Christopher J. Duffy

Simulating the river-basin response to atmospheric forcing by linking a mesoscale meteorological model and hydrologic model system

Abstract The purpose of this article is to test the ability of a distributed meteorological/hydrologic model to simulate the hydrologic response to three single-storm events passing over the Upper West Branch of the Susquehanna River Basin. The high-resolution precipitation fields for three storms are provided by observations and by the Penn State–NCAR Mesoscale Meteorological Model (MM5) with three nested domains. The MM5 simulation successfully captures the storm patterns over the study area, although some temporal and spatial discrepancies exist between observed and simulated precipitation fields. Observed and simulated precipitation data for those storms are used to drive the Hydrologic Model System (HMS). The output from HMS is compared to the measured hydrographic streamflow at the outlet of the Upper West Branch. The Curve Number and Green-Ampt methods of rainfall-runoff partitioning are used in HMS and evaluated for streamflow simulation. The results of the hydrologic simulation compare well with observed data when using the Curve Number partitioning, but underestimate observed data when using the Green-Ampt. The likely cause is the lack of heterogeneity in hydraulic parameters. The simulated streamflow with the MM5-simulated precipitation is lower than the simulated streamflow with observed precipitation. The experiments suggest that the subgrid-scale spatial variability in precipitation and hydraulic parameters should be included in future model development

A Two‐State Integral‐Balance Model for Soil Moisture and Groundwater Dynamics in Complex Terrain

A dynamical model is devised for a hydrologic system where unsaturated and saturated storage serve as the principal control on rainfall-runoff and where complex topography, drainage area, and variable depth of moisture penetration describe the flow geometry. The model is formed by direct integration of the local conservation equation with respect to the partial volumes occupied by unsaturated and saturated moisture storage, respectively. This yields an “integral-balance” model in just two state variables. The relationship of the dynamical model to field data in complex terrain is found through a joint probability density for terrain features. This serves as a “volume” weighting function to construct conditional averages for the state variables and fluxes over a specified range of terrain features. The scale of averaging could range from hillslopes to river basins. Two examples of the joint probability of terrain features (altitude and aspect) are demonstrated for Valley, Ridge, and Appalachian Plateau digital elevation models. The strategy of a dynamical model formed by conditional averages of state variables with respect to terrain features is proposed as a way of simplifying the dynamics while preserving the natural spatial and temporal scales contributing to runoff response. The parametric form of the storage-flux or constitutive relationships for the proposed model is determined from numerical experiments in a simple hillslope flow geometry. The results show that a competitive relation exists between unsaturated and saturated storage except for the lowest precipitation rates. Saturation overland flow is proposed to be a storage-feedback relation. Solutions to the integral-balance model are presented in terms of the phase portrait, which represents all possible solution trajectories in state-space. The timing and magnitude of peaks in the runoff hydrograph from pulse-type input events demonstrate quick flow from near-stream saturated storage, saturation overland flow including rejected rainfall (storage-feedback), and late-time infiltration from upslope subsurface flow.

Characterization of deep weathering and nanoporosity development in shale - a neutron study

Abstract We used small-angle and ultra-small-angle neutron scattering (SANS/USANS) to characterize the evolution of nanoscale features in weathering Rose Hill shale within the Susquehanna/Shale Hills Observatory (SSHO). The SANS/USANS techniques, here referred to as neutron scattering (NS), characterize porosity comprised of features ranging from approximately 3 nm to several micrometers in dimension. NS was used to investigate shale chips sampled by gas-powered drilling (“saprock”) or by hand-augering (“regolith”) at ridgetop. At about 20 m depth, dissolution is inferred to have depleted the bedrock of ankerite and all the chips investigated with NS are from above the ankerite dissolution zone. NS documents that 5-6% of the total ankerite-free rock volume is comprised of isolated, intraparticle pores. At 5 m depth, an abrupt increase in porosity and surface area corresponds with onset of feldspar dissolution in the saprock and is attributed mainly to peri-glacial processes from 15 000 years ago. At tens of centimeters below the saprock-regolith interface, the porosity and surface area increase markedly as chlorite and illite begin to dissolve. These clay reactions contribute to the transformation of saprock to regolith. Throughout the regolith, intraparticle pores in chips connect to form larger interparticle pores and scattering changes from a mass fractal at depth to a surface fractal near the land surface. Pore geometry also changes from anisotropic at depth, perhaps related to pencil cleavage created in the rock by previous tectonic activity, to isotropic at the uppermost surface as clays weather. In the most weathered regolith, kaolinite and Fe-oxyhydroxides precipitate, blocking some connected pores. These precipitates, coupled with exposure of more quartz by clay weathering, contribute to the decreased mineral-pore interfacial area in the uppermost samples. These observations are consistent with conversion of bedrock to saprock to regolith at SSHO due to: (1) transport of reactants (e.g., water, O2) into primary pores and fractures created by tectonic events and peri-glacial effects; (2) mineral-water reactions and particle loss that increase porosity and the access of water into the rock. From deep to shallow, mineral-water reactions may change from largely transport-limited where porosity was set largely by ancient tectonic activity to kinetic-limited where porosity is changing due to climate-driven processes.

Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists—in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems—to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.

Development of a Coupled Land Surface Hydrologic Model and Evaluation at a Critical Zone Observatory

AbstractA fully coupled land surface hydrologic model, Flux-PIHM, is developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater at spatial resolutions sufficient to resolve upland stream networks, Flux-PIHM is able to represent heterogeneities due to topography and soils at high resolution, including spatial structure in the link between groundwater and the surface energy balance (SEB). Flux-PIHM has been implemented at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Multistate observations of discharge, water table depth, soil moisture, soil temperature, and sensible and latent heat fluxes in June and July 2009 are used to manually calibrate Flux-PIHM at hourly temporal resolution. Model predictions from 1 March to 1 December 2009 are evaluated. Both hydrologic predictions and SEB predictions show goo...

Low-frequency oscillations in precipitation, temperature, and runoff on a west facing mountain front: A hydrogeologic interpretation

This paper examines the space-time patterns of annual, interannual, and decadal components of precipitation, temperature, and runoff (P-T-R) using long-record time series across the steep topographic gradient of the Wasatch Front in northern Utah. This region forms the major drainage area to the Great Salt Lake. The approach is to use multichannel singular spectrum analysis as a means of detecting dominant oscillations and spatial patterns in the data and to discuss the relation to the unique mountain and basin hydrologic setting. Results of the analysis show that high-elevation runoff is dominated by the annual and seasonal harmonics, while low-elevation runoff exhibits strong interannual and decadal oscillations. For precipitation and temperature, only the annual/seasonal spectral peaks were found to be significantly different from the underlying noise floor, and these components increase with altitude similar to the mean orographic pattern. Spectral peaks in runoff show a more complex pattern with altitude, with increasing low-frequency components at intermediate and lower elevation. This pattern is then discussed in terms of basin storage effects and groundwater-stream interaction. A conceptual hydrogeologic model for the mountain and basin system proposes how losing streams and deep upwelling groundwater in the alluvial aquifer could explain the strong low-frequency component in streams entering the Great Salt Lake. The phase-plane trajectories of the dominant components for P-T-R are reconstructed as a function of altitude showing the relation of hydrogeologic conditions to the strongest oscillations in mountain runoff and discharge to the Great Salt Lake. The paper shows that weak interannual and decadal oscillations in the climate signal are strengthened where groundwater discharge dominates streamflow.

A tightly coupled GIS and distributed hydrologic modeling framework

Distributed, physics-based hydrologic models require spatially explicit specification of parameters related to climate, geology, land-cover, soil, and topography. Extracting these parameters from national geodatabases requires intensive data processing. Furthermore, mapping these parameters to model mesh elements necessitates development of data access tools that can handle both spatial and temporal datasets. This paper presents an open-source, platform independent, tightly coupled GIS and distributed hydrologic modeling framework, PIHMgis (www.pihm.psu.edu), to improve model-data integration. Tight coupling is achieved through the development of an integrated user interface with an underlying shared geodata model, which improves data flow between the PIHMgis data processing components. The capability and effectiveness of the PIHMgis framework in providing functionalities for watershed delineation, domain decomposition, parameter assignment, simulation, visualization and analyses, is demonstrated through prototyping of a model simulation. The framework and the approach are applicable for watersheds of varied sizes, and offer a template for future GIS-Model integration efforts. A coupled GIS and distributed hydrologic modeling framework, PIHMgis was developed.PIHMgis uses national geospatial dataset to setup, execute, and analyze simulations.Procedural framework improves model-data integration using shared geodata model.

A low-dimensional model for concentration-discharge dynamics in groundwater stream systems

In this paper we investigate the physical basis and validity of a dynamical model for environmental tracer response for a groundwater-dominated stream reach or small catchments. The dynamical model is formed by volume averaging of the local equations of saturated flow and solute transport. The approach interprets the empirical concentration-discharge C-Q as a pair of integrated state variables from an underlying state space (or phase space) for the hillslope or catchment response. The inputs represent episodic, seasonal, and random recharge rate and concentration time series. A closed form solution is found for constant inputs. Results are compared with numerical solutions of the governing partial differential equations, and agreement is found for a full range of initial states and levels of forcing. For pulse-type or piecewise constant recharge events, the phase plane trajectories for C-Q are shown to exhibit looping behavior, without the need for an assumption of hysteresis in the model. The orientation and looping direction of these solutions are shown to be controlled by the dimensionless ratio of solute residence time to hydraulic relaxation time and the relative phase lag between recharge and recharge concentration. The closed form solution is extended to the case of piecewise constant, random, input sequences resulting in a “random map” for C-Q. An application is presented for seasonal storage and flushing of SO−4 in runoff for a small catchment in central Pennsylvania.

An efficient domain decomposition framework for accurate representation of geodata in distributed hydrologic models

Physically‐based, fully‐distributed hydrologic models simulate hydrologic state variables in space and time while using information regarding heterogeneity in climate, land use, topography and hydrogeology. Since fine spatio‐temporal resolution and increased process dimension will have large data requirements, there is a practical need to strike a balance between descriptive detail and computational load for a particular model application. In this paper, we present a flexible domain decomposition strategy for efficient and accurate integration of the physiographic, climatic and hydrographic watershed features. The approach takes advantage of different GIS feature types while generating high‐quality unstructured grids with user‐specified geometrical and physical constraints. The framework is able to anchor the efficient capture of spatially distributed and temporally varying hydrologic interactions and also ingest the physical prototypes effectively and accurately from a geodatabase. The proposed decomposition framework is a critical step in implementing high quality, multiscale, multiresolution, temporally adaptive and nested grids with least computational burden. We also discuss the algorithms for generating the framework using existing GIS feature objects. The framework is successfully being used in a finite volume based integrated hydrologic model. The framework is generic and can be used in other finite element/volume based hydrologic models.

Most computational hydrology is not reproducible, so is it really science?

Reproducibility is a foundational principle in scientific research. Yet in computational hydrology the code and data that actually produces published results are not regularly made available, inhibiting the ability of the community to reproduce and verify previous findings. In order to overcome this problem we recommend that reuseable code and formal workflows, which unambiguously reproduce published scientific results, are made available for the community alongside data, so that we can verify previous findings, and build directly from previous work. In cases where reproducing large-scale hydrologic studies is computationally very expensive and time-consuming, new processes are required to ensure scientific rigor. Such changes will strongly improve the transparency of hydrological research, and thus provide a more credible foundation for scientific advancement and policy support.