Stream Discharge Data Research Articles

Stream chemical response is mediated by hydrologic connectivity and fire severity in a Pacific Northwest forest

AbstractLarge‐scale wildfires are becoming increasingly common in the wet forests of the Pacific Northwest (USA), with predicted increases in fire prevalence under future climate scenarios. Wildfires can alter streamflow response to precipitation and mobilize water quality constituents, which pose a risk to aquatic ecosystems and downstream drinking water treatment. Research often focuses on the impacts of high‐severity wildfires, with stream biogeochemical responses to low‐ and mixed‐severity fires often understudied, particularly during seasonal shifts in hydrologic connectivity between hillslopes and streams. We studied the impacts of the 2020 Holiday Farm Fire at the HJ Andrews Experimental Forest where rare pre‐fire stream discharge and chemistry data allowed us to evaluate the influence of mixed‐severity fire on stream water quantity and quality. Our research design focused on two well‐studied watersheds with low and low‐moderate burn severity where we examined long‐term data (pre‐ and post‐fire), and instantaneous grab samples collected during four rain events occurring immediately following wildfire and a prolonged dry summer. We analysed the impact of these rain events, which represent the transition from low‐to‐high hydrologic connectivity of the subsurface to the stream, on stream discharge and chemistry behaviour. Long‐term data revealed total annual flows and mean flows remained fairly consistent post‐fire, while small increases in baseflow were observed in the low‐moderately burned watershed. Stream water concentrations of nitrate, phosphate and sulfate significantly increased following fire, with variance in concentration increasing with fire severity. Our end member mixing models suggested that during rain events, the watershed with low‐moderate severity fire had greater streamflow inputs from soil water and groundwater during times of low connectivity compared to the watershed with low severity fire. Finally, differences in fire severity impacts on concentration‐discharge relationships of biogenic solutes were most expressed under low catchment connectivity conditions. Our study provides insights into post‐wildfire impacts to stream water quality, with the goal of informing future research on stream chemistry responses to low, moderate and mixed severity wildfire.

Analysis of streamflow and rainfall trends and variability over the Lake Kariba catchment, Upper Zambezi Basin

ABSTRACT Hydro-meteorological trend analysis is critical for assessing climate change and variability at basin and regional levels. This study examined the long- and short-term trends from stream discharge and rainfall data in the Lake Kariba catchment. A trend and change point analysis was carried out on the mean, minimum and maximum monthly average time series for 14 gauging stations that are located within the Kariba catchment. The Mann–Kendall and the Pettitt tests were used to determine the trend and any changes in the long-term average of the time series. The magnitude of the trend was determined by Sen's slope method. The results indicate that generally there has been a decreasing trend in river and rainfall long-term mean values across the catchment. A statistically significant trend (p ≤ 0.05) was observed at Zambezi River at Lukulu, Senanga and Victoria Falls, with a positive correlation in Pearsons's coefficient of water levels and rainfall at Lukulu (0.312) and Senanga (0.365). The decrease in the time series trend and the change point observed have been attributed to anthropogenic activities, climate change and variability impact on the catchment. The findings are critical for climate risk management and reduction decisions for near- and long-term timescales.

Water‐rock interactions drive chemostasis

AbstractThe western U.S. is experiencing shifts in recharge due to climate change, and it is currently unclear how hydrologic shifts will impact geochemical weathering and stream concentration–discharge (C–Q) patterns. Hydrologists often use C–Q analyses to assess feedbacks between stream discharge and geochemistry, given abundant stream discharge and chemistry data. Chemostasis is commonly observed, indicating that geochemical controls, rather than changes in discharge, are shaping stream C–Q patterns. However, few C–Q studies investigate how geochemical reactions evolve along groundwater flowpaths before groundwater contributes to streamflow, resulting in potential omission of important C–Q controls such as coupled mineral dissolution and clay precipitation and subsequent cation exchange. Here, we use field observations—including groundwater age, stream discharge, and stream and groundwater chemistry—to analyse C–Q relations in the Manitou Experimental Forest in the Colorado Front Range, USA, a site where chemostasis is observed. We combine field data with laboratory analyses of whole rock and clay x‐ray diffraction and soil cation‐extraction experiments to investigate the role that clays play in influencing stream chemistry. We use Geochemist's Workbench to identify geochemical reactions driving stream chemistry and subsequently suggest how climate change will impact stream C–Q trends. We show that as groundwater age increases, C–Q slope and stream solute response are not impacted. Instead, primary mineral dissolution and subsequent clay precipitation drive strong chemostasis for silica and aluminium and enable cation exchange that buffers calcium and magnesium concentrations, leading to weak chemostatic behaviour for divalent cations. The influence of clays on stream C–Q highlights the importance of delineating geochemical controls along flowpaths, as upgradient mineral dissolution and clay precipitation enable downgradient cation exchange. Our results suggest that geochemical reactions will not be impacted by future decreasing flows, and thus where chemostasis currently exists, it will continue to persist despite changes in recharge.

Multi‐Year Controls on Groundwater Storage in Seasonally Snow‐Covered Headwater Catchments

AbstractSeasonally snow‐covered catchments in the western United States supply water to growing populations as both annual snowmelt‐driven streamflow and multi‐year groundwater recharge. Although interannual variability in streamflow is driven largely by precipitation, runoff efficiency (the ratio of streamflow to precipitation) in individual catchments varies by 50% or more. Recent work suggests that interannual variability in groundwater storage, inferred from winter baseflow, is a primary control on runoff efficiency, highlighting a need to quantify both the time scales on which groundwater storage varies and the hydro‐climatic drivers of storage. Using over a century of daily stream discharge data from 10 seasonally snow‐covered catchments in northern Utah, we find that temporal variability in winter baseflow, an index of groundwater storage, measured from mean daily January discharge, exhibits a 2–5‐ and 12–15‐year periodicity, driven by regional precipitation patterns and snowmelt dynamics. Specifically, multiple linear regression (MLR) modeling using antecedent hydro‐climatic variables demonstrates that winter baseflow (groundwater storage) was positively related to 3–4 years of antecedent annual precipitation, negatively related to the previous year's mean annual temperature, and positively related to 1–4 antecedent years of snowmelt rate and duration. Because antecedent baseflow (groundwater storage) is strongly related to runoff efficiency, these results suggest that more frequent and longer droughts in a future climate will reduce surface water supplies faster than otherwise expected. More broadly, these results highlight the importance of including the influence of antecedent climate on groundwater storage when modeling and managing water supplies from seasonally snow‐covered catchments.

Water availability and seasonality shape elemental stoichiometry across space and time.

The interaction of climate change and increasing anthropogenic water withdrawals is anticipated to alter surface water availability and the transport of carbon (C), nitrogen (N), and phosphorus (P) in river networks. But how changes to river flow will alter the balance, or stoichiometry, of these fluxes is unknown. The Lower Flint River Basin (LFRB) is part of an interstate watershed relied upon by several million people for diverse ecosystem services, including seasonal crop irrigation, municipal drinking water access, and public recreation. Recently, increased water demand compounded with intensified droughts have caused historically perennial streams in the LFRB to cease flowing, increasing ecosystem vulnerability. Our objectives were to quantify how riverine dissolved C: N: P varies spatially and seasonally and determine how monthly stoichiometric fluxes varied with overall water availability in a major tributary of LFRB. We used a long-term record (21-29 years) of solute water chemistry (dissolved organic carbon, nitrate/nitrite, ammonia, and soluble reactive phosphorus) paired with long-term stream discharge data across six sites within a single LFRB watershed. We found spatial and seasonal differences in soluble nutrient concentrations and stoichiometry attributable to groundwater connections, the presence of a major floodplain wetland, and flow conditions. Further, we showed that water availability, as indicated by the Palmer Drought Severity Index (PDSI), strongly predicted stoichiometry with generally lower C:N and C:P and higher N:P fluxes during periods of low water availability (PDSI < -4). These patterns suggest there may be long term and significant changes to stream ecosystem function as water availability is being dramatically altered by human demand with consequential impacts to solute transport, in-stream processing, and stoichiometric ratios. This article is protected by copyright. All rights reserved.

Nutrient delivery by groundwater discharge to headwater streams in agricultural catchments

AbstractNutrient concentrations in riparian groundwater are variable from site to site, making it challenging to use these data to quantify nutrient fluxes contributed by groundwater discharge to headwater streams. Instead, we define event‐excluded baseflow (BFEE), and use stream discharge data and stream samples collected during BFEEto estimate groundwater discharge and loading of nutrients to the streams. Based on this method, in two study catchments (Thames River basin, Ontario, Canada) groundwater discharge during BFEEcontributed about 30% of the total streamflow and 20%–30% of the total loading of soluble reactive phosphorus (SRP) and nitrate. Previous estimates of baseflow using hydrographic separation techniques indicate that groundwater discharge likely contributes even larger fractions, ~50%–60% of flow in these catchments. We infer that groundwater likely contributes ~40% of the annual SRP load and ~ 50%–60% of the nitrate‐N load. These results indicate that groundwater discharge plays an important role in the nutrient loading to headwater streams. This reinforces the findings of earlier studies that have inferred a dominant influence of legacy reservoirs of nutrients in the subsurface of similar agricultural catchments on the loads of these nutrients in headwater streams.

Hillslope-scale exploration of the relative contribution of base flow, seepage flow and overland flow to streamflow dynamics

Surface and subsurface flows interact at different spatial and temporal scales through the development of saturated areas occurring when the aquifer reaches the surface. While this interaction exerts a strong control in the partitioning of water between base flow, seepage flow and overland flow, its quantification remains a challenge. Here, we propose a novel modeling approach based on two equivalent hillslopes to capture spatial and temporal variabilities of the main processes. We calibrate their subsurface hydraulic properties based on the temporal dynamics of stream discharge. The model is tested on two pilot catchments located in Brittany (France). For both catchments, the model is successfully calibrated on 40 years of stream discharge data. The results demonstrate that contrasted hydraulic properties are required, with: (1) a relatively low conductive hillslope (conductivities between 3x10–8 m/s and 2x10–6 m/s) enhancing overland flows during recharge periods while also sustaining low flows in the late recession period through slow aquifer discharge, and (2) a highly diffusive hillslope (diffusivity between 5x10–3 m2/s and 3x10–1 m2/s) dominantly shaping the event- to seasonal-scale streamflow recession behavior. The strong contrast of the two hillslopes reveals the fundamental role of heterogeneity in controlling groundwater storage-discharge functions, ruling out any homogeneous equivalent at the catchment scale. Low flows appear to be a non-obvious combination of the contributions of the two hillslopes, the less diffusive hillslope catching up to the more conductive one by the end of the low flow period. Catchment-scale responses integrate complex interactions between recharge, groundwater and overland flows through the volume of subsurface storage and the extent of the saturated area.

Broad scale assessment of key drivers of streamflow generation in urban and urbanizing rivers

AbstractUrbanization is characterized by increased impervious cover, artificial drainage via sewers, soil compaction, and vegetation removal, which fundamentally alters how water moves across landscapes. Less rainwater and snowmelt infiltrate the subsurface and stream responses to precipitation are faster and larger compared to natural environments. While the impacts of catchment imperviousness on hydrologic processes have been widely investigated, the relationship between stream hydrologic response and infrastructure‐mediated hydrologic connectivity across a wide range of urban watersheds has not. This study examines the relative magnitude of control that catchment characteristics, total impervious area (TIA), and sewer‐corrected TIA have on broad‐scale spatial variability in hydrologic response. Sewer‐corrected TIA accounts for inter‐catchment water transfer via storm and/or combined sewer pipes and is feasible to estimate at the watershed‐scale using urban drainage asset data. Daily stream discharge data were used to calculate the Richards‐Baker Flashiness Index for 96 watersheds located across southern Ontario, Canada. For a subset of watersheds (n = 39) with suitable stream discharge and rainfall data, watershed average event runoff ratio (RR) was calculated, and watersheds with spatial sewer network data (n = 24), were used to assess if sewer‐corrected TIA is a better predictor of hydrologic response than TIA. As expected, stream flashiness and RR increased linearly as a function of TIA and sewer‐corrected TIA, however, sewer‐corrected TIA did not explain any additional variability in the response variables. Likewise, the relative control of catchment characteristics on the spatial variability in streamflow generation were negligible. Despite sewer‐corrected TIA not improving our understanding of broad scale variation in runoff response, it could be a useful metric to consider when assessing inter‐event variability in runoff response of, heavily urbanized sub‐catchments for improved understanding of flooding and water quality.

Water availability drives instream conditions and life-history of an imperiled desert fish: A case study to inform water management

In arid ecosystems, available water is a critical, yet limited resource for human consumption, agricultural use, and ecosystem processes—highlighting the importance of developing management strategies to meet the needs of multiple users. Here, we evaluated how water availability influences stream thermal regimes and life-history expressions of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) in the arid Truckee River basin in the western United States. We integrated air temperature and stream discharge data to quantify how water availability drives stream temperature during annual spawning and rearing of Lahontan cutthroat trout. We then determined how in situ stream discharge and temperature affected adult spawning migrations, juvenile growth opportunities, and duration of suitable thermal conditions. Air temperatures had significant, large effects (+) on stream temperature across months; the effects of discharge varied across months, with significant effects (−) during May through August, suggesting increased discharge can help mitigate temperatures during seasonally warm months. Two models explained adult Lahontan cutthroat trout migration, and both models indicated that adult Lahontan cutthroat trout avoid migration when temperatures are warmer (~ > 12 °C) and discharge is higher (~ > 50 m3*s−1). Juvenile size was best explained by a quadratic relationship with cumulative degree days (CDD; days>4 °C) as size increased with increasing CDDs but decreased at higher CDDs. We also found an interaction between CDDs and discharge explaining juvenile size: when CDDs were low, higher discharge was associated with larger size, but when CDDs were high, higher discharge was associated with smaller size. Stream temperatures also determined the duration of juvenile rearing, as all juvenile emigration ceased at temperatures >24.4 °C. Together, our results illustrated how stream discharge and temperature shape the life-history of Lahontan cutthroat trout at multiple stages and can inform management actions to offset warming temperatures and facilitate life-history diversity and population resilience.

A Hybrid of Copula Prediction and Time Series Computation to Estimate Stream Discharge Based on Precipitation Data

AbstractStream discharge is a key hydrological factor for water supply planning, wetland loss investigation, ecological service assessment, and climate change impact estimation. Conceptually, stream discharge is expected to be highly and positively related to precipitation. In reality, however, such a relationship may be weaker because precipitation characteristics are affected by local climate of watersheds. For many watersheds around the world, a vast amount of precipitation data are readily available but the stream discharge data are very limited or unavailable. It would be time‐saving and cost‐effective to predict stream discharge based on precipitation data. Unfortunately, this task is very difficult to achieve using the traditional methods. Although the copula method is able to establish a good relationship (or a good dependence structure) between discharges and precipitations, this relationship does not include the time series process, and thus is impractical for applications. Therefore, a hybrid of copula prediciton and time series computation was developed (with detailed procedures) here to estimate stream discharge based on precipitation data. The method was validated using the measured daily discharges with the good statistical measures, that is, the Kandell’s τ (0.42–0.44), normalized root mean square error (2.19–2.28 m3/s), and R2 (0.66–0.84). This study suggests that the hybrid method is a useful tool to predict stream discharges based on precipitation data.

Tracer‐aided modelling reveals quick runoff generation and young streamflow ages in a tropical rainforest catchment

AbstractThere is still limited understanding of where stream water originates, their flow paths, how water sources mix, and for how long water transits montane tropical catchments. Here, we used a simple gamma convolution integral model (GM), ensemble hydrograph separation (EHS) and a tracer‐aided model (TAM) to assess runoff generation, mixing processes and water ages in the pristine tropical rainforest Quebrada Grande catchment in Costa Rica. Model simulations are based on a four‐year record (2016–2019) of continuous hydrometric and stable isotope observations. Comparative model tests included multi‐objective calibration (2017–2019) and validation (2016) using stream discharge and isotope data as well as an independent model evaluation using groundwater and soil water isotope data. GM and TAM agreed on the dominance of young water in streamflow that was less than 95 days old for 75% of the study period. The EHS suggested a young water fraction threshold of 12 ± 2 days with a transit time distribution that approximates the best‐fit GM. These short water ages are the result of high annual rainfall even during drier years such as 2019 with 4300 mm/a and consistent quick near‐surface runoff generation with limited mixing. A supra‐regional loss (~55%) of likely older groundwater was detected. The TAM‐based hydrograph separation (streamflow KGE &gt; 0.78, δ2H KGE &gt; 0.90) suggested an average near‐surface water contribution of more than 60% to streamflow emphasizing the dominance of quick flow paths. This tropical rainforest represents one of the quickest streamflow responses of mostly young water of pristine catchments globally.

Identificação da interação rio-aquífero, por meio de gradientes de temperatura, em área de afloramento do Aquífero Guarani

ABSTRACT The use of temperature as a natural tracer in hydrology is noticed since the 1960s. In recent years, there has been a revival of the use of this physical property in the investigation of water cycle. The main reasons are the cost reduction of temperature measurements and the development of distributed temperature sensing. Here, we present a study of the groundwater-surface water interaction in the Onça Creek Watershed (Guarani Aquifer System outcrop) using stream discharge data and temperature as a natural tracer. Two Parshall flumes were installed 1.2 km apart to quantify stream discharge and determine groundwater contribution. We used an optic fiber cable to identify interaction locations and a probe with thermistors to measure the vertical temperature gradient and estimate flux rates. The results show a discharge difference of ~250 m3.h-1 between both flumes, which we interpret as baseflow contribution. The distributed temperature sensing allowed the identification of regions with gaining behavior. Discharge rates between 200 and 300 mm.day-1 were determined from vertical temperature measurements, which agrees with the streamflow data. The study demonstrated that temperature is attractive as natural tracer in tropical conditions, where the groundwater temperature is higher than the surface water temperature, especially during the winter.

Long‐term precipitation and stream discharge records at seven forested experimental watersheds along a latitudinal transect in Japan: Jozankei, Kamabuchi, Takaragawa, Tsukuba, Tatsunokuchi‐yama, Kahoku and Sarukawa

AbstractThis data note introduces a database of long‐term daily total precipitation and stream discharge data for seven forested watersheds in Japan that have been continuously monitored by the Forestry and Forest Products Research Institute. Three of the watersheds started data collection in the 1930s. Forest cover across the sites ranges from cool to warm temperate regions with the latitude spanning from 31 to 44° N and annual precipitation ranging from 1200 to 3000 mm yr−1. The effects of vegetation change via clearcutting, thinning and forest fire (among other stressors) on stream discharge can be analysed from the long‐term observation sites. Moreover, this multi‐site dataset allows for inter‐ and intra‐site comparisons of annual water loss (difference of annual precipitation and stream discharge). These long‐term datasets can provide comprehensive insights into the effects of climate change and other stressors on forested ecosystems, not only in Japan but across a spectrum of forest types, if combined with other long‐term records from other forested watersheds across the world.

A water-level based calibration of rainfall-runoff models constrained by regionalized discharge indices

Rainfall-runoff models are generally calibrated by using continuous stream discharge data. However, most catchments around the globe remain ungauged due to the difficulty in installing gauges in river channels with complex morphology and due to the high costs of installation and maintenance. Recently, new calibration methods that use water level data instead of gauged discharge to calibrate rainfall-runoff models have been proposed. With emerging low-cost local water-level monitoring technologies or with satellite altimetry, these water-level based calibration methods have the potential to significantly extend runoff prediction capability. However, rainfall-runoff models calibrated from using water-level information alone may lead to biased discharge even when water-level variations are accurately reproduced. It has been shown that this bias problem can be significantly alleviated when just a few discharge measurements, especially of high flows, are available and incorporated into the model calibration. However, it is rare to have discharge measurement data when catchments are ungauged. In this study, we incorporate discharge estimates derived from regionalization into a water-level based calibration using an inverse rating curve (IRC) method. Specifically, discharge indices such as the 95th percentile of daily discharge (Q95) and the mean daily discharge (Qmean) are estimated from catchment and climate characteristics based on regionalized relationships. These estimated discharge indices are then used to constrain the IRC calibration. We evaluate both constrained and unconstrained IRC methods over 130 study catchments where observed discharge time series are available but used only for validation in this study. Modelled discharge time series from the constrained IRC methods have median Nash Sutcliffe Efficiency (NSE) values of 0.61–0.63, compared with 0.54 from the unconstrained IRC method. Improvement is seen in around 75% of the catchments, with more than 0.2 increase in NSE values in 25% of the catchments. Improvement in the modelled discharges from using regionalized discharge indices is comparable to using observed discharge indices. Using regionalized Qmean yields greater improvement than using regionalized Q95. The constrained IRC methods tend to perform better in wetter catchments than in drier ones. This method can significantly extend rainfall-runoff model calibration in a wider range of catchments, including real ungauged catchments.

Flood Impacts on Critical Infrastructure in a Coastal Floodplain in Western Puerto Rico during Hurricane María

Flooding during extreme weather events damages critical infrastructure, property, and threatens lives. Hurricane María devastated Puerto Rico (PR) on 20 September 2017. Sixty-four deaths were directly attributable to the flooding. This paper describes the development of a hydrologic model using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), capable of simulating flood depth and extent for the Añasco coastal flood plain in Western PR. The purpose of the study was to develop a numerical model to simulate flooding from extreme weather events and to evaluate the impacts on critical infrastructure and communities; Hurricane María is used as a case study. GSSHA was calibrated for Irma, a Category 3 hurricane, which struck the northeastern corner of the island on 7 September 2017, two weeks before Hurricane María. The upper Añasco watershed was calibrated using United States Geological Survey (USGS) stream discharge data. The model was validated using a storm of similar magnitude on 11–13 December 2007. Owing to the damage sustained by PR’s WSR-88D weather radar during Hurricane María, rainfall was estimated in this study using the Weather Research Forecast (WRF) model. Flooding in the coastal floodplain during Hurricane María was simulated using three methods: (1) Use of observed discharge hydrograph from the upper watershed as an inflow boundary condition for the coastal floodplain area, along with the WRF rainfall in the coastal flood plain; (2) Use of WRF rainfall to simulate runoff in the upper watershed and coastal flood plain; and (3) Similar to approach (2), except the use of bias-corrected WRF rainfall. Flooding results were compared with forty-two values of flood depth obtained during face-to-face interviews with residents of the affected communities. Impacts on critical infrastructure (water, electric, and public schools) were evaluated, assuming any structure exposed to 20 cm or more of flooding would sustain damage. Calibration equations were also used to improve flood depth estimates. Our model included the influence of storm surge, which we found to have a minimal effect on flood depths within the study area. Water infrastructure was more severely impacted by flooding than electrical infrastructure. From these findings, we conclude that the model developed in this study can be used with sufficient accuracy to identify infrastructure affected by future flooding events.

Trend analysis of selected hydro-meteorological variables for the Rietspruit sub-basin, South Africa

AbstractIdentifying hydro-meteorological trends is critical for assessing climate change and variability both at a basin and regional level. This study examined the long- and short-term trends from stream discharge, temperature, and rainfall data around the Rietspruit sub-basin in South Africa. The data were subjected to homogeneity testing before performing the trend tests. Inhomogeneity was widely detected in discharge data, hence no further analyses were performed on such data. Temperature and rainfall trends and their magnitudes at yearly, seasonal, and monthly time steps were identified after applying the non-parametric Mann-Kendall and Sen's slope estimator. The possible starting point of a trend was determined by performing the sequential Mann-Kendall test. This study revealed a combination of upward and downward trends in both temperature and rainfall data for the time steps under observation. For rainfall on an annual basis, there were no statistically significant monotonic trends detected, although non-significant downward trends were dominant. However, significant decreasing rainfall trends were observed in dry and low rainfall months, which were April, August, September, and November. In contrast, significant upward temperature trends were detected at the Vereeniging climate station at an annual scale and in October, November, spring, and winter. The findings are critical for climate risk management and reduction decisions for both near- and long-term timescales.

Catchment landscape components alter relationships between discharge and stream water nutrient ratios in the Xitiao River Basin China

The terrestrial environment of a watershed is a source of potential carbon (C), nitrogen (N), and phosphorus (P) exports, and the hydrological regime provides the mechanism to turn the potential exports into reality when water is available. However, the extent to which the terrestrial environment alters the strength and nature of streamflow in transporting stream water nutrient ratios remains largely unknown. This study combined monthly stream discharge data with synchronously sampled stream water C:N:P ratios in 14 catchment streams in the Xitiao River Basin (XRB) in Zhejiang Province, China. The transport effect of streamflow on C:N:P ratios varied depending on the nutrient element, flow condition, and terrestrial environment. In the lower reaches of the XRB, there were negative relationships between C:N ratios, C:P ratios and watershed discharge, and positive relationships between N:P ratios and watershed discharge in both high and low flow conditions. In the middle and upper reaches of the XRB, the C:N-discharge relationship changed from negative to positive when the streamflow conditions altered from low to high flow. The C:P- and N:P-discharge relationships were negative regardless of high or low flows, but the regression coefficient significantly decreased with increasing streamflow. The C:N-discharge correlation over the course of the year shifted from negative to positive, as urban areas expanded within the catchment. The C:P-discharge relationship altered from negative to positive with more cropland and wetland but from positive to negative with a greater forest percentage and mean percentage slope. Our results indicate that changes in the terrestrial environment (e.g., the proportion of a particular land cover within a watershed) generally produced a threshold flow above which the coupling relationships between element fluxes from the terrestrial to riverine ecosystem changed sharply.

A Streamflow Bias Correction and Performance Evaluation Web Application for GEOGloWS ECMWF Streamflow Services

We present the development and testing of a web application called the historical validation tool (HVT) that processes and visualizes observed and simulated historical stream discharge data from the global GEOGloWS ECMWF streamflow services (GESS), performs seasonally adjusted bias correction, computes goodness-of-fit metrics, and performs forward bias correction on subsequent forecasts. The HVT corrects GESS output at a local scale using a technique that identifies and corrects model bias using observed hydrological data that are accessed using web services. HVT evaluates the performance of the GESS historic simulation data and provides more accurate historic simulation and bias-corrected forecast data. The HVT also allows users of the GEOGloWS historical streamflow data to use local observed data to both validate and improve the accuracy of local streamflow predictions. We developed the HVT using Tethys Platform, an open-source web application development framework. HVT presents data visualization using web mapping services and data plotting in the web map interface while functions related to bias correction, metrics reporting, and data generation for statistical analysis are computed by the back end. We present five case studies using the HVT in Australia, Brazil, Colombia, the Dominican Republic, and Peru. In these case studies, in addition to presenting the application, we evaluate the accuracy of the method we implemented in the HVT for bias correction. These case studies show that the HVT bias correction in Brazil, Colombia, and Peru results in significant improvement in historic simulation across the countries, while bias correction only resulted in marginal historic simulation improvements in Australia and the Dominican Republic. The HVT web application allows users to use local data to adjust global historical simulation and forecasts and validate the results, making the GESS modeling results more useful at a local scale.

Stream discharge and water quality data for East Fork Poplar Creek beginning 2012

AbstractThis data note describes 15‐min discharge and in situ water quality data at two locations along East Fork Poplar Creek in east Tennessee, USA. Data records include temperature, gauge height, water surface elevation above mean sea level, and volumetric discharge. Water quality measurements include temperature, specific conductance, pH, dissolved oxygen (percent saturation and concentration), turbidity, and less extensive fDOM data at one site. The data records begin in 2012 at one site and 2015 at the second site; monitoring at both sites is ongoing (as of 2021). The goal of this data collection is to improve understanding of watershed functions, hydrologic dynamics, and material flux. The data will contribute to site conceptual and numerical models, exposure and risk evaluation, remediation selection and design, and performance monitoring. The data are publicly available and can be accessed via unique url or DOI.

Water Balance Backward: Estimation of Annual Watershed Precipitation and Its Long-Term Trend with the Help of the Calibration-Free Generalized Complementary Relationship of Evaporation

Watershed-scale annual evapotranspiration (ET) is routinely estimated by a simplified water balance as the difference in catchment precipitation (P) and stream discharge (Q). With recent developments in ET estimation by the calibration-free generalized complementary relationship, the water balance equation is employed to estimate watershed/basin P at an annual scale as ET + Q on the United States (US) Geological Survey’s Hydrologic Unit Code (HUC) 2- and 6-level watersheds over the 1979–2015 period. On the HUC2 level, mean annual PRISM P was estimated with a correlation coefficient (R) of 0.99, relative bias (RB) of zero, root-mean-squared-error (RMSE) of 54 mm yr−1, ratio of standard deviations (RS) of 1.08, and Nash–Sutcliffe efficiency (NSE) of 0.98. On the HUC6 level, R, RS, and NSE hardly changed, RB remained zero, while RMSE increased to 90 mm yr−1. Even the long-term linear trend values were found to be fairly consistent between observed and estimated values with R = 0.97 (0.81), RMSE = 0.63 (1.63) mm yr−1, RS = 0.99 (1.05), NSE = 0.92 (0.59) on the HUC2 and HUC6 (in parentheses) levels. This calibration-free water-balance method demonstrates that annual watershed precipitation can be estimated with an acceptable accuracy from standard atmospheric/radiation and stream discharge data.