Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa
Scientific Investigations Report 2017-5108
Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR–692)
- David A. Eash, Kimberlee K. Barnes, Padraic S. O'Shea, and Brian K. Gelder
Basin-characteristic measurements related to stream length, stream slope, stream density, and stream order have been identified as significant variables for estimation of flood, flow-duration, and low-flow discharges in Iowa. The placement of channel initiation points, however, has always been a matter of individual interpretation, leading to differences in stream definitions between analysts.
This study investigated five different methods to define stream initiation using 3-meter light detection and ranging (lidar) digital elevation models (DEMs) data for 17 streamgages with drainage areas less than 50 square miles within the Des Moines Lobe landform region in north-central Iowa. Each DEM was hydrologically enforced and the five stream initiation methods were used to define channel initiation points and the downstream flow paths. The five different methods to define stream initiation were tested side-by-side for three watershed delineations: (1) the total drainage-area delineation, (2) an effective drainage-area delineation of basins based on a 2-percent annual exceedance probability (AEP) 12-hour rainfall, and (3) an effective drainage-area delineation based on a 20-percent AEP 12-hour rainfall.
Generalized least squares regression analysis was used to develop a set of equations for sites in the Des Moines Lobe landform region for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs. A total of 17 streamgages were included in the development of the regression equations. In addition, geographic information system software was used to measure 58 selected basin-characteristics for each streamgage.
Results of the regression analyses of the 15 lidar datasets indicate that the datasets that produce regional regression equations (RREs) with the best overall predictive accuracy are the National Hydrographic Dataset, Iowa Department of Natural Resources, and profile curvature of 0.5 stream initiation methods combined with the 20-percent AEP 12-hour rainfall watershed delineation method. These RREs have a mean average standard error of prediction (SEP) for 4-, 2-, and 1-percent AEP discharges of 53.9 percent and a mean SEP for all eight AEPs of 55.5 percent. Compared to the RREs developed in this study using the basin characteristics from the U.S. Geological Survey StreamStats application, the lidar basin characteristics provide better overall predictive accuracy.
Eash, D.A., Barnes, K.K., O’Shea, P.S., and Gelder, B.K., 2018, Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa: U.S. Geological Survey Scientific Investigations Report 2017–5108, 23 p., https://doi.org/10.3133/sir20175108.
ISSN: 2328-0328 (online)
Table of Contents
- Hydrologic Conditioning of Lidar DEMs
- Stream Initiation Methods
- Dataset Development for Streamgages
- Comparison of Lidar and StreamStats Basin Characteristics
- Development of Regional Peak-Flow Regression Equations using Lidar Basin Characteristics
- References Cited
Additional publication details
- Publication type:
- Publication Subtype:
- USGS Numbered Series
- Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa
- Series title:
- Scientific Investigations Report
- Series number:
- Year Published:
- U.S. Geological Survey
- Publisher location:
- Reston, VA
- Contributing office(s):
- Iowa Water Science Center
- vi, 23 p.
- United States
- Other Geospatial:
- Des Moines Lobe landform region
- Online Only (Y/N):
- Additional Online Files (Y/N):