Rainfed agriculture is a critical component of global food production and farmers' livelihoods in developing countries, yet it is increasingly under pressure from global climate change. This escalating climate risk impacts both the production (upstream) and industrial (downstream) segments of the agricultural supply chain. Addressing such crises in these regions requires approaches that go beyond conventional methods such as supply augmentation. Recent attention has shifted toward regenerative agriculture, which aims to boost rainfed agriculture without the need for irrigation while mitigating climate risks in economically vulnerable regions. However, sustainable solutions such as water-saving interventions have often lacked adequate financial support, traditionally relying on insufficient public sector investments or not given consideration at all. This case study investigates the potential of water-saving interventions to enhance crop water use efficiency in rainfed agriculture and explores how green finance mechanisms, particularly green bonds, can support the widespread adoption of such practices in the central-Indian cotton supply chain. It further aims to establish the first steps toward a transactional water trading system through the newly emerging concept of water credits, which incentivizes the conservation and efficient use of water resources. A socio-hydrological model is utilized to account for crop-water-farmer feedback and biochar is applied as the soil moisture-saving intervention. The intervention focuses on soil-hydrological dynamics and introduces field capacity changes into the model. The financial feasibility of these interventions is evaluated using a compound interest model that relates rates of return to treatment levels (tons per hectare). Results demonstrate profitability in the majority of the study area, although different treatment levels are observed for optimal returns. Annual return projections range between 3\%-12\%, with the majority of application rates clustering around 2, 15, and 30 tons/hectare, representing a regular trimodal distribution. Strong heterogeneity is observed across the region with non-linear dependence on soil-hydrological parameters. Green bonds, although eligible for such an initiative, are currently unsuitable for financial support due to the immaturity of the Indian green market, lack of issuance for agriculture and water projects, and a primary focus on large-scale projects. The study provides an initial path for a field-scale pilot application scheme in Maharashtra cotton production, though rigorous monitoring plans are essential for assessment. Despite the model's profitable outcomes, the Indian green bond market is still in the growth phase, and more mature markets (e.g., the EU and USA) with institutions that hold more diverse portfolios may be approached to support projects of such scales. Supporting a water credit system is deemed challenging due to India's strongly established groundwater-energy dynamics (irrigation and pumping with fossil fuels) and the government's erratic subsidy programs.

This study explores domestic water use in the rural areas of Santiago de Cali and Restrepo, Colombia, focusing on the application of the Values, Beliefs, and Norms (VBN) theory to understand individual water use behaviours. Recognizing the critical importance of water as a fundamental resource, the research addresses the complexities of water management, particularly in the context of increasing demand and inconsistent availability. The study seeks to fill gaps in traditional water use research by incorporating psychological factors and decision-making frameworks, aiming to contribute to the broader field of water management. Utilizing data from 926 households, the study employs a multi-linear regression analysis to examine the relationships between socio-economic factors (SEC) and VBN psychological factors with three dependent variables: perceived total water use, shower time, and the use of watersaving devices. The analysis identified significant predictors of water use behaviour, with VBN factors providing additional explanatory power beyond that of socioeconomic variables. Specifically, VBN factors accounted for an additional 2% of the variance in total water use, 3.3% in shower time, and 4% in the use of water-saving devices. Values, particularly biospheric and altruistic, were the most consistent contributors to water-saving behaviours, while beliefs had minimal impact. The findings highlight the importance of promoting biospheric and altruistic values, as well as reinforcing personal norms related to water conservation, in encouraging sustainable water use behaviours. Educational campaigns that emphasize the moral responsibility to conserve water and the community benefits of sustainable water use are likely to be effective, particularly in rural areas. The study also notes that individuals with strong egoistic values, such as a desire for unlimited water supply, are less inclined to adopt water-saving behaviours, suggesting the need for targeted interventions that connect personal benefits with conservation efforts. In conclusion, while the VBN framework provides valuable insights into specific water use behaviours, its overall impact on total domestic water use is moderated by contextual and socioeconomic factors. Future research should continue to explore these dynamics, with an emphasis on developing tailored interventions that address both the psychological and contextual determinants of water use behaviour. This approach can help policymakers and environmental educators foster more sustainable domestic water use, particularly in rural areas where such factors play a significant role.

Natural disasters, particularly floods, pose a significant threat to cities and communities, and their fre- quency and severity are increasing due to climate change. Data from the EM-DAT database reveals that floods have been the most frequent natural disasters since 2002. Projections from the Intergovern- mental Panel on Climate Change suggest that heavy rainfall events will continue to increase, making floods more likely in the 21st century.
There is an urgent need to address the socio-economic impact of these disasters, particularly on the most vulnerable populations. Economic losses not only disrupt efforts to mitigate climate change, but also worsen inequalities, especially between high and low-income groups. Traditional risk assessments are based solely on property losses. Previous research highlighted that this is not sufficient to measure the socio-economic impact of floods. An interdisciplinary approach is required to integrate methodolo- gies, improve representation of vulnerable populations and fully understand the complex challenges posed by poverty and climate change.
This study uses a modelling framework applied to a case study of Charleston, South Carolina. For the case study, an extreme hurricane was chosen to test the model. The framework aims to measure well-being losses due to flooding and to evaluate the impact of insurance policies on vulnerable groups. The well-being losses are derived from household consumption levels.
Results from the case study show that total well-being losses exceeded total asset losses. Absolute well-being losses were similar across income groups. The relative well-being losses, represented per dollar of damaged assets, were higher for the low-income groups. The implementation of insurance policies reduced overall well-being losses. When the scenario with full insurance coverage is in force, there are still well-being losses. In order to create complete resilience, it is necessary to implement multiple measures.
Further research is recommended to improve the modelling framework. Many assumptions increased the uncertainty of the model. Detailed and additional data would improve the certainty of the results. Ultimately, the research aims to provide useful evidence for policy makers and stakeholders to make more informed decisions to build resilient communities and reduce inequalities in the face of climate change.

Recent Conflict Early Warning Systems have found little evidence of predictive power of drought indicators for conflict prediction. However, this may result from the context-specificity of the drought-conflict relationship, as stressed in the more recent climate-conflict literature.

The present thesis assesses the local role of meteorological drought indicators for communal conflict prediction in North-Western Kenya, as a region where the narrative of resource-scarcity driven conflicts exists.

A local-scale literature review on conflict dynamics followed by a fixed-effects logistic regression modelling approach stress the importance of the spatial dimension when analysing drought-conflict relationships. The role of cross-border transhumance in linking climate variability to conflict occurrence is stressed by the lower confidence intervals and more significant effects when moving the regression analysis from the spatial delimitation of administrative units to the agency level of ethnic groups.

Differences in between ethnic groups in the obtained patterns of conflict behaviour in response to drought or water abundance are explained by their migratory behaviour along with a differentiated account of their relative drought vulnerability.

The lack of any considerable role of drought in the subsequently built quasi-replication of the WPS Global Early Warning Tool, is therefore assigned to the mismatch of administrative units as the spatial
unit of analysis in a pastoralist area, where herders frequently move their cattle to the other side of the border.

It is advocated for an ethnic-group centered approach to predicting conflict, which relaxes assumptions on spatial containment of conflict events. However, whether this alternative model specification leads
to a greater role of drought indicators in conflict prediction and better overall predictions, needs to be assessed in future work.

This study investigates the connection between macro-scale parameters (MSP) and micro-scale water quality parameters (MSWQP) in the Brantas River, employing a multivariate linear regression (MLR) modelling approach. The analysis reveals several critical insights into the complex dynamics of water quality in this river system.

Key findings indicate that high-quality input data, both in terms of quantity and measurement frequency, play a key role in the effectiveness of predictive models. Seasonality is a useful predictor and is recommended to be supplemented with rainfall data to better capture its influence on runoff and water quality. The study introduces the concept of basin accumulation and the implementation of buffer areas, demonstrating that these enhancements lead to improved model performance.

In conclusion, it can be said that relying just on macro-scale parameters is insufficient to generate an effective linear regression model. However, with the right optimizations and useful input data, it can be an insightful and valuable tool for water quality prediction.

Environmental guidelines (EU WFD) impose a strict effluent phosphate target on wastewater treatment plants (WWTP). An abundance of phosphate (and other nutrients) in a water body is called eutrophication. Eutrophication can lead to algal blooms which result in very low oxygen concentrations in the water. Other species, like fish and aquatic plants, can die because of the lack of oxygen. Most WWTPs in the Netherlands are performing well and reach phosphate effluent concentrations below 1 mg/l. Nevertheless, Dutch water authorities are looking for ways to improve nutrient removal to perform even better then the WDF guidelines. At the same time they are anticipating on the expectation of more strict phosphate effluent targets in the future.

This research is focusing on VFA production from the sieved fraction of activated sludge. Sieves with a mesh size of 0.5 mm were used to sieve cellulose fibers from the sludge. Microbial conversion processes are stimulated in the VFA production reactors. A pilot plant that was performed resulted in very high phosphate concentrations in the reactor. The first phase of this research was devoted to identifying the source of the high phosphate concentration. The second phase was focused on phosphate removal and recovery strategies.

It was found that 20% of the sievings consisted of PAO sludge. The conditions in the VFA production pilot lead to extreme phosphate release by PAO. This resulted in high phosphate levels ranging up to 200 mg/l.

The released phosphate potentiates recovery methods. It was not able to precipitate struvite at the low pH levels at which the VFA production reactor was operated. Calcium carbonate addition could decrease phosphate levels (50%) and can be used to control pH in the reactor. The applied method does not allow for easy recovery because the precipitate ends up in the sievings. Finally vivianite precipitation was achieved by adding FeCl2. 90% phosphate removal was achieved. The para-magnetic property of vivianite allows for easy recovery with a magnetic separator. This results in the production of 2 valuable streams from a waste stream: VFA and vivianite.

The water quality of the Brantas river in Indonesia is of concern to several agencies on East Java. These agencies all measure its water quality in their own way in terms of locations, rhythms and parameters. The goal of this thesis is to find out if these agencies measure the same and if not, how these measurements differ. From these measurements, perspectives are constructed for each agency with the use of Principal Component Analysis. The agencies investigated are the Dinas Lingkungan Hidup Jawa Timur (DLH Jatim), Belai Besar Wilayah Sungai Brantas (BBWS) and Perum Jasa Tirta I (PJT). As an addition to the PCA, a neural network model is constructed and trained to recognize the measurement agency of a datapoint from the measurement values. It was found that the all three agencies recognized oxygen as a dominant driver in water quality processes. Secondary processes were mostly driven by rainfall, but the effect of this was seen differently by the agencies. DLH Jatim distinguishes surface waste runoff separately from rainfall, while Perum Jasa Tirta I will see them as inherently connected. BBWS will not recognize the surface waste runoff process as a significant factor in the water quality. These differences found in the representation of core processes in the Brantas outline how different agencies can have a different perspective on water quality. This was further underlined by the conclusions from the neural network analysis. Here it was found that the author could be recognized from the measurement values alone on 88% of agency data.

In Ethiopia, rainfall variability and changes in rainfall patterns, induced by climate change, could increase the frequency and occurrence of floods and droughts. Due to smallholder farmers in the Gumera sub-basin, Ethiopia, mostly relying on rainfed agriculture, climatic changes highly influence the agricultural production with corresponding negative effects on food security and their economic well-being. To reduce their vulnerability to climate variability, the majority of smallholder farmers take up adaptation strategies, whereas a small group of farmers does not have the capacity to adapt. However, the understanding of what factors drive the climate adaptive capacity of farmers and how climate adaptive behaviour influences a farmer’s economic well-being is limited. Therefore, via a bottom-up approach, this study aims to determine what factors drive the climate adaptive capacity of smallholder farmers in the Gumera sub-basin and how they adapt to climate variability. Focus Group Discussions are conducted prior to an individual household survey to obtain local-level knowledge and data on the characteristics of smallholder farmers. Subsequently, this data is used to develop a methodology to incorporate the climate adaptive behaviour of smallholder farmers in socio-hydrological modelling. By implementing a logit model, the (dynamic) adaptive capacity of smallholder farmers is implemented, which provides the opportunity to create a better understanding of why farmers adapt to climate variability and its impact on their economic well-being. From the Focus Group Discussions and the individual household survey it is observed that the majority of farmers adapt to climate variability in case of a bad year, defined as a drought, by changing to a short cycle crop, mostly potato, and adjusting the planting and harvesting dates. The drivers that are found to mainly influence the uptake of these adaptation strategies are farm size, altitude, level of education, the number of livestock owned, capital, experience, access to a weather forecast, and labour availability. A small group of farmers does not take up adaptation strategies instead. First of all, their adaptive capacity is constrained by a lack of land, labour, and a weather forecast. Secondly, the rather optimistic perception of non-adapting farmers towards climate change seems to limit their adaptive capacity. Thirdly, especially the limited use of the onset of rains by non-adapting farmers was observed to negatively influence their climate adaptive capacity. Incorporating the climate adaptive behaviour of smallholder farmers in socio-hydrological modelling by enabling a logit model showed to be a successful approach. Based on the main drivers for the climate adaptive capacity, the model is able to simulate the agricultural practices with respect to climate variability. As such, the model has shown to be able to simulate agricultural practices that better coincide with what is observed during both the Focus Group Discussions and the household survey. In addition, the methodology used to evaluate the long-term effect of climate adaptation on the economic well-being of a farmer has the potential to help in creating a better understanding of why farmers adapt to climate variability.

Water, energy and food resources are fundamental for human survival and are critical for supporting economic development. However, ensuring adequate supply is a major concern for the entire world, specifically in some countries and regions. Under the pressure of population growth, economic development, international trade, urbanization, diversifying diets, cultural and technological changes, global projections indicate a significant further increase in demand for water, energy and food over the next decades. Moreover, the development of these water, energy and food resources are intertwined. As a result, when demand grows, but resources are no longer abundant, competition between sectors increases. Especially in regions with upstream-downstream water connectivity, a national sectoral approach may result in friction, a decrease in mutual trust and international conflicts. On the other hand, the synergistic effects associated with regional resource coordination can contribute to improved resource availability and downstream livelihoods.

To overcome the shortcomings of the current generation of hydro-economic and WEF-nexus models in describing resource cooperation at regional level, in this study a new WEF-framework has been developed in which the heterogeneity in agro-climatic, socio-economic and resource availability, as well as the description of water and electric conveyance infrastructure is included spatially and temporally explicitly. The aim of this research is to create an integrated WEF-framework and to investigate the possibilities for, the relevance of and the challenges and difficulties associated with the implementation of such an integrated model.

The proposed framework includes the river conveyance infrastructure in a multi state river basin by means of a dynamic network model. In addition, a novel approach is used to describe both irrigated and rainfed agriculture in great detail on a regional scale, enabling a good representation of crops with multiple growing cycles per season, a distinction between annual and perennial crop management and the inclusion of agricultural losses. The framework is implemented as a model predictive control (MPC) problem. In this control problem, the reservoir operations and agricultural planning resulting in maximum economic value creation with the available resources are determined with the help of a non-linear problem solver. Receding horizon control accomplishes as part of the MPC framework feedback against uncertain disturbances (e.g. deviations in climate forcing) by applying only the optimal outputs in the first instance of the horizon in simulation and then updating the system states using new information. In addition, this control technique enables information exchange between riparian states within each MPC iteration. This allows us to add two new cooperation scenarios between the often studied scenarios of unilateralism and full coordination, with which the value of information exchange of river flows and trade flows can be studied.

Once developed, the framework is applied in the Eastern Nile basin. The Eastern Nile Basin is home to a large and rapidly growing population. Along with future population growth, changes in socio-economic conditions are expected, which will improve the coverage of the electricity grid and alter diets and water consumption. To meet the growing demand for food and energy, the Nile riparian countries have developed, and intend to further develop, their water resources. However, currently this development takes place unilaterally and can thereby threaten the livelihood in the downstream countries that are highly dependent on these water resources. The application of the proposed model framework aims to describe the qualitative and quantitative benefits and impacts of further collaboration in resource management within a predefined structural environment.

Simulation experiments with a monthly time step are conducted over a historical period between 1990-2010 and a future period between 2020-2040, by screening and incorporation of data on structural, socio-economic and climate constraints and demands. In addition to the four named cooperation scenarios, experiments are compiled to determine trade-offs between hydropower and agricultural water demand, the robustness of the solutions to imperfect climate foresights and the economic trade-offs related to different levels of agricultural self-sufficiency.

Comparative research with trade data from the FAO database indicates that historically every riparian state in the Eastern Nile basin could have benefited from the proposed integrated resource management, even in the unilateral national cases. Despite the variability in extent, all proposed and included forms of cooperation would have been beneficial for all individual states. Regionally, the flow-information, trade-information and regional coordination scenarios could have provided additional benefits of $32, $37 and $50 billion respectively throughout the period. Sharing information about the expected border flows would have generated, relatively in Sudan and absolutely in Egypt, by far the largest additional benefits. However, these benefits appear to correlate strongly with perfect climate foresight information. Because of its upstream location, Ethiopia could not have benefited economically from this flow information sharing. Overall, the benefits of resource optimization would have been relatively small in Ethiopia due to the limited infrastructure present during this period. In addition to the quantitative benefits mentioned, regional coordination also would have enabled the states to increase their resilience against long-lasting droughts and price fluctuations in the external market.

Results of the future model experiments suggest that every state will be disadvantaged in a regional coordinative scenario. To correct these physically and mathematically incorrect results, the current soft constrained implementation of the non-smooth complementarity relations for the reservoir filling process will have to be reconsidered. These non-smooth functions are the first out of three major difficulties encountered when implementing the proposed framework. Other difficulties arise when describing processes on different time scales (e.g. annual crop seasons) and when keeping the problem robust (in case predictions deviate from real events).

Overall, the case study illustrates that the proposed framework can account for spatial and temporal multisectoral trade-offs while finding non-trivial solutions for varying forms of national and regional cooperative resource management. Moreover, the operational resource reallocation choices proposed by this new framework and the spatial diversity in productivity that were discovered indicate that inadequate inclusion of these heterogeneities in WEF-nexus studies results in incomplete and potentially incorrect conclusions

Chennai, one of the largest cities in India, has been suffering from ‘’too little, too much and too polluted’’ water. As a response, in 2002, the local government took a step forward at the policy level by mandating the provision of rainwater water harvesting structure for every building. This system contributes to take advantage of the excess water during monsoon and palliating the situation during the dry season, while preventing it from being discharged into the polluted waterways. However, the widespread uptake of rooftop rainwater harvesting systems has been slow partly due to the lack of accurate and reliable information on the benefits of rooftop rainwater harvesting to make more informed decision. This research seeks to bring forward the potential of leveraging decentralized rooftop rainwater harvesting (RRWH) systems to mitigate Chennai’s water challenges by quantifying the hydrological effect of RRWH using a multi-purpose approach. To do so, a RRWH model was developed using daily continuous simulation method with ‘Yield Before Spill’’ as the operational rule to determine the optimum design capacity required to meet the domestic water demand and to provide its associated hydrological benefits on water supply, groundwater recharge and urban flooding. In this research, a closed system of RRWH designed to maximize water supply is applied for the analysis. Two areas of Chennai were investigated : urban area and peri-urban area. The Mambalam area, located in the historical center of Chennai, was selected as the urban area case study. Assuming 380,000 inhabitants are living in an estimated area of 11,690,000m2, approx. four million cubic meters of water can be harvested annually from the existing building’s roofs. From this, 50% of the buildings in the Mambalam is assumed to be residential which can provide 51d/yr/p of the domestic water demand. Thus, other sources of water supply are required to supplement the water demand. Maximizing water supply reduces groundwater recharge to nearly 0m3/yr in the Mambalam area. There is clearly a trade-off between water supply and groundwater recharge. However, when considering the adoption of RRWH for groundwater recharge (also refer as open system of RRWH) for the remaining 50% of the non-residential buildings in the Mambalam, approx. two million m3/aof rainwater can be recharged into the aquifer, balancing out the urban water system. This volume of recharged groundwater can also be considered as available groundwater for water supply because in urban area, groundwater is also used for domestic water supply. Together, the potential of decentralized water supply is increased up to 30% of the annual water demand (equivalent to 105d/yr/p) . Finally, the combined systems of RRWH for water supply and RRWH for groundwater recharge can contribute to reduce a volume of approx. four million m3/yr going into the stormwater drainage network and the polluted waterways in Chennai. According to the results, RRWH can reduce up to 60% of the stormwater runoff during a heavy rain event in the Mambalam. The results show that scaling up RRWH at the macro-scale level can have a significant impact in terms of drought and flood resilience for the Mambalam area. These numbers can serve as inputs for stakeholders’ dialogues to make informed decisions and raise awareness on the benefits of multi-purpose RRWH to transition Chennai toward a water resilient city. In practice, retrofitting existing building with RRWH for water supply in urban areas may become challenging mainly due to political, legal, physical and socio-economic factors. The adoption of a close system for RRWH is found to be more relevant for the periurban areas of Chennai. Indeed, buildings are developed on top of marshland with a high-water table level and saline water. This is the case of many residential apartment complexes located along the IT Corridor in the southern part of Chennai. Groundwater recharge and groundwater abstraction for water supply are not possible. As a
consequence, people need to rely solely on water tankers which is around 20 times more expensive than the cost of water per kiloliters in urban areas. The case of Sabari Terrace residential apartment complex showed that the adoption of RRWH for water supply contributes to 15% of the annual water demand and it saves up to $6/yr/p.

Urban sanitation in developing countries requires systems thinking as there is a plethora different variables which can impact the delivery of adequate sanitation for the people. In the traditional sense, sanitation planning in urban cities focuses on keeping people away from human-waste related pathogens. As cities in India and several developing countries are growing at exponential rates, government agencies are struggling to provide adequate safe sanitation in their cities. In recent years, due to a range of factors such as increasing water stress, recreational needs and biodiversity protection in an urban fabric, urban waterbodies are deemed worthy of conservation. The objective of this research was to systematically understand urban sanitation and how it relates to urban waterbody health. Having understood the system adequately, the aim of the thesis was to answer the research question, can “Citywide Inclusive Sanitation as a planning approach aid in the betterment of urban waterbodies?”. The study adopted a mixed method which comprises of quantitative water quality testing in Kommaghatta lake in Bengaluru city, India and a qualitative analysis at the Bengaluru city level. It included elements of qualitative social research methods such as field observations, informal conversations and semi-structured interviews to answer the research questions. Water quality results and qualitative analysis suggests that there are three significant pollution pathways into Bengaluru lakes, each carrying different wastewater characteristics and pollution load. The predominant pathway for the pollution of waterbodies in the city is through the stormwater drainage. Additionally, sewer pipes and desludging trucks which dispose faecal waste from on-site sanitation systems also contribute to pollutant load entering into the lakes in the city. From the semi-structured interviews, a conceptual model of urban sanitation in Bengaluru city and how it relates to waterbodies was developed. From conducting a qualitative analysis, six major system levers were identified. They levers influence the dynamics of urban sanitation in Bengaluru and forms the basis for the pollution pathways that enter into the lake. They six major system levers for Bengaluru urban sanitation are:
1.Rapid urbanization
2.Fragmentation of government entities
3.Sewer infrastructure
4.Feacal sludge management
5.Treated water reuse
6.Citizen group involvement The study shows that CWIS principles have a significant relevance for solving urban sanitation issues which were identified through the system levers. In addition to solving urban sanitation issues which centres on public health matters, the study also shows that there is also an environmental case for CWIS by arresting waterbody pollution through the identified pollution pathways. Findings from this research can help to improve decision making in terms of urban sanitation by paying close attention to the cause-effect relationships between variables in the urban sanitation sphere and improve waterbody health in their cities.

Anaerobic wastewater treatment is a preferred attractive treatment mainly because of its simplicity and compactness as it produces lesser sludge compared to the aerobic system. Despite this, it has its own disadvantages as it takes more time for bacterial growth and treatment and also contributes to nutrients such as N and P to the effluent. Anaerobic digestion can be divided into four categories namely hydrolysis, acetogenesis, acidogenesis and methanogenesis. Hydrolysis is generally the rate limiting step of an anaerobic digestion. Studies show that hydrolysis is faster in aerobic process than in anaerobic process. Hence, hydrolysis may be fastened by supplying air. But oxygen inhibits the growth of strong anaerobes in the later stages of anaerobic digestion mainly affecting methanogenesis. This study focusses on studying the removal of organics by using 0.05vvm air into the filtration part of an 8-litre side-stream AnMBR with a fly ash membrane filter module. The result thus obtained is compared with a 100-litre AnMBR of similar construction without any air. The study observed a higher removal of COD in the aerated system than the non-aerated system.

The United Nations 2030 Agenda for Sustainable Development defines the mutual values of the international community. These values are captured in the goals as agreed upon by its Member States. Each of the goals has a set of defined targets whose progress can be measured through a change in the associated data indicator. This way, the pursuit of the Agenda becomes an organized, globalized effort that can be tracked, measured and evaluated. While the achievement of many of these goals and targets are inherent in pursuing good politics, as, for example, there are few heads of state that will strive for economic decline (opposite of SDG 8), progress on the overall Agenda can in many other ways become complex. An example of this is when there exists potentially a conflict or synergy between targets of a goal - where improving on one target comes at the cost or benefit of another. This report aims to analyse the possible relationships between the SDG 6 targets. This is done through the comparison and juxtaposition of different data sets that are then evaluated with each other statistically. Given the considerable amount of data constraints, only few possible intralinkages could be identified. No negative trends were discovered, while positive trends were found between the access to drinking water (6.1.1) and the following: integrated water resources management (6.5.1), official development assistance for water (6.a.1) and water management participation (6.b.1). Other positive trends were identified with the not-published, national data on integrated water resources management (6.5.1) and: access to drinking water (6.1.1), access to sanitation (6.2.1), and official development assistance for water (6.a.1). These results reveal that Integrated Water Resources Management is an effective tool for achieving SDG 6 of the 2030 Agenda on Sustainable Development.