Rainfall simulation experiments in the southwestern USA using the Walnut Gulch Rainfall Simulator
| Autor: | Ginger B. Paige, Jeffry J. Stone, Jared Buono, Rae-Landa Gomez-Pond, Mark A. Nearing, Viktor O. Polyakov, Chandra Holifield Collins |
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| Rok vydání: | 2018 |
| Předmět: |
lcsh:GE1-350
Hydrology geography geography.geographical_feature_category 010504 meteorology & atmospheric sciences lcsh:QE1-996.5 Gulch 04 agricultural and veterinary sciences 01 natural sciences Arid Grassland lcsh:Geology Infiltration (hydrology) Grazing 040103 agronomy & agriculture Erosion 0401 agriculture forestry and fisheries General Earth and Planetary Sciences Environmental science Rangeland Surface runoff lcsh:Environmental sciences 0105 earth and related environmental sciences |
| Zdroj: | Earth System Science Data, Vol 10, Pp 19-26 (2018) |
| ISSN: | 1866-3516 |
| DOI: | 10.5194/essd-10-19-2018 |
| Popis: | This dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semiarid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30 % of the plots, simulations were conducted up to five times during the decade of study. The rainfall was generated using the Walnut Gulch Rainfall Simulator on 2 m by 6 m plots. Simulation sites included brush and grassland areas with various degrees of disturbance by grazing, wildfire, or brush removal. This dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to estimate runoff, infiltration, and erosion rates at a variety of ecological sites in the Southwestern USA. The inclusion of wildfire and brush treatment locations combined with long-term observations makes it important for studying vegetation recovery, ecological transitions, and the effect of management. It is also a valuable resource for erosion model parameterization and validation. The dataset is available from the National Agricultural Library at https://data.nal.usda.gov/search/type/dataset (DOI: https://doi.org/10.15482/USDA.ADC/1358583). |
| Databáze: | OpenAIRE |
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