A New Methodological Framework for the Determination of Water Resource Classes and Resource Quality Objectives: A Case Study for the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7)

Abstract

The current paper determined water resource classes and Resource Quality Objectives (RQOs) for significant water resources in the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7) to facilitate sustainable use of the water resources while maintaining ecological integrity. A novel stepwise quantitative and qualitative method was developed to ensure water resource protection in the study area. The methodological approach is proposed as a model framework that could be adopted as guideline and transferable to other catchments in the implementation of Resource Directed Measures (RDMs). The method used water quality and quality components of water resources to determine the classes and RQOs. The study’s major findings were that nineteen Integrated Units of Analysis (IUAs) were delineated, and ninety-five Resource Units were identified and prioritized for both surface and groundwater. Driving water quality variables (nutrients, electrical conductivity, and Escherichia coli) were observed and primary water users (irrigation, settlements, and wastewater treatment works) were identified per Integrated Units of Analysis. Five water resource scenarios were developed and evaluated to capture a likely water resource condition for the present and future. The scenario analysis showed impact is expected under any of the operational scenarios assessed at selected reaches. The water resource classes were determined, with eleven IUAs classified as Class lll, seven IUAs as Class ll, and one IUA as Class l. Water quality and quantity RQOs were set to ensure that both river and groundwater resources are compliant and protected. Therefore, the study recommends that this methodological framework, where classes and RQOs were determined, needs to be implemented and tested.

1. Introduction

Globally, water resources are regarded as the most essential resources for development and human survival [1]. A study by World Wildlife Fund [2] reported that exploitation of these resources has increased over the world and threatened prospects for socio-economic development, political stability, and ecosystem integrity. Further, the study discovered that since 1970, about 30% of global freshwater ecosystems have degraded, and 84% of global freshwater species populations have been lost.

In South Africa, Gassert et al. [3] reported that the country falls into the high-water stress class and has less water per person than countries widely considered being much drier such as Namibia and Botswana. In addition, a study by Pienaar et al. [4] revealed that many catchments in the country are fast approaching a point at which all the available freshwater resources are fully utilized. To ensure a sustainable water balance requires a multitude of strategies, which include water resource protection, water conservation, water demand management, and an increased use of previously under-utilized resources such as groundwater, desalination of seawater, water re-use, rainwater harvesting, and treating Acid Mine Drainage [4]. A study by Makanda et al. [5] indicated that water resource protection is central to improving instream water quality and water supply for basic human needs and ecological ecosystem functioning. As a result, water resource managers have a responsibility of ensuring that policy objectives on protection of water resource and sustainable water use are achieved and maintained [5].

The South African National Water Act [6] (Act 36 of 1998) provides for the protection of water resources through three main measures, namely, (1) classification of water resources; (2) determination of the Reserve; and (3) setting the Resource Quality Objectives (RQOs) for the selected class. These together form the Resource Directed Measures (RDMs) described in detail in Chapter 3 of the Act. In addition, these measures provide sustainable use of water resources by ensuring protection of water resources by striking a balance between protection and use of water resources [7].

The South African Department of Water and Sanitation is mandated by the Act to implement the measures across all catchments in the country. Therefore, the balance between water resource protection and water uses is significant to achieve aquatic ecosystem integrity, sustainability, and socio-economic development [8]. The classification of water resources represents the first stage in the protection of the resources by determining water resource classes (i.e., Class I, II, and III) for significant water resources [4]. Further, the Act defines three water resource classes reflecting a gradual shift from resources that will be minimally used to those that are heavily utilized [4]. On the other hand, RQOs define the water resource classes and further give directions to resource managers on how the resource should be managed. Further, the resource managers give effect to this through the allocation of water use licenses, with the resulting impacts being constrained by the overall quality of the resource as set by RQOs [9]. A study by WRC [10] indicated that these measures (water resource classes and Resource Quality Objectives) are important for water resource protection by informing decisions regarding the authorization of future water use and putting appropriate water use conditions to the proposed developments.

However, due to budgetary constraints and lack of resources, the implementation of Chapter 3 of the Act has not yet been undertaken across all catchments, and/or the implementation process is moving at a slow pace. The Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7) is understudied, and there are no measures in place to protect water resources. A study by Mulangaphuma et al. [11] revealed that water quality remained a challenge in WMA7. The study identified parameters of concern such as phosphate (PO₄), ammonia (NH₄), and nitrate + nitrite (NO₃ + NO₂), which did not comply with the South African Water Quality Guidelines limits, suggesting that the WMA7 was impacted by anthropogenic activities such as industry, sewage works, agriculture (irrigation), etc. Further, the groundwater quality assessment found that the main parameters of concern were electrical conductivity (EC), NO₃ + NO₂, and sulphate (SO₄). Subsequently, a study by Mulangaphuma and Jovanovic [12] investigated the increase in water use or water abstraction recorded in the study area. The study identified that increase in water use was a possible cause of water quality deterioration. The study found that agriculture (irrigation) was the largest water user for both surface and groundwater, with an estimated 60% of the total requirement. Therefore, the study results necessitated the need for the determination of water resource classes and Resource Quality Objectives to strike a balance between resource protection and use in the study area.

Based on the reported water quality and use challenges in the study area, the overall aim of the current study is to determine water resource classes and Resource Quality Objectives for significant water resources in the WMA7 to facilitate sustainable use of the water resources while maintaining ecological integrity. The specific objectives were (1) to delineate the study area into Integrated Units Analysis and priority Resource Units; (2) to identify driving water quality variables within the Integrated Units of Analysis; (3) to identify water resource scenarios and evaluate their implications to resource quality and quantity; and (4) to determine water resource classes for Integrated Units of Analysis and then set Resource Quality Objectives for prioritized Resource Units. Due to the diversity and complexity of water use patterns and socio-economic development, a clear understanding between water use, water quality, and resource protection measures remains elusive. The demand for water by sectors continues to rise, and water quality deterioration provides a serious water resource management challenge. The current study diverted from the traditional RDM method by focusing on quality and quantity components to strike a balance between water resource protection and use. No research has comprehensively explored the balance between use and protection of water resources, though it has been advocated much in the National Water Act (NWA). The implementation of these measures to address water quality and quantity challenges becomes of central importance for sustainable water supply in the WMA7. Further, this will assist the South African Department of Water and Sanitation in the management of water resources in the WMA7 and aid in making informed decisions regarding the authorization of the future use of water.

2. Materials and Methods

This section provides a study area description and detailed methodology used to address the four objectives of the study. It is envisaged that the methodological framework for determining water resource classes and Resource Quality Objectives developed in the current study could be used as an ideal guideline and transferable to other catchments in the country.

2.1. Study Area Description

The study area is largely situated in the Eastern Cape Province of the Republic of South Africa [11]. The study area consists of 345 quaternary catchments and covers an area of approximately 143,382 km². The climate is strongly influenced by its location relative to the sea and topography [12]. Figure 1 shows the location of the Water Management Area 7 (WMA7).

Figure 1 shows that the study area is subdivided into different primary catchments, namely, the Great Kei (S), Great Fish (Q), Mbashe (T), Sundays (N), and Gamtoos (L), and some smaller coastal systems (such as Swartkop (M), Keiskamma (R), and Kouga (P)). Each primary catchment is represented by a single letter, corresponding to distinct natural boundaries that reflect the flow of water across regions [12].

The Mzimvubu to Tstsikamma Water Management Area (WMA7) is characterized by various water resources, i.e., rivers, groundwater, wetlands, estuaries, and dams. The rivers range from large perennial to semi-ephemral with small costal systems, which drains towards the Indian Ocean [13]. Further, the major rivers (catchments) include the Gamtoos, Sundays, Great Fish, Great Kei, Mzimvubu, and Mbashe, as well as smaller river systems in-between. The study area is further characterized by a total of 30,171 ha (hectares) of channeled, unchanneled valley-bottom and pan or depression wetlands [13]. According to a study by DWS [13], the majority of wetlands are in good ecological condition, ranked either A or B (natural to largely natural). In terms of groundwater, the study area is characterized by major aquifer systems such as the Karoo and Cape Supergroups [11]. These systems are mainly of a fractured type, where groundwater occurrence is due to secondary deformation relating to faults, bedding planes, fractures, fissures, and joints [11]. In terms of estuaries, the study area comprises 154 estuaries and an additional 97 microsystems [13]. In addition, these systems spread over two biogeographic areas, namely, subtropical and warm temperate bioregions. In the study area, there are large dams in the Great Fish and Gamtoos River catchments, which transfer water between catchments for irrigation and domestic purposes [12].

In the study area, irrigated lands occupy about 948 km² along the Great Fish, Kat, and Sunday rivers, using water from the Orange River through a transfer scheme, with the main crops including vegetables, citrus, and lucerne [12]. Further, the study reported that afforestation occupies land of about 417 km² in the Tsitsikamma area. The study area contributes a total of 7.7% of the national Gross Domestic Products (GDPs), and the economy is mainly supported by the tertiary sector (wholesale and retail trade, tourism, and communications), followed by the sectors of manufacturing (large proportion by the automotive sub-sector), agriculture, and agro-processing [13]. In addition, the study area consists of several large and small dams, which allow for water transfers between catchments. One of the largest transfer schemes in the WMA7 is water transferred from the Gariep Dam in the Upper Orange WMA to the upper reaches of the Great Fish River (Grassridge Dam). Mulangaphuma et al. [11] reported that the study area’s basement rocks consist mainly of quartzite, limestone, and phyllite, which are unconformably overlain by the Cape Supergroup, Table Mountain, Bokkeveld, and Witteberg groups of alternating quartzitic sandstone and shale.

2.2. Methodology

Stepwise quantitative and qualitative methods were applied to guide the process for the determination of water resource classes and Resource Quality Objectives in the study area. Traditionally, the methodological approach for the determination of RDMs (classification, the Reserve, and RQO) is a 7-step process, as outlined by UNDP-GEF [14] and Makanda et al. [1,5]. The methodological approach covered the following: ecosystem services, socio-economic, ecological water requirements, basic human needs (BHNs), ecology components (quality, quantity, habitat, and biota), and stakeholder engagement. However, in the current study, the methodological approach was simplified by considering the quality and quantity components of water resource to address water quality and use challenges in WMA7, as indicated in Figure 2. This methodological approach is proposed as a model framework that could be adopted as a guideline and transferred to other catchments for the implementation of Resource Directed Measures (RDMs).

The flow chart for the research methodology (in Figure 2) is explained in detail, step-by-step, as follows for better understanding:

(i)

Delineation of Integrated Units of Analysis and priority Resource Units

The first step is to delineate Integrated Units of Analysis (IUAs) and identify high priority Resource Units (RUs) within WMA7. Geographic Information System (ArcMap: version 10.8) spatial layers and Google Earth Pro (version 7.1.8) tools were used to delineate the study area into different IUAs and RUs. A study by DWS [9] defined IUAs as homogenous catchments or river reaches that can be managed as single entity. The following spatial data layers were considered to delineate catchment into IUAs: catchment area boundaries, socio-economic zones, land use characteristics, location of water resource infrastructure, and ecological similarities. Thereafter, each IUA was further divided into smaller units referred to as Resource Units (RUs). The RU is defined as a stretch of resource that is ecologically distinct to warrant its own specification of ecological water requirements [9]. In the current study, the delineation process of Resource Units was conducted at the sub-quaternary scale, as this level of spatial representation provided greater resolution of the data. Shapefiles of the following spatial data were sourced from the South African Department of Water and Sanitation and other studies: quaternary catchments, biophysical nodes, rivers, dams, Ecological Water Requirement (EWR) sites, and provincial and international boundaries. The ecological database from the Department of Water and Sanitation provided detailed metadata for EWR sites and biophysical nodes of the study area. Map preparation steps used GIS (ArcMap 10.8) to select a new map and the following layers for sub-quaternaries, rivers, biophysical nodes, EWR sites, and water quality condition, and water users were also added to the map. The sub-quaternary catchments that do not fall within the IUAs or have significant portion of their area outside the study area were edited. On the other hand, the RU selection and prioritization was based on a decision support tool, the Resource Use Prioritization Tool [9]. The tool incorporated a multi-criteria decision analyses approach to assess the importance of monitoring each Resource Unit as part of the management operations to identify priority Resource Units [9]. The multi-criteria approach was used to select the priority Resource Units for the setting of Resource Quality Objectives. Therefore, the approach included the position of RUs within an IUA, the importance of the RUs to users, threats posed to water resource quality for users and the environment, ecological considerations, management consideration, and practical constraints [14]. The prioritized Groundwater Resource Units (GRUs) were based on quaternary catchment boundaries, groundwater use, water quality condition, and aquifer type such as primary aquifer, secondary aquifer, and karst aquifer. The priority Resource Units for both surface and groundwater were identified, along with the associated level of detail required for the assessment: priority 1 (surveyed during wet and dry seasons) and priority 2 (surveyed once during dry season). The delineation of IUAs and RUs provided the basis for detailed water quality and user assessments in the study area.

(ii)

Identification of driving water quality variables for water quality changes in the study area

The purpose of the second step is to identify driving variables for water quality changes and main water users per IUA within the study area. Thereafter, present conditions of resource are linked to identified users by means of Google Earth Pro (version 7.1.8) and field assessment, where water quality samples were collected. The Google Earth Pro tool was used to locate different water users, landcover features, and pollution sources in the study area [12]. In addition, water resource condition was assessed against the South African Water Quality Guidelines [15,16] as a benchmark. Further, surface water quality samples were collected as per the standard procedure outlined in a study by Mulangaphuma et al. [11] and water quality sampling manual for the aquatic environment [17] of South Africa for identified users. In terms of groundwater, standard data collection procedure was followed, as outlined by Nzama et al. [18] and the Groundwater Resource Directed Measures manual [19]. Field surveys/assessments were conducted between February 2021 and November 2023 to cover all seasons (dry and wet months). As a result, a total of 67 surface and groundwater monitoring sites, with long-term data availability, were selected in the study area. Site selection was based on water use types and the position of water quality monitoring sites, whether the site is in the mainstem or not. In addition, standard laboratory techniques were applied to samples for chemical analyses validation, such as Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and Flammable Atomic Absorption Spectrophotometry (FAAS). After laboratory analyses were completed, the results were stored in the Water Management System (WMS) database of the Department of Water and Sanitation.

The water quality variables of concern were based on water quality guidelines, requirements of water users, and known pollution sources that might impact water quality within the RUs. Further, the water quality impacts were rated using methods developed during a study by DWS [20], which determined the present ecological state/ecological importance and sensitivity (PES/EIS) for the country. The study used physico-chemical metrics to rate water quality impact as follows: 0: no impact; 1: little impact; 2: moderate impact; 3: large impact; 4: serious impact; and 5: critical impact. The water quality impact ratings of above 3 (large impact) were used to identify pollution areas or water quality hotspots [20]. Based on that, the water quality and use assessments provided baseline information for the next step: identification and evaluation of water resource scenarios. Since changes in water quality condition under each water resource scenario were linked to changes in driving variables resulting in the changed overall condition, these changes were evaluated against the requirements of identified users or role players in the study area.

(iii)

Identification and evaluation of water resource scenarios

The third step is to identify water resource scenarios and evaluate their implications to resource quality and quantity for water users or role players other than the aquatic ecosystem. Scenarios, in the context of water resource management and planning, are plausible definitions (settings) of all the factors (variables) that influence the water balance and water quality in a catchment and the system as a whole [21]. In the current study, based on the information gathered from a range of studies and consultations with relevant authorities (such as municipalities, water boards, etc.) within the study area, water resource scenarios were identified for analysis. After consultation, a final range was selected for the purposes of modeling and scenario assessment. Version 3.2.8 of the hydrological model, the Water Resources Yield Model, Ref. [22] was used to model flow scenarios for all the systems that were assessed and simulate the long-term hydrological flow time series for the catchments/IUAs at the selected EWR sites and biophysical nodes. The development of scenarios considered different variables that capture the variety of uncertainty and likely condition of water resource now and in the future. Sources of uncertainty includes climate variability, catchment development levels, and ecological protection. In terms of climate variability, the longest possible period of simulation was utilized, namely, over 100 years of rainfall and streamflow data, with associated inherent climate variability. The impacts of a number of dry and wet periods including significant floods and droughts were thus tested within this extended continuous hydrological record. Stochastic analyses were not utilized because the models being used for the ecological impacts assessment are not configured to handle stochastic inputs and work with extended continuous monthly inputs, and the current study aimed to compare projected streamflows and associated impacts against known events. In terms of catchment developmental levels, an example was for the higher water requirement projection scenario associated with greater development levels in the future; there were multiple possible augmentation options due to uncertainty around which schemes might be completed at that time to meet the growing water requirements. The scenarios representing the possible uncertainty of future development levels were then combined with two scenarios (with and without the implementation of ecological water requirements) to display the results of different possible operational approaches.

Therefore, the model input data included average monthly flows, socio-economic developmental levels (such as current and future water users), water supply volumes, climate change and ecological protection level targets of the catchments. The hydrological model used natural and present-day data from different sources such as the Algoa Water Assessment and Allocation study, reconciliation strategies for the Algoa and Amathole systems, and dam operating rule studies. Time series (Microsoft Excel 2016) of average monthly flows and water supply volumes were used to get the average annual volumes at all the key monitoring sites. A scenario comparison matrix, based on flow changes, was developed to compare scenarios with baseflows, natural conditions, and Recommended Ecological Category. In the current study, the identification of scenarios considered developmental levels (related to socio-economic development of catchment), ecological protection level targeted, climate change (considered as an additional possible impact on the selected sites), flow- and water quality-related aspects. The climate change scenario was based on the data from the Algoa water supply system reconciliation strategy study performed by the Department of Water and Sanitation [23]. In addition, identification and evaluation of scenarios was undertaken for those reaches containing the EWR sites and key biophysical nodes, which may potentially be impacted by operational scenarios. In addition, monthly abstraction volumes for industries, domestic, and irrigation users were adjusted to the monthly averages over the hydrological cycle, especially for those systems where present-day set-ups were not available. A study by Mulangaphuma and Jovanovic [12] defined EWRs as flow patterns (such as duration, timing, and magnitude) and water quality needed to sustain a riverine ecosystem in a particular condition. Each scenario was evaluated to meet the Recommended Ecological Category (REC) at the EWR sites because a key component of the study was to find appropriate balance between protection of the ecology and using water to sustain the desired socio-economic activities that depend on the resources. The REC refers to the desired or targeted ecological state for a resource [24]. The determination of REC considers the importance (in maintaining ecological functionality and diversity) and sensitivity (ability to tolerate disturbance) of the system. Then, the ecological aim should be to improve or maintain the condition of a resource. This relates to whether the problems in the catchment can be addressed and mitigated. Generally, the greater the water use, the lower the level of protection attained [25]. Therefore, the selection of scenarios to further determine water resource class was based on scenarios that provided desirable balance between the protection of the environment and the utilization of resource for socio-economic purposes. The output of the current step is a seasonal hydrograph, showing changes in wet (flood) and dry (baseflow) seasons, which is important to show ecological consequences in the study area. It, thus, provides baseline information to assist in determining the desirable management class.

(iv)

Determination of water resource classes

The objective of this step is to integrate the implications or consequences of each scenario, the present ecological categories, and the Recommended Ecological Category to arrive at the determination of water resource classes per IUA. The classification of water resources was based on the guidelines as outlined in the Water Resource Classification System (WRCS) of the Department of Water and Sanitation [26].

Table 1. Determination of water resource classes per Integrated Units of Analysis [26].

Class and Description		Percentage (%) of Sub-Quaternary Reaches in the IUA Falling Into the Indicated Ecological Category Groups
		≥A/B	≥B	≥C	≥D	>D
I: Minimally used and distribution of Ecological Category of that water resource minimally altered from its pre-development conditions		0	60	80	95	5-
II: Moderately used and distribution of Ecological Category of that water resource moderately altered from its pre-development conditions			0	70	90	10
III: Heavily used and distribution of Ecological Category of that water resource significantly altered from its pre-development conditions	Either			0	80	20
	Or				100	-

outlines criteria for assigning a water resource class per IUA in the study area.

According to the WRCS guidelines, the classification of an IUA is determined by the distribution of ecological categories (ECs) for biophysical nodes and/or monitoring points within the IUAs. The Water Research Commission [22] defined the EC as a system of defining ecological condition of a water resource in terms of the deviation of biophysical components from the natural state or reference condition. Further, the ecological evaluation process assigns an ecological category (A to F: A = natural and F = critically modified) to represent the ecological status of the water resource [24]. In the current study, updated data for the ecological categories were sourced from the PES/EIS study [27]. Generally, an IUA is classified as Class I if the majority of nodes fall within ‘A’ or ‘B’ ecological categories, Class II if most nodes are in a ‘C’ ecological category, and Class III if the majority are in a ‘D’ ecological category. According to the classification guidelines, the ecological categories (E and F) are deemed unsustainable [26]. Therefore, they were not considered for evaluation in the current study. Different ecological category percentage information is added into a matrix (as indicated in Table 1) for the determination of water resource classes. In terms of water use, each class represents a different level of protection that is required for the water resource and the extent to which the water resource can be used [26]. For example, water resource classes (i = minimal use, ii = moderate use, and iii = heavily use). In addition, IUA in Class i restricts heavy water users such as mining activities and commercial irrigation; only minimal impact uses, such as recreation and domestic water supply, will be permitted. This is because Class i is assumed to be in a natural state or a pre-development state. Another example, two IUAs that are both in a water resource class iii could differ significantly in terms of their configuration and their specific management objectives. Therefore, it is this specific configuration/distribution of ecological categories that guide planning, decision-making, and management of water resources.

(v)

Determination of Resource Quality Objectives

The purpose of this final step is to set water management objectives (Resource Quality Objectives) per priority Resource Unit for both surface and groundwater quality and quantity in the study area. A study by DWS [9] indicated that RQOs translate the determined water resources classes and ecological needs into measurable management goals that give direction to resource managers on how the resource should be managed. The setting of RQOs considered the requirements of meeting the class, the desired protection level, current and future water use, and the needs of water users. Further, land-based activities and anticipated potential impacts that these activities may have on water resources were also considered. The range of priority users was identified in the previous steps and current water resource conditions assessed. Therefore, different water users all have needs for water resources, which vary in terms of both quality and quantity. As a result, water quality and quantity RQOs were developed for high priority RUs using numeric and/or narrative statements. Narrative statements are essentially qualitative and describe the overall objectives of an IUA or RU; however, numerical RQOs are generally quantitative that can be used for monitoring compliance. Therefore, this is what was performed to set numerical RQOs for water quality in the current study: the assessment of ecological categories for water quality served as a central metric for inferring water quality conditions in the RUs within IUAs. By analyzing the Present Ecological State (PES) within the selected RUs, the study inferred key water quality issues and variations in the ecological response to anthropogenic and natural influence. The DWS [26] manual for determining water quality RQOs for ecology provided a structured framework. This manual offered practical guidelines for identifying critical ecological and water quality parameters and for establishing acceptable thresholds for water quality variables and corresponding numerical RQO values aligned with the PES. Further, the reflection of the current water quality conditions (PES) will ensure compliance with South African Water Quality Guidelines [15,16] and international best practices as a benchmark. A study by Palmer et al. [28] noted that RQOs can be more protective than ecological requirements if there is a particularly sensitive user need in the study area, but generally the ecological requirements define the protection level. Further, the study noted that when a user has a more sensitive water quality or flow requirement than the ecology or ecosystem, and the user requirements do not impair the ecosystem’s condition, the user requirement becomes the RQO [28]. Therefore, effective RQOs for water quality management must be both aspirational and achievable, grounded in the realities of the current water quality conditions [29].

2.3. Conceptualization of Resource Directed Measures

Figure 3 shows the conceptualization of Resource Directed Measures within the Integrated Water Resource Management (IWRM) framework.

Figure 3 shows that the Resource Directed Measure process is a stakeholder-driven process. The process starts by engaging various stakeholders who have interest in a particular catchment (catchment visioning process). Visioning is a key step in the RDM process because it aligns competing and diverse interests in the water resource into a collective desired future state [9]. A study by Pienaar et al. [4] outlined that the Resource Directed Measure process does not occur in isolation; it is therefore an integral part of the Integrated Water Resource Management environment framework. Integration includes other processes in the planning of water resource development, utilization and protection, and in the control and management of water use. For example, proposed water resource classes and Resource Quality Objectives have significant implications to water resource allocation schedule. In addition, the IWRM framework is an iterative process of evaluating water resource scenarios with stakeholders where trade-offs (social, economic, and ecological) are made, out of which the water resource schedule, model system installation, Class, Reserve, RQO, and catchment management strategy emerge [4].

3. Results and Discussion

3.1. Delineated Integrated Units of Analysis and Priority Resource Units Within the WMA7

Owing to the large number of catchments, a total of nineteen IUAs were delineated and ninety-five RUs for surface and groundwater were identified and prioritized. The IUAs and RUs were assigned codes to differentiate them in the study area, as illustrated in Figure 3.

Figure 4 shows nineteen IUAs delineated, and each IUA was assigned a code to differentiate them in the study area. The IUAs were further divided into a total of forty-seven prioritized RUs for the rivers and forty-eight Groundwater Resource Units (GRUs) for groundwater. The delineation of the catchments is significant for assigning water resource classes per IUA, while prioritized RUs are important for setting Resource Quality Objectives. As a result, the delineation of IUAs and the identification of RUs provided basis for detailed water quality and user assessments in the study area.

3.2. Identification of Driving Water Quality Variables for Water Quality Changes Within the Integrated Units of Analysis

Table 2. Summary of hotspots, driving water quality variables, and associated water users for the Mzimvubu to Tsitsikamma Water Management Area (WMA7).

IUA Code	Resource Unit	Water Quality Impact (Rating)	Water Quality Sources/Users	Driving Variables	Comment
IUA_K01	R_RU02_I	3	Wastewater Treatment Works, Irrigation, Cattle farming	E. coli, Electrical conductivity, Nutrients	Upstream towns and villages.
	R_RU01_I	3	Irrigation	Nutrients, Electrical conductivity	Dominated by citrus farming.
IUA_L01	R_RU05_I	3	Wastewater Treatment Works, Irrigation, Cattle farming	Nutrients (High Algae Content)	Dominated by cattle farming.
IUA_M01	R_RU03_I	3	Industry, Cattle farming	Electrical Conductivity, Nutrients	Downstream of the Groendal Dam. Limited impacts due to conservation area.
IUA_LN01	R_RU04_I	3	Irrigation and cattle farming	Nutrients	Elevated nutrient load.
IUA_Q02	R_RU08_I	3	Human settlement, Sediment mining, Erosion, Irrigation	Total Dissolved Solids, Salinity	High sedimentation (highly turbid) from erosion and settlement.
	R_RU06_I	3	Upstream Town	Clarity, Total Dissolved Solids, Salinity	High sedimentation. Cradock Town is located upstream.
	R_RU26_R	3	Cattle trampling and grazing	Nutrients	Extensive bank erosion.
IUA_R01	R_RU0_12	3	Irrigation	Electrical conductivity, Nutrients, pH	Upstream Tois River contributes to the sediment loads.
	R_RU10_I	3	Wastewater Treatment Works, Human settlement	E. coli, Nutrients, Total Dissolved Solids	Nutrients (algae) mainly from wastewater treatment works pipeline leakage downstream.
	R_RU09_I	3	Wastewater Treatment Works, Bank erosion, sand mining	E. coli, Clarity, Nutrients	High silt loads during higher flows; Deposition of sand on the lower flood features.
IUA_R02	R_RU13_I	3	Irrigation	Electrical conductivity, NH4	Elevated nutrient load.
	R_RU20_R	4	Wastewater Treatment Works	Nutrients, E. coli	Point sources posing health hazards to both humans and the environment.
IUA_S02	R_RU24_R	3	Irrigation, Wastewater Treatment Works, abstraction	Nutrients, E. coli, Chemical Oxygen	Nutrient enrichment (algae). Evidence of bank collapse and bank erosion due to flood event.
IUA_T01	R_RU17_I	3	Wastewater Treatment Works, Human Settlement	E. coli, Nutrients	Nutrient enrichment (algae).
IUA_T02	R_RU14_I	3	Human settlement, Sediment mining, Erosion	Electrical conductivity, Salinity, Clarity	Erosion and deposition along the channel margins.
IUA_T03	R_RU15_I	4	Wastewater Treatment Works, Cattle trampling and Grazing	E. coli, Nutrients, Clarity	Algae and fine silt layer over stone biotope, erosion from cattle grazing.

shows eleven IUAs with water quality challenges and associated water users in the study area. Further, the table contains Resource Units and associated resource names. This is because a resource/river could have one or more Resource Unit/s in it due to ecological distinction and associated water user type found in that stretch of the river.

Table 2 shows eleven IUAs with large water quality impact (3) and serious water quality impact (4) within the study area. According to the table, water quality parameters of concern were electrical conductivity (EC), Escherichia coli (E. coli), Total Dissolved Solids (TDSs), nutrients and ammonia (NH₄), and turbidity/clarity. The study observed that irrigation and Wastewater Treatment Works (WWTWs) are driving water users for water quality changes, and this is further supported by the presence of high nutrients, EC, and E. coli in many parts of the study area. As reported by Mulangaphuma and Jovanovic [12], commercial vegetable farming such as maize, cabbage, tomatoes, and lucerne dominated the irrigation sector. Wastewater Treatment Works are the major source of water pollution, suggesting that the infrastructure may be unable to cope with the growth of the cities and towns. As reported by DWS [30] that Buffalo (IUA_R02) and Mthatha (IUA_T02) Towns have a long history of experiencing challenges with WWTWs due to high population rate and poor maintenance. A study by Nkosi et al. [8] reported that WWTWs can have various contaminants of emerging concern (heavy metals, antiretrovirals, antibiotics, pesticides, plastics, and microplastics) and significant pathogen loads. In the channel of the Buffalo River, water hyacinth (E. crassipes) and thick silt drapes in the pools were seen during the field assessment. This could be attributed to high nutrients presence in the river. The presence of water hyacinth in water bodies has potential to change water chemistry and kill native aquatic life (e.g., fish). In the lower reaches of the Mthatha River, a silt drape was seen on the gravels, cobbles, and boulders, where water velocities were low in pool habitats. These findings are critical for understanding the condition of the water resource and their potential implications to native biota, water users, and groundwater stress.

3.3. Identification and Evaluation of Water Resource Scenarios

3.3.1. Identified Water Resource Scenarios in the Study Area

The current study identified five possible water resource scenarios and associated scenario descriptions for the study area, as detailed in

Table 3. A summary of water resource scenarios and descriptions identified in the study area.

Scenario	Scenario Descriptions
Scenario 1 (Sc1)	Present Day Demands	Sc1a (without EWR)_“modelling flows in rivers and supply to users without EWR”
		Sc1b (with EWR-rivers)_“the EWR for rivers included into the models and assess if EWRs are met, including socio-economic needs with potential trade-offs”
Scenario 2 (Sc2)	Medium Term (2030)	Sc2a (without EWR)
		Sc2b (with EWR-rivers)
Scenario 3 (Sc3)	Long Term (2050)	Sc3a (without EWR)
		Sc3b (with EWR-rivers)
Scenario 4 (Sc4)	Water Quality (Considered and Predicted)	Only selected IUAs were assessed, where water quality was identified to be of concern. The future water quality status (either deterioration or improvement) was based on Sc1b_the present-day status of the water quality, along with the EWRs for the set Recommended Ecological Category for rivers.
Scenario 5 (Sc5)	Climate Change (Considered and Predicted)	Only one climate change scenario was assessed, and the following IUAs were assessed: IUA_K01 (Kromme River); IUA_KL01 (Gamtoos River); IUA_L01 (Kouga River); IUA_M01 (Swartkops River).

. The identification of scenarios was based on developmental levels, level of protection targeted, climate change, and flow- and water quality-related aspects. Table 3 shows a summary of water resource scenarios identified in the Mzimvubu to Tsitsikamma Water Management Area.

Table 3 shows that the scenarios were identified for the present-day, medium-term, and long-term demands. Therefore, the scenarios, which include the EWRs, were meant to capture the impacts of prioritizing the environmental or ecological protection, and the corresponding impacts on socio-economic (consumptive) water supply. Scenarios that do not include the EWRs were meant to show the impacts of prioritizing the socio-economic water supply (users) and the corresponding impacts on the ecology and environment. In this case, this provided important information for the trade-off process in consultation with different authorities in the study area. The consultation was based on the desired water resource condition (visioning process) by different authorities in the study area. In terms of water quality scenario (scenario 4), the focus was on those IUAs where water quality assessment was identified to be of concern. The climate change scenario (scenario 5) was considered as an additional possible impact on water resources. After operational scenario identification, the scenarios were then evaluated in the next subsection to determine their implications to water resources and users.

3.3.2. Evaluation of Water Resource Scenarios in the WMA7

The objective of this substep of scenario evaluation is to find the appropriate balance between the level of environmental protection and the use of water to sustain socio-economic activities. Figure 5 provides a seasonal hydrograph of the evaluated water resource scenarios at the four selected sites. The site selection was based on the data availability for climate change scenario in the study area.

Figure 5 shows a month-by-month comparison of the flow duration curves of the applicable scenarios. In the current study, the present-day scenario uses the 2021 to 2022 hydrological data, together with the best estimates of present-day water use and water resources development levels. According to DWS [31], baseflow refers to the sustained low flow of a river that happens during dry periods, while natural flow refers to unimpeded pattern of water flow in a river, which is defined by components like timing, frequency, duration, magnitude, and rate of change [31]. As reported by Mulangaphuma and Jovanovic [12], the data for baseflow, present-day, and natural flow time series were compared to obtain flows at the selected EWR sites and at gauging weirs or streamflow gauging stations in the study area.

The flow durations of the scenarios were compared between operating scenarios in Figure 5a–d and climate change scenarios in Figure 5e–h for better understanding. The scenarios were assessed in terms of how the changes in hydrology will impact the level of stress experienced in the system. The highlighted red areas in all figures indicate where the Ecological Water Requirements (EWRs) could not be met.

In Figure 5a,e (Gamtoos), baseflow is too low throughout all months, except in March when there is slight improvement. This could be due to the abstraction of surface water for irrigation and supply of water to the nearby towns. All the scenarios evaluated show reductions from the natural flows for all months, especially the drier months (May, June, and July). The analysis showed that impact is expected under any of the operational scenarios assessed at selected reaches. When the EWR is implemented from the present-day scenario (scenario 1b) to the climate change scenario (scenario 5b), this clearly shows variability and demonstrates the significant impact on river system flows. As a result, this reduction is inevitably expected to have a cascading effect on the ecology. A study by DWS [31] observed that the fish populations and macroinvertebrates are already stressed, particularly during the dry season, when the EWR is not implemented.

In Figure 5b,f (Swartkops), both scenarios evaluated show reductions from the natural flows for all the months. Generally, the water quality in the upstream reaches of this river is good. However, field observations coupled with satellite imagery indicate that the water quality deteriorates downstream because of surrounding settlements and activities around the city of Gqeberha, especially towards the Swartkops Estuary [12]. The poor water quality expected in the lower reaches of the river is largely because of wastewater entering various tributaries throughout the catchment. Under the climate change scenario, a slight increase in flow is anticipated due to dam releases; however, concerns remain that the flow requirements needed to support biotic components.

In Figure 5c,g (Kouga), scenarios evaluated show reductions from the natural flows for all the months. From the present-day to climate change scenario 5 (Figure 5c–g), the significant impact on river system flows is clearly demonstrated. This reduction inevitably has a cascading effect on the ecology of the Kouga River. A study by DWS [31] observed that fish population declines during both the wet and dry season, when the EWR is not implemented. Thus, with climate change, the potential for reduced flows (Scenario 5a) will only exacerbate the situation, particularly for flow-dependent fish species.

In Figure 5d,h (Upper Kromme), scenarios evaluated show small reductions from the natural flows for most of the months, except from October to December, where the scenario flows are higher than natural flows. In Figure 5h, climate change scenario and the potential for reduced flows could affect the system. With less water available, the impacts may extend into the wet season, rather than being limited to the dry season as observed in scenario 1a. Baseflow is too low in the Upper Kromme River, and this could be due to the impact from the abstraction for irrigation.

The water quality scenarios (Sc4) were narrated and assessed to determine their implications to water users downstream. A qualitative or narrative assessment was conducted for the water quality scenario (Sc4) due to lack of a water quality model and load calculations in the catchments at the time of the current study. Therefore, the future deterioration or improvement of water quality status was based on the current state of the water quality and activities in the study area. As previously indicated in Table 2, the poor water quality condition is expected to worsen significantly and reach a critical point in the future. As a result of reduced flow in the system, river health could significantly decline, impairing the ability of this system to deliver natural biota and ecosystem goods and services. Considering the dysfunctional WWTWs and intensive irrigation as major reason for declining water quality in many Integrated Units of Analysis, worsening water quality is likely to (a) allow water borne diseases to become more frequent and persistent, and (b) seasonally increase risks for local dependent communities, recreational users, and biodiversity associated with the river system.

The scenario results were considered for the final selection of operational scenarios and associated water resource classes. The selection of operational scenarios was based on the requirements of the ecology and water users and consideration of planned development in the study area.

Table 4. Selection of operational scenarios in the Mzimvubu to Tsitsikamma WMA.

Scenario	Scenario Description	Reason for Selection
Scenario 1b	Present-Day Demands (With EWR)	To ensure flow of water in the system for the survival of flow dependent fish and macroinvertebrates.
Scenario 2b	Mid-Term (With EWR)	To ensure flow of water in the system is maintained and improved for sustainable water use.
Scenario 4	Water Quality Scenario	To ensure that present and future water quality condition is improved for the ecosystem and water users

shows the selected scenarios and reasons for their selection.

Table 4 shows that scenario selection was undertaken with the aim of improving the protection of the ecosystem in the study area. This is due to high surface and groundwater use for irrigation and domestic water supply, as well as water quality deterioration resulting from dysfunctional WWTWs and irrigation practices. Therefore, the outcome of the scenario analysis should be incorporated into water resource classes and Resource Quality Objectives determination processes.

3.4. Determination of Water Resources Classes per IUA and Resource Quality Objectives per RU

3.4.1. Determination Water Resources Classes per IUA

The assigning of water resource classes was based on the distributions of ecological categories for biophysical nodes within the IUAs, as outlined in the WRCS guidelines [26]. The determined water resource classes per IUA for the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7) are presented in Figure 6.

Figure 6 shows that the findings of the current study identified eleven IUAs classified as Class lll, seven IUAs as Class ll, and one IUA as Class l. Class III represents areas of high developmental demand or ecological significance, necessitating more stringent management measures. In the current study, Class III could be attributed to poor water quality conditions because of intensive irrigation practices and poorly maintained WWTWs in the study area. A study by Nkosi et al. [8] observed that untreated or poorly treated wastewater is one of the largest contributors to pollution in water resources as a result of population growth migration to urban areas. Further, field assessments observed intensive groundwater use for irrigation and planned groundwater developments in those IUAs in Class III. As a result, potential implications for these IUAs may arise due to these future developments. Therefore, increased groundwater abstraction could lead to over-exploitation of the resource where abstraction rates exceed natural recharge. Implications for that could lead to long-term depletion of groundwater reserves and/or reduction in individual borehole yields. Seven IUAs in Class II denote areas of moderate ecological sensitivity and developmental pressure, allowing limited utilization while preserving ecological functions. In the current study, the impacts on these IUAs are primarily associated with rural development, minimal agricultural activities, large dams and WWTWs. One IUA in Class I represents a near-natural water resource in the study area. In this case, the IUA (IUA_T04) is in the Pondoland protected area and Mkambati Nature Reserve. This IUA is characterized by various ecologically sensitive and free-flowing flagship rivers such as Nkodusweni, Mntafufu, Mzintlava, Mtentu, Mnyameni, and Mzamba.

As reported by Mulangaphuma and Jovanovic [12], high groundwater uses for irrigation, domestic water supply, and poor water quality conditions could also be attributed to severe drought conditions experienced in many parts of the study area. Flagging these water resources with high-water use and poor water quality will ensure their protection and maintenance, thereby supporting their long-term sustainability.

3.4.2. Setting of Resource Quality Objectives per RU

As reported by DWA [9], the RQOs are descriptive or quantitative goals defined to protect the water resource. Therefore, it is critically important to understand that different water resources require different levels of protection [12].

Table 5. Water quality and quantity Resource Quality Objectives for rivers in the Mzimvubu to Tsitsikamma Water Management Area.

IUA	Class	REC	Component	Sub- Component	Indicator	RQO
						Narrative	Numeric
* IUA_K01	iii	C	Quantity	Flows	High	Freshets and floods required for the upper Kromme River	4.16 m3/s
					Low		0.16 m3/s
			Quality	Salts	EC	_	≤55 mS/m
				Nutrients	TIN	_	≤0.75 mg/L
					PO4-P	_	<0.015 mg/L
				System variables	DO	_	>7 mg/L
					pH	_	5th Percentile: 6.00–6.24; 95th Percentile: 8.37–8.69
				Pathogens	Fecal coliforms and E. coli	_	Meet targets for use in Table 6 detailing high health risk guidelines
* IUA_KL01	ii	B	Quantity	Flows	High	Continuous flows required at the Kouga River	8.5 m3/s
					Low		0.34 m3/s
			Quality	Salts	EC	_	≤55 mS/m
				System variables	DO	_	>7 mg/L
					pH	_	5th Percentile: 6.00–6.24; 95th Percentile: 8.37–8.69
		C	Quantity	Flows	High	Continuous flows required at the river	9.3 m3/s
					Low		0.49 m3/s
			Quality	Salts	EC	_	<85 mS/m
				Nutrients	TIN	_	<4 mg/L
					PO4-P	_	<0.125 mg/L
				System variables	Water temperature	Natural temperature range is estimated from air temperature	_
					TSS	_	<10% of the background TSS concentrations at a specific site and time. TSS ≤ 117.0 mg/L
* IUA_T04	Class I	B	Quantity	Flows	High	_	0.038 m3/s
					Low	_	0.016 m3/s
			Quality	Salts	EC	_	≤85 mS/m
				Nutrients	TIN	_	≤2.0 mg/L
					PO4-P	_	<0.025 mg/L
				System variables	DO	_	>6 mg/L
					pH	_	5th Percentile: 5.00–5.23 95th Percentile: 9.05–9.36
					Clarity	Aim for clarity to be approximately ≥95 cm	≥95 cm
		B	Quantity	Flows	High	_	0.465 m3/s
					Low	_	0.201 m3/s
			Quality	Salts	EC	_	≤55 mS/m
				Nutrients	TIN	_	≤0.75 mg/L
					PO4-P	_	<0.015 mg/L
				System variables	DO	_	>7 mg/L
					pH	_	5th Percentile: 6.00–6.24 95th Percentile: 8.37–8.69
					Clarity	Use on-site observations and expert opinion.	≥81 cm

* IUA_K01 = RU (RU01); water resource (Kromme River); quaternary catchment (K90A). * IUA_KL01 = RU (RU03, RU04); water resource (Kouga and Twee rivers); quaternary catchment (L82D). * IUA_T04 = RU (RU19.3 and RU19.6); water resource (Nqabarha and Mngazi rivers); quaternary catchment (T90B and T70B).

and

Table 6. Water quality and quantity Resource Quality Objectives for groundwater in the Mzimvubu to Tsitsikamma Water Management Area.

IUA	Component	Sub- Component	Indicator	RQO
				Narrative	Numeric Limit
* IUA_K01	Quantity	Abstraction	Allocation	New users are to remain within the allocable groundwater volume.	-
		Groundwater level	Time series	Drawdown in monitoring boreholes should not exceed peak drawdown.	Peak drawdown < 16.2 m 75th percentile drawdown < 10.2 m
	Quality	Nutrients	NO3/NO2	Trend should not exceed the 75th percentile or the TWQR for domestic use (in brackets) if higher for Compounds of Concern.	<1.4
		Salt	EC		<74 mS/m (70)
			SO4		<16 mg/L (200)
			Na		<104 mg/L (100)
			Cl		<165 mg/L (100)
			F		<0.2 mg/L (1)
* IUA_KL01	Quantity	Abstraction	Allocation	Existing users to comply with allocation schedules.	-
		Groundwater level	Monthly time series	_	Peak drawdown < 13.4 m 75th percentile drawdown < 8.5 m
	Quality	Nutrients	NO3/NO2	Trend should not exceed the 75th percentile or the TWQR for domestic use (in brackets) if higher for Compounds of Concern.	<0.1 mg/L
		Salt	EC		<109 mS/m (70)
			SO4		<48 mg/L (200)
			Na		<89 mg/L (100)
			Cl		<200 mg/L (100)
* IUA_L01	Quantity	Abstraction	Allocation	New and existing water users to comply with allocation condition.	_
		Groundwater level	Time series	Identify suitable monitoring borehole.	_
	Quality	Nutrients	NO3/NO2	Trend should not exceed the 75th percentile or the TWQR for domestic use (in brackets) if higher for Compounds of Concern.	<0.4 mg/L
		Salt	EC		<21 mS/m (70)
			SO4		<5 mg/L (200)
			Na		<25 mg/L (100)
			Cl		<47 mg/L (100)
			F		< 0.1 mg/L (1)
			Pb		<0.015 mg/L (0.01)
* IUA_LN01	Quantity	Abstraction	Allocation	New and existing water users to comply with allocation condition.	_
		Groundwater level	Time series	_	peak drawdown < 2.5 m 75th percentile drawdown < 2.2 m
	Quality	Nutrients	NO3/NO2	Trend should not exceed the 75th percentile or the TWQR for domestic use (in brackets) if higher for Compounds of Concern.	<5.4 mg/L
		Salt	EC		<116 mS/m (70)
			SO4		<123 mg/L (200)
			Na		<100 mg/L (100)
			Cl		<115 mg/L (100)
			F		<0.9 mg/L (1)
			Mg		<48 (mg/L 30)
	Quantity	Abstraction	Allocation	New and existing water users to comply with allocation condition.	_
		Groundwater level	Time series	_	peak drawdown < 16.5 m 75th percentile drawdown < 8.7 m
	Quality	Nutrients	NO3/NO2	Trend should not exceed the 75th percentile or the TWQR for domestic use (in brackets) if higher for Compounds of Concern.	<0.1 mg/L
		Salt	EC		<402 mS/m (70)
			SO4		<501 mg/L (200)
			Na		<632 mg/L (100)
			Cl		<722 mg/L (100)
			F		0.7 mg/L (1)
			Mg		<121 mg/L (30)
			Pb		<0.045 mg/L (0.01)
	Quantity	Abstraction	Allocation	New and existing water users to comply with allocation condition.	_
		Groundwater level	Time series		peak drawdown < 20.6 m 75th percentile drawdown < 15.7 m
	Quality	Nutrients	NO3/NO2	Trend should not exceed the 75th percentile or the TWQR for domestic use (in brackets) if higher for Compounds of Concern.	<6.4
		Salt	EC		<235 mS/m (70)
			SO4		<150 mg/L (200)
			Na		<196 mg/L (100)
			Cl		<441 mg/L (100)
			F		<1.3 mg/L (1)
			Mg		<69 mg/L (30)
			Pb		<0.045 mg/L (0.01)

* IUA_K01 = Groundwater Resource Units (GW_RU01); quaternary catchment (K80A, K80B, K80C, K80D, K80E, K80F, K90A, K90B). * IUA_KL01 = Groundwater Resource Units (GW_RU02); quaternary catchment (K90E, K90F, K90G). * IUA_L01 = Groundwater Resource Units (GW_RU03); quaternary catchment (L82B, L82D). * IUA_LN01 = Groundwater Resource Units (GW_RU12; GW_RU13;GW_RU14).

show that the determination of the RQOs have considered the requirements of meeting the class, the desired protection level, and the current and future needs of water users. Further, the tables show selected Resource Quality Objectives for both river and groundwater, illustrating examples of some RQO results.

Table 5 presents the quality and quantity RQOs per Resource Units (within Integrated Units of Analysis) for the rivers in the Mzimvubu to Tsitsikamma Water Management Area (WMA7). The IUA (IUA_K01) is as Class III, with Resource Units at targeted ecological category C. The current study observed that WWTWs are the main sources of pollution, with significant impact on the water resource. Similarly, a study by Munzhelele et al. [32] found that increased physico-chemical parameters in the downstream of the river could be due to land use activities such as agriculture and WWTWs from increased human population. The condition could be improved by ensuring that dysfunctional WWTWs are not discharging directly into the water resources. Stringent numerical RQOs were set to ensure that the resource improves to achieve the objectives of the REC. While IUA_KL01 (RU_03 and RU_04) is Class II, the water quality ranges from marginal to poor condition. This is attributed to nutrients from intensive irrigation and urban dumping. RU_03 and RU_04 are at B and C Recommended Ecological categories; the system should aim to improve and/or maintain the provision of goods and services. Munzhelele et al. [32] reported that activities such as erosion and agricultural runoff contributed to higher nutrients and EC values in the downstream of the catchment.

The only IUA in Class I is at IUA_T4, with the majority of the IUAs in a protected area. Therefore, it is recommended that the system is maintained in the same REC of B and water resource Class I. In the current study, hydrological information is representative of the required flow regime in the river, where the variability is dependent on the seasonal and temporal pattern of natural flow conditions. Therefore, the average monthly flow represented high and low flow requirements of a representative wet and dry month.

Table 6 presents narrative and numeric RQOs for groundwater levels, abstraction, and groundwater quality parameters for the same IUAs as the surface water. In many parts of the study area, groundwater quality is good when compared against the South African Water Quality Guideline for drinking water use [15]. However, fluoride levels may be elevated due to the prevalence of doleritic intrusions in the study area. In Table 6, numeric RQOs for groundwater quality variables of concern were set (with percentiles) for monitoring compliance. A study by Mulangaphuma et al. [11] reported that groundwater quality in the western and central areas of the study area reflected marginal to poor groundwater quality. This was attributed to lithology, limited groundwater recharge, and rainfall conditions, which have a bearing on the quality of groundwater. Therefore, the narrative RQOs were presented in the table to ensure new and existing water users comply with allocation conditions. According to WARMS (the national water user licensing database), the study area saw an increase in groundwater use in 2017 and early 2022. This was attributed to severe droughts, which resulted in extensive groundwater exploitation (municipal and private) occurring in the catchment [12].

4. Conclusions

The overall aim of the current study was to determine water resource classes and Resource Quality Objectives for both surface and groundwater resources in the Mzimvubu to Tsitsikamma Water Management Area. A novel stepwise quantitative and qualitative method was developed to ensure water resource protection in the study area. This methodological framework is recommended as a model guideline for the determination of water resource classes and RQOs, transferable to other catchments. The method used water quality and quality components of water resources to determine the classes and RQOs and was successfully implemented to provide a balanced objective of protection and sustainable utilization of resources. The study’s major findings were the following:

• Nineteen Integrated Units of Analysis were delineated, and ninety-five Resource Units were identified and prioritized for both surface and groundwater, which provided key insights into areas where stricter measures will be established to safeguard these critical resources.
• Driving water quality variables (nutrients, EC, and E. coli) were observed, and primary water users (irrigation, settlements, and WWTWs) were identified per IUA in the study area.
• Five water resource scenarios were designed and evaluated to capture a likely water resource condition for the present and future. The analysis showed that impact is expected under any of the operational scenarios assessed at the selected reaches. However, the climate change scenarios (Sc5a and Sc5b) showed significant variability in the Upper Kromme, Swartkop, Kouga, and Gamtoos systems.
• The water resource classes were determined, of which eleven IUAs were classified to be in Class lll, seven IUAs in Class ll, and one IUA in Class l. This necessitates more stringent management measures to improve resource conditions in the study area.
• Water quality and quantity Resource Quality Objectives were set to ensure that both river and groundwater resources are compliant and protected, while allowing socio-economic development in the study area.

These findings are important for water resource management in the study area. In a broader context, the findings of the current study are applicable beyond South African borders because they are aligned with Sustainable Development Goals (SDGs) for 2030. Thus, improved management of wastewater and irrigation practices will guarantee safe and secure access to clean water and proper sanitation for all.

The adjustment of RQOs is possible through a process of negotiation and consensus-seeking among all stakeholder groups, which should be represented in this process. In addition, the current study identifies all primary water users within Resource Units. However, water users such as ecology, informal uses, and illegal water uses were not considered due to the complexity they might bring to the current study. Further, trace elements such as arsenic, uranium, copper, cobalt, nickel, lead, and zinc were not considered due to limited data available and user type in the study area. In addition, the qualitative method was used to analyze water quality scenario 4 (Sc4) due to absence of water quality model in the catchments at the time of writing this paper. The study recommends that future studies on socio-economic implications (e.g., loss of production), due to the determination or implementation of water resource classes and Resource Quality Objectives to consumptive users, be undertaken. It recommends that further studies on potential health effects, due to poor water quality conditions, on downstream users or communities be investigated.