Kooperativer Bibliotheksverbund

Language: English

In: Journal of Hydrology, October 2015, Vol.529, pp.1754-1767

Description: Soil moisture plays a key role in the water and energy balance in soil, vegetation and atmosphere systems. According to Wood et al. (2011) there is a grand need to increase global-scale hyper-resolution water–energy–biogeochemistry land surface modelling capabilities. These modelling capabilities should also recognize epistemic uncertainties, as well as the nonlinearity and hysteresis in its dynamics. Unfortunately, it is not clear how to parameterize hydrological processes as a function of scale, and how to test deterministic models with regard to epistemic uncertainties. In this study, high resolution long-term simulations were conducted in the highly instrumented TERENO hydrological observatory of the Wüstebach catchment. Soil hydraulic parameters were derived using inverse modelling with the Hydrus-1D model using the global optimization scheme SCE-UA and soil moisture data from a wireless soil moisture sensor network. The estimated parameters were then used for 3D simulations of water transport using the integrated parallel simulation platform ParFlow-CLM. The simulated soil moisture dynamics, as well as evapotranspiration (ET) and runoff, were compared with long-term field observations to illustrate how well the model was able to reproduce the water budget dynamics. We investigated different anisotropies of hydraulic conductivity to analyze how fast lateral flow processes above the underlying bedrock affect the simulation results. For a detail investigation of the model results we applied the empirical orthogonal function (EOF) and wavelet coherence methods. The EOF analysis of temporal–spatial patterns of simulated and observed soil moisture revealed that introduction of heterogeneity in the soil porosity effectively improves estimates of soil moisture patterns. Our wavelet coherence analysis indicates that wet and dry seasons have significant effect on temporal correlation between observed and simulated soil moisture and ET. Our study demonstrates the usefulness of the EOF and wavelet coherence methods for a more in-depth validation of spatially highly resolved hydrological 3D models.

Keywords: 3d Hydrological Simulation ; Soil Moisture ; Eof Analysis ; Wavelet Coherence Analysis ; Geography

ISSN: 0022-1694

E-ISSN: 1879-2707

DOI: 10.1016/j.jhydrol.2015.08.011

URL: View record in ScienceDirect (Access to full text may be restricted)

Language: English

In: Journal of Hydrology, May 2016, Vol.536, pp.365-375

Description: In distributed hydrological modelling one often faces the problem that input data need to be aggregated to match the model resolution. However, aggregated data may be too coarse for the parametrization of the processes represented. This dilemma can be circumvented by the adjustment of certain model parameters. For instance, the reduction of local hydraulic gradients due to spatial aggregation can be partially compensated by increasing soil hydraulic conductivity. In this study, we employed the information entropy concept for the scale dependent parameterization of soil hydraulic conductivity. The loss of information content of terrain curvature as consequence of spatial aggregation was used to determine an amplification factor for soil hydraulic conductivity to compensate the resulting retardation of water flow. To test the usefulness of this approach, continuous 3D hydrological simulations were conducted with different spatial resolutions in the highly instrumented Wüstebach catchment, Germany. Our results indicated that the introduction of an amplification factor can effectively improve model performances both in terms of soil moisture and runoff simulation. However, comparing simulated soil moisture pattern with observation indicated that uniform application of an amplification factor can lead to local overcorrection of soil hydraulic conductivity. This problem could be circumvented by applying the amplification factor only to model grid cells that suffer from high information loss. To this end, we tested two schemes to define appropriate location-specific correction factors. Both schemes led to improved model performance both in terms of soil water content and runoff simulation. Thus, we anticipate that our proposed scaling approach is useful for the application of next-generation hyper-resolution global land surface models.

Keywords: Scale Dependent Parameterization ; 3d Hydrological Modelling ; Topographical Information Content ; Soil Hydraulic Conductivity ; Geography

ISSN: 0022-1694

E-ISSN: 1879-2707

DOI: 10.1016/j.jhydrol.2016.03.020

URL: View record in ScienceDirect (Access to full text may be restricted)

Language: English

In: Environmental Earth Sciences, April, 2014, Vol.71(7), p.3025(13)

Description: Byline: Zhufeng Fang (1), Zhangshuan Hou (1), Guang Lin (2), Dave Engel (2), Yilin Fang (1), Paul Eslinger (1) Keywords: Carbon sequestration; Inversion; Monitoring network; Reservoir characterization Abstract: This study examined the impacts of reservoir properties on carbon dioxide (CO.sub.2) migration after subsurface injection and evaluated the possibility of characterizing reservoir properties using CO.sub.2 monitoring data such as spatial--temporal distributions of gas pressure, which can be reasonably monitored in practice. The injection reservoir was assumed to be located 1,400--1,500 m below the ground surface such that CO.sub.2 remained in the supercritical state. The reservoir was assumed to contain layers with alternating conductive and resistive properties, which is analogous to actual geological formations such as the Mount Simon Sandstone unit. The CO.sub.2 injection simulation used a cylindrical grid setting in which the injection well was situated at the center of the domain, which extended out 8,000 m from the injection well. The CO.sub.2 migration was simulated using the latest version of the simulator, subsurface transport over multiple phases (the water--salt--CO.sub.2--energy module), developed by Pacific Northwest National Laboratory. A nonlinear parameter estimation and optimization modeling software package, Parameter ESTimation (PEST), is adopted for automated reservoir parameter estimation. The effects of data quality, data worth, and data redundancy were explored regarding the detectability of reservoir parameters using gas pressure monitoring data, by comparing PEST inversion results using data with different levels of noises, various numbers of monitoring wells and locations, and different data collection spacing and temporal sampling intervals. This study yielded insight into the use of CO.sub.2 monitoring data for reservoir characterization and how to design the monitoring system to optimize data worth and reduce data redundancy. The feasibility of using CO.sub.2 saturation data for improving reservoir characterization was also discussed. Author Affiliation: (1) Earth Systems Science Division, Pacific Northwest National Laboratory, Post Office Box 999, Richland, WA, 99352, USA (2) Computational Science and Mathematics Division, Pacific Northwest National Laboratory, Post Office Box 999, Richland, WA, 99352, USA Article History: Registration Date: 17/07/2013 Received Date: 22/10/2012 Accepted Date: 17/07/2013 Online Date: 28/07/2013

Keywords: Carbon Dioxide -- Discovery And Exploration ; Carbon Dioxide -- Analysis ; Greenhouse Effect -- Analysis ; Injection Wells -- Discovery And Exploration ; Injection Wells -- Analysis

ISSN: 1866-6280

Source: Cengage Learning, Inc.

Language: English

In: Journal of Hydrology, February 2016, Vol.533, pp.234-249

Description: The objective of this study is to inter-compare three spatially distributed hydrological models (HydroGeoSphere, MIKE SHE and ParFlow-CLM) by means of their ability to simulate soil moisture patterns. This study pools the catchment modeling efforts which have been undertaken at the Wüstebach catchment; one of TERENO’s hydrological observatories. The catchment is densely instrumented with a wireless sensor network (SoilNET) which allows continuous measurements of the spatio-temporal soil moisture dynamics. This unique dataset is ideal to benchmark hydrological models as it poses distinct challenges like seasonality and spatial heterogeneity. Two scenarios of soil parametrization assess the modeling implications of moving from homogeneous to heterogeneous porosity. The three given models perform well in terms of discharge and accumulated water balance components. However, their ability to predict soil moisture is found to be more diverging. Interpretations are ambiguous and depend on what performance metric and what level of spatial aggregation is chosen. In comparison to the other models, ParFlow-CLM performs more accurate at predicting the temporal dynamics and the heterogeneity aggregated to catchment scale. Nevertheless, at local scale HydroGeoSphere and MIKE SHE provide more detailed soil moisture predictions. Overall, a clear increase in performance can be attested to the scenario that includes heterogeneous porosity. Next to soil parametrization, topography is among the main drivers of soil moisture variability which was found to have an overemphasized feedback in ParFlow-CLM compared to the other models. This study stresses that further efforts toward spatially distributed input data need to emerge alongside a more suitable soil parametrization that can account for the observed heterogeneity and seasonality of soil moisture.

Keywords: Distributed Hydrological Modeling ; Model Inter-Comparison ; Soil Moisture ; Spatial Patterns ; Soil Parametrization ; Spatial Model Evaluation ; Geography

ISSN: 0022-1694

E-ISSN: 1879-2707

DOI: 10.1016/j.jhydrol.2015.12.002

URL: View record in ScienceDirect (Access to full text may be restricted)

Language: English

In: Mathematical Geosciences, 2013, Vol.45(7), pp.799-817

Description: A new uncertainty quantification framework is adopted for carbon sequestration to evaluate the effect of spatial heterogeneity of reservoir permeability on CO 2 migration. Sequential Gaussian simulation is used to generate multiple realizations of permeability fields with various spatial statistical attributes. In order to deal with the computational difficulties, the following ideas/approaches are integrated. First, different efficient sampling approaches (probabilistic collocation, quasi-Monte Carlo, and adaptive sampling) are used to reduce the number of forward calculations, explore effectively the parameter space, and quantify the input uncertainty. Second, a scalable numerical simulator, extreme-scale Subsurface Transport Over Multiple Phases, is adopted as the forward modeling simulator for CO 2 migration. The framework has the capability to quantify input uncertainty, generate exploratory samples effectively, perform scalable numerical simulations, visualize output uncertainty, and evaluate input-output relationships. The framework is demonstrated with a given CO 2 injection scenario in heterogeneous sandstone reservoirs. Results show that geostatistical parameters for permeability have different impacts on CO 2 plume radius: the mean parameter has positive effects at the top layers, but affects the bottom layers negatively. The variance generally has a positive effect on the plume radius at all layers, particularly at middle layers, where the transport of CO 2 is highly influenced by the subsurface heterogeneity structure. The anisotropy ratio has weak impacts on the plume radius, but affects the shape of the CO 2 plume.

Keywords: Uncertainty quantification ; Efficient sampling ; Reservoir heterogeneity ; Carbon sequestration

ISSN: 1874-8961

E-ISSN: 1874-8953

DOI: 10.1007/s11004-013-9459-0

URL: View full text in Springer (Subscribers only)

Language: English

In: Environmental Earth Sciences, 2014, Vol.71(7), pp.3025-3037

Description: This study examined the impacts of reservoir properties on carbon dioxide (CO 2 ) migration after subsurface injection and evaluated the possibility of characterizing reservoir properties using CO 2 monitoring data such as spatial–temporal distributions of gas pressure, which can be reasonably monitored in practice. The injection reservoir was assumed to be located 1,400–1,500 m below the ground surface such that CO 2 remained in the supercritical state. The reservoir was assumed to contain layers with alternating conductive and resistive properties, which is analogous to actual geological formations such as the Mount Simon Sandstone unit. The CO 2 injection simulation used a cylindrical grid setting in which the injection well was situated at the center of the domain, which extended out 8,000 m from the injection well. The CO 2 migration was simulated using the latest version of the simulator, subsurface transport over multiple phases (the water–salt–CO 2 –energy module), developed by Pacific Northwest National Laboratory. A nonlinear parameter estimation and optimization modeling software package, Parameter ESTimation (PEST), is adopted for automated reservoir parameter estimation. The effects of data quality, data worth, and data redundancy were explored regarding the detectability of reservoir parameters using gas pressure monitoring data, by comparing PEST inversion results using data with different levels of noises, various numbers of monitoring wells and locations, and different data collection spacing and temporal sampling intervals. This study yielded insight into the use of CO 2 monitoring data for reservoir characterization and how to design the monitoring system to optimize data worth and reduce data redundancy. The feasibility of using CO 2 saturation data for improving reservoir characterization was also discussed.

Keywords: Carbon sequestration ; Inversion ; Monitoring network ; Reservoir characterization

ISSN: 1866-6280

E-ISSN: 1866-6299

DOI: 10.1007/s12665-013-2680-9

URL: View full text in Springer (Subscribers only)

Language: English

In: Journal of Hydrology, March 2019, Vol.570, pp.726-738

Description: Snowmelt is the principal control on the timing and magnitude of water flow through mountainous watersheds. The effects of precipitation type and quantity on storage and hydrologic connectivity in mountainous systems were explored by combining the observed stable isotope δ in rain, snow, snowmelt, and streamflow with numerically simulated hydrologic boundary fluxes and inverse techniques applied to transient travel time distributions (TTD) using StorAge Selection (SAS) functions. Hydrologic simulations of the East River (ER, 85 km ), a snow-dominated Colorado River headwater basin, for water years 2006–2017 were used to test a diverse set of snow accumulation scenarios. During the snowmelt period, the ER released younger water during high storage periods across seasonal and annual timescales (an “inverse storage effect”). Additionally, more young water was released from storage during wet years than during dry years. However, wet years also appeared to increase hydrologic connectivity, which simultaneously flushed older water from the basin. During years with reduced snowpack, flow paths were inactivated and snowmelt remained in the subsurface to become older water that was potentially reactivated in subsequent wet years. Incremental warming in hydrologic model simulations was used to evaluate TTD sensitivity to precipitation changing from snow to rain. Despite the altered timing of boundary fluxes because of warming, years with basin average precipitation above 3.25 mm d (1200 mm y ) were resilient to temperature increases up to 10 °C with respect to annual water balance partitioning and streamflow TTD. In contrast, years with less precipitation were sensitive to increased temperatures, showing marked increases in the fraction of inflow lost to evapotranspiration. Younger water was preferentially lost to evapotranspiration, which led to an increase in the mean age of streamflow in drier years.

Keywords: East River ; Snowmelt ; Travel Time Distributions ; Hydrologic Model ; Warming Climate ; Geography

ISSN: 0022-1694

E-ISSN: 1879-2707

DOI: 10.1016/j.jhydrol.2019.01.029

URL: View record in ScienceDirect (Access to full text may be restricted)

Language: English

In: International Journal of Greenhouse Gas Control, August 2014, Vol.27, pp.69-80

Description: This study focused on CO plume expansion subsequent to wellbore CO leakage into a shallow unconfined aquifer post-CO injection. The target response variables included CO plume size, as well as flux to the atmosphere. Many processes contribute to CO plume expansion in the aquifer; here we considered process and model parameters including those affecting the abandoned well leak rate, aquifer hydraulic properties, and aquifer geochemistry. In order to identify the significant factors affecting leakage, we adopted an uncertainty quantification framework to quantify input uncertainty, generate exploratory samples effectively, perform scalable numerical simulations, visualize output uncertainty, and evaluate input–output relationships. We combined quasi-Monte Carlo and adaptive sampling approaches to reduce the number of forward calculations while fully exploring the input parameter space and quantifying the output uncertainty. The CO migration was simulated with STOMP-CO2 (water–salt–CO module). Response surfaces of model outputs were built with respect to input parameters to determine the individual and combined effects. Four most significant parameters were identified to be dominating the CO plume expansion process subsequent to wellbore CO leakage: distance between the leaky and injection wells, maximum leakage rate, porosity, and hydraulic conductivity.

Keywords: Carbon Sequestration ; Uncertainty Quantification ; Wellbore Leakage ; Response Surface ; Adaptive Sampling ; Engineering

ISSN: 1750-5836

E-ISSN: 1878-0148

DOI: 10.1016/j.ijggc.2014.05.004

URL: View record in ScienceDirect (Access to full text may be restricted)

Language: English

In: Journal of Hydrometeorology, 14:1754–1772, 01 December 2013

Description: With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.

Keywords: Uncertainty ; Analysis ; Runoff ; Simulations ; Parameter ; Identifiability ; Community ; Land ; Model ; Evidence ; Mopex ; Basins

ISSN: 1525755X

E-ISSN: 15257541

DOI: 10.1175/JHM-D-12-0138.1

URL: View record in SciTech Connect

In: 中国实用眼科杂志 - Chinese Journal of Practical Ophthalmology, 2015, Vol.33(08), pp.930-932

Description: 目的采用多层螺旋CT（MSCT）研究眼眶滑车的解剖特点及临床意义。方法对2012年11月至2013年8月在奉化市人民医院眼科就诊的413例眼眶滑车根据有无钙化分组进行观察，127例行MPR与VR。结果滑车均双侧对称，位置固定，附着于眶内侧壁前上方，与上斜肌反折肌腱连成一体。无钙化组325例，呈软组织密度；钙化组88例，占21.31％（88／413），单侧钙化39例，双侧49例，双侧钙化大小形状可不一致。结论MSCT显示眼眶滑车的解剖特点极具特征，对滑车钙化的鉴别诊断具有重要的临床意义。

Description: Objective To observe the anatomical characteristics and clinical significance of orbital trochlea using multi-slice spiral CT （MSCT）. Methods In this research, 413 patients with MST CT routine inspection were divided into two groups according to the presence...

Keywords: 眼眶滑车 ; 钙化 ; 体层摄影术 ; X线计算机 ; Orbital Trochlea; Calcification; Tomography, X-Ray Computed

ISSN: 1006-4443

Source: 维普数据 (Chongqing VIP Information Co.)