Articles | Volume 1, issue 1
https://doi.org/10.5194/soil-1-47-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/soil-1-47-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Original research article
| 
06 Jan 2015
Original research article |
| 06 Jan 2015
Quantifying soil and critical zone variability in a forested catchment through digital soil mapping
M. Holleran
Department of Soil, Water and Environmental Science, Univ. of Arizona, Tucson, Arizona, USA
now at: Geosyntec Consultants, San Francisco, California, USA
M. Levi
USDA-ARS Jornada Experimental Range, New Mexico State Univ., Las Cruces, New Mexico, USA
Department of Soil, Water and Environmental Science, Univ. of Arizona, Tucson, Arizona, USA
Viewed
Total article views: 5,378 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 May 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,733 | 2,160 | 485 | 5,378 | 377 | 402 |
- HTML: 2,733
- PDF: 2,160
- XML: 485
- Total: 5,378
- BibTeX: 377
- EndNote: 402
Total article views: 4,286 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Jan 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,144 | 1,698 | 444 | 4,286 | 355 | 384 |
- HTML: 2,144
- PDF: 1,698
- XML: 444
- Total: 4,286
- BibTeX: 355
- EndNote: 384
Total article views: 1,092 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 May 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 589 | 462 | 41 | 1,092 | 22 | 18 |
- HTML: 589
- PDF: 462
- XML: 41
- Total: 1,092
- BibTeX: 22
- EndNote: 18
Cited
30 citations as recorded by crossref.
- sUAS and their application in observing geomorphological processes J. Gallik & L. Bolešová https://doi.org/10.5194/se-7-1033-2016
- Understanding Critical Zone Evolution through Predicting the Three‐Dimensional Soil Chemical Properties of a Small Forested Catchment C. Shepard et al. https://doi.org/10.2136/sssaj2018.03.0119
- Assessment of the soil fertility status in Benin (West Africa) – Digital soil mapping using machine learning K. Hounkpatin et al. https://doi.org/10.1016/j.geodrs.2021.e00444
- Spatial Heterogeneity of Soil C:N Ratio in a Mollisol Watershed of Northeast China S. Zhang et al. https://doi.org/10.1002/ldr.2427
- Assessing Spatial Variation and Driving Factors of Available Phosphorus in a Hilly Area (Gaozhou, South China) Using Modeling Approaches and Digital Soil Mapping W. Zhang et al. https://doi.org/10.3390/agriculture13081541
- Geochemical evolution of the Critical Zone across variable time scales informs concentration‐discharge relationships: Jemez River Basin Critical Zone Observatory J. McIntosh et al. https://doi.org/10.1002/2016WR019712
- Soil Aggregates as a Source of Dissolved Organic Carbon to Streams: An Experimental Study on the Effect of Solution Chemistry on Water Extractable Carbon M. Cincotta et al. https://doi.org/10.3389/fenvs.2019.00172
- A framework for optimizing environmental covariates to support model interpretability in digital soil mapping B. Kasraei et al. https://doi.org/10.1016/j.geoderma.2024.116873
- Selected highlights in American soil science history from the 1980s to the mid-2010s E. Brevik et al. https://doi.org/10.1016/j.catena.2016.06.021
- Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions J. Martínez-Murillo et al. https://doi.org/10.1016/j.scitotenv.2017.03.291
- Metabolic scaling from cells to catchments P. Marquet & A. Gaxiola https://doi.org/10.1073/pnas.2420171121
- Suitability estimation for urban development using multi-hazard assessment map G. Bathrellos et al. https://doi.org/10.1016/j.scitotenv.2016.10.025
- Soil mapping, classification, and pedologic modeling: History and future directions E. Brevik et al. https://doi.org/10.1016/j.geoderma.2015.05.017
- Vegetation greenness response to water availability in northern China from 1982 to 2006 F. Zhang & Y. An https://doi.org/10.5194/se-7-995-2016
- A fuzzy intelligent system for land consolidation – a case study in Shunde, China J. Wang et al. https://doi.org/10.5194/se-6-997-2015
- A probabilistic approach to quantifying soil physical properties via time-integrated energy and mass input C. Shepard et al. https://doi.org/10.5194/soil-3-67-2017
- Predictive mapping of soil-landscape relationships in the arid Southwest United States N. Regmi & C. Rasmussen https://doi.org/10.1016/j.catena.2018.02.031
- Why Do Large‐Scale Land Surface Models Produce a Low Ratio of Transpiration to Evapotranspiration? L. Chang et al. https://doi.org/10.1029/2018JD029159
- Machine learning for modelling compositional soil properties in digital soil mapping S. Van der Westhuizen & K. Masoumifard https://doi.org/10.1016/j.catena.2026.110650
- S‐World: A Global Soil Map for Environmental Modelling J. Stoorvogel et al. https://doi.org/10.1002/ldr.2656
- U-Th signatures of agricultural soil at the European continental scale (GEMAS): Distribution, weathering patterns and processes controlling their concentrations P. Négrel et al. https://doi.org/10.1016/j.scitotenv.2017.12.005
- Vegetation source water identification using isotopic and hydrometric observations from a subhumid mountain catchment R. Dwivedi et al. https://doi.org/10.1002/eco.2167
- Soil Sealing: Quantifying Impacts on Soil Functions by a Geospatial Decision Support System M. Piero et al. https://doi.org/10.1002/ldr.2802
- Deep learning in land-use classification and geostatistics in soil pH mapping: a case study at Lakehead University Agricultural Research Station, Thunder Bay, Ontario, Canada V. Carrillo et al. https://doi.org/10.1117/1.JRS.16.034519
- A remote sensing–based approach to the regionalization of socioeconomic indicators in an agricultural headwater catchment in Northern Benin Y. Bossa et al. https://doi.org/10.5194/piahs-389-45-2026
- A Web-based spatial decision supporting system for land management and soil conservation F. Terribile et al. https://doi.org/10.5194/se-6-903-2015
- A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry M. Li et al. https://doi.org/10.1016/j.geoderma.2020.114239
- Vulnerability and tsunami disaster on the west coast Banten province, Indonesia M. Muzani et al. https://doi.org/10.1080/27669645.2024.2323355
- Influence of climate variability on water partitioning and effective energy and mass transfer in a semi-arid critical zone X. Zapata-Rios et al. https://doi.org/10.5194/hess-20-1103-2016
- A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage J. Perdrial et al. https://doi.org/10.1007/s10533-018-0440-3
30 citations as recorded by crossref.
- sUAS and their application in observing geomorphological processes J. Gallik & L. Bolešová https://doi.org/10.5194/se-7-1033-2016
- Understanding Critical Zone Evolution through Predicting the Three‐Dimensional Soil Chemical Properties of a Small Forested Catchment C. Shepard et al. https://doi.org/10.2136/sssaj2018.03.0119
- Assessment of the soil fertility status in Benin (West Africa) – Digital soil mapping using machine learning K. Hounkpatin et al. https://doi.org/10.1016/j.geodrs.2021.e00444
- Spatial Heterogeneity of Soil C:N Ratio in a Mollisol Watershed of Northeast China S. Zhang et al. https://doi.org/10.1002/ldr.2427
- Assessing Spatial Variation and Driving Factors of Available Phosphorus in a Hilly Area (Gaozhou, South China) Using Modeling Approaches and Digital Soil Mapping W. Zhang et al. https://doi.org/10.3390/agriculture13081541
- Geochemical evolution of the Critical Zone across variable time scales informs concentration‐discharge relationships: Jemez River Basin Critical Zone Observatory J. McIntosh et al. https://doi.org/10.1002/2016WR019712
- Soil Aggregates as a Source of Dissolved Organic Carbon to Streams: An Experimental Study on the Effect of Solution Chemistry on Water Extractable Carbon M. Cincotta et al. https://doi.org/10.3389/fenvs.2019.00172
- A framework for optimizing environmental covariates to support model interpretability in digital soil mapping B. Kasraei et al. https://doi.org/10.1016/j.geoderma.2024.116873
- Selected highlights in American soil science history from the 1980s to the mid-2010s E. Brevik et al. https://doi.org/10.1016/j.catena.2016.06.021
- Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions J. Martínez-Murillo et al. https://doi.org/10.1016/j.scitotenv.2017.03.291
- Metabolic scaling from cells to catchments P. Marquet & A. Gaxiola https://doi.org/10.1073/pnas.2420171121
- Suitability estimation for urban development using multi-hazard assessment map G. Bathrellos et al. https://doi.org/10.1016/j.scitotenv.2016.10.025
- Soil mapping, classification, and pedologic modeling: History and future directions E. Brevik et al. https://doi.org/10.1016/j.geoderma.2015.05.017
- Vegetation greenness response to water availability in northern China from 1982 to 2006 F. Zhang & Y. An https://doi.org/10.5194/se-7-995-2016
- A fuzzy intelligent system for land consolidation – a case study in Shunde, China J. Wang et al. https://doi.org/10.5194/se-6-997-2015
- A probabilistic approach to quantifying soil physical properties via time-integrated energy and mass input C. Shepard et al. https://doi.org/10.5194/soil-3-67-2017
- Predictive mapping of soil-landscape relationships in the arid Southwest United States N. Regmi & C. Rasmussen https://doi.org/10.1016/j.catena.2018.02.031
- Why Do Large‐Scale Land Surface Models Produce a Low Ratio of Transpiration to Evapotranspiration? L. Chang et al. https://doi.org/10.1029/2018JD029159
- Machine learning for modelling compositional soil properties in digital soil mapping S. Van der Westhuizen & K. Masoumifard https://doi.org/10.1016/j.catena.2026.110650
- S‐World: A Global Soil Map for Environmental Modelling J. Stoorvogel et al. https://doi.org/10.1002/ldr.2656
- U-Th signatures of agricultural soil at the European continental scale (GEMAS): Distribution, weathering patterns and processes controlling their concentrations P. Négrel et al. https://doi.org/10.1016/j.scitotenv.2017.12.005
- Vegetation source water identification using isotopic and hydrometric observations from a subhumid mountain catchment R. Dwivedi et al. https://doi.org/10.1002/eco.2167
- Soil Sealing: Quantifying Impacts on Soil Functions by a Geospatial Decision Support System M. Piero et al. https://doi.org/10.1002/ldr.2802
- Deep learning in land-use classification and geostatistics in soil pH mapping: a case study at Lakehead University Agricultural Research Station, Thunder Bay, Ontario, Canada V. Carrillo et al. https://doi.org/10.1117/1.JRS.16.034519
- A remote sensing–based approach to the regionalization of socioeconomic indicators in an agricultural headwater catchment in Northern Benin Y. Bossa et al. https://doi.org/10.5194/piahs-389-45-2026
- A Web-based spatial decision supporting system for land management and soil conservation F. Terribile et al. https://doi.org/10.5194/se-6-903-2015
- A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry M. Li et al. https://doi.org/10.1016/j.geoderma.2020.114239
- Vulnerability and tsunami disaster on the west coast Banten province, Indonesia M. Muzani et al. https://doi.org/10.1080/27669645.2024.2323355
- Influence of climate variability on water partitioning and effective energy and mass transfer in a semi-arid critical zone X. Zapata-Rios et al. https://doi.org/10.5194/hess-20-1103-2016
- A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage J. Perdrial et al. https://doi.org/10.1007/s10533-018-0440-3
Saved (final revised paper)
Latest update: 11 Oct 2026
