Water resources planning and modelling tools for the assessment of land use change in the Luvuvhu Catchment, South Africa

Jewitt, Graham; Garratt, James; Calder, Ian R.; Fuller, L.

doi:10.1016/j.pce.2004.09.020

Cited by 52 publications

(28 citation statements)

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“…Based on the simulation results presented above and that the E f ranged between 0.847 and 0.597, it is suggested that the ACRU model can be used with confidence to simulate the streamflows of the Mgeni, Luvuvhu and Upper Breede Catchments. The ACRU model has been used to aid decision-making in South Africa, and applied in numerous hydrological designs, water resource assessments and research projects both in South Africa and internationally (Schulze, and George, 1987;Schulze, 1988;Smithers, 1991;Tarboton, and Schulze, 1991;Smithers, and Caldecott, 1993;New and Schulze, 1996;Butterworth et al, 1999;Jewitt and Schulze, 1999;Smithers et al, 2001;Schulze and Smithers, 2004;Jewitt et al, 2004;Kiker et al, 2006). To demonstrate the model's ability and acceptance, confirmation studies, and in particular confirmation studies at a daily time interval, need to be undertaken.…”

Section: Discussionmentioning

confidence: 99%

“…The ACRU model has been applied extensively in South Africa for both land use impact studies (e.g. Schulze and George, 1987;Tarboton and Schulze, 1990;Kienzle and Schulze, 1995;Kienzle et al, 1997;Schulze et al, 1997;Jewitt and Schulze, 1999;Schulze, 2000;Jewitt et al, 2004) and climate change impact studies (Perks and Schulze, 1999;Perks, 2001;. Additionally, the ACRU model has been applied in Zimbabwe (Butterworth et al, 1999;Makoni, 2001), Eritrea (Ghile, 2004), the USA (Martinez et al, 2008), Germany (Herpertz, 1994;Herpertz, 2001) and more recently in New Zealand (Kienzle and Schmidt, 2008;Schmidt et al, 2009) and Canada (Forbes et al, 2010).…”

Section: The Acru Agrohydrological Modelmentioning

confidence: 99%

“…Available and good quality observed streamflow data were a constraint for the confirmation study in the Luvuvhu catchment. However, based on a previous study by Jewitt et al (2004), the Upper Mutale WMU (Fig. 4) presented an ideal opportunity for a confirmation study as high quality streamflow data were available and additionally the land use and climate was representative of the larger Luvuvhu catchment (Table 3).…”

Section: Luvuvhu Catchmentmentioning

confidence: 99%

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Confirmation of <i>ACRU</i> model results for applications in land use and climate change studies

Warburton

Schulze

Jewitt

2010

Hydrol. Earth Syst. Sci.

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Abstract. The hydrological responses of a catchment are sensitive to, and strongly coupled to, land use and climate, and changes thereof. The hydrological responses to the impacts of changing land use and climate will be the result of complex interactions, where the change in one may moderate or exacerbate the effects of the other. Further difficulties in assessing these interactions are that dominant drivers of the hydrological system may vary at different spatial and temporal scales.To assess these interactions, a process-based hydrological model, sensitive to land use and climate, and changes thereof, needs to be used. For this purpose the daily time step ACRU model was selected. However, to be able to use a hydrological model such as ACRU with confidence its representation of reality must be confirmed by comparing simulated output against observations across a range of climatic conditions. Comparison of simulated against observed streamflow was undertaken in three climatically diverse South African catchments, ranging from the semi-arid, sub-tropical Luvuvhu catchment, to the winter rainfall Upper Breede catchment and the sub-humid Mgeni catchment. Not only do the climates of the catchments differ, but their primary land uses also vary. In the upper areas of the Mgeni catchment commercial plantation forestry is dominant, while in the middle reaches there are significant areas of commercial plantation sugarcane and urban areas, while the lower reaches are dominated by urban areas. The Luvuvhu catchment has a large proportion of subsistence agriculture and informal residential areas. In the Upper Breede catchment in the Western Cape, commercial orchards and vineyards are the primary land uses.Correspondence to: M. L. Warburton (warburtonm@ukzn.ac.za) Overall the ACRU model was able to represent the high, low and total flows, with satisfactory Nash-Sutcliffe efficiency indexes obtained for the selected catchments. The study concluded that the ACRU model can be used with confidence to simulate the streamflows of the three selected catchments and was able to represent the hydrological responses from the range of climates and diversity of land uses present within the catchments.

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Section: Discussionmentioning

confidence: 99%

Section: The Acru Agrohydrological Modelmentioning

confidence: 99%

Section: Luvuvhu Catchmentmentioning

confidence: 99%

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Confirmation of <i>ACRU</i> model results for applications in land use and climate change studies

Warburton

Schulze

Jewitt

2010

Hydrol. Earth Syst. Sci.

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“…In order to manage water in a sustainable manner, it is important to have a sound understanding of the processes that control its existence, the variability in time and space, and our ability to quantify that variability (Jewitt et al, 2004;Hu et al, 2011;Montanari et al, 2013;Hughes et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Drivers of spatial and temporal variability of streamflow in the Incomati River basin

Okello

Masih

Uhlenbrook

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. The Incomati is a semi-arid trans-boundary river basin in southern Africa, with a high variability of streamflow and competing water demands from irrigated agriculture, energy, forestry and industries. These sectors compete with environmental flows and basic human water needs, resulting in a "stressed" water resource system. The impacts of these demands, relative to the natural flow regime, appear significant. However, despite being a relatively well-gauged basin in South Africa, the natural flow regime and its spatial and temporal variability are poorly understood and remain poorly described, resulting in a limited knowledge base for water resource planning and management decisions. Thus, there is an opportunity to improve water management, if it can be underpinned by a better scientific understanding of the drivers of streamflow availability and variability in the catchment.In this study, long-term rainfall and streamflow records were analysed. Statistical analysis, using annual anomalies, was conducted on 20 rainfall stations, for the period 1950-2011. The Spearman test was used to identify trends in the records on annual and monthly timescales. The variability of rainfall across the basin was confirmed to be high, both intraand inter-annually. The statistical analysis of rainfall data revealed no significant trend of increase or decrease. Observed flow data from 33 gauges were screened and analysed, using the Indicators of Hydrologic Alteration (IHA) approach. Temporal variability was high, with the coefficient of variation of annual flows in the range of 1 to 3.6. Significant declining trends in October flows, and low flow indicators, were also identified at most gauging stations of the Komati and Crocodile sub-catchments; however, no trends were evident in the other parameters, including high flows. The trends were mapped using GIS and were compared with historical and current land use. These results suggest that land use and flow regulation are larger drivers of temporal changes in streamflow than climatic forces. Indeed, over the past 40 years, the areas under commercial forestry and irrigated agriculture have increased over 4 times.

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“…Hydrological models use observed meteorological data to simulate streamflow, and are often verified using observed streamflow or other measurable hydrological variables (Rosso 1994, Brooks et al 2007, Liu et al 2009. A model should be able to reasonably reproduce historical streamflow records, in order to be used in climate change studies, and can only be applied with confidence once the model output has been verified against observed data (Loukas et al 2002, Jewitt et al 2004. Models are simplifications of reality, but are important tools in assessing future scenarios for water management strategies, if accurately parameterized and verified (Beven 1989).…”

Section: Introductionmentioning

confidence: 99%

Multi-variable verification of hydrological processes in the upper North Saskatchewan River basin, Alberta, Canada

Nemeth¹,

Kienzle

Byrne

2012

Hydrological Sciences Journal

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The ACRU agro-hydrological modelling system was set up to simulate the impacts of climate change on the hydrological responses of the 3856-km 2 Cline River watershed, the major headwater of the upper North Saskatchewan River basin in central Alberta, Canada. The physical-conceptual ACRU model was set up to simulate all elements of the hydrological cycle on a daily time step for the 1961-1990 baseline period, to serve as the basis for later climate change impact simulations. After parameterization, the output from the ACRU model was verified against temperature, snow water equivalent, glacier mass balance, potential evapotranspiration, and two sets of long-term daily streamflow records. The multi-variable verification analyses were implemented to instil confidence that the simulated streamflow time series is based on a realistic combination of bio-physical parameters and represents the watershed behaviour in terms of annual water yields, seasonality, shape and magnitude of the hydrographs, and streamflow variability.Key words hydrological simulation model; streamflow; snow; glacier; verification; ACRU model; Canada Vérification multi-variable des processus hydrologiques dans le bassin supérieur de la rivière North Saskatchewan, Alberta, Canada Résumé Le système de modélisation agro-hydrologique ACRU a été mis en place pour simuler les impacts des changements climatiques sur les réponses hydrologiques du bassin versant de la Rivière Cline (3856 km 2 ), source majeure du bassin supérieur de la rivière North Saskatchewan dans le centre de l'Alberta, au Canada. Le modèle physique-conceptuel ACRU a été mis en place pour simuler tous les éléments du cycle hydrologique au pas de temps journalier pour la période de référence 1961-1990, pour servir de base à des simulations ultérieures des impacts des changements climatiques. Après le paramétrage, les sorties du modèle ACRU ont été vérifiées sur la température, l'équivalent en eau de la neige, le bilan de masse des glaciers, l'évapotranspiration potentielle, et deux enregistrements de long terme de débits quotidiens. Les analyses de vérification multi-variables ont été mises en oeuvre pour s'assurer que la série des débits simulés est basée sur une combinaison réaliste de paramètres biophysiques et représente le comportement du bassin versants en termes d'écoulement annuel, de saisonnalité, de forme et d'ampleur des hydrogrammes et de variabilité du débit.

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Water resources planning and modelling tools for the assessment of land use change in the Luvuvhu Catchment, South Africa

Cited by 52 publications

References 5 publications

Confirmation of <i>ACRU</i> model results for applications in land use and climate change studies

Confirmation of <i>ACRU</i> model results for applications in land use and climate change studies

Drivers of spatial and temporal variability of streamflow in the Incomati River basin

Multi-variable verification of hydrological processes in the upper North Saskatchewan River basin, Alberta, Canada

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Water resources planning and modelling tools for the assessment of land use change in the Luvuvhu Catchment, South Africa

Cited by 52 publications

References 5 publications

Confirmation of &lt;i&gt;ACRU&lt;/i&gt; model results for applications in land use and climate change studies

Confirmation of &lt;i&gt;ACRU&lt;/i&gt; model results for applications in land use and climate change studies

Drivers of spatial and temporal variability of streamflow in the Incomati River basin

Multi-variable verification of hydrological processes in the upper North Saskatchewan River basin, Alberta, Canada

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Confirmation of <i>ACRU</i> model results for applications in land use and climate change studies

Confirmation of <i>ACRU</i> model results for applications in land use and climate change studies