Field verification of stream-aquifer interactions: Colorado School of Mines survey field, Golden, Colorado

June 1993.Includes bibliographical references (pages 102-105).The nature of stream/aquifer interactions is determined in a field study on a stream at the Colorado School of Mines survey field in Golden, Colorado. The study measured the temporal and spatial variability during the spring and summer of 1992 of hydraulic parameters controlling stream/aquifer interactions at the streambed level of detail. Included is the determination of the shallow hydraulic gradient directly beneath the stream; measurement using established piesometers and an air permeameter; and, characterization of the streambed. The area was monitored during a variety of conditions. A number of conclusions are drawn regarding the nature of stream/aquifer interactions at the site. The duration of groundwater was found to depend on the amount of precipitation in the area. The response of the groundwater system to precipitation is on the order of days, while the responses to changes in stream stage is almost immediate. The shallow groundwater gradients calculated form the water level data indicates the presence of two groundwater discharge zones at the site. The total reach of stream is generally gaining water form the groundwater system. The range of stream flow velocities observed is fairly uniform and sufficient to transport unconsolidated sediments up to 2 mm in diameter. The grain size distribution was analyzed.Grant no. 14-08-0001-2008, Project no. 11; financed in part by the U.S. Dept. of the Interior, Geological Survey, through the Colorado Water Resources Research Institute

Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models

A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particle Swarm Optimization (PSO), Adaptive Particle Swarm Optimization (APSO; the TRIBES strategy), and an existing hybrid optimization strategy (hPSO). All the strategies are tested on 2D, 5D and 10D Rosenbrock and Griewank polynomial test functions and a synthetic hydrogeologic application to identify the source of a contaminant plume in an aquifer. Tests are performed using a series of runs with random initial guesses for the estimated (function/model) parameters. Squads is observed to have the best performance when both robustness and efficiency are taken into consideration than the other strategies for all test functions and the hydrogeologic application

Field assessment of stream/aquifer interaction under semi-arid conditions and problems with computer representation

June 1994.Also listed online under Open file reports list as no. 6.Revision of Bissett's thesis (M. Eng.--Colorado School of Mines, 1994).Includes bibliographical references (pages 59-60).Financed in part by the U.S. Dept. of the Interior, Geological Survey

Modelling gap-size distribution of parked cars using random-matrix theory

We apply the random-matrix theory to the car-parking problem. For this purpose, we adopt a Coulomb gas model that associates the coordinates of the gas particles with the eigenvalues of a random matrix. The nature of interaction between the particles is consistent with the tendency of the drivers to park their cars near to each other and in the same time keep a distance sufficient for manoeuvring. We show that the recently measured gap-size distribution of parked cars in a number of roads in central London is well represented by the spacing distribution of a Gaussian unitary ensemble.Comment: 7 pages, 1 figur

Assessing the effects of spatial discretization on large-scale flow model performance and prediction uncertainty

Large-scale physically-based and spatially-distributed models (>100 km2) constitute useful tools for water management since they take explicitly into account the heterogeneity and the physical processes occurring in the subsurface for predicting the evolution of discharge and hydraulic heads for several predictive scenarios. However, such models are characterized by lengthy execution times. Therefore, modelers often coarsen spatial discretization of large-scale physically-based and spatially-distributed models for reducing the number of unknowns and the execution times. This study investigates the influence of such a coarsening of model grid on model performance and prediction uncertainty. The improvement of model performance obtained with an automatic calibration process is also investigated. The results obtained show that coarsening spatial discretization mainly influences the simulation of discharge due to a poor representation of surface water network and a smoothing of surface slopes that prevents from simulating properly surface water-groundwater interactions and runoff processes. Parameter sensitivities are not significantly influenced by grid coarsening and calibration can compensate, to some extent, for model errors induced by grid coarsening. The results also show that coarsening spatial discretization mainly influences the uncertainty on discharge predictions. However, model prediction uncertainties on discharge only increase significantly for very coarse spatial discretizations.Peer reviewe

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

Obtaining Parsimonious Hydraulic Conductivity Fields Using Head and Transport Observations: A Bayesian Geostatistical Parameter Estimation Approach

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained

Using Heat to Characterize Streambed Water Flux Variability in Four Stream Reaches

Estimates of streambed water fl ux are needed for the interpretation of streambed chemistry and reactions. Continuous temperature and head monitoring in stream reaches within four agricultural watersheds (Leary Weber Ditch, IN; Maple Creek, NE; DR2 Drain, WA; and Merced River, CA) allowed heat to be used as a tracer to study the temporal and spatial variability of fluxes through the streambed. Synoptic methods (seepage meter and differential discharge measurements) were compared with estimates obtained by using heat as a tracer. Water flux was estimated by modeling one-dimensional vertical flow of water and heat using the model VS2DH. Flux was influenced by physical heterogeneity of the stream channel and temporal variability in stream and ground-water levels. During most of the study period (April–December 2004), flux was upward through the streambeds. At the IN, NE, and CA sites, high-stage events resulted in rapid reversal of flow direction inducing short-term surface-water flow into the streambed. During late summer at the IN site, regional ground-water levels dropped, leading to surface-water loss to ground water that resulted in drying of the ditch. Synoptic measurements of flux generally supported the model flux estimates. Water flow through the streambed was roughly an order of magnitude larger in the humid basins (IN and NE) than in the arid basins (WA and CA). Downward flux, in response to sudden high streamflows, and seasonal variability in flux was most pronounced in the humid basins and in high conductivity zones in the streambed

Recent Developments and Applications of the HYDRUS Computer Software Packages

The HYDRUS-1D and HYDRUS (2D/3D) computer software packages are widely used finite-element models for simulating the one- and two- or three-dimensional movement of water, heat, and multiple solutes in variably saturated media, respectively. In 2008, Šimůnek et al. (2008b) described the entire history of the development of the various HYDRUS programs and related models and tools such as STANMOD, RETC, ROSETTA, UNSODA, UNSATCHEM, HP1, and others. The objective of this manuscript is to review selected capabilities of HYDRUS that have been implemented since 2008. Our review is not limited to listing additional processes that were implemented in the standard computational modules, but also describes many new standard and nonstandard specialized add-on modules that significantly expanded the capabilities of the two software packages. We also review additional capabilities that have been incorporated into the graphical user interface (GUI) that supports the use of HYDRUS (2D/3D). Another objective of this manuscript is to review selected applications of the HYDRUS models such as evaluation of various irrigation schemes, evaluation of the effects of plant water uptake on groundwater recharge, assessing the transport of particle-like substances in the subsurface, and using the models in conjunction with various geophysical methods