292 research outputs found
Reply to comment by H. Lough, Department of Civil Engineering, University of Canterbury, Christchurch, New Zealand, on the paper “Stream depletion predictions using pumping test data from a heterogeneous stream–aquifer system (a case study from the Great Plains, USA)”
1. General remark
2. The study by Kollet and Zlotnik (2003)
3. Remark on the explanation of the drawdown behavior
4. Remark on the re-analysis of the data from piezometer C2d
5. Summar
Causal deep learning models for studying the Earth system
Earth is a complex non-linear dynamical system. Despite decades of research and considerable scientific and methodological progress, many processes and relations between Earth system variables remain poorly understood. Current approaches for studying relations in the Earth system rely either on numerical simulations or statistical approaches. However, there are several inherent limitations to existing approaches, including high computational costs, uncertainties in numerical models, strong assumptions about linearity or locality, and the fallacy of correlation and causality. Here, we propose a novel methodology combining deep learning (DL) and principles of causality research in an attempt to overcome these limitations. On the one hand, we employ the recent idea of training and analyzing DL models to gain new scientific insights into relations between input and target variables. On the other hand, we use the fact that a statistical model learns the causal effect of an input variable on a target variable if suitable additional input variables are included. As an illustrative example, we apply the methodology to study soil-moisture–precipitation coupling in ERA5 climate reanalysis data across Europe. We demonstrate that, harnessing the great power and flexibility of DL models, the proposed methodology may yield new scientific insights into complex non-linear and non-local coupling mechanisms in the Earth system.</p
The topographic control on land surface energy fluxes:a statistical approach to bias correction in Journal of Hydrology
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Quantifying the effects of three-dimensional subsurface heterogeneity on Hortonian runoff processes using a fully-coupled numerical, stochastic approach.
The impact of three-dimensional subsurface heterogeneity on hillslope runoff generated by excess infiltration (so called Hortonian runoff) is examined. A fully-coupled, parallel subsurface overland flow model is used to simulate runoff from an idealized hillslope. Ensembles of correlated, Gaussian random fields of saturated hydraulic conductivity are used to create uncertainty and variability (i.e. structure) due to subsurface heterogeneity. A large number of cases are simulated in a parametric manner with variance of the hydraulic conductivity varied over two orders of magnitude. These cases include rainfall rates above, equal and below the geometric mean of the hydraulic conductivity distribution. These cases are also compared to theoretical considerations of runoff production based on simple assumptions regarding (1) the rainfall rate and the value of hydraulic conductivity in the surface cell using a spatially-indiscriminant approach; and (2) a percolation-theory type approach to incorporate so-called runon. Simulations to test the ergodicity of hydraulic conductivity on hillslope runoff are also performed. Results show three-dimensional features (particularly in the vertical dimension) in the hydraulic conductivity distributions that create shallow perching, which has an important effect on runoff behavior that is fundamentally different in character than previous two dimensional analyses. The simple theories are shown to be very poor predictors of the saturated area that might runoff due to excess infiltration. It is also shown that ergodicity is reached only for a large number of integral scales ({approx}30) and not for cases where the rainfall rate is less than the geometric mean of the saturated hydraulic conductivity
Implementation and scaling of the fully coupled Terrestrial Systems Modeling Platform (TerrSysMP) in a massively parallel supercomputing environment – a case study on JUQUEEN (IBM Blue Gene/Q)
Continental-scale hyper-resolution simulations constitute a grand challenge in characterizing non-linear feedbacks of states and fluxes of the coupled water, energy, and biogeochemical cycles of terrestrial systems. Tackling this challenge requires advanced coupling and supercomputing technologies for earth system models that are discussed in this study, utilizing the example of the implementation of the newly developed Terrestrial Systems Modeling Platform (TerrSysMP) on JUQUEEN (IBM Blue Gene/Q) of the Jülich Supercomputing Centre, Germany. The applied coupling strategies rely on the Multiple Program Multiple Data (MPMD) paradigm and require memory and load balancing considerations in the exchange of the coupling fields between different component models and allocation of computational resources, respectively. These considerations can be reached with advanced profiling and tracing tools leading to the efficient use of massively parallel computing environments, which is then mainly determined by the parallel performance of individual component models. However, the problem of model I/O and initialization in the peta-scale range requires major attention, because this constitutes a true big data challenge in the perspective of future exa-scale capabilities, which is unsolved
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Modeling Interactions of Surface-Subsurface Flow Using a Free-Surface Overland Flow Boundary Condition in a Parallel Flow Simulator
Models incorporating interactions between surface and subsurface flow are commonly based on the conductance concept that presumes a distinct interface at the land surface, separating the surface from the subsurface domain. In these models the subsurface and surface domains are linked via an exchange flux that depends upon the magnitude and direction of the hydraulic gradient across the interface and a proportionality constant (a measure of the hydraulic connectivity). Because experimental evidence of such a distinct interface is often lacking in the field, a more general coupled modeling approach would be preferable. We present a more general approach that incorporates a two-dimensional overland flow simulator into the parallel three-dimensional variably saturated subsurface flow code ParFlow developed at LLNL. This overland flow simulator takes the form of an upper, free-surface boundary condition and is, thus, fully integrated without relying on the conductance concept. Another advantage of this approach is the efficient parallelism of ParFlow, which is exploited by the overland flow simulator. Several verification and simulation examples are presented that focus on the two main processes of runoff production: excess infiltration and saturation. The usefulness of our approach is demonstrated in an application of the model to an urban watershed. The influence of heterogeneity of the shallow subsurface on overland flow and transport is also examined. The results show the uncertainty in flow and transport predictions due to heterogeneity. This is important in determining, for example, total maximum daily loads of surface water systems
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Demonstrating fractal scaling of residence time distributions on the catchment scale using a fully-coupled, variably-saturated groundwater and land surface model and a Lagrangian particle tracking approach
The influence of the vadose zone, land surface processes, and macrodispersion on scaling behavior of residence time distributions (RTDs) is studied using a fully coupled watershed model in conjunction with a Lagrangian, particle-tracking approach. Numerical experiments are used to simulate groundwater flow paths from recharge locations along the hillslope to the streambed. These experiments are designed to isolate the influences of topography, vadose zone/land surface processes, and macrodispersion on subsurface RTDs of tagged parcels of water. The results of these simulations agree with previous observations that RTDs exhibit fractal behavior, which can be identified from the power spectra. For cases incorporating residence times that are influenced by vadose zone/land surface processes, increasing macrodispersion increases the slope of the power spectra. In general the opposite effect is demonstrated if the vadose zone/land surface processes are neglected. The concept of the spectral slope being a measure of stationarity is raised and discussed
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The groundwater-land-surface-atmosphere connection: soil moisture effects on the atmospheric boundary layer in fully-coupled simulations
This study combines a variably-saturated groundwater flow model and a mesoscale atmospheric model to examine the effects of soil moisture heterogeneity on atmospheric boundary layer processes. This parallel, integrated model can represent spatial variations in land-surface forcing driven by three-dimensional (3D) atmospheric and subsurface components. The development of atmospheric flow is studied in a series of idealized test cases with different initial soil moisture distributions generated by an offline spin-up procedure or interpolated from a coarse-resolution dataset. These test cases are performed with both the fully-coupled model (which includes 3D groundwater flow and surface water routing) and the uncoupled atmospheric model. The effects of the different soil moisture initializations and lateral subsurface and surface water flow are seen in the differences in atmospheric evolution over a 36-hour period. The fully-coupled model maintains a realistic topographically-driven soil moisture distribution, while the uncoupled atmospheric model does not. Furthermore, the coupled model shows spatial and temporal correlations between surface and lower atmospheric variables and water table depth. These correlations are particularly strong during times when the land surface temperatures trigger shifts in wind behavior, such as during early morning surface heating
Haematopoietic stem cell migration to the ischemic damaged kidney is not altered by manipulating the SDF-1/CXCR4-axis
Background. Haematopoietic stem cells (HSC) have been shown to migrate to the ischemic kidney. The factors that regulate the trafficking of HSC to the ischemic damaged kidney are not fully understood. The stromal cell-derived factor-1 (SDF-1)/CXCR4-axis has been identified as the central signalling axis regulating trafficking of HSC to the bone marrow. Therefore, we hypothesized that SDF-1/CXCR4 interactions are implicated in the migration of HSC to the injured kidney
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A dynamically-coupled groundwater, land surface and regional climate model to predict seasonal watershed flow and groundwater response, FINAL LDRD REPORT.
This final report is organized in four sections. Section 1 is the project summary (below), Section 2 is a submitted manuscript that describes the offline, or spinup simulations in detail, Section 3 is also a submitted manuscript that describes the online, or fully-coupled simulations in detail and Section 3, which is report that describes work done via a subcontract with UC Berkeley. The goal of this project was to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, the land surface, and groundwater. The project involved coupling three distinct submodels that are traditionally used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This coupled model lead to (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration and groundwater flow) at the watershed scale over a range of timeframes; (3) a simulation of hydrologic response of a characteristic watershed that will provide insight into the certainty of hydrologic forecasting, dominance and sensitivity of groundwater dynamics on land-surface fluxes; and (4) a more realistic model representation of weather predictions, precipitation and temperature, at the regional scale. Regional climate models are typically used for the simulation of weather, precipitation and temperature behavior over 10-1000 km domains for weather or climate prediction purposes, and are typically driven by boundary conditions derived from global climate models (GCMs), observations or both. The land or ocean surface typically represents a bottom boundary condition of these models, where important mass (water) and energy fluxes are approximated. The viability and influence of these approximations on the predictions is not well understood because of the detail and complexity in land and subsurface processes and the need for computational efficiency. However, theoretical and experimental data suggest that these interactions may have a profound impact upon hydrologic and climatic budgets and weather predictions. Conversely, land-surface and groundwater models are typically applied on smaller domains (< 10 km in scale) to analyze runoff, streamflow, infiltration, evapotranspiration behavior, but are still influenced in many ways by couplings with the atmosphere (as in precipitation and temperature). Atmospheric inputs to these classes of models are typically represented as simplified ''upper'' boundary conditions, derived, in part, from coarse observations, uncoupled simulations, or other idealized simplifications. In this project, we developed a framework to couple these models by developing a new land-surface/subsurface model and coupling it to a regional climate model at the same temporal and spatial scales. We focused the coupling to examine the role of important mass and energy couplings between these models as a means to understand the difference between traditional and detailed approaches to this interconnection. From this understanding of these interconnections, we were able to determine to what extent these connections need to be abstracted or preserved in modeling atmospheric, land-surface and groundwater interactions. We have found a strong connection between groundwater dynamics (i.e. aquifer storage) and energy fluxes at the land surface and in the Atmospheric Boundary Layer (ABL). The following papers outline this connection theoretically, demonstrate it with coupled modeling and propose strategies for better observing it in real settings
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