Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Copernicus Publicati...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Copernicus Publications
Other ORP type . 2018
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Identification and simulation of space–time variability of past hydrological drought events in the Limpopo River basin, southern Africa

Authors: Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.;

Identification and simulation of space–time variability of past hydrological drought events in the Limpopo River basin, southern Africa

Abstract

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer-resolution version (0.05° × 0.05°) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979–2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

50 references, page 1 of 5

Abramowitz, M. and Stegun, I. A.: Handbook of mathematical functions, with formulas, graphs, and mathematical tables, Dover Publications, Dover, 1046 pp., 1965.

Allen, R. G., Pereira, L., Raes, D., and Smith, M.: Crop evapotranspiration - Guidelines for computing crop water requirements, FAO Irrigation and drainage paper No. 56, FAO, Rome, 26-40, 1998.

Alley, W. M.: The Palmer Drought Severity Index: Limitations and Assumptions, J. Clim. Appl. Meteorol., 23, 1100-1109, doi:10.1175/1520-0450(1984)023<1100:tpdsil>2.0.co;2, 1984.

Alston, M. and Kent, J.: Social impacts of drought, Centre for Rural Social Research, Charles Sturt University, Wagga Wagga, NSW, 2004.

Balsamo, G., Boussetta, S., Lopez, P., and Ferranti, L.: Evaluation of ERA-Interim and ERA-Interim-GPCP-rescaled precipitation over the USA, ECMWF ERA Report Series 5, 1-25, available at: http://www.ecmwf.int/publications/library/do/references/list/ 782009 (last access: December 2013), 2010.

Barbosa, P., Naumann, G., Valentini, L., Vogt, J., Dutra, E., Magni, D., and De Jager, A.: A Pan-African map viewer for drought monitoring and forecasting, 14th Waternet Symposium, 30 October-1 November 2013, Dar es Salaam, Tanzania, 2013.

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553- 597, doi:10.1002/qj.828, 2011.

Department of Agriculture of South Africa: Crops and markets - First quarter 2006, Vol. 87, No. 927, Directorate Agricultural Statistics - Department of Agriculture, http://www.daff.gov. za/docs/statsinfo/Crops_0106.pdf (last access: December 2013), 2006.

DEWFORA: WP6-D6.1 - Implementation of improved methodologies in comparative case studies - Inception report for each case study, DEWFORA Project - EU FP7, www.dewfora.net (last access: December 2013), 2012.

Dube, O. P., and Sekhwela, M. B. M.: Community coping strategies in Semiarid Limpopo basin part of Botswana: Enhancing adaptation capacity to climate change, 1-40, http://www.aiaccproject.org/working_papers/Working% 20Papers/AIACCWP47_Dube.pdf (last access: December 2013), 2007.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    Powered byBIP!BIP!
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Funded by
Related to Research communities