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Sediment core and water quality data, together with historical information on land use/land cover (LULC), were used to reconstruct changes in phosphorus (P) loading and cycling in Lake Wilcox, Ontario, Canada, since the early 1920s. After first being cleared for farming, the originally forested watershed subsequently underwent urbanization. The large increase in P loading accompanying agricultural intensification after World War II caused the eutrophication of the lake. However, improved soil conservation since the 1980s and urban stormwater management since the 1990s have brought watershed P loading and sediment accumulation down to levels comparable to the early 1900s. Yet, the lake continues to exhibit eutrophication‐like symptoms, especially the intensification of hypoxia in the hypolimnion. Post‐2000 water quality data indicate that the latter is not driven by external P loading from the watershed, but rather by rapid salinization that strengthens the lake's summer stratification and enhances internal P loading. Salinization is caused by the increasing application of deicing agents in the expanding urban area. Curbing salt inputs will therefore be essential to restore the lake. Overall, our results provide new insights into the shifts in lake biogeochemistry associated with LULC changes and the implementation of best management practices. The approaches and findings of our case study have broad applicability for the large number of freshwater ecosystems worldwide that are experiencing salinization. Plain Language Summary: The impacts of a century of land use changes on a receiving lake were analyzed, from the early land clearing for farming to the recent rapid urban growth. We focused on the loading of the nutrient element phosphorus (P) to the lake and the resulting changes in water quality and biological productivity. The lake experienced the highest P loading during the period of intensive farming following World War II, which stimulated algal growth and the depletion of dissolved oxygen in the lake's deeper part. Since the 1980s, soil conservation measures have helped in reducing P loading and reversing water quality deterioration. From the early 1990s till today, as the urban area expanded, the lake saw its P loading drop to its lowest level because of the retention of P in urban stormwater ponds. Nonetheless, the lake still suffers from low oxygen concentrations. This is explained by the rising application of road salt in the urban areas of the watershed. The saltier runoff makes it more difficult for the lake to mix and reduces the amount of oxygen in the deeper waters. Thus, controlling salt, rather than P, loading to the lake will be needed to restore the lake. Key Points: Sediment core data link historical changes in land use/land cover to lake phosphorus loading, trophic state, and bottom water oxygenationExternal phosphorus loading and sediment burial peaked during agricultural intensification and dropped with urbanization of the watershedAgricultural soil conservation practices and urban stormwater ponds are very effective at lowering watershed phosphorus exports [ABSTRACT FROM AUTHOR]

Excess nutrient inputs from agricultural and urban sources have accelerated eutrophication and increased the incidence of algal blooms in the Great Lakes Basin (GLB). Lake basin management to address these threats relies on understanding the key drivers of pollution. Here, we use a random forest machine learning model to leverage information from 202 monitored streams in the GLB to predict seasonal and annual flow‐weighted concentrations of nitrogen and phosphorus, as well as nutrient ratios across the GLB. Land use (agricultural and urban land) and land management (tile drainage and wetland density) emerge as the two most important predictors for dissolved inorganic nitrogen (DIN; NO3− + NO2−) and soluble reactive phosphorus (SRP; PO43), while soil type and wetland density are more important for particulate P (PP). Partial dependence plots demonstrate increasing nutrient concentrations with increasing tile density and decreasing wetland density. In addition, increasing tile and livestock densities and decreasing forest cover correspond to higher SRP:Total Phosphorus (TP) ratios. Seasonally, the highest proportions of SRP occur in summer and fall. Higher livestock densities are also correlated with increasing N:P (DIN:TP) ratios. Livestock operations can contribute to the buildup of soil nutrients from excess manure application, while increasing subsurface drainage can provide transport pathways for dissolved nutrients. Given that both SRP:TP and the N:P ratios are strong predictors of harmful algal blooms, our study highlights the importance of livestock management, drainage management, and wetland restoration in efforts to address eutrophication in intensively managed landscapes. Plain Language Summary: While attempts have been made to improve water quality and reduce algal blooms in the Great Lakes Basin, we still have a limited understanding of where the greatest inputs of nutrients to the lakes are coming come from and why. In the current study, we have used nitrogen and phosphorus concentration data from over 200 monitoring stations around the Great Lakes to model daily, seasonal, and annual concentrations and to link these concentration magnitudes to a variety of watershed characteristics. Our results show that land use and land management are important predictors of nitrogen and phosphorus concentrations, with tile drainage emerging as a key driver of higher nitrate and soluble phosphorus concentrations. For particulate phosphorus, however, our results show that soil type and wetland density are more important predictors. Higher tile drainage densities and livestock densities were found to be associated with higher N:P ratios and higher ratios of soluble to total phosphorus. We also found that concentrations of soluble reactive phosphorus are highest during the summer and fall months in watersheds dominated by agriculture, which is in contrast to seasonal patterns observed in less‐impacted watersheds. Understanding watershed drivers of nutrient concentrations is critical for managing and improving water quality Key Points: Random forest model, developed using data from 202 streams, identifies various land use and management controls on nutrientsHigh livestock densities correspond with greater proportions of bioavailable P and higher N:P ratios, and thus greater risk of bloomsThe highest proportions of bioavailable P occur seasonally in summer and fall, and in the Lake Erie Basin [ABSTRACT FROM AUTHOR]

Excess nitrogen from intensive agricultural production, atmospheric N deposition, and urban point sources elevates stream nitrate concentrations, leading to problems of eutrophication and ecosystem degradation in coastal waters. A major emphasis of current US‐scale analysis of water quality is to better our understanding of the relationship between changes in anthropogenic N inputs within watersheds and subsequent changes in riverine N loads. While most water quality modeling assumes a positive linear correlation between watershed N inputs and riverine N, many efforts to reduce riverine N through improved nutrient management practices result in little or no short‐term improvements in water quality. Here, we use nitrate concentration and load data from 478 US watersheds, along with developed N input trajectories for these watersheds, to quantify time‐varying relationships between N inputs and riverine N export. Our results show substantial variations in watershed N import‐export relationships over time, with quantifiable hysteresis effects. Our results show that more population‐dense urban watersheds in the northeastern U.S. more frequently show clockwise hysteresis relationships between N imports and riverine N export, with accelerated improvements in water quality being achieved through the implementation of point‐source controls. In contrast, counterclockwise hysteresis dynamics are more common in agricultural watersheds, where time lags occur between the implementation of nutrient management practices and water‐quality improvements. Finally, we find higher tile‐drainage densities to be associated with more linear relationships between N inputs and riverine N. The empirical analysis in this study is bolstered by modeled simulations to reproduce and further explain drivers behind the hysteretic relationships commonly observed in the monitored watersheds. Plain Language Summary: For decades, efforts have been made to improve nutrient management, reduce riverine N loads, and improve water quality. While measurable improvements have been achieved in some watersheds, in others, elevated N loads have persisted. To better our understanding of the time‐varying relationships between anthropogenic N inputs to watersheds and riverine N export, we analyze long‐term monitoring data from more than 478 U.S. watersheds, together with watershed N input trajectories. Our analysis shows that in the 400 watersheds in which net N inputs have decreased or plateaued, 33% demonstrate lagged responses to these changes, and another 30% show no clear response. In contrast, approximately 24% of all watersheds exhibit accelerated improvements in water quality, with riverine N reductions actually outpacing reductions in N inputs. Bettering our understanding of the relationships between watershed N management and riverine N export across the U.S. allows us to identify water quality success stories and provides critical insight into effective management scenarios for impacted watersheds. Key Points: Relationships between watershed N inputs and riverine N export frequently change over time, with quantifiable hysteresis resultsAgricultural watersheds commonly exhibit lagged relationships between N inputs and riverine N export due to legacy N accumulation within the watershedMany urban watersheds in the northeastern U.S. are exhibiting accelerated improvements in water quality due to point‐source controls [ABSTRACT FROM AUTHOR]

Pulling the rabbit out of the hat: Unravelling hidden nitrogen legacies in catchment-scale water quality models Human activities have significantly perturbed the global cycle of nitrogen by excess inputs of reactive nitrogen (N) to the environment (Rockström et al., 2009). Both hydrological and biogeochemical processes can lead to substantial legacy effects that result in accumulation of N in the soil and subsurface, and time lags in the propagation of N input flux to N responses in water bodies (Ascott et al., 2021; Basu et al., 2022). However, as N fluxes from the soil pools propagate through the model compartments, we need to quantify and evaluate soil N legacy in water quality models to more accurately simulate N fluxes and concentrations in receiving water bodies. [Extracted from the article]

Improving nitrogen (N) status in European water bodies is a pressing issue. N levels depend not only on current but also past N inputs to the landscape, that have accumulated through time in legacy stores (e.g., soil, groundwater). Catchment‐scale N models, that are commonly used to investigate in‐stream N levels, rarely examine the magnitude and dynamics of legacy components. This study aims to gain a better understanding of the long‐term fate of the N inputs and its uncertainties, using a legacy‐driven N model (ELEMeNT) in Germany's largest national river basin (Weser; 38,450 km2) over the period 1960–2015. We estimate the nine model parameters based on a progressive constraining strategy, to assess the value of different observational data sets. We demonstrate that beyond in‐stream N loading, soil N content and in‐stream N concentration allow to reduce the equifinality in model parameterizations. We find that more than 50% of the N surplus denitrifies (1480–2210 kg ha−1) and the stream export amounts to around 18% (410–640 kg ha−1), leaving behind as much as around 230–780 kg ha−1 of N in the (soil) source zone and 10–105 kg ha−1 in the subsurface. A sensitivity analysis reveals the importance of different factors affecting the residual uncertainties in simulated N legacies, namely hydrologic travel time, denitrification rates, a coefficient characterizing the protection of organic N in source zone and N surplus input. Our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce the equifinality in water quality modeling. Plain Language Summary: Lowering nitrogen (N) amounts in European surface waters is a pressing issue. N levels largely result from fertilizer application in agricultural areas, and deposition of atmospheric N coming from fossil fuel combustion. These N inputs to the landscape can accumulate below the ground surface in so‐called legacy stores (including the soil and aquifer), from which they can be released progressively through time. Therefore, N levels depend not only on the recent N inputs, but also on their history. Our modeling study aims to improve our understanding of the long‐term fate of the N inputs and its uncertainties in Germany's largest national river basin (Weser) over the period 1960–2015. It suggests that more than 50% of the N inputs to land is lost to the atmosphere (denitrification, 1480–2210 kg ha−1) and the stream export amounts to around 18% (410–640 kg ha−1), leaving behind as much as around 16% (264–820 kg ha−1) in the landscape (legacy). However, the uncertainties in these estimates remain large, partly due to a lack of observational data on internal (legacy) components and uncertainties in N inputs. Overall, our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce them. Key Points: We use a parsimonious model to examine the long‐term (1960–2015) fate of nitrogen inputs to the landscape including the legacy buildupMore than 50% of the nitrogen surplus denitrifies and around 491 kg ha−1 accumulates in legacy stores in Germany's largest river basinHydrologic travel time and denitrification rates largely contribute to the residual uncertainty in the simulated nitrogen legacies [ABSTRACT FROM AUTHOR]

The presence of estrogens has been linked to adverse ecological effects in surface waters downstream of agricultural and domestic wastewater sources. While laboratory studies suggest that these estrogens should not persist because of fast degradation rates, elevated concentrations in surface waters impacted by agricultural activities are commonly observed. Using a combination of measured data and a stream‐hyporheic zone (HZ) model applied to a 100 km reach in a tile‐drained catchment, we show that the HZ can increase the persistence of estrogens. Field data reveal high concentrations of sorbed estrogens in sediments and elevated in‐stream concentrations during low‐flow summer months, suggesting that the HZ acts as a source of estrogens when transport into the streams is minimal. Model results provide further insight into the underlying mechanisms that enable sustained estrogen concentrations in streams, with the HZ acting as a source of dissolved estrogens for 95% of the year. We show that stream water interactions with the HZ may lead to overall suppression of degradation processes and an increase in the persistence of estrogens. Results suggest that when the model considered exchange in the HZ, approximately 28%–49% of estrogen mass remained in the stream ecosystem, while all estrogen mass was degraded in a 100‐km reach in the model without the HZ. The remaining mass increased with increasing estrogen sorption coefficient, and this would potentially increase the lag time for lowering estrogen concentrations in surface water bodies even when inputs have ceased. Our findings highlight the importance of including HZ dynamics in estrogen transport models. Plain Language Summary: Steroidal hormones are commonly found in manure and are frequently detected in agricultural streams. There is an increased interest in the fate of these hormones in the aquatic environment as prolonged exposure to these compounds at trace‐level concentrations can cause severe impacts in sensitive aquatic species, including fish. An outstanding question is why hormones are so common in streams when lab studies suggest that they should break down quickly, on the order of hours to days. Through field data analysis and model simulations, we show that the physical and chemical interactions within the streambed increase the persistence of hormones in the stream. Our model shows that the streambed is a storage or "sink" for hormones when stream water concentrations of hormones are high whereas under low stream water concentrations, the streambed behaves as a "source" by releasing the hormones back into the stream water. The streambed increases the amount of time that the hormones stay in the stream because light helps in hormone degradation, and this is reduced in the streambed. Our study highlights the need to consider this streambed interaction in models because ignoring this "source‐sink" behavior can lead to underestimations of where and for how long hormones remain in streams. Key Points: Hyporheic zone (HZ) acts as a persistent source of estrogens for 95% of the year and a sink only during high flow events (5% of year)Estrogen sorption in the HZ inhibits photodegradation, and thus increases its persistence in the stream ecosystemIncreasing estrogen sorption increases persistence and leads to higher lag times in water quality improvement after inputs have ceased [ABSTRACT FROM AUTHOR]

The Upper Mississippi River Basin is the largest source of reactive nitrogen (N) to the Gulf of Mexico. Concentration‐discharge (C‐Q) relationships offer a means to understand both the terrestrial sources that generate this reactive N and the in‐stream processes that transform it. Progress has been made on identifying land use controls on C‐Q dynamics. However, the impact of basin size and river network structure on C‐Q relationships is not well characterized. Here, we show, using high‐resolution nitrate concentration data, that tile drainage is a dominant control on C‐Q dynamics, with increasing drainage density contributing to more chemostatic C‐Q behavior. We further find that concentration variability increases, relative to discharge variability, with increasing basin size across six orders of magnitude, and this pattern is attributed to different spatial correlation structures for C and Q. Our results show how land use and river network structure jointly control riverine N export. Plain Language Summary: Nitrate is a major agricultural pollutant that can harm freshwater and marine ecosystems. Understanding the relationships between the concentration of nitrate in a river and the river's flow rate (discharge) can allow us to infer drivers of nitrate release from land into waterways and to better manage nutrient pollution. Here, we found that artificial (i.e. tile) drainage increases the stability of nitrate concentrations in the rivers of the Upper Mississippi basin across a wide range of flow rates. We also found that the variability of nitrate concentrations, relative to discharge, increased as rivers grew larger and had more tributaries contributing to flow. This shows that both on‐land and in‐river processes control the concentration‐discharge relationships of nitrate. Key Points: Nitrate concentrations in UMRB show a threshold response, chemodynamic at low flows but chemostatic at high flowsTile drainage increases the degree of nitrate chemostasis in the UMRBNitrate concentrations for rivers within Upper Mississippi River Basin (UMRB) are more chemodynamic with increasing basin size [ABSTRACT FROM AUTHOR]

As urban droughts make headlines across the globe, it is increasingly relevant to critically evaluate the long‐term sustainability of both water supply and demand in the world's cities. This is the case even in water‐rich regions, where upward swings in water demands during periods of hot, dry weather can aggravate already strained water supplies and increase cities' vulnerability to water shortage. Summer spikes in water demand have motivated several cities to impose permanent restrictions on outdoor water uses; however, little is yet known about their effectiveness. This paper examines daily water production data from 15 Canadian cities to (1) quantify how overall and seasonal demands are evolving over time across humid and semiarid settings and (2) determine whether permanent water use restrictions have been effective in curbing summer water demands both seasonally and during specific hot and dry periods. Results show that while per‐capita water demand is declining in all cities studied, the seasonal distribution of that demand has remained largely stable in all but a few cases. While average demands in the summer months remain largely unaffected by the imposition of permanent restrictions, cities that enforce stringent limits on outdoor water use have seen a reduction in the variability of daily demands and a decline in peak demands following their implementation. During short‐term periods of exceptionally hot and dry weather when vulnerability to water shortage is most acute, cities with strict restrictions also see smaller surges in demand than those with weaker or no restrictions in place. Key Points: Water production records from 15 Canadian cities show a decline in per‐capita demand, with rate of decline greater in semiarid cities with high seasonal variabilityPermanent water use restrictions have only minor impacts on mean or median summer day water demandsHowever, stringent restrictions are shown to reduce demand variability at the daily scale, reduce peaks, and suppress demand surges during heat events [ABSTRACT FROM AUTHOR]

Changes in seasonal nutrient dynamics are occurring across a range of climates and land use types. Although it is known that seasonal patterns in nutrient availability are key drivers of both stream metabolism and eutrophication, there has been little success in developing a comprehensive understanding of seasonal variations in nutrient export across watersheds or of the relationship between nutrient seasonality and watershed characteristics. In the present study, we have used concentration and discharge data from more than 200 stations across U.S. and Canadian watersheds to identify (1) archetypal seasonal concentration regimes for nitrate, soluble reactive phosphorus (SRP), and total phosphorus, and (2) dominant watershed controls on these regimes across a gradient of climate, land use, and topography. Our analysis shows that less impacted watersheds, with more forested and wetland area, most commonly exhibit concentration regimes that are in phase with discharge, with concentration lows occurring during summer low‐flow periods. Agricultural watersheds also commonly exhibit in‐phase behavior, though the seasonality is usually muted compared to that seen in less impacted areas. With increasing urban area, however, nutrient concentrations frequently become essentially aseasonal or even exhibit clearly out‐of‐phase behavior. In addition, our data indicate that seasonal SRP concentration patterns may be strongly influenced by proximal controls such as the presence of dams and reservoirs. In all, these results suggest that human activity is significantly altering nutrient concentration regimes, with large potential consequences for both in‐stream metabolism and eutrophication risk in downstream waterbodies. [ABSTRACT FROM AUTHOR]

Reported groundwater recovery in South India has been attributed to both increasing rainfall and political interventions. Findings of increasing groundwater levels, however, are at odds with reports of well failure and decreases in the land area irrigated from shallow wells. We argue that recently reported results are skewed by the problem of survivor bias, with dry or defunct wells being systematically excluded from trend analyses due to missing data. We hypothesize that these dry wells carry critical information about groundwater stress that is missed when data are filtered. Indeed, we find strong correlations between missing well data and metrics related to climate stress and groundwater development, indicative of a systemic bias. Using two alternative metrics, which take into account information from dry and defunct wells, our results demonstrate increasing groundwater stress in South India. Our refined approach for identifying groundwater depletion hot spots is critical for policy interventions and resource allocation. Plain Language Summary: Over the last century, groundwater has become an important source of freshwater to meet agricultural and drinking water needs. Increasing use of groundwater has contributed to depletion of groundwater reserves around the world, with India being at the forefront of this problem. Recent studies suggest that groundwater levels have been increasing in South India due to increasing rainfall and political interventions. This finding is at odds with local reports of groundwater stress, and increasing well failures. Our study explains this disagreement by showing that previous conclusions have been skewed by the problem of survivor bias, with wells with data gaps being routinely excluded from analysis of long‐term groundwater storage trends. We find that traditional groundwater trend assessment methods are not suitable for hard‐rock aquifer systems that characterize South India. Indeed, strong correlation exists between climate and groundwater stress and wells with missing data, indicative of a systemic bias. We develop metrics that use data from these wells, and show using these metrics increasing evidence of groundwater stress in South India over the last two decades (1996 to 2016). Our results provide insight into the management of groundwater depletion in India, while highlighting potential biases in groundwater sustainability assessments globally. Key Points: Reported recovery of groundwater levels in South India is at odds with increasing well failures and reports of groundwater stressApparent paradox is explained by survivor bias, where wells with missing data are routinely excluded from analysis of groundwater trendsLong‐term trend analysis is not appropriate for hard‐rock aquifer of South India; alternative metrics developed that highlight groundwater stress [ABSTRACT FROM AUTHOR]

Land use change and agricultural intensification have increased food production but at the cost of polluting surface and groundwater. Best management practices implemented to improve water quality have met with limited success. Such lack of success is increasingly attributed to legacy nutrient stores in the subsurface that may act as sources after reduction of external inputs. However, current water‐quality models lack a framework to capture these legacy effects. Here we have modified the SWAT (Soil Water Assessment Tool) model to capture the effects of nitrogen (N) legacies on water quality under multiple land‐management scenarios. Our new SWAT‐LAG model includes (1) a modified carbon‐nitrogen cycling module to capture the dynamics of soil N accumulation, and (2) a groundwater travel time distribution module to capture a range of subsurface travel times. Using a 502‐km2 Iowa watershed as a case study, we found that between 1950 and 2016, 25% of the total watershed N surplus (N Deposition + Fertilizer + Manure + N Fixation − Crop N uptake) had accumulated within the root zone, 14% had accumulated in groundwater, while 27% was lost as riverine output, and 34% was denitrified. In future scenarios, a 100% reduction in fertilizer application led to a 79% reduction in stream N load, but the SWAT‐LAG results suggest that it would take 84 years to achieve this reduction, in contrast to the 2 years predicted in the original SWAT model. The framework proposed here constitutes a first step toward modifying a widely used modeling approach to assess the effects of legacy N on the time required to achieve water‐quality goals. Plain Language Summary: For nearly a century, we have used nitrogen fertilizers to boost crop yields. However, the environmental effects of fertilizer use have been severe. Drinking water with high nitrate levels threatens human health, and high nitrogen loads in rivers lead to the creation of dead zones in coastal waters that make it impossible for fish or underwater plants to survive. Although we have tried for decades to reduce nitrogen levels in our waterways, the results have been disappointing. Scientists now believe that improvements may be slow to come because there are large amounts of nitrogen that have accumulated in soil and groundwater—legacy nitrogen—that continue to pollute our rivers even after farmers have reduced fertilizer use or improved management. However, policymakers still struggle to predict how long it will take to improve water quality. In our work, we have created a new model, Soil Water Assessment Tool‐LAG, that allows us to predict the time lags caused by legacy nitrogen. Using an agricultural watershed in Iowa as a case study, we show that it can take as long as 80 years to see the full effects of new management practices and that these time lags must be considered when setting policy goals. Key Points: A novel approach was developed to incorporate nitrate lag times in commonly used water‐quality model for watershed managementSWAT‐LAG model showed that lag times to achieve Nutrient Task Force's recommended 60% nitrate load reduction can vary from 6 to 80 yearsGreater implementation of new management practices lead to shorter lag times to achieving water‐quality goals [ABSTRACT FROM AUTHOR]

Hydrologic models partition flows into surface and subsurface pathways, but their calibration is typically conducted only against streamflow. Here we argue that unless model outcomes are constrained using flow pathway data, multiple partitioning schemes can lead to the same streamflow. This point becomes critical for biogeochemical modeling as individual flow paths may yield unique chemical signatures. We show how information on flow pathways can be used to constrain hydrologic flow partitioning and how improved partitioning can lead to better water quality predictions. As a case study, an agricultural basin in Ontario is used to demonstrate that using tile discharge data could increase the performance of both the hydrology and the nitrogen transport models. Watershed‐scale tile discharge was estimated based on sparse tile data collected at some tiles using a novel regression‐based approach. Through a series of calibration experiments, we show that utilizing tile flow signatures as calibration criteria improves model performance in the prediction of nitrate loads in both the calibration and validation periods. Predictability of nitrate loads is improved even with no tile flow data and by model calibration only against an approximate understanding of annual tile flow percent. However, despite high values of goodness‐of‐fit metrics in this case, temporal dynamics of predictions are inconsistent with reality. For instance, the model predicts significant tile discharge in summer with no tile flow occurrence in the field. Hence, the proposed tile flow upscaling approach and the partitioning‐constrained model calibration are vital steps toward improving the predictability of biogeochemical models in tiled landscapes. Key Points: Tile flow data were used to constrain flow partitioning in hydrologic modelsNovel methodology developed to upscale from single tile to watershed scaleConstraining tile flow resulted in better performance of the nitrogen model [ABSTRACT FROM AUTHOR]

Subsurface drainage systems are common in agricultural landscapes around the world, and yet there is insufficient understanding on how they modify the hydrologic flow regime, from the field to the watershed scale. Here, we study the effect of agricultural subsurface drainage (tiling) on the hydrologic response as a function of the watershed scale by using the field-scale model DRAINMOD in conjunction with a linearized routing equation for two watersheds in eastern Iowa. Note that we primarily used the stream network, dominant soil types, and climate forcings in these watersheds and focused on a synthetic analysis to uncover the effect of tiling, while keeping other factors constant. Tile drainage was observed to increase low flows, decrease intermediate flows, and have minimal effect on the largest floods. The reduction in peak flows was observed to be dependent on the event size, antecedent conditions, and spatial scale, such that the greatest flow reductions were apparent at the intermediate scale (100 to 1,000 km2), with lower reduction at the largest scale (>10,000 km2). The scale dependence can be attributed to the fact that peak flows at larger scales are typically not caused by a single rainfall event but by the accumulation of flows over a longer temporal window. We further demonstrate that peak flows can vary for a basin with the same percentage of tiling but a different spatial organization of the tiled hillslopes. We connect our results to the width function, a well-known geomorphological descriptor of river network topology, and demonstrate how tile placement in relation to the width function controls watershed response. Although we focus primarily on peak flows, our results indicate that the impact of tiling on the flow distribution is also scale dependent, and alterations to this distribution will, in turn, control sediment and nutrient transport in a basin. [ABSTRACT FROM AUTHOR]

Wetlands across the globe provide extensive ecosystem services. However, many wetlands -- especially those surrounded by uplands, often referred to as geographically isolated wetlands (GIWs) -- remain poorly protected. Protection and restoration of wetlands frequently requires information on their hydrologic connectivity to other surface waters, and their cumulative watershed- scale effects. The integration of measurements and models can supply this information. However, the types of measurements and models that should be integrated are dependent on management questions and information compatibility. We summarize the importance of GIWs in watersheds and discuss what wetland connectivity means in both science and management contexts. We then describe the latest tools available to quantify GIW connectivity and explore crucial next steps to enhancing and integrating such tools. These advancements will ensure that appropriate tools are used in GIW decision making and maintaining the important ecosystem services that these wetlands support. [ABSTRACT FROM AUTHOR]

Increased loading of nitrogen (N) and phosphorus (P) from agricultural and urban intensification has led to severe degradation of inland and coastal waters. Lakes, reservoirs, and wetlands (lentic systems) retain these nutrients, thus regulating their delivery to downstream waters. While the processes controlling N and P retention are relatively well-known, there is a lack of quantitative understanding of how these processes manifest across spatial scales. We synthesized data from 600 lentic systems around the world to gain insight into the relationship between hydrologic and biogeochemical controls on nutrient retention. Our results indicate that the first-order reaction rate constant, k [T−1], is inversely proportional to the hydraulic residence time, τ [T], across 6 orders of magnitude in residence time for total N, total P, nitrate, and phosphate. We hypothesized that the consistency of the relationship points to a strong hydrologic control on biogeochemical processing, and validated our hypothesis using a sediment-water model that links major nutrient removal processes with system size. Finally, the k-τ relationships were upscaled to the landscape scale using a wetland size-frequency distribution. Results suggest that small wetlands play a disproportionately large role in landscape-scale nutrient processing-50% of nitrogen removal occurs in wetlands smaller than 102.5 m2 in our example. Thus, given the same loss in wetland area, the nutrient retention potential lost is greater when smaller wetlands are preferentially lost from the landscape. Our study highlights the need for a stronger focus on small lentic systems as major nutrient sinks in the landscape. [ABSTRACT FROM AUTHOR]

More than 50% of global wetland area has been lost over the last 200 years, resulting in losses of habitat and species diversity as well as decreased hydrologic and biogeochemical functionality. Recognition of the magnitude of wetland loss as well as the wide variety of ecosystem services provided by wetlands has in recent decades led to an increased focus on wetland restoration. Restoration activities, however, often proceed in an ad hoc manner, with a focus on maximizing the total restored area rather than on other spatial attributes of the wetland network, which are less well understood. In this study, we have addressed the question of how human activities have altered the size distribution and spatial organization of wetlands over the Prairie Pothole Region of the Des Moines Lobe using highresolution LIDAR data. Our results show that as well as the generally accepted 90% loss of depressional wetland area, there has been a preferential loss of smaller wetlands, with a marked alteration of the historical power-law relationship observed between wetland size and frequency and a resulting homogenization of the wetland size distribution. In addition, our results show significant decreases in perimeter-to-area ratios, increased mean distances between wetlands, particularly between smaller wetlands, and a reduced likelihood that current wetlands will be located in upland areas. Such patterns of loss can lead to disproportionate losses of ecosystem services, as smaller wetlands with larger perimeter-to area ratios have been found to provide higher rates of biogeochemical processing and groundwater recharge, while increased mean distances between wetlands hinder species migration and thus negatively impact biodiversity. These results suggest the need to gear restoration efforts toward understanding and recreating the size distribution and spatial organization of historical wetlands, rather than focusing primarily on an increase in overall area. [ABSTRACT FROM AUTHOR]

Anthropogenic modifications to the landscape, with agricultural activities being a primary driver, have resulted in significant alterations to the hydrologic cycle. Artificial drainage, including surface and subsurface drainage (tile drains), is one of the most extensive manipulations in agricultural landscapes and thus is expected to provide a distinct signature of anthropogenic modification. This study adopts a data synthesis approach in an effort to characterize the signature of artificial subsurface drainage. Daily discharge data from 24 basins across the state of Iowa, which encapsulate a range of anthropogenic modifications, are assessed using a variety of flow metrics. Results indicate that the presence of artificial subsurface drainage leads to a homogenization of landscape hydrologic response. Non-tiled watersheds exhibit a decrease in the area-normalized peak discharge and an increase in the baseflow ratio (baseflow/streamflow) with increases in the spatial scale, while scale invariance is apparent in tiled basins. Within-basin variability in hydrograph recession coefficients also appears to decrease with increases in the proportion of the catchment that is artificially drained. Finally, the differences between tiled and non-tiled landscapes disappear at scales greater than approximately 2200 km2, indicating that this may be a threshold scale for studying the effects of tile drainage. This decrease in within-basin variability and the scale invariance of hydrologic metrics in artificially drained watersheds are attributed to the creation of a bypass flow hydrologic pathway that bypasses the complexity of the catchment travel paths. Spatial homogeneity in responses implies that it may be possible to develop more parsimonious hydrologic models for these regions. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Pollutant delivery through artificial subsurface drainage networks to streams is an important transport mechanism, yet the impact of drainage tiles on groundwater hydrology at the watershed scale has not been well documented. In this study, we developed a two-dimensional, steady-state groundwater flow model for a representative Iowa agricultural watershed to simulate the impact of tile drainage density and incision depth on groundwater travel times and proportion of baseflow contributed by tile drains. Varying tile drainage density from 0 to 0.0038 m−1, while maintaining a constant tile incision depth at 1.2 m, resulted in the mean groundwater travel time to decrease exponentially from 40 years to 19 years and increased the tile contribution to baseflow from 0% to an upper bound of 37%. In contrast, varying tile depths from 0.3 to 2.7 m, while maintaining a constant tile drainage density of 0.0038 m−1, caused mean travel times to decrease linearly from 22 to 18 years and increased the tile contribution to baseflow from 30% to 54% in a near-linear manner. The decrease in the mean travel time was attributed to decrease in the saturated thickness of the aquifer with increasing drainage density and incision depth. Study results indicate that tile drainage affects fundamental watershed characteristics and should be taken into consideration when evaluating water and nitrate export from agricultural regions. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We have used a dynamic hydrologie network model, coupled with a transient storage zone solute transport model, to simulate dissolved nutrient retention processes during transient flow events at the channel network scale. We explored several scenarios with a combination of rainfall variability, and biological and geomorphic characteristics of the catchment, to understand the dominant factors that control the transport of dissolved nutrients (e.g., nitrate) along channel networks. While much experimental work has focused on studying nutrient retention during base flow periods in headwater streams, our model-based theoretical analyses, for the given parameter combinations used, suggest that high-flow periods can contribute substantially to overall nutrient retention, and that bulk nutrient retention is greater in larger rivers compared to headwaters. The relative efficiencies of nutrient retention during high- and low-flow periods vary due to changes in the relative sizes of the main channel and transient storage zones, as well as due to differences in the relative strengths of the various nutrient retention mechanisms operating in both zones. Our results also indicate that nutrient retention efficiency at all spatial scales of observation has strong dependence on within-year variability of streamflow (e.g., frequency and duration of high and low flows), as well as on the relative magnitudes of the coefficients that govern biogeochemical uptake processes: the more variable the streamflow, the greater the export of nutrients. Despite limitations of the model parameterizations, our results suggest that increased attention must be paid to field observations of the interactions between process hydrology and nutrient transport and reaction processes at a range of scales to assist with extrapolation of understandings and estimates gained from site-specific studies to ungauged basins across gradients in climate, human impacts, and landscape characteristics. [ABSTRACT FROM AUTHOR]

This paper synthesizes a 3-year collaborative effort to characterize the biogeochemical and hydrological features of intensively managed agricultural catchments by combining data analysis, modeling, and preliminary hypothesis testing. The specific focus was on the Midwestern region of the United States. The results suggest that: (1) water management, specifically the homogenization of evapotranspiration losses driven by mono-cultural vegetation cover, and the homogenization of runoff generation driven by artificial drainage, has created engineered, predictable hydrologic systems; (2) nutrient and pesticide management, specifically their regular applications have created two kinds of biogeochemical export regimes: chemostatic (low variability in concentration as exhibited by nitrate) and episodic (high variability in concentration as exhibited by pesticides); (3) coupled mass-balance models for water and solutes reproduce these two regimes as a function of chemical rate constants. Phosphorus transport regimes were found to be episodic at smaller spatial scales, but chemostatic at larger scales. Chemostatic response dominates in transport-limited catchments that have internal sources of the solute to buffer the periodicity in episodic mputs, while episodic response dominates in source-limited catchments. The shift from episodic nitrate export in pristine catchnients to chemostatic regimes in managed watersheds was attributed to legacy stores of nitrogen (built from continued fertilizer applications) that buffer interannual variations in biogeochemical processing. Fast degradation kinetics of pesticides prevents the build-up of legacy sources, and leads to episodic export. Analytical expressions were derived for the probability density functions of solute delivery ratio as a function of the stochastics of rainfall-runoff events and biogeochemical controls. [ABSTRACT FROM AUTHOR]

The scale dependence of nutrient loads exported from a catchment is a function of complex interactions between hydrologic and biogeochemical processes that modulate the input signals from the hillslope by aggregation and attenuation in a converging river network. Observational data support an empirical inverse relation between the biogeochemical cycling rate constant for nitrate k (T-1) and the stream stage h (L), k = vf/h, with vf, the uptake velocity (LT-1), being constant in space under steady flow conditions. Here we offer a physical explanation for the persistence of this pattem across scales and then extend the analysis to spatiotemporal scaling of k under transient-flow conditions. Inverse k-h dependence arose as an emergent pattern by coupling the mechanistic Transient Storage Model with a network model. Analytical modeling mdicated that (1) nitrate processing efficiency increases with increasing variability in the discharge Q and (2) temporal averaging had no effect on the exponent a of the k-h relationship (k = vf/ha) in catchments with low Q variability, but strong dependence arose in catchments with high variability in Q. Network modeling in domains with low Q variability confirmed that the exponent a was independent of temporal averaging, but vf was a function of the averaging timescale. The probability distribution functions for k could be adequately predicted using analytical approaches. Understanding the k-h scaling relationships enables the direct estimation of the variability in nutrient losses due to in-stream reactions without requiring explicit information for spatially distributed network modeling. [ABSTRACT FROM AUTHOR]

Human activities exert global-scale impacts on our environment with significant implications for freshwater-driven services and hazards for humans and nature. Our approach to the science of hydrology needs to significantly change so that we can understand and predict these implications. Such an adjustment is a necessary prerequisite for the development of sustainable water resource management strategies and to achieve long-term water security for people and the environment. Hydrology requires a paradigm shift in which predictions of system behavior that are beyond the range of previously observed variability or that result from significant alterations of physical (structural) system characteristics become the new norm. To achieve this shift, hydrologists must become both synthesists, observing and analyzing the system as a holistic entity, and analysts, understanding the functioning of individual system components, while operating firmly within a well-designed hypothesis testing framework. Cross-disciplinary integration must become a primary characteristic of hydrologic research, catalyzing new research and nurturing new educational models. The test of our quantitative understanding across atmosphere, hydrosphere, lithosphere, biosphere, and anthroposphere will necessarily lie in new approaches to benchmark our ability to predict the regional hydrologic and connected implications of environmental change. To address these challenges and to serve as a catalyst to bring about the necessary changes to hydrologic science, we call for a long-term initiative to address the regional implications of environmental change. [ABSTRACT FROM AUTHOR]

The central premise of this paper is that extensive modifications of land use and hydrology, coupled with intensive management of watersheds in the Midwestern United States over the past century, have increased the predictability of hydrologic responses, allowing for the use of simpler, minimum-calibration models. In these engineered watersheds, extensive tile-and-ditch networks have increased the effective drainage density and have created bypass flow hydrologic systems that generate 'flashy' and 'predictable' hydrographs. We propose a simple, threshold-based model, the Threshold-Exceedance-Lagrangian Model (TELM), for predicting event hydrographs. TELM was evaluated by comparing predicted hydrographs with those measured over a 4 year period at the outlet of a mesoscale watershed (Cedar Creek, ∼700 km2) in northeastern Indiana. Application of the Soil-Land Inference Model (SoLIM) indicated that, despite structural heterogeneities (e.g., spatial variability in soil taxonomic mapping units), about 80% of the area of the watershed could be assigned a single value of available soil water storage, which was the primary soil parameter that defined hydrograph response. Hydrograph recession curves for multiple events were described well using an exponential function, with the mean arrival time ( t r) estimated on the basis of the contributing drainage area ( A) and the mean occurrence time ( t h) of the event hyetograph. Also, functional responses (event hydrographs) at the subwatershed scale could be grouped into just two categories on the basis of only spatial variability in rainfall patterns. TELM, with no parameter calibration, matched the observed hydrographs as well as the widely used SWAT model predictions with calibration. Advantages and limitations of the proposed modeling approach were identified, and needed improvements were discussed. [ABSTRACT FROM AUTHOR]

Simulations of nonpartitioning and partitioning tracer tests were used to parameterize the equilibrium stream tube model (ESM) that predicts the dissolution dynamics of dense nonaqueous phase liquids (DNAPLs) as a function of the Lagrangian properties of DNAPL source zones. Lagrangian, or stream-tube-based, approaches characterize source zones with as few as two trajectory-integrated parameters, in contrast to the potentially thousands of parameters required to describe the point-by-point variability in permeability and DNAPL in traditional Eulerian modeling approaches. The spill and subsequent dissolution of DNAPLs were simulated in two-dimensional domains having different hydrologic characteristics (variance of the log conductivity field = 0.2, 1, and 3) using the multiphase flow and transport simulator UTCHEM. Nonpartitioning and partitioning tracers were used to characterize the Lagrangian properties (travel time and trajectory-integrated DNAPL content statistics) of DNAPL source zones, which were in turn shown to be sufficient for accurate prediction of source dissolution behavior using the ESM throughout the relatively broad range of hydraulic conductivity variances tested here. The results were found to be relatively insensitive to travel time variability, suggesting that dissolution could be accurately predicted even if the travel time variance was only coarsely estimated. Estimation of the ESM parameters was also demonstrated using an approximate technique based on Eulerian data in the absence of tracer data; however, determining the minimum amount of such data required remains for future work. Finally, the stream tube model was shown to be a more unique predictor of dissolution behavior than approaches based on the ganglia-to-pool model for source zone characterization. [ABSTRACT FROM AUTHOR]