An official website of the United States government
Abstract Summer streamflow predictions are critical for managing water resources; however, warming‐induced shifts from snow to rain regimes impact low‐flow predictive models. Additionally, reductions in snowpack drive earlier peak flows and lower summer flows across the western United States increasing reliance on groundwater for maintaining summer streamflow. However, it remains poorly understood how groundwater contributions vary interannually. We quantify recession limb groundwater (RLGW), defined as the proportional groundwater contribution to the stream during the period between peak stream flow and low flow, to predict summer low flows across three diverse western US watersheds. We ask (a) how do snow and rain dynamics influence interannual variations of RLGW contributions and summer low flows?; (b) which watershed attributes impact the effectiveness of RLGW as a predictor of summer low flows? Linear models reveal that RLGW is a strong predictor of low flows across all sites and drastically improves low‐flow prediction compared to snow metrics at a rain‐dominated site. Results suggest that strength of RLGW control on summer low flows may be mediated by subsurface storage. Subsurface storage can be divided into dynamic (i.e., variability saturated) and deep (i.e., permanently saturated) components, and we hypothesize that interannual variability in dynamic storage contribution to streamflow drives RLGW variability. In systems with a higher proportion of dynamic storage, RLGW is a better predictor of summer low flow because the stream is more responsive to dynamic storage contributions compared to deep‐storage‐dominated systems. Overall, including RLGW improved low‐flow prediction across diverse watersheds.
more »
« less
On the Effect of Nonlinear Recessions on Low Flow Variability: Diagnostic of an Analytical Model for Annual Flow Duration Curves
Abstract Predicting the proportion of the water year a given stream will remain at or above various flow thresholds is critically important for making sound water management decisions. Flow duration curves (FDCs) succinctly capture this information using all data available over some historical period, while annual flow duration curves (AFDCs) instead use data from each individual water year. Analyzing the population of AFDCs, and in particular the tails of this distribution, can allow water managers to better prepare for years with extreme streamflow conditions. However, long time series of observations are necessary to capture interannual streamflow variations and are problematic to obtain in rapidly changing and poorly gauged catchments. By incorporating a process‐based model to construct AFDCs based on daily rainfall statistics and flow recession characteristics, the proposed approach is a first step toward addressing this challenge. Results indicate that prediction performance varies substantially across flow quantiles and that the current model fails to properly capture the interannual variability of low flows. Numerical analyses attributed these errors to nonlinearity in storage‐discharge relation, rather than cross‐scale streamflow correlations and non‐Poissonian rainfall, explaining the origin of commonly observed heavy‐tailed behavior in low flow quantiles. We present a case study on hydroelectric power generation, showing that faithfully capturing both interannual streamflow variability and recession nonlinearity has important implications for installation profitability.
more »
« less
- Award ID(s):
- 1331940
- PAR ID:
- 10371963
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 55
- Issue:
- 7
- ISSN:
- 0043-1397
- Page Range / eLocation ID:
- p. 6125-6137
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Tropical regions are experiencing high rates of forest cover loss coupled with changes in the volume and timing of rainfall. These shifts can compromise streamflow and water provision, highlighting the need to identify how forest cover influences streamflow generation under variable rainfall conditions. Although rainfall is the key driver of streamflow regimes, the role of forests is less clear, particularly in tropical regions where forest loss is an ongoing risk. Forest cover loss alters evapotranspiration, rainfall infiltration and storage, and may increase stream ecosystem vulnerability to rainfall extremes. Puerto Rico, an island with spatially heterogenous forest cover and a marked geographic rainfall gradient, is projected to experience more frequent droughts and flash flooding. Using 15‐min streamflow data collected between 2005 and 2016 from 20 US Geological Survey stream gages and 3‐hourly Multi‐Source Weighted‐Ensemble Precipitation rainfall estimates, we utilized flow‐duration curves and linear mixed regression models to examine the role of forest cover in regulating the timing and volume of streamflow. The mixed model approach helps to account for differences in watershed characteristics. We determined the effects of rainfall and forest cover on low and peak flows in Puerto Rican streams, then evaluated changes in these relationships under dry and wet antecedent rainfall conditions. Watersheds with high forest cover had consistently greater low and peak streamflow than deforested ones under all rainfall conditions, although the effect was more marked during wet antecedent conditions, suggesting that peak flow is largely the result of saturation excess overland flow. During dry antecedent rainfall conditions, highly forested watersheds had higher streamflow than deforested ones, suggesting greater hillslope storage and release may also be at play. Our results demonstrate that forest cover generated a net increase in hillslope infiltration and storage and may lessen drought impacts on streamflow in Puerto Rico. Resilience to prolonged drought may be limited by finite water storage potential in this steep, mountainous setting, highlighting maintenance of forest cover as an important water management strategy to increase infiltration.more » « less
-
Understanding how diverse headwater streams contribute water downstream is critical for accurate modelling of seasonal flow dynamics in larger systems. This study investigated how headwater catchments, with diverse subsurface storage, influence downstream flows within Lookout Creek—a 62 km2, 5th‐order catchment in the rain‐snow transition zone in western Oregon, USA. We analysed one year of hydrometric and water stable isotope data collected at 10 stream locations, complemented by a decade of precipitation isotopic data. As expected, isotopic data revealed that most of the streamflow was sourced from large fall and winter storms. Generally, stream isotope ratios decrease with elevation. However, some streams had higher isotopic values than expected, reflecting the influence of isotopically heavy storms and relatively low storage. Other streams that tended to have low flow variability in response to precipitation inputs had lower isotopic values, indicating higher elevation water sources than their topographic watershed boundaries. Both hydrometric data and water isotope‐based end‐member mixing models suggest storage differences among headwater catchments influenced the seasonal water contributions from tributaries. Most notably, the contributions of Cold and Longer Creeks, which occupy less than 10% of the Lookout Creek drainage area, sustain up to 50% of the streamflow in the summer. These catchments have high storage and high groundwater contributions, as evidenced by flat flow duration curves. Finally, our data suggest that geologic variability and geomorphic complexity (presence of earthflows and landslides) can be indicators of storage that dramatically influence water movement through the critical zone, the variation in streamflow, and the response of streams to precipitation events. Heterogeneity in headwater catchment storage is key to understanding flow dynamics in mountainous regions and the response of streams to changes in climate and other disturbances.more » « less
-
Abstract As stormwater control measures (SCMs) capture surface runoff from impervious areas, a shift in the water balance and flow regime components may emerge in urban watersheds, but the amount of SCM treatment needed to detectably shift these components may vary. We used the Soil and Water Assessment Tool (SWAT) hydrologic model to assess the sensitivity of 16 hydrologic metrics as an increasingly dense rain garden SCM network was applied across the West Creek watershed, near Cleveland, Ohio (USA). As the area treated by SCMs increased, annual baseflow increases matched decreases in surface runoff, while water yield and evapotranspiration changes remained small. The stream's peak response to rainfall decreased with SCM implementation across storm sizes, ranging from the threshold rainfall depth (4.8 mm) to values higher than the design storm of a single rain garden (19 mm). SCM networks draining >20% of directly connected impervious area (DCIA) significantly decreased the magnitude of discharges with a return period of less than 1 year, the percentage of time above mean flow, and flashiness. Recession slopes and annual 1‐ and 7‐day low flows exhibited a slight response that fell within uncertainty limits of the model. Water balance and rainfall response metrics exhibited the greatest sensitivity to different intensities of stormwater management, while infrequent high and low flows were resistant to detectable change even at high levels of SCM treatment when model uncertainty was included.more » « less
-
Abstract Rainfall in southern California is highly variable, with some fluctuations explainable by climate patterns. Resulting runoff and heightened streamflow from rain events introduces freshwater plumes into the coastal ocean. Here we use a 105-year daily sea surface salinity record collected at Scripps Pier in La Jolla, California to show that El Niño Southern Oscillation and Pacific Decadal Oscillation both have signatures in coastal sea surface salinity. Averaging the freshest quantile of sea surface salinity over each year’s winter season provides a useful metric for connecting the coastal ocean to interannual winter rainfall variability, through the influence of freshwater plumes originating, at closest, 7.5 km north of Scripps Pier. This salinity metric has a clear relationship with dominant climate phases: negative Pacific Decadal Oscillation and La Niña conditions correspond consistently with lack of salinity anomaly/ dry winters. Fresh salinity anomalies (i.e., wet winters) occur during positive phase Pacific Decadal Oscillation and El Niño winters, although not consistently. This analysis emphasizes the strong influence that precipitation and consequent streamflow has on the coastal ocean, even in a region of overall low freshwater input, and provides an ocean-based metric for assessing decadal rainfall variability.more » « less
