Water Balance Research Articles

Anthropogenic Aerosol Dominates the Decadal Change in Evapotranspiration over Southeastern China in the Past Four Decades

Evapotranspiration (ET) is vital for global water balance, energy cycle, and biological processes, representing a key component of Earth systems interactions. However, how human activities affect regional ET is still unknown. This study identified a decadal decrease in ET before 2000, followed by an increase over southeastern China in observations. Simulations from the coupled model intercomparison project phase 6 (CMIP6) models well reproduced the observed decadal ET change, with a lag of 10 years, which may be due to the spatial and temporal simplification of aerosol forcing data in CMIP6. Attribution analysis reveals that the change in anthropogenic aerosol emissions was the primary driver of the ET change, while the contribution of greenhouse gas was negligible. The Penman–Monteith framework identified that the net surface radiation contributed 77% of the ET trend change in the anthropogenic aerosol-only experiment. The increase and reduction in anthropogenic aerosol emissions reduce and increase the shortwave radiation reaching the Earth’s surface, respectively, resulting in the different trends of energy sources for ET. Our findings underscore the critical role of aerosols in shaping surface energy balance and influencing regional hydrological cycles.

Beyond SGLT2: proximal tubule transporters as potential drug targets for chronic kidney disease.

The proximal tubule is responsible for reabsorbing about 60% of filtered solutes and water and is critical for the secretion of metabolic waste products, drugs and toxins. A large number of highly specialized ion channels and transport proteins belonging to the SLC and ABC transporter families are involved. Their activity is directly or indirectly linked to ATP consumption and requires large quantities of energy and oxygen supply. Moreover, the activity of these transporters is often coupled to the movement of Na+ ions thus influencing also salt and water balance, as well as transport and regulatory processes in downstream segments. Because of their relevance for systemic ion balance, for renal metabolism or for affecting regulatory processes, proximal tubule transporters are attractive targets for existing drug and for novel strategies to reduce kidney disease progression or to alleviate the consequences of decreased kidney function. In this review, the relevance of some major proximal tubule transport systems as drug targets in individuals with chronic kidney disease (CKD) is discussed. Inhibitors of the sodium-glucose cotransporter 2, SGLT2, are now part of standard therapy in patients with CKD and/or heart failure. Also, indirect inhibition of Na+/H+-exchangers by carbonic anhydrase inhibitors and uricosuric drugs have been used for decades. Inhibition of phosphate and amino acid transporters have recently been proposed as novel principles to remove excess phosphate or to protect the proximal tubule metabolically, respectively. In addition, organic cation and anion transporters involved in drug and toxin excretion may serve as targets of new drugs. The advantages and challenges associated with (novel) drugs targeting proximal tubule transport are discussed.

Modeling Lake Titicaca's water balance: the dominant roles of precipitation and evaporation

Abstract. In the face of climate change and increasing anthropogenic pressures, a reliable water balance is crucial for understanding the drivers of water level fluctuations in large lakes. However, in poorly gauged hydrosystems such as Lake Titicaca, most components of the water balance are not measured directly. Previous estimates for this lake have relied on scaling factors to close the water balance, which introduces additional uncertainty. This study presents an integrated modeling framework based on conceptual models to quantify natural hydrological processes and net irrigation consumption. It was implemented in the Water Evaluation and Planning System (WEAP) platform at a daily time step for the period 1982–2016, considering the following terms of the water balance: upstream inflows, direct precipitation and evaporation over the lake, and downstream outflows. To estimate upstream inflows, we evaluated the impact of snow and ice processes and net irrigation withdrawals on predicted streamflow and lake water levels. We also evaluated the role of heat storage change in evaporation from the lake. The results showed that the proposed modeling framework makes it possible to simulate lake water levels ranging from 3808 to 3812 m a.s.l. with good accuracy (RMSE = 0.32 m d−1) over a wide range of long-term hydroclimatic conditions. The estimated water balance of Lake Titicaca shows that upstream inflows account for 56 % (958 mm yr−1) and direct precipitation over the lake for 44 % (744 mm yr−1) of the total inflows, while 93 % (1616 mm yr−1) of the total outflows are due to evaporation and the remaining 7 % (121 mm yr−1) to downstream outflows. The water balance closure has an error of −15 mm yr−1 without applying scaling factors. Snow and ice processes, together with net irrigation withdrawals, had a minimal impact on variations in the lake water level. Thus, Lake Titicaca is primarily driven by variations in precipitation and high evaporation rates. These results will be useful for supporting decision-making in water resource management. We demonstrate that a simple representation of hydrological processes and irrigation enables accurate simulation of water levels. The proposed modeling framework could be replicated in other poorly gauged large lakes because it is relatively easy to implement, requires few data, and is computationally inexpensive.

Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study

Abstract. Modern hydrology is embracing a data-intensive new era, with information from diverse sources currently providing support for hydrological inferences at broader scales. This results in a plethora of data-reliability-related challenges that remain unsolved. The water budget non-closure is a widely reported phenomenon in hydrological and atmospheric systems. Many existing methods aim to enforce water budget closure constraints through data fusion and bias correction approaches, often neglecting the physical interconnections between water budget components. To solve this problem, this study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed the PHPM-MDCF. The concept of decomposing the total water budget residuals into inconsistency and omission residuals is embedded in this framework to account for different residual sources. We examined the efficiency of the PHPM-MDCF and the distribution of residuals across 475 contiguous United States (CONUS) basins selected by hydrological simulation reliability. The results indicate that the inconsistency residuals dominate the total water budget residuals, exhibiting highly consistent spatiotemporal patterns. This portion of residuals can be significantly reduced through PHPM-MDCF correction and achieved satisfactory efficiency. The total water budget residuals decreased by 49 %, on average, across all basins, with reductions exceeding 80 % in certain basins. The credibility of the correction framework was further verified through noise experiments and comparisons with existing methods. In the end, we explored the potential factors influencing the distribution of residuals and found notable scale effects, along with the key role of hydro-meteorological conditions. This emphasizes the importance of carefully evaluating the water balance assumption when employing multisource datasets for hydrological inference in small and humid basins.

Shorter growing seasons may moderate climate change effects on crop water demands

Abstract Rising evaporative demand (ETo) with a warming climate contributes to diminished water availability in water-stressed agricultural regions globally. While increased ETo typically necessitates increased irrigation, we explore how crop phenological response can moderate this challenge. Focusing on five key agricultural crops in California’s San Joaquin Valley, we employ coupled water balance and phenology models to project crop water demands as a function of increased ETo and changing phenology. All crops exhibited accelerated growth from a shortened growing season with warming. The shortened crop maturation period partially to fully offset increased crop water demands due to rising ETo, with the largest phenological influence for annual crops such as tomato and corn. By contrast, models that do not account for phenological changes showed increased irrigation demands of approximately 3.5-4.5% per °C of global warming primarily due to increased ETo. Integration with dynamic phenological models for the five key crops across the extent of agricultural land in the San Joaquin Valley showed a 1.6% decrease in irrigation needs under a 2°C warming scenario. While phenological change alongside plant physiological responses to increased atmospheric CO2 may help buffer the impact of climate change on crop irrigation demand, decreased crop yields with a shorter growing season and continued reliance of groundwater reserves for agricultural water use and reduced spring snowpack will threaten coupled agricultural and water security in the region.

Optimizing industrial flow measurements in mineral processing: Utilizing radiotracers for enhanced data reliability within Mining 4.0.

As the mining sector undergoes rapid transformation, Industry 4.0 principles — such as data digitalization, process automation, and Big Data Analytics — are crucial for developing intelligent mineral processing plants. These principles advance processes towards an interconnected sequence of steps, each relying on high-quality data. Within this framework, low-uncertainty flowmeter data is vital for accurate metallurgical mass balance determination, efficient process control, and the correct application of advanced analytical tools. However, harsh mining conditions can cause significant deviations in flowmeter readings, necessitating robust data validation methods. This paper introduces the novel application of the radiotracer methodology, which provides certified uncertainties around 1%, to optimize flowmeter data accuracy and align with Mining 4.0 requirements. Three industrial validation examples are presented: Flow meter adjustment in leaching processes, evaluating a NaHS loop piping circuit in a molybdenum flotation plant and validating flow meters to assess the hydraulic behavior of recirculation pumping stations for water balance quantification. On-site validations at the leaching plant revealed that only 36% of the measurements were within the acceptable 5% error margin. Flow assurance was confirmed in the NaHS loop piping circuit as radiotracer velocity data showed no blockages. Deviations in the recirculation pumping stations, ranging from 6.91% to 22.55%, highlighted the need for flowmeter adjustments. These findings underscore the value of radiotracers as a validation method. This paper also provides insights for water and environmental impact assessment, metallurgical mass balance calculations, and process optimization, emphasizing the need to integrate radiotracer methodology within the Mining 4.0 framework.

Predicted distribution of curl-leaf mountain mahogany (Cercocarpus ledifolius) in the Bighorn Canyon National Recreation Area.

Distributions of plants are expected to change in response to climate change, but the relative probability of that change is often unknown. Curl-leaf mountain mahogany (Cercocarpus ledifolius), an important browse species used by ungulates as forage and cover across the western US, is thought to be moderately to highly vulnerable to climate change this century, and a reduction in curl-leaf mountain mahogany occurrence may negatively impact ungulates reliant upon it. A combination of probability density estimation and vector analysis was used to predict curl-leaf mountain mahogany distribution across the species range relative to climate space and how that relationship would affect curl-leaf mountain mahogany at a local scale. Locally, we used the curl-leaf mountain mahogany population at the Bighorn Canyon National Recreation Area (BICA) in Montana and Wyoming for comparison. We modeled the probability of curl-leaf mountain mahogany occurrence across its distribution using water balance data to spatially and temporally assess the vulnerability of a population at a local scale. Modeled probabilities of occurrence and vector analysis indicated the species to remain in some areas within BICA but will be vulnerable in others given the predicted changes in temperature and precipitation in BICA if historical trajectories continue. This information allows managers to direct limited resources to other management actions by using the best available science to inform decisions. Other curl-leaf mountain mahogany populations currently inhabiting wetter, drier sites may follow a similar trajectory as the effects of climate change manifest. The approach used serves as a model to assess the predicted trend for species-specific plant communities of concern that may be adversely affected by climate change.

Leaf Spectroscopy Reveals Drought Response Variation in Fagus sylvatica Saplings From Across the Species' Range

AbstractThe common European beech (Fagus sylvatica), sensitive to prolonged drought, is expected to shift its distribution with climate change. To persist in novel environments, young trees rely on the capacity to express diverse response phenotypes. Several methods exist to study drought effects on trees and their diverse adaptive mechanisms, but these are usually destructive and challenging for the large sample numbers needed to investigate biological variation. We conducted a common garden experiment outdoors, but under controlled watering conditions, with 180 potted 2‐year‐old saplings from 16 beech provenances across the species' range, representing three distinct genetic clusters. Drought stress was simulated by interrupting irrigation and stomatal conductance and soil moisture were used to assess drought severity. We measured leaf reflectance of visible to short‐wave infrared electromagnetic radiation to determine drought‐induced changes in biochemical and structural traits derived from spectral indices and a model of leaf optical properties. We quantified changes in pigmentation, water balance, nitrogen, lignin, epicuticular wax, and leaf mass per area in drought‐treated saplings, revealing differences in likely adaptive responses to drought. F. sylvatica saplings from the Iberian Peninsula showed signatures of greater drought resistance, that is, the least drought‐induced change in spectrally derived traits related to leaf pigments and leaf water content. We demonstrate that high‐resolution leaf spectroscopy is an effective and non‐destructive tool to assess individual drought responses that can characterize functional intraspecific variation among young beech trees. Next, this approach should be scaled up to canopy‐level or airborne spectroscopy to support drought response assessments of forests.

New insights into uranium stress responses of Arabidopsis roots through membrane- and cell wall-associated proteome analysis.

Uranium (U) is a non-essential and toxic metal for plants. In Arabidopsis thaliana plants challenged with uranyl nitrate, we showed that U was mostly (64-71% of the total) associated with the root insoluble fraction containing membrane and cell wall proteins. Therefore, to uncover new molecular mechanisms related to U stress, we used label-free quantitative proteomics to analyze the responses of the root membrane- and cell wall-enriched proteome. Of the 2,802 proteins identified, 458 showed differential accumulation (≥1.5-fold change) in response to U. Biological processes affected by U include response to stress, amino acid metabolism, and previously unexplored functions associated with membranes and the cell wall. Indeed, our analysis supports a dynamic and complex reorganization of the cell wall under U stress, including lignin and suberin synthesis, pectin modification, polysaccharide hydrolysis, and Casparian strips formation. Also, the abundance of proteins involved in vesicular trafficking and water flux was significantly altered by U stress. Measurements of root hydraulic conductivity and leaf transpiration indicated that U significantly decreased the plant's water flux. This disruption in water balance is likely due to a decrease in PIP aquaporin levels, which may serve as a protective mechanism to reduce U toxicity. Finally, the abundance of transporters and metal-binding proteins was altered, suggesting that they may be involved in regulating the fate and toxicity of U in Arabidopsis. Overall, this study highlights how U stress impacts the insoluble root proteome, shedding light on the mechanisms used by plants to mitigate U toxicity.

Balanced water and heat energy recycling by full evaporation of wastewater (FEW) in dry biorefining processes of lignocellulose biomass.

Lignocellulosic biorefinery technology requires minimum energy consumption and wastewater generation to overcome challenges in industrial applications. This study established a rigorous model and a comprehensive physical property database of dry biorefining process on Aspen Plus platform for production including L-lactic acid, citric acid, sodium sugar acids, amino acid, and ethanol based on the experimental data. Full evaporation of wastewater (FEW) approach was proposed to completely replaced the external steam supply, and significantly reduced the freshwater input by 67% ∼ 85% and wastewater generation by 64% ∼ 89%, depending on the specific products. The carbon-neutral heat energy from lignin residue combustion generates an extra heat output of 1.098∼4.772 GJ per ton of dry wheat straw (DW) after all the heat energy needs of the biorefinery process and FEW treatments are satisfied, equivalent to a reduction of 0.219∼0.952kg CO2 eq/kg DM emission. This study provided a self-consistent solution for water and energy balance in biorefinery processes.

Chain entanglement and free-volume effects in branched poly(arylene piperidinium) anion-exchange membranes: random-branched versus end-branched

Poly(arylene piperidinium) (PAP) anion-exchange membranes (AEMs) are attractive platform materials currently used for anion-exchange membrane fuel cells (AEMFCs) and chain branching modifications on PAP polymer structures have recently drawn much attention for effectively regulating the membrane properties. To better understand the influence and interplay of the polymer chain entanglement and free volume effect from various branched architectures, herein, lightly end-branched EB-PTP/TPB AEMs, using poly(p-terphenyl dimethylpiperidinium) (PTP) as the polymer backbone and bulky rigid 1,3,5-triphenylbenzene (TPB) as the branching agent, are designed and compared to previously reported random-branched RB-PTP/TPB and linear-chain PTP membranes. Intrinsic viscosity, bulk density and positron annihilation lifetime spectroscopy suggest a lesser extent of chain entanglement, but more evident free-volume elements for end-branched EB-PTP/TPB, particularly for higher branched EB-PTP/TPB-1% containing 1 mol% of TPB branching agent, compared with the random-branched RB-PTP/TPB that exhibits a more predominant chain entanglement effect. EB-PTP/TPB AEMs with increased free volume exhibit faster water sorption kinetics and slightly higher ion conductivity, but the concurrent high water sorption levels are disadvantageous to high-temperature ion transport, alkaline stability and water balance management. Even so, EB-PTP/TPB AEMs still show sufficient mechanical robustness, restricted swelling and higher alkaline stability than linear-chain PTP membranes, aided by the considerable extent of chain entanglement. This work reveals branched architecture–AEM property relationships and provides valuable insights towards branched architecture design.

Water balance analysis of hydrological processes in cyclic irrigation: A case study of the Imbanuma irrigation area in Chiba, Japan

Water balance analysis of hydrological processes in cyclic irrigation: A case study of the Imbanuma irrigation area in Chiba, Japan

Changes and drivers of long-term land evapotranspiration in the Yangtze River Basin: A water balance perspective

Changes and drivers of long-term land evapotranspiration in the Yangtze River Basin: A water balance perspective

Influences of rainfall characteristics on water saving and stormwater control performances of rainwater harvesting systems.

Rainwater harvesting systems (RHS) are extensively executed to manage stormwater control and water shortage issues in cities. However, the influences of rainfall characteristics on the performances of RHS are still not deeply explored. In this research, a methodology framework is developed to explore the influences of rainfall characteristics on stormwater control and water saving performances of RHS, by using daily precipitation data during 1968-2017at 30 stations across the Beijing region as a testbed. The proposed methodology framework applies a water balance model, which requires daily rainfall and water demands, catchment area, tank size, runoff losses and first flush as input data, to assess water saving efficiency (WSE), reliability (R), and stormwater capture efficiency (SCE) of RHS, and a clustering approach to determine if same rainfall patterns produce similar/equivalent outputs of RHS. Rainfall characteristics are quantified using 10 rainfall indices, and their influences on the performances of RHS are investigated. Results demonstrate that WSE, R, and SCE of RHS emerge less scattered when clustering becomes more accurate. Equivalent outputs of RHS for combined water demand can be obtained by dividing 30 stations into eight clusters. Furthermore, 6 rainfall indices (mean annual rainfall, standard precipitation index, rainfall concentration degree, ratio of dry and rainy days, consecutive number of dry days per year, average duration of dry days) are found significantly influencing the stormwater control and water saving performances of RHS. Therefore, they are recommended to be carefully considered to quantify rainfall characteristics and support the performance evaluation and design of RHS.

Hydrological performance of bioretention in field experiments and models: A review from the perspective of design characteristics and local contexts.

Bioretention is a widely used countermeasure to address stormwater runoff issues and restore the urban water balance. This review investigated the variety of designs and local contexts covered by earlier studies, as well as the means for assessing the hydrological performance of a bioretention system. It built on the analysis of 75 documents to discuss the adequacy of experimental setups or models for the evaluation of different performance indicators, and to summarise current knowledge regarding the impact of local context or design parameters on the hydrologic functioning of bioretention systems. The current literature was found to only partially cover the potential variety of local contexts or bioretention designs, and to sometimes omit critical information. Studies were for instance concentrated in regions with low seasonal rainfall variability for which limits the potential for investigating drought resilience issues and more generally restricts the applicability of their findings to other climate conditions. Regarding bioretention design, the use of environmental-friendly materials (renewable and local materials) as alternatives to traditional materials (sand, gravel, geotextile), as well as simpler designs with limited inputs of external materials (e.g. limited use of concrete or polymeric materials), remains largely overlooked. Besides, the over representation of lined system in current studies leads to a lack of understanding of the interactions between bioretention and the surrounding soil, despite evidence of their potential impact on the overall performance of bioretention in the case of unlined systems. In the reviewed studies, certain limitations of the most commonly used monitoring and modelling methods were identified. Event-based and short-term approaches made up a large proportion of the modelling and monitoring methods, but they lead to inaccuracies in annual and long-term performance. 1D models gained popularity due to their ease of use, but the simplification of configuration and hydrological processes and thus their influence on performance was rarely discussed.

An objective methodology for waterlogging risk assessment based on the entropy weighting method and machine learning

Waterlogging disasters are one of the most severe and widespread agricultural meteorological disasters. They affect about 15% of land surface globally, causing a significant reduction in crop growth and yields. This paper presents an objective methodology for assessing waterlogging risk, primarily in non-urban, predominantly agricultural areas. The waterlogging risk was assessed by evaluating vulnerability and hazard based on key environmental, anthropogenic, and climatic factors. The weights of factors affecting the waterlogging vulnerability were determined using the entropy weight method (EWM), assuring the objectivity of the overall evaluation results. The obtained waterlogging risk map was validated by comparing it with observed and detected waterlogged sites using Sentinel-2 imagery and Random Forest classification. The key novelties of this study are the use of the entropy weight method to objectively determine the relative importance of factors influencing waterlogging vulnerability, and a two-step validation process which includes field-based comparison and remote sensing validation. The presented methodology was demonstrated in the Vojvodina region, Serbia. The following waterlogging vulnerability factors were used: soil properties, geomorphology, surface depressions, average phreatic water table depth, and land cover. The EWM shows that surface depressions and soil properties have the most significant influence on waterlogging vulnerability. The highest waterlogging hazard classes occur in about 31% of the analyzed territory. The waterlogging hazard was estimated based on water balance for the non-vegetation season and maximum daily precipitation in spring, both modeled using the Generalize Extreme Value distribution function. The highest waterlogging hazard classes occur in about 31% of the analyzed territory. The final risk map shows that the high waterlogging risk occurs in about 11% of the territory. Those are mainly areas in the central, eastern, and southeastern parts of the Vojvodina region, usually along the main watercourses. High agreement between the detected waterlogged areas and the produced waterlogging risk map was achieved, validating the proposed methodology. The presented waterlogging risk assessment methodology is valuable for planning and policy-making for various water management and environmental activities. Although it is demonstrated in Vojvodina, by selecting the appropriate factors of vulnerability and hazard, it can be applied to any other region.

Role of syringic acid in enhancing growth, photosynthesis, and antioxidant defense in lettuce exposed to arsenic stress.

Heavy metal pollution, especially arsenic toxicity, significantly impairs plant growth and development. Phenolic acids, known for their antioxidant properties and involvement in stress signaling, are gaining increased attention as plant secondary metabolites with the potential to enhance plant resistance to these stressors. This study aimed to investigate the effects of different concentrations of syringic acid (SA1, 10 μM; SA2, 250 μM; SA3, 500 μM) on growth, photosynthetic parameters, and antioxidant activity in lettuce seedlings subjected to arsenic stress (As, 100 μM). Arsenic stress reduced growth by 56.7%, water content by 7.39%, and osmotic potential by 26.2% in lettuce leaves compared to control. Conversely, SA1 and SA2 treatments mitigated the adverse effects of arsenic on growth and preserved the water balance in plants. However, the SA3 treatment led to a decrease in growth by 18.9% and 39.5% in the SA3 and As+SA3 groups, respectively, indicating that high-dose SA treatment adversely affected lettuce leaves under both control and stress conditions. Exogenous SA1 treatment significantly improved photosynthesis, whereas SA2 provided milder benefits and SA3 did not reduce the adverse effects of arsenic exposure. Arsenic stress increased H2O2 content by 47.3% and lipid peroxidation by 33.4% in lettuce seedlings. SA1 treatment effectively reduced oxidative stress by enhancing the activities of key antioxidant enzymes, such as superoxide dismutase (SOD) and peroxidase (POX). Moreover, SA1 was successful in maintaining the glutathione (GSH) pool, whereas SA2 primarily promoted ascorbate (AsA) regeneration. In conclusion, 10 μM of syringic acid (SA1) was identified as the optimal dose for reducing arsenic stress in lettuce by enhancing antioxidant activity and supporting growth. Overall, the findings underscore the potential of SA1 treatment in enhancing the resilience of lettuce to heavy metal toxicity.

Enhanced Cd Tolerance in Bamboo: Synergistic Effects of Nano-Hydroxyapatite and Fe3O4 Nanoparticles on Reactive Oxygen Species Scavenging, Cd Detoxification, and Water Balance

Enhanced Cd Tolerance in Bamboo: Synergistic Effects of Nano-Hydroxyapatite and Fe3O4 Nanoparticles on Reactive Oxygen Species Scavenging, Cd Detoxification, and Water Balance

The Integrative Physiology of Hormone Signaling: Insights from Insect models.

Hormones orchestrate virtually all physiological processes in animals, and enable them to adjust internal responses to meet diverse physiological demands. Studies in both vertebrates and insects have uncovered many novel hormones and dissected the physiological mechanisms they regulate, demonstrating a remarkable conservation in endocrine signaling across the tree of life. In this review, we focus on recent advances in insect research, which have provided a more integrative view of the conserved interorgan communication networks that control physiology These new insights have been driven by experimental advantages inherent to insects, which over the past decades have aligned with new technologies and sophisticated genetic tools, to transform insect genetic models into a powerful testbed for posing new questions and exploring longstanding issues in endocrine research. Here, we illustrate how insect studies have addressed classic questions in three main areas-hormonal control of growth and development, neuroendocrine regulation of ion and water balance, and hormonal regulation of behavior and metabolism- and how these discoveries have illuminated our fundamental understanding of endocrine signaling in animals. The application of integrative physiology in insect systems to questions in endocrinology and physiology is expanding, and is poised to be a crucible of discovery, revealing fundamental mechanisms of hormonal regulation that underlie animal adaptations to their environments.

Evaluating best management practices for nutrient load reductions in tile-drained watersheds of the Laurentian Great Lakes Basin: A literature review.

Tile drainage systems are extensively implemented across the Laurentian Great Lakes Basin (GLB) to enhance agricultural productivity on poorly drained soils. However, these systems substantially contribute to excess nutrient runoff, particularly phosphorus (P) and nitrogen (N), exacerbating eutrophication and harmful algal blooms in the Great Lakes. This literature review synthesized current knowledge on nutrient loadings from tile-drained agricultural watersheds and evaluated the effectiveness of various agricultural best management practices (BMPs) in mitigating nutrient losses in the GLB. Through a meta-synthesis of field and watershed scale monitoring and modeling studies and statistical analysis using Box-Whisker plots and Monte Carlo simulations, we assessed the nutrient reduction potential of representative BMPs, including cover cropping, nutrient management, controlled drainage, and constructed wetlands in tile-drained landscapes. Findings indicated that individual BMPs substantially reduced nutrient loadings, but the effectiveness of these BMPs depended on site-specific factors, including climate conditions, soil type, and drainage system design. Integrated approaches at field, edge-of-field, and watershed scales with a combination of multiple BMPs enhanced nutrient reduction benefits, aligning with regional water quality targets. The review also highlighted the challenges of climate change that may undermine BMP performance by altering precipitation patterns and increasing extreme weather events. To address these complexities, we proposed a framework for developing adaptive BMP scenarios tailored to specific watershed conditions, emphasizing the need for long-term monitoring and hydrologic model enhancements. This framework was designed to help policymakers, stakeholders, and farmers protect water quality and balance agricultural productivity in the GLB and similar agricultural regions globally.