Runoff Efficiency Research Articles

Forest Dieback Alters Nutrient Pathways in a Temperate Headwater Catchment

ABSTRACTForested headwater catchments ensure good water quality for downstream ecosystems and human consumption. Climate change and the exacerbating likelihood of extreme events elevate the risk of severe forest dieback. However, the effects of forest dieback on the quantity and quality of stream water are not fully understood. Here, we analyse high‐frequency observations of discharge, electrical conductivity (EC), dissolved organic carbon (DOC) and nitrate (NO3N) obtained before, during and after a drought‐induced forest dieback in a headwater stream in the German Harz Mountains. We focus on the characteristics of concentration‐discharge (C‐Q) relationships at the scale of runoff events to assess the effects of forest dieback on the sources, mobilisation and pathways of EC, DOC and NO3N. When comparing pre‐ and post‐dieback conditions, we found a significant increase in runoff efficiency and a doubling of DOC loads exported from the catchment, while DOC concentrations increased only moderately and their C‐Q patterns did not change. EC exhibit no changes in concentrations but a steepening of C‐Q dilution patterns. We explain these findings with a dieback‐induced decrease in evapotranspiration, which leads to more intensive drainage of the upper organic soil layers in the riparian zone. In contrast, we observed a strong increase in NO3N concentrations and fluxes by a factor of ~5, while C‐Q patterns at the event scale changed from enrichment to dilution. We argue that the dieback led to an excess of NO3N on the hillslopes that connect to the stream via surficial flowpaths. In this way, NO3N bypasses the riparian zone, reducing the catchment's efficiency in attenuating this nutrient. Our study emphasises the pivotal role of riparian zones in mediating water quality in headwater streams. Different configurations of the riparian zone and its connection to the hillslopes and the stream network may be a missing piece in explaining differences in water quality responses of catchments to forest dieback.

Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to +3.5∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+3.5\\,^\\circ$$\\end{document}C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥1.7∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge 1.7\\,^\\circ$$\\end{document}C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

Flooding Resiliency of Surigao del Sur, Caraga Region, Philippines Residences Through Rainwater Catchment and Storage System

Urbanised areas in Northeastern Mindanao have a problem of addressing flooding occurrences. This study primarily aimed to provide insights into how the rainwater catchment system of uptown communities and their cooperation could increase flood resiliency of downtown communities in the Surigao del Sur, Caraga Region, Philippines. This research employed quantitative analysis of the eleven (11) year (2010-2020) data from the Philippine Atmospheric, Geophysical, and Astronomical Services Administration - Hinatuan, Surigao del Sur station. The recommendable optimum rainwater storage capacities for a given number of household occupants, roof areas at run-off efficiency of 90%, and three (3) day rainfall characteristics at 36.9% averaged probability of exceedance were initially determined. Through scenario analysis, uptown communities emptying their rainwater storages before heavy downpour occurs could provide sufficient flood volume reduction and buffer time for downtown communities to prepare. The output of this research is vital in the environmental planning, management, and policies of cities and regions.

Potential Predictability of Two-Year Droughts in the Missouri River Basin

Abstract Potential predictability of 2-yr droughts indicated by low runoff in the consecutive April–September seasons in the upper Missouri River basin (UMRB) and lower Missouri River basin (LMRB) is examined with observed estimates and climate models. The majority of annual runoff is generated in April–September, which is also the main precipitation and evapotranspiration season. Physical features related to low April–September runoff in both UMRB and LMRB include a dry land surface state indicated by low soil moisture, low snowpack indicated by low snow water equivalent, and a wave train across the Pacific–North American region that can be generated internally by the atmosphere or forced by the La Niña phase of El Niño–Southern Oscillation. When present in March, these features increase the risk of low runoff in the following April–September warm seasons. Antecedent low soil moisture significantly increases low runoff risks in each of the following two April–September, as the dry land surfaces decrease runoff efficiency. Initial low snow water equivalent, especially in the Missouri River headwaters of Montana, generates less runoff in the subsequent warm season. La Niña increases the risk of low runoff during the warm seasons by suppressing precipitation via dynamically induced atmospheric circulation anomalies. Model simulations that differ in their radiative forcing suggest that climate change increases the predictability of 2-yr droughts in the Missouri River basin related to La Niña. The relative risk of low runoff in the second April–September following a La Niña event in March is greater in the presence of stronger radiative forcing. Significance Statement Drought spanning consecutive years in the upper Missouri River basin (UMRB) and lower Missouri River basin (LMRB) poses threats to a region whose economy depends on reliable water quantity to support transportation and recreation, adequate water supply for irrigated agriculture, and sufficient streamflow to generate hydroelectric power. We examined physical features in March related to low runoff in the following April–September—low soil moisture, low snow water equivalent, and La Niña events—and examined their effect on the risk of 2-yr drought occurrences. These physical features lead to sustained impacts on the surface water balance. Low snow water equivalent generates less runoff, low soil moisture reduces the runoff efficiency of converting precipitation into runoff, and La Niña inhibits warm-season precipitation and runoff via atmospheric circulation anomalies.

Alignment between water inputs and vegetation green‐up reduces next year's runoff efficiency

AbstractIn the western United States, water supplies largely originate as snowmelt from forested land. Forests impact the water balance of these headwater streams, yet most predictive runoff models do not explicitly account for changing snow‐vegetation dynamics. Here, we present a case study showing how warmer temperatures and changing forests in the Henrys Fork of the Snake River, a seasonally snow‐covered headwater basin in the Greater Yellowstone Ecosystem, have altered the relationship between April 1st snow water equivalent (SWE) and summer streamflow. Since the onset and recovery of severe drought in the early 2000s, predictive models based on pre‐drought relationships over‐predict summer runoff in all three headwater tributaries of the Henrys Fork, despite minimal changes in precipitation or snow accumulation. Compared with the pre‐drought period, late springs and summers (May–September) are warmer and vegetation is greener with denser forests due to recovery from multiple historical disturbances. Shifts in the alignment of snowmelt and energy availability due to warmer temperatures may reduce runoff efficiency by changing the amount of precipitation that goes to evapotranspiration versus runoff and recharge. To quantify the alignment between snowmelt and energy on a timeframe needed for predictive models, we propose a new metric, the Vegetation‐Water Alignment Index (VWA), to characterize the synchrony of vegetation greenness and snowmelt and rain inputs. New predictive models show that in addition to April 1st SWE, the previous year's VWA and summer reference evapotranspiration are the most significant predictors of runoff in each watershed and provide more predictive power than traditionally used metrics. These results suggest that the timing of snowmelt relative to the start of the growing season affects not only annual partitioning of streamflow, but can also determine the groundwater storage state that dictates runoff efficiency the following spring.

Evaluating Noah‐MP Simulated Runoff and Snowpack in Heavily Burned Pacific‐Northwest Snow‐Dominated Catchments

AbstractTerrestrial hydrology is altered by fires, particularly in snow‐dominated catchments. However, fire impacts on catchment hydrology are often neglected from land surface model (LSM) simulations. Western U.S. wildfire activity has been increasing in recent decades and is projected to continue increasing over at least the next three decades, and thus it is important to evaluate if neglecting fire impacts in operational land surface models (LSMs) is a significant error source that has a noticeable signal among other sources of uncertainty. We evaluate a widely used state‐of‐the‐art LSM (Noah‐MP) in runoff and snowpack simulations at two representative fire‐affected snow‐dominated catchments in the Pacific Northwest: Andrew's Creek in Washington and Johnson Creek in Idaho. These two catchments are selected across all western U.S. fire‐affected catchments because they are snow‐dominated and experienced more than 50% burning in a single fire event with minimal burning outside of this event, which allows analyses of distinct pre‐ and post‐fire periods. There are statistically significant shifts in model skills from pre‐to post‐fire years in simulating runoff and snowpack. At both study catchments, simulations miss enhancements in early‐spring runoff and annual runoff efficiency during post‐fire years, resulting in persistent underestimates of annual runoff anomalies throughout the 12‐year post‐fire analysis periods. Enhanced post‐fire snow accumulation and melt contributes to observed but unmodeled increases of spring runoff and annual runoff efficiency at these catchments. Informing simulations with satellite observed land cover classifications, leaf area index, and green fraction do not consistently improve the model ability to simulate hydrologic responses to fire disturbances.

Spatial variation in drainage area — Runoff relationships and implications for bankfull geometry scaling

Fluvial geomorphic analyses frequently require knowledge of bankfull channel geometries, which are thought to be related to characteristic stream discharges. However, relating bankfull geometry to characteristic discharge is challenged by spatially limited stream discharge measurements, which may also lack extensive temporal records. Because of these limitations, discharge is commonly assumed to scale linearly with watershed drainage area. Here we evaluate the assumption of a linear relationship between discharge and drainage area for watersheds across the United States and Canada with limited anthropogenic disturbance. Using machine-learning to objectively cluster hydrologically similar gauges, we find that discharge scales linearly with drainage area for most of North America. However, regions with low average runoff efficiency tend to have non-linear discharge scaling. In regions with non-linear discharge scaling, bankfull channel dimensions increase more rapidly with drainage area than in regions with linear discharge scaling. These results suggest that the recurrence interval of the characteristic discharge that sets channel geometry may be larger in regions where discharge scales non-linearly with drainage area compared to those regions where linear discharge scaling applies.

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.

Asymmetric emergence of low-to-no snow in the midlatitudes of the American Cordillera

Societies and ecosystems within and downstream of mountains rely on seasonal snowmelt to satisfy their water demands. Anthropogenic climate change has reduced mountain snowpacks worldwide, altering snowmelt magnitude and timing. Here the global warming level leading to widespread and persistent mountain snowpack decline, termed low-to-no snow, is estimated for the world’s most latitudinally contiguous mountain range, the American Cordillera. We show that a combination of dynamical, thermodynamical and hypsometric factors results in an asymmetric emergence of low-to-no-snow conditions within the midlatitudes of the American Cordillera. Low-to-no-snow emergence occurs approximately 20 years earlier in the southern hemisphere, at a third of the local warming level, and coincides with runoff efficiency declines (8% average) in both dry and wet years. The prevention of a low-to-no-snow future in either hemisphere requires the level of global warming to be held to, at most, +2.5 °C.

The Simulation and Subseasonal Forecasting of Hydrological Variables: Insights from a Simple Water Balance Model

Abstract Past work has shown that a land surface model’s (LSM) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM’s hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the United States, and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in nature and can serve as potentially useful targets for further LSM development. Significance Statement For all their complexity, and for all the work that underlies their development, the land surface model components of Earth system models may be suboptimal in fundamental yet unstudied ways. Here we estimate how the joint control of soil moisture over evapotranspiration and runoff processes in nature differs from that built implicitly into a state-of-the-art land model. Validation exercises demonstrate how this difference appears to lead to reduced accuracy in the land model’s simulation and forecasting of such hydrological variables as streamflow and soil moisture. Our results indicate that the relationships estimated for nature could serve as a potentially valuable target for further land model development.

Investigating the Role of Snow Water Equivalent on Streamflow Predictability during Drought

Abstract Snowpack provides the majority of predictive information for water supply forecasts (WSFs) in snow-dominated basins across the western United States. Drought conditions typically accompany decreased snowpack and lowered runoff efficiency, negatively impacting WSFs. Here, we investigate the relationship between snow water equivalent (SWE) and April–July streamflow volume (AMJJ-V) during drought in small headwater catchments, using observations from 31 USGS streamflow gauges and 54 SNOTEL stations. A linear regression approach is used to evaluate forecast skill under different historical climatologies used for model fitting, as well as with different forecast dates. Experiments are constructed in which extreme hydrological drought years are withheld from model training, that is, years with AMJJ-V below the 15th percentile. Subsets of the remaining years are used for model fitting to understand how the climatology of different training subsets impacts forecasts of extreme drought years. We generally report overprediction in drought years. However, training the forecast model on drier years, that is, below-median years (P15, P57.5], minimizes residuals by an average of 10% in drought year forecasts, relative to a baseline case, with the highest median skill obtained in mid- to late April for colder regions. We report similar findings using a modified National Resources Conservation Service (NRCS) procedure in nine large Upper Colorado River basin (UCRB) basins, highlighting the importance of the snowpack–streamflow relationship in streamflow predictability. We propose an “adaptive sampling” approach of dynamically selecting training years based on antecedent SWE conditions, showing error reductions of up to 20% in historical drought years relative to the period of record. These alternate training protocols provide opportunities for addressing the challenges of future drought risk to water supply planning. Significance Statement Seasonal water supply forecasts based on the relationship between peak snowpack and water supply exhibit unique errors in drought years due to low snow and streamflow variability, presenting a major challenge for water supply prediction. Here, we assess the reliability of snow-based streamflow predictability in drought years using a fixed forecast date or fixed model training period. We critically evaluate different training protocols that evaluate predictive performance and identify sources of error during historical drought years. We also propose and test an “adaptive sampling” application that dynamically selects training years based on antecedent SWE conditions providing to overcome persistent errors and provide new insights and strategies for snow-guided forecasts.

Basin management inspiration from impacts of alternating dry and wet conditions on water production and carbon uptake in Murray-Darling Basin

The impacts of alternating dry and wet conditions on water production and carbon uptake at different scales remain unclear, which limits the integrated management of water and carbon. We quantified the response of runoff efficiency (RE) and plant water-use efficiency (PWUE) to a typical shift from dry to wet episode of 2003–2014 in Australia's Murray-Darling basin using good and specific data products for local application, including Australian Water Availability Project, Penman-Monteith-Leuning Evapotranspiration V2 product, MODIS MCD12Q1 V6 Land Cover Type and MODIS MOD17A3 V055 GPP product. The results show that there are significant power function relationships between RE and precipitation for basin and all ecosystems, while the PWUE had a negative quadratic correlation with precipitation and satisfied the significance levels of 0.05 for basin and the ecosystems except the grassland and cropland. The shrubs can achieve the best water production and carbon uptake under dry conditions, while the evergreen broadleaf trees and evergreen needleleaf trees can obtain the best water production and carbon uptake in wet conditions, respectively. These findings help integrated basin management for balancing water resource production and climate change mitigation.

The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites

Abstract. The recent advances in remote sensing provide opportunities for estimating the parameters of conceptual hydrologic models more reliably. However, the question of whether and to what extent the use of satellite data in model calibration may assist in transferring model parameters to ungauged catchments has not been fully resolved. The aim of this study is to evaluate the efficiency of different methods for transferring model parameters obtained by multiple-objective calibrations to ungauged sites and to assess the model performance in terms of runoff, soil moisture, and snow cover predictions relative to existing regionalization approaches. The model parameters are calibrated to daily runoff, satellite soil moisture (Advanced Scatterometer – ASCAT), and snow cover (Moderate Resolution Imaging Spectroradiometer – MODIS) data. The assessment is based on 213 catchments situated in different physiographic and climate zones of Austria. For the transfer of model parameters, eight methods (global and local variants of arithmetic mean, regression, spatial proximity, and similarity) are examined in two periods, i.e., the period in which the model is calibrated (2000–2010) and an independent validation period (2010–2014). The predictive accuracy is evaluated by the leave-one-out cross-validation. The results show that the method by which the model is calibrated in the gauged catchment has a larger impact on runoff prediction accuracy in the ungauged catchments than the choice of the parameter transfer method. The best transfer methods are global and local similarity and the kriging approach. The performance of the transfer methods differs between lowland and alpine catchments. While the soil moisture and snow cover prediction efficiencies are higher in lowland catchments, the runoff prediction efficiency is higher in alpine catchments. A comparison of the model transfer methods, based on parameters calibrated to runoff, snow cover, and soil moisture with those based on parameters calibrated to runoff, only indicates that the former outperforms the latter in terms of simulating soil moisture and snow cover. The performance of simulating runoff is similar, and the accuracy depends mainly on the weight given to the runoff objective in the multiple-objective calibrations.

Analyzing the significance of morphometric parameters in runoff efficiency: a case study in Valakkayi Tode tropical watershed, Valapattanam River, Kerala, India

Analyzing the significance of morphometric parameters in runoff efficiency: a case study in Valakkayi Tode tropical watershed, Valapattanam River, Kerala, India

Stochastic Decadal Projections of Colorado River Streamflow and Reservoir Pool Elevations Conditioned on Temperature Projections

AbstractDecadal (∼10‐year)‐scale flow projections in the Colorado River Basin (CRB) are increasingly important for water resources management and planning of its reservoir system. Physical models, ensemble streamflow prediction (ESP), do not have skill beyond interannual time scales. However, Global Climate Models have good skill in projecting decadal temperatures. This, combined with the sensitivity of CRB flows to temperature from recent studies, motivate the research question, can skill in decadal temperature projections be translated to operationally skillful flow projections and consequently, water resources management? To explore this, we used temperature projections from the Community Earth System Model‐Decadal Prediction Large Ensemble (CESM‐DPLE) along with past basin runoff efficiency as covariates in a Random Forest (RF) method to project ensembles of multiyear mean flow at the key aggregate gauge of Lees Ferry, Arizona. RF streamflow projections outperformed both ESP and climatology in a 1982–2017 hindcast, as measured by ranked probability skill score. The projections were disaggregated to monthly and subbasin scales to drive the Colorado River Mid‐term Modeling System (CRMMS) to generate ensembles of water management variables. The projections of pool elevations in Lakes Powell and Mead, the two largest U.S. reservoirs that are critical for water resources management in the basin, were found to reduce the hindcast median root mean square error by up to −20% and −30% at lead times of 48 and 60 months, respectively, relative to projections generated from ESP. This suggests opportunities for enhancing water resources management in the CRB and potentially elsewhere.

The Influence of Natural and Anthropogenic Forcing on Water and Energy Balance and on Photosynthesis

Land surface processes are rarely studied in Detection and Attribution Model Inter-comparison Project (DAMIP) experiments on climate change. We analyzed a CMIP6 DAMIP historical experiment by using multi-linear regression (MLRM) and analysis of variance methods. We focused on energy and water budgets, including gross primary productivity (GPP). In MLRM, we estimated each forcing’s contribution and identified the role of natural forcing, which is usually ignored. Contributions of the forcing factors varied by region, and high-ranked variables such as net radiation could receive multiple influences. Greenhouse gases (GHG) accelerated energy and water cycles over the global land surface, including evapotranspiration, runoff, GPP, and water-use efficiency. Aerosol (AER) forcing displayed the opposite characteristics, and natural forcing accounted for short-term changes. A long-term analysis of total soil moisture and water budget indicated that as the AER increases, the available water on the global land increases continuously. In the recent past, an increase in net radiation (i.e., a lowered AER) reduced surface moisture and hastened surface water cycle (GHG effect). The results imply that aerosol emission and its counterbalance to GHG are essential to most land surface processes. The exception to this is GPP, which was overdominated by GHG effects.

Groundwater‐Mediated Memory of Past Climate Controls Water Yield in Snowmelt‐Dominated Catchments

AbstractAccelerating warming, changes in the amount, timing, and form of precipitation, and rapidly growing populations highlight the need for improved predictions of snowmelt‐driven water supplies. Although decadal‐scale trends in reduced streamflow are common, minimal progress has been made in improving streamflow prediction on the annual time scales on which management decisions are made. Efficient allocation of dwindling supplies requires incorporating rapidly evolving knowledge of streamflow generation into parsimonious models capable of improving prediction on seasonal, annual, and multiyear time scales of water resource management. We address this need using long‐term streamflow and climate records in 12 catchments averaging 90 years of observations and totaling more than 1,080 site‐years of data. These catchments experience similar regional climate forcing each year, but are diverse enough to represent broad ranges in precipitation, temperature, vegetation, and geology characteristic of much of the western US. We find that January baseflow across all catchments exhibits a coherent, quasi‐decadal periodicity that presumably is indicative of groundwater response to decadal climate. Although the direct contribution of this discharge to streamflow is small, interannual variability in groundwater discharge is a consistently strong predictor of runoff efficiency suggesting that antecedent groundwater storage alters precipitation routing to streamflow. Incorporating antecedent groundwater storage with precipitation and melt dynamics in multiple linear regression models reduces uncertainty in annual runoff from approximately 40% to <5%. These simple models, using readily available data, provide immediately useful tools for water managers to anticipate and respond to streamflow variability on time scales of 1 to 10 years.

Enhancing nitrate and phosphorus removal from stormwater in a fold-flow bioretention system with saturated zones.

The traditional bioretention systems possess a remarkably low nitrogen and phosphorus removal effect. The removal rate fluctuates greatly, and even appears as negative removal of nitrogen and phosphorus. Four simulated bioretention experimental columns with different bilayer media, packing composition and structure were constructed. Based on the traditional fillers, the modified composite fillers with hydroxy-aluminum and modified vermiculite sludge particle (HAVSP) were added. The traditional filler (C1) and the modified composite filler (C2) were added respectively, moreover saturated zones were set up to enhance the effect of nitrogen and phosphorus removal. Removal of nutrients from experimental columns by simulated runoff efficiency was evaluated and compared. In addition, the effect of media depth on phosphorus retention and denitrifying enzyme activity in bioretention columns was also evaluated. The experimental column #2 filled with C2 had the optimum removal effect on TP (93.70%), however, the removal effect of TP by filling C1 experimental columns was insufficient (57.36%). Designed to remove nitrate (NO3--N) and total nitrogen, the experimental column #4 showed the best performance (83.54% and 92.15%, respectively). In this study, we propose a fold-flow bioretention system by filling HAVSP in combination with saturated zones. The runoff water quality can be effectively improved, and a new bioretention cell configuration can be provided for efficient stormwater treatment.

Responses of Runoff and Soil Loss on Slopes to Land Use Management and Rainfall Characteristics in Northern China.

Soil conservation measures are widely used to control soil erosion and sediment loss; however, their proper usage relies on a deep understanding of the responses of runoff and sediment loss to land management and rainfall characteristics. In the present study, a long-term (2014–2020) monitored dataset derived from ten runoff plots in the upstream catchment of the Miyun Reservoir in Beijing, China, was used to study runoff and sediment loss responses to land use management and rainfall characteristics. The study results show that plots with no soil conservation measures had the highest runoff depth of 75 mm and suffered the highest sediment loss, at a rate of 3200 t km−2 yr−1. The terraced and vegetated plots generated lower runoff depths, with soil loss rates less than 213.0 t km−2 yr−1. With the exception of the contour tillage plots on steep slopes, the vegetation and engineering measures can efficiently reduce runoff and sediment loss, with both runoff and sediment reduction efficiencies higher than 76%. Statistical analyses indicate that, on the plots of bare soil and cultivation without soil conservation measures, runoff and sediment loss were mainly affected by the maximum 30 min rainfall intensity. However, on the plots with soil conservation measures, they were mainly determined by rainfall amount and duration. The sediment loss rate can be well fitted with the runoff depth using a power function. Based on the analyses, water-saving soil conservation measures are recommended for the study area. In addition, the size of terraces should be reconsidered on gentle slopes, and the coverage of forest, shrubs, and grass on slopes should be reduced, thus allowing for more surface runoff generation to ensure drinking water safety. In general, for the study area, soil conservation measures are required on the bare soil and cultivated slopes.

The sensitivity of runoff generation to spatial snowpack uniformity in an alpine watershed: Green Lakes Valley, Niwot Ridge Long‐Term Ecological Research station

AbstractSeasonal water storage in high‐elevation alpine catchments are critical sources of water for mountainous regions like the western U.S. The spatial distribution of snow in these topographically complex catchments is primarily governed by orography, solar radiation, and wind redistribution. While the effect of solar shading is relatively consistent from year‐to‐year, the redistribution of snow due to wind is more variable – capable of producing snowpacks that have varying degrees of uniformity across these hydrologically‐important catchments. A reasonable hypothesis is that a warmer climate will cause snowfall to become more dense (i.e. wetter and heavier), possibly leading to less wind redistribution and thus produce a more uniformly distributed snowpack across the landscape. In this study, we investigate the role of increasingly uniform spatial snowpack distributions on streamflow generation in the Green Lakes Valley Niwot Ridge Long Term Ecological Research station, within the headwaters of the Boulder Creek watershed in Colorado. A set of idealized hydrologic simulation experiments driven by reconstructed snowpacks spanning 2001–2014 show that more a more uniform spatial snowpack distribution leads to an earlier melt‐out of 31 days on average and tends to produce less total streamflow, with maximum decreases as large as 7.5%. Isolating the role of snowpack heterogeneity from melt‐season precipitation, we find that snowpack uniformity reduces total streamflow by as much as 13.2%. Reductions in streamflow are largely explained by greater exposure to solar radiation in the uniformly distributed case relative to a more heterogeneous snowpack, with this exposure driving shifts towards earlier snowmelt and changes in soil water storage. Overall, we find that the runoff efficiency from shallower snowpacks is more sensitive to the effects of uniformity than deeper snowpacks, which has potential implications for a warming climate where shallower snowpacks and enhanced sensitivities may be present.