Multiorder Hydrologic Position in the Conterminous United States: A Set of Metrics in Support of Groundwater Mapping at Regional and National Scales

被引:21
|
作者
Belitz, Kenneth [1 ]
Moore, Richard B. [2 ]
Arnold, Terri L. [3 ]
Sharpe, Jennifer B. [3 ]
Starn, J. J. [4 ]
机构
[1] US Geol Survey, Carlisle, MA 01741 USA
[2] USGS New England Water Sci Ctr, Pembroke, NH USA
[3] USGS Cent Midwest WSC, Urbana, IL USA
[4] USGS New England WSC, E Hartford, CT USA
关键词
hydrology; groundwater; machine learning; mapping; GIS; CATCHMENT TRANSIT-TIME; CENTRAL VALLEY; THEORETICAL-ANALYSIS; LANDSCAPE POSITION; GLOBAL PATTERNS; RANDOM FOREST; BASE-FLOW; NITRATE; MODELS; WATER;
D O I
10.1029/2019WR025908
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The location of a point on the landscape within a stream network (hydrologic position) can be an important predictive measure in hydrology. Hydrologic position is defined here by two metrics: lateral position and distance from stream to divide, both measured horizontally. Lateral position (dimensionless) is the relative position of a point between the stream and its watershed divide. Distance from stream to divide (units of length) is an indicator of position within a watershed: generally small near a confluence and generally large in headwater areas. Watersheds and watershed divides are defined here by Thiessen polygons rather than topographic divides. Lateral position and distance from stream to divide are also defined in the context of hydrologic order. Hydrologic order "n" is defined as the network of streams, and associated divides, of order n and higher. And given that a point can have different positions in different hydrologic orders the term multiorder hydrologic position (MOHP) is used to describe the ensemble of hydrologic positions. MOHP was mapped across the conterminous United States for nine hydrologic orders at a spatial resolution of 30 m (about 8.7 billion pixels). There are 18 metrics for each pixel. Four case studies are presented that use MOHP metrics as explanatory factors in random forest machine learning models. The case studies show that lower order MOHP metrics can serve as indicators of hydrologic process while higher-order metrics serve as indicators of location. MOHP is shown to have utility as a predictor variable across a large range of scales (50,000 to 8,000,000 km(2)).
引用
收藏
页码:11188 / 11207
页数:20
相关论文
共 12 条
  • [1] Determination of burn severity models ranging from regional to national scales for the conterminous United States
    Picotte, Joshua J.
    Cansler, C. Alina
    Kolden, Crystal A.
    Lutz, James A.
    Key, Carl
    Benson, Nathan C.
    Robertson, Kevin M.
    REMOTE SENSING OF ENVIRONMENT, 2021, 263
  • [2] Determination of burn severity models ranging from regional to national scales for the conterminous United States
    Picotte, Joshua J.
    Cansler, C. Alina
    Kolden, Crystal A.
    Lutz, James A.
    Key, Carl
    Benson, Nathan C.
    Robertson, Kevin M.
    Remote Sensing of Environment, 2021, 263
  • [3] Mapping hydrologic alteration and ecological consequences in stream reaches of the conterminous United States
    Ryan A. McManamay
    Rob George
    Ryan R. Morrison
    Benjamin L. Ruddell
    Scientific Data, 9
  • [4] Mapping hydrologic alteration and ecological consequences in stream reaches of the conterminous United States
    McManamay, Ryan A.
    George, Rob
    Morrison, Ryan R.
    Ruddell, Benjamin L.
    SCIENTIFIC DATA, 2022, 9 (01) : 450
  • [5] Regional estimation of base flow for the conterminous United States by hydrologic landscape regions
    Santhi, C.
    Allen, P. M.
    Muttiah, R. S.
    Arnold, J. G.
    Tuppad, P.
    JOURNAL OF HYDROLOGY, 2008, 351 (1-2) : 139 - 153
  • [6] Hydrologic Prediction over the Conterminous United States Using the National Multi-Model Ensemble
    Mo, Kingtse C.
    Lettenmaier, Dennis P.
    JOURNAL OF HYDROMETEOROLOGY, 2014, 15 (04) : 1457 - 1472
  • [7] Regional hydrologic response to climate change in the conterminous United States using high-resolution hydroclimate simulations
    Naz, Bibi S.
    Kao, Shih-Chieh
    Ashfaq, Moetasim
    Rastogi, Deeksha
    Mei, Rui
    Bowling, Laura C.
    GLOBAL AND PLANETARY CHANGE, 2016, 143 : 100 - 117
  • [8] Estimation of Base Flow by Optimal Hydrograph Separation for the Conterminous United States and Implications for National-Extent Hydrologic Models
    Foks, Sydney S.
    Raffensperger, Jeff P.
    Penn, Colin A.
    Driscoll, Jessica M.
    WATER, 2019, 11 (08)
  • [9] The US Geological Survey National Hydrologic Model infrastructure: Rationale, description, and application of a watershed-scale model for the conterminous United States
    Regan, R. S.
    Juracek, K. E.
    Hay, L. E.
    Markstrom, S. L.
    Viger, R. J.
    Driscoll, J. M.
    LaFontaine, J. H.
    Norton, P. A.
    ENVIRONMENTAL MODELLING & SOFTWARE, 2019, 111 : 192 - 203
  • [10] Designing a Multi-Objective, Multi-Support Accuracy Assessment of the 2001 National Land Cover Data (NLCD 2001) of the Conterminous United States
    Stehman, Stephen V.
    Wickham, James D.
    Wade, Timothy G.
    Smith, Jonathan H.
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2008, 74 (12): : 1561 - 1571