Watershed Size Research Articles

Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds

Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km2) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

A novel explainable PSO-XGBoost model for regional flood frequency analysis at a national scale: Exploring spatial heterogeneity in flood drivers

Identifying flood drivers and accurately estimating design floods play a crucial role in fostering sustainable and effective planning and management strategies for mitigating flood risks. Regional Flood frequency Analysis (RFFA) is one of the most commonly used approaches to estimate design floods in ungauged watersheds. This study used XGBoost coupled with Particle Swarm Optimization (PSO) to estimate different quantiles of the design floods with return periods (from 2-year to 1000-year). After a preliminary assessment, 373 nationwide hydrometric stations were selected to conduct at-site flood frequency analysis by identifying the best-fitting distribution. Using the capabilities of GIS and Google Earth Engine (GEE), 83 independent features including different physiographical, geomorphological, land-use, soil types, and long-term hydro-climatic and environmental variables were extracted for the upstream watersheds. After fine-tuning the hyper-parameters of the XGBoost method for each flood quantile, the feature importance values were used to eliminate the insignificant features and refine the developed models. Additionally, classical methods such as Support Vector Regression (SVR) and Random Forest (RF) were implemented, to evaluate the XGBoost models efficiency. Different statistics demonstrated that the models effectively estimated flood quantiles, with the Nash-Sutcliffe Efficiency (NSE) varying from 0.709 to 0.840 across all models. A comparison of model performance reveals that the XGBoost method outperformed RF and SVR across all flood quantiles. Based on the developed models, design floods have been estimated for 949 stations across Iran. Furthermore, the Shapley additive explanation (SHAP) values were used to identify the main contributing features to model outputs and investigate the spatial heterogeneity of main flood drivers. According to the results, the perimeter and length of the watershed and heavy rainfall exhibit notably high importance compared to other features for all models. Based on the local SHAP values, in Northern, Northwestern, and Western basins, features associated with watershed sizes, such as perimeter, area and length exhibit the highest levels of importance. Moreover, the Southwest basins are more influenced by “heavy rainfall”. These findings demonstrate the promise of the developed models for estimating flood quantiles across diverse environmental, geomorphological, and hydro-climatic conditions. This capability is valuable for sustainable watershed management, especially in environments with limited maximum discharge data.

Advancing freshwater science with sensor data collected by community scientists

Autonomous sensor networks providing real‐time data are growing in popularity with community scientists due to instant availability of high‐frequency data. What role does this monitoring play in watershed assessment alongside agency‐run monitoring programs? How accessible, interoperable, and reusable are the data for other researchers? We compared a community science‐led stream monitoring network—EnviroDIY—in the Delaware River Basin, in which more than 50 watershed organizations have deployed more than 100 stations monitoring temperature, electric conductivity, depth, and sometimes turbidity, with the Basin's US Geological Survey (USGS) stream gauge network. The EnviroDIY network (n = 124) complemented the USGS network (n = 102) by monitoring sites with different watershed sizes and land‐use distributions. Although data were accessible and interoperable using a web data portal, community scientists had difficulty sharing metadata that would enable data reuse outside this project and they required support analyzing these large datasets to understand threats to watershed conditions. We address those needs here with a conceptual framework for interpreting data and communicating results.

Forest Disturbance Thresholds and Cumulative Hydrological Impacts

AbstractForest disturbance threshold is defined as a critical disturbance level (e.g., % of forest cover change) in forested landscapes above which significant hydrological impacts are detected. Determining disturbance thresholds is critically important for supporting forest management to ensure the sustaining of ecological and hydrological functions. However, there are very few quantitative evaluations of forest disturbance thresholds globally. In this study, we applied a well‐tested methodology (the modified double mass curve) to derive the long‐term, continuous hydrological response curves and then to quantify forest disturbance thresholds on annual streamflow in 42 forested watersheds in British Columbia, Canada. The results show that forest disturbance thresholds for significant and cumulative hydrological impacts vary from 7% to 52% of cumulative equivalent clear‐cut area with an average of 17% or from 8% to 52% of disturbed area with an average of 19%. Climate (inter‐annual and intra‐annual) and watershed properties exert critical controls on forest disturbance thresholds. Watersheds with greater snowfall proportions (more annual precipitation falling as snow), more desynchronizations (temporal mismatching) of energy demand and water supply at the intra‐annual scale, less diverse ecosystems, and larger watershed sizes have lower forest disturbance thresholds. Given the present forest disturbance levels in the central interior of British Columbia, about half (53%) of the forested watersheds have already crossed the average disturbance threshold. These results highlight that watershed planning and management using forest disturbance thresholds must carefully consider local climate and watershed properties. The methodology can be effectively and robustly extended elsewhere around the globe.

A Boatable Days Framework for Quantifying Whitewater Recreation—Insights from Three Appalachian Whitewater Rivers

Outdoor recreation is one of the fastest-growing economic sectors in the United States and is being used by communities to support economic development, social prosperity, and environmental protection. For communities that have whitewater rivers, whitewater recreation provides a powerful economic alternative to ailing extractive and manufacturing industries that have long dominated rural communities. In order to promulgate a whitewater recreation-based economy, stakeholders need information about their whitewater resources, including how often and when they can be paddled. The overall goal of this study, therefore, was to develop an analytical framework that quantifies boatable days, that is, the number of days that streamflow exceeds the minimum boatable flow levels needed to paddle downstream. Importantly, our framework uses publicly available streamflow and minimum boatable flow information that can be used to quantify boatable days for any whitewater run in the country, irrespective of watershed size or river flashiness. We applied the framework to three world-class whitewater rivers in the central Appalachian Mountains, USA, and found abundant and stable boating opportunities throughout the year. Our results underscore the potential for strategically developing whitewater recreation as a means of economic diversification and highlight how boatable days analysis can be used for quantifying whitewater resources.

Phytoplankton in headwater streams: spatiotemporal patterns and underlying mechanisms

Phytoplankton are key members of river ecosystems wherein they influence and regulate the health of the local environment. Headwater streams are subject to minimal human activity and serve as the sources of rivers, generally exhibiting minimal pollution and strong hydrodynamic forces. To date, the characteristics of phytoplankton communities in headwater streams have remained poorly understood. This study aims to address this knowledge gap by comparing phytoplankton communities in headwater streams with those in plain rivers. The results demonstrated that within similar watershed sizes, lower levels of spatiotemporal variability were observed with respect to phytoplankton community as compared to plain rivers. Lower nutrient levels and strong hydrodynamics contribute to phytoplankton growth limitation in these streams, thereby reducing the levels of spatiotemporal variation. However, these conditions additionally contribute to greater phytoplankton diversity and consequent succession towards Cyanophyta. Overall, these results provide new insights into the dynamics of headwater stream ecosystems and support efforts for their ecological conservation.

Understanding the spatial variation in lithium concentration of high Andean Salars using diagnostic factors

Salars (basins of internal drainage) in the “Lithium Triangle” countries (Argentina, Bolivia, Chile) hold >50 % of the global lithium resources within lithium-rich brines. Given the imperative for lithium production to enable the energy transition and that salars by their very nature are highly variable, so a framework to both characterise their differences as well as identifying their similarities would be beneficial to understanding their provenance and potential for exploitation.In this study, data for 29 salars based on environmental factors: rainfall, evaporation as well as their physical characteristic: pan size and basin size have been used to characterise them along with those describing their setting land-use/cover and geological outcrop. These parameters have been normalised by creating a ratio of the lithium concentration divided by the factor for each salar. Cross-correlation has been used to develop relationships between these normalised factors, combined with principal component analysis to identify clustering and to further characterise groupings of behaviours.Two such relationships emerge out of this process: regional and local. Regional covers factors such as elevation, precipitation, and evaporation; local includes size of watershed, salar nucleus, land cover and geological outcrop in the watershed. However, Salar de Atacama is identified as an outlier and so the transferability of the understanding of its provenance and operation must be treated with caution. Other salars could be added to the framework as more information becomes available. The methodology presented here could help exploration by characterising salars into categories as their smaller size may not necessarily mean lower lithium mass. Further, such a framework can inform policy decisions and instruments by recognising the complexity of salars combined with the need to understand the environmental impacts of brine extraction.

Permafrost Wetlands Are Sources of Dissolved Iron and Dissolved Organic Carbon to the Amur‐Mid Rivers in Summer

AbstractDissolved iron (dFe) transported by the Amur River greatly contributes to phytoplankton growth in the Sea of Okhotsk. Nevertheless, there has been little research on the source of dFe to rivers, especially in the Amur‐Mid Basin, which is situated in a sporadic permafrost area. In the Amur‐Mid Basin, permafrost generally exists in wetlands in flat valleys, and these permafrost wetlands could be a source of dFe to rivers. To assess the importance of permafrost wetlands for dFe export, we conducted a local survey on land and soil characteristics of wetlands, and moreover analyzed the chemical composition (dFe, dissolved organic carbon [DOC], pH, and electrical conductivity [EC]) of 24 rivers with different watershed sizes in summer. As a result of local survey, the thickly accumulated peat soils in the permafrost wetland were almost saturated and rich in organic matter from the surface to a greater depth near the permafrost table. In addition, the coverage of such permafrost wetlands in watersheds showed significant positive correlations with dFe (r2 = 0.67, p = 1.7e−6) and DOC (r2 = 0.48, p = 1.8e−4) and a negative correlation with EC (r2 = 0.52, p = 7.7e−5). The dFe concentration was also correlated well with DOC concentration (r2 = 0.68, p = 7.3e−7) but not correlated with pH and watershed area. These findings are the first to indicate that permafrost wetlands in the Amur‐Mid Basin considerably contribute to dFe and DOC export to rivers, and their coverage primarily determines riverine dFe and DOC concentrations in summer.

Relationships between Landscape Patterns and Hydrological Processes in the Subtropical Monsoon Climate Zone of Southeastern China

With rapid economic development, extensive human activity has changed landscape patterns (LPs) dramatically, which has further influenced hydrological processes. However, the effects of LPs changes on hydrological processes, especially for the streamflow–sediment relationship in the subtropical monsoon climate zone, have not been reported. In our study, 10 watersheds with different sizes in the subtropical monsoon climate zone of southeastern China were chosen as the study area, and the effect of the 14 most commonly used landscape metrics (LMs) on 4 typical hydrological indices (water yields (WY), the runoff coefficient (RC), the soil erosion modulus (SEM), and the suspended sediment concentration (SSC)) were analyzed based on land use maps and hydrological data from 1990 to 2019. The results reveal that the LP characteristics within the study area have changed significantly. The number of patches and landscape shape indices were significantly positively correlated with watershed size (p < 0.01). For most watersheds, the largest patch index was negatively correlated with WY, RC, and SEM, and the perimeter area fractal dimension was positively correlated with WY, RC, SEM, and SSC. The effects of several LMs on the hydrological indices had scale effects. WY/RC and the interspersion and juxtaposition index were negatively correlated in most larger watersheds but were positively correlated in most smaller watersheds. Similar results were found for Shannon’s diversity/evenness index and SEM. In general, an increase in a small patch of landscape and in landscape diversity would increase WY, the fragmentation of LPs would result in more soil erosion, and LPs would affect the relationship between streamflow and sediment yield. As a result, a proper decrease in landscape fragmentation and physical connectivity in the subtropical monsoon climate zone of southeastern China would benefit soil erosion prevention. These results enhance the knowledge about the relationship between LPs and hydrological processes in the subtropical monsoon climate zone of southeastern China and benefit local water and soil conservation efforts.

Dynamics of dissolved organic carbon during drought and flood events: A phase-by-stages perspective

Dissolved organic carbon (DOC) is a key water quality parameter that plays a crucial role in controlling aquatic ecosystems and carbon cycling. Understanding DOC dynamics during hydrological extremes (i.e., droughts and floods) helps in managing water quality, but such variability is rarely studied. Furthermore, how differences in DOC concentrations among phase-by-stages of drought/flood affect simulation performances based on hydrological features remains unclear. Here, phase-by-stages of hydrological drought (flood) were divided into intensification (rising) and recovery (falling) periods based on drought peak intensity (flood peak intensity). The long-term (1976–2019) daily discharge and weekly (biweekly) DOC concentrations from four headwater streams with different watershed sizes (from 9.97 to 119.09 ha) in south-central Ontario, Canada, were used to achieve the above aims. The results showed that (i) the average DOC concentration during intensification (rising) stage of drought (flood) was smaller (larger) than during recovery (falling). (ii) Simulations performed better when accounting for phase-by-stages of drought/flood, with reductions in mean absolute percentage error of 32.85 % and 53.59 % for drought and flood events, respectively. These results will help understand the dynamics of DOC during hydrological extremes and improve simulation performance of numerical models for water quality parameters under changing environmental conditions.

Assessing the influence of lake and watershed attributes on snowmelt bypass at thermokarst lakes

Abstract. Snow represents the largest potential source of water for thermokarst lakes, but the runoff generated by snowmelt (freshet) can flow beneath lake ice and via the outlet without mixing with and replacing pre-snowmelt lake water. Although this phenomenon, called “snowmelt bypass”, is common in ice-covered lakes, it is unknown which lake and watershed properties cause variation in snowmelt bypass among lakes. Understanding the variability of snowmelt bypass is important because the amount of freshet that is mixed into a lake affects the hydrological and biogeochemical properties of the lake. To explore lake and watershed attributes that influence snowmelt bypass, we sampled 17 open-drainage thermokarst lakes for isotope analysis before and after snowmelt. Isotope data were used to estimate the amount of lake water replaced by freshet and to observe how the water sources of lakes changed in response to the freshet. Among the lakes, a median of 25.2 % of lake water was replaced by freshet, with values ranging widely from 5.2 % to 52.8 %. For every metre that lake depth increased, the portion of lake water replaced by freshet decreased by an average of 13 %, regardless of the size of the lake's watershed. The thickness of the freshet layer was not proportional to maximum lake depth, so that a relatively larger portion of pre-snowmelt lake water remained isolated in deeper lakes. We expect that a similar relationship between increasing lake depth and greater snowmelt bypass could be present at all ice-covered open-drainage lakes that are partially mixed during the freshet. The water source of freshet that was mixed into lakes was not exclusively snowmelt but a combination of snowmelt mixed with rain-sourced water that was released as the soil thawed after snowmelt. As climate warming increases rainfall and shrubification causes earlier snowmelt timing relative to lake ice melt, snowmelt bypass may become more prevalent, with the water remaining in thermokarst lakes post-freshet becoming increasingly rainfall sourced. However, if climate change causes lake levels to fall below the outlet level (i.e., lakes become closed-drainage), more freshet may be retained by thermokarst lakes as snowmelt bypass will not be able to occur until lakes reach their outlet level.

Neonicotinoid contamination in tropical estuarine waters of Indonesia

Previous studies conducted in other countries showed that neonicotinoid insecticides contaminated environmental waters and reduced aquatic invertebrate abundance. This study analysed neonicotinoid concentrations in estuarine waters of Indramayu Regency, Indonesia, and their potential toxicity to the aquatic environment. Data collection included water sampling and analysis, watershed and paddy field analyses, and literature review. The results showed that the detection frequency of neonicotinoids was 75%, with imidacloprid and thiamethoxam having the highest mean concentrations compared to other compounds. The sample collected in August 2021 from an estuary in the Patrol sub-district contained the highest total neonicotinoid concentration (140.26 ng/L). Five samples (31.25%) contained imidacloprid concentrations that exceeded the chronic benchmark regulated by the Netherlands, thus related regulation and policies are encouraged to be established in Indonesia to prevent potential harmful effect of neonicotinoids to the aquatic environment. There was no significant correlation between the neonicotinoid concentrations and the paddy field and watershed sizes as well as the land use proportion for paddy fields within the watershed. This study is the first to report neonicotinoid contamination in Indonesian estuarine waters.

Exploring Homogeneity among Catchments forEfficient Province-wide Watershed Managementin Negros Occidental, Philippines

Catchment classification is one approach in natural resource management that is widely adopted in taking efficient steps towards implementing suitable soil and water conservation measures across a basin or region. Catchments have unique characteristics emerging from the heterogeneity and complexity of the systems and classifying them paves way to achieve order and simplicity. However, some constraints related to data availability could be a problem in a region where only few rivers are gauged and with only one type of climate data available. This study presents a way to decrease complexity by grouping these catchments based on their biophysical characteristics extracted from readily available datasets and using simple statistical approaches. Principal component analysis was first conducted to twenty-four biophysical variables which were reduced to eight factor components. A hierarchical clustering method was then performed to define the number of clusters and K-means clustering procedure was followed for the final grouping. Nine watershed clusters were formed with watershed size having the greatest contribution. Grouping catchments into clusters with similar biophysical characteristics does not only promote simplicity but also facilitates understanding of the nature of not only one watershed but also its relationship with other watersheds in a bigger landscape. The study also confirmed that spatially close watersheds exhibit similar characteristics.

Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

BackgroundAltered hydrology is a stressor on aquatic life, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota. Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish-community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to an impairment threshold of the corresponding stream class (FIBI_BCG4). Relations between hydrology and fish community responses were examined using three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.ResultsRegression models demonstrated significant relations between hydrologic explanatory metrics and fish-based biological response metrics, and the five regression models with the strongest linear relations explained over 70% of the variability in the biological metric using three hydrologic metrics as explanatory variables. Tolerance-based biological metrics demonstrated the strongest linear relations to hydrologic metrics. The most commonly used hydrologic metrics were related to bankfull flows and aspects of flow variability.ConclusionsFinal regression models represent paired streamgage records and biological samples throughout the State of Minnesota and encompass differences in stream orders, hydrologic landscape units, and watershed sizes. Presented methods can support evaluations of stream fish communities and facilitate targeted efforts to improve the health of fish communities. Methods also can be applied to locations outside of Minnesota with continuous streamgage data and fish-community samples.

Global Controls on DOC Reaction Versus Export in Watersheds: A Damköhler Number Analysis

AbstractThe relative capacity for watersheds to eliminate or export reactive constituents has important implications on aquatic ecosystem ecology and biogeochemistry. Removal efficiency depends on factors that affect either the reactivity or advection of a constituent within river networks. Here, we characterized Damköhler number (Da) for dissolved organic carbon (DOC) uptake in global river networks. Da equals the advection to reaction timescale ratio and thus provides a unitless indicator for DOC reaction intensity during transport within river networks. We aim to demonstrate the spatial and temporal patterns and interplays among factors that determine DOC uptake across global river networks. We show that watershed size imposes a primary control on river network DOC uptake due to a three orders of magnitude difference in water residence time (WRT) between the smallest and largest river networks. DOC uptake capacity in tropical river networks is 2–6 times that in temperate and the Arctic river networks, coinciding with larger DOC removals in warm than in cold watersheds. River damming has a profound impact on DOC uptake due to significantly extended WRTs, particularly in temperate watersheds where most constructed dams are situated. Global warming is projected to increase river network DOC uptake by ca. 19% until year 2100 under the RCP4.5 scenario.

Controls on watershed flashiness across the continental US

Hydrograph flashiness is a commonly used and valuable measure of hydrologic behavior, calculated directly from streamflow measurements. There is limited understanding of how and why flashiness varies at continental scales and within different hydroclimatic regions, which can aid in predicting regional responses to an accelerating water cycle. We addressed this knowledge gap by calculating a widely used metric of flashiness, the Richards-Baker Flashiness index (RBI), for 1144 watersheds across the continental US for a ten year period, using daily streamflow from USGS gages. While regional studies have suggested that flashiness is organized by watershed size, we show that flashiness is poorly organized by drainage area at continental scales. Moreover, relationship strengths and directions with drainage area varied by hydroclimatic regions. Using a regionally based random forest analysis, we show that empirical relationships between watershed characteristics and flashiness are diverse, emphasizing that drivers of flashiness are likely related to regional or smaller scale features that encapsulate relationships between climate, human impacts, and the subsurface.

Superlinear scaling of riverine biogeochemical function with watershed size

River networks regulate carbon and nutrient exchange between continents, atmosphere, and oceans. However, contributions of riverine processing are poorly constrained at continental scales. Scaling relationships of cumulative biogeochemical function with watershed size (allometric scaling) provide an approach for quantifying the contributions of fluvial networks in the Earth system. Here we show that allometric scaling of cumulative riverine function with watershed area ranges from linear to superlinear, with scaling exponents constrained by network shape, hydrological conditions, and biogeochemical process rates. Allometric scaling is superlinear for processes that are largely independent of substrate concentration (e.g., gross primary production) due to superlinear scaling of river network surface area with watershed area. Allometric scaling for typically substrate-limited processes (e.g., denitrification) is linear in river networks with high biogeochemical activity or low river discharge but becomes increasingly superlinear under lower biogeochemical activity or high discharge, conditions that are widely prevalent in river networks. The frequent occurrence of superlinear scaling indicates that biogeochemical activity in large rivers contributes disproportionately to the function of river networks in the Earth system.

Strength and Memory of Precipitation's Control Over Streamflow Across the Conterminous United States

AbstractHow precipitation (P) is translated into streamflow (Q) and over what timescales (i.e., “memory”) is difficult to predict without calibration of site‐specific models or using geochemical approaches, posing barriers to prediction in ungauged basins or advancement of general theories. Here, we used a data‐driven approach to identify regional patterns and exogenous controls on P–Q interactions. We applied an information flow analysis, which quantifies uncertainty reduction, to a daily time series of P and Q from 671 watersheds across the conterminous United States. We first demonstrated that information transfer from P to Q primarily reflects the quickflow component of water‐budgets, based on a watershed model. Readily quantifiable information flows show a functional relationship with model parameters, suggesting utility for model calibration. Second, applied to real watersheds, P–Q information flows exhibit seasonally varying behavior within regions in a manner consistent with dominant runoff generation mechanisms. However, the timing and the magnitude of information flows also reflect considerable subregional heterogeneity, likely attributable to differences in watershed size, baseflow contributions, and variation in aerial coverage of preferential flow paths. A regression analysis showed that a combination of climate and watershed characteristics are predictive of P–Q information flows. Though information flows cannot, in most cases, uniquely determine dominant runoff mechanisms, they provide a means to quantify the heterogeneous outcomes of those mechanisms within regions, thereby serving as a benchmarking tool for models developed at the regional scale. Last, information flows characterize regionally specific ways in which catchment connectivity changes from the wet to dry season.

Fractal Behaviors of Hydraulic Head and Surface Runoff of the Nested Groundwater Flow Systems in Response to Rainfall Fluctuations

AbstractThe responses of the nested groundwater flow systems (NGFS) to rainfall fluctuations and the impacts of the NGFS on surface runoff are explored using a fully coupled variably saturated groundwater‐surface water model in conjunction with spectral analysis. Numerical experiments are designed to investigate the fractal behaviors of hydraulic head and surface runoff in different scenarios. The results show that the inlets, outlets, and flow patterns of the sub‐systems of NGFS can change with rainfall. The scaling‐exponent, defined as the slope of the power spectra of the fluctuations of hydraulic head or runoff, is used to depict the fractal behaviors. The scaling‐exponent of the hydraulic head is highly variable within the unsaturated zone and local flow systems but remains constant within the intermediate and regional systems. Whether the scaling‐exponent of surface runoff exhibits a linear relation with the watershed size depends on the proportion of baseflow in the runoff.

δ15N of Chironomidae: An index of nitrogen sources and processing within watersheds for national aquatic monitoring programs

Nitrogen (N) removal along flowpaths to aquatic ecosystems is an important regulating ecosystem service that can help reduce N pollution in the nation's waterways, but can be challenging to measure at large spatial scales. Measurements that integrate N processing within watersheds would be particularly useful for assessing the magnitude of this vital service. Because most N removal processes cause isotopic fractionation, δ15N from basal food-chain organisms in aquatic ecosystems can provide information on both N sources and the degree of watershed N processing. As part of EPA's National Aquatic Resource Surveys (NARS), we measured δ15N of Chironomidae collected from over 2000 lakes, rivers and streams across the continental USA. Using information on N inputs to watersheds and summer total N concentrations ([TN]) in the water column, we assessed where elevated chironomid δ15N would indicate N removal rather than possible enriched sources of N. Chironomid δ15N values ranged from −4 to +20‰, and were higher in rivers and streams than in lakes, indicating that N in rivers and streams underwent more processing and cycling that preferentially removes 14N than N in lakes. Chironomid δ15N increased with watershed size, N inputs, and water chemical components, and decreased as precipitation increased. In rivers and streams with high watershed N inputs, we found lower [TN] in streams with higher chironomid δ15N values, suggesting high rates of gaseous N loss such as denitrification. At low watershed N inputs, the pattern reversed; streams with elevated chironomid δ15N had higher [TN] than streams with lower chironomid δ15N, possibly indicating unknown sources elevated in δ15N such as legacy N, or waste from animals or humans. Chironomid δ15N values can be a valuable tool to assess integrated watershed-level N sources, input rates, and processing for water quality monitoring and assessment at large scales.