The potential impacts of up-scaled rainwater harvesting on ecosystem goods and services in the Potshini and Makanya catchments.

Abstract

Water scarcity is fast becoming a global concern, with at least each continent facing water-related issues regarding quantity, quality and delivery. An estimated 8.8% of South Africans do not have access to potable water, according to the World Wildlife Fund’s 2011 South African census (2016). The inaccessibility to water for domestic, agricultural or economic activities directly impacts on food security and poverty. Communities living in rural surroundings and depending directly on the environment to support their livelihoods are most affected by water shortages. The 1.2 km2 Potshini Catchment, located in the foothills of the Drakensburg Mountains in South Africa, and the 300 km2 Makanya Catchment, situated on the western side of the South Pare Mountains in Tanzania, provide good case studies to assess how communities, vulnerable to poverty and food security, cope with water shortages. Both catchments have well-established rainwater harvesting (RWH) networks that supplement the rainfed subsistence crops. RWH is a method of capturing, conveying and storing rainwater and runoff for future use. It is a valuable practice in agriculture, intended to improve the availability of water to crops towards the end of high rainfall months and during dry-spells. The conservation of water, in these instances, has the potential to secure and improve livelihoods, and to lessen the pressure placed on ecosystem goods and services. Albeit that RWH is an alternative water innovation, supporting the ideals of integrative water resource management, the impacts of up-scaled RWH on streamflow are still to be determined. Little is known about how ecosystem goods and services will respond to the expansion of RWH, as well as the presence of a feedback mechanism. Therefore, the aim of this study was gain a better understanding of the nature of RWH and its potential impacts on the environment in the form of a literature review. Secondly, a hydrological method or tool was developed to understand the impacts of RWH on ecosystem goods and services, in order to improve the catchment management of upstream and downstream communities alike. This was achieved by determining the relevant ecosystem goods and services within each catchment. Thereafter, the impacts of RWH on streamflow and soil moisture were determined by hydrological modelling of each catchment, using the ACRU Model. Using a scenario-based approach, the limits to RWH may be determined by increasing the level of water harvested in each case. Once the significance of this has been determined, the impact on related ecosystem goods and services can be understood. The Makanya and Potshini Catchments are located in rural settlements, whose population relies mostly on the environment for daily survival. Ecosystem goods and services, such as water supply and regulation, are high priority benefits. Water is supplied, filtered and purified through natural processes in the environment, whilst floods and droughts are regulated. Through the promotion of infiltration and reduced flow velocities by vegetation, the ecosystem controls the harsh effects of natural variability. Soil formation and retention assists the growth of crops through the facilitation of soil water infiltration and the transport of nutrients from the topsoil. Other basic goods and services within the catchments are the provision of food (fauna and flora), raw materials, and natural habitats for breeding, as well as cultural and recreational areas. The ACRU Model was successful in simulating daily streamflow and soil moisture in the Makanya and Potshini Catchments. A general reduction in streamflow as a result of increased RWH was modelled over the 56-year study period between 1952 and 2007, for both catchments. A virtual dam within the ACRU model is created to capture rainfall. Increased RWH scenarios are based on 30%, 60% and 90% of the current RWH conditions. It has been estimated that harvesting runoff in the drier months of the year could have the greatest impact on the environment, as low flows are initially reduced by a lack of rainfall. As RWH was increased, a gradual reduction in baseflow was modelled for the Potshini Catchment, whilst baseflows were reduced to zero mm in the Makanya Catchment, as rivers ran dry in low rainfall seasons. When compared to the baseline, the cumulative streamflow over the study period was reduced by 50% and 30%, respectively, in the Makanya and Potshini Catchments. This reduction was significant at all levels (30%, 60% and 90% increase in RWH relative to current conditions) of RWH in Makanya, whilst scenarios up-scaling RWH over 60% had a significant impact on the ecosystem in Potshini (95% confidence interval based on a t-test). The introduction and up-scaling of RWH had a positive impact on soil moisture, increasing total soil water content values far above the baseline values. Harvested water is allocated for irrigation to improve crop yields. Increased water availability improved crop yields up to 50% (assuming no other crop stress occurred), particularly in the Potshini Catchment, thus potentially improving food security within rural communities. Improved soil moisture through RWH acts a means of mitigating the reduction of streamflow downstream. Water is reallocated in the ecosystem and used to improve the delivery of goods and services for human benefit. Whilst, the environment may have the ability to absorb the initial shock, the continual expansion of RWH has the potential to reduce the resilience of the environment and the goods and services they provide. The large-scale employment of RWH over a long period can attest to a portion of the degradation found in the Makanya Catchment. This is commonly known as a negative feedback mechanism. As a result of improved crop yields, greater expanses of the catchment are converted to runoff generation areas, to increase the opportunities for harvesting water. As agriculture expands and population densities increase, further threats to the environment are created. Although future predictions cannot be accurately made, it is necessary to attempt to understand the possible outcomes of various theories. The accuracy of this scenario-based research is limited by the accuracy by which each scenario represents RWH, the accuracy with which ACRU represent all key processes and quality of historical data used. However, this study presents a method to determine the likely limits to up-scaling RWH in water-scarce regions, in order to safeguard the integrity of the environment for future generations.