The Indus basin is one of the regions in the world that is faced with major challenges for its water sector, due to population growth, rapid urbanisation and industrialisation, environmental ...degradation, unregulated utilization of the resources, inefficient water use and poverty, all aggravated by climate change. The Indus Basin is shared by 4 countries - Pakistan, India, Afghanistan and China. With a current population of 237 million people which is projected to increase to 319 million in 2025 and 383 million in 2050, already today water resources are abstracted almost entirely (more than 95% for irrigation). Climate change will result in increased water availability in the short term. However in the long term water availability will decrease. Some current aspects in the basin need to be re-evaluated. During the past decades water abstractions - and especially groundwater extractions - have augmented continuously to support a rice-wheat system where rice is grown during the kharif (wet, summer) season (as well as sugar cane, cotton, maize and other crops) and wheat during the rabi (dry, winter) season. However, the sustainability of this system in its current form is questionable. Additional water for domestic and industrial purposes is required for the future and should be made available by a reduction in irrigation requirements. This paper gives a comprehensive listing and description of available options for current and future sustainable water resources management (WRM) within the basin. Sustainable WRM practices include both water supply management and water demand management options. Water supply management options include: (1) reservoir management as the basin is characterised by a strong seasonal behaviour in water availability (monsoon and meltwater) and water demands; (2) water quality conservation and investment in wastewater infrastructure; (3) the use of alternative water resources like the recycling of wastewater and desalination; (4) land use planning and soil conservation as well as flood management, with a focus on the reduction of erosion and resulting sedimentation as well as the restoration of ecosystem services like wetlands and natural floodplains. Water demand management options include: (1) the management of conjunctive use of surface and groundwater; as well as (2) the rehabilitation and modernization of existing infrastructure. Other demand management options are: (3) the increase of water productivity for agriculture; (4) crop planning and diversification including the critical assessment of agricultural export, especially (basmati) rice; (5) economic instruments and (6) changing food demand patterns and limiting post-harvest losses.
Parallel flow routing in SWMM 5 Burger, G.; Sitzenfrei, R.; Kleidorfer, M. ...
Environmental modelling & software : with environment data news,
03/2014, Letnik:
53
Journal Article
Recenzirano
The hydrodynamic rainfall-runoff and urban drainage simulation model SWMM (Storm Water Management Model) is a state of the art software tool applied likewise in research and practice. In order to ...reduce the computational burden of long simulation runs and to use the extra power of modern multi-core computers, a parallel version of SWMM is presented herein. The challenge has been to modify the software in such minimal way that the resulting code enhancement may find its way into the commercial and non-commercial software tools that depend on SWMM for its calculation engine. A pragmatic approach to identify and enhance only the critical parts of the software in terms of run-time was chosen in order to keep the code changes as low as possible. The enhanced software was first tested for coherence against the original code and then benchmarked on four different input scenarios ranging from a very small village to a medium sized urban area. For the investigated sewer systems a speedup of six to ten times on a twelve core system was realized, thus decreasing the execution time to an acceptable level even for tedious system analysis.
•A parallel version of SWMM for multi-core processors is herein presented.•The enhanced software was first tested for coherence and then benchmarked.•Changes were kept minimal in order to encourage adoption.•A speedup of six to ten times on a twelve-core system was realized.
Long term planning of urban water infrastructure requires acknowledgement that transitions in the water system are driven by changes in the urban environment, as well as societal dynamics. Inherent ...to the complexity of these underlying processes is that the dynamics of a system's evolution cannot be explained by linear cause-effect relationships and cannot be predicted under narrow sets of assumptions. Planning therefore needs to consider the functional behaviour and performance of integrated flexible infrastructure systems under a wide range of future conditions. This paper presents the first step towards a new generation of integrated planning tools that take such an exploratory planning approach. The spatially explicit model, denoted DAnCE4Water, integrates urban development patterns, water infrastructure changes and the dynamics of socio-institutional changes. While the individual components of the DAnCE4Water model (i.e. modules for simulation of urban development, societal dynamics and evolution/performance of water infrastructure) have been developed elsewhere, this paper presents their integration into a single model. We explain the modelling framework of DAnCE4Water, its potential utility and its software implementation. The integrated model is validated for the case study of an urban catchment located in Melbourne, Australia.
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•Long term planning of urban water infrastructure needs to account for transitions.•DAnCe4Water links urban and societal dynamics with infrastructure evolution.•The complexity of the system requires an exploratory planning approach.•The model was able to predict transition towards decentralized drainage solutions.
The new coronavirus 2 (SARS-CoV-2) is known to be also shed through feces, which makes wastewater-based surveillance possible, independent of symptomatic cases and unbiased by any testing strategies ...and frequencies. We investigated the entire population of the Principality of Liechtenstein with samples from the wastewater treatment plant Bendern (serving all 39,000 inhabitants). Twenty-four-hour composite samples were taken once or twice a week over a period of 6 months from September 2020 to March 2021. Viral RNA was concentrated using the PEG centrifugation method followed by reverse transcription quantitative PCR. The aim of this research was to assess the suitability of SARS-CoV-2 fragments to relate the viral wastewater signal to the incidences and assess the impact of the emerging B.1.1.7. variant. The viral load in the wastewater peaked at almost 9 × 10
viral fragments per person equivalent (PE) and day on October 25, and showed a second peak on December 22 reaching a viral load of approximately 2 × 10
PE
d
. Individual testing showed a lag of 4 days and a distinct underestimation of cases at the first peak when testing frequency was low. The wastewater signal showed an immediate response to the implementation of non-pharmaceutical interventions. The new virus variant B.1.1.7. was first detected in wastewater on December 23, while it was first observed with individual testing on January 13, 2021. Further, our data indicate that the emergence of new virus variant may change the wastewater signal, probably due to different shedding patterns, which should be considered in future models.
NA61/SHINE (SPS Heavy Ion and Neutrino Experiment) is a multi-purpose experimental facility to study hadron production in hadron-proton, hadron-nucleus and nucleus-nucleus collisions at the CERN ...Super Proton Synchrotron. It recorded the first physics data with hadron beams in 2009 and with ion beams (secondary super(7)Be beams) in 2011. NA61/SHINE has greatly profited from the long development of the CERN proton and ion sources and the accelerator chain as well as the H2 beamline of the CERN North Area, The latter has recently been modified to also serve as a fragment separator as needed to produce the Be beams for NA61/SHINE. Numerous components of the NA61/SHINE set-up were inherited from its predecessors, in particular, the last one, the NA49 experiment. Important new detectors and upgrades of the legacy equipment were introduced by the NA61/SHINE Collaboration. This paper describes the state of the NA61/SHINE facility - the beams and the detector system - before the CERN Long Shutdown I, which started in March 2013.
The impact of climate change, water scarcity, land use change, population growth and also population shrinking can only be predicted with uncertainties. Especially for assets with a long planning ...horizon this is a critical part for planning and design. One solution is to make centralized organized water infrastructure with a long-planning horizon resilient and adaptive. For existing centralized infrastructure such a transition would be to increasingly implement decentralized measures. But such a transition can cause severe impacts on existing centralized infrastructure. Low flow conditions in urban drainage systems can cause sediment deposition, and for water supply systems water age problems may occur. This work focuses on city-scale analysis for assessing the impact of such measures. For that a coupled model for integrated city-scale analysis is applied and further developed. In addition, a geographic information system (GIS)-based approach for sensitivity analysis is enhanced and also implemented in that model. The developed approach is applied to assess the water infrastructure of an alpine case study. With the obtained results it is demonstrated how the planning process is enhanced by indicating where and where not to implement decentralized measures in an existing water infrastructure.
Stormwater models are important tools in the design and management of urban drainage systems. Understanding the sources of uncertainty in these models and their consequences on the model outputs is ...essential so that subsequent decisions are based on reliable information. Model calibration and sensitivity analysis of such models are critical to evaluate model performance. The aim of this paper is to present the performance and parameter sensitivity of stormwater models with different levels of complexities, using the formal Bayesian approach. The rather complex MUSIC and simple KAREN models were compared in terms of predicting catchment runoff, while an empirical regression model was compared to a process-based build-up/wash-off model for stormwater pollutant prediction. A large dataset was collected at five catchments of different land-uses in Melbourne, Australia. In general, results suggested that, once calibrated, the rainfall/runoff models performed similarly and were both able to reproduce the measured data. It was found that the effective impervious fraction is the most important parameter in both models while both were insensitive to dry weather related parameters. The tested water quality models poorly represented the observed data, and both resulted in high levels of parameter uncertainty.
•Impacts of measured data uncertainty on conceptual urban stormwater models.•Error models to reflect common systematic and random errors in measured data.•Bayesian approach to perform model ...sensitivity and uncertainty analysis.•Sensitivity of the models to parameters did not alter significantly.•In general, parameters were able to compensate for the errors in measured data.
Assessing uncertainties in models due to different sources of errors is crucial for advancing urban drainage modelling practice. This paper explores the impact of input and calibration data errors on the parameter sensitivity and predictive uncertainty by propagating these errors through an urban stormwater model (rainfall runoff model KAREN coupled with a build-up/wash-off water quality model). Error models were developed to disturb the measured input and calibration data to reflect common systematic and random uncertainties found in these types of datasets. A Bayesian approach was used for model sensitivity and uncertainty analysis. It was found that random errors in measured data had minor impact on the model performance and sensitivity. In general, systematic errors in input and calibration data impacted the parameter distributions (e.g. changed their shapes and location of peaks). In most of the systematic error scenarios (especially those where uncertainty in input and calibration data was represented using ‘best-case’ assumptions), the errors in measured data were fully compensated by the parameters. Parameters were unable to compensate in some of the scenarios where the systematic uncertainty in the input and calibration data were represented using extreme worst-case scenarios. As such, in these few worst case scenarios, the model’s performance was reduced considerably.
The lifespan and therefore planning horizon of central organized water infrastructure can be up to 100years. The impact of climate change, water scarcity, land use change, population growth but also ...population shrinking can only be predicted for such a time horizon with uncertainties. One solution is to make centralized organized water infrastructure more flexible (i.e. implement decentralized measures). But these can cause severe impacts on existing centralized infrastructure. Low flow conditions in urban drainage systems can cause sediment deposition and for water supply systems water age problems may occur. This work focuses on city scale analysis for assessing the impact of such measures (i.e. transitions from centralized to decentralized solutions).
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