Geology topics

John C. Hammond

Publications and source records attributed to John C. Hammond.

43 records · Page 3Linked to original sources

USGS2021

The drying regimes of non-perennial rivers and streams

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.

Geophysical Research Letters↗

USGS2021

Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States

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.

contiguous United States↗

USGS2021

Managing nonperennial headwater streams in temperate forests of the United States

Forest management guidelines are designed to protect water quality from unintended effects of land use changes such as timber harvest, mining, or forest road construction. Although streams that periodically cease to flow (nonperennial) drain the majority of forested areas, these streams are not consistently included in forest management guidelines. This paper reviews management guidelines for nonperennial (intermittent and ephemeral) streams draining temperate forests in the continental U.S., evaluates potential impacts of land use activities on ecosystem services provided by these streams, and identifies information needed to incorporate nonperennial streams into water quality protection practices. For federally administered lands, national management guidance is deliberately nonprescriptive, deferring to regional and forest-level recommendations for both perennial and nonperennial streams. Most state guidelines recommend riparian management zone (RMZ) protection for perennial streams (48/50 states) and intermittent streams (45/50 states), but only Alaska and West Virginia require RMZs around ephemeral streams. Based on the National Hydrography Dataset, an average of 58% of forested land area in the U.S. drains to nonperennial headwater streams, making these stream types the most common connectors between forested lands and the aquatic system. Land uses that modify flow regimes in these streams can affect sediment and organic matter transport and distribution, stream temperature dynamics, and biogeochemical processing. Nonperennial streams also provide material subsidies to downstream waters and serve as temporary habitats for some aquatic species. However, limited research has examined how forest land uses affect ecosystem services and biota in these streams. Therefore we highlight a set of key questions about nonperennial streams in forests, not the least of which is simply understanding where headwater stream channels are located and associated patterns of flow duration. Although many questions remain, we also note where recent advances in data collection, modeling and process-level research provide opportunities to resolve uncertainties around nonperennial streams in forested landscapes of the continental U.S.

Forest Ecology and Management↗

USGS2021

Evaluating low flow patterns, drivers and trends in the Delaware River Basin

In the humid, temperate Delaware River Basin (DRB) where water availability is generally reliable, summer low flows can cause competition between various human and ecological water uses. As temperatures continue to rise, population increases and development expands, it is critical to understand historical low flow variability to anticipate and plan for future flows. Using a sample of 325 U.S. Geological Survey gages, we evaluated spatial patterns in several low flow metrics, the biophysical and climatic drivers of these metrics, and trends in low flows for two periods: 1950-2018 and 1980-2018. We calculated the annual 7-day low flow and date, low flow deficit as the departure below a long-term daily flow threshold and the number of discrete low flow periods below this threshold. We also aggregated several climate metrics to watershed scale and used existing watershed properties quantifying land cover, topography, soils, geology, and human activity. Random forest models were used to assess the hierarchy of variable importance in explaining mean-annual low flow variability for each low flow metric using all gages. We find muted regional patterns in mean-annual low flow and low flow variability, likely due to the myriad of anthropogenic, landscape, and flow modifications that obscure flow regimes from their natural characteristics. In contrast, individual years show markedly different spatial patterns in low flow magnitude and severity. Coincident with increases in precipitation, 7-day low flows have generally increased and low flow deficits decreased for both 1950-2018 and 1980-2018 periods. However, 7-day low flows have decreased in the Coastal Plain physiographic province where water use and impervious area have increased in recent decades, highlighting the effects of land and water management on low flows. With continued change expected in the DRB, additional research needs are highlighted to enable estimation of future low flows and to plan for periods of prolonged low flow.

Delaware, New Jersey, New York, Pennsylvania↗

USGS2020

Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S.

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.

Water Resources Research↗

USGS2020

Zero or not? Causes and consequences of zero-flow stream gage readings

Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed‐scale processes. When stream gages read zero, this may indicate that the stream has dried at this location; however, zero‐flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero‐flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to inaccurate hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero‐flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human‐driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero‐flow interpretations. We also highlight additional methods for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero‐flow gage readings and implications for reach‐ and watershed‐scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero‐flows will only attain greater importance in a more variable and changing hydrologic climate.

WIREs Water↗

USGS2020

Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model

The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of subgrid or subwatershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey National Hydrologic Model infrastructure with the Precipitation-Runoff Modeling System (NHM-PRMS) represents the subgrid variability of SWE with snow depletion curves (SDCs), which relate snow-covered area to watershed-average SWE during the snowmelt period. The main objective of this research was to evaluate the sensitivity of simulated runoff to SDC representation within the NHM-PRMS across the continental United States (CONUS). SDCs for the model experiment were derived assuming a range of SWE coefficient of variation (CV) values and a lognormal probability distribution function. The NHM-PRMS was simulated at a daily time step for each SDC over a 14-year period. Results highlight that increasing the subgrid snow variability (by changing the SDC) resulted in a consistently slower snowmelt rate and longer snowmelt duration when averaged across the hydrologic response unit scale. Simulated runoff was also found to be sensitive to SDC representation, as increases in the subgrid SWE CV by 1.0 resulted in decreases in runoff ratio by as much as 12 percent in snow-dominated regions of the CONUS. Simulated decreases in runoff associated with slower snowmelt rates were approximately inversely proportional to increases in simulated evapotranspiration. High snow persistence and peak SWE:annual precipitation combined with a water limited dryness index were associated with the greatest runoff sensitivity to changing snowmelt. Results from this study highlight the importance of carefully parameterizing SDCs for hydrologic modeling. Furthermore, improving model representation of snowmelt input variability and its relation to runoff generation processes is shown to be an important consideration for future modeling applications.

Hydrological Processes↗