Bulk density effects on soil hydrologic and thermal characteristics: A numerical investigation

Soil bulk density (ρ_b) is commonly treated as static in studies of land surface dynamics. Magnitudes of errors associated with this assumption are largely unknown. Our objectives were to (a) quantify ρ_b effects on soil hydrologic and thermal properties and (b) evaluate effects of ρ_b on surface energy balance and heat and water transfer. We evaluated 6 soil properties, volumetric heat capacity, thermal conductivity, soil thermal diffusivity, water retention characteristics, hydraulic conductivity, and vapour diffusivity, over a range of ρ_b, using a combination of 6 models. Thermal conductivity, water retention, hydraulic conductivity, and vapour diffusivity were most sensitive to ρ_b, each changing by fractions greater than the associated fractional changes in ρ_b. A 10% change in ρ_b led to 10–11% change in thermal conductivity, 6–11% change in saturated and residual water content, 49–54% change in saturated hydraulic conductivity, and 80% change in vapour diffusivity. Subsequently, 3 field seasons were simulated with a numerical model (HYDRUS‐1D) for a range of ρ_b values. When ρ_b increased 25% (from 1.2 to 1.5 Mg m^?3), soil temperature variation decreased by 2.1 °C in shallow layers and increased by 1 °C in subsurface layers. Surface water content differed by 0.02 m³ m^?3 for various ρ_b values during drying events but differences mostly disappeared in the subsurface. Matric potential varied by >100 m of water. Surface energy balance showed clear trends with ρ_b. Latent heat flux decreased 6%, sensible heat flux increased 9%, and magnitude of ground heat flux varied by 18% (with a 25% ρ_b increase). Transient ρ_b impacted surface conditions and fluxes, and clearly, it warrants consideration in field and modelling investigations.     

Linking hydrologic signatures to hydrologic processes: A review

Hydrologic signatures are metrics that quantify aspects of streamflow response. Linking signatures to underlying processes enables multiple applications, such as selecting hydrologic model structure, analysing hydrologic change, making predictions in ungauged basins, and classifying watershed function. However, many lists of hydrologic signatures are not process-based, and knowledge about signature-process links has been scattered among studies from experimental watersheds and model selection experiments. This review brings together those studies to catalogue more than 50 signatures representing evapotranspiration, snow storage and melt, permafrost, infiltration excess, saturation excess, groundwater, baseflow, connectivity, channel processes, partitioning, and human alteration. The review shows substantial variability in the number, type, and timescale of signatures available to represent each process. Many signatures provide information about groundwater storage, partitioning, and connectivity, whereas snow processes and human alteration are underrepresented. More signatures are related to the seasonal scale than the event timescale, and land surface processes (ET, snow, and overland flow) have no signatures at the event scale. There are limitations in some signatures that test for occurrence but cannot quantify processes, or are related to multiple processes, making automated analysis more difficult. This review will be valuable as a reference for hydrologists seeking to use streamflow records to investigate a particular hydrologic process or to conduct large-sample analyses of patterns in hydrologic processes.     

The role of sensitivity analysis in hydrologic modeling

Sensitivity is a measure of the effect of change in one factor on another factor. Sensitivity analysis is potentially useful in all phases of the modeling process: model formulation, model calibration and model verification. The sensitivity of model parameters should be recognized as a special case of the above general definition. Parametric sensitivity is a vital part of most optimization techniques. However, other facets of sensitivity need to be recognized. The time-dependent nature of sensitivity should be considered in the formulation of hydrologic models. A variety of simplified hydrologic models are used to demonstrate the potential of sensitivity in all phases of the modeling process. The failure to recognize and exploit the potential of sensitivity analysis results primarily from the inadequacy of the mathematical foundations of sensitivity. A comprehensive mathematical framework of sensitivity is provided and additional research needs are identified.     

多震源地震正演数值模拟技术

常规地震采集技术因受相邻时间激发炮之间时间间隔的制约而存在采集周期过长,采集成本过高的问题,而多震源同步激发地震采集技术可以克服这方面的缺陷,但存在着波场过于复杂的问题,地震正演模拟技术可以帮助我们提高对这种复杂波场的认识水平,为此采用2D弹性波方程交错网格高阶有限差分格式,开发了多震源同步激发波场正演数值模拟技术,能够模拟任意多个同步激发震源的弹性波波场,震源函数可以是雷克子波,也可以是可控震源扫描信号,且同步激发震源之间可以有随机时差.模型试算结果分析表明,该技术既是一项高精度的多震源正演模拟技术,也是一项高效率的地震正演数值模拟技术.     

The significance of surface complexation reactions in hydrologic systems: a geochemist's perspective

Complexation reactions at the mineral–water interface affect the transport and transformation of metals and organic contaminants, nutrient availability in soils, formation of ore deposits, acidification of watersheds and the global cycling of elements. Such reactions can be understood by quantifying speciation reactions in homogeneous aqueous solutions, characterizing reactive sites at mineral surfaces and developing models of the interactions between aqueous species at solid surfaces. In this paper, the application of thermodynamic principles to quantify aqueous complexation reactions is described. This is followed by a brief overview of a few of the methods that have been used to characterize reactive sites on mineral surfaces. Next, the application of empirical and semi-empirical models of adsorption at the mineral–water interface, including distribution coefficients, simple ion exchange models, and Langmuir and Freundlich isotherms is discussed. Emphasis is placed on the limitations of such models in providing an adequate representation of adsorption in hydrological systems. These limitations arise because isotherms do not account for the structure of adsorbed species, nor do they account for the development of surface charge with adsorption. This is contrasted with more sophisticated models of adsorption, termed ‘surface complexation models’, which include the constant capacitance model, the diffuse layer model, the triple layer model and the MUSIC model. In these models, speciation reactions between surface functional groups and dissolved species control the variable surface charge build-up and the specific adsorption properties of minerals in aqueous solutions. Next, the influence of mineral surface speciation on the reactivity of adsorbed species and on far from equilibrium dissolution rates of minerals is discussed. Finally, the applicability of microscopic models of surface complexation to field-scale systems is explored and the need to integrate sophisticated surface chemical and hydrological modeling approaches is stressed.     

Spatial interpolation schemes of daily precipitation for hydrologic modeling

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.     

A terrain-following grid transform and preconditioner for parallel,large-scale,integrated hydrologic modeling

A terrain-following grid formulation (TFG) is presented for simulation of coupled variably-saturated subsurface and surface water flow. The TFG is introduced into the integrated hydrologic model, ParFlow, which uses an implicit, Newton Krylov solution technique. The analytical Jacobian is also formulated and presented and both the diagonal and non-symmetric terms are used to precondition the Krylov linear system. The new formulation is verified against an orthogonal stencil and is shown to provide increased accuracy at lower lateral spatial discretization for hillslope simulations. Using TFG, efficient scaling to a large number of processors (16,384) and a large domain size (8.1 Billion unknowns) is shown. This demonstrates the applicability of this formulation to high-resolution, large-spatial extent hydrology applications where topographic effects are important. Furthermore, cases where the analytical Jacobian is used for the Newton iteration and as a non-symmetric preconditioner for the linear system are shown to have faster computation times and better scaling. This demonstrates the importance of solver efficiency in parallel scaling through the use of an appropriate preconditioner.     

Characteristics of concentrated flow hydraulics for rangeland ecosystems: implications for hydrologic modeling

Concentrated flow is often the dominant source of water erosion following disturbance on rangelands. Because of the lack of studies that explain the hydraulics of concentrated flow on rangelands, cropland‐based equations have typically been used for rangeland hydrology and erosion modeling, leading to less accurate predictions due to different soil and vegetation cover characteristics. This study investigates the hydraulics of concentrated flow using unconfined field experimental data over diverse rangeland landscapes within the Great Basin Region, United States. The results imply that the overall hydraulics of concentrated flow on rangelands differ significantly from those of cropland rills. Concentrated flow hydraulics on rangelands are largely controlled by the amount of cover or bare soil and hillslope angle. New predictive equations for concentrated flow velocity (R² = 0·47), hydraulic friction (R² = 0·52), and width (R² = 0·4) representing a diverse set of rangeland environments were developed. The resulting equations are applicable across a wide span of ecological sites, soils, slopes, and vegetation and ground cover conditions and can be used by physically‐based rangeland hydrology and erosion models to estimate rangeland concentrated flow hydraulic parameters. Published in 2011. This article is a US Government work and is in the public domain in the USA.     

A perspective on numerical analysis of the diffusion equation

The equation of transient groundwater motion is founded on the principle of mass conservation and can be mathematically described by the diffusion equation. Recently, powerful integral formulations have been developed for numerically solving the diffusion equation under complex conditions. In the literature, it is customary to formulate the integral equations by integrating point differential equations. Instead, in this paper, we shall employ a direct method of formulation, starting from the concepts of set and measure, the notion of partitions and the definition of set-averages.When the direct approach is applied to formulate the well-known finite element (FEM) equations, it is seen that the ‘Galerkin’ weighting function, which is mathematically treated as an artifice for weighting residuals, is but an appropriate spatial partition function. The logical framework of the direct approach is then applied to study the properties of ‘lumped’ and ‘consistent’ matrices arising in the use of the FEM. The lumped matrix, stemming naturally from the direct approach, seeks to conserve mass locally as well as globally, while the consistent matrix, which results only when the differential equation is integrated in a specific fashion, attempts only to preserve global mass balance.It is concluded that the direct approach is simple and complete and, in so far as the integral formulation is concerned, there is little to be gained in starting with the differential equation. Further, in formulating integral equations, it is common practice to evaluate only the time-dependent changes in the mass content of the system and ignore the evaluation of the mass content of the system at any given instant of time. In order to be complete in itself, a true integral approach should evaluate both the time-dependent changes in the mass content of the system as well as the instantaneous mass content at any given time.     

Increasingly important role of numerical modeling in oceanic observation design strategy: A review

Science China Earth Sciences - Oceanic observation design is of considerable significance and has made remarkable progress during the past several decades. This study addresses the critical role of...     

Use of the Beta-Dagum and Beta-Singh-Maddala distributions for modeling hydrologic data

Starting from a recent paper by Murshed (Stoch Environ Res Risk Assess 25:897–911, 2011) in which a good performance of the Beta-k distribution in analyzing extreme hydrologic events is shown, in this paper, we propose the use of two new four-parameters distribution functions strongly related to the Beta-k distribution, namely the Beta-Dagum and the Beta-Singh-Maddala distributions. More in detail, the new distributions are a generalization of a reparametrization of Beta-k and Beta-p distributions, respectively. For these distributions some particular interpretations in terms of maximum and minimum of sequences of random variables can be derived and the maximal and minimal domain of attraction can be obtained. Moreover, the method of maximum likelihood, the method of moments and the method of L-moments are examined to estimate the parameters. Finally, two different applications on real data regarding maxima and minima of river flows are reported, in order to show the potentiality of these two models in the extreme events analysis.     

上地幔俯冲板块的动力学过程:数值模拟

大洋板块俯冲到地幔转换带,进而可形成不同的形态：板块可以停滞在660 km不连续面,抑或穿过地幔转换带进入下地幔.这些不同的俯冲模式可进一步影响到海沟的运动.为更好地理解上地幔中俯冲板片的变形行为以及俯冲过程与海沟运动之间的关系,本文通过建立一系列高精度二维热-力学自由俯冲的数值模型,揭示了俯冲板块在上地幔中的变形方式及其与地幔转换带之间的相互作用过程.模拟结果显示,在俯冲板块与地幔转换带的相互作用过程中,其动力学过程可以分为以海沟后撤主导、海沟前进主导以及稳定型海沟等三种主要动力学类型.对于年龄较老,厚度较大的俯冲板块容易形成海沟后撤型俯冲,俯冲板块停滞在660 km不连续面.相反,年龄较小,塑性强度较小的板块容易形成海沟前进型俯冲,俯冲板块穿越660 km不连续面.

     

Evolutionary assimilation of streamflow in distributed hydrologic modeling using in-situ soil moisture data

This study has applied evolutionary algorithm to address the data assimilation problem in a distributed hydrological model. The evolutionary data assimilation (EDA) method uses multi-objective evolutionary strategy to continuously evolve ensemble of model states and parameter sets where it adaptively determines the model error and the penalty function for different assimilation time steps. The assimilation was determined by applying the penalty function to merge background information (i.e., model forecast) with perturbed observation data. The assimilation was based on updated estimates of the model state and its parameterizations, and was complemented by a continuous evolution of competitive solutions.The EDA was illustrated in an integrated assimilation approach to estimate model state using soil moisture, which in turn was incorporated into the soil and water assessment tool (SWAT) to assimilate streamflow. Soil moisture was independently assimilated to allow estimation of its model error, where the estimated model state was integrated into SWAT to determine background streamflow information before they are merged with perturbed observation data. Application of the EDA in Spencer Creek watershed in southern Ontario, Canada generates a time series of soil moisture and streamflow. Evaluation of soil moisture and streamflow assimilation results demonstrates the capability of the EDA to simultaneously estimate model state and parameterizations for real-time forecasting operations. The results show improvement in both streamflow and soil moisture estimates when compared to open-loop simulation, and a close matching between the background and the assimilation illustrates the forecasting performance of the EDA approach.     

Multisource hydrologic modeling uncertainty analysis using the IBUNE framework in a humid catchment

Hydrologic cycle is a complex system associated with both certain and uncertain constituents. The propagation of confidence bounds from different uncertainty sources to model output is of great significance for hydrologic modeling. In this paper, we applied the integrated bayesian uncertainty estimator to quantify the effects of parameter, input and model structure uncertainty on hydrologic modeling progressively. Two hydrologic models (Xinanjiang model and TOPMODEL) were applied to a humid catchment under three scenarios. Case I: the shuffled complex evolution metropolis (SCEM-UA) algorithm was conducted to determine the posterior parameter distribution of hydrologic models and analyze the corresponding forecast uncertainty. Case II: input uncertainty was also considered by assuming rain depth bias follows a normal distribution, and integrated with SCEM-UA. Case III: Simulations from two models were combined by the Bayesian model averaging to fully quantify multisource uncertainty effects. Results suggested that, from Case I to II, the containing ratio (percentage of observed streamflow enveloped by 95% confidence interval) obviously increased by an average magnitude of 10% for the study period 2000–2006. Besides, it also found that the width of 95% confidence interval became wider and narrower for Xinanjiang model and TOPMODEL, respectively, from Case I to II. This may indicate that the uncertainty of TOPMODEL results was more remarkable than Xinanjiang model in Case I. By combining results from two models, model structure uncertainty was also considered in Case III. The accuracy of uncertainty bounds further improved with the containing ratio of 95% confidence interval >95%. In addition, the optimized deterministic results from the uncertainty analysis showed that the average Nash–Sutcliffe coefficient increased continually from Case I to II and III (0.82, 0.84 and 0.90, respectively) for the study period. The analysis demonstrated the improvement of modeling accuracy when extra uncertainty sources were also quantified, and this finding also proved the applicability of IBUNE framework in hydrologic modeling.     

Progress in the numerical modeling of mantle plumes

The mantle plume model, as an integral part of the Earth’s internal convection system, is complementary to the theory of plate tectonics. They together constitute the key configuration of material circulation and energy transport in the Earth’s interior. Seismology, high-temperature and high-pressure mineralogy, geology, and geodynamic numerical modeling have conducted comprehensive studies on the mantle plume model since it was proposed. In particular, numerical simulation, which investigates t...     

Progress in numerical modeling of subducting plate dynamics

The core concerns of plate tectonics theory are the dynamics of subducting plates, which can be studied by integrating multidisciplinary fields such as seismology, mineral physics, rock geochemistry, geological formation studies, sedimentology, and numerical simulations. By establishing a theoretical model and solving it with numerical methods, one can replicate the dynamic effects of a subducting plate, quantifying its evolution and the surface response. Simulations can also explain the observations and experimental results of other disciplines. Therefore, numerical models are among the most important tools for studying the dynamics of subducting plates. This paper provides a review on recent advances in the numerical modeling of subducting plate dynamics. It covers various aspects, namely, the origin of plate tectonics, the initiation process and thermal structure of subducting slab, and the main subduction slab dynamics in the upper mantle, mantle transition zone, and lower mantle. The results of numerical models are based on the theoretical equations of mass, momentum, and energy conservation. To better understand the dynamic progress of subducting plates, the simulation results must be verified in comparisons with the results from natural observations by geology, geophysics and geochemistry. With the substantial increase in computing power and continuous improvement of simulation methods, numerical models will become a more accurate and efficient means of studying the frontier issues of Earth sciences, including subducting plate dynamics.     

Wetland buffers: numerical modeling of wave dissipation by vegetation

The resiliency of coastal communities is imperative because these areas experience risk of damage from coastal storms as well as increasing population pressures and development. The severity of this hazard is compounded by sea level rise and a potential increase in storm intensities due to climate change. The ability of coastal communities to plan for, resist, and quickly and completely recover from severe coastal storm events and flooding is of critical importance. There is a growing interest in applying complementary and redundant approaches to reduce the flood risk of these vulnerable communities, such as incorporating natural and nature‐based features into the project planning process. However, accounting for the benefits of these nature‐based features in coastal design is still challenging. One of the natural features generally acknowledged to offer coastal protection benefits is wetlands. Using laboratory experiments of artificial vegetation as a foundation, the bounds of wave dissipation by vegetation are explored analytically and the effectiveness of wave dissipation by vegetation over large scales is investigated using the spectral wave model STWAVE. Wave heights modeled using a vegetation dissipation formulation are compared to those modeled with the current practice of representing vegetation using bottom friction, particularly the Manning formulation. The vegetation dissipation formulation reduced more wave energy than the Manning bottom friction formulation for submerged wetlands. Because the Manning formulation does not integrate vegetation properties, to achieve consistent results would require varying the Manning n coefficient to account for the spatial and temporal variation in form drag induced by the plants due to changes in plant density, diameter, and degree of plant submergence. Thus, a re‐evaluation of existing methods for assessing wave dissipation by vegetation is recommended for wider application of vegetation dissipation formulations in numerical models. Such models are critical for evaluating coastal resiliency of communities protected by wetland features. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.     

Dynamics of unstable continental subduction: Insights from numerical modeling

Numerical experiments are used in this study to systematically investigate the effects of convergence rate, crustal rheological strength, and lithospheric thermal structure on the dynamics of continental collision. The study focuses on the types, conditions and processes of unstable continental subduction. Modelling results suggest that the development of unstable continental subduction can be promoted by conditions that tend to decrease rheological strength of the lithosphere, such as low crustal rheological strength, “hot” thermal structure of the lithosphere, or low convergence rate. Unstable subduction mode can be further categorized into three types: (1) multi-stage slab breakoff, (2) continuously “flowing” of fluid-like slab into the upper mantle, and (3) large-scale detachment of the thickened orogenic root. These three types of unstable continental subduction are respectively associated with (1) a low convergence rate, (2) “hot” thermal structure of the lithosphere with a high convergence rate, and (3) moderate-high crustal rheological strength with a low convergence rate. It is also revealed that the evolution of crustal melting is dominated by the deformation pattern of continental collision, which is mainly controlled by crustal rheological strength. The modelling results have important implications for understanding of continental subduction mode selection under specific geodynamic conditions.     

Using maximum likelihood to derive various distance-based goodness-of-fit indicators for hydrologic modeling assessment

Currently used goodness-of-fit (GOF) indicators (i.e. efficiency criteria) are largely empirical and different GOF indicators emphasize different aspects of model performance; a thorough assessment of model skill may require the use of robust skill matrices. In this study, based on the maximum likelihood method, a statistical measure termed BC-GED error model is proposed, which firstly uses the Box–Cox (BC) transformation method to remove the heteroscedasticity of model residuals, and then employs the generalized error distribution (GED) with zero-mean to fit the distribution of model residuals after BC transformation. Various distance-based GOF indicators can be explicitly expressed by the BC-GED error model for different values of the BC transformation parameter λ and GED kurtosis coefficient β. Our study proves that (1) the shape of error distribution implied in the GOF indicators affects the model performance on high or low flow discharges because large error-power (β) value can cause low probability of large residuals and small β value will lead to high probability of zero value; (2) the mean absolute error could balance consideration of low and high flow value as its assumed error distribution (i.e. Laplace distribution, where β = 1) is the turning point of GED derivative at zero value. The results of a study performed in the Baocun watershed via comparison of the SWAT model-calibration results using six distance-based GOF indicators show that even though the formal BC-GED is theoretically reasonable, the calibrated model parameters do not always correspond to high performance of model-simulation results because of imperfection of the hydrologic model. However, the derived distance-based GOF indicators using the maximum likelihood method offer an easy way of choosing GOF indicators for different study purposes and developing multi-objective calibration strategies.     

岩石物理的理论模拟和数值实验新方法

当代物理实验科学和计算机科学技术的巨大进步为岩石物理的理论和实验研究开辟了新的领域.在细胞自动机基础上发展起来的格子气自动机和格子玻尔滋曼方法就是这种技术进步的产物.本文讨论了格子气自动机的发展及其应用于研究多孔岩石微观孔隙结构对宏观导电特性影响的新方法. 我们开发的模拟多孔岩石导电特性的数值实验新方法，提供了一种可深入到从微观孔隙结构这个尺度上来考察具有复杂孔隙结构的，孔隙度小于10%的低孔、低渗岩石的宏观导电特性及其影响因素.研究表明:Archie 系数m,n并不是传统上的意义，研究各种不同条件下F-、I-Sw关系，结果显示非阿尔奇现象与孔隙介质中孔隙、骨架和流体的混合导电网络有关，得出新的饱和度计算公式.同时还研究了泥质含量和分布、电阻率各向异性对宏观导电特性的影响，提出适用于电阻率各向异性地层的F-、I-Sw的关系.本文最后探讨了应用格子气自动机和格子玻尔滋曼方法进行岩心渗流和核磁共振数值实验的新方法及其发展前景.