Combined soil-terrain stratification for characterizing catchment-scale soil moisture variation

Doug Baldwin, Kusum J. Naithani, Hangsheng Lin

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Soil properties and terrain characteristics influence spatiotemporal patterns of soil moisture across a watershed. To improve the predictive power of landscape hydrologic models, it is essential to consider both soil and terrain attributes when stratifying a catchment into similar hydrologic functional units. In this study, we developed and validated a new catchment-scale stratification scheme for the Shale Hills watershed by combining soil and terrain attributes in an attempt to delineate soil-landscape units with similar soil moisture dynamics. Terrain was combined with soils information by first using a Random Forest supervised classification algorithm to predict a detailed soil map using 47 field soil samples and terrain variables derived from 1-m LiDAR. A slope class map generated from the LiDAR-derived digital elevation model (DEM) was overlaid on the predicted soil map to delineate areas of similar slope value across the catchment. We compared the performance of this new stratification scheme with two classical stratification schemes, a soil map developed from detailed field survey and a landform unit map based on the DEM, for estimating soil moisture time-series across the forested watershed. The combined soil-terrain method outperformed classical stratification schemes in estimating soil moisture time-series over a 4-year period. Our results demonstrate that combining soil and terrain attributes can help improve the stratification of a catchment into similar soil hydrologic functional units, which is valuable to distributed hydrology modeling and other applications.

Original languageEnglish (US)
Pages (from-to)260-269
Number of pages10
JournalGeoderma
Volume285
DOIs
StatePublished - Jan 1 2017

Fingerprint

stratification
soil moisture
soil water
catchment
soil
digital elevation models
watershed
time series analysis
digital elevation model
time series
forested watersheds
shale
landforms
hydrologic models
hydrology
image classification
soil properties
field survey
landform
soil sampling

All Science Journal Classification (ASJC) codes

  • Soil Science

Cite this

@article{ada48c58fcfd4151a1e9a50ef5a3a603,
title = "Combined soil-terrain stratification for characterizing catchment-scale soil moisture variation",
abstract = "Soil properties and terrain characteristics influence spatiotemporal patterns of soil moisture across a watershed. To improve the predictive power of landscape hydrologic models, it is essential to consider both soil and terrain attributes when stratifying a catchment into similar hydrologic functional units. In this study, we developed and validated a new catchment-scale stratification scheme for the Shale Hills watershed by combining soil and terrain attributes in an attempt to delineate soil-landscape units with similar soil moisture dynamics. Terrain was combined with soils information by first using a Random Forest supervised classification algorithm to predict a detailed soil map using 47 field soil samples and terrain variables derived from 1-m LiDAR. A slope class map generated from the LiDAR-derived digital elevation model (DEM) was overlaid on the predicted soil map to delineate areas of similar slope value across the catchment. We compared the performance of this new stratification scheme with two classical stratification schemes, a soil map developed from detailed field survey and a landform unit map based on the DEM, for estimating soil moisture time-series across the forested watershed. The combined soil-terrain method outperformed classical stratification schemes in estimating soil moisture time-series over a 4-year period. Our results demonstrate that combining soil and terrain attributes can help improve the stratification of a catchment into similar soil hydrologic functional units, which is valuable to distributed hydrology modeling and other applications.",
author = "Doug Baldwin and Naithani, {Kusum J.} and Hangsheng Lin",
year = "2017",
month = "1",
day = "1",
doi = "10.1016/j.geoderma.2016.09.031",
language = "English (US)",
volume = "285",
pages = "260--269",
journal = "Geoderma",
issn = "0016-7061",
publisher = "Elsevier",

}

Combined soil-terrain stratification for characterizing catchment-scale soil moisture variation. / Baldwin, Doug; Naithani, Kusum J.; Lin, Hangsheng.

In: Geoderma, Vol. 285, 01.01.2017, p. 260-269.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Combined soil-terrain stratification for characterizing catchment-scale soil moisture variation

AU - Baldwin, Doug

AU - Naithani, Kusum J.

AU - Lin, Hangsheng

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Soil properties and terrain characteristics influence spatiotemporal patterns of soil moisture across a watershed. To improve the predictive power of landscape hydrologic models, it is essential to consider both soil and terrain attributes when stratifying a catchment into similar hydrologic functional units. In this study, we developed and validated a new catchment-scale stratification scheme for the Shale Hills watershed by combining soil and terrain attributes in an attempt to delineate soil-landscape units with similar soil moisture dynamics. Terrain was combined with soils information by first using a Random Forest supervised classification algorithm to predict a detailed soil map using 47 field soil samples and terrain variables derived from 1-m LiDAR. A slope class map generated from the LiDAR-derived digital elevation model (DEM) was overlaid on the predicted soil map to delineate areas of similar slope value across the catchment. We compared the performance of this new stratification scheme with two classical stratification schemes, a soil map developed from detailed field survey and a landform unit map based on the DEM, for estimating soil moisture time-series across the forested watershed. The combined soil-terrain method outperformed classical stratification schemes in estimating soil moisture time-series over a 4-year period. Our results demonstrate that combining soil and terrain attributes can help improve the stratification of a catchment into similar soil hydrologic functional units, which is valuable to distributed hydrology modeling and other applications.

AB - Soil properties and terrain characteristics influence spatiotemporal patterns of soil moisture across a watershed. To improve the predictive power of landscape hydrologic models, it is essential to consider both soil and terrain attributes when stratifying a catchment into similar hydrologic functional units. In this study, we developed and validated a new catchment-scale stratification scheme for the Shale Hills watershed by combining soil and terrain attributes in an attempt to delineate soil-landscape units with similar soil moisture dynamics. Terrain was combined with soils information by first using a Random Forest supervised classification algorithm to predict a detailed soil map using 47 field soil samples and terrain variables derived from 1-m LiDAR. A slope class map generated from the LiDAR-derived digital elevation model (DEM) was overlaid on the predicted soil map to delineate areas of similar slope value across the catchment. We compared the performance of this new stratification scheme with two classical stratification schemes, a soil map developed from detailed field survey and a landform unit map based on the DEM, for estimating soil moisture time-series across the forested watershed. The combined soil-terrain method outperformed classical stratification schemes in estimating soil moisture time-series over a 4-year period. Our results demonstrate that combining soil and terrain attributes can help improve the stratification of a catchment into similar soil hydrologic functional units, which is valuable to distributed hydrology modeling and other applications.

UR - http://www.scopus.com/inward/record.url?scp=85006827195&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85006827195&partnerID=8YFLogxK

U2 - 10.1016/j.geoderma.2016.09.031

DO - 10.1016/j.geoderma.2016.09.031

M3 - Article

AN - SCOPUS:85006827195

VL - 285

SP - 260

EP - 269

JO - Geoderma

JF - Geoderma

SN - 0016-7061

ER -