Characterization of roof runoff microbial quality in four U.S. cities with varying climate and land use characteristics.

Roof runoff has the potential to serve as an important local water source in regions with growing populations and limited water supply. Given the scarcity of guidance regulating the use of roof runoff, a need exists to characterize the microbial quality of roof runoff. The objective of this 2-year research effort was to examine roof runoff microbial quality in four U.S. cities: Fort Collins, CO; Tucson, AZ; Baltimore, MD; and Miami, FL. Seven participants, i.e., homeowners and schools, were recruited in each city to collect roof runoff samples across 13 precipitation events. Sample collection was done as part of a citizen science approach. The presence and concentrations of indicator organisms and potentially human-infectious pathogens in roof runoff were determined using culture methods and digital droplet polymerase chain reaction (ddPCR), respectively. The analyzed pathogens included Salmonella spp., Campylobacter spp., Giardia duodenalis, and Cryptosporidium parvum. Several factors were evaluated to study their influence on the presence of potentially human-infectious pathogens including the physicochemical characteristics (total suspended solids, volatile suspended solids, total dissolved solids, chemical oxygen demand, and turbidity) of roof runoff, concentrations of indicator organisms, presence/absence of trees, storm properties (rainfall depth and antecedent dry period), percent of impervious cover surrounding each sampling location, seasonality, and geographical location. E. coli and enterococci were detected in 73.4% and 96.2% of the analyzed samples, respectively. Concentrations of both E. coli and enterococci ranged from <0 log10 to >3.38 log10 MPN/100 mL. Salmonella spp. invA, Campylobacter spp. ceuE, and G. duodenalis ß - giardin gene targets were detected in 8.9%, 2.5%, and 5.1% of the analyzed samples, respectively. Campylobacter spp. mapA and C. parvum 18S rRNA gene targets were not detected in any of the analyzed samples. The detection of Salmonella spp. invA was influenced by the geographical location of the sampling site (Chi-square p-value < 0.001) as well as the number of antecedent dry days prior to a rain event (p-value = 0.002, negative correlation). The antecedent dry period was negatively correlated with the occurrence of Campylobacter spp. ceuE as well (p-value = 0.07). On the other hand, the presence of G. duodenalis ß-giardin in roof runoff was positively correlated with rainfall depth (p-value = 0.05). While physicochemical parameters and impervious area were not found to be correlated with the presence/absence of potentially human-infectious pathogens, significant correlations were found between meteorological parameters and the presence/absence of potentially human-infectious pathogens. Additionally, a weak, yet significant positive correlation, was found only between the concentrations of E. coli and those of Giardia duodenalis ß-giardin. This dataset represents the largest-scale study to date of enteric pathogens in U.S. roof runoff collections and will inform treatment targets for different non-potable end uses for roof runoff. However, the dataset is limited by the low percent detection of bacterial and protozoan pathogens, an issue that is likely to persist challenging the characterization of roof runoff microbial quality given sampling limitations related to the volume and number of samples.

Stakeholder participation, indicators, assessment, and decision-making: applying adaptive management at the watershed scale.

Climate change, population growth, and declining federal budgets are threatening the health of ecosystems, and the services they provide. Under these changing conditions, managing landscapes and resources assumes new and unprecedented challenges. Adaptive management has been identified as a natural resource management approach that allows practitioners to incorporate change and uncertainty into decision-making through an iterative process that involves long-term monitoring and continued review and adjustment of management actions. However, the success of these efforts in watershed health relies on the collective and sustained monitoring of indicators, which is seldom studied. The purpose of this analysis is to examine (1) the practical challenge of choosing a list of indicators for long-term monitoring, (2) the negotiation process among stakeholders around the selection and interpretation of indicators, and (3) the communication tools that can be used to convey the assessment's results and findings. To do this, we analyze our ongoing work in the Cienega Watershed in southern Arizona. Our analysis shows that the selective use of indicators, regular assessment and review, and establishment of partnerships among stakeholders are all important elements in establishing effective adaptive management efforts. The selection of indicators and data sources is a moving target that requires regular consensus and review among stakeholders. The assessment itself is also a powerful engagement tool with the public at large, providing legitimacy and support to land management decision-making. Here, we outline some lessons learned that can be transferred to other cases and identify potential barriers for engagement, decision-making, and project success.

Comparing potential recharge estimates from three Land Surface Models across the Western US.

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01-15% for Mosaic, 3.2-42% for Noah, and 6.7-31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions.

Seasonalizing mountain system recharge in semi-arid basins-climate change impacts.

Climate variability and change impact groundwater resources by altering recharge rates. In semi-arid Basin and Range systems, this impact is likely to be most pronounced in mountain system recharge (MSR), a process which constitutes a significant component of recharge in these basins. Despite its importance, the physical processes that control MSR have not been fully investigated because of limited observations and the complexity of recharge processes in mountainous catchments. As a result, empirical equations, that provide a basin-wide estimate of mean annual recharge using mean annual precipitation, are often used to estimate MSR. Here North American Regional Reanalysis data are used to develop seasonal recharge estimates using ratios of seasonal (winter vs. summer) precipitation to seasonal actual or potential evapotranspiration. These seasonal recharge estimates compared favorably to seasonal MSR estimates using the fraction of winter vs. summer recharge determined from isotopic data in the Upper San Pedro River Basin, Arizona. Development of hydrologically based seasonal ratios enhanced seasonal recharge predictions and notably allows evaluation of MSR response to changes in seasonal precipitation and temperature because of climate variability and change using Global Climate Model (GCM) climate projections. Results show that prospective variability in MSR depends on GCM precipitation predictions and on higher temperature. Lower seasonal MSR rates projected for 2050-2099 are associated with decreases in summer precipitation and increases in winter temperature. Uncertainty in seasonal MSR predictions arises from the potential evapotranspiration estimation method, the GCM downscaling technique and the exclusion of snowmelt processes.

RIPGIS-NET: a GIS tool for riparian groundwater evapotranspiration in MODFLOW.

RIPGIS-NET, an Environmental System Research Institute (ESRI's) ArcGIS 9.2/9.3 custom application, was developed to derive parameters and visualize results of spatially explicit riparian groundwater evapotranspiration (ETg), evapotranspiration from saturated zone, in groundwater flow models for ecohydrology, riparian ecosystem management, and stream restoration. Specifically RIPGIS-NET works with riparian evapotranspiration (RIP-ET), a modeling package that works with the MODFLOW groundwater flow model. RIP-ET improves ETg simulations by using a set of eco-physiologically based ETg curves for plant functional subgroups (PFSGs), and separates ground evaporation and plant transpiration processes from the water table. The RIPGIS-NET program was developed in Visual Basic 2005, .NET framework 2.0, and runs in ArcMap 9.2 and 9.3 applications. RIPGIS-NET, a pre- and post-processor for RIP-ET, incorporates spatial variability of riparian vegetation and land surface elevation into ETg estimation in MODFLOW groundwater models. RIPGIS-NET derives RIP-ET input parameters including PFSG evapotranspiration curve parameters, fractional coverage areas of each PFSG in a MODFLOW cell, and average surface elevation per riparian vegetation polygon using a digital elevation model. RIPGIS-NET also provides visualization tools for modelers to create head maps, depth to water table (DTWT) maps, and plot DTWT for a PFSG in a polygon in the Geographic Information System based on MODFLOW simulation results.

Using ¹7O to investigate nitrate sources and sinks in a semi-arid groundwater system.

We apply a triple isotope approach for nitrate that utilizes Δ(17)O as a conservative tracer, in combination with δ(18)O and δ(15)N, to assess source/sink dynamics of groundwater nitrate beneath alluvial washes in a semiarid urban setting. Other studies have used δ(18)O and δ(15)N to determine nitrate sources and cycling, but the atmospheric δ(18)O signature can be overprinted by biogeochemical processes. In this study, δ(18)O and δ(15)N values of nitrate were coupled with δ(17)O values of nitrate to quantify atmospheric nitrate inputs and denitrification amounts. Results show generally low groundwater nitrate concentrations (<0.2 mmol/L) throughout the basin; high nitrate concentrations (up to 1 mmol/L) with evidence for some denitrification were detected in areas where effluent was the predominant source of recharge to groundwater. Furthermore, the denitrification was inferred from elevated δ(18)O and δ(15)N values which were reinforced by increases in observed δ(17)O values. Finally, relatively low, but significant atmospheric nitrate concentrations were measured in groundwater (up to 6% of total nitrate). This study concludes that the triple isotope approach improves determination of the proportion of atmospheric nitrate and the significance of denitrification in natural waters, allowing us to develop a conceptual model of the biogeochemical processes controlling nitrogen in an urban setting.

Risk-based determination of critical nitrogen deposition loads for fire spread in southern California deserts.

Fire risk in deserts is increased by high production of annual forbs and invasive grasses that create a continuous fine fuel bed in the interspaces between shrubs. Interspace production is influenced by water, nitrogen (N) availability, and soil texture, and in some areas N availability is increasing due to anthropogenic N deposition. The DayCent model was used to investigate how production of herbaceous annuals changes along gradients of precipitation, N availability, and soil texture, and to develop risk-based critical N loads. DayCent was parameterized for two vegetation types within Joshua Tree National Park, California, USA: creosote bush (CB) and piñon-juniper (PJ). The model was successfully calibrated in both vegetation types, but validation showed that the model is sensitive to soil clay content. Despite this fact, DayCent (the daily version of the biogeochemical model CENTURY) performed well in predicting the relative response of production to N fertilization and was used to determine estimates of fire risk for these ecosystems. Fire risk, the probability that annual biomass exceeds the fire threshold of 1000 kg/ha, was determined for each vegetation type and began to increase when N deposition increased 0.05 g/m2 above background levels (0.1 g/m2). Critical loads were calculated as the amount of N deposition at the point when fire risk began to increase exponentially. Mean critical loads for all soil types and precipitation <21 cm/yr, representing the majority of our study region, were 0.32 +/- 0.07 and 0.39 +/- 0.09 g N/m2 for CB and PJ, respectively. Critical loads decreased with increasing soil clay content and increasing precipitation, such that the wettest areas with clay contents of 6-14% may have critical loads as low as 0.15 g N/m2. Mean fire risks approached their maximum at 0.93 +/- 0.21 and 0.87 +/- 0.17 g N/m2 in CB and PJ, indicating that precipitation is the driver of fire above these N deposition levels, which are currently observed in some areas of the Sonoran and Mojave Deserts. Overall, this analysis demonstrates the importance of considering both N deposition and precipitation when evaluating fire risk across arid landscapes.

Smog nitrogen and the rapid acidification of forest soil, San Bernardino Mountains, southern California.

We report the rapid acidification of forest soils in the San Bernardino Mountains of southern California. After 30 years, soil to a depth of 25 cm has decreased from a pH (measured in 0.01 M CaCl2) of 4.8 to 3.1. At the 50-cm depth, it has changed from a pH of 4.8 to 4.2. We attribute this rapid change in soil reactivity to very high rates of anthropogenic atmospheric nitrogen (N) added to the soil surface (72 kg ha(-1) year(-1)) from wet, dry, and fog deposition under a Mediterranean climate. Our research suggests that a soil textural discontinuity, related to a buried ancient landsurface, contributes to this rapid acidification by controlling the spatial and temporal movement of precipitation into the landsurface. As a result, the depth to which dissolved anthropogenic N as nitrate (NO3) is leached early in the winter wet season is limited to within the top approximately 130 cm of soil where it accumulates and increases soil acidity.

Altered ecohydrologic response drives native shrub loss under conditions of elevated nitrogen deposition.

Many regions of southern California's coastal sage scrub (CSS) are rapidly declining as exotic annual plants replace native shrubs. During this conversion, the subsurface hydrology of the semiarid hillslopes that support CSS may be altered. This could chronically suppress the ability of native shrubland to revegetate the landscape since ecosystem processes of nutrient availability and of seedling establishment rely on spatial patterns of available soil water. In this work, soil water and nutrient N regimes were compared over a 2-yr period between a southern California site where CSS has declined (approximately 5% shrub cover) with high additions of anthropogenic N, and one where CSS remains dominant (over 50% shrub cover) with predominantly background atmospheric additions of N. These two sites have similar climate, bedrock lithology, soils, and topography, and had the same vegetation type (Riversidean CSS) 30 years ago. We found that the depth and rate of rainwater percolation into wildland hillslope soils in response to early-season storm events has been greatly reduced after loss of CSS shrubs and vegetation type conversion to invasive grassland. With decreased rainwater redistribution to soil depths of 100 to 150 cm, the predominant zone of soil water has become the upper 25 cm. This shift exacerbates vegetation type conversion by (i) concentrating smog-produced nitrogenous (N) chemicals in the uppermost soil, where they become readily available, along with high soil water, to shallow-rooted exotic grasses early in the growing season and (ii) depriving adult and juvenile shrubs of deeper regolith water.

Tracing atmospheric nitrate deposition in a complex semiarid ecosystem using delta17O.

The isotopic composition of nitrate collected from aerosols, fog, and precipitation was measured and found to have a large 17O anomaly with delta17O values ranging from 20 percent per thousand to 30% percent per thousand (delta17O = delta17O - 0.52(delta18O)). This 17O anomaly was used to trace atmospheric deposition of nitrate to a semiarid ecosystem in southern California. We demonstrate that the delta17O signal is a conserved tracer of atmospheric nitrate deposition and is a more robust indicator of N deposition relative to standard delta18O techniques. The data indicate that a substantial portion of nitrate found in the local soil, stream, and groundwater is of atmospheric origin and does not undergo biologic processing before being exported from the system.