- Open Access
Watershed modeling using arc hydro based on DEMs: a case study in Jackpine watershed
© Li; licensee Springer. 2014
- Received: 11 December 2013
- Accepted: 8 January 2014
- Published: 11 March 2014
Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). In this study, DEMs and stream network data were used to model the Jackpine Watershed in Ontario, Canada, using Arc Hydro Tools.
The modeling results include stream network and catchment delineation. The effects of the DEM reconditioning process and the stream threshold value on the modeling accuracy were examined through three simulations. The accuracy was discussed by overlying the actual and simulated maps, as well as by comparing stream densities, network lengths and numbers of streams, catchment area, and number of catchments. Other possible methods to improve the watershed modeling were also discussed.
It is concluded that Arc Hydro is capable of performing watershed modeling with satisfactory performance. It is shown that DEM reconditioning can improve the accuracy of watershed modeling. It is also implied that lower stream threshold value can not only lead to a more detailed stream network but also enhance the accuracy of catchment delineation.
- Digital elevation models
- Watershed modeling
- Stream network
- Catchment delineation
- Arc Hydro
Hydrologic models and the associated flooding models, water pollutants transportation models and water supply models are usually integrated in Geographic Information System (GIS) for distributed hydrologic stimulations (Fairfield and Leymarie 1991; Konadu and Fosu 2009; Moharana and Kar 2002; Wu et al. 2008). Extracting characteristics of the watershed, such as stream network and catchment delineation is essential for hydrological analysis and water resource management in GIS (Zhang et al. 2013). The foundation of these hydrologic models lies on how to obtain hydrologic and topographic parameters, i.e. watershed characteristics, from Digital Elevation Models (DEMs) (Ames et al. 2009; Jenson 1991; Lacroix et al. 2002).
There were many studies on the algorithms of watershed characteristics extraction in the past 20 years (Jones 2002; Turcotte et al. 2001; Fairfield and Leymarie 1991; Zhang et al. 2013). Wu et al. (2008) discussed about DEM-derived primary topographic attributes for hydrologic applications. Zhang and Huang (2009) and Zhang et al. (2013) proposed an algorithm to establish channel networks in digital elevation models. Many GIS-based tools have been developed based on the previous researches. The “Hydrology” toolset in ArcGIS, developed by Esri (2004), has been commonly used for DEM preprocessing and surface stream simulation. WinBasin is a watershed analysis system that can automatically calculate depressionless flow directions, delineate watersheds/sub-watersheds, extract realistic drainage networks, and calculate geomorphologic indices and hydrological responses from DEMs (Lin et al. 2008). NRCS GeoHydro is an ArcGIS application that can compute catchments, drainage points, drainage lines, and cross-section details for a storm event hydrologic model (Merkel et al. 2008). Arc Hydro is an ArcGIS-based system geared to support application involving water resources. There are two key components, including Arc Hydro Data Model and Arc Hydro Tools. These two components, together with the generic programming framework, provide basic database design and set of tools that facilitate analysis often performed in the water resources area (ESRI 2004). With these tools, watershed characteristics such as stream network, flow length, catchment, and channel networks can be rapidly and reliably determined or extracted from DEMs (Lin et al. 2008). However, few has been done to analyze the effects of DEM processing on watershed modeling accuracy (Konadu and Fosu 2009; Murphy et al. 2007). Therefore, the objective of this study is to extract the characteristics of the Jackpine watershed in Canada, and to investigate influential factors on the modeling accuracy. The stream network and catchment in the study area will be modeled based on DEMs using Arc Hydro tools. Three simulations will be conducted to analyze the factors that influence the modeling accuracy.
Stream network simulation
Results of the three simulations
Summary of stream networks and catchments compared
Network length (km)
Number of streams
Catchment area (km2)
Number of catchments
The stream network and catchment of Jackpine watershed in Ontario were modeled in three simulations using Arc Hydro. The three simulations were designed to analyze how the DEM reconditioning process and stream threshold value would effect on the accuracy of stream network and catchment modeling. The accuracy were examined by overlaying the actual and simulated map as well as by comparing the stream densities, network lengths, numbers of streams, catchment areas and numbers of catchments. The results demonstrated that Ayc Hydro could provide watershed simulation with satisfactory performance. It was proved that DEM reconditioning could improve the accuracy of watershed modeling, and that lower stream threshold value could not only lead to a more detailed stream network but also improve the accuracy of catchment modeling. However, even though DEM recondition was processed and the optimal stream threshold value was chosen, there were still deviations in the simulated results. It is believed that other factors, such as local precipitation, DEM resolution, parameter values and flow calculation algorithms might be the reason of deviations. Extracting characteristics of a watershed from DEM dataset is essential for hydrological analysis. It is the first step of process analysis in distributed hydrological models. The results could be further applied to many other watershed characteristics extraction and watershed delineation applications, and provide decision support for water resources management in various regions.
There are many factors that might influence the accuracy of watershed modeling with Arc Hydro, but only the DEM reconditioning and stream threshold value were examined in this study. Therefore, future work with the consideration of more factors, such as DEM resolution and other parameter setting in Arc Hydro is desired. More research on the flow calculation algorithms would also help improve the accuracy of watershed modeling.
The study area is affected by both warm, humid air from the Gulf of Mexico and cold, dry air from the Arctic. The Great Lakes have a significant influence on the climate in this watershed. Acting as a giant heat sink, the lakes moderate the temperatures of the surrounding land, cooling the summers and warming the winters (Magnuson et al. 1997). Climate is milder in this watershed compared to other locations of similar latitude. The lakes also increase the moisture content of the air in the watershed throughout the year.
Watershed boundary and stream network data
Digital elevation model sources
Digital elevation data was collected from the GeoBase Web portal of Canada. The source data was extracted from the National Topographic Data Base (NTDB) or various data acquired from the provinces and territories. Digital data at the scale of 1:50,000 were chosen for the study area. The grid spacing, based on geographic coordinates, was in the resolution of 0.75 arc seconds. Ground Elevations were recorded in meters relative to Mean Sea Level (MSL), based on the North American Datum 1983 (NAD83) horizontal reference datum. The DEM sections were first converted to raster files and then combined using ArcGIS tools. The obtained DEM map of Jackpine watershed is shown in Figure 2.
Modeling stream networks using digital elevation models
The modeling of stream network was based on the aforementioned stream network and DEMs data using the functions in the Arc Hydro application. A depressionless DEM was created based on the input DEM to ensure that flow was not altered by artificial depressions. The flow direction algorithm D8 (i.e., deterministic eight-node algorithm) was used to produce a grid of flow directions. This grid was used to produce the surface flow accumulation network. All the cells in the flow accumulation grid that had a value greater than the given threshold grid was given a value of “1” and defined as stream grid. Stream segments that might be a head segment, or might be defined as a segment between two segment junctions were created to produce a stream link grid map. Finally, the drainage line and catchment delineation were obtained based on the stream link grid.
In Arc Hydro, the original DEM grid can be further enhanced by overlaying and “burning” hydrographic details such as streams, lakes, and shorelines into this grid, to ensure that the modeled flow is forced to conform to already mapped surface water features (Saunders 2000; MacMillan et al. 2003). This is also called the “DEM reconditioning”, which uses the “AGREE” method and produces a “hydrologically corrected” DEM (Zhang et al. 2013). Although there is still little published work about this process in peer-reviewed journals, there are numerous studies in reports and on the internet and it has been adopted for the USGS National Hydrography Dataset (Murphy et al. 2007).
Main parameter settings of simulation A, B, and C
Stream threshold value
Without hydrological correction
Default value: 18919
With hydrological correction
Default value: 17506
With hydrological correction
The work was supported by China Scholarship Council and Faculty of Graduate Studies & Research, University of Regina. The author would like to express thanks to Dr. Joe Piwowar his constructive comments and suggestions.
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