Short name: GRM
Long name: Grid based rainfall-Runoff Model
Model type: Event and continuous in time; grid based distributed in space
Flood Mechanism: Riverine flood, rural flash flood; rainfall- snowmelt derived
Usage: Short to medium range riverine flow forecasting including dam operation and sink or source stream flow.
Special Features: General rainfall-runoff event and continuous simulation. Stream flow analysis including dam operantion and sink or source flow by pumping or conduit, etc. High resolution flood simulation for the watershed runoff and flood forecasting system.
Background: The GRM is a physically-based distributed runoff model using uniform square grid. The model was developed for the high resolution flood simulation of a watershed and flood forecasting system. It was first developed for the rainfall-runoff event simulation, and has been improved to enable the continuous simulation. The first version was released in 2008. The current version was released in 2022. Development is very active and all the source codes and binaries are managed and released through the open source platform, Github. QGIS plug-in(QGRM) is suggested for GRM GUI at Github.
Channel routing: Kinematic wave
Reservoir operation: Observed release, specified release, atuo-ROM, storage-discharge curve
Shortwave radiation: None at this time
Longwave radiation: None at this time
Precipitation: Specified time-series, specified gridded, inverse distance, frequency storm, or hypothetical storm
Evapotranspiration: Blaney-Criddle, Hamon, Hargreaves, and Priestly-Taylor methods
Snowmelt: A method suggested by Anderson. Simulate snowpack changes by precipitation and snow melting according to the temperature
Infiltration: Green Ampt and gridded soil moisture accounting.
Surface runoff: Kinematic wave
Interflow: Kinematic wave and hydraulic conductivity
Percolation: Calculated using hydraulic conductivity
Baseflow: Darcy’s law using the head difference of each grid for unconfined aquifer and stream
Input data: Precipitation at a minimum for the event simulation. Other weather data (e.g. temperature, daytime length, solar radiation, snow pack temperature, etc) are required for the continuous simulation. Reservoir specification and the release flow, sink flow, and source flow for the simulation of stream flow control. Raster data for initial stream flow and initial soil saturation are optional.
Input format: Text file, ASCII raster file, xml format text file.
Input time interval: Options range from 1 minute to daily. Daily input data are subdivided into the model calculation time step (dt).
Optimization or Calibration: Multiple external optimization algorithms are available for estimating parameters using the GRM.exe(console window application), the optimization tool and observed flow data. But not integrated with the forecasting simulation.
Data Assimilation: If the new observed flow is provided, the model could be calibrated again using the new data.
Ensemble: Ensemble meteorologic forecasts data can be used by applying each time-series to the GRM. Mutiple GRM execution file(GRM.exe) can be executed.
Uncertainity: Multiple uncertainty analysis tools which are using console window exe application are available, but not integrated with the forecasting simulation.
Simulation Time Interval: Options range from 1 minute to daily. The internal calculation time step (dt) is set by the model automatically using CFL condition.
Model Output Time-Series: Land surface flow is available at all elements (all grid cells). Additional types of data are available for surface runoff, infiltration, baseflow, and reservoir pool state variables, evapotranspiration, interception, and snow melt.
Time-Series format: Textfile and ASCII raster file
Model Output Statistics: Mean areal precipitation for applied raster distributed rainfall, and mean flow for the specified time interval.
Statistics Format: Text file
Inventory Platform: Desktop (Windows console exe)
Installation: Not installation. Just copy the files.
User Education: BSc
Degree of Difficulty: 3
GIS support: GUI was developed with QGIS plugin. All types of GIS tool can be used to make the model input files(ASCII raster and text file format).
Data Preparation: Using GIS tools and text file editor.
Land Surface Parameters: 7 to 22, depending on the selected hydrological components and user choices.
Parameter Estimation: Default parameters are suggested and parameter database (xml format) could be used.
Model Calibration: Manual adjustment. Auto calibration is possible by connecting GRM.exe running in console window mode without GUI with the external optimization tool.
Model Verification: None at this time
Hardware Requirements: PC
Operating System: MicroSoft Windows
Language of Core Code: C/C++
Open Source: Yes
Last Update and Version: Aug. 2023: Version GRM v2022
Next Update and Version: Continuously being developed. Next upate is planned in Nov. 2023 as GRM v2023
Active Development Community: Yes.
Download URL: The GRM model : https://github.com/floodmodel/GRM
QGIS plug-in GUI for the GRM model: https://github.com/floodmodel/Plugin_repository_QGIS3.10/tree/main/QGIS_GRM
Free to Download and Use: Yes
Language of Software Interface: English, Korean
Online Support URL: https://github.com/floodmodel/GRM/issues
https://github.com/floodmodel/GRM/discussions
Training Material URL (including example data sets): https://github.com/floodmodel/GRM/tree/master/DownloadStableVersion
https://github.com/floodmodel/References
Language of Trainings: English, Korean
Guidance Material URL (including case studies and benchmarking of performance/speed):
https://github.com/floodmodel/GRM/tree/master/DownloadStableVersion
https://github.com/floodmodel/GRM/wiki/Home_English
Language of Guidance: English, Korean
References:
Choi, Y.S., Choi, C.K., Kim, H.S., Kim, K.T., Kim, S.J. 2015. Multi-site calibration using a grid-based event rainfall–runoff model: a case study of the upstream areas of the Nakdong River basin in Korea. Hydrological Processes, 29, pp. 2089-2099.
Shin, M.J. and Choi, Y.S. 2018a. Combining an R-Based Evolutionary Algorithm and Hydrological Model for Effective Parameter Calibration. Water, 10:1339.
Shin, M.J. and Choi, Y.S. 2018b. Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model. Water, 10:1839.
Choi, Y.S., Shin, M.J., and Kim, K.T. 2020. A Study on a Simple Algorithm for Parallel Computation of a Grid-Based One-Dimensional Distributed Rainfall-Runoff Model. KSCE Journal of Civil Engineering, 24(2):682-690.
Choi, Y.S. and Kim, K.T. 2023. Grid based Rainfall-runoff Model User’s Manual. Korea Institute of Civil Engineering and Building Technology.
Owner:
Korea Institute of Civil Engineering and Building Technology
https://www.kict.re.kr/
Mailing Address:
Department of the Hydro Science and Engineering Research
Korea Institute of Civil Engineering and Building Technology
283, Goyang-daero, Ilsanseo-gu, Goyang-si, Gyeonggi-do, 10223, Rep. of Korea
KICT Phone: +82 (0)31.910.0590
KICT Fax: +82 (0)31.910.0251
Developer:
Yun-Seok, Choi
Ph.D., Research fellow
Department of the Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology (KICT)
E-mail : yschoi51@kict.re.kr
Phone: +82 (0)31.910.0590