Model Library

EcoHydrological Assessment Tools (EcoHAT)

Model name: EcoHydrological Assessment Tools (EcoHAT)

Developed by: Dr. ChangMing Liu, Dr. ShengTian Yang, Dr. Xiaowen Li, Dr. Fanghua Hao, and Dr. Hongguang Cheng at Beijing Normal University and Chinese Academy of Sciences (Last update: 2009)

Model type: Process-based, ecohydrological, watershed model

Computational requirements: N/A

Software requirements: GIS: recommended.

Link to download model: Not open-source.

Capabilities and Limitations:

Capabilities

  • It has a modular design;
  • It can combine remote sensing (RS) and GIS to integrate remote-sensing data with earth surface parameters;
  • It is most used to calculate nonpoint source (NPS) pollution loads regionally and per pixel (Song et al., 2012);
  • EcoHAT features flexible spatial scales, suitability for mixed watersheds with agricultural and urban areas, and supports multiple temporal scales (daily, monthly, yearly) (Zhao et al., 2022);
  • It incorporates Fractional Vegetation Cover (FVC) as an input, improving runoff NPS estimation accuracy (Zheng et al., 2009);
  • It effectively simulates the rainfall-runoff relationship, aligning with China's environmental characteristics (Zhao et al., 2022).

Limitations

  • Not open-source;
  • EcoHAT still needs improvement in ecohydrological processes between pixel grids and the impacts of human activities on ecohydrological processes (Liu et al., 2009);
  • Limited availability of information and applications;
  • It is mostly applied in China.

Model Inputs and Outputs:

Inputs

Morphology data, LULC data, Soil data, Meteorological data, Hydrological data, Water quality data, Management data

Outputs

  • It estimates NPS pollution loads in watersheds.
  • It determines NPS pollution's contribution to river water quality and assesses NPS pollution's impact on the environment.

Examples:

References

Zhao, C. S., Pan, X., Yang, S. T., et al. (2021). Effects and prediction of nonpoint source pollution on the structure of aquatic food webs. Ecohydrology, 14, e2257. https://doi.org/10.1002/eco.2257

Zhao, C., Li, M., Wang, X., Liu, B., Pan, X., & Fang, H. (2022). Improving the accuracy of nonpoint-source pollution estimates in inland waters with coupled satellite-UAV data. Water Research, 225, 119208. https://doi.org/10.1016/j.watres.2022.119208

Objectives

The main objective of this study was to quantitatively analyze and predict the effects of nonpoint source pollution on the structure of aquatic food webs.

The objective of the study is to improve the accuracy of NPS pollution modeling by coupling satellite and UAV images and developing a new method for NPS pollution modeling verification. This involves using satellite data to obtain fractional vegetation coverage (FVC), capturing high-accuracy ground parameters through coupled UAV and satellite images, and developing a new method as a proxy for NPS measurements to verify the NPS pollution simulations.