africa. 3rd ed. Pretoria: Government Printers.
   Google Scholar
• Andréassian, V., et al. 2001. Impact of imperfect rainfall knowledge on the efficiency and the parameters of watershed models. Journal of Hydrology, 250 (1–4), 206–223. doi:10.1016/S0022-1694(01)00437-1
   Web of Science ®Google Scholar
• Arnell, N.W. and Gosling, S.N., 2013, The impacts of climate change on river flow regimes at the global scale. Journal of Hydrology, 486 (1), 351–364. doi:10.1016/j.jhydrol.2013.02.010
   Web of Science ®Google Scholar
• Beven, K. and Binley, A., 1992. The future of distributed models: model calibration and uncertainty prediction. In: B. E Moore, ed. Terrain analiysis and distributed modelling in hydrology. Chichester: John Wiley & Sons, 227–246.
   Google Scholar
• Beven, K. and Freer, J., 2001, Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. Journal of Hydrology, 249 (1–4), 11–29. doi:10.1016/S0022-1694(01)00421-8
   Web of Science ®Google Scholar
• Beven, K.J., 2011. Rainfall-runoff modelling: the primer. Chichester: John Wiley & Sons.
   Google Scholar
• Bezuidenhout, C.N., 2005. Development and evaluation of model-based operational yield forecasts in the South African sugar industry. ( PhD). University of KwaZulu-Natal, South Africa.
   Google Scholar
• Borga, M., 2002, Accuracy of radar rainfall estimates for streamflow simulation. Journal of Hydrology, 267 (1–2), 26–39. doi:10.1016/S0022-1694(02)00137-3
   Web of Science ®Google Scholar
• Borga, M., Degli Esposti, S., and Norbiato, D., 2006. Influence of errors in radar rainfall estimates on hydrological modeling prediction uncertainty. Water Resources Research, 42 (8). doi:10.1029/2005WR004559
   Web of Science ®Google Scholar
• Bringi, V., et al. 2001. An areal rainfall estimator using differential propagation phase: evaluation using a C-band radar and a dense gauge network in the tropics. Journal of Atmospheric and Oceanic Technology, 18 (11), 1810–1818. doi:10.1175/1520-0426(2001)018<1810:AAREUD>2.0.CO;2
   Web of Science ®Google Scholar
• Chen, H., Xu, C.-Y., and Guo, S., 2012, Comparison and evaluation of multiple GCMs, statistical downscaling and hydrological models in the study of climate change impacts on runoff. Journal of Hydrology, 434–435 (0), 36–45. doi:10.1016/j.jhydrol.2012.02.040
   Web of Science ®Google Scholar
• Chiew, F., et al. 2010. Comparison of runoff modelled using rainfall from different downscaling methods for historical and future climates. Journal of Hydrology, 387 (1–2), 10–23. doi:10.1016/j.jhydrol.2010.03.025
   Web of Science ®Google Scholar
• Coutinho, J., et al., 2014. Characterization of sub-daily rainfall properties in three raingauges located in northeast Brazil. Proceedings of the International Association of Hydrological Sciences, 364, 345–350. doi:10.5194/piahs-364-345-2014
   Google Scholar
• Fand, B.B., et al. 2014. Predicting the impact of climate change on regional and seasonal abundance of the mealybug Phenacoccus solenopsis Tinsley (Hemiptera: pseudococcidae) using temperature-driven phenology model linked to GIS. Ecological Modelling, 288 (0), 62–78. doi:10.1016/j.ecolmodel.2014.05.018
   Web of Science ®Google Scholar
• Gabellani, S., et al. 2007. Propagation of uncertainty from rainfall to runoff: A case study with a stochastic rainfall generator. Advances in Water Resources, 30 (10), 2061–2071. doi:10.1016/j.advwatres.2006.11.015
   Web of Science ®Google Scholar
• Gorard, S., 2005, Revisiting a 90-year-old debate: the advantages of the mean deviation. British Journal of Educational Studies, 53 (4), 417–430. doi:10.1111/j.1467-8527.2005.00304.x
   Web of Science ®Google Scholar
• Gosling, S., et al. 2011. A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models. Hydrology and Earth System Sciences, 15 (1), 279–294. doi:10.5194/hess-15-279-2011
   Web of Science ®Google Scholar
• Graham, L.P., et al. 2011. Using multiple climate projections for assessing hydrological response to climate change in the Thukela River Basin, South Africa. Physics and Chemistry of the Earth, Parts A/B/C, 36 (14–15), 727–735. doi:10.1016/j.pce.2011.07.084
   Web of Science ®Google Scholar
• Gush, M., et al. 2002. A new approach to modelling streamflow reductions resulting from commercial afforestation in South Africa. The Southern African Forestry Journal, 196 (1), 27–36. doi:10.1080/20702620.2002.10434615
   Google Scholar
• Hargreaves, G.H. and Samani, Z.A., 1985, Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1 (2), 96–99. doi:10.13031/2013.26773
   Google Scholar
• Hewitson, B. and Crane, R., 2006, Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa. International Journal of Climatology, 26 (10), 1315–1337. doi:10.1002/(ISSN)1097-0088
   Web of Science ®Google Scholar
• Hewitson, B.C., and Tadross, M.A., 2011. Developing regional climate change projections. In: R.E. Schulze, B.C. Hewitson, K.R. Barichievy, M.A. Tadross, R.P. Kunz, M.J.C. Horan, T.G. Lumsden, eds. Methodological approaches to assessing eco-hydrological responses to climate change in South Africa. Report K5/1562. Pretoria: Water Research Commission.
   Google Scholar
• Honti, M., Scheidegger, A., and Stamm, C., 2014, The importance of hydrological uncertainty assessment methods in climate change impact studies. Hydrology and Earth System Sciences, 18 (8), 3301–3317. doi:10.5194/hess-18-3301-2014
   Web of Science ®Google Scholar
• Hossain, F., et al. 2004. Hydrological model sensitivity to parameter and radar rainfall estimation uncertainty. Hydrological Processes, 18 (17), 3277–3291. doi:10.1002/hyp.5659
   Web of Science ®Google Scholar
• Hostache, R., et al. 2011. Propagation of uncertainties in coupled hydro-meteorological forecasting systems: A stochastic approach for the assessment of the total predictive uncertainty. Atmospheric Research, 100 (2–3), 263–274. doi:10.1016/j.atmosres.2010.09.014
   Web of Science ®Google Scholar
• Hughes, D., 2004, Three decades of hydrological modelling research in South Africa. South African Journal of Science, 100 (11 & 12), 638–642.
   Web of Science ®Google Scholar
• Hughes, D., 2013. A review of 40 years of hydrological science and practice in southern Africa using the Pitman rainfall-runoff model. Journal of Hydrology, 501, 111–124. doi:10.1016/j.jhydrol.2013.07.043
   Web of Science ®Google Scholar
• Hughes, D., 2016. Hydrological modelling, process understanding and uncertainty in a southern African context: lessons from the northern hemisphere. Hydrological Processes, 30 (14), 2419–2431. doi:10.1029/2008WR006833
   Web of Science ®Google Scholar
• Hughes, D., Kapangaziwiri, E., and Sawunyama, T., 2010, Hydrological model uncertainty assessment in southern Africa. Journal of Hydrology, 387 (3–4), 221–232. doi:10.1016/j.jhydrol.2010.04.010
   Web of Science ®Google Scholar
• Hughes, D., Mantel, S., and Mohobane, T., 2014, An assessment of the skill of downscaled GCM outputs in simulating historical patterns of rainfall variability in South Africa. Hydrology Research, 45 (1), 134–147. doi:10.2166/nh.2013.027
   Web of Science ®Google Scholar
• Ji, F., et al. 2014. Evaluating rainfall patterns using physics scheme ensembles from a regional atmospheric model. Theoretical and Applied Climatology, 115 (1–2), 297–304. doi:10.1007/s00704-013-0904-2
   Web of Science ®Google Scholar
• Kapangaziwiri, E., Hughes, D., and Wagener, T., 2012, Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa. Hydrological Sciences Journal, 57 (5), 1000–1019. doi:10.1080/02626667.2012.690881
   Web of Science ®Google Scholar
• Kienzle, S.W., et al. 2012. Simulating the hydrological impacts of climate change in the upper North Saskatchewan River basin, Alberta, Canada. Journal of Hydrology, 412–413 (0), 76–89. doi:10.1016/j.jhydrol.2011.01.058
   Web of Science ®Google Scholar
• Kusangaya, S., et al., 2014. Impacts of climate change on water resources in southern Africa: A review. Physics and Chemistry of the Earth, Parts A/B/C, 67, 47–54. doi:10.1016/j.pce.2013.09.014
   Web of Science ®Google Scholar
• Kusangaya, S., et al., 2016. An evaluation of how downscaled climate data represents historical precipitation characteristics beyond the means and variances. Global and Planetary Change, 144, 129–141. doi:10.1016/j.gloplacha.2016.07.014
   Web of Science ®Google Scholar
• Li, F., et al. 2013. The impact of climate change on runoff in the southeastern Tibetan Plateau. Journal of Hydrology, 505 (0), 188–201. doi:10.1016/j.jhydrol.2013.09.052
   Web of Science ®Google Scholar
• Li, F., Zhang, G., and Xu, Y.J., 2014, Spatiotemporal variability of climate and streamflow in the Songhua River Basin, northeast China. Journal of Hydrology, 514 (0), 53–64. doi:10.1016/j.jhydrol.2014.04.010
   Web of Science ®Google Scholar
• Liu, Y., et al. 2012. Quantifying uncertainty in catchment-scale runoff modeling under climate change (case of the Huaihe River, China). Quaternary International, 282 (0), 130–136. doi:10.1016/j.quaint.2012.04.029
   Web of Science ®Google Scholar
• Liu, Y. and Gupta, H.V., 2007, Uncertainty in hydrologic modeling: toward an integrated data assimilation framework. Water Resources Research, 43 (7), W07401. doi:10.1029/2006WR005756
   Web of Science ®Google Scholar
• Lumsden, T., Schulze, R., and Hewitson, B., 2009, Evaluation of potential changes in hydrologically relevant statistics of rainfall in Southern Africa under conditions of climate change. Water Sa, 35 (5), 649–656. doi:10.4314/wsa.v35i5.49190
   Web of Science ®Google Scholar
• Mazvimavi, D., 2010, Climate change, water availability and supply. SARUA Leadership Dialogue Series, 2 (4), 81–97.
   Google Scholar
• Moulin, L., Gaume, E., and Obled, C., 2009, Uncertainties on mean areal precipitation: assessment and impact on streamflow simulations. Hydrology and Earth System Sciences, 5 (4), 2067–2110. doi:10.5194/hessd-5-2067-2008
   Google Scholar
• Najafi, M., Moradkhani, H., and Jung, I., 2011, Assessing the uncertainties of hydrologic model selection in climate change impact studies. Hydrological Processes, 25 (18), 2814–2826. doi:10.1002/hyp.v25.18
   Web of Science ®Google Scholar
• Nikolopoulos, E.I., et al. 2010. Understanding the scale relationships of uncertainty propagation of satellite rainfall through a distributed hydrologic model. Journal of Hydrometeorology, 11 (2), 520–532. doi:10.1175/2009JHM1169.1
   Web of Science ®Google Scholar
• Nikulin, G., et al. 2012. Precipitation climatology in an ensemble of CORDEX-Africa regional climate simulations. Journal of Climate, 25 (18), 6057–6078. doi:10.1175/JCLI-D-11-00375.1
   Web of Science ®Google Scholar
• NWA, 1998. National Water Act, Act No. 36 of 1998. Pretoria, RSA: Government Printers.
   Google Scholar
• Ogden, F., et al. 2000. Hydrologic analysis of the Fort Collins, Colorado, flash flood of 1997. Journal of Hydrology, 228 (1–2), 82–100. doi:10.1016/S0022-1694(00)00146-3
   Web of Science ®Google Scholar
• Pappenberger, F., et al. 2005. Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS). Hydrology and Earth System Sciences Discussions, 9 (4), 381–393. doi:10.5194/hess-9-381-2005
   Web of Science ®Google Scholar
• Praskievicz, S. and Chang, H., 2009, A review of hydrological modelling of basin-scale climate change and urban development impacts. Progress in Physical Geography, 33 (5), 650–671. doi:10.1177/0309133309348098
   Web of Science ®Google Scholar
• Sawunyama, T. and Hughes, D., 2008, Application of satellite-derived rainfall estimates to extend water resource simulation modelling in South Africa. Water Sa, 34 (1), 1–10.
   Web of Science ®Google Scholar
• Schulze, R., 1995. Hydrology and agrohydrology: A text to accompany the ACRU 3.00 agrohydrological modelling system. Pretoria, South Africa: Water Research Commission.
   Google Scholar
• Schulze, R., 2005. Climate change and water resources in Southern Africa: studies on scenarios, impacts, vulnerabilities and adaptation. Pretoria, South Africa: Water Research Commission.
   Google Scholar
• Schulze, R., 2011. Methodological approaches to assessing eco-hydrological responses to climate change in South Africa. Pretoria, South Africa: Water Research Commission.
   Google Scholar
• Schulze, R., Kunz, R., and Knoesen, D., 2003. Atlas of climate change and water resources in South Africa. Pretoria, South Africa: Water Research Commission.
   Google Scholar
• Schulze, R. and Maharaj, M., 2004. Development of a database of gridded daily temperatures for Southern Africa. Pretoria, South Africa: Water Research Commission.
   Google Scholar
• Schulze, R., and Perks, L., 2000. Assessment of the impact of climate change on hydrology and water resources in South Africa. ACRUcons Report 33. Pretoria: Water Research Commission.
   Google Scholar
• Senarath, S.U., et al. 2000. On the calibration and verification of two‐dimensional, distributed, Hortonian, continuous watershed models. Water Resources Research, 36 (6), 1495–1510. doi:10.1029/2000WR900039
   Web of Science ®Google Scholar
• Sharif, H.O., et al. 2002. Numerical simulations of radar rainfall error propagation. Water Resources Research, 38 (8). doi:10.1029/2001WR000525
   Web of Science ®Google Scholar
• Sharif, H.O., et al. 2004. Statistical analysis of radar rainfall error propagation. Journal of Hydrometeorology, 5 (1), 199–212. doi:10.1175/1525-7541(2004)005<0199:SAORRE>2.0.CO;2
   Web of Science ®Google Scholar
• Smithers, J. and Schulze, R., 1995. ACRU Agrohydrological Modelling System: User manual, version 3.00. (Report TT70/95). Pretoria: Water Research Commission.
   Google Scholar
• Smithers, J., Schulze, R., and Kienzle, S., 1997, Design flood estimation using a modelling approach: a case study using the ACRU model. IAHS Publications-Series of Proceedings and Reports-Intern Assoc Hydrological Sciences, 240, 365–376.
   Google Scholar
• Summerton, M., 2008. A preliminary assessment of the impact of climate change on the water resources of the uMgeni catchment. Report Number 160.8/R001/2008. Pietermaritzburg: Umgeni Water, Planning Services Department.
   Google Scholar
• Summerton, M., and Schulze, R., 2009. A framework for determining the possible impacts of a changing climate on water supply. In: Starrett, S. eds. World environmental and water resources congress 2009@ great rivers, 2012, Kansas City, MO, 4623–4633.
   Google Scholar
• Summerton, M., Schulze, R., and Graham, P., 2010. Impacts of a changing climate on hydrology and water supply in the Mgeni catchment, South Africa. In: Walsh, C. eds. Proceedings of the British hydrological society third international symposium, managing consequences of a changing global environment, Newcastle UK.
   Google Scholar
• Summerton, M., Schulze, R., and Liebscher, H., 2009, Hydrological consequences of a changing climate: the Umgeni Water utility case study. IAHS Publication, 327, 237.
   Google Scholar
• Tadross, M., Jack, C., and Hewitson, B., 2005, On RCM‐based projections of change in southern African summer climate. Geophysical Research Letters, 32 (23), 23–35. doi:10.1029/2005GL024460
   Web of Science ®Google Scholar
• Tarboton, K. and Schulze, R., 1992. Distributed hydrological modelling system for the mgeni catchment. Pretoria, South Africa: Water Research Commission.
   Google Scholar
• Teng, J., et al. 2012. Assessment of an analogue downscaling method for modelling climate change impacts on runoff. Journal of Hydrology, 472–473 (0), 111–125. doi:10.1016/j.jhydrol.2012.09.024
   Web of Science ®Google Scholar
• Vaze, J., et al. 2010. Climate non-stationarity–validity of calibrated rainfall–runoff models for use in climate change studies. Journal of Hydrology, 394 (3–4), 447–457. doi:10.1016/j.jhydrol.2010.09.018
   Web of Science ®Google Scholar
• Warburton, M., Schulze, R., and Jewitt, G., 2010, Confirmation of ACRU model results for applications in land use and climate change studies. Hydrology and Earth System Sciences, 14 (12), 2399–2414. doi:10.5194/hess-14-2399-2010
   Web of Science ®Google Scholar
• Warburton, M., Schulze, R., and Maharaj, M., 2005. Is South Africa’s temperature changing? An analysis of trends from daily records, 1950–2000. In: Schulze, R. eds. Climate change and water resources in southern Africa: studies on scenarios, impacts, vulnerabilities and adaptation (WRC Report 1430/1/05). Pretoria: Water Research Commission, 275–295.
   Google Scholar
• Warburton, M.L., Schulze, R.E., and Jewitt, G.P., 2012. Hydrological impacts of land use change in three diverse South African catchments. Journal of Hydrology, 414, 118–135. doi:10.1016/j.jhydrol.2011.10.028
   Web of Science ®Google Scholar
• Zhang, X., Xu, Y.-P., and Fu, G., 2014, Uncertainties in SWAT extreme flow simulation under climate change. Journal of Hydrology, 515 (0), 205–222. doi:10.1016/j.jhydrol.2014.04.064
   Web of Science ®Google Scholar
• Zhijia, L., et al., 2004. Coupling between weather radar rainfall data and a distributed hydrological model for real-time flood forecasting. Hydrological Sciences Journal, 49 (6), 945–958.
   Web of Science ®Google Scholar
• Zhu, D., Peng, D., and Cluckie, I., 2013, Statistical analysis of error propagation from radar rainfall to hydrological models. Hydrology and Earth System Sciences, 17 (4), 1445–1453. doi:10.5194/hess-17-1445-2013
   Web of Science ®Google Scholar