Metamodels to Bridge the Gap Between Modeling and Decision Support

Insights from process-based models are a mainstay of many groundwater investigations; however, long runtimes often preclude their use in the decision-making process. Screening-level predictions are often needed in areas lacking time or funding for rigorous process-based modeling. The U.S. Geological Survey (USGS) Groundwater Resources and National Water Quality Assessment Programs are addressing these issues by evaluating the “metamodel” to bridge these gaps. A metamodel is a statistical model founded on a computationally expensive model. Although faster, the question remains: Can a statistical model provide similar insights to a numerical model with faster results

Bridging groundwater models and decision support with a Bayesian network

Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Water Resources Research 49 (2013): 6459–6473, doi:10.1002/wrcr.20496.Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.This work was funded by the USGS Climate and Land Use Mission Area, Research and Development Program and the USGS Natural Hazards Mission Area, Coastal and Marine Geology Program

Effects of sea-level rise on barrier island groundwater system dynamics – ecohydrological implications

This paper is not subject to U.S. copyright. The definitive version was published in Ecohydrology 7 (2014): 1064–1071, doi:10.1002/eco.1442.We used a numerical model to investigate how a barrier island groundwater system responds to increases of up to 60 cm in sea level. We found that a sea-level rise of 20 cm leads to substantial changes in the depth of the water table and the extent and depth of saltwater intrusion, which are key determinants in the establishment, distribution and succession of vegetation assemblages and habitat suitability in barrier islands ecosystems. In our simulations, increases in water-table height in areas with a shallow depth to water (or thin vadose zone) resulted in extensive groundwater inundation of land surface and a thinning of the underlying freshwater lens. We demonstrated the interdependence of the groundwater response to island morphology by evaluating changes at three sites. This interdependence can have a profound effect on ecosystem composition in these fragile coastal landscapes under long-term changing climatic conditions.We used a numerical model to investigate how a barrier island groundwater system responds to increases of up to 60 cm in sea level. We found that a sea-level rise of 20 cm leads to substantial changes in the depth of the water table and the extent and depth of saltwater intrusion, which are key determinants in the establishment, distribution and succession of vegetation assemblages and habitat suitability in barrier islands ecosystems. In our simulations, increases in water-table height in areas with a shallow depth to water (or thin vadose zone) resulted in extensive groundwater inundation of land surface and a thinning of the underlying freshwater lens. We demonstrated the interdependence of the groundwater response to island morphology by evaluating changes at three sites. This interdependence can have a profound effect on ecosystem composition in these fragile coastal landscapes under long-term changing climatic conditions. Published 2013. This article is a U.S. Government work and is in the public domain in the USA

Growing Pains of Crowdsourced Stream Stage Monitoring Using Mobile Phones: The Development of CrowdHydrology

Citizen science-based approaches to monitor the natural environment tend to be bimodal in maturity. Older and established programs such as the Audubon’s Christmas bird count and Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) have thousands of participants across decades of observations, while less mature citizen science projects have shorter lifespans often focused on local or regional observations with tens or hundreds of participants. For the latter, it can be difficult to transition into a more mature and sustainable citizen science-based research program. This paper focuses on this transition by evaluating CrowdHydrology (ca. 2010), a citizen science project that has transitioned from a regional to national network. It evaluates the data accuracy, citizen participation, and station popularity. The CrowdHydrology network asks citizens to send in text messages of water levels in streams and lakes, which has resulted in 16,294 observations submitted by over 8,000 unique participants at 120 unique locations. Using water level data and participation records from CrowdHydrology, we analyze the expansion and citizen participation from a regional to national citizen science network. We identify barriers to participation and evaluate why some citizen science observation stations are popular while others are not. We explore our chosen contributory program model for CrowdHydrology and the influence this model has had on long-term participation. Results demonstrate a highly variable rate of contributions of citizen scientists. This paper proposes hypotheses on why many of our observations are from one-time participants and why some monitoring stations are more popular than others. Finally, we address the future expansion of the CrowdHydrology network by evaluating successful monitoring locations and growing interest of watershed groups to expand the network of gauges

Understanding the DayCent model: Calibration, sensitivity, and identifiability through inverse modeling

AbstractThe ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil NO3− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil NO3− and NH4+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent

An Interactive Bayesian Geostatistical Inverse Protocol for Hydraulic Tomography

Hydraulic tomography is a powerful technique for characterizing heterogeneous hydrogeologic parameters. An explicit trade-off between characterization based on measurement misfit and subjective characterization using prior information is presented. We apply a Bayesian geostatistical inverse approach that is well suited to accommodate a flexible model with the level of complexity driven by the data and explicitly considering uncertainty. Prior information is incorporated through the selection of a parameter covariance model characterizing continuity and providing stability. Often, discontinuities in the parameter field, typically caused by geologic contacts between contrasting lithologic units, necessitate subdivision into zones across which there is no correlation among hydraulic parameters. We propose an interactive protocol in which zonation candidates are implied from the data and are evaluated using cross validation and expert knowledge. Uncertainty introduced by limited knowledge of dynamic regional conditions is mitigated by using drawdown rather than native head values. An adjoint state formulation of MODFLOW-2000 is used to calculate sensitivities which are used both for the solution to the inverse problem and to guide protocol decisions. The protocol is tested using synthetic two-dimensional steady state examples in which the wells are located at the edge of the region of interest

Characterization of a fluvial aquifer at a range of depths and scales: the Triassic St Bees Sandstone Formation, Cumbria, UK

Fluvial sedimentary successions represent porous media that host groundwater and geothermal resources. Additionally, they overlie crystalline rocks hosting nuclear waste repositories in rift settings. The permeability characteristics of an arenaceous fluvial succession, the Triassic St Bees Sandstone Formation in England (UK), are described, from core-plug to well-test scale up to ~1 km depth. Within such lithified successions, dissolution associated with the circulation of meteoric water results in increased permeability (K~10−1–100 m/day) to depths of at least 150 m below ground level (BGL) in aquifer systems that are subject to rapid groundwater circulation. Thus, contaminant transport is likely to occur at relatively high rates. In a deeper investigation (> 150 m depth), where the aquifer has not been subjected to rapid groundwater circulation, well-test-scale hydraulic conductivity is lower, decreasing from K~10−2 m/day at 150–400 m BGL to 10−3 m/day down-dip at ~1 km BGL, where the pore fluid is hypersaline. Here, pore-scale permeability becomes progressively dominant with increasing lithostatic load. Notably, this work investigates a sandstone aquifer of fluvial origin at investigation depths consistent with highly enthalpy geothermal reservoirs (~0.7–1.1 km). At such depths, intergranular flow dominates in unfaulted areas with only minor contribution by bedding plane fractures. However, extensional faults represent preferential flow pathways, due to presence of high connective open fractures. Therefore, such faults may (1) drive nuclear waste contaminants towards the highly permeable shallow (< 150 m BGL) zone of the aquifer, and (2) influence fluid recovery in geothermal fields

MODFLOW-style parameters in underdetermined parameter estimation

In this article, we discuss the use of MODFLOW-Style parameters in the numerical codes MODFLOW_2005 and MODFLOW_2005-Adjoint for the definition of variables in the Layer Property Flow package. Parameters are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the parameter approach for model input can make data input easier. We found that if each estimable parameter is defined by one parameter, the codes require a large computational effort and substantial gains in efficiency are achieved by removing logical comparison of character strings that represent the names and types of the parameters. An alternative formulation already available in the current implementation of the code can also alleviate the efficiency degradation due to character comparisons in the special case of distributed parameters defined through multiplication matrices. The authors also hope that lessons learned in analyzing the performance of the MODFLOW family codes will be enlightening to developers of other Fortran implementations of numerical codes

HESS opinions: Repeatable research: What hydrologists can learn from the Duke cancer research scandal

In the past decade, difficulties encountered in reproducing the results of a cancer study at Duke University resulted in a scandal and an investigation which concluded that tools used for data management, analysis, and modeling were inappropriate for the documentation of the study, let alone the reproduction of the results. New protocols were developed which require that data analysis and modeling be carried out with scripts that can be used to reproduce the results and are a record of all decisions and interpretations made during an analysis or a modeling effort. In the hydrological sciences, we face similar challenges and need to develop similar standards for transparency and repeatability of results. A promising route is to start making use of open-source languages (such as R and Python) to write scripts and to use collaborative coding environments (such as Git) to share our codes for inspection and use by the hydrological community. An important side-benefit to adopting such protocols is consistency and efficiency among collaborators.Water Resource

Simulation of Groundwater Flow and Effects of Groundwater Irrigation on Stream Base Flow in the Elkhorn and Loup River Basins, Nebraska, 1895-2055: Phase Two

Regional groundwater-flow simulations for a 30,000-square-mile area of the High Plains aquifer, referred to collectively as the Elkhorn-Loup Model, were developed to predict the effects of groundwater irrigation on stream base flow in the Elkhorn and Loup River Basins, Nebraska. Simulations described the stream-aquifer system from predevelopment through 2005 [including predevelopment (pre-1895), early development (1895–1940), and historical development (1940 through 2005) conditions] and future hypothetical development conditions (2006 through 2033 or 2055). Predicted changes to stream base flow that resulted from simulated changes to groundwater irrigation will aid development of long-term strategies for management of hydrologically connected water supplies. The predevelopment through 2005 simulation was calibrated using an automated parameter-estimation method to optimize the fit to pre-1940 groundwater levels and base flows, 1945 through 2005 decadal groundwater-level changes, and 1940 through 2005 base flows. The calibration results of the pre-1940 period indicated that 81 percent of the simulated groundwater levels were within 30 feet of the measured water levels. The results did not indicate large areas of simulated groundwater levels that were biased too high or too low, indicating that the simulation generally captures the regional trends. Calibration results using 1945 through 2005 decadal groundwater-level changes indicated that a majority of the simulated groundwater-level changes were within 5 feet of the changes calculated from measured groundwater levels. Simulated groundwater-level rises generally were smaller than measured rises near surface-water irrigation districts. Simulated groundwater-level declines were larger than measured declines in several parts of the study area having large amounts of irrigated crops. Base-flow trends and volumes generally were reproduced by the simulation at most sites. Exceptions include downward trends of simulated base flow from the 1970s to the end of the calibration period for the Elkhorn River at Norfolk, Beaver Creek at Genoa, and Cedar River near Fullerton. Effects of groundwater irrigation on stream base flow were predicted using several methods: (1) simulated base-flow depletion was mapped to represent the percentage of water pumped from a hypothetical well during 2006 through 2055 that corresponds to base-flow depletions at the end of that 50-year period; (2) the groundwater-flow simulation predicted changes in stream base flow that result from modifying the number of irrigated acres in a 25-year period (2009 through 2033); and (3) a simulation-optimization model determined the minimum reduction of groundwater pumpage that would be necessary in the Elkhorn River Basin in a 25-year period (2009 through 2033) to comply with various hypothetical base-flow requirements for the Elkhorn River. The results are not intended to determine specific management plans that must be adopted, but rather to improve the understanding of how base flow is affected by irrigation. A 50-year simulation (2006–55) indicated that depletions of less than 10 percent of pumpage mainly occur in areas that are about 10 miles or farther from the Elkhorn and Loup Rivers and their tributaries. The calibrated simulation was used to predict the 25-year effect on base flow of a 10 percent decrease in irrigated acres and the effect of increasing acres at the presently (2010) allowed rate. Hypothesized changes to irrigated acres were applied only to areas where mapped base-flow depletions were at least 10 percent of pumpage. The effect of changes in irrigated acres includes the combined effects of changes to pumpage and additional recharge from irrigated acres. When irrigated acres were decreased by 10 percent within selected areas of four Natural Resources Districts (a total reduction of about 120,000 acres and a 5 percent reduction in irrigation pumpage), simulated base flow was predicted to increase by as much as 13.0 cubic feet per second in the Loup River Basin and by as much as 23.8 cubic feet per second in the Elkhorn River Basin. The largest increases to base flow were simulated at downstream locations. When irrigated land was increased by about 25,000 acres, predicted base flow decreased by a maximum of 2.9 cubic feet per second in the Loup River Basin and by as much as 6.9 cubic feet per second in the Elkhorn River Basin. Changes to base flow were related to the proximity of the hypothetical newly irrigated acres to a stream. When a simulation-optimization model was formulated to maximize pumpage, while maintaining base flow in two key reaches of the Elkhorn River at the estimated rate needed to support the average historical frequency (about 70 percent) at which streamflow met or exceeded an in-stream flow criterion for a downstream reach in the Platte River, maximum overall pumpage was optimized when simulated pumpage within the Lower Elkhorn Natural Resources District was reduced by approximately 40 percent and pumpage within the Upper Elkhorn Natural Resources District was reduced by about 8 percent. When the simulation-optimization model was formulated to maximize pumpage, while maintaining base flow in the two key reaches of the Elkhorn River at a more conservative estimated rate (at 65 percent of 2005 simulated base flow) needed to support the in-stream flow criterion, maximum overall pumpage was optimized when simulated pumpage within the Lower Elkhorn Natural Resources District was reduced by about 49 percent and pumpage within the Upper Elkhorn Natural Resources District was reduced by about 17 percent. Neither of these two base-flow target rates are regulatory requirements, but the results provide benchmarks for the Natural Resources Districts for determination of appropriate management goals. Accuracy of the simulations is affected by input data limitations, system simplifications, assumptions, and resources available at the time of the simulation construction and calibration. Most of the important limitations relate either to data used as simulation inputs or data used to estimate simulation inputs. Development of the regional simulations focused on generalized hydrogeologic characteristics within the study area, and did not attempt to describe variations important to local-scale conditions. For example, a single unconfined layer was used to simulate the aquifer. Therefore, these simulations are most appropriate for analyzing groundwater-management scenarios over large areas and long time periods, and are not reliable for analysis of small areas or short time periods