title: Coherence among climate signals, precipitation, and groundwater.
abstract: Climate signals may affect groundwater level at different time scales in different geographical regions, and those patterns or time scales can be estimated using coherence analysis. This study shows that the synthesis effort required to search for patterns at the physical geography scale is possible, and this approach should be applicable in other regions of the world. The relations between climate signals, Southern Oscillation Index, Pacific Decadal Oscillation, North Atlantic Oscillation, North Pacific Pattern (SOI, PDO, NAO, and NP), precipitation, and groundwater level in three geographical areas of Wisconsin are examined using a three-tiered coherence analysis. In the high frequency band (<4(-1) cycles/year), there is a significant coherence between four climate signals and groundwater level in all three areas. In the low frequency band (>8(-1) to ≤23(-1) cycles/year), we found significant coherence between the SOI and NP signals and groundwater level in the forested area, characterized by shallow wells constructed in sand and gravel aquifers. In the high frequency band, there is significant coherence between the four climate signals and precipitation in all three areas. In the low frequency band, the four climate signals have effect on precipitation in the agricultural area, and SOI and NP have effect on precipitation in the forested and driftless areas. Precipitation affects groundwater level in all three areas, and in high, low and intermediate frequency bands. In the agricultural area, deeper aquifers and a more complex hydrostratigraphy and land use dilute the effect of precipitation on groundwater level for interdecadal frequencies.
authors.affiliation: Department of Civil Engineering and Mechanics, University of Wisconsin-Milwaukee, 3200 N. Cramer Street, Milwaukee, WI 53211, USA. rghanbari@ucmerced.edu
authors.forename: Reza Namdar
authors.initials: RN
authors.lastname: Ghanbari
authors.forename: Hector R
authors.initials: HR
authors.lastname: Bravo
mesh_terms: D002980:Climate; D005843:Geography; D011891:Rain; D013223:Statistics as Topic; D058438:Water Cycle; D014881:Water Supply; D014922:Wisconsin