304 research outputs found

    Modelling of point and non-point source pollution of nitrate with SWAT in the river Dill, Germany

    No full text
    International audienceWe used the Soil and Water Assessment Tool (SWAT) to simulate point and non-point source pollution of nitrate in a mesoscale mountainous catchment. The results show that the model efficiency for daily discharge is 0.81 for the calibration period (November 1990 to December 1993) and 0.56 for the validation period (April 2000 to January 2003). The model efficiency for monthly nitrate load is 0.66 and 0.77 for the calibration period (April 2000 to March 2002) and validation period (April 2002 to January 2003), respectively. However, the model efficiency for daily loads is low (0.15), which cannot only be attributed to the quality of input data of point source effluents. An analysis of the internal fluxes and cycles of nitrogen pointed out considerable weaknesses in the models conceptualisation of the nitrogen modules which will be improved in future research

    Assessing the model performance of an integrated hydrological and biogeochemical model for discharge and nitrate load predictions

    Get PDF
    International audienceIn this study, we evaluate the performance of the SWAT-N model, a modified version of the widely used SWAT version, for discharge and nitrate predictions at the mesoscale Dill catchment (Germany) for a 5-year period. The underlying question is, whether the model efficiency is sufficient for scenario analysis of land-use changes on both water quantity and quality. The Shuffled Complex Evolution (SCE-UA) algorithm is used to calibrate the model for daily discharge at the catchments outlet. Model performance is assessed with a split-sampling as well as a proxy-basin test using recorded hydrographs of four additional gauges located within the catchment. The efficiency regarding nitrate load simulation is assessed without further calibration on a daily, log-daily, weekly, and monthly basis as compared to observations derived from an intensive sampling campaign conducted at the catchments outlet. A new approach is employed to test the spatial consistency of the model, where simulated longitudinal profiles of nitrate concentrations were compared with observed longitudinal profiles. It is concluded that the model efficiency of SWAT-N is sufficient for the assessment of scenarios for daily discharge predictions. SWAT-N can be employed without further calibration for nitrate load simulations on both a weekly and monthly basis with an acceptable degree of accuracy. However, the model efficiency for daily nitrate load is insufficient, which can be attributed to both data uncertainty (i.e. point-source effluents and actual farming practise) as well as structural errors. The simulated longitudinal profiles meet the observations reasonably well, which suggests that the model is spatially consistent

    Evaluation of evapotranspiration methods for model validation in a semi-arid watershed in northern China

    Get PDF
    International audienceThis study evaluates the performance of four evapotranspiration methods (Priestley-Taylor, Penman-Monteith, Hargreaves and Makkink) of differing complexity in a semi-arid environment in north China. The results are compared to observed water vapour fluxes derived from eddy flux measurements. The analysis became necessary after discharge simulations using an automatically calibrated version of the Soil and Water Assessment Tool (SWAT) failed to reproduce runoff measurements. Although the study area receives most of the annual rainfall during the vegetation period, high temperatures can cause water scarcity. We investigate which evapotranspiration method is most suitable for this environment and whether the model performance of SWAT can be improved with the most adequate evapotranspiration method. The evapotranspiration models were tested in two consecutive years with different rainfall amounts. In general, the simple Hargreaves and Makkink equations outmatch the more complex Priestley-Taylor and Penman-Monteith methods, although their performance depended on water availability. Effects on the quality of SWAT runoff simulations, however, remained minor. Although evapotranspiration is an important process in the hydrology of this steppe environment, our analysis indicates that other driving factors still need to be identified to improve SWAT simulations

    Abflussprozesse auf der Mesoskala? - Grenzen und Moeglichkeiten multivariater Tracer Methoden

    Get PDF
    Auf Grundlage von hydrochemischen Zeitreihen wurden tracer basierte Mischungsmodelle zur Ableitung von Abflussprozessen zwischen Teileinzugs-gebieten des Dill-Einzugsgebiets (Hessen) miteinander verglichen. Hierzu wurden die Grundwasserabfluesse von Teileinzugsgebieten mit Einzugsgebietseigenschaften, wie mittlere Hangneigung, in Beziehung gesetzt. Die Ergebnisse zeigen, dass die Wahl der Tracerkombinationen und die Metrik der Tracerdaten (z.B. PCA) einen erheblichen Einfluss auf die Aussage zu den Einflussgroessen des hydrologischen Verhaltens eines Einzugsgebiets haben

    The Causal Structure of Emotions in Aristotle: Hylomorphism, Causal Interaction between Mind and Body, and Intentionality

    Get PDF
    Recently, a strong hylomorphic reading of Aristotelian emotions has been put forward, one that allegedly eliminates the problem of causal interaction between soul and body. Taking the presentation of emotions in de An. I 1 as a starting point and basic thread, but relying also on the discussion of Rh. II, I will argue that this reading only takes into account two of the four causes of emotions, and that, if all four of them are included into the picture, then a causal interaction of mind and body remains within Aristotelian emotions, independent of how strongly their hylomorphism is understood. Beyond the discussion with this recent reading, the analysis proposed of the fourfold causal structure of emotions is also intended as a hermeneutical starting point for a comprehensive analysis of particular emotions in Aristotle. Through the different causes Aristotle seems to account for many aspects of the complex phenomenon of emotion, including its physiological causes, its mental causes, and its intentional object

    Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model

    Get PDF
    Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures – for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil–plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten–Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need for including agricultural management options in the coupled model

    Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging

    Get PDF
    Irrigation agriculture plays an increasingly important role in food supply. Many evapotranspiration models are used today to estimate the water demand for irrigation. They consider different stages of crop growth by empirical crop coefficients to adapt evapotranspiration throughout the vegetation period. We investigate the importance of the model structural versus model parametric uncertainty for irrigation simulations by considering six evapotranspiration models and five crop coefficient sets to estimate irrigation water requirements for growing wheat in the Murray–Darling Basin, Australia. The study is carried out using the spatial decision support system SPARE:WATER. We find that structural model uncertainty among reference ET is far more important than model parametric uncertainty introduced by crop coefficients. These crop coefficients are used to estimate irrigation water requirement following the single crop coefficient approach. Using the reliability ensemble averaging (REA) technique, we are able to reduce the overall predictive model uncertainty by more than 10%. The exceedance probability curve of irrigation water requirements shows that a certain threshold, e.g. an irrigation water limit due to water right of 400 mm, would be less frequently exceeded in case of the REA ensemble average (45%) in comparison to the equally weighted ensemble average (66%). We conclude that multi-model ensemble predictions and sophisticated model averaging techniques are helpful in predicting irrigation demand and provide relevant information for decision making

    Spatial distribution of soils determines export of nitrogen and dissolved organic carbon from an intensively managed agricultural landscape

    Get PDF
    The surrounding landscape of a stream has crucial impacts on the aquatic environment. This study pictures the hydro-biogeochemical situation of the Tyrebækken creek catchment in central Jutland, Denmark. The intensively managed agricultural landscape is dominated by rotational croplands. The small catchment mainly consist of sandy soil types besides organic soils along the streams. The aim of the study was to characterise the relative influence of soil type and land use on stream water quality. Nine snapshot sampling campaigns were undertaken during the growing season of 2009. Total dissolved nitrogen (TDN), nitrate (NO3-), ammonium nitrogen and dissolved organic carbon (DOC) concentrations were measured, and dissolved organic nitrogen (DON) was calculated for each grabbed sample. Electrical conductivity, pH and flow velocity were measured during sampling. Statistical analyses showed significant differences between the northern, southern and converged stream parts, especially for NO3- concentrations with average values between 1.4 mg N l-1 and 9.6 mg N l-1. Furthermore, throughout the sampling period DON concentrations increased to 2.8 mg N l-1 in the northern stream contributing up to 81% to TDN. Multiple-linear regression analyses performed between chemical data and landscape characteristics showed a significant negative influence of organic soils on instream N concentrations and corresponding losses in spite of their overall minor share of the agricultural land (12.9%). On the other hand, organic soil frequency was positively correlated to the corresponding DOC concentrations. Croplands also had a significant influence but with weaker correlations. For our case study we conclude that the fractions of coarse textured and organic soils have a major influence on N and DOC export in this intensively used landscape. Meanwhile, the contribution of DON to the total N losses was substantial

    Aristotle’s assertoric syllogistic and modern relevance logic

    Get PDF
    This paper sets out to evaluate the claim that Aristotle’s Assertoric Syllogistic is a relevance logic or shows significant similarities with it. I prepare the grounds for a meaningful comparison by extracting the notion of relevance employed in the most influential work on modern relevance logic, Anderson and Belnap’s Entailment. This notion is characterized by two conditions imposed on the concept of validity: first, that some meaning content is shared between the premises and the conclusion, and second, that the premises of a proof are actually used to derive the conclusion. Turning to Aristotle’s Prior Analytics, I argue that there is evidence that Aristotle’s Assertoric Syllogistic satisfies both conditions. Moreover, Aristotle at one point explicitly addresses the potential harmfulness of syllogisms with unused premises. Here, I argue that Aristotle’s analysis allows for a rejection of such syllogisms on formal grounds established in the foregoing parts of the Prior Analytics. In a final section I consider the view that Aristotle distinguished between validity on the one hand and syllogistic validity on the other. Following this line of reasoning, Aristotle’s logic might not be a relevance logic, since relevance is part of syllogistic validity and not, as modern relevance logic demands, of general validity. I argue that the reasons to reject this view are more compelling than the reasons to accept it and that we can, cautiously, uphold the result that Aristotle’s logic is a relevance logic

    First LIGO search for gravitational wave bursts from cosmic (super)strings

    Get PDF
    We report on a matched-filter search for gravitational wave bursts from cosmic string cusps using LIGO data from the fourth science run (S4) which took place in February and March 2005. No gravitational waves were detected in 14.9 days of data from times when all three LIGO detectors were operating. We interpret the result in terms of a frequentist upper limit on the rate of gravitational wave bursts and use the limits on the rate to constrain the parameter space (string tension, reconnection probability, and loop sizes) of cosmic string models.Comment: 11 pages, 3 figures. Replaced with version submitted to PR
    corecore