Yuning Shi

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...

Parameterization for distributed watershed modeling using national data and evolutionary algorithm

Distributed hydrologic models supported by national soil survey, geology, topography and vegetation data products can provide valuable information about the watershed hydrologic cycle. However numerical simulation of the multi-state, multi-process system is structurally complex and computationally intensive. This presents a major difficulty in model calibration using traditional techniques. This paper presents an efficient calibration strategy for the physics-based, fully coupled, distributed hydrologic model Penn State Integrated Hydrologic Model (PIHM) with the support of national data products. PIHM uses a semi-discrete Finite Volume Method (FVM) formulation of the system of coupled ordinary differential equations (e.g. canopy interception, transpiration, soil evaporation) and partial differential equations (e.g. groundwater-surface water, overland flow, infiltration, channel flow, etc.). The matrix of key parameters to be estimated in the optimization process was partitioned into two groups according to the sensitivity to difference in time scales. The first group of parameters generally describes hydrologic processes influenced by hydrologic events (event-scale group: EG), which are sensitive to short time runoff generation, while the second group of parameters is largely influenced by seasonal changes in energy (seasonal time scale group: SG). The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is used to optimize the EG parameters in Message Passing Interface (MPI) environment, followed by the estimation of parameters in the SG. The calibration strategy was applied at three watersheds in central PA: a small upland catchment (8.4ha), a watershed in the Appalachian Plateau (231km^2) and the Valley and Ridge of central Pennsylvania (843km^2). A partition calibration enabled a fast and efficient estimation of parameters.

Evaluation of the Parameter Sensitivities of a Coupled Land Surface Hydrologic Model at a Critical Zone Observatory

AbstractLand surface models (LSMs) and hydrologic models are parameterized models. The number of involved parameters is often large. Sensitivity analysis (SA) is a key step to understand the complex relationships between parameters and between state variables and parameters. SA is also critical to understand system dynamics and to examine the parameter identifiability. In this paper, parameter SA for a fully coupled, physically based, distributed land surface hydrologic model, namely, the Flux–Penn State Integrated Hydrologic Model (Flux–PIHM), is performed. Multiparameter and single-parameter tests are performed to examine the three dimensions of identifiability: distinguishability, observability, and simplicity. Results show that Flux–PIHM model predictions of discharge, water table depth, soil moisture, land surface temperature, and surface heat fluxes are very sensitive to the selection of parameter values. Parameter uncertainties produce large uncertainties in hydrologic and land surface variable pre...

Understanding watershed hydrogeochemistry: 2. Synchronized hydrological and geochemical processes drive stream chemostatic behavior

Why do solute concentrations in streams remain largely constant while discharge varies by orders of magnitude? We used a new hydrological land surface and reactive transport code, RT-Flux-PIHM, to understand this long-standing puzzle. We focus on the nonreactive chloride (Cl) and reactive magnesium (Mg) in the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO). Simulation results show that stream discharge comes from surface runoff (Qs), soil lateral flow (QL), and deeper groundwater (QG), with QL contributing >70%. In the summer, when high evapotranspiration dries up and disconnects most of the watershed from the stream, Cl is trapped along planar hillslopes. Successive rainfalls connect the watershed and mobilize trapped Cl, which counteracts dilution effects brought about by high water storage (Vw) and maintains chemostasis. Similarly, the synchronous response of clay dissolution rates (Mg source) to hydrological conditions, maintained largely by a relatively constant ratio between “wetted” mineral surface area Aw and Vw, controls Mg chemostatic behavior. Sensitivity analysis indicates that cation exchange plays a secondary role in determining chemostasis compared to clay dissolution, although it does store an order-of-magnitude more Mg on exchange sites than soil water. Model simulations indicate that dilution (concentration decrease with increasing discharge) occurs only when mass influxes from soil lateral flow are negligible (e.g., via having low clay surface area) so that stream discharge is dominated by relatively constant mass fluxes from deep groundwater that are unresponsive to surface hydrological conditions.

Understanding watershed hydrogeochemistry: 1. Development of RT‐Flux‐PIHM

Model development in hydrology and geochemistry has been advancing separately with limited integration. We developed a watershed hydrogeochemical code RT-Flux-PIHM to understand complex interactions between hydrological processes (PIHM), land-surface processes (FLUX—Noah Land Surface Model), and multicomponent subsurface reactive transport (RT). The RT module simulates geochemical processes including aqueous complexation, surface complexation, mineral dissolution and precipitation, and cation exchange. The RT module is verified against the widely used reactive transport code CrunchFlow. The code uses semidiscrete finite volume method and irregular gridding and offers data harvesting capabilities from national databases. The application of RT-Flux-PIHM is demonstrated in the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO). We aim to understand key processes that govern hydrogeochemical dynamics of the nonreactive chloride and reactive magnesium. Simulation results indicate that watershed characteristics, in particular topography, dictate the spatial distributions of water content and soil dissolution rates. Ion exchange provides buffering capacities and leads to a hysteresis loop of concentration and discharge relationship of magnesium, which differs from the open hysteresis of chloride. RT-Flux-PIHM offers physics-based modeling capabilities to integrate the vast amount of water and chemistry data that have now become available, to differentiate the relative importance of competing processes, and to test hypotheses at the interface of hydrology and geochemistry.

Virtual Experiments Guide Calibration Strategies for a Real-World Watershed Application of Coupled Surface-Subsurface Modeling

AbstractVirtual experiments have been designed for the development and validation of coupled surface-subsurface modeling. Potentially, virtual experiments can guide model calibration as well. To address the role of virtual experiments in model calibration, a novel approach was described for a real watershed calibration of Penn State Integrated Hydrologic Model (PIHM) guided by the V-shaped catchment simulation. First, a benchmarking experiment of coupled surface-subsurface modeling was developed and documented on the V-shaped catchment. Then, the performance of hydrologic predictions for the V-shaped catchment was calculated and demonstrated different levels of correlations. The correlations were found stable, which had the potential to be used as the weights of multiobjective calibration. Therefore, a weighted multiobjective calibration was developed for a real-world watershed by transferring the correlations obtained from the virtual experiments. Expectedly, the parameters calibrated using the weighted ...