CHOSEN: A synthesis of hydrometeorological data from intensively monitored catchments and comparative analysis of hydrologic extremes. Issue 11 (25th November 2021)

• Record Type: Journal Article
• Authors: Zhang, Liang; Moges, Edom; Kirchner, James W.; Coda, Elizabeth; Liu, Tianchi; Wymore, Adam S.; Xu, Zexuan; Larsen, Laurel G.
• Is Part Of: Hydrological processes. Volume 35:Issue 11(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-11-25
• Subjects: climate change -- comparative hydrology -- comprehensive hydrologic dataset -- hydrologic extremes -- intensively monitored catchments -- trends of extreme events; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.14429
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: Comparative hydrology has been hampered by limited availability of geographically extensive, intercompatible monitoring data on comprehensive water balance stores and fluxes. These limitations have, for example, restricted comprehensive assessment of multiple dimensions of wetting and drying related to climate change and hampered understanding of why widespread changes in precipitation extremes are uncorrelated with changes in streamflow extremes. Here, we address this knowledge gap and underlying data gap by developing a new data synthesis product and using that product to detect trends in the frequencies and magnitudes of a comprehensive set of hydroclimatic and hydrologic extremes. CHOSEN (Comprehensive Hydrologic Observatory Sensor Network) is a database of streamflow, soil moisture, and other hydroclimatic and hydrologic variables from 30 study areas across the United States. An accompanying data pipeline provides a reproducible, semi‐automated approach for assimilating data from multiple sources, performing quality assurance and control, gap‐filling and writing to a standard format. Based on the analysis of extreme events in the CHOSEN dataset, we detected hotspots, characterized by unusually large proportions of monitored variables exhibiting trends, in the Pacific Northwest, New England, Florida and Alaska. Extreme streamflow wetting and drying trends exhibited regional coherence. Drying trends in the Pacific Northwest and Southeast were often associated with trends in soil moisture and precipitation (Pacific Northwest) and evapotranspiration‐related variables (Southeast). In contrast, wetting trends in the upper Midwest and the Rocky Mountains showed few univariate associations with other hydroclimatic extremes, but their latitudes and elevations suggested the importance of changing snowmelt characteristics. On the whole, observed trends are incompatible with a 'drying‐in‐dry, wetting‐in‐wet' paradigm for climate‐induced hydrologic changes over land. Our analysis underscores the need for more extensive, longer‐term observational data for soil moisture, snow and evapotranspiration. Abstract : We used a data pipeline to synthesize streamflow, soil moisture, and other hydroclimatic data from 30 study areas across the United States to the CHOSEN dataset. We analyzed the magnitude and frequency trends of the hydrometeorological variables in the dataset and detected hotspots, characterized by unusually large proportions of monitored variables exhibiting trends, in the Pacific Northwest, New England, Florida, and Alaska. Results showed that changing low‐flow extremes were commonly associated with evapotranspiration trends.