A comparative assessment of water use by Acacia longifolia invasions occurring on hillslopes and riparian zones in the Cape Agulhas region of South Africa

Abstract. In South Africa, the invasion of riparian forests by alien trees has the potential to affect the country's limited water resources. Tree water-use measurements have therefore become an important component of recent hydrological studies. It is difficult for South African government initiatives, such as the Working for Water (WfW) alien clearing program, to justify alien tree removal and implement rehabilitation unless hydrological benefits are known. Consequently, water use within a riparian forest along the Buffeljags River in the Western Cape of South Africa was monitored over a 3-year period. The site consisted of an indigenous stand of Western Cape afrotemperate forest adjacent to a large stand of introduced Acacia mearnsii. The heat ratio method of the heat pulse velocity sap flow technique was used to measure the sap flow of a selection of indigenous species in the indigenous stand, a selection of A. mearnsii trees in the alien stand and two clusters of indigenous species within the alien stand. The indigenous trees in the alien stand at Buffeljags River showed significant intraspecific differences in the daily sap flow rates varying from 15 to 32 L day−1 in summer (sap flow being directly proportional to tree size). In winter (June), this was reduced to only 7 L day−1 when limited energy was available to drive the transpiration process. The water use in the A. mearnsii trees showed peaks in transpiration during the months of March 2012, September 2012 and February 2013. These periods had high average temperatures, rainfall and high daily vapor pressure deficits (VPDs – average of 1.26 kPa). The average daily sap flow ranged from 25 to 35 L in summer and approximately 10 L in the winter. The combined accumulated daily sap flow per year for the three Vepris lanceolata and three A. mearnsii trees was 5700 and 9200 L, respectively, clearly demonstrating the higher water use of the introduced Acacia trees during the winter months. After spatially upscaling the findings, it was concluded that, annually, the alien stand used nearly 6 times more water per unit area than the indigenous stand (585 mm a−1 compared to 101 mm a−1). This finding indicates that there would be a gain in groundwater recharge and/or streamflow if the alien species are removed from riparian forests and rehabilitated back to their natural state.

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The 8%-4% debate: Commercial afforestation and water use in South Africa

The Southern African Forestry Journal ◽

10.1080/20702620.2002.10434586 ◽

2002 ◽

Vol 194 (1) ◽

pp. 1-5 ◽

Cited By ~ 5

Keyword(s):

South Africa ◽

Water Use

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Optimization of irrigation water in South Africa for sustainable and beneficial use

10.51415/10321/2467 ◽

2017 ◽

Author(s):

◽

Akinola Mayowa Ikudayisi

Keyword(s):

South Africa ◽

Water Use ◽

Crop Yield ◽

Optimization Algorithm ◽

Irrigation Water ◽

Irrigation Scheduling ◽

Crop Water ◽

Land Area ◽

Water Requirements ◽

Irrigation Water Use

Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.

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A comparative assessment of the contribution of two different models for clearing invasive alien plants using grazing regimes in the Eastern Cape, South Africa

African Journal of Range and Forage Science ◽

10.2989/10220119.2020.1750483 ◽

2020 ◽

Vol 37 (3) ◽

pp. 226-236

Author(s):

T Morokong ◽

JN Blignaut

Keyword(s):

South Africa ◽

Alien Plants ◽

Comparative Assessment ◽

Eastern Cape ◽

Invasive Alien Plants

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Analysis of virtual water flows associated with the trade of maize in the SADC region: importance of scale

Hydrology and Earth System Sciences ◽

10.5194/hess-13-1967-2009 ◽

2009 ◽

Vol 13 (10) ◽

pp. 1967-1977 ◽

Cited By ~ 15

Author(s):

J. M. Dabrowski ◽

E. Masekoameng ◽

P. J. Ashton

Keyword(s):

South Africa ◽

Water Use Efficiency ◽

Water Content ◽

Water Use ◽

Water Scarcity ◽

Virtual Water ◽

Blue Water ◽

Maize Production ◽

Water Flows ◽

Use Efficiency

Abstract. The concept of virtual water encourages a country to view agricultural crops in terms of the amount of water required to produce those crops, with a view to implementing trading policies that promote the saving of scarce water resources. Recently, increased attention has focussed on partitioning the virtual water content of crops into green and blue water (derived from rainfall and irrigation, respectively) as the latter has higher opportunity costs associated with its use and therefore impacts directly on scarcity. Maize is the most important crop traded within the SADC region. South Africa is the largest producer and exporter of maize, with the majority of its exports destined for other SADC countries. In comparison to other SADC countries, South Africa produces maize relatively efficiently, with a low virtual water content and a high green (868 m3 t−1) to blue (117 m3 t−1) water ratio. The blue water content is however higher than for maize produced in all other SADC countries, with the exception of Namibia (211 m3 t−1). Current trade patterns therefore result in a net expenditure of blue water (66×106 m3), almost all of which is exported by South Africa (65×106 m3). South Africa is one of the most water scarce countries in the region and analysis of virtual water flows indicates that current SADC maize trading patterns are influenced by national productivity as opposed to water scarcity. The virtual water content of maize was estimated for each of South Africa's nineteen Water Management Area's (WMA) and used as a proxy to represent water use efficiency for maize production. The virtual water content varied widely across all of the WMAs, ranging from 360 m3 t−1 in the Ustutu Mhlatuze to 1000 m3 t−1 in the Limpopo. A comparison of the virtual water content and production of maize (expressed as a percentage of the total national production) identified those WMAs where maize production is highly water inefficient (e.g. Lower Orange and Limpopo WMAs). Results suggest that, while a national estimate of the virtual water content of a crop may indicate a relatively efficient use of water, an analysis of the virtual water content at smaller scales can reveal inefficient use of water for the same crop. Therefore, analysis of the virtual water content of crops and trading of agricultural products at different spatial scales (i.e. regional, national and WMA) could be an important consideration within the context of water allocation, water use efficiency and alleviation of water scarcity.

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