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Development and evaluation of ArcGIS based watershed-scale L-THIA ACN-WQ system for watershed management

Authors :
Yong Seok Kim
Jonggun Kim
Gwanjae Lee
Won Seok Jang
Kyoung Jae Lim
Ji-Chul Ryu
Kwang-Sik Yoon
Source :
Water Supply. 18:1206-1221
Publication Year :
2017
Publisher :
IWA Publishing, 2017.

Abstract

The Long-term Hydrologic Impact Assessment Model with Asymptotic Curve Number Regression Equation and Water Quality model (L-THIA ACN-WQ) has been developed to simulate streamflow as well as instream water quality using fewer parameters, compared to other watershed models. However, since model input parameters (i.e. hydraulic response unit (HRU) map, stream network, database (DB), etc.) should be built by user manually, it is difficult to use the model for a nonprofessional or environmental policy decision-maker. In addition, it is difficult to analyze model outputs in time and space because the model does not provide geographic information system (GIS) information for the simulation results. To overcome the limitations, an advanced version of L-THIA ACN-WQ system which is based on ArcGIS interface was developed in this study. To evaluate the applicability of the developed system, it was applied to the Banbyeon A watershed in which total maximum daily load (TMDL) has been implemented. The required model input datasets were automatically collected in the system, and stream flow, T-N and T-P pollutant loads were simulated for the watershed. Furthermore, flow duration curve (FDC) and load duration curve (LDC) were generated to analyze hot spot areas in the system through automatic processes included in the system. The system can establish the model input data easily, automatically provide the graphs of FDC and LDC, and provide hot spot areas which indicate high pollutant loads. Therefore, this system can be useful in establishing various watershed management plans.

Details

ISSN :
16070798 and 16069749
Volume :
18
Database :
OpenAIRE
Journal :
Water Supply
Accession number :
edsair.doi...........484d64f866d61220bfde6e36155e03bf
Full Text :
https://doi.org/10.2166/ws.2017.176