Geology topics

Albert J. Valocchi

Publications and source records attributed to Albert J. Valocchi.

3 recordsLinked to original sources

USGS2017

Expanding the role of reactive transport models in critical zone processes

Models test our understanding of processes and can reach beyond the spatial and temporal scales of measurements. Multi-component Reactive Transport Models (RTMs), initially developed more than three decades ago, have been used extensively to explore the interactions of geothermal, hydrologic, geochemical, and geobiological processes in subsurface systems. Driven by extensive data sets now available from intensive measurement efforts, there is a pressing need to couple RTMs with other community models to explore non-linear interactions among the atmosphere, hydrosphere, biosphere, and geosphere. Here we briefly review the history of RTM development, summarize the current state of RTM approaches, and identify new research directions, opportunities, and infrastructure needs to broaden the use of RTMs. In particular, we envision the expanded use of RTMs in advancing process understanding in the Critical Zone, the veneer of the Earth that extends from the top of vegetation to the bottom of groundwater. We argue that, although parsimonious models are essential at larger scales, process-based models offer tools to explore the highly nonlinear coupling that characterizes natural systems. We present seven testable hypotheses that emphasize the unique capabilities of process-based RTMs for (1) elucidating chemical weathering and its physical and biogeochemical drivers; (2) understanding the interactions among roots, micro-organisms, carbon, water, and minerals in the rhizosphere; (3) assessing the effects of heterogeneity across spatial and temporal scales; and (4) integrating the vast quantity of novel data, including “omics” data (genomics, transcriptomics, proteomics, metabolomics), elemental concentration and speciation data, and isotope data into our understanding of complex earth surface systems. With strong support from data-driven sciences, we are now in an exciting era where integration of RTM framework into other community models will facilitate process understanding across disciplines and across scales.

Earth-Science Reviews↗

USGS2014

Parameter estimation for groundwater models under uncertain irrigation data

The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p < 0.05) bias in estimated parameters and model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.

Groundwater↗

USGS2013

Development of a Fluvial Egg Drift Simulator to evaluate the transport and dispersion of Asian carp eggs in rivers

Asian carp are migrating towards the Great Lakes and are threatening to invade this ecosystem, hence there is an immediate need to control their population. The transport of Asian carp eggs in potential spawning rivers is an important factor in its life history and recruitment success. An understanding of the transport, development, and fate of Asian carp eggs has the potential to create prevention, management, and control strategies before the eggs hatch and develop the ability to swim. However, there is not a clear understanding of the hydrodynamic conditions at which the eggs are transported and kept in suspension. This knowledge is imperative because of the current assumption that suspension is required for the eggs to survive. Herein, FluEgg (Fluvial Egg Drift Simulator), a three-dimensional Lagrangian model capable of evaluating the influence of flow velocity, shear dispersion and turbulent diffusion on the transport and dispersal patterns of Asian carp eggs is presented. The model's variables include not only biological behavior (growth rate, density changes) but also the physical characteristics of the flow field, such as mean velocities and eddy diffusivities. The performance of the FluEgg model was evaluated using observed data from published flume experiments conducted in China with water-hardened Asian carp eggs as subjects. FluEgg simulations show a good agreement with the experimental data. The model was also run with observed data from the Sandusky River in Ohio to provide a real-world demonstration case. This research will support the identification of critical hydrodynamic conditions (e.g., flow velocity, depth, and shear velocity) to maintain eggs in suspension, assist in the evaluation of suitable spawning rivers for Asian carp populations and facilitate the development of prevention, control and management strategies for Asian carp species in rivers and water bodies.

Ecological Modelling↗