Effects of Irrigation on Water, Carbon, and Nitrogen Budgets in a Semiarid Watershed in the Pacific Northwest: A Modeling Study

Abstract

In this study, we use the Community Land Model Version 5 (CLM5) to investigate how irrigation modulates hydrologic and biogeochemical dynamics in the Upper Columbia‐Priest Rapids (UCPR) watershed, a typical semiarid watershed located in the northwestern United States dominated by cropland. To our knowledge, this constitutes the first application of CLM5 with landscape heterogeneity fully resolved over a watershed. The model is calibrated and evaluated against flux measurements from an AmeriFlux site and the Moderate Resolution Imaging Spectroradiometer (MODIS) products. Two numerical experiments (i.e., irrigated and rainfed) are performed at hyperresolution (~1 km) over the period of 2010–2018, accounting for realistic crop types and management practices. Our results show that irrigation fundamentally alters hydrologic and biogeochemical dynamics of the watershed. By adding 79.6 mm year−1 water in addition to the mean annual precipitation of 204.0 mm year−1, irrigation leads to increases in evapotranspiration and runoff, accompanied by shallower groundwater table depths. Increases in crop productivity in response to irrigation result in more carbon storage in the watershed, and drastically large seasonal fluctuations in soil organic carbon in response to changes in soil temperature and moisture. Irrigation also intensifies the rate of denitrification and mineralization during the growing season, enhancing the interactions between soil mineral nitrogen, the atmosphere, and freshwater systems. Our study demonstrates the potential of CLM5 as an effective tool for understanding hydrological and biogeochemical dynamics in highly managed semiarid watersheds.

Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis

“…First, data are rapidly increasing in volume and complexity. For example, there is increasing use of ensemble model runs (e.g., Harp et al, 2016;Koven et al, 2020;Cromwell et al, 2021) and very high-resolution simulations (Bisht et al, 2017;Zhu et al, 2020Zhu et al, , 2021, which are critical for watershed models and the global land-surface modeling community and result in very large output data volumes. Second, the data are extremely diverse across scientific domains and spatial and temporal scales.…”

Impact of Vegetation Physiology and Phenology on Watershed Hydrology in a Semiarid Watershed in the Pacific Northwest in a Changing Climate

“…The monthly climatology over 2000-2015 calculated based on NLDAS2 and observations from stations at the overlapping grid cells were then used to derive monthly averaged NLDAS2/observations ratios for solar radiation and wind, and the average monthly biases (i.e., NLDAS2-Observations) for air T. Finally, we apply the ratios and difference to the interpolated hourly NLDAS2 data on the other 1/16th grid cells to bias-correct the NLDAS2 data against the observational data, using the Bias-Correction Spatial Disaggregation (BCSD) method from Wood et al (2004). This is the same forcing data set used in Zhu et al (2020).…”

“…Interested readers are referred to Zhu et al. (2020) for details on model configuration and calibration.…”

“…We extend a 1-km CLM5 configuration validated over the historical period (B. Zhu et al, 2020) to the end of the 21st century under different scenarios of climate, CO 2 concentration, atmospheric N deposition, and fertilization rates data sets to test our hypothesis.…”

“…The model is fully calibrated and validated by comparing with in situ and remotely sensed datasets. Interested readers are referred to Zhu et al (2020) for details on model configuration and calibration.…”