John Hammond

Dr. John Hammond

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Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 January 2021 in Geophysical Research Letters
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Journal Article
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JHJohn Hammond
John Hammond
MZMargaret Zimmer
Margaret Zimmer
Margaret ShanafieldMargaret Shanafield
Margaret Shanafield
KKKendra Elena Kaiser
Kendra Elena Kaiser
SGSarah E. Godsey
Sarah E. Godsey
DADaniel C. Allen
Daniel C. Allen
Over half of global rivers and streams lack perennial flow, and understanding the distribution and drivers of their flow regimes is critical for understanding their hydrologic, biogeochemical, and ecological functions. We analyzed nonperennial flow regimes using 540 U.S. Geological Survey watersheds across the contiguous United States from 1979 to 2018. Multivariate analyses revealed regional differences in no‐flow fraction, date of first no flow, and duration of the dry‐down period, with further divergence between natural and human‐altered watersheds. Aridity was a primary driver of no‐flow metrics at the continental scale, while unique combinations of climatic, physiographic and anthropogenic drivers emerged at regional scales. Dry‐down duration showed stronger associations with nonclimate drivers compared to no‐flow fraction and timing. Although the sparse distribution of nonperennial gages limits our understanding of such streams, the watersheds examined here suggest the important role of aridity and land cover change in modulating future stream drying.

27 April 2020 in WIREs Water
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MZMargaret A. Zimmer
Margaret A. Zimmer
KKKendra Elena Kaiser
Kendra Elena Kaiser
JBJoanna R. Blaszczak
Joanna R. Blaszczak
SZSamuel Zipper
Samuel Zipper
JHJohn Hammond
John Hammond
DADaniel C. Allen
Daniel C. Allen

10 July 2018 in International Journal of Climatology
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Journal Article
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JHJohn Hammond
John Hammond
FSFreddy A. Saavedra
Freddy A. Saavedra
SKStephanie K. Kampf
Stephanie K. Kampf
Seasonal snow is a critical component of the surface energy balance and hydrologic cycle, yet global maps of seasonal snow boundaries are not readily available. Snow persistence (SP), the fraction of a year that snow is present on the ground, is an easily globally observed snow metric that can be used to map snow zones globally. Here we map snow zones across the globe using SP calculated from the MODIS10A2 product; evaluate how SP relates to precipitation, temperature, and climate indices; and examine trends in annual SP for 2001–2016. In the Northern Hemisphere, intermittent, seasonal, and permanent snow zones occupy a far greater percent (63%) of the land surface than in the Southern Hemisphere (95%). SP is most variable from year to year near the snow line, which has a relatively consistent decrease in elevation with increasing latitude across all continents. At lower elevations, SP is typically best correlated with temperature, whereas precipitation has greater relative importance for SP at high elevations. SP is best correlated with the North Atlantic Oscillation in all continents except South America, where the Southern Annular Mode is a stronger influence, and Africa, where the strongest correlation is with the Oceanic Niño Index. Areas with decreasing SP trends cover 5.8% of snow zone areas, whereas those with increasing trends cover 1.0% of this area. The largest areas of declining SP are in the seasonal snow zones of the Northern Hemisphere. Trend patterns vary within individual regions, with elevation, and on windward‐leeward sides of the mountains. This study supplies a framework for comparing snow between regions, highlights areas with snow changes, and can facilitate analyses of why snow changes vary within and between regions.

18 April 2020 in Water Resources Research
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JHJohn Hammond
John Hammond
Stephanie KampfStephanie Kampf
Stephanie Kampf
Streamflow generation in mountain watersheds is strongly influenced by snow accumulation and melt, and multiple studies have found that snow loss leads to earlier snowmelt timing and declines in annual streamflow. However, hydrologic responses to snow loss are heterogeneous, and not all areas experience streamflow declines. This research examines whether streamflow generation is different for rainfall versus snowmelt inputs. We compiled a sample of 57 small U.S. Geological Survey watersheds in the western United States containing a Natural Resource Conservation Service Snow Telemetry site and having ratios of mean annual peak snow water equivalent to precipitation ratios >0.25. Daily streamflow was separated into quickflow and baseflow using a digital filter, and quickflow was then divided into quickflow response intervals using thresholds in quickflow slope. Each quickflow response interval was categorized by its fraction of input from snowmelt. Most sites exhibited two streamflow generation peaks each year, with one peak in the winter when runoff efficiency is greatest, and the second in the spring during peak snowmelt input. On average, study watersheds were dominated by snowmelt inputs (70%), and snowmelt and mixed inputs usually generated greater streamflow than rainfall because of higher inputs and longer durations. However, rainfall produced high streamflow generation in winter, when watersheds have their highest runoff efficiency (81%) across all input types. We demonstrate that while snowmelt is important for streamflow generation due to high input over long periods, increases in rain and mixed input during wet winter periods can countervail tendencies for reduced streamflow with declining snowpacks.

16 July 2021 in Geophysical Research Letters
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APAdam N. Price
Adam N. Price
CJC. Nathan Jones
C. Nathan Jones
JHJohn Hammond
John Hammond
MZMargaret A. Zimmer
Margaret A. Zimmer
SZSamuel Zipper
Samuel Zipper
The flow regime paradigm is central to the aquatic sciences, where flow drives critical functions in lotic systems. Non‐perennial streams comprise the majority of global river length, thus we extended this paradigm to stream drying. Using 894 USGS gages, we isolated 25,207 drying events from 1979 to 2018, represented by a streamflow peak followed by no flow. We calculated hydrologic signatures for each drying event and using multivariate statistics, grouped events into drying regimes characterized by: (a) fast drying, (b) long no‐flow duration, (c) prolonged drying following low antecedent flows, (d) drying without a distinctive hydrologic signature. 77% of gages had more than one drying regime at different times within the study period. Random forests revealed land cover/use are more important to how a river dries than climate or physiographic characteristics. Clustering stream drying behavior may allow practitioners to more systematically adapt water resource management practices to specific drying regimes or rivers.

30 August 2022 in Water Resources Research
Verified
Journal Article
Closed access
JHJohn Hammond
John Hammond
CSCaelan Simeone
Caelan Simeone
JHJory S. Hecht
Jory S. Hecht
GHGlenn A. Hodgkins
Glenn A. Hodgkins
MLMelissa Lombard
Melissa Lombard
APAdam N. Price
Adam N. Price