Soil infiltration rates are underestimated by models in an urban watershed in central North Carolina, USA.

Stormwater management problems are expanding as urbanization continues and precipitation patterns are increasingly extreme. Urban soils are often more disturbed and compacted than non-urban soils, therefore, rainfall run-off estimates based on models designed for non-urban soils may not be accurate due to altered soil infiltration rates. Our objective was to quantify soil infiltration rates across an urban watershed and compare them to estimates from rainfall-runoff models commonly used in stormwater management (Horton and Green-Ampt) as well as an alternate, random-forest model created using available geospatial data. We measured infiltration rates and collected data on soil properties (texture, bulk density) and context (land use, ground cover, time since development) at 89 points across the 102 ha Walnut Creek watershed in Raleigh, North Carolina (USA). Forest land covers and forest ground covers (leaf litter) had the highest infiltration capacities; however, all of our measurements indicate that urban soils in the Walnut Creek watershed are able to absorb most precipitation events and are likely capable of infiltrating additional urban stormwater runoff. Comparisons between observations and the rainfall-runoff model estimates reveal that both underestimated urban soil infiltration rates. Despite higher than expected urban soil infiltration capacity, stormwater management remains a challenge in this urban watershed. Therefore, to reduce stormwater runoff from impervious surfaces through soil infiltration, impervious surfaces should be disconnected, especially adjacent to new development, and urban forests should be conserved. Further, because our random forest model more accurately captured watershed infiltration rates than the rainfall-runoff models, we propose this type of machine learning approach as an alternative method for informing stormwater management and prioritizing areas for impervious disconnection.

Restoring forest structure and process stabilizes forest carbon in wildfire-prone southwestern ponderosa pine forests.

Changing climate and a legacy of fire-exclusion have increased the probability of high-severity wildfire, leading to an increased risk of forest carbon loss in ponderosa pine forests in the southwestern USA. Efforts to reduce high-severity fire risk through forest thinning and prescribed burning require both the removal and emission of carbon from these forests, and any potential carbon benefits from treatment may depend on the occurrence of wildfire. We sought to determine how forest treatments alter the effects of stochastic wildfire events on the forest carbon balance. We modeled three treatments (control, thin-only, and thin and burn) with and without the occurrence of wildfire. We evaluated how two different probabilities of wildfire occurrence, 1% and 2% per year, might alter the carbon balance of treatments. In the absence of wildfire, we found that thinning and burning treatments initially reduced total ecosystem carbon (TEC) and increased net ecosystem carbon balance (NECB). In the presence of wildfire, the thin and burn treatment TEC surpassed that of the control in year 40 at 2%/yr wildfire probability, and in year 51 at 1%/yr wildfire probability. NECB in the presence of wildfire showed a similar response to the no-wildfire scenarios: both thin-only and thin and burn treatments increased the C sink. Treatments increased TEC by reducing both mean wildfire severity and its variability. While the carbon balance of treatments may differ in more productive forest types, the carbon balance benefits from restoring forest structure and fire in southwestern ponderosa pine forests are clear.

Riparian buffers increase future baseflow and reduce peakflows in a developing watershed.

Land conversion and climate change are stressing freshwater resources. Riparian areas, streamside vegetation/forest land, are critical for regulating hydrologic processes and riparian buffers are used as adaptive management strategies for mitigating land conversion effects. However, our ability to anticipate the efficacy of current and alternative riparian buffers under changing conditions remains limited. To address this information gap, we simulated hydrologic responses for different levels of buffer protection under a future scenario of land/climate change through the year 2060. We used the Soil and Water Assessment Tool (SWAT) to project future streamflow in the Upper Neuse River watershed in North Carolina, USA. We tested the capacity of riparian buffers to mitigate the effects of future land use and climate change on daily mean streamflow under three buffer treatments: present buffer widths and fully forested 15 m and 30 m buffers throughout the basin. The treatments were tested using a combination of a future climate change scenario and landcover projections that indicated a doubling of low-intensity development between 2017 and 2060. In areas with >50 % development, the 30 m buffers were particularly effective at increasing average daily streamflow during the lowest flow events by 4 % and decreasing flow during highest flow events by 3 % compared to no buffer protection. In areas between 20 and 50 % development, both 15 m and 30 m buffers reduced low flow by 8 % with minimal effects on high flow. Results indicate that standardized buffers might be more effective at a local scale with further research needing to focus on strategic buffer placement at the watershed scale. These findings highlight a novel approach for integrating buffers into hydrologic modeling and potential for improved methodology. Understanding the effects of riparian buffers on streamflow is crucial given the pressing need to develop innovative strategies that promote the conservation of invaluable ecosystem services.

Forested watersheds provide the highest water quality among all land cover types, but the benefit of this ecosystem service depends on landscape context.

Conversion of natural land cover can degrade water quality in water supply watersheds and increase treatment costs for Public Water Systems (PWSs), but there are few studies that have fully evaluated land cover and water quality relationships in mixed use watersheds across broad hydroclimatic settings. We related upstream land cover (forest, other natural land covers, development, and agriculture) to observed and modeled water quality across the southeastern US and specifically at 1746 PWS drinking water intake facilities. While there was considerable complexity and variability in the relationship between land cover and water quality, results suggest that Total Nitrogen (TN), Total Phosphorus (TP) and Suspended Sediment (SS) concentrations decrease significantly with increasing forest cover, and increase with increasing developed or agricultural cover. Catchments with dominant (>90 %) agricultural land cover had the greatest export rates for TN, TP, and SS based on SPARROW model estimates, followed by developed-dominant, then forest- and other-natural-dominant catchments. Variability in modeled TN, TP, and SS export rates by land cover type was driven by variability in natural background sources and catchment characteristics that affected water quality even in forest-dominated catchments. Both intake setting (i.e., run-of-river or reservoir) and upstream land cover were important determinants of water quality at PWS intakes. Of all PWS intakes, 15 % had high raw water quality, and 85 % of those were on reservoirs. Of the run-of-river intakes with high raw water quality, 75 % had at least 50 % forest land cover upstream. In addition, PWS intakes obtaining surface water supply from smaller upstream catchments may experience the largest losses of natural land cover based on projections of land cover in 2070. These results illustrate the complexity and variability in the relationship between land cover and water quality at broad scales, but also suggest that forest conservation can enhance the resilience of drinking water supplies.

Terra incognita: The unknown risks to environmental quality posed by the spatial distribution and abundance of concentrated animal feeding operations.

Concentrated animal feeding operations (CAFOs) pose wide ranging environmental risks to many parts of the US and across the globe, but datasets for CAFO risk assessments are not readily available. Within the United States, some of the greatest concentrations of CAFOs occur in North Carolina. It is also one of the only states with publicly accessible location data for classes of CAFOs that are required to obtain water quality permits from the U.S. Environmental Protection Agency (EPA); however, there are no public data sources for the large number of CAFOs that do not require EPA water quality permits. We combined public records of CAFO locations with data collected in North Carolina by the Waterkeeper and Riverkeeper Alliances to examine the distribution of both permitted and non-permitted CAFOs across the state. Over half (55%) of the state's 6646 CAFOs are located in the Coastal Plain, a low-lying region vulnerable to flooding associated with regular cyclonic and convective storms. We identified 19% of CAFOs ≤ 100 m of the nearest stream, and some as close as 15 m to the nearest stream, a common riparian buffer width for water quality management. Future climate scenarios suggest large storm events are expected to become increasingly extreme, and dry interstorm periods could lengthen. Such extremes could exacerbate the environmental impacts of CAFOs. Understanding the potential impacts of CAFO agroecosystems will require remote sensing to identify CAFOs, fieldwork to determine the extent of environmental footprints, and modeling to identify thresholds that determine environmental risk under changing conditions.

Assessment of hydrologic vulnerability to urbanization and climate change in a rapidly changing watershed in the Southeast U.S.

This study assessed the combined effects of increased urbanization and climate change on streamflow in the Yadkin-Pee Dee watershed (North Carolina, USA) and focused on the conversion from forest to urban land use, the primary land use transition occurring in the watershed. We used the Soil and Water Assessment Tool to simulate future (2050-2070) streamflow and baseflow for four combined climate and land use scenarios across the Yadkin-Pee Dee River watershed and three subwatersheds. The combined scenarios pair land use change and climate change scenarios together. Compared to the baseline, projected streamflow increased in three out of four combined scenarios and decreased in one combined scenario. Baseflow decreased in all combined scenarios, but decreases were largest in subwatersheds that lost the most forest. The effects of land use change and climate change were additive, amplifying the increases in runoff and decreases in baseflow. Streamflow was influenced more strongly by climate change than land use change. However, for baseflow the reverse was true; land use change tended to drive baseflow more than climate change. Land use change was also a stronger driver than climate in the most urban subwatershed. In the most extreme land use and climate projection the volume of the 1-day, 100 year flood nearly doubled at the watershed outlet. Our results underscore the importance of forests as hydrologic regulators buffering streamflow and baseflow from hydrologic extremes. Additionally, our results suggest that land managers and policy makers need to consider the implications of forest loss on streamflow and baseflow when planning for future urbanization and climate change adaptation options.