skip to main content

Search for: All records

Award ID contains: 2025982

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract

    To increase the adoption and reliability of low impact development (LID) practices for stormwater runoff management and other co-benefits, we must improve our understanding of how climate (i.e. patterns in incoming water and energy) affects LID hydrologic behavior and effectiveness. While others have explored the effects of precipitation patterns on LID performance, the role of energy availability and well-known ecological frameworks based on the aridity index (ratio of potential evapotranspiration (ET) to precipitation, PET:P) such as Budyko theory are almost entirely absent from the LID scientific literature. Furthermore, it has not been tested whether these natural system frameworks can predict the fate of water retained in the urban environment when human interventions decrease runoff. To systematically explore how climate affects LID hydrologic behavior, we forced a process-based hydrologic model of a baseline single-family parcel and a parcel with infiltration-based LID practices with meteorological records from 51 U.S. cities. Contrary to engineering design practice which assumes precipitation intensity is the primary driver of LID effectiveness (e.g. through use of design storms), statistical analysis of our model results shows that the effects of LID practices on long-term surface runoff, deep drainage, and ET are controlled by the relative balance and timingmore »of water and energy availability (PET:P, 30 d correlation of PET and P) and measures of precipitation intermittency. These results offer a new way of predicting LID performance across climates and evaluating the effectiveness of infiltration-based, rather than retention-based, strategies to achieve regional hydrologic goals under current and future climate conditions.

    « less
  2. The urban heat island (UHI) effect, the phenomenon by which cities are warmer than rural surroundings, is increasingly important in a rapidly urbanizing and warming world, but fine-scale differences in temperature within cities are difficult to observe accurately. Networks of air temperature (Tair) sensors rarely offer the spatial density needed to capture neighborhood-level disparities in warming, while satellite measures of land surface temperature (LST) do not reflect the air temperatures that people physically experience. This analysis combines both Tair measurements recorded by a spatially-dense stationary sensor network in Dane County, Wisconsin, and remotely-sensed measurements of LST over the same area—to improve the use and interpretation of LST in UHI studies. The data analyzed span three summer months (June, July, and August) and eight years (2012–2019). Overall, Tair and LST displayed greater agreement in spatial distribution than in magnitude. The relationship between day of the year and correlation was fit to a parabolic curve (R2 = 0.76, p = 0.0002) that peaked in late July. The seasonal evolution in the relationship between Tair and LST, along with particularly high variability in LST across agricultural land cover suggest that plant phenology contributes to a seasonally varying relationship between Tair and LST measurementsmore »of the UHI.« less
  3. Lakes are key ecosystems within the global biogeosphere. However, the bottom-up controls on the biological productivity of lakes, including surface temperature, ice phenology, nutrient loads and mixing regime, are increasingly altered by climate warming and land-use changes. To better understand the environmental drivers of lake productivity, we assembled a dataset on chlorophyll-a concentrations, as well as associated water quality parameters and surface solar irradiance, for temperate and cold-temperate lakes experiencing seasonal ice cover. We developed a method to identify periods of rapid algal growth from in situ chlorophyll-a time series data and applied it to measurements performed between 1964 and 2019 across 357 lakes, predominantly located north of 40°. Long-term trends show that the algal growth windows have been occurring earlier in the year, thus potentially extending the growing season and increasing the annual productivity of northern lakes. The dataset is also used to analyze the relationship between chlorophyll-a growth rates and solar irradiance. Lakes of higher trophic status exhibit a higher sensitivity to solar radiation, especially at moderate irradiance values during spring. The lower sensitivity of chlorophyll-a growth rates to solar irradiance in oligotrophic lakes likely reflects the dominant role of nutrient limitation. Chlorophyll-a growth rates are significantly influencedmore »by light availability in spring but not in summer and fall, consistent with a switch to top-down control of summer and fall algal communities. The growth window dataset can be used to analyze trends in lake productivity across the northern hemisphere or at smaller, regional scales. We present some general trends in the data and encourage other researchers to use the open dataset for their own research questions.« less