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Adrian A. Harpold

Publications and source records attributed to Adrian A. Harpold.

3 recordsLinked to original sources

The influence of mountain streamflow on nearshore ecosystem metabolism in a large, oligotrophic lake across a drought and a wet year

The influence of streamflow can be highly heterogeneous around lake edges, making it challenging to predict how benthic productivity in the littoral zone responds to hydroclimatic change. The degree to which streamflow affects nearshore productivity varies as a function of catchment characteristics, internal lake morphometry, and processes. This study investigates the relative influence of streamflow on nearshore metabolism (e.g., gross primary productivity [GPP], ecosystem respiration [ER], and net ecosystem productivity [NEP]) for shores with large, small, or no stream inflows (four locations across two shores) during two contrasting water years (one drought and one wet) in Lake Tahoe (Nevada/California, USA). Using Bayesian structural equation modeling, we found streamflow decreased water temperature, benthic light, and GPP across both years. Compared to the drought year, the subsequent wet year had 54% higher annual streamflow, 37% less light, and lower NEP at locations with large or small inflows (39% Δ −0.32 mmol O₂ m −3 d −1% and 49% Δ −1.19 mmol O₂ m −3 d −1 , respectively). During the wet year, we observed a 68% increase in the negative association between streamflow and nearshore GPP at the large inflow and a 62% decrease in the positive association between streamflow and GPP at the small inflow. This work demonstrates how oligotrophic littoral productivity varies across shorelines and in response to hydrological conditions, with streamflow and precipitation exerting contrasting effects depending on the proximity to inflowing streams. Our results suggest future lake responses to climate volatility depend on spatial and temporal hydrologic connectivity to catchments and upland processes.

California, Nevada

Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly

Atmospheric rivers (ARs) drive most riverine floods on the United States (U.S.) West Coast. However, estimating flood risk based solely on AR intensity and duration is challenging because precipitation phase, antecedent conditions, and physical watershed characteristics (e.g., slope and soil depth) can influence the magnitude of floods. Here, we analyze how antecedent soil moisture (ASM) conditions contribute to variability in streamflow during AR events and how that changes across climatic regimes and physiography in 122 U.S. West Coast watersheds. We identify a robust non-linear relationship between streamflow and ASM during ARs in 89% of watersheds. The inflection point in this relationship represents a watershed-specific critical ASM threshold, above which event maximum streamflow is, on average, two to four and a half times larger. Wet ASM conditions amplify the hydrologic impacts of more frequent but weaker, lower moisture transport AR events, while dry ASM conditions attenuate the hydrologic impacts that stronger, higher moisture transport AR events could otherwise cause. Our research shows that watersheds prone to ASM-amplified streamflows have higher evaporation ratios, lower cold-season precipitation, lower snow-to-rain ratios, and shallower, clay-rich soils. Higher evaporation and lower precipitation lead to greater ASM variability during the cold season, increasing streamflow during wet periods and buffering streamflow during dry periods. Lower snow fraction and shallower soils limit the antecedent water storage capacity of a watershed, contributing to greater sensitivity of streamflow peaks to ASM variability. Incorporating ASM thresholds into hydrologic models in these regions prone to AR-amplified streamflow could improve forecasts and decrease uncertainty.

California, Nevada, Oregon, Washington

Hydrogeomorphology explains acidification-driven variation in aquatic biological communities in the Neversink Basin, USA

Describing the distribution of aquatic habitats and the health of biological communities can be costly and time-consuming; therefore, simple, inexpensive methods to scale observations of aquatic biota to watersheds that lack data would be useful. In this study, we explored the potential of a simple “hydrogeomorphic” model to predict the effects of acid deposition on macroinvertebrate, fish, and diatom communities in 28 sub-watersheds of the 176-km 2 Neversink River basin in the Catskill Mountains of New York State. The empirical model was originally developed to predict stream-water acid neutralizing capacity (ANC) using the watershed slope and drainage density. Because ANC is known to be strongly related to aquatic biological communities in the Neversink, we speculated that the model might correlate well with biotic indicators of ANC response. The hydrogeomorphic model was strongly correlated to several measures of macroinvertebrate and fish community richness and density, but less strongly correlated to diatom acid tolerance. The model was also strongly correlated to biological communities in 18 sub-watersheds independent of the model development, with the linear correlation capturing the strongly acidic nature of small upland watersheds (<1 km 2 ). Overall, we demonstrated the applicability of geospatial data sets and a simple hydrogeomorphic model for estimating aquatic biological communities in areas with stream-water acidification, allowing estimates where no direct field observations are available. Similar modeling approaches have the potential to complement or refine expensive and time-consuming measurements of aquatic biota populations and to aid in regional assessments of aquatic health.

New York