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All of the possible strategies to reduce water losses in piped distribution systems follow the law of diminishing returns: the higher the expenditure on water loss reduction, the lower the progressive return in terms of water saved. Therefore, water utilities need to estimate the economic level of water losses (ELWL) so that they can reduce their water loss to the level where the cost to reduce the water losses is equal to the value of the water saved. This paper aims to estimate the ELWL using four different methods: the total cost method, the marginal cost method, the cumulative cost–benefit method, and the component-based methods. This analysis is based on data (2011–2016) on the water utilities of the city of Malang (PDAM Kota Malang), Indonesia. It was found that the total cost and marginal cost methods gave almost similar results for ELWL. However, the total cost method is preferred to calculate ELWL because it is the most accurate, easier to apply, and does not need a long data series. In addition, the estimated ELWL for PDAM Kota Malang was 21.76%, which is 3.71% higher than the water loss level estimated in 2016, which means that their strategies to reduce water loss are not cost-efficient. Moreover, the lack of data is a major challenge in the estimation of ELWL in Indonesia. This study emphasizes the importance of estimating the ELWL so that water utilities, especially in Indonesia, can evaluate their strategies in reducing water loss and improving their cost-effectiveness.

This contribution focuses on surface complexes in the calcite-brine-surfactant system. This is relevant for the recovery of oil when using a new hybrid enhanced oil recovery (EOR) method, which combines smart-water (i.e., ionically modified brine) and foam-flooding (SWAF) of light oil with dissolved carbon dioxide (CO2) at high pressure in carbonate (i.e., calcite) reservoirs. Using this new hybrid EOR-method (i.e., the SWAF-process) is not only economically attractive (i.e., it reduces opex costs) but also enhances the effectiveness of the production process, and thus reduces the environmental impact. Ionically modified brine (i.e., low-salinity) has a dual improvement effect. It not only leads to more stable foam lamellae, but also helps to change the carbonate rock wettability, leading for some conditions to more favorable relative permeability behavior. The mechanism for the modified permeability behavior in the presence of ionically modified brine is only partly understood. Therefore, we study this process initially in a zero dimensional (thermodynamics) setting, which can be used for the one dimensional (1D) displacement process with an oleic phase that contains carbon dioxide (CO2) and an aqueous phase that contains both carbon dioxide (CO2) and all the ionic substances. Using DLVO theory and surface complexation modeling to better understand the mechanism(s) of ionically modified brine as wettability modifier and foam stabilizer. We perform simulations using both (NaCl) and (MgCl2) to show the effect of a divalent ion at the high-salinity (8500 mmol/kg-w) and low-salinity (0.4 mmol/kg-w) for both ambient-conditions at (25°C) and at the reservoir-conditions (80°C). We confine our analysis to a description that uses the Dzombak-Morel model of surface complexes, which is based on the Debye-Hückel theory (i.e., valid up to ionic strength of 0.3 (mol/kilogram of water)). We also investigate the effect of carbon dioxide (CO2) on the stability of low-salinity foam-laminae. We model the foam-laminae, which contain as surface complex a (cationic) surfactant in an aqueous phase. We use the PHREEQC-software to calculate the surface charge and the surface potential. The presence of a carbon dioxide (CO2) phase leads to dissolution of four valent C(IV) compounds in the aqueous film. PHREEQC also calculates the equilibrium concentrations and surface potential and allows the study of the effect of salinity and the carbon dioxide (CO2) gas pressure. For the soap-film (foam-film) in a carbon dioxide (CO2) atmosphere we do use Pitzer activity coefficients (i.e., valid up to 6 (mol/kilogram of water)). As our aim is to show the methodology and the versatility of this approach, we leave more realistic choices of these parameters for future work.sFor the conditions considered we can qualitatively state that, in the presence of (NaCl i.e., at pH > 10) and (MgCl2 i.e., pH > 10.3), the low-salinity case shows a more stable water-film behavior at (25°C) and at (80°C) than the high-salinity case for both (25°C) and (80°C). Moreover, high carbon dioxide (CO2) pressures have a destabilizing effect on the film, as they reduce the surface potential. A reduced surface potential leads to a decreasing electrostatic double layer repulsion and thus destabilizes the foam-film, whereas low-salinity leads to less screening of the surface potential and thus improves the stability of the foam-film. The low-salinity flow is characterized by a high residual oil saturation and low end-point permeability for the two phase oil-water flow. This leads to a more favorable mobility ratio and thus a more favorable displacement process. For the calcite surface an enhanced stability helps to stabilize the water film on the calcite surface if the oil-water surface charge has the same sign as the surface charge on the calcite surface. Our calculations show the pH range where the sign of these charges is the same or opposite at low-salinity and high-salinity conditions. Admittedly these calculations only show trends, but can be used to delineate optimal conditions for the application of “Smart Water Assisted Foam (SWAF) Flooding”. It is expected that the SWAF-process under the optimum conditions will make the proposed new hybrid Enhanced Oil Recovery (EOR) process environmentally and economically attractive.

The supercritical water gasification process is an alternative to both conventional gasification as well as anaerobic digestion as it does not require drying and the process takes place at much shorter residence times; a few minutes at most. The drastic changes in the thermo-physical properties of water from the liquid state to the supercritical state make it a promising technology for the efficient conversion of wet biomass into a product gas that after upgrading can be used as substitute natural gas. The earliest research goes back as far as the 1970s and since then, supercritical water has been the subject of many research works in the field of thermochemical conversion of wet biomass. This article reviews the state of the art of the supercritical water gasification technology starting from the thermophysical properties of water and the chemistry of reactions to the process challenges of such a biomass based supercritical water gasification process plant.

This paper evaluates the impact of reduction of doublet well spacing, below the current West Netherlands Basin standard of 1000 to 1500 m, on the Net Present Value (NPV) and the life time of fluvial Hot Sedimentary Aquifer (HSA) doublets. First, a sensitivity analysis is used to show the possible advantage of such reduction on the NPV. The parameter value ranges are derived from West Netherlands Basin HSA doublet examples. The results indicate that a reduction of well spacing from 1400 to 1000 m could already influence NPV by up to 15%. This effect would be larger in more marginally economic HSA doublets compared to the West Netherlands Basin base case scenario. The possibility to reduce well spacing is supported by finite element production simulations, utilizing detailed facies architecture models. Furthermore, our results underline the necessity of detailed facies architecture models to assess the potential and risks of HSA doublets. This factor significantly affects doublet life time and net energy production of the doublet.

The modelling frameworks, which include greenhouse gas emission scenarios, climate models, downscaling methods and hydrological models, are generally used to assess climate change impacts on river floods. In this research, the uncertainty associated with each component of the modelling framework is analysed with particular reference to climate change impacts on flood frequency. A method of risk-averse economic optimisation has been proposed for adapting river dikes to climate change under uncertainty. The Huai River Basin in China has been selected as a case study. The outputs of climate models, i.e., General Circulation Models (GCMs), under greenhouse gas emission scenarios have been commonly used as fundamental inputs of the climate change impact assessments. The analysis in this thesis employed the climate model projections of the WCRP CMIP3 and CMIP5 datasets. In Chapter 2, a brief introduction of emission scenarios, as well as a preliminary analysis of the simulative ability and future projections of the participating climate models, is provided. The results confirm the necessity to bias-correct and downscale the climate model outputs before being used in impact-related studies. The annual mean temperature in the study area is suggested to increase up to 8oC at the end of this century under a high greenhouse gas emission scenario without mitigation measures. The standard deviation of precipitation intensity is suggested to increase, especially in summer, which may in the future lead to high-magnitude floods. Empirical statistical downscaling methods are becoming increasingly popular in climate change impact assessments that require downscaling multi-GCM projections. In Chapter 3 empirical statistical downscaling methods are classified based on calibration strategies and statistical transformations. Ten combinations of calibration strategies and transformation methods were used to represent a range of empirical statistical downscaling methods. To test the performance of these methods in downscaling daily precipitation and temperature, an inter-model cross validation was carried out using an ensemble of 16 GCMs. These downscaling methods were further applied to downscale the climate for the future period to assess the associated uncertainties. The results show that the change factor based methods outperform the bias correction based methods in projecting the probability distribution of downscaled daily temperature. With the change factor calibration strategy, simply adding (for temperature) or multiplying (for precipitation) the mean change factor is sufficient to represent most of the relative changes projected by GCMs. The use of quantile based methods appear to be advantageous only at the tails of the distribution. More sophisticated bias correction based methods are needed to remove the biases in the higher-order statistics of the GCM outputs. The two calibration strategies led to fundamentally different temporal structures and spatial variability of the downscaled climatic variables. Bias correction based methods produced larger uncertainty bounds of inter-annual variability than the change factor methods. For downscaled precipitation, the uncertainty arising from the downscaling methods is comparable to the uncertainty arising from GCMs, while more uncertainty is introduced by calibration strategies than statistical transformation methods. There is a growing consensus that the performance of hydrological models should be routinely evaluated before being used in impact-related studies. The uncertainty, which stems from transferring calibrated models to a changing future climate, is receiving increasing attention. Chapter 4 assesses the uncertainties associated with the parameter calibration of the lumped Xinanjiang hydrological model when assessing the climate change impacts on river flow. The transferability of model parameters was tested in the context of historical climate variability using the differential split-sample test. The parameters calibrated from the periods representing differing climatic conditions were used to project future river flow in a changing climate. The uncertainties in projected future river flows stemming from the choice of calibration periods and parameter equifinality were compared. The results show that the transferability of the parameters calibrated from a wet period to a dry period is poorer than the other way around. The model error as well as the variability in the simulations due to equifinality increase with the increase of the difference in rainfall between the calibration and validation periods. The uncertainty due to the choice of calibration periods takes the majority of the total parameter uncertainty in the projected future mean discharge. When the calibration period contains enough information on climate variability, the equifinality effect and the choice of calibration periods contribute comparable magnitudes of uncertainty in terms of extreme discharge. Five sources of uncertainty mentioned above were compared in Chapter 5, i.e. GCM structure, greenhouse gas emission scenario, downscaling method, choice of period for calibrating the hydrological model, and non-uniqueness of hydrological parameters. Multiple samples of flood frequency curves were generated through the combinations of different emission scenarios, GCMs, downscaling methods and hydrological model settings. All samples were given equal weights in the analysis. The results show that the future flood magnitude is expected to increase, not only due to the increase in mean precipitation, but also due to the increase in variation of precipitation. Nonetheless, there is still a small likelihood that the flood quantiles with a high return period (above 20 years) will decrease in the future. The results of uncertainty comparison suggest that the GCM structure is the dominant source of uncertainty, emission scenarios and empirical statistical downscaling methods also result in considerable uncertainty, and the uncertainties related to hydrological model are less than those related to other uncertainty sources. To guarantee a safe flood defence in a changing environment, the adaptation to climate change needs to be considered in the design of river dikes. However, the large uncertainty in the projections of the future climate leads to varied estimations of future flood probability. How to cope with the uncertainties in future flood probability under climate change is an inevitable question in adaptation decision-makings. In Chapter 6, the uncertainty introduced by climate projections was integrated into the ‘expected predictive flood probability’, and the risk-aversion attitude was introduced in the adaptation of river dikes. The uncertainty in the climate change projections on flood probability was represented by the uncertainty in the parameters of the probabilistic model. This parameter uncertainty was estimated based on the outputs from the GCMs participating in IPCC AR4. The parameter uncertainty, estimated from the selected GCMs under different scenarios, was integrated into the expected predictive probability of flooding, which was then used in the risk-averse economic optimization. Different optimal results were obtained based on varied values of the risk-aversion index which represents the risk-averse altitude of decision makers. The case of a dike ring area in the Bengbu City in the Huai River Basin is studied as an example using the proposed approach. The results show that the uncertainty of climate change decreases the optimal safety level and increases the optimal dike heightening up to 8.23 m (with the risk-aversion index of 1.5) in a gradually changing climate. The value would be even larger if the climate will change sooner. Integrated adaptive measures rather than only dike heightening are needed to respond to the uncertain impacts in the future. The proposed approach enables decision makers to cope with climate change and the associated uncertainty by adjusting the level of risk aversion.

The 2014 hukou reform introduced by the Chinese central government was a turning point in China’s policies towards migration. Different from the previous hukou policies, which were largely exclusionary, the reformed policy encouraged migrants to permanently settle in their destination cities and make use of the public services available there. However, the actual results and consequences of this policy seem to vary between cities. This is due to the fact that Chinese municipal governments still have their own discretionary power when it comes to defining the criteria for accessing a local hukou. This raises the question of what the real impact of the hukou policy reform has been. This paper attempts to answer this question. It starts with a hukou access policy analysis of 20 different cities in the Yangtze River delta urban region. This analysis shows that the strictness of the local hukou access policy is related to city specific factors such as economic strength, share of migrant population, and population size. In the second part of the paper, we examine the impact of local hukou access policies on the intentions of migrants. Based on two logistic regression models, we find that the stricter the local hukou access policy is, the more willing migrants are to convert their current hukou into a local hukou. Furthermore, we observed that the settlement intention of migrants has a V-shaped rather than a linear relation with the strictness of local hukou access policies. Cities with relatively loose and cities with relatively strict hukou access policies are more desired as permanent settlement location than cities with moderately strict hukou access policies.

Supplying high-quality water at competitive cost is a major challenge for water utilities worldwide, especially with ever increasing water quality standards and energy prices. A number of pump scheduling methods for optimizing simultaneously water quality and energy cost have been developed already. However, none of these methods is ideal because of the complexity of water networks and the nonlinear behavior of water flow. In this research, a new optimization method named iterative extended lexicographic goal programming (iELGP) is developed to optimize energy cost and water quality (residual chlorine) in water networks with a mixture of fixed speed pumps (FSPs) and variable speed pumps (VSPs). Two different approaches were used to indirectly improve chlorine. The new method was tested on the C-Town water network and compared with the graph theory method from the literature. The results obtained show the ability of the iELGP method to optimize energy cost and water quality in water networks in a computationally very efficient manner. They also show that the iELGP method can identify lower energy cost pump schedules and do this faster than the comparison method. Using VSPs instead of FSPs improves the water quality and decreases the related energy and maintenance cost in water networks.