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Scientific and Practical Tools for Dealing with Water Resource Estimations for the Future : Volume 371, Issue 371 (12/06/2015)

By Hughes, D. A.

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Book Id: WPLBN0004021435
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Scientific and Practical Tools for Dealing with Water Resource Estimations for the Future : Volume 371, Issue 371 (12/06/2015)  
Author: Hughes, D. A.
Volume: Vol. 371, Issue 371
Language: English
Subject: Science, Proceedings, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Hughes, D. A. (2015). Scientific and Practical Tools for Dealing with Water Resource Estimations for the Future : Volume 371, Issue 371 (12/06/2015). Retrieved from http://www.ebooklibrary.org/


Description
Description: Institute for Water Research, Rhodes University, Grahamstown, South Africa. Future flow regimes will be different to today and imperfect knowledge of present and future climate variations, rainfall–runoff processes and anthropogenic impacts make them highly uncertain. Future water resources decisions will rely on practical and appropriate simulation tools that are sensitive to changes, can assimilate different types of change information and flexible enough to accommodate improvements in understanding of change. They need to include representations of uncertainty and generate information appropriate for uncertain decision-making. This paper presents some examples of the tools that have been developed to address these issues in the southern Africa region. The examples include uncertainty in present day simulations due to lack of understanding and data, using climate change projection data from multiple climate models and future catchment responses due to both climate and development effects. The conclusions are that the tools and models are largely available and what we need is more reliable forcing and model evlaution information as well as methods of making decisions with such inevitably uncertain information.

Summary
Scientific and practical tools for dealing with water resource estimations for the future

Excerpt
Gao, H., Hrachowitz, M., Schymanski, S. J., Fenicia, F., Sriwongsitanon, N., and Savenije, H. H. G.: Climate controls how ecosystems size the root zone storage capacity at catchment scale, Geophys. Res. Lett., 41, 7916–7923, 2014.; Görgens, A. H. M. and Van Wilgen, B. W.: Invasive alien plants and water resources in South Africa: Current understanding, predictive ability and research challenges, S. Afr. J. Sci., 100, 27–33, 2004.; Hewitson, B. and Crane, R.: Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa, Int. J. Climatol., 26, 1315–1337, 2006.; Hrachowitz, M., Savenije, H. H. G., Blöschl, G., McDonnell, J. J., Sivapalan, M., Pomeroy, J. W., Arheimer, B., Blume, T., Clark, M. P., Ehret, U., Fenicia, F., Freer, J. E., Gelfan, A., Gupta, H. V., Hughes, D. A., Hut, R. W., Montanari, A., Pande, S., Tetzlaff, D., Uhlenbrook, S., Wagener, T., Winsemius, H. C., and Woods, R. A.: A decade of Predictions in Ungauged Basins (PUB) – a review, Hydrolog. Sci. J., 58, 1198–1255, 2013.; Hughes, D. A.: A review of 40 years of hydrological science and practice in southern Africa using the Pitman rainfall–runoff model, J. Hydrol., 501, 111–124, 2013.; Hughes, D. A.: Simulating temporal variability in catchment response using a monthly rainfall–runoff model, Hydrolog. Sci. J., doi:10.1080/02626667.2014.909598, in press, 2014.; Hughes, D. A. and Mantel, S. K.: Estimating the uncertainty in the impacts of small farm dams on stream flow regimes in South Africa, Hydrolog. Sci. J., 55, 578–592, 2010.; Hughes, D. A., Mantel, S., and Mohobane, T.: An assessment of the skill of downscaled GCM outputs in simulating historical patterns of rainfall variability, Hydrol. Res., 45, 134–147, 2014.; Kalognomou, E.-A., Lennard, C., Shongwe, M., Pinto, I., Favre, A., Kent, M., Hewitson, B., Dosio, A., Nikulin, G., Panitz, H.-J., and Büchner, M.: A diagnostic evaluation of precipitation in CORDEX models over Southern Africa, J. Climate, 26, 9477–9506, 2013.; Kapangaziwiri, E., Hughes, D. A., and Wagener, T.: Constraining uncertainty in hydrological predictions for ungauged basins in southern Africa, Hydrolog. Sci. J., 57, 1000–1019, 2012.; Matrosov, E. S., Woods, A. M., and Harou, J. J.: Robust Decision Making and Info-Gap Decision Theory for water resource system planning, J. Hydrol., 494, 43–58, 2013.; Montanari, A., Young, G., Savenije, H., Hughes, D. A., Wagener, T., Ren, L., Koutsoyiannis, D., Cudennec, C., Grimaldi, S., Bloeschl, G., Sivapalan, M., Beven, K., Gupta, H., Arheimer, B., Huang, Y., Schumann, A., Post, D., Srinivasan, V., Boegh, E., Hubert, P., Harman, C., Thompson, S., Rogger, M., Hipsey, M., Toth, E., Viglione, A., Di Baldassarre, G., Schaefli, B., McMillan, H., Schymanski, S. J., Characklis, G., Yu, B., Pang, Z., and Belyaev, V.: Panta Rhei – Everything Flows: Change in hydrology and society – The IAHS Scientific Decade 2013–2022, Hydrolog. Sci. J., 58, 1256–1275, 2013.; Pappenberger, F. and Beven, K.: Ignorance is bliss: Or seven reasons not to use uncertainty analysis, Water Resour. Res., 42, W05302, doi:10.1029/2005WR004820, 2006.; Pomeroy, J. W., Spence, C., and Whitfield, P. H. (Eds.): Putting Prediction in Ungauged Basins into Practice, Canadian Water Resources Association, Canada, 2014.; Srikanthan, R. and Pegram, G. G. S.: A nested multisite daily rainfall stochastic generation model, J. Hydrol., 371, 142–153, 2009.; Tristam, D., Hughes, D. A., and Bradshaw, K.: Accelerating a hydrological uncertainty ensemble model using Graphics Processing Units (GPUs), Comput. Geosci., 62, 178–186, 2014.; Tumbo, M. and Hughes, D. A.: Uncertain hydrological modelling: Application of the Pitman model in the Great Ruaha River Basin, Tanzania, Hydrolog. Sci. J., doi:10.1080/02626667.2015


 

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