ABSTRACT:

Code provided here was used for processing and analyses of data for a manuscript published in Hydrological Processes entitled, 'Water isotopic composition traces source and dynamics of water supply in a semi-arid agricultural landscape'. Data visualizations and analyses were performed in R programming software (version 4.2.1). Generalized linear mixed model statistical analysis was performed using R package 'nlme' (version 3.1-160). Data analyzed for this manuscript include isotopic compositions of water collected from rain, snowmelt, terrace soil water, terrace groundwater, riparian ground and surface water, and stream water. Volume of terrace soil water was also collected. We analyzed meteorological and soil climate variables, including cumulative snow water equivalent, precipitation volume, atmospheric temperature, relative humidity, soil moisture content, and soil temperature. Data collection methods are described in detail in the referenced manuscript and dataset. Data were analyzed to understand soil, aquifer, and stream hydrological processes and integration of source waters in a semi-arid, non-irrigated agricultural landscape.

ABSTRACT:

Data and code provided here were used for analyses for a manuscript published in JGR Biogeosciences entitled, 'Riparian Processes in Semi-Arid Landscapes: Understanding Controls on Nitrate Loss and Sulfate Production in Agricultural Stream Corridors'. Data were collected at variable frequencies between 2013 and 2022. Terrace groundwater was collected from 2013 to 2022 from wells and springs (n = 6) across the Moccasin terrace landform. Riparian groundwater was collected from 2021 to 2022 across three stream corridors on the Moccasin terrace. Stream water was collected from 2013 to 2022 from streams draining the Moccasin terrace. All groundwater and surface water were sampled using a peristaltic pump (Geotech Environmental Equipment; Denver, CO) and pumped through a 0.45-μm capsule filter (Geotech Environmental Equipment; Denver, CO) into 24 mL glass vials without headspace and 60 mL HDPE vials with headspace with duplicates. Data were collected to assess geochemical composition of landscape water to understand soil, aquifer, and stream biogeochemical processes in a semi-arid, non-irrigated agricultural landscape. Data visualizations and analyses were performed in R programming software (version 4.2.2). Generalized linear mixed model statistical analysis was performed using R package 'lme4' (version 1.1–35.1).