Industrial effluents with high concentrations of heavy metals are widespread pollutants of great concerns as they are known to be persistent and non-degradable. Continuous monitoring and treatment of the effluents become pertinent because of their impacts on wastewater treatment plants. The aim of this study is to determine the correlation between heavy metal pollution in water and the location of industries in order to ascertain the effectiveness of the municipal waste water treatment plant. Heavy metal identification and physico-chemical analysis were done using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and multi-parameter probe respectively. Correlation coefficients of the measured values were done to investigate the effect of the industrial effluents on the treatment plants. Heavy metal resistant bacteria were identified and characterised by polymerase chain reaction and sequencing. Leeuwkuil wastewater treatment plants were effective in maintaining temperature, pH, and chemical oxygen demand within South Africa green drop and SAGG Standards whereas the purification plant was effective in maintaining the values of Cu, Zn, Al, temperature, BOD, COD, and TDS within the SANS and WHO standard for potable water. This findings indicated the need for the treatment plants to be reviewed.The industrial wastewater were identified as a point source of heavy metal pollution that influenced Leeuwkuil wastewater treatment plants and the purification plants in Vaal, Vereenining South Africa. Pseudomonas aeruginosa, Serratia marcescens, Bacillus sp. strain and Bacillus toyonensis that showed 100% similarity were found to be resistant to Al, Cu, Pb and Zn. These identified bacteria can be considered for further study in bioremediation. / Environmental Sciences / M. Sc. (Environmental Science)

Includes bibliographical references (leaves 112-115) Towed DC Resistivity and Transient Electromagnetic arrays have been trialled for suitability in monitoring salt-loads on the Murray River at Waikerie, South Australia.

Includes list of publications issued during the candidature. / Bibliography: leaves 176-197. / iii, ix, 197, [22] leaves : ill., maps ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Phosphorus retention was measured in five pilot-scaled constructed wetlands with different configurations in terms of macrophyte species and substrates in order to evaluate the phosphorus removal efficiency of water plants and substrates in experimental ponds; assess the contribution of macrophytes to phosphorus removal through direct uptake, modification of water chemistry and impacts on the phosphorus adsorption characteristics of substrate; and, contribute to the optimal design and operation of constructed wetlands for the treatment of agricultural drainage water. / Thesis (Ph.D.)--University of Adelaide, Dept. of Soil and Water, 2002?

Two of the most important environmental challenges in the 21st century are to protect the quality of fresh water resources and to utilize renewable energy sources to lower greenhouse gas emissions. This study contributes to the solution of the first challenge by providing methodologies for optimal design of real-time water quality monitoring systems and interpretation of data supplied by the monitoring system to identify potential pollution sources in river networks. In this study, the optimal river water quality monitoring network design aspect of the overall monitoring program is addressed by a novel methodology for the analysis of this problem. In this analysis, the locations of sampling sites are determined such that the contaminant detection time is minimized for the river network while achieving maximum reliability for the monitoring system performance. The data collected from these monitoring stations can be used to identify contamination source locations. This study suggests a methodology that utilizes a classification routine which associates the observations on a contaminant spill with one or more of the candidate spill locations in the river network. This approach consists of a training step followed by a sequential elimination of the candidate spill locations which lead to the identification of potential spill locations. In order to contribute the solution of the second environmental challenge, this study suggests utilizing available excess energy in water distribution systems by providing a methodology for optimal design of energy recovery systems. The energy recovery in water distribution systems is possible by using micro hydroelectric turbines to harvest available excess energy inevitably produced to satisfy consumer demands and to maintain adequate pressures. In this study, an optimization approach for the design of energy recovery systems in water distribution networks is proposed. This methodology is based on finding the best locations for micro hydroelectric plants in the network to recover the excess energy. Due to the unsteady nature of flow in water distribution networks, the proposed methodology also determines optimum operation schedules for the micro turbines.

In this study, methodologies for modeling grey uncertainty in water resources systems are developed, specifically for the problems in two identified areas in water resources: waste load allocation in streams and floodplain planning. A water resources system is associated with some degree of uncertainty, due to randomness of hydrologic and hydraulic parameters, imprecision and subjectivity in management goals, inappropriateness in model selection, inexactness of different input parameters for inadequacy of data, etc. Uncertainty due to randomness of input parameters could be modeled by the probabilistic models, when probability distributions of the parameters may be estimated. Uncertainties due to imprecision in the management problem may be addressed by the fuzzy decision models. In addition, some parameters in any water resources problems need to be addressed as grey parameters, due to inadequate data for an accurate estimation but with known extreme bounds of the parameter values. Such inexactness or grey uncertainty in the model parameters can be addressed by the inexact or grey optimization models, representing the parameters as interval grey numbers. The research study presented in this thesis deals with the development of grey and fuzzy optimization models, and the combination of the two for water resources systems decision-making. Three grey fuzzy optimization models for waste load allocation, namely (i) Grey Fuzzy Waste Load Allocation Model (GFWLAM), (ii) two-phase GFWLAM and (iii) multiobjective GFWLAM, and a Grey Integer Programming (GIP) model for floodplain planning, are developed in this study. The Grey Fuzzy Waste Load Allocation Model (GFWLAM) for water quality management of river system addresses uncertainty in the membership functions for imprecisely stated management goals of the Pollution Control Agency (PCA) and dischargers. To address the imprecision in fixing the boundaries of membership functions (also known as membership parameters), the membership functions themselves are treated as imprecise in the model and the membership parameters are expressed as interval grey numbers. The conflict between the fuzzy goals of PCA and dischargers is modeled using the concept of fuzzy decision, but because of treating the membership parameters as interval grey numbers, in the present study, the notion of ‘fuzzy decision’ is extended to the notion of ‘grey fuzzy decision’. A terminology ‘grey fuzzy decision’ is used to represent the fuzzy decision resulting from the imprecise membership functions. The model provides flexibility for PCA and dischargers to specify their aspirations independently, as the membership parameters for membership functions are interval grey numbers in place of a deterministic real number. In the solution, optimal fractional removal levels of the pollutants are obtained in the form of interval grey numbers. This enhances the flexibility and applicability in decision-making, as the decision-maker gets a range of optimal solutions for fixing the final decision scheme considering technical and economic feasibility of the pollutant treatment levels. The methodology is demonstrated with the case studies of a hypothetical river system and the Tunga-Bhadra river system in Karnataka, India. Formulation of GFWLAM is based on the approach for solving fuzzy multiple objective optimization problem using max-min as the operator, which usually may not result in a unique solution. The two-phase GFWLAM captures all the alternative optimal solutions of the GFWLAM. The solution technique in the Phase 1 of two-phase GFWLAM is the same as that of GFWLAM. The Phase 2 maximizes upper bounds and minimizes lower bounds of decision variables, keeping the optimal value of goal fulfillment level same as obtained in the Phase 1. The two-phase GFWLAM gives the unique, widest, intervals of the optimal fractional removal levels of pollutant corresponding to the optimal value of goal fulfillment level. The solution increases the widths of interval-valued fractional removal levels of pollutants by capturing all the alternative optimal solutions and thus enhances the flexibility and applicability in decision-making. The model is applied to the case study of Tunga-Bhadra river system, which shows the existence of multiple solutions when the GFWLAM is applied to the same case study. The width of the interval of optimal fractional removal level plays an important role in the GFWLAM, as more width in the fractional removals implies a wider choice to the decision-makers and more applicability in decision-making. The multiobjective GFWLAM maximizes the width of the interval-valued fractional removal levels for providing a latitude in decision-making and minimizes the width of goal fulfillment level for reducing the system uncertainty. The multiobjective GFWLAM gives a new methodology to get a satisfactory deterministic equivalent of a grey fuzzy optimization problem, using the concept of acceptability index for a meaningful ranking between two partially or fully overlapping intervals. The resulting multiobjective optimization model is solved by fuzzy multiobjective optimization technique. The consistency of the solution is verified by solving the problem with fuzzy goal programming technique. The multiobjective GFWLAM avoids intermediate submodels unlike GFWLAM, so that the solution from a single deterministic equivalent of the GFWLAM adequately covers all possible situations. Although the solutions obtained from multiobjective GFWLAM provide more flexibility than those of the GFWLAM, its application is limited to grey fuzzy goals expressed by linear imprecise membership functions only, whereas GFWLAM has the capability to solve the model with any monotonic nonlinear imprecise membership functions also. The methodology is demonstrated with the case studies of a hypothetical river system and the Tunga-Bhadra river system in Karnataka, India. The Grey Integer Programming (GIP) model for floodplain planning is based on the floodplain planning model developed by Lund (2002), to identify an optimal mix of flood damage reduction options with probabilistic flood descriptions. The model demonstrates how the uncertainty of various input parameters in a floodplain planning problem can be modeled using interval grey numbers in the optimization model. The GIP model for floodplain planning does not replace a post-optimality analysis (e.g., sensitivity analysis, dual theory, parametric programming, etc.), but it provides additional information for interpretation of the optimal solutions. The results obtained from GIP model confirm that the GIP is a useful technique for interpretation of the solutions particularly when a number of potential feasible measures are available in a large scale floodplain planning problem. Though the present study does not directly compare the GIP technique with sensitivity analysis, the results indicate that the rigor and extent of post-optimality analyses may be reduced with the use of GIP for a large scale floodplain planning problem. Application of the GIP model is demonstrated with the hypothetical example as presented in Lund (2002).

Waste Load Allocation (WLA) in rivers refers to the determination of required pollutant fractional removal levels at a set of point sources of pollution to ensure that water quality standards are maintained throughout the system. Optimal waste load allocation implies that the selected pollution treatment vector not only maintains the water quality standards, but also results in the best value for the objective function defined for the management problem. Waste load allocation problems are characterized by uncertainties due to the randomness and imprecision. Uncertainty due to randomness arises mainly due to the random nature of the variables influencing the water quality. Uncertainty due to imprecision or fuzziness is associated with setting up the water quality standards and goals of the Pollution Control Agencies (PCA), and the dischargers (e.g., industries and municipal dischargers). Many decision problems in water resources applications are dominated by natural, extreme, rarely occurring, uncertain events. However usually such events will be absent or be rarely present in the historical records. Due to the scarcity of information of these uncertain events, a realistic decision-making becomes difficult. Furthermore, water resources planners often deal with imprecision, mostly due to imperfect knowledge and insufficient or inadequate data. Therefore missing data is very common in most water resources decision problems. Missing data introduces inaccuracy in analysis and evaluation. For instance, the sample mean of the available data can be an inaccurate estimate of the mean of the complete data. Use of sample statistics estimated from inadequate samples in WLA models would lead to incorrect decisions. Therefore there is a necessity to incorporate the uncertainty due to missing data also in WLA models in addition to the uncertainties due to randomness and imprecision. The uncertainty in the input parameters due to missing or inadequate data renders the input parameters (such as mean and variance) as interval grey parameters in water quality decision-making. In a Fuzzy Waste Load Allocation Model (FWLAM), randomness and imprecision both can be addressed simultaneously by using the concept of fuzzy risk of low water quality (Mujumdar and Sasikumar, 2002). In the present work, an attempt is made to also address uncertainty due to partial ignorance due to missing data or inadequate data in the samples of input variables in FWLAM, considering the fuzzy risk approach proposed by Mujumdar and Sasikumar (2002). To address the uncertainty due to missing data or inadequate data, the input parameters (such as mean and variance) are considered as interval grey numbers. The resulting output water quality indicator (such as DO) will also, consequently, be an interval grey number. The fuzzy risk will also be interval grey number when output water quality indicator is an interval grey number. A methodology is developed for the computation of grey fuzzy risk of low water quality, when the input variables are characterized by uncertainty due to partial ignorance resulting from missing or inadequate data in the samples of input variables. To achieve this, an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system to address uncertainties due to randomness, fuzziness and also due to missing data or inadequate data. Monte Carlo Simulation (MCS) incorporating a water quality simulation model is performed two times for each set of randomly generated input variables: once for obtaining the upper bound of DO and once for the lower bound of DO, by using appropriate upper or lower bounds of interval grey input variables. These two bounds of DO are used in the estimation of grey fuzzy risk by substituting the upper and lower values of fuzzy membership functions of low water quality. A backward finite difference scheme (Chapra, 1997) is used to solve the water quality simulation model. The goal of PCA is to minimize the bounds of grey fuzzy risk, whereas the goal of dischargers is to minimize the fractional removal levels. The two sets of goals are conflicting with each other. Fuzzy multiobjective optimization technique is used to formulate the multiobjective model to provide best compromise solutions. Probabilistic Global Search Lausanne (PGSL) method is used to solve the optimization problem. Finally the results of the model are compared with the results of risk minimization model (Ghosh and Mujumdar, 2006), when the methodology is applied to the case study of the Tunga-Bhadra river system in South India. The model is capable of determining a grey fuzzy risk with the corresponding bounds of DO, at each check point, rather than specifying a single value of fuzzy risk as done in a Fuzzy Waste Load Allocation Model (FWLAM). The IFWLAM developed is based on fuzzy multiobjective optimization problem with ‘max-min’ as the operator, which usually may not result in a unique solution and there exists a possibility of obtaining multiple solutions (Karmakar and Mujumdar, 2006b). Karmakar and Mujumdar (2006b) developed a two-phase Grey Fuzzy Waste Load Allocation Model (two-phase GFWLAM), to determine the widest range of interval-valued optimal decision variables, resulting in the same value of interval-valued optimal goal fulfillment level as obtained from GFWLAM (Karmakar and Mujumdar 2006a). Following Karmakar and Mujumdar (2006b), two optimization models are developed in this study to capture all the decision alternatives or multiple solutions: one to maximize and the other to minimize the summation of membership functions of the dischargers by keeping the maximum goal fulfillment level same as that obtained in IFWLAM to obtain a lower limit and an upper limit of fractional removal levels respectively. The aim of the two optimization models is to obtain a range of fractional removal levels for the dischargers such that the resultant grey fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision-making. The models are applied to the case study of Tunga-Bhadra river system. A range of upper and lower limits of fractional removal levels is obtained for each discharger; within this range, the discharger can select the fractional removal level so that the resulting grey fuzzy risk will also be within specified bounds. In IFWLAM, the membership functions are subjective, and lower and upper bounds are arbitrarily fixed. Karmakar and Mujumdar (2006a) developed a Grey Fuzzy Waste Load Allocation Model (GFWLAM), in which uncertainty in the values of membership parameters is quantified by treating them as interval grey numbers. Imprecise membership functions are assigned for the goals of PCA and dischargers. Following Karmakar and Mujumdar (2006a), a Grey Optimization Model with Grey Fuzzy Risk is developed in the present study to address the uncertainty in the memebership functions of IFWLAM. The goals of PCA and dischargers are considered as grey fuzzy goals with imprecise membership functions. Imprecise membership functions are assigned to the fuzzy set of low water quality and fuzzy set of low risk. The grey fuzzy risk approach is included to account for the uncertainty due to missing data or inadequate data in the samples of input variables as done in IFWLAM. Randomness and imprecision associated with various water quality influencing variables and parameters of the river system are considered through a Monte-Carlo simulation when input parameters (such as mean and variance) are interval grey numbers. The model application is demonstrated with the case study of Tunga-Bhadra river system in South India. Finally the results of the model are compared with the results of GFWLAM (Karmakar and Mujumdar, 2006a). For the case study of Tunga Bhadra River system, it is observed that the fractional removal levels are higher for Grey Optimization Model with Grey Fuzzy Risk compared to GFWLAM (Karmakar and Mujumdar, 2006a) and therefore the resulting risk values at each check point are reduced to a significant extent. The models give a set of flexible policies (range of fractional removal levels). Corresponding optimal values of goal fulfillment level and the grey fuzzy risk are all in terms of interval grey numbers. The IFWLAM and Grey Fuzzy Optimization Model with Grey Fuzzy Risk, developed in the study do not limit their application to any particular pollutant or water quality indicator in the river system. Given appropriate transfer functions for spatial distribution of the pollutants in water body, the models can be used for water quality management of any general river system.

South Africa is a semi arid country in which the average rainfall of 450mm/year is well below the world average of about 860mm/year. As a result, South Africa’s water resources are scarce in global terms and limited in extent. Current predictions are that demand will outstrip water availability in the next 15 years. A coordinated approach to improve both water quality and quantity is needed and in order to achieve that, it is crucial to strengthen capacities of local community involvement in identifying the problems that affect them and strategies to solve them. This research was undertaken to develop a deeper understanding of community learning processes in integrated water resources management (IWRM) practices. The study drew on situated and social learning theory which explains that knowledge and skills are learned and embedded in the contexts in which knowledge is obtained and applied in everyday situations. Multiple data collection techniques were used within a case study design and included document analysis, interviews, focus group discussions and field observations. Data analysis was done in three phases and involved uncovering patterns and trends in the data sets. In this context I discovered, through careful observation and interviews with members of the different communities of practice, that people are learning through social learning interactions with other community members as they engage in their daily water management and food production practices. Learning interactions take place through both informal and formal processes such as meetings, training workshops, conversations and interactions with outsiders. I also discovered that people learn from ‘external groups’ or training programmes which bring new knowledge and expertise, but this needs to be contextualised in the local communities of practice. The research has also shown that there are a number of challenges that appear to exist in these learning contexts. For instance it was found that participation and social learning processes and interactions are influenced by a range of causal mechanisms that are contextual. These insights into how communities learn, as well as the tensions and difficulties that are experienced in the learning processes are important for furthering learning and participation in community-based IWRM practices, projects and programmes.

Inadequately treated wastewater effluent is harmful to the receiving aquatic environment. Water-borne chemicals and microbial pathogens pose a health risk to anyone living downstream from sewage treatment facilities. This study assessed the effluent from a package plant with a design capacity of 48kℓ/24 hours, servicing 12 household units and a restaurant in Mogale City. Over a 12 month period, fortnightly water samples were collected from ten selected sites including two boreholes, a river and two dams. Standard parameters including physical (pH, EC, temperature, DO and SS), chemical (nutrient concentration) and biological (bacterial counts) were analysed using handheld meters, standard membrane filter techniques and colorimetric methods. One borehole was affected by pathogen and nitrate runoff from an adjacent poultry farm. If regularly monitored, the package plant effectively removed microbes (most samples contained 0 cfu/100mℓ) but above limit COD, ammonia and phosphate was released in the effluent (with maximum values of 322 mg/ℓ, 42.52 mg/ℓ and 7.18 mg/ℓ, respectively). Generally, river and dam water at the site was of good quality. / Environmental Science / M. Sc. (Environmental Science)

CAPES; CNPq / Considerada como o maior complexo hídrico do Paraná, a Bacia do Iguaçu tem importância estratégica, principalmente no que se refere à característica do rio – por sua extensão e potencial hidrelétrico altamente explorado – com a formação de cinco reservatórios para gerar mais de 6.000 MW de energia. Em detrimento de sua importância estratégica, o represamento em cascada do Rio Iguaçu faz com que suas características hidráulicas sejam modificadas, podendo gerar passivos ambientais, como a incidência de florações de cianobactérias nos reservatórios, podendo apresentar potencial tóxico. São poucos estudos que contemplem a bacia do Iguaçu como um todo, avaliando o rio e os reservatórios formadores desse importante complexo hidrográfico. Pautado nesse entendimento, este estudo tem como objetivo avaliar a relação entre a qualidade da água na Bacia do Rio Iguaçu e a influência na ocorrência e concentração da cianotoxina microcistina-LR nos seus reservatórios. Com esta finalidade, foram realizadas três coletas de amostras de água no Rio Iguaçu da sua nascente na Região Metropolitana de Curitiba até sua foz, em Foz do Iguaçu. Também foram realizadas amostragens em quatro dos cinco reservatórios grandes reservatórios da Bacia: Foz do Areia, Segredo, Salto Santiago e Salto Caxias e avaliado variáveis físicas e químicas, teor e fonte de matéria orgânica e a contaminação nos reservatórios pela cianotoxina microcistina-LR na água. A avaliação dos resultados obtidos possibilitou a observação das principais influências no Rio Iguaçu, tais como atividade antrópica na Região Metropolitana de Curitiba, sazonalidade, e a influencia da mudança hidráulica promovida pelos reservatórios. Nos reservatórios estudados, as principais variáveis estão relacionadas com a sazonalidade, tempo de retenção hidráulico, nutrientes e produtividade primária. A Microcistina-LR foi detectada nos reservatórios de Foz do Areia, Segredo e Salto Santiago, este ultimo com a maior concentração de toxina intracelular obtida no centro da região lacustre, com concentração de 18,62 μg por litro filtrado e Foz do Areia, com 65,5 μg por litro filtrado em um ponto de margem com alta concentração de clorofila-a. As analises estatísticas permitiram a compreensão das variáveis possivelmente responsáveis pelo aumento da biomassa fitoplantônica, porém, não foi possível obter relações significativas que pudessem explicar a produção da microcistina intracelular. Diante dos resultados observados, fazem-se necessárias políticas de maior controle ambiental, visando à melhoria no tratamento de efluentes e uso e ocupação do solo em toda a extensão da bacia hidrográfica, porém, mais urgentemente na região do Alto Iguaçu. / Considered the largest hydric complex in Paraná, the basin Iguaçu has strategic importance, especially regarding the characteristics of the river, by its great extension and the highly exploited hydropower, forming five reservoirs that generate more than 6.000 MW energy. In detriment of its strategic significance, the damming of the Iguassu River modifies the hydraulic characteristics, which may cause some environmental damage, as the incidence of cyanobacterial blooms in reservoirs may submit toxic potential. Are few studies that consider the Iguaçu basin as a whole, evaluating the river and reservoirs forming this important hydrographic complex. Guided by this understanding, this study aims to evaluate the relationship between water quality in the Rio Iguaçu basin and the influence on the occurrence and concentration of microcystin-LR in its reservoirs. For this purpose, three collections of sampling were performed in Iguazu River from its source in the Metropolitan Region of Curitiba to its mouth in Foz do Iguaçu. Samples in four of the five major reservoirs Basin reservoirs were also performed: Foz do Areia, Segredo, Salto and Salto Caxias Santiago and evaluated physical and chemical variables, content and source of organic matter in reservoirs and contamination by microcystin-LR cyanotoxin. Furthermore, in the reservoirs was evaluated the possibility of contamination by cyanotoxin microcystin-LR. The results evaluation enabled the observation of the main influences on the Iguaçu River, such as anthropogenic influences in Curitiba Metropolitan Region, seasonality, and the influence of change promoted by the hydraulic reservoirs. In the studied reservoirs, the main variables are related to hydraulic seasonal retention time, nutrients and primary productivity. The microcystin- LR was detected in the reservoirs of Foz do Areia, Segredo and Salto Santiago, the latter with the highest concentration of intracellular toxin in the center of the lake region, with a concentration of 18.62μg per liter filtered and Foz do Areia, 65μg, on a point margin with a high concentration of chlorophyll-a. The statistical analysis allowed to understand the variables as possibly responsible for increasing phytoplankton biomass, however, it was not possible to obtain significant relations which could explain the production of intracellular microcystin. Front of the observed outcomes, this study points to the need of policies to increase environmental control, aiming to improve in wastewater treatment and the ground use and occupation all along the basin, but more urgently in the Alto Iguaçu.

Public participation in water management processes is one of the internationally recognised and adopted principles of Integrated Water Resource Management. The South African Department of Water Affairs and Forestry aims to facilitate the decentralisation of water management powers to the local community level via the establishment of regional and local water management institutions, namely Catchment Management Agencies, Water User Associations and Catchment Forums. The National Water Act (No. 36 of 1998) acknowledges that the discriminatory laws and practices of the past have prevented equal access to water and the use of water resources. The contribution of water management institutions to social and economic development, in particular poverty eradication and food security, is mentioned in the water act. The participation of poor rural communities living in the Kat valley, an area where an elite minority reap the benefits of water use for agriculture, is the focus of this research. Their participation, perceptions and experiences are documented and explored to determine how the promulgation of post-apartheid water policy and legislation has affected their access to water. The results of this research are based on data collected from several methods including surveys, workshops and observation. Analysis of these data revealed the complicated and stagnant nature of participation from Kat valley rural communities in local water management initiatives and organisations. Existing water management organisations were not successful in stimulating poor people’s participation as they were unable to address their primary concerns, namely a secure source of potable water, employment and access to water for agricultural purposes. This thesis asserts that the Department of Water Affairs and Forestry, as the custodian of South Africa’s water resources, has not taken on a supportive, accountable role in assisting marginalised communities with improving their access to water for domestic purposes and securing access to water rights for productive use. This, in turn, has led to dissatisfaction among these communities and a wariness of participatory activities that focus mainly on raising environmental awareness. The establishment of effective accountability relationships among all stakeholders, pro-poor water management structures and initiatives, as well as integrated and co-operative management of natural resources, are needed to revitalise the present participation of poor communities living in rural areas.