A review of surrogate models and their application to groundwater modeling

The spatially and temporally variable parameters and inputs to complex groundwater models typically result in long runtimes which hinder comprehensive calibration, sensitivity, and uncertainty analysis. Surrogate modeling aims to provide a simpler, and hence faster, model which emulates the specified output of a more complex model in function of its inputs and parameters. In this review paper, we summarize surrogate modeling techniques in three categories: data-driven, projection, and hierarchical-based approaches. Data-driven surrogates approximate a groundwater model through an empirical model that captures the input-output mapping of the original model. Projection-based models reduce the dimensionality of the parameter space by projecting the governing equations onto a basis of orthonormal vectors. In hierarchical or multifidelity methods the surrogate is created by simplifying the representation of the physical system, such as by ignoring certain processes, or reducing the numerical resolution. In discussing the application to groundwater modeling of these methods, we note several imbalances in the existing literature: a large body of work on data-driven approaches seemingly ignores major drawbacks to the methods; only a fraction of the literature focuses on creating surrogates to reproduce outputs of fully distributed groundwater models, despite these being ubiquitous in practice; and a number of the more advanced surrogate modeling methods are yet to be fully applied in a groundwater modeling context

An 27Al NMR study of the interaction of water with AlPO4-11

Exptl. and spectral simulations of 27Al MAS and double rotation NMR spectra measured at 7.0 T proved the preferential hydration of 1 tetrahedral Al site in AlPO-11, transforming this site reversibly into octahedral Al. [on SciFinder (R)

Surface water numerical modelling for the Galilee subregion Product 2.6.1 for the Galilee subregion from the Lake Eyre Basin Bioregional Assessment

No abstract available

Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment

No abstract available

Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment

No abstract available

The Prospective Dutch Colorectal Cancer (PLCRC) cohort: real-world data facilitating research and clinical care

Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treatments in daily practice. Since 2013, the Prospective Dutch Colorectal Cancer (PLCRC) cohort, linked to the Netherlands Cancer Registry, serves as an infrastructure for scientific research collecting additional patient-reported outcomes (PRO) and biospecimens. Here we report on cohort developments and investigate to what extent PLCRC reflects the “real-world”. Clinical and demographic characteristics of PLCRC participants were compared with the general Dutch CRC population (n = 74,692, Dutch-ref). To study representativeness, standardized differences between PLCRC and Dutch-ref were calculated, and logistic regression models were evaluated on their ability to distinguish cohort participants from the Dutch-ref (AU-ROC 0.5 = preferred, implying participation independent of patient characteristics). Stratified analyses by stage and time-period (2013–2016 and 2017–Aug 2019) were performed to study the evolution towards RWD. In August 2019, 5744 patients were enrolled. Enrollment increased steeply, from 129 participants (1 hospital) in 2013 to 2136 (50 of 75 Dutch hospitals) in 2018. Low AU-ROC (0.65, 95% CI: 0.64–0.65) indicates limited ability to distinguish cohort participants from the Dutch-ref. Characteristics that remained imbalanced in the period 2017–Aug’19 compared with the Dutch-ref were age (65.0 years in PLCRC, 69.3 in the Dutch-ref) and tumor stage (40% stage-III in PLCRC, 30% in the Dutch-ref). PLCRC approaches to represent the Dutch CRC population and will ultimately meet the current demand for high-quality RWD. Efforts are ongoing to improve multidisciplinary recruitment which will further enhance PLCRC’s representativeness and its contribution to a learning healthcare system

Incorporating topography-dependent groundwater storage in AWRA-L improves groundwater flux estimation

The landscape component of the Australian Water Resources Assessment system, AWRA-L, is a grid-distributed biophysical model designed to simulate water storage in and flows between vegetation, soil, surface water and groundwater for the Australian continent [van Dijk, 2010a]. This study addresses three known issues with the representation of groundwater dynamics in version 0.5 of AWRA-L: 1. The saturated area fraction per grid cell, which controls surface runoff, soil and groundwater evaporation, is computed as the ratio of groundwater storage over a reference groundwater storage, rather than a function of groundwater storage and topography. 2. The entire groundwater store is ultimately accessible for evapotranspiration, while in reality only the fraction of the groundwater store in reach of plant roots is accessible. 3. Groundwater discharge to rivers is a function of groundwater storage without taking into account the connection status of the river. Ephemeral streams are therefore not well represented in AWRAL. These issues are addressed by using topography information in the calculation of saturated area fraction and baseflow. Topographic variability within an AWRA-grid cell is represented by hypsometric curves derived from a 9" Digital Elevation Model. The minimum elevation within the cell is assumed to be equal to the drainage elevation. The DEM data is transformed into potential groundwater storage by multiplying cell ground elevation by effective porosity. The saturated area fraction corresponding to a groundwater storage level is then obtained from hypsometric curves. By subtracting an extinction depth from the hypsometric curve, the fraction of groundwater storage available for evapotranspiration can be computed. This provides a mechanism for groundwater storage to be lower than the storage corresponding to drainage elevation. Under the assumption that the river system is disconnected or losing in this situation, base flow to rivers is only computed if storage is greater than the drainage elevation. Results for a limited number of test locations, representative for a range of Australian conditions, show that the results of the modified model are in better agreement with the conceptual understanding of groundwater dynamics at these locations

Conceptual evaluation of continental land-surface model behaviour

Continental land-surface models, such as the landscape component of the Australian Water Resources Assessment System (AWRA-L), aim to simulate the water balance over a wide variety of climates, land forms and land uses. To accommodate this range of hydrological conditions, model conceptualisation has to be flexible, while at the same time robust and parsimonious to allow for calibration using sparse data sets.In this study a Monte Carlo sensitivity analysis of the AWRA-L system is carried out as a step preceding calibration in which the hyperspace formed by parameters and initial conditions is explored using Latin Hypercube Sampling. The main goal is to test whether the model behaviour is in accordance with current understanding of Australian hydrology and to guide calibration. To visualise and analyse the high-dimensionality of the output space and the complex, non-linear interactions between processes and parameters, we used Self Organizing Maps, a non-parametric neural network.The results show that the main cause of non-linear model behaviour can be attributed to the ratio of rainfall over potential evaporation ratio, which determines which processes will dominate the water balance and the persistence of initial conditions. The model behaviour corresponds well to the current understanding of the hydrology of the Australian continent

Beginnende geletterdheid bij kinderen met cerebrale parese

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