Climate and human development impacts on municipal water demand: A spatially-explicit global modeling framework

Municipal water systems provide crucial services for human well-being, and will undergo a major transformation this century following global technological, socioeconomic and environmental changes. Future demand scenarios integrating these drivers over multi-decadal planning horizons are needed to develop effective adaptation strategies. This paper presents a new long-term scenario modeling framework that projects future daily municipal water demand at a 1/8° global spatial resolution. The methodology incorporates improved representations of important demand drivers such as urbanization and climate change. The framework is applied across multiple future socioeconomic and climate scenarios to explore municipal water demand uncertainties over the 21st century. The scenario analysis reveals that achieving a low-carbon development pathway can potentially reduce global municipal water demands in 2060 by 2–4%, although the timing and scale of impacts vary significantly with geographic location.     

Integrated assessment model of society-biosphere-climate-economy-energy system

The feedback based integrated assessment model ANEMI_2 represents the society-biosphere-climate-economy-energy system of the earth and biosphere. The ANEMI_2 model is based on the system dynamics simulation approach that (a) allows for the understanding and modeling of complex global change and (b) assists in the investigation of possible policy options for mitigating, and/or adapting to changing global conditions within an integrated assessment modeling framework. This paper outlines the ANEMI_2 model and its nine system components: climate, carbon cycle, land-use, population, food production, hydrologic cycle, water demand, water quality, and energy-economy. To evaluate market and nonmarket costs and benefits of climate change, the ANEMI_2 model integrates an economic optimization approach, with a focus on the international energy stock and fuel price, climate interrelations and temperature change. The model takes into account all major greenhouse gases (GHG) influencing global temperature and sea-level variation. Results from several scenarios (a) compare well with other information available in the scientific literature, (b) present comprehensive response of the society-biosphere-climate-economy-energy system to the selected scenarios, and (c) confirm the support role of the ANEMI_2 model in the policy development and analyses.     

Application of genetic programming to project climate change impacts on the population of Formosan Landlocked Salmon

This work presents a novel methodology, genetic programming (GP), for developing environmental response functions for Formosan Landlocked Salmon (Oncorhynchus masou formosanus); these functions are then applied to evaluate the impacts of climate changes. Average daily temperature and maximal flows between two sampling periods were adopted as principal factors for categorizing environmental conditions. The GP successfully identified the response functions for various environmental categories. The response functions were further applied to assess the impact of climate change. Fourteen future possible climate scenarios were derived based on the equilibrium and transition experiments by GCMs. Impact assessment results indicated that climate change may significantly influence populations of Formosan Landlocked Salmon due to more frequent higher temperatures. Adaptation strategies are required to mitigate the impact of global climate change as current conservation measures for Formosan Landlocked Salmon habitat only reduce local human-induced effects. In the situation of complicated relationships between fish population and environmental conditions, GP provides a useful tool to obtain some information from the limited data.     

Application of a global model to the study of Arctic basin pollution: radionuclides,heavy metals and oil hydrocarbons

The status of pollution of the Arctic basin is studied in ecological terms, and the interactions of the Arctic ecosystem with the global system are estimated. A spatial simulation model for the kinetics of pollutants in the Arctic basin is proposed in which the ecological and spatial distribution of the hydrological parameters is taken into account. The model includes blocks describing the flows of pollutants in the trophic chains, the exchange between the water–ice system and the atmosphere and the interaction of the water ecosystem with the global biosphere–climate system. A global model controls the inputs of the simulation model and makes it possible to compute the dynamics of the distribution of pollutants between the Arctic aquatories, which include the Central basin and the peripheral seas. The model uses both published data and the data of the US/Russian expedition to Siberia accomplished in the summer of 1995. Climatic and anthropogenic processes are described in the form of scenarios. The results of computer experiments are given demonstrating the advantages of the simulation model to forecast and to estimate the dynamics of radionuclides, heavy metals and oil hydrocarbons in the Arctic Seas. The total and local pictures of the spatial distribution of pollutants in the Arctic basin are given as functions of various environmental and anthropogenic parameters. It is concluded that the use of the global biospheric model enables the consideration of the interactions between the Arctic basin environment and adjoining territories. This allows estimates to be made of the consequences of the anthropogenic impact on the Arctic ecosystem.     

Review article: Priorities of global change and the development of remote sensing in Japan

A survey has been made of basic environmental problems and priorities of global change in the context of the biotic regulation of the environment. The recent history of the development of satellite remote sensing has been considered and illustrated by some results in the fields of meteorology and oceanography. Emphasis has been made on the launch of ADEOS (Midori) satellite which took place on 17 August 1996. The scientific programme and instrumentation developed for the Advanced Earth Observing Satellite-II (ADEOS-II), to be launched in 1999, have been discussed in the context of previous efforts and future research in the fields of global change, with relevance to problems such as global climate change (with special emphasis on the global energy and water cycles), the global carbon cycle (respectively, marine and terrestrial biosphere dynamics), high altitude environmental dynamics, natural calamities (earthquakes, tsunami, volcanic eruptions etc.) and other environmental problems.     

Modelling the long term water yield impact of wildfire and other forest disturbance in Eucalypt forests

Disturbance of forested catchments by fire, logging, or other natural or human induced events that alter the evapotranspiration regime may be a substantial threat to domestic, environmental and industrial water supplies. This paper describes the physically-based modelling of the long term changes in water yield from two wildfire affected catchments in north-eastern Victoria, Australia, and of fire and climate change scenarios in Melbourne's principal water supply catchment. The effect of scale, data availability and quality, and of forest species parameterisation are explored. The modelling demonstrates the importance of precipitation inputs, with Nash and Sutcliffe Coefficients of Efficiency of predicted versus observed monthly flows increasing from 0.5 to 0.8 with a higher density of rainfall stations, and where forest types are well parameterised. Total predicted flow volumes for the calibrations were within 1% of the observed for the Mitta Mitta River catchment and <4% for the Thomson River, but almost ?10% for the less well parameterised Tambo River. Despite the issues of data availability simulations demonstrated the potential for significant impacts to water supply in SE Australia from wildfire and climate change. For example, for the catchments modelled the moderate climate change impact on water yield was more pronounced than the worst fire scenario. Both modelled cases resulted in long term water yield declines exceeding 20%, with the climate change impact nearing 30%. A simulation using observed data for the first four post-fire years at the Mitta Mitta River catchment showed Macaque was able to accurately predict total flow.     

Implications of complexity and uncertainty for integrated modelling and impact assessment in river basins

The paper focuses on implications of complexity and uncertainty in climate change impact assessment at the river basin and regional scales. The study was performed using the process-based ecohydrological spatially semi distributed model SWIM (Soil and Water Integrated Model). The model integrates hydrological processes, vegetation/crop growth, erosion and nutrient dynamics in river basins. It was developed from the SWAT and MATSALU models for climate and land use change impact assessment. The study area is the German part of the Elbe River basin (about 100,000 km²). It is representative for semi-humid landscapes in Europe, where water availability during the summer season is the limiting factor for plant growth and crop yield. The validation method followed the multi-scale, multi-site and multi-criteria approach and enabled to reproduce (a) water discharge and nutrient load at the river outlet along with (b) local ecohydrological processes like water table dynamics in subbasins, nutrient fluxes and vegetation growth dynamics at multiple scales and sites. The uncertainty of climate impacts was evaluated using comprehensive Monte Carlo simulation experiments.     

Cellular automata approach for modelling climate change impact on water resources

ABSTRACT

In this work, we consider the cellular automata (CA) approach for modelling the climate change impact on water resources. This consists in: constructing a CA model that describes the water cycle dynamics taking into account physical terrain attributes and climatic constraints; coupling the CA model with climate projection scenarios for a considered region as input data; determining and analysing in output the variations of the underground, surface and evaporated water. We present these variations per time interval and per zone of influence. As an application, we consider simulation for a basin in northern Morocco using a simulation software we have designed in Java Object Oriented Programming.

We consider cellular automata (CA) approach for modelling climate change impact on water resources. This consists in, first constructing a CA model that describes the water cycle dynamics taking into account physical terrain attributes and climatic constraints, then coupling the CA model with climate projection scenarios for a considered region as input data, and we determine and analyze in output the variations of the water resources (groundwater and surface water). We present these variations per time interval and per zone of influence. The approach application is for a basin in northern Morocco for which we use simulation software that we have designed in Java Object Oriented Programming. Digital terrain model, geological map and satellites image are used for input data.     

Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change

Urban bulk water systems supply water with high reliability and, in the event of extreme drought, must avoid catastrophic economic and social collapse. In view of the deep uncertainty about future climate change, it is vital that robust solutions be found that secure urban bulk water systems against extreme drought. To tackle this challenge an approach was developed integrating: 1) a stochastic model of multi-site streamflow conditioned on future climate change scenarios; 2) Monte Carlo simulation of the urban bulk water system incorporated into a robust optimization framework and solved using a multi-objective evolutionary algorithm; and 3) a comprehensive decision space including operating rules, investment in new sources and source substitution and a drought contingency plan with multiple actions with increasingly severe economic and social impact. A case study demonstrated the feasibility of this approach for a complex urban bulk water supply system. The primary objective was to minimize the expected present worth cost arising from infrastructure investment, system operation and the social cost of “normal” and emergency restrictions. By introducing a second objective which minimizes either the difference in present worth cost between the driest and wettest future climate change scenarios or the present worth cost for driest climate scenario, the trade-off between efficiency and robustness was identified. The results show that a significant change in investment and operating strategy can occur when the decision maker expresses a stronger preference for robustness and that this depends on the adopted robustness measure. Moreover, solutions are not only impacted by the degree of uncertainty about future climate change but also by the stress imposed on the system and the range of available options.     

A web-based screening model for climate risk to water supply systems in the northeastern United States

The aim of this study is to describe the development and application of a web-based decision support tool (ViRTUE) for performing climate risk evaluations of water supply systems. The tool is designed for small-scale water utilities in the northeastern United States that may lack the resources for detailed climate change risk investigations. Development of this tool demonstrates a relatively new approach to web application development using the Shiny framework for the R programming language to create an interactive environment for stakeholders and water managers to explore climate vulnerabilities. Using a decision-scaling framework, the tool allows the user to perform a climate stress test to evaluate the performance and vulnerability to water supply shortfalls of local reservoir systems over a wide range of potential climate change scenarios using a generic systems model. Probabilities of future climate conditions derived from climate projections then help inform utility operators of impending risk.     

Analysing the forcing mechanisms for net primary productivity changes in the Heihe River Basin,north‐west China

Most of the inland river basins in north‐west China have experienced ecosystem degradation and even desertification in the last few decades. As a case study, we estimated the net primary productivity (NPP) of the Heihe river basin and analysed its difference between 2002 and 1998 by using the C‐Fix, a Monteith type parametric NPP model. The data used include the normalized difference vegetation index (NDVI) derived from the 1‐km SPOT/VEGETATION sensor and other environmental records. By obtaining the spatiotemporal patterns of NPP change as well as land use changes from higher resolution imagery in the basin, we identified its forcing factors in terms of climate change and human activities. We suggest that a decline in rainfall over the five years was one reason for NPP decrease in the basin. Other factors, such as irrational reclamation upstream and intensive development of irrigated farmland in the midstream play more important roles. They reinforce water competition between artificial and natural ecosystems over the whole basin. It is also found that human activities can produce very different NPP changes in a short time in mountainous regions. The NPP decreased in the east Qilian Mountains due to farmland reclamation and overgrazing but increased in the west, according to the ecosystem preserve project.     

Spatially-explicit water balance implications of carbon capture and sequestration

Implementation of carbon capture and sequestration (CCS) will increase water demand due to the cooling water requirements of CO₂ capture equipment. If the captured CO₂ is injected into saline aquifers for sequestration, brine may be extracted to manage the aquifer pressure, and can be desalinated to provide additional freshwater supply. We conduct a geospatial analysis to determine how CCS may affect local water supply and demand across the contiguous United States. We calculate baseline indices for each county in the year 2005, and project future water supply and demand with and without CCS through 2030. We conduct sensitivity analyses to identify the system parameters that most significantly affect water balance. Water supply changes due to inter-annual variability and projected climate change are overwhelmingly the most significant sources of variation. CCS can have strong local effects on water supply and demand, but overall it has a modest effect on water balances.     

Integrated assessment of sea-level rise adaptation strategies using a Bayesian decision network approach

The exposure to sea-level rise (SLR) risks emerges as a challenging issue in the broader debate about the possible consequences of global environmental change for at least four reasons: the potentially serious impacts, the very high uncertainty regarding future projections of SLR and their effects on the environmental and socio-economic system, the multiple scales involved, and the need to take effective management decisions in terms of climate change adaptation. Unfortunately, mechanistic models generally demonstrated a limited ability to characterise in appropriate detail how complex coastal systems and their constituent parts may respond to climate change drivers and to possible adaptation initiatives. The research reported here develops an innovative methodological framework, which integrates different research areas – participatory and probabilistic modelling, and decision analysis – within a coordinated process aimed at decision support. The effectiveness of alternative adaptation measures in a lagoon in north-east Italy is assessed by means of Bayesian Decision Network (BDN) models, developed upon judgments elicited from selected experts. A concept map of the system was first developed in a group brainstorming context and was later evolved into BDN models, thus providing a simplified quantitative structure. Conditional probabilities, quantifying the causal links between the direct and indirect consequences of SLR on the area of study, are elicited from the experts. The proposed methodological framework allows the integrated assessment of factors and processes belonging to different domains of knowledge. Moreover, it activates an informed and transparent participatory process involving disciplinary experts and policy makers, where the main risk factors are considered together with the expected effects of the adaptation options, with effective treatment and communication of the uncertainty pervading the SLR issue. Finally, the framework shows potentials for being further developed and applied to consider new evidences and/or different adaptation strategies, and it results sufficiently flexible to be adopted and effectively reused in other similar case studies.     

Historical and future land-cover changes in the Upper Ganges basin of India

The green revolution represents one of the greatest environmental changes in India over the last century. The Upper Ganges (UG) basin is experiencing rapid rates of change of land cover and irrigation practices. In this study, we investigated the historical rate of change and created future scenario projections by means of 30 m-resolution multi-temporal Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus data of the UG basin. Post-classification change analysis methods were applied to Landsat images in order to detect and quantify land-cover changes in the UG basin. Subsequently, Markov chain analysis was applied to project future scenarios of land-cover change. Fifteen different scenarios were generated based on historic land-cover change. These scenarios diverged in terms of future projections, highlighting the dynamic nature of the changes. This study has shown that between the years 1984 and 2010 the main land-cover change trends are conversion from shrubs to forest (+4.7%), urbanization (+5.8%), agricultural expansion (+1.3%), and loss of barren land (–9.5%). The land-cover change patterns in the UG basin were mapped and quantified, showing the capability of Landsat data in providing accurate land-cover maps. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support regional land-use planning and develop future-proof water resource management strategies.     

A non-linear optimization model for water treatment planning of a river basin

The primary objective of this study is to develop a long-range planning model for water treatment management of a river basin.

In order to satisfy environmental standards concerning river water pollution, it is fundamentally necessary to construct area-wide sewerages and sewage treatment plants. Hero, an optimal planning problem to construct these public sewage treatment systems is formulated as a non-linear optimization one. In addition the water supply planning problem is taken into consideration by assuming that waste water treated by public tertiary treatment plants can be roused for industrial purposes. The objective function adopted in this model is the total cost of both construction and operation necessary for public sewage treatment systems, and the optimal solution which minimizes this objective function is determined using the generalized reduced gradient (GRG) algorithm.

Through the study of the Yodo river basin in Japan, it is ascertained that various information necessary for planning can be obtained from the model developed in this study.     

Scenario analysis and management options for sustainable river basin management: Application of the Elbe DSS

We developed a decision support system (DSS) for sustainable river basin management in the German Elbe catchment (～100,000 km²), called Elbe-DSS. The system integrates georeferenced simulation models and related data sets with a user friendly interface and includes a library function. Design and content of the DSS have been developed in close cooperation with end users and stakeholders. The user can evaluate effectiveness of management actions like reforestation, improvement of treatment plant technology or the application of buffer strips under the influence of external constraints on climate, demographic and agro-economic changes to meet water management objectives such as water quality standards and discharge control. The paper (i) describes the conceptual design of the Elbe-DSS, (ii) demonstrates the applicability of the integrated catchment model by running three different management options for phosphate discharge reduction (reforestation, erosion control and ecological-farming) under the assumption of regional climate change based on IPCC scenarios, (iii) evaluates the effectiveness of the management options, and (iv) provides some lessons for the DSS-development in similar settings. The georeferenced approach allows the identification of local inputs in sub-catchments and their impact on the overall water quality, which helps the user to prioritize his management actions in terms of spatial distribution and effectiveness.     

Paradigm shift to enhanced water supply planning through augmented grids,scarcity pricing and adaptive factory water: A system dynamics approach

This paper details a system dynamics model developed to simulate proposed changes to water governance through the integration of supply, demand and asset management processes. To effectively accomplish this, interconnected feedback loops in tariff structures, demand levels and financing capacity are included in the model design, representing the first comprehensive life-cycle modelling of potable water systems. A number of scenarios were applied to Australia's populated South-east Queensland region, demonstrating that introducing temporary drought pricing (i.e. progressive water prices set inverse with availability), in conjunction with supply augmentation through rain-independent sources, is capable of efficiently providing water security in the future. Modelling demonstrated that this alternative tariff structure reduced demand in scarcity periods thereby preserving supply, whilst revenues are maintained to build new water supply infrastructure. In addition to exploring alternative tariffs, the potential benefits of using adaptive pressure-retarded osmosis desalination plants for both potable water and power generation was explored. This operation of these plants for power production, when they would otherwise be idle, shows promise in reducing their net energy and carbon footprints. Stakeholders in industry, government and academia were engaged in model development and validation. The constructed model displays how water resource systems can be reorganised to cope with systemic change and uncertainty.     

Efficient parallelization of a dynamic global vegetation model with river routing

The LPJ dynamic global vegetation and hydrology model with river routing is implemented on a compute cluster in order to reduce the overall computation time. In order to achieve this, a parallel algorithm had to be developed for the river routing part of the LPJ code. It can be shown that the run time of the parallel LPJ model scales well with the number of parallel tasks, even getting a super-linear speedup for 8–128 tasks. The sequential part of the model code can be estimated to be only 0.16%. This offers the opportunity, for example, to apply the model to find optimal climate change mitigation/adaptation paths requiring a multitude of subsequent simulation runs. The algorithm can also be used for networks with a different topology than river routing networks.