Simulation and parameterization of superimposed ice formation

In cold Arctic snowpacks, meltwater retention is a significant factor controlling the timing and magnitude of runoff. Meltwater percolates vertically through the snowpack until it reaches an impermeable horizon, whereupon a saturated zone is established. If the underlying media is below the freezing point, accretive ice formation takes place. This process has previously been crudely parameterized or modelled numerically. Such ice is called either superimposed ice on glaciers or basal ice on bare land. Using theory derived from sea‐ice formation, an analytical solution to basal ice growth is proposed. Results are compared against growth rates derived from numerical modelling. In addition, model results are compared to field observations of ice temperatures. The analytical solution is further extended to account for the temperature gradient inside the underlying media and the variable thermal properties of the underlying media. In the analysis, observations and references have predominantly relied on knowledge from glaciers. However, the process of accretive ice growth is equally important in seasonal snow packs with a cold snow‐ground interface and on Arctic sea ice where the ice‐snow interface is well below freezing point. The simplification of this accretive ice growth problem makes the solution attractive for incorporation in large‐scale cryospheric models. Copyright © 2007 John Wiley & Sons, Ltd.     

Emulation of a process-based estuarine hydrodynamic model

Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed “neuroemulator” retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology.     

Assessment of Management Options in Marine Fisheries by Qualitative Modelling Techniques

An effective management of the rapidly dwindling marine fish resources is of great ecological, economic and social importance for the future. An over-development of commercial fisheries has brought about a multitude of negative environmental impacts, such as an accelerated exploitation of stocks or a decrease of marine biodiversity, and furthermore, a profound structural change in fish industry. However, the main reason for the non-prosperous rationing of marine resources is the lack of knowledge about certain processes as well as the non-availability of adequate steering instruments. This paper addresses the lack of conceptualization in the case of uncertain knowledge. It proposes a model approach which can be used for weak but improved decision support under the premise of vague knowledge. The usage of qualitative differential equations illustrates general patterns of overcapitalization of fishing fleets. The extension of traditional model approaches by integration of additional socio-economic phenomena in this context supplies deeper insights in the dynamics of a coupled economic and ecological system. The approach provides a set of characteristic system behaviours which can be fruitfully used for the development of future management tasks.     

Deriving the relationship among discharge,biomass and Manning's coefficient through a calibration approach

The subject of environmental engineering is currently of great interest. Field experiments as well as numerical models have proven their worth in this research field. An introduction to hydrodynamic modelling, coupled to the modelling of vegetation biomass is described. The developed Strive (STream RIVer Ecosystem) model is set up in the Femme (‘Flexible Environment for Mathematically Modelling the Environment’) environment and has already proven its worth in a large number of calculations (De Doncker et al., 2006 , 2008b ). Discharges and water levels are modelled together with modelling of electrical conductivity (EC). Extensive measurement campaigns are carried out to collect a large number of observations and calibration of the model is based on this data set. Furthermore, calibration methods and the discussion of this process are displayed. As a result, it is seen that the developed Strive model can model both, hydrodynamic and ecological processes, in an accurate way. The work highlights the importance of detailed determination of Manning's coefficient, dependent on discharge and amount of biomass, as an important calibration parameter for accurate modelling. Copyright © 2011 John Wiley & Sons, Ltd.     

River management system development in Asia based on Data Integration and Analysis System (DIAS) under GEOSS

This paper introduces the process of development and practical use implementation of an advanced river management system for supporting integrated water resources management practices in Asian river basins under the framework of GEOSS Asia water cycle initiative (AWCI). The system is based on integration of data from earth observation satellites and in-situ networks with other types of data, including numerical weather prediction model outputs, climate model outputs, geographical information, and socio-economic data. The system builds on the water and energy budget distributed hydrological model (WEB-DHM) that was adapted for specific conditions of studied basins, in particular snow and glacier phenomena and equipped with other functions such as dam operation optimization scheme and a set of tools for climate change impact assessment to be able to generate relevant information for policy and decision makers. In situ data were archived for 18 selected basins at the data integration and analysis system of Japan (DIAS) and demonstration projects were carried out showing potential of the new system. It included climate change impact assessment on hydrological regimes, which is presently a critical step for sound management decisions. Results of such three case studies in Pakistan, Philippines, and Vietnam are provided here.     

Challenges in operationalizing the water–energy–food nexus

Concerns about the water–energy–food (WEF) nexus have motivated many discussions regarding new approaches for managing water, energy and food resources. Despite the progress in recent years, there remain many challenges in scientific research on the WEF nexus, while implementation as a management tool is just beginning. The scientific challenges are primarily related to data, information and knowledge gaps in our understanding of the WEF inter-linkages. Our ability to untangle the WEF nexus is also limited by the lack of systematic tools that could address all the trade-offs involved in the nexus. Future research needs to strengthen the pool of information. It is also important to develop integrated software platforms and tools for systematic analysis of the WEF nexus. The experience made in integrated water resources management in the hydrological community, especially in the framework of Panta Rhei, is particularly well suited to take a lead in these advances.     

Finite element modeling assumptions impact on seismic response demands of MRF-buildings

Recent seismic events have raised concerns over the safety and vulnerability of reinforced concrete moment resisting frame “RC-MRF” buildings. The seismic response of such buildings is greatly dependent on the computational tools used and the inherent assumptions in the modelling process. Thus, it is essential to investigate the sensitivity of the response demands to the corresponding modelling assumption. Many parameters and assumptions are justified to generate effective structural finite element (FE) models of buildings to simulate lateral behaviour and evaluate seismic design demands. As such, the present study focuses on the development of reliable FE models with various levels of refinement. The effects of the FE modelling assumptions on the seismic response demands on the design of buildings are investigated. the predictive ability of a FE model is tied to the accuracy of numerical analysis; a numerical analysis is performed for a series of symmetric buildings in active seismic zones. The results of the seismic response demands are presented in a comparative format to confirm drift and strength limits requirements. A proposed model is formulated based on a simplified modeling approach, where the most refined model is used to calibrate the simplified model.     

Potential of soil moisture observations in flood modelling: Estimating initial conditions and correcting rainfall

Rainfall runoff (RR) models are fundamental tools for reducing flood hazards. Although several studies have highlighted the potential of soil moisture (SM) observations to improve flood modelling, much research has still to be done for fully exploiting the evident connection between SM and runoff. As a way of example, improving the quality of forcing data, i.e. rainfall observations, may have a great benefit in flood simulation. Such data are the main hydrological forcing of classical RR models but may suffer from poor quality and record interruption issues. This study explores the potential of using SM observations to improve rainfall observations and set a reliable initial wetness condition of the catchment for improving the capability in flood modelling. In particular, a RR model, which incorporates SM for its initialization, and an algorithm for rainfall estimation from SM observations are coupled using a simple integration method. The study carried out at the Valescure experimental catchment (France) demonstrates the high information content retained by SM for RR transformation, thus giving new possibilities for improving hydrological applications. Results show that an appropriate configuration of the two models allows obtaining improvement in flood simulation up to 15% in mean and 34% in median Nash Sutcliffe performances as well as a reduction of the median error in volume and on peak discharge of about 30% and 15%, respectively.     

TOPCAT‐NP: a minimum information requirement model for simulation of flow and nutrient transport from agricultural systems

Future catchment planning requires a good understanding of the impacts of land use and management, especially with regard to nutrient pollution. A range of readily usable tools, including models, can play a critical role in underpinning robust decision‐making. Modelling tools must articulate our process understanding, make links to a range of catchment characteristics and scales and have the capability to reflect future land‐use management changes. Hence, the model application can play an important part in giving confidence to policy makers that positive outcomes will arise from any proposed land‐use changes. Here, a minimum information requirement (MIR) modelling approach is presented that creates simple, parsimonious models based on more complex physically based models, which makes the model more appropriate to catchment‐scale applications. This paper shows three separate MIR models that represent flow, nitrate losses and phosphorus losses. These models are integrated into a single catchment model (TOPCAT‐NP), which has the advantage that certain model components (such as soil type and flow paths) are shared by all three MIR models. The integrated model can simulate a number of land‐use activities that relate to typical land‐use management practices. The modelling process also gives insight into the seasonal and event nature of nutrient losses exhibited at a range of catchment scales. Three case studies are presented to reflect the range of applicability of the model. The three studies show how different runoff and nutrient loss regimes in different soil/geological and global locations can be simulated using the same model. The first case study models intense agricultural land uses in Denmark (Gjern, 114 km²), the second is an intense agricultural area dominated by high superphosphate applications in Australia (Ellen Brook, 66 km²) and the third is a small research‐scale catchment in the UK (Bollington Hall, 2 km²). Copyright © 2007 John Wiley & Sons, Ltd.     

Climacogram versus autocovariance and power spectrum in stochastic modelling for Markovian and Hurst–Kolmogorov processes

Three common stochastic tools, the climacogram i.e. variance of the time averaged process over averaging time scale, the autocovariance function and the power spectrum are compared to each other to assess each one’s advantages and disadvantages in stochastic modelling and statistical inference. Although in theory, all three are equivalent to each other (transformations one another expressing second order stochastic properties), in practical application their ability to characterize a geophysical process and their utility as statistical estimators may vary. In the analysis both Markovian and non Markovian stochastic processes, which have exponential and power-type autocovariances, respectively, are used. It is shown that, due to high bias in autocovariance estimation, as well as effects of process discretization and finite sample size, the power spectrum is also prone to bias and discretization errors as well as high uncertainty, which may misrepresent the process behaviour (e.g. Hurst phenomenon) if not taken into account. Moreover, it is shown that the classical climacogram estimator has small error as well as an expected value always positive, well-behaved and close to its mode (most probable value), all of which are important advantages in stochastic model building. In contrast, the power spectrum and the autocovariance do not have some of these properties. Therefore, when building a stochastic model, it seems beneficial to start from the climacogram, rather than the power spectrum or the autocovariance. The results are illustrated by a real world application based on the analysis of a long time series of high-frequency turbulent flow measurements.     

Challenges in operationalizing the water–energy–food nexus

ABSTRACT

Concerns about the water–energy–food (WEF) nexus have motivated many discussions regarding new approaches for managing water, energy and food resources. Despite the progress in recent years, there remain many challenges in scientific research on the WEF nexus, while implementation as a management tool is just beginning. The scientific challenges are primarily related to data, information and knowledge gaps in our understanding of the WEF inter-linkages. Our ability to untangle the WEF nexus is also limited by the lack of systematic tools that could address all the trade-offs involved in the nexus. Future research needs to strengthen the pool of information. It is also important to develop integrated software platforms and tools for systematic analysis of the WEF nexus. The experience made in integrated water resources management in the hydrological community, especially in the framework of Panta Rhei, is particularly well suited to take a lead in these advances.     

Six decades of ecohydrological research connecting landscapes and riverscapes in the Girnock Burn,Scotland: Atlantic salmon population and habitat dynamics in a changing world

Long-term data are crucial for understanding ecological responses to climate and land use change; they are also vital evidence for informing management. As a migratory fish, Atlantic salmon are sentinels of both global and local environmental change. This paper reviews the main insights from six decades of research in an upland Scottish stream (Girnock Burn) inhabited by a spring Atlantic salmon population dominated by multi-sea-winter fish. Research began in the 1960s providing a census of returning adults, juvenile emigrants and in-stream production of Atlantic salmon. Early research pioneered new monitoring techniques providing new insights into salmon ecology and population dynamics. These studies underlined the need for interdisciplinary approaches for understanding salmon interactions with physical, chemical and biological components of in-stream habitats at different life-stages. This highlighted variations in catchment-scale hydroclimate, hydrology, geomorphology and hydrochemistry as essential to understanding freshwater habitats in the wider landscape context. Evolution of research has resulted in a remarkable catalogue of novel findings underlining the value of long-term data that increases with time as modelling tools advance to leverage more insights from “big data”. Data are available on fish numbers, sizes and ages across multiple life stages, extending over many decades and covering a wide range of stock levels. Combined with an unusually detailed characterization of the environment, these data have enabled a unique process-based understanding of the controls and bottlenecks on salmon population dynamics across the entire lifecycle and the consequences of declining marine survival and ova deposition. Such powerful datasets, methodological enhancements and the resulting process understanding have informed and supported the development of fish population assessment tools which have been applied to aid management of threatened salmon stocks at large-catchment, regional and national scales. Many pioneering monitoring and modelling approaches developed have been applied internationally. This history shows the importance of integrating discovery science with monitoring for informing policy development and assessing efficacy of management options. It also demonstrates the need to continue to resource long-term sites, which act as a focus for inter-disciplinary research and innovation, and where the overall value of the research greatly exceeds the costs of individual component parts.     

CATCHMENT-WIDE, SECTIONAL AND LOCAL ASPECTS IN SEDIMENT TRANSPORT MODELLING AND MONITORING

1.INTRODUCTIONOVerthelastdecadesmuchprogresshasbeenmadeconcerningsedimenttransPOrtmodellingandmonitoring.Thedifferelltiationincatchmeflt-tvide,sectionalandlocalaspectsreflectsthefactthatmanysedimenttransportandpredictionmodelsaredealingwithspecialpartsofriverSystems,mainlydifferinginscale.Overthepastyears,scaleissuesinhydrologyhaverapidlyincreasedinimportance(BLoSCHL,1996).Onalargescaletheapplicationoffractals,self-similarityanalysistolandscapeorganizationandoptimalchannelnetlvorks(O…     

Sensitivity analysis of prior model probabilities and the value of prior knowledge in the assessment of conceptual model uncertainty in groundwater modelling

A key point in the application of multi‐model Bayesian averaging techniques to assess the predictive uncertainty in groundwater modelling applications is the definition of prior model probabilities, which reflect the prior perception about the plausibility of alternative models. In this work the influence of prior knowledge and prior model probabilities on posterior model probabilities, multi‐model predictions, and conceptual model uncertainty estimations is analysed. The sensitivity to prior model probabilities is assessed using an extensive numerical analysis in which the prior probability space of a set of plausible conceptualizations is discretized to obtain a large ensemble of possible combinations of prior model probabilities. Additionally, the value of prior knowledge about alternative models in reducing conceptual model uncertainty is assessed by considering three example knowledge states, expressed as quantitative relations among the alternative models. A constrained maximum entropy approach is used to find the set of prior model probabilities that correspond to the different prior knowledge states. For illustrative purposes, a three‐dimensional hypothetical setup approximated by seven alternative conceptual models is employed. Results show that posterior model probabilities, leading moments of the predictive distributions and estimations of conceptual model uncertainty are very sensitive to prior model probabilities, indicating the relevance of selecting proper prior probabilities. Additionally, including proper prior knowledge improves the predictive performance of the multi‐model approach, expressed by reductions of the multi‐model prediction variances by up to 60% compared with a non‐informative case. However, the ratio between‐model to total variance does not substantially decrease. This suggests that the contribution of conceptual model uncertainty to the total variance cannot be further reduced based only on prior knowledge about the plausibility of alternative models. These results advocate including proper prior knowledge about alternative conceptualizations in combination with extra conditioning data to further reduce conceptual model uncertainty in groundwater modelling predictions. Copyright © 2009 John Wiley & Sons, Ltd.     

基于四维变分同化法的巢湖流域南淝河水质模拟

针对河流模拟中未知不确定性源对模拟精度的影响,以巢湖流域南淝河为研究对象,建立了基于四维变分同化方法的南淝河干流水质模型,研究了含未知污染源的南淝河水质过程模拟.模型以未知污染负荷的动态变化过程为控制变量,通过同化沿河不同断面的逐日水质监测数据,识别不同河段的逐日入河污染负荷过程来实现水质过程的模拟,改变了常规模型模拟需提前预知并输入污染负荷的应用前提.模拟结果表明,采用四维变分同化方法的水质模拟结果有明显改进,重点河段水质模拟的纳什效率系数从小于0提高到0.5以上.识别的入河污染过程与降雨过程波动总体一致,证实南淝河的入河污染与降雨过程密切;同时,模型也可识别异常的入河负荷,提高模型对水环境问题的诊断分析能力.该方法可推广应用于复杂河流系统,为巢湖等流域污染来源定量解析、水质预测预警及污染管控提供支持.     

Biogeomorphology,quo vadis? On processes,time, and space in biogeomorphology

Biogeomorphology has been expanding as a discipline, due to increased recognition of the role that biology can play in geomorphic processes, as well as due to our increasing capacity to measure and quantify feedback between biological and geomorphological systems. Here, we provide an overview of the growth and status of biogeomorphology. This overview also provides the context for introducing this special issue on biogeomorphology, and specifically examines the thematic domains of biogeomorphological research, methods used, open questions and conundrums, problems encountered, future research directions, and practical applications in management and policy (e.g. nature-based solutions). We find that whilst biogeomorphological studies have a long history, there remain many new and surprising biogeomorphic processes and feedbacks that are only now being identified and quantified. Based on the current state of knowledge, we suggest that linking ecological and geomorphic processes across different spatio-temporal scales emerges as the main research challenge in biogeomorphology, as well as the translation of biogeomorphic knowledge into management approaches to environmental systems. We recommend that future biogeomorphic studies should help to contextualize environmental feedbacks by including the spatio-temporal scales relevant to the organism(s) under investigation, using knowledge of their ecology and size (or metabolic rate). Furthermore, in order to sufficiently understand the ‘engineering’ capacity of organisms, we recommend studying at least the time period bounded by two disturbance events, and recommend to also investigate the geomorphic work done during disturbance events, in order to put estimates of engineering capacity of biota into a wider perspective. Finally, the future seems bright, as increasingly inter-disciplinary and longer-term monitoring are coming to fruition, and we can expect important advances in process understanding across scales and better-informed modelling efforts. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd     

Geospatial knowledge-based verification and improvement of GlobeLand30

Assuring the quality of land-cover data is one of the major challenges for large- area mapping projects. Although the use of geospatial knowledge and ancillary data in improving land-cover classification has been studied since the early 1980s, mature methods and efficient supporting tools are still lacking. This paper presents a geospatial knowledge-based verification and improvement approach for global land cover (GLC) mapping at 30-m resolution. A set of verification rules is derived from three types of land cover and its change knowledge (natural, cultural and temporal constraints). A group of web-based supporting tools is developed to facilitate the integration of and access to large amounts of ancillary data and to support online data manipulation and analysis as well as collaborative verification workflows. With this approach, two 30-m GLC datasets (GlobeLand-2000 and GlobeLand-2010) were verified and modified. The results indicate that the data quality of GlobeLand30 has been largely improved.     

Training the rivers and exploring the coasts. Knowledge evolution in the Netherlands in two engineering fields between 1800 and 1940

In this paper, the author wants to explore the knowledge development in two crucial fields, river management and coast management in the 19th century and first decades of the 20th century. Were there similar characteristics in this development? Which types of knowledge can be distinguished? Who were the principal actors in these processes? Did the knowledge evolution have a Dutch stamp or a rather international flavour?To structure the analysis, the author uses the concept of technology regime, a set of technical rules which shapes the know-how of engineers, their design rules and research processes. The analysis shows that the knowledge development of river management and coastal management followed different evolution paths between 1800 and 1940. In the field of river management, a substantial amount of mathematical and physical theories had been gradually developed since the end of the 17th century. After 1850, the regularization approach met gradually a widespread support. Empirical data, design rules, theoretical knowledge and engineering pivoted around the regularization approach, and a technology regime around this approach emerged. The regularization regime further developed in the 20th century, and handbooks were increasingly shaped by mathematical and physical reasoning and formulas. On the other hand, coastal management was until the 1880s a rather marginal activity. Coastal engineering was an extremely complex and multidimensional field of knowledge which no engineer was able to grasp.The foundation of a Dutch weather institute was a first important step towards a more theoretical approach. The Zuiderzee works (starting in 1925) gave probably the most important stimuli to scientific coastal research. It was also a main factor in setting up scientific institutes by Rijkswaterstaat. So from the 1920s, Rijkswaterstaat became a major producer of scientific knowledge, not only in tidal modelling but also in coastal research. Due to a multidisciplinary knowledge network, coastal research transformed from a marginal to a first-rank scientific field, and this transformation enabled Rijkswaterstaat to set a much higher level of ambition in coastal management. The 1953 flood and the Deltaworks marked a new era. New design rules for sea dykes and river levees, based on a revolutionary statistical risk approach were determined, and design rules for the Deltaworks estuary closures were developed, being enabled by the development of hydraulic research.