Stochastic inputs are essential for incorporating hydrological variability in water resources assessment, planning, and management. However, most studies focus on the generation of precipitation and temperature, precipitation and streamflow, and precipitation and evaporation, with limited incorporation of groundwater levels. This study assessed the ability of the Variable Length Block (VLB) bootstrapping model for simultaneously generating stochastic sequences of rainfall, evaporation, and groundwater levels. The performance of the model was assessed by comparing single statistics of historical time series located within the box plots of 100 annual and monthly stochastically generated time series. The model preserved eight of the nine statistics adequately, except for skewness, across all variables, with historical values for evaporation and groundwater levels falling below and above the interquartile range for 12 months. All the historic statistics for rainfall, evaporation, and groundwater levels were within the interquartile ranges of the box plots for 83, 71, and 71% of the time, respectively. The historic statistics for rainfall, evaporation, and groundwater levels were within the box plot ranges for 100, 98, and 99% of the time, respectively. These findings indicated reasonably successful generation, and the VLB generator was therefore considered applicable for the stochastic generation of multiple hydrometric data types.

AbstractThika Dam, with a storage capacity of 70,000,000 m3 at full capacity and situated at an altitude of 2041 m above sea level, supplies 84% of the total water used by Nairobi city and its surrounding areas. Since becoming operational in 1994, the dam has been providing water through the Ngethu Water Treatment Plant. Due to rapid population growth in Nairobi and neighboring towns, water demand has risen significantly, leading to the construction of the Northern Collector Tunnel (NCT 1) to augment the dam's inflows. The Kigoro Treatment Plant was also constructed to help meet demand, supplying 1.6 m3/s, while Ngethu supplies 4.8 m3/s. To ensure that the reservoir meets the demand and maintains high reliability, the operations are based on policies developed in 2018. However, the 2018 rules were developed based entirely on historical river flows and excluded the Kayuyu River, which contributes 20% of the dam's inflows. Additionally, it was assumed that all the river inflows into the system of the same exceedance probability coincide over time, which is unlikely to happen in practice. This study, therefore, aimed to develop new operating rules that do not have the above‐mentioned limitations of the current rules. The rules were developed in four steps: (i) hydrological simulation of the historical river flows for 26 years from 1997 to 2022; (ii) the stochastic generation of 101 temporary‐correlated streamflow, rainfall, and evaporation sequences using the variable length block bootstrap (VLB) model, each 1000 years long; (iii) multiple monthly short‐term (5‐year long) system simulations for different decision months and initial reservoir storage states, to obtain 505 stochastic base yields for each combination of decision month and initial storage state; (iv) the use of the base yields to formulate probabilistic operating rules that are considered more robust and more straightforward to use than the current rules.

Editorial: Innovating a new knowledge base for water justice studies: hydrosocial, sociohydrology, and beyond

AbstractWater distribution networks are costly long‐term investments, prompting researchers to seek cost reduction and efficient design solutions using optimization techniques. In this context, the Penalty‐Free Multi‐Objective Evolutionary Algorithm (PFMOEA) is employed alongside pressure‐dependent analysis (PDA) to optimize water distribution systems (WDSs). This integrated approach facilitates a multi‐objective evolutionary search, leading to improved WDS designs. The research aimed to improve the computational efficiency of PFMOEA by using real coding, where decision variables are represented as real numbers rather than integers or binary formats. Additionally, it adjusted the allocation of feasible and infeasible solutions near the Pareto front (the boundary of optimal or least‐cost solutions) during the elitism step of the optimization process. A feasible solution was regarded as the one that meets all the pressure and flow rate requirements while an infeasible solution fails to meet these requirements. These adjustments were labeled as PFMOEA‐A, PFMOEA‐B, and PFMOEA‐C, with allocation percentages of 15% feasible and 15% infeasible solutions, 20% feasible and 10% infeasible solutions, and 30% feasible and 0% infeasible solutions, respectively. The study utilized two benchmark network problems, the two‐looped and Hanoi networks, for analysis. A comparative assessment was then conducted to evaluate the performance of the real‐coded PFMOEA in comparison to other approaches documented in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real‐coded PFMOEA achieved the novel best‐known solutions ($419,000 and $6.081 million) and a zero‐pressure deficit for the two networks, requiring fewer function evaluations than the binary‐coded PFMOEA. Additionally, by replacing 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was enhanced. This led to a 20% and 17% reduction in the number of function evaluations required to identify the optimal solutions for the Two‐looped network and the Hanoi network, respectively. The findings of this study aim to contribute to a more equitable and resilient water management framework. Ultimately, the insights gained will not only support the optimization of existing water distribution networks but also inform policy decisions that prioritize sustainability and resource conservation. This holistic approach will facilitate improved water security and support the overarching goal of achieving sustainable water management against the growing challenges related to climate change and urbanization.HIGHLIGHTS PFMOEA eliminates the need for penalties through the adoption of a pressure‐dependent analysis within a multi‐objective optimization search. Employing real coding in PFMOEA instead of binary coding enhances the computational efficiency of PFMOEA. Retaining a small percentage of infeasible solutions near the boundary of optimal solutions during optimization also improves the computational performance of PFMOEA.

A socio-hydrological model that simulates, couples and co-evolves reservoir operation and human behaviour to assess the impact of unauthorized water abstractions on reservoir performance is developed. The model relates hydrological state, well-being, user compliance and management competence and is applied to two reservoirs. To generalize the modelling, well-being, user compliance and management competence are normalized (0 to 1) and modelled using logistic functions. When compliance is below the set threshold, unauthorized water abstraction occurs; the magnitude depends on water allocation, user compliance and management competence. In the absence of real data, eight hypothetical scenarios are applied. The expected dependence of well-being on the hydrological state and that of well-being, virtues and management competence on user risk perception and user compliance was realized as initially hypothesized. The variation of the effect of human factors on storage and yield was found to be more pronounced during low hydrological states (drought). The modelling is considered applicable for assessing the likely impact of humans on real reservoir performance.

This paper considers the theoretical and empirical potential of a focus on water justice to ground sociohydrology scholarship. The field of sociohydrology recognises the role of humans in altering – deliberately or not – hydrological flows and seeks to account for the feedbacks and interactions between human and water systems. This scholarship, however, tends to reduce the role of humans and societies to social variables and indicators and is anchored in the ontological separation of nature-society, with nature as the 'anchor' of truth claims. The preference is for larger datasets, and for knowers as positioned outside of (and as independent from) what they study. These approaches are less suited for unravelling the social processes generative of so-called global water challenges, while they also are difficult to translate into actionable insights and tools that are useful to those making actual water decisions (water managers, policy makers, and civil society actors). In our paper, we discuss possible ways of ‘grounding’ sociohydrology in order to better capture sociohistorical contexts, recognize power relations and embrace multiple ways of knowing water. Conceptually, we examine how critical water studies – focusing on water equity and justice - can provide ways of ‘grounding’ sociohydrological understandings of water-society relations. We specifically consider how Haraway’s (1988) notion of situated knowledges in helping do this methodologically and conceptually. Empirically, we draw on our own research expertise to argue that grounded, empirical case studies can significantly add to theorisations of socionatural change, providing critical insights into processes of societal inclusion and exclusion, and the production of social difference through water – insights that can provide a good basis for imagining and helping develop just transformations to water sustainability.

This paper considers the theoretical and empirical potential of a focus on water justice to ground sociohydrology scholarship. The field of sociohydrology recognises the role of humans in altering – deliberately or not – hydrological flows and seeks to account for the feedbacks and interactions between human and water systems. This scholarship, however, tends to reduce the role of humans and societies to social variables and indicators and is anchored in the ontological separation of nature-society, with nature as the 'anchor' of truth claims. The preference is for larger datasets, and for knowers as positioned outside of (and as independent from) what they study. These approaches are less suited for unravelling the social processes generative of so-called global water challenges, while they also are difficult to translate into actionable insights and tools that are useful to those making actual water decisions (water managers, policy makers, and civil society actors). In our paper, we discuss possible ways of ‘grounding’ sociohydrology in order to better capture sociohistorical contexts, recognize power relations and embrace multiple ways of knowing water. Conceptually, we examine how critical water studies – focusing on water equity and justice - can provide ways of ‘grounding’ sociohydrological understandings of water-society relations. We specifically consider how Haraway’s (1988) notion of situated knowledges in helping do this methodologically and conceptually. Empirically, we draw on our own research expertise to argue that grounded, empirical case studies can significantly add to theorisations of socionatural change, providing critical insights into processes of societal inclusion and exclusion, and the production of social difference through water – insights that can provide a good basis for imagining and helping develop just transformations to water sustainability.

Mining activities are notorious for their environmental impact, with acid mine drainage (AMD) being among the most significant issues. Specifically, AMD has recently been a topical issue of prime concern, primarily due to the magnitude of its environmental, ecotoxicological, and socioeconomic impacts. AMD originates from both active and abandoned mines (primarily gold and coal) and is encountered in Canada, China, Russia, South Africa, USA, and other countries with strong mining industry. Owing to its acidity, AMD contains elevated levels of dissolved (toxic) metals, metalloids, rare-earth elements, radionuclides, and sulfates. Practical and cost-effective solutions to prevent its formation are still pending, while for its treatment active (driven by frequent input of chemicals and energy) or passive (based on oxidation/reduction) technologies are typically employed with the first being more efficient in contaminants removal, however, at the expense of process complexity, cost, and materials and energy consumption. More recently, and under the circular economy concept, hybrid (combination of active and passive technologies) and particularly integrated (sequential or stepwise treatment) systems have been explored for AMD beneficiation and valorisation. These systems are costly to install and operate but are cleaner production systems since they can effectively prevent pollution and can be used for closed-loop and sustainable AMD management (e.g., zero liquid discharge (ZLD) systems). Herein, the body of knowledge on AMD treatment, beneficiation (metals/minerals recovery), valorisation (water reclamation), and life cycle assessment (LCA) is comprehensively reviewed and discussed, with focus placed on circular economy. Future research directions to introduce reuse, recycle, and resource recovery paradigms in wastewater treatment and to inspire innovation in valorising this toxic and hazardous effluent are also provided. Overall, AMD beneficiation and valorisation appears promising since the reclaimed water and the recovered minerals/metals could offset treatment costs and environmental impacts. However, the main challenges include high-cost, complexity, co-contamination in the recovered minerals, and the generation of a higly heterogeneous and mineralised sludge.

This study proposes a reservoir yield analysis that incorporates the realities of upstream illegal human activities relating to water abstraction. The study assesses the impact of such unlawful human activities on reservoir storage and yields quantitatively. A reservoir operation water balance model was simulated and coupled with upstream irrigation users’ propensity to unauthorized water abstraction and set to co-evolve for the entire simulation period. The model was developed using four-state drivers (hydrological state, users’ compliance, management competence and reservoir performance). The impact of human behaviour (users’ and management) was assessed using 9 plausible human behaviour scenarios. The model was applied to a system of 5 reservoirs using the 90-year historical hydrologic dataset. The trajectories of the storage, yield-demand and storage-yield ratios were analyzed under different human behaviour scenarios. Both storage and yield were found to substantially decrease as users’ compliance and management competence deteriorated for the same reservoir hydrological state. Depending on the scenario, the annual yield (%) was observed to reduce from 100 to 80 or 50 or even 30 of the annual demand due to changing behaviour. Also, most of the years in which the yield differs significantly from one scenario to the other are years with shallow storage due to drought. A yield difference of about 23% was recorded between the scenarios without and with the highest unauthorized abstractions. The study, therefore, revealed how human behaviour can significantly affect reservoir storage and yield performances. This highlighted the need to be incorporating the impact of unlawful human activities into yield analysis models to quantitatively assess the impact of human behaviour on reservoir performance.

Knowledge on hydraulic characteristics of fractured crystalline basement aquifers is limited resulting to lack of reliable information for effective groundwater management. This is crucial as these aquifers provide good sources of potable water in most rural communities. Heterogeneous nature of these aquifers requires detailed understanding and accurate estimation of hydraulic characteristics. This study estimated hydraulic characteristics of a fractured crystalline basement aquifer and inferred their influence on groundwater storage potential and flow. Aquifer Test Solver was used for automatic curve matching to identify appropriate aquifer models and test solutions for estimating hydraulic characteristics. Root-mean-square error (RMSE), mean absolute error (MAE) and correlation coefficient (R) were used to evaluate the performance of the fitted models. Plotted derivative curves were used to identify the presence of fracture dewatering in the aquifer. The R, RMSE and MAE ranged from 0.702 to 0.995, 0.31-3.45 m and 0.23 to 3.06 m, respectively. The fits between measured and estimated drawdowns were good and performance mostly acceptable and comparable to those of related studies. Storativity, transmissivity and hydraulic conductivity ranged from 0.0003 to 0.0680, 0.78 to 12.3 m(2)/day and 8.56 x 10(-7) to 5.32 x 10(-6) m/s, respectively. The storage potential of the aquifer varied from low to high, ability to transmit water per unit area was mostly medium though the ability to transmit water through its entire thickness was mostly low. The study area is dominated by leaky aquifer and fracture dewatering. Groundwater use should be monitored and managed effectively to avoid fracture dewatering and its associated risks.

Rainwater harvesting (RWH) from roofs or other impervious surfaces for on-site use is a common source of water supply in many regions of the world. Modeling RWH storage-yield-reliability relationships is fundamentally similar to the modeling of these relationships for water supply reservoirs, and the commonly used RWH storage-yield analysis methods are adaptations of reservoir storage-yield analysis methods. Continuous simulation via behavior analysis is a commonly applied and versatile method for RWH storage-yield analysis and is presented. The sequent peak algorithm and Rippl's method are described. The chapter discusses the key considerations for enabling effective storage-yield-reliability analysis. It highlights the need to: obtain and apply as long and reliable dataset of rainfall as possible; apply a realistic modeling approach such as continuous daily simulation, and; incorporate a statistics-based assessment of reliability.

Water resources infrastructure is critical for energy and food security; however, the development of large-scale infrastructure, such as hydropower dams, may significantly alter downstream flows, potentially leading to water resources management conflicts and disputes. Mutually agreed upon water sharing policies for the operation of existing or new reservoirs is one of the most effective strategies for mitigating conflict, yet this is a complex task involving the estimation of available water, identification of users and demands, procedures for water sharing, etc. A water sharing policy framework that incorporates reservoir operating rules optimization based on conflicting uses and natural hydrologic variability, specifically tailored to drought conditions, is proposed. First, the trade-off between downstream and upstream water availability utilizing multi-objective optimization of reservoir operating rules is established. Next, reservoir operation with the candidate (optimal) rules is simulated, followed by their performance evaluations, and the rule selections for balancing water uses. Subsequently, a relationship between the reservoir operations simulated from the selected rules and drought-specific conditions is built to derive water sharing policies. Finally, the reservoir operating rules are re-optimized to evaluate the effectiveness of the drought-specific water sharing policies. With a case study of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile river, it is demonstrated that the derived water sharing policy can balance GERD power generation and downstream releases, especially in dry conditions, effectively sharing the hydrologic risk in inflow variability among riparian countries. The proposed framework offers a robust approach to inform water sharing policies for sustainable management of water resources.

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As water demand increases rainwater harvesting (RWH) systems are increasingly being installed for water supply but comprehensive hydrologic design guidelines for RWH do not exist in many parts of the world. The objective of this study was to develop guidelines for the hydrologic design and assessment of rainwater harvesting (RWH) systems in the City of Johannesburg, South Africa. The data for developing the guidelines were mainly obtained from multiple daily simulations of potential RWH systems in the city. The simulations used daily rainfall from 8 stations and demands based on the probable non-potable uses of RWH systems – toilet flushing, air conditioning and irrigation. The guidelines were confined to systems that would typically fill up in the wet season and empty towards the end of the dry season of the same year. Therefore, supply-to-demand ratios ranging from 0.1 to 0.9 were applied. Two generalized design charts of dimensionless relationships were developed. One relates the yield ratio with supply-to-demand ratio and reliability while the other relates the yield ratio with the storage-to-demand ratio and reliability. Reliability was defined as the probability of exceedance of annual yield in order to incorporate the large inter-annual variability of rainfall experienced in the region. The analyses and design of an example RWH system is used to illustrate the application of the design charts.

Contour ridges are an in-situ rainwater harvesting technology developed initially for soil erosion control but are currently also widely promoted for rainwater harvesting. The effectiveness of contour ridges depends on geophysical, hydro-climatic and socio economic factors that are highly varied in time and space. Furthermore, field-scale data on these factors are often unavailable. This together with the complexity of hydrological processes at field scale limits the application of classical distributed process modelling to highly-instrumented experimental fields. This paper presents a framework that combines fuzzy logic and process-based approach for modelling contour ridges for rainwater harvesting where detailed field data are not available. Water balance for a representative contour-ridged field incorporating the water flow processes across the boundaries is integrated with fuzzy logic to incorporate the uncertainties in estimating runoff. The model is tested using data collected during the 2009/2010 and 2010/2011 rainfall seasons from two contour-ridged fields in Zhulube located in the semi-arid parts of Zimbabwe. The model is found to replicate soil moisture in the root zone reasonably well (NSE = 0.55 to 0.66 and PBIAS = −1.3 to 6.1 %). The results show that combining fuzzy logic and process based approaches can adequately model soil moisture in a contour ridged-field and could help to assess the water dynamics in contour ridged fields.

In this study, a process of fractional and step-wise recovery of metals from Acid Mine Drainage (AMD) using calcined cryptocrystalline magnesite was explored. pH Redox Equilibrium (in C language) (PHREEQC) was used to complement the experimental studies. Half a liter (1/2 L) of coal mine drainage was used for chemical species recovery. The metal recovery process was done using an overhead stirrer in a step-wise fashion. Chemical species were recovered via a sequential and fractional precipitation of chemical components at varying pH gradients. Both experimental and modelling results revealed that chemical species were recovered at varying pH ranges. Fe was recovered at pH >= 3-3.5, gypsum at pH >= 4-10, Al at pH >= 6.5, Mn at pH >= 9.5, Cu at pH >= 7, Zn at pH >= 8, Pb at pH >= 8 and Ni at pH >= 9. Greater than 99% efficacy was achieved for all the chemical species at given pH regimes. The experimental results corroborated the geochemical modelling and XRD results. This technology successfully proved that calcined cryptocrystalline magnesite can be used as a seeding material to facilitate a fractional and sequential recovery of chemical species from acid mine drainage. This will go a long way in minimising the disposal cost incurred from the generated sludge, thus, off-setting the running cost and making the acid mine drainage (AMD) treatment process environmentally friendly. This will also contribute significantly in environmental engineering processes.

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic monthly rainfalls were 86 and 90% of the mean naturalised streamflow. In calibration, 33% of the naturalised flow located within the streamflow ranges with historic rainfall simulations and using stochastic rainfalls increased this to 66%. In validation the respective percentages of naturalised flows located within the simulated streamflow ranges were 32 and 72% respectively. The analysis reveals that monthly areal rainfall uncertainty is significant and incorporating it into streamflow simulation would add validity to the results.

The objective of this study was to develop guidelines for analysing rainwater harvesting (RWH) systems of shopping centres in South Africa. A model consisting of three dimensionless relationships relating rainwater supply and demand to storage capacity, yield and reliability was formulated. Data from daily simulation of potential RWH systems of 19 shopping were used to obtain the relationships. The simulations revealed within-year storage behaviour with considerable variation of annual yield. By applying the Weibull plotting position formula, yield–reliability relationships were derived. The aim to maximize yield and reliability whilst minimizing storage identified Pareto-optimal combinations of the three variables and these combinations were used to develop two dimensionless relationships. An additional relationship based on the dependence of the slope of the yield–reliability plots on yield was formulated to enable analysis of hydrologically non-optimal systems. Verification tests using four RWH systems obtained results that matched those from simulation and the model could therefore be applied for RWH feasibility analysis and preliminary design. This study highlights the need to incorporate inter-annual variability in RWH analysis and shows how reliability can be used to quantify this. This study further demonstrates how reliability can be fully integrated into regression relationships for generalized RWH analysis.

Pollution source identification in groundwater contaminant transport using limited concentration data of the contaminant plume is an inverse problem. In this paper, we develop a numerical-optimization approach that utilizes the green element method (GEM) and the shuffled complex evolutionary (SCE) technique to identify pollution source strengths and recover the concentration distribution of the plume for contaminant transport in groundwater systems. Two test cases are used to evaluate our proposed methodology: 1D transient case with an analytical solution and 2D transient hypothetical case that mimics a real life situation. The results indicate that the proposed methodology gives good estimates of the release history and the historical distribution of the plume even in the presence of observation and parameter errors.

Hluhluwe Dam, with a 30 million m3 reservoir that supplies water for irrigation and Hluhluwe municipality in Kwa-Zulu Natal Province, South Africa, was consistently experiencing low storage levels over several non-drought years since 2001. The dam was operated by rules of thumb and there were no records of water releases for irrigation - the main user of the dam. This paper describes an assessment of the historic behaviour of the reservoir since its completion in 1964 and the development of operating rules that accounted for: i) the multiple and different levels of reliability at which municipal and irrigation demands need to be supplied, and ii) inter-annual and inter-decadal variability of climate and inflows into the dam. The assessment of the behaviour of the reservoir was done by simulation assuming trigonometric rule curves that were optimized to maximize both yield and storage state using the SCE-UA method. The resulting reservoir behaviour matched the observed historic trajectory reasonably well and indicated that the dam has mainly been operated at a demand of 10 million m3/year until 2000 when the demand suddenly rose to 25 million m3/year. Operating rules were developed from a statistical analysis of the base yields from 500 simulations of the reservoir each using 5 year-long stochastically generated sequences of inflows, rainfall and evaporation. After the implementation of the operating rules in 2009, the storage state of the dam improved and matched those of other reservoirs in the region that had established operating rules.