Factors Affecting Estimates of Average Watershed Slope

Hill, A. Jason; Neary, Vincent S.

doi:10.1061/(asce)1084-0699(2005)10:2(133)

Cited by 16 publications

(11 citation statements)

References 17 publications

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“…This is supported by other studies, which showed that reduced DEM resolution negatively affects slope accuracy especially in areas of steep elevation changes as in the Baga watershed (e.g. Chang and Tsai, 1991;Gao, 1997) and cause a systematic underestimation of slope (Hill and Neary, 2005). Nevertheless, from the acquired field knowledge on the watershed it can be concluded that the general slope pattern is well represented.…”

Section: Results Methodssupporting

confidence: 77%

Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania

2006

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Effective soil and water conservation programmes require the concentration of resources on limited areas. For that purpose regional-scale assessments of erosion risk are required. However, availability of good-quality spatial data for such assessments is often poor, especially in regions like sub-Saharan Africa. This study was conducted to evaluate the potential of analysing regional erosion risk using a limited amount of readily available data. The analysis was executed for the 70-km 2 Baga watershed in the West Usambara Mountains, Tanzania. Principal data sources were a Landsat image and an SRTM DEM. Two qualitative mapping methods resulting in five erosion risk classes were evaluated against field-based erosion risk estimates. The first method derived slope classes from the DEM and fractional vegetation cover (FVC) classes from the Landsat image and FVC field estimates. Data integration was achieved with a decision tree. The second method did not apply field data for the map construction, but combined five equally sized NDVI classes and five slope classes using the minimum-operator. Resulting maps showed a high and comparable accuracy, 80 per cent for Method 1, and 81 per cent for Method 2, when allowing a maximum difference of one class with field erosion risk estimates. Spatial patterns of erosion risk were well represented by both methods and high erosion risk areas can be properly identified within the Baga watershed. Due to the limited data requirement of Method 2, it has a high potential for quick identification of erosion risk in other areas of the East African Highlands.

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Section: Results Methodssupporting

confidence: 77%

Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania

2006

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“…The DHS method was used to calculate the slope (in degrees) from a central cell (cell e , in Figure 4) in one of eight directions with the maximum elevation drop (Zhang et al , 1999; Hill and Neary, 2005), i.e. where:…”

Section: Methodsmentioning

confidence: 99%

GIS‐evaluation of two slope‐calculation methods regarding their suitability in slope analysis using high‐precision LiDAR digital elevation models

Ashraf

Zhao

Bourque

et al. 2011

Hydrological Processes

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Abstract:Slope is a metric that is essential to describe surface hydrological processes, including overland flow, soil erosion, and sediment transport. Most commercial GIS have built-in functions to calculate the slope from Digital Elevation Models (DEMs) by means of average neighbourhood methods that are appropriate for coarse-resolution DEMs. Emergence of high-resolution DEMs from LiDAR data creates a need to re-assess the suitability of existing algorithms for calculating slope in hydrological applications.In this study, we investigate the properties of two different slope-calculation methods: an average-neighbourhood-slope (ANS) and a downhill-slope (DHS) method. Conceptually, the DHS method provides a more intuitive description of surface water-flow characteristics in an uneven terrain. DEMs of five different types were used to evaluate the methods, namely a 1-m and 10-m resolution DEM interpolated from irregular elevation point-data generated with conventional photogrammetric techniques, and a 1-m, 5-m, and 10-m resolution DEM derived from LiDAR data. The slopes calculated were summarized for the entire watershed, along mapped streams, and within pre-defined 'stream buffers'. Slopes generated for the entire watershed with 1-m resolution LiDAR DEM indicated that the ANS method on an average produced smaller slopes than the DHS method (0Ð64°). A similar trend was observed in stream buffers, with greatest slope differences (S) between methods within 20-m buffers, when the 1-m LiDAR-based DEM was used (S D 1Ð12°). In contrast, the ANS-calculated slopes along mapped streams were generally larger than those calculated with the DHS method for LiDAR-based DEMs (S D 0Ð81°). The results from this study signal the need for caution when estimating slopes along streams from high-accuracy, LiDAR-generated DEMs.

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“…Further, the larger number of parameters in SWAT-SSURGO may increase the model prediction uncertainty (Gupta et al, 1999). Given that the soils mainly affect overland hydrologic processes and that the relative importance of channel processes to overland processes increases when moving downstream (Hill and Neary, 2005), it may be that the differences between the streamflows predicted by SWAT-STATSGO and the corresponding values predicted by SWAT-SSURGO would be smaller downstream than at an upstream point within the same watershed. Thus, when the streamflows at downstream points, where the streamflows could be predicted by either SWAT-STATSGO or SWAT-SSURGO with a similar accuracy, are of interest, STATSGO may be superior to SSURGO due to its smaller file sizes and the ease with which the data can be processed by AvSWAT.…”

Section: Statsgo and Ssurgomentioning

confidence: 99%

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION¹

Wang¹,

Melesse

2006

J American Water Resour Assoc

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Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.

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Factors Affecting Estimates of Average Watershed Slope

Cited by 16 publications

References 17 publications

Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania

Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania

GIS‐evaluation of two slope‐calculation methods regarding their suitability in slope analysis using high‐precision LiDAR digital elevation models

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION¹

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Factors Affecting Estimates of Average Watershed Slope

Cited by 16 publications

References 17 publications

Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania

Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania

GIS‐evaluation of two slope‐calculation methods regarding their suitability in slope analysis using high‐precision LiDAR digital elevation models

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

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EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION¹