The User Guide of SHUD model: html
The Simulator for Hydrologic Unstructured Domain (SHUD - pronounced “SHOULD”) is a multi-process, multi-scale hydrological model where major hydrological processes are fully coupled using the semi-discrete Finite Volume Method (FVM).
SHUD encapsulates the strategy for the synthesis of multi-state distributed hydrological models using the integral representation of the underlying physical process equations and state variables. As a heritage of Penn State Integrated Hydrologic Model (PIHM), the SHUD model is a continuation of 16 years of PIHM modeling in hydrology and related fields since the release of its first PIHM version (Qu, 2004).
The SHUD’s design is based on a concise representation of a watershed and river basin’s hydrodynamics, which allows for interactions among major physical processes operating simultaneously, but with the flexibility to add or drop states/processes/constitutive relations depending on the objectives of the numerical experiment for research purpose.
The SHUD is a distributed hydrological model in which the domain is discretized using an unstructured triangular irregular network (e.g., Delaunay triangles) generated with constraints (geometric and parametric). A local prismatic control volume is formed by the vertical projection of the Delaunay triangles forming each layer of the model. Given a set of constraints (river network, watershed boundary, elevation, and hydraulic properties), an “optimized mesh” is generated. The “optimized mesh” indicates the hydrological processes with the unstructured mesh can be calculated efficiently, stably and rationally (Farthing and Ogden, 2017; Vanderstraeten and Keunings, 1995; Kumar, Bhatt and Duffy, 2009). River volume cells are also prismatic, with trapezoidal or rectangular cross-section, and maintain the topological relation with the Delaunay triangles. The local control volumes encapsulate all equations to be solved and are herein referred to as the model kernel.
The conceptual structure of the two-state integral-balance model for soil moisture and groundwater dynamics is devised by (Duffy, 1996), in which the partial volumes occupied by unsaturated and saturated moisture storage were integrated di- rectly upon local conservation equation. This two-state integral-balance structure simplified the hydrological dynamics while preserving the natural spatial and temporal scales contributing to runoff response. Brandes et al. (1998) use FEMWATER to realize the numeric calculation of inflow/outflow behavior within a hillslope-stream scheme. In 2004, Qu (2004) embedded the evapotranspiration and river network, and released Penn State Integrated Hydrologic Model (PIHM) v1.0, which is the most important milestone of the two-state integral-balance model. Since PIHM v1.0 (Qu, 2004), the PIHM is a generic hydrological model applicable to various watersheds or basins. After that, PIHM v2.0 (Kumar et al., 2009; Kumar and Duffy, 2009) enhance the land surface modeling. A GIS-tool, PIHMgis(Bhatt et al., 2014) and the Essential Terrestrial Variables Data Server (HydroTerre Leonard and Duffy (2013)) dramatically motivated the model deployment and applications with PIHM. Because of the sophisticated hydrological modeling and efficient spatial representative of PIHM, various model coupling project ini- tialized. For example, Flux-PIHM coupled the NOAH Land Surface Model into PIHM to calculate more details in energy balance and evapotranspiration (Shi et al., 2015, 2014). Zhang et al. (2016) coupled the landscaping evolution with PIHM (LE-PIHM). Bao (Bao, 2016; Bao et al., 2017) coupled the reaction transport module with PIHM (RT-PIHM, RT-Flux-PIHM). Flux-PIHM-BGC (Shi et al., 2018) coupled the biogeochemistry into Flux-PIHM. The Multi-Module PIHM (MM-PIHM) project (https://github.com/PSUmodeling/MM-PIHM) planned to build a uniform repository for all coupled modules. Still, more PIHM coupling projects are ongoing, such as sediments, lakes, crops, etc.. In addition, a finite volume-based integrated hydrologic modeling (FIHM) was developed (Kumar et al., 2009), which used second-order accuracy and solved 2D unsteady overland flow and 3D subsurface flow. Figure 1 shows the family tree of PIHM and SHUD. Every revision/branch received cross-pollination from others. Although PIHM and SHUD share the same fundamental conceptual two-state integral model, both the input/output are incompatible. Details of differences between them are summarised in the last section of this paper.
Figure 1 The family tree of PIHM and SHUD. PIHM and SHUD share the same fundamental conceptual model, but use different realization. The PIHMgis and rSHUD are GIS-tools for pre- and post-processing.
As a descendent of PIHM, SHUD inherits the fundamental idea of solving hydrological variables in CVODE. The code has been completely rewritten in a new programming language, with a new discretization and corresponding improvements to the underlying algorithms, adapting new mathematical schemes and a new user-friendly input/output data format. Although SHUD is forked from PIHM’s track, SHUD still inherits the use of CVODE for solving the ODE system, but modernizes and extends PIHM’s technical and scientific capabilities. The major differences are following:
We now briefly summarize the technical model improvements and technical capabilities of the model, compared to PIHM. This elaboration of the relevant technical features aims to assist future developers and advanced users with model coupling. Compared with PIHM, SHUD …