Disentangling the Influence of Landscape Characteristics, Hydroclimatic Variability and Land Management on Surface Water NO3-N Dynamics : Spatially Distributed Modeling Over 30 yr in a Lowland Mixed Land Use Catchment

Funding Information: Songjun Wu is funded by the Chinese Scholarship Council (CSC). Contributions from Chris Soulsby were supported by the Leverhulme Trust through the ISO‐LAND project (grant no. RPG 2018 375). The authors thank the German Weather Service (DWD) for providing meteorological data set. The staff of the IGB chemical analytics and biogeochemistry lab were appreciated for NO‐N analyses, and for compiling the long‐term DMC data set. The authors also thank Aaron Smith for supports in terms of comparing results between mHM‐Nitrate and EcHO‐iso.Peer reviewedPublisher PD

Method for assessing impacts of parameter uncertainty in sediment transport modeling applications, A

2009 Summer.Covers not scanned.Includes bibliographical references.Print version deaccessioned 2022.Numerical sediment transport models are widely used to evaluate impacts of water management activities on endangered species, to identify appropriate strategies for dam removal, and many other applications. The SRH-1D (Sedimentation and River Hydraulics - One Dimension) numerical model, formerly known as GST ARS, is used by the U.S. Bureau of Reclamation for many such evaluations. The predictions from models such as SRH-1D include uncertainty due to assumptions embedded in the model 's mathematical structure, uncertainty in the values of parameters, and various other sources. In this paper, we aim to develop a method that quantifies the degree to which parameter values are constrained by calibration data and determines the impacts of the remaining parameter uncertainty on model forecasts. Ultimately, this method could be used to assess how well calibration exercises have constrained model behavior and to identify data collection strategies that improve parameter certainty. The method uses a new multi-objective version of Generalized Likelihood Uncertainty Estimation (GLUE). In this approach, the likelihoods of parameter values are assessed using a function that weights different output variables using their first order global sensitivities, which are obtained from the Fourier Amplitude Sensitivity Test (FAST). The method is applied to SRH-1D models of two flume experiments: an erosional case described by Ashida and Michiue (1971) and a depositional case described by Seal et al. (1997). Overall, the results suggest that the sensitivities of the model outputs to the parameters can be rather different for erosional and depositional cases and that the outputs in the depositional case can be sensitive to more parameters. The results also suggest that the form of the likelihood function can have a significant impact on the assessment of parameter uncertainty and its implications for the uncertainty of model forecasts

Testing a spatially distributed tracer-aided runoff model in a snow-influenced catchment : effects of multi-criteria calibration on streamwater ages

This work was funded by the European Research Council (project GA 335910 VeWa). Dr. Huaxia Yao, Chris McConnell and Tim Field were instrumental to the collection of isotope samples and for many aspects of hydrological data collection.Peer reviewedPostprin

Natural attenuation of dissolved petroleum fuel constituents in a fractured Chalk aquifer: Contaminant mass balance with probabilistic analysis

A plume-scale mass balance is developed to assess the natural attenuation (NA) of dissolved organic contaminants in fractured, dual porosity aquifers. This methodology can be used to evaluate contaminant distribution within the aquifer, plume source term, contaminant biodegradation and plume status. The approach is illustrated for a site on the UK Upper Chalk aquifer impacted by petroleum fuel containing MTBE and TAME. Variability in site investigation data and uncertainty in the mass balance was assessed using probabilistic analysis. The analysis shows that BTEX compounds are biodegraded primarily by denitrification and sulphate reduction in the aquifer, with an equivalent plume-scale first-order biodegradation rate of 0.49 year-1. Other biodegradation processes are less important. Sorption contributes to hydrocarbon attenuation in the aquifer but is less important for MTBE and TAME. Uncertainty in the plume source term and site hydrogeological parameters had the greatest effect on the mass balance. The probabilistic analysis enabled the most likely long-term composition of the plume source term to be deduced and provided a site-specific estimate of contaminant mass flux for the prediction of plume development. The mass balance methodology provides a novel approach to improve NA assessments for petroleum hydrocarbons and other organic contaminants in these aquifer settings

Climate change impacts on future snow, ice and rain runoff in a Swiss mountain catchment using multi-dataset calibration

Study region The hydropower reservoir of Gigerwald is located in the alpine valley Calfeisental in eastern Switzerland. The lake is fed by runoff from rain, snow melt and ice melt from a few small glaciers, as well as by water collected in a neighbouring valley. Study focus Water resources in the Alps are projected to undergo substantial changes in the coming decades. It is therefore essential to explore climate change impacts in catchments with hydropower facilities. We present a multi-dataset calibration (MDC) using discharge, snowcover data and glacier mass balances for an ensemble of hydrological simulations performed using the Hydrologiska Byråns Vattenbalansavdelning (HBV)-light model. The objective is to predict the future changes in hydrological processes in the catchment and to assess the benefits of a MDC compared to a traditional calibration to discharge only. New hydrological insights for the region We found that the annual runoff dynamics will undergo significant changes with more runoff in winter and less in summer by shifting parts of the summer melt runoff to an earlier peak in spring. We furthermore found that the MDC reduces the uncertainty in the projections of glacial runoff and leads to a different distribution of runoff throughout the year than if calibrated to discharge only. We therefore argue that MDC leads to more consistent model results by representing the runoff generation processes more realistically.J. Seibert and M. Vis provided important support regarding the application of the HBV-light model. We furthermore want to thank Kirsti Hakala for providing valuable comments on the selection of climate models. We also acknowledge the Kraftwerke Sarganserland AG for the discharge data, MeteoSwiss for the gridded weather datasets and the EU-funded FP6 Integrated Project ENSEMBLES for the climate projections. Comments by two anonymous reviewers helped to improve the manuscript."Peer Reviewed

Advanced Bayesian framework for uncertainty estimation of sediment transport models

2018 Summer.Includes bibliographical references.Numerical sediment transport models are widely used to forecast the potential changes in rivers that might result from natural and/or human influences. Unfortunately, predictions from those models always possess uncertainty, so that engineers interpret the model results very conservatively, which can lead to expensive over-design of projects. The Bayesian inference paradigm provides a formal way to evaluate the uncertainty in model forecasts originating from uncertain model elements. However, existing Bayesian methods have rarely been used for sediment transport models because they often have large computational times. In addition, past research has not sufficiently addressed ways to treat the uncertainty associated with diverse sediment transport variables. To resolve those limitations, this study establishes a formal and efficient Bayesian framework to assess uncertainty in the predictions from sediment transport models. Throughout this dissertation, new methodologies are developed to represent each of three main uncertainty sources including poorly specified model parameter values, measurement errors contained in the model input data, and imperfect sediment transport equations used in the model structure. The new methods characterize how those uncertain elements affect the model predictions. First, a new algorithm is developed to estimate the parameter uncertainty and its contribution to prediction uncertainty using fewer model simulations. Second, the uncertainties of various input data are described using simple error equations and evaluated within the parameter estimation framework. Lastly, an existing method that can assess the uncertainty related to the selection and application of a transport equation is modified to enable consideration of multiple model output variables. The new methodologies are tested with a one-dimensional sediment transport model that simulates flume experiments and a natural river. Overall, the results show that the new approaches can reduce the computational time about 16% to 55% and produce more accurate estimates (e.g., prediction ranges can cover about 6% to 46% more of the available observations) compared to existing Bayesian methods. Thus, this research enhances the applicability of Bayesian inference for sediment transport modeling. In addition, this study provides several avenues to improve the reliability of the uncertainty estimates, which can help guide interpretation of model results and strategies to reduce prediction uncertainty

Exploring the possibilities of parsimonious nitrogen modelling in different ecosystems

[EN] Nitrogen is a fundamental component of living organisms, but it is also in short supply in forms in which vegetation can assimilate. As a result, nitrogen is a limiting element for vegetation growth. However, as a consequence of the human-mediated introduction of mineral nitrogen, nitrogen is also a major pollutant in anthropogenic ecosystems. Both natural and anthropogenic ecosystems supply important goods and services for the human wellbeing and in order to maintain the human living standards, there is a necessity of preserving natural ecosystems over time on one side, while improving the sustainability of anthropogenic ecosystems on the other. In that sense, mathematical models including the nitrogen cycle are useful tools which allow the analysis of the relationships and behaviours of these ecosystems, and there is a clear need to continue to develop and test nitrogen models, principally, models with an integrated approach, capable to deal with the different characteristics and behaviours of natural and anthropogenic ecosystems. Hence, the aim of the present thesis is to improve the nitrogen cycle modelling, exploring different parsimonious modelling approaches within the plant-soil-water continuum in natural and anthropogenic semiarid ecosystems. To face this objective, two parsimonious nitrogen models have been developed and implemented in two different data availability scenarios. Firstly, a new parsimonious carbon and nitrogen model, TETIS-CN, is implemented in a semiarid natural forest ecosystem trying to contribute to a better understanding and modelling of the hydrological and biogeochemical (carbon and nitrogen) cycles and their interactions in semiarid conditions and to test its capability to satisfactorily reproduce them. The results are satisfactory and suggest that it is important to include carbon observations in the calibration process, to consider all the existing vegetation species in the simulation, and that a fixed daily potential uptake may not be appropriate to reproduce the plant nitrogen uptake process. Secondly, a new parsimonious nitrogen model, TETIS-N, is implemented in a semiarid anthropogenic agricultural ecosystem. Since agriculture is the major source of diffuse pollution, being nitrogen and sediment pollution of water bodies its main associated environmental impacts, this second approach aims to improve its sustainability by evaluating the impact of several management practices on nitrogen and sediment loads, and horticultural crop yields. As a result, each management practice resulted effective in reducing a certain type of diffuse pollution, and therefore, combined scenarios are necessary to cope with all agricultural pollution sources. This thesis proved that each ecosystem has different characteristics and behaviours and therefore, different modelling necessities. Consequently, current models should include an integrate modelling of both natural and anthropogenic ecosystems.[ES] El nitrógeno es un componente fundamental de los organismos vivos, pero también es escaso en las formas en que la vegetación puede asimilarlo, lo que lo convierte en un elemento limitante para el crecimiento de la vegetación. Sin embargo, debido a la introducción de nitrógeno mineral por el hombre, también se ha convertido en un contaminante importante en los ecosistemas. Tanto los ecosistemas naturales como los antrópicos, suministran bienes y servicios importantes y, para poder mantener los niveles de vida, es necesario preservar los ecosistemas naturales, por un lado, y mejorar la sostenibilidad de los ecosistemas antrópicos por otro. De esta forma, los modelos matemáticos que incluyen la modelización del ciclo de nitrógeno son herramientas útiles que permiten el análisis de las relaciones y los comportamientos de estos ecosistemas. Por lo que existe una clara necesidad de continuar desarrollando y probando nuevos modelos de nitrógeno, principalmente con un enfoque integrado, capaces de abordar las diferentes características y comportamientos de los ecosistemas naturales y antrópicos. De esta forma, el objetivo de esta tesis es mejorar la modelización del ciclo de nitrógeno, explorando diferentes enfoques de modelización parsimoniosa dentro del continuo planta-suelo-agua en ecosistemas semiáridos naturales y antrópicos. Para abordar este objetivo, se han desarrollado e implementado dos modelos de nitrógeno parsimoniosos en dos escenarios diferentes En primer lugar, se ha desarrollado e implementado un nuevo modelo parsimonioso de carbono y nitrógeno, TETIS-CN, en un ecosistema de bosque natural semiárido. Este primer enfoque intenta contribuir a una mejor comprensión y modelización de los ciclos hidrológico y biogeoquímicos (carbono y nitrógeno) y de sus interacciones en condiciones semiáridas. Así mismo, se comprueba la capacidad del modelo propuesto para reproducirlos satisfactoriamente. Los resultados son satisfactorios y sugieren que es importante incluir observaciones de carbono en el proceso de calibración, considerar todas las especies de vegetación existentes en la simulación, y que una absorción potencial diaria fija puede no ser apropiada para reproducir el proceso de absorción de nitrógeno por parte de la vegetación. En segundo lugar, se ha desarrollado e implementado un nuevo modelo de nitrógeno parsimonioso, TETIS-N, en un ecosistema agrícola antrópico semiárido. Dado que la agricultura es la principal fuente de contaminación difusa, siendo la contaminación por nitrógeno y sedimentos de las masas de agua, su principal impacto ambiental, este segundo enfoque tiene como objetivo evaluar el impacto de varias prácticas de gestión en las descargas de nitrógeno y sedimentos, así como en la producción de los cultivos hortícolas. Como resultado, cada práctica de gestión resulta efectiva en la reducción de cierto tipo de contaminación difusa y, por lo tanto, se necesitan escenarios combinados para hacer frente a todas las fuentes de contaminación agrícola. Esta tesis ha demostrado que cada ecosistema tiene diferentes características y comportamientos y, por lo tanto, diferentes necesidades de modelización, por lo que los modelos actuales deben incluir una modelización integrada de los ecosistemas naturales y antrópicos.[CA] El nitrogen és un component fonamental dels organismes vius, però també és escàs en les formes en què la vegetació pot assimilar-ho, convertint-lo en un element limitant per al creixement de la vegetació. No obstant, a causa de la introducció de nitrogen mineral per l'home, també s'ha convertit en un contaminant important als ecosistemes. Tant els ecosistemes naturals com els antròpics, subministren béns i serveis importants i, per a poder mantenir els nivells de vida, és necessari preservar els ecosistemes naturals, d'una banda, i millorar la sostenibilitat dels ecosistemes antròpics per altra. D'aquesta forma, els models matemàtics que inclouen la modelització del cicle del nitrogen són eines útils que permeten l'anàlisi de les relacions i els comportaments d'aquests ecosistemes. Per tant, existeix una clara necessitat de continuar desenvolupant i provant nous models de nitrogen, principalment amb un enfocament integrat, capaços d'abordar les diferents característiques i comportaments dels ecosistemes naturals i antròpics. D'aquesta forma, l'objectiu d'aquesta tesi és millorar la modelització del cicle del nitrogen, explorant diferents enfocaments de modelització parsimoniosa dins del continu planta-sòl-aigua en ecosistemes semiàrids naturals i antròpics. Per a abordar aquest objectiu, s'han desenvolupat i implementat dos models de nitrogen parsimoniosos en dos escenaris diferents. En primer lloc, s'ha desenvolupat i implementat un nou model parsimoniós de carboni i nitrogen, TETIS-CN, en un ecosistema de bosc natural semiàrid. Aquest primer enfocament intenta contribuir a una millor comprensió i modelització dels cicles hidrològic i biogeoquímics (carboni i nitrogen) i de les seues interaccions en condicions semiàrides. Així mateix, comprova la capacitat del model proposat per a reproduir-los satisfactòriament. Els resultats són satisfactoris i suggereixen que és important incloure observacions de carboni en el procés de calibratge, considerar totes les espècies de vegetació existents en la simulació, i que una absorció potencial diària fixa pugues no ser apropiada per a reproduir el procés d'absorció de nitrogen per part de la vegetació. En segon lloc, s'ha desenvolupat i implementat un nou model de nitrogen parsimoniós, TETIS-N, en un ecosistema agrícola antròpic semiàrid. Atès que l'agricultura és la principal font de contaminació difusa, sent la contaminació per nitrogen i sediments de les masses d'aigua, el seu principal impacte ambiental, aquest segon enfocament té com a objectiu avaluar l'impacte de diverses pràctiques de gestió en les descàrregues de nitrogen i sediments, així com en la producció dels cultius hortícoles. Com a resultat, cada pràctica de gestió resulta efectiva en la reducció de cert tipus de contaminació difusa i, per tant, es necessiten escenaris combinats per a fer front a totes les fonts de contaminació agrícola. Aquesta tesi ha demostrat que cada ecosistema té diferents característiques i comportaments i, per tant, diferents necessitats de modelització, per tant, els models actuals han d'incloure una modelització integrada dels ecosistemes naturals i antròpics.Esta tesis doctoral no habría sido posible sin la financiación proporcionada por el Ministerio de Ciencia e Innovación a través del proyecto TETISMED (CGL2014-58127-C3-3-R) y la Unión Europea a través del proyecto LIFE17 CCA/ES/000063 RESILIENTFORESTS.Puertes Castellano, C. (2020). Exploring the possibilities of parsimonious nitrogen modelling in different ecosystems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/138141TESI

Análise comparativa de três formulações do topmodel na bacia do Rio Pequeno - PR

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Engenharia AmbientalO conhecimento obtido pelo monitoramento de fenômenos hidrológicos tem melhorado a representação da realidade pelos modelos. O modelo matemático possui vantagens sobre os outros tipos de modelos, dada à sua facilidade de implementação, baixo custo, rápida visualização dos resultados e a simulação de experimentos inviáveis na prática. Um destes modelos matemáticos é o TOPMODEL. Este modelo possui uma simples e funcional conceituação, baseada em um índice de similaridade hidrológica, sobre os fenômenos que ocorrem em uma bacia hidrográfica. Devido a livre disponibilização do TOPMODEL, desde a sua criação ele vem sendo utilizado e alterado. Entretanto, existem poucos trabalhos comparativos entre a versão original e as alteradas. O presente trabalho teve como objetivo comparar e avaliar três formulações do TOPMODEL na simulação de hidrogramas. Duas formulações do TOPMODEL foram implementadas no código da formulação original. Estas duas formulações modificam o índice topográfico da formulação original. As formulações implementadas geraram dois novos modelos. Os três modelos (MODELO 1 - TOPMODEL original (BEVEN et al., 1984); MODELO 2 - modificado por CAMPLING et al. (2002) e MODELO 3 - modificado por DATIN (1998)) foram analisados e comparados com dados obtidos na bacia Rio Pequeno no município de São José dos Pinhais - PR. Um modelo matemático denominado WADI, utilizando uma rede de triângulos irregulares, foi implementado em linguagem orientada a objetos para extrair a partir de curvas de nível digitalizadas da bacia a função distância-área. Esta função foi convertida em um histograma tempo-área dentro do TOPMODEL. Os intervalos válidos dos parâmetros dos três modelos foram estimados de acordo com recomendações da bibliografia e com prévias simulações. Os modelos foram testados com duas séries de dados horários de precipitação e vazão, uma para calibração dos modelos e a outra para validação. Conjuntos de parâmetros com melhores eficiências foram selecionados a partir de simulações utilizando a técnica Monte Carlo. O critério de escolha do valor da eficiência para exclusão de conjuntos de parâmetros foi baseado na percentagem (60%) de parâmetros excluídos para cada modelo. Por meio da distribuição de freqüência destas eficiências, os limites de incerteza referentes a 5% e 95% foram encontrados nos hidrogramas. Os conjuntos dos melhores parâmetros determinados na primeira série de dados foram aplicados na segunda série. Através de um método estatístico usando a equação de Bayes, as eficiências dos conjuntos de parâmetros da segunda série foram combinadas com as da primeira, implicando na redução do intervalo de incerteza para a segunda série. Hidrogramas das vazões observadas e simuladas com os três modelos foram traçados e estes foram comparados e analisados de acordo com as medidas de desempenho (índice de Nash, entropia e incerteza). Foi observado que para a bacia de aplicação e para as séries de dados escolhidas os três modelos obtiveram desempenhos semelhantes na simulação de hidrogramas. O MODELO 2 tem intervalos de incerteza mais estreitos, desta forma possuindo menos incerteza na calibração de parâmetros. Além disso, este modelo compreende o maior número de vazões observadas dentro dos limites de incerteza. Portanto, o MODELO 2 é considerado o melhor dos três modelos analisados na simulação de hidrogramas, às custas da introdução de um novo parâmetro