Pervasive changes in stream intermittency across the United States

Abstract

Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of ‘perennial’ and ‘non-perennial’ are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future.

Hydrological Intensification Will Increase the Complexity of Water Resource Management

“…For ecosystems, longer periods of water limitation are particularly concerning due to the potential for interactions between declining soil moisture and rising atmospheric VPD which can stress plants from the perspective of both water supply and atmospheric demand (Humphrey et al., 2021). Longer periods of water limitation also have increased the prevalence and duration of no flow conditions in streams, causing some perennial systems to shift to intermittent flow (Zipper et al., 2021).…”

Quantifying Streamflow Depletion from Groundwater Pumping: A Practical Review of Past and Emerging Approaches for Water Management

“…2020), streamflow change (Zipper, Hammond, et al. 2021), and surface water metrics (Worland et al. 2018), to the best our knowledge, they have not been applied to streamflow depletion (though machine learning techniques have been used for metamodeling of streamflow depletion trained on numerical model output, as described in the “Numerical Models” section).…”

“…Recent applications have shown the ability of machine learning models to provide better predictions than physically based hydrological models of daily streamflow in both gaged and ungaged locations (Kratzert, Klotz, Herrnegger, et al 2019;Kratzert, Klotz, Shalev, et al 2019). While machine learning methods have been applied separately to estimate groundwater levels (Sahoo et al 2017), groundwater use (Majumdar et al 2020), streamflow change (Zipper, Hammond, et al 2021), and surface water metrics (Worland et al 2018), to the best our knowledge, they have not been applied to streamflow depletion (though machine learning techniques have been used for metamodeling of streamflow depletion trained on numerical model output, as described in the "Numerical Models" section). Simple machine learning techniques such as random forests have the advantages of (1) allowing for many predictors with nonlinear relationships to the response variable, (2) not being constrained by our current best understanding of process across scales, (3) reasonable transparency and interoperability through variable importance analysis, and (4) strong performance in prediction mode with reproducible uncertainty estimates (Addor et al 2018).…”

“…Streamflow depletion is particularly problematic when it causes streamflow to drop below environmental flows, defined as "the quantity, timing, and quality of freshwater flows and levels necessary to sustain aquatic ecosystems which, in turn, support human cultures, economies, sustainable livelihoods, and well-being" (Arthington et al 2018). Streamflow depletion has already impaired environmental flows around the world (Konikow and Leake 2014;de Graaf et al 2019), with diverse local impacts including transitions from perennial to non-perennial streams (Zimmer et al 2020;Zipper, Hammond, et al 2021), impairment of surface water right holders (Idaho Water Resource Board 2019) and collapse of aquatic ecosystems (Perkin et al 2017). Impairment of environmental flows due to streamflow depletion is anticipated to become more widespread in the future and will be exacerbated by climate change (de Graaf et al 2019).…”

“…2020; Zipper, Hammond, et al. 2021), impairment of surface water right holders (Idaho Water Resource Board 2019) and collapse of aquatic ecosystems (Perkin et al. 2017).…”