更新时间：2019年07月11日

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科研成果

- PIHM (Penn State Integrated Hydrologic Model) 水文模型v4.0

It is our intention to begin a debate on the role of *Community Models* in the hydrologic sciences. Our research is a response to recent trends in US funding for *Observatory Science* that have emerged at NSF over the last few years, namely, the NSF-funded **CUAHSI** program (Consortium of Universities for Advanicing Hydrologic Sciences).

PIHM represents our strategy for the synthesis of *multi-state*, *multiscale* distributed hydrologic models using the integral representation of the underlying physical process equations and state variables.

Our interest is in devising a concise representation of watershed and/or river basin hydrodynamics, which allows interactions among major physical processes operating simultaneously, but with the flexibility to add or eliminate states/processes/constitutive relations depending on the objective of the numerical experiment or purpose of the scientific or operational application.

To satisfy the objectives, the PIHM

- is distributed hydrologic model, based on the semi-discrete **Finite-Volume Method (FVM)** in which domain discretization is an unstructured triangular irregular network (e.g. Delaunay triangles) generated with constraints (geometric, and parametric). A local prismatic control volume is formed by vertical projection of the Delauney triangles forming each layer of the model. Given a set of constraints (e.g. river network support, watershed boundary, altitude zones, ecological regions, hydraulic properties, climate zones, etc), an “optimal” mesh is generated. River volume elements are also prismatic, with trapezoidal or rectangular cross-section, and are generated along or cross edges of Delauney triangles. The local control volume contains all equations to be solved and is referred to as the model kernel.

- is physically-based model, in which all equations used is descibing the physics of the hydrological processes which control the catchment. The physical model is ablr to predict the water in ungage water system, to estimate the sediment, pullutants and vegetation etc, such that it is practical to be coupled with biochemistry, geomorphology, limnology and other water-related research.

The global ODE system is assembled by combining all local ODE systems throughout the domain and then solved by a state-of-the-art parallel ODE solver known as CVODE developed at the Lawrence- Livermore National Laboratory.

- is fully-couple hydrologic model, where the state and flux variables in the hydrologic system are solved within same time step and conserve the mass. The fluxes are infiltration, overland flow, groundwater recharge, lateral groundwater flow, exchange of river and soil/groundwater and river discharge.

- is adaptable temporal and spatial resolution. The spatial resolution of model varies from meters to kilometers based requirement of modeling and computing resources. Internal time step of iteration step are adjustable; it is able to export the status of catchment in less 1 sencond to days. Also the time interval for exporting results is configured flexiblly. The flexible spatial and temporal resolution is rather valueable for community model coupling.

- is open source model, anyone can access the source code, use and submit their improvement.

- is long-term yield and single-event flood model.

An important partnership and motivation for this work was the Project Leaders participation in two community-science research activites over the last few years: The University of Arizona-led Science and Technology Center (SAHRA: Sustainability of Water Resources in Semi- Arid Regions), and the Chesapeake Community Modeling Project (CCMP). Each of these research programs has been essential to supporting the concept of **Community Models** for environmental prediction and helping to make it happen.

改进的 PIHM 模型。 模型计算已经全部重写。改进内容：1) OpenMP和MPI高性能并行化计算； 2) 协方差矩阵遗传算法的自动模型校准；3)改进的垂直水分运动； 4) 考虑动态土地利用变化； 5) 面向对象化编程。

- PIHMgisR 自动化水文分析工具

R开发包——处理空间数据、空间数据分析产生不规则三角形网、模型数据读写、水文数据分析、空间二维三维可视化。

- 元胞自动机土地利用变化模型(Cellular Automation Landuse Change Model, CALUC) (https://github.com/shulele/CALUC)

使用元胞自动机处理水文空间数据和现有土地利用数据，预测历史或未来土地利用状况的 R 开发包。

- NLDAS气象数据下载和转换工具(https://github.com/happynotes/NLDAS2TS)

R开发包，用于下载、存储和分析全球/全美在分析气象数据(NLDAS, GLDAS, FLDAS等).

专利