Variation in groundwater recharge and surface-water quality due to climatic extremes in semi-arid mountainous watersheds
| Autor: | Connor P. Newman |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Hydrology
Watershed 010504 meteorology & atmospheric sciences Groundwater flow 0208 environmental biotechnology Climate change 02 engineering and technology Groundwater recharge Snowpack 01 natural sciences Arid 020801 environmental engineering Earth and Planetary Sciences (miscellaneous) Environmental science Precipitation Groundwater 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | Hydrogeology Journal. 27:1627-1643 |
| ISSN: | 1435-0157 1431-2174 |
| DOI: | 10.1007/s10040-019-01967-4 |
| Popis: | Climate change has the potential to substantially impact groundwater recharge, groundwater/surface-water dynamics, and surface-water quality. Changes in climate could be manifested as decreasing overall snowpack or an increase in the variability of snowpack year-to-year, and may affect wildfire occurrence and severity. Observed climatic extremes, including abnormal seasonal snowfall (both drought and extreme precipitation) and wildfires, have occurred in recent years in a semi-arid region of the Great Basin in the western United States. These climatic extremes have caused focused groundwater recharge following winters with elevated snowfall (2011 and 2017). Groundwater recharge calculated using the water-table fluctuation method, for periods following the elevated snowfall, was more than 10 times greater than previous studies in the basin that utilized distributed recharge calculation methods. Caution must be exercised when using results of these calculations in subsequent analyses such as groundwater flow modeling, to assure that all required assumptions are met and that calculated recharge rates are spatially applicable. Although water-quality changes due to the elevated snowfall were not evident in the surface-water data, several geochemical constituents (Ba, Ca, K, Mg, Na, pH, and specific conductance) indicated statistically significant concentration differences following a downstream wildfire in the watershed (representing the climatic extreme of drought). Both recharge calculations and statistical evaluations of water chemistry were completed using an easily modified Python script, which could be utilized by water managers to aid in water-resource planning under potentially variable future climatic conditions. |
| Databáze: | OpenAIRE |
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