100 citations as recorded by crossref.

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24. Ecohydrologic structure and function of stream networks with earthen upstream and concrete‐lined downstream P. Gomes & O. Wai https://doi.org/10.1002/eco.2088
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35. Water quality change of rivers during rainy events in a watershed with different land uses in Southern Brazil R. Girardi et al. https://doi.org/10.1590/2318-0331.011615179
36. An improved method for interpretation of riverine concentration‐discharge relationships indicates long‐term shifts in reservoir sediment trapping Q. Zhang et al. https://doi.org/10.1002/2016GL069945
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39. Identifying seasonal patterns of phosphorus storm dynamics with dynamic time warping R. Dupas et al. https://doi.org/10.1002/2015WR017338
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41. Event-scale hysteresis metrics to reveal processes and mechanisms controlling constituent export from watersheds: A review✰ W. Liu et al. https://doi.org/10.1016/j.watres.2021.117254
42. Synthesis of nutrient and sediment export patterns in the Chesapeake Bay watershed: Complex and non-stationary concentration-discharge relationships Q. Zhang https://doi.org/10.1016/j.scitotenv.2017.09.221
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44. Temporal hydrochemical dynamics of the River Wensum, UK: Observations from long-term high-resolution monitoring (2011–2018) R. Cooper et al. https://doi.org/10.1016/j.scitotenv.2020.138253
45. Using hysteresis analysis of high-resolution water quality monitoring data, including uncertainty, to infer controls on nutrient and sediment transfer in catchments C. Lloyd et al. https://doi.org/10.1016/j.scitotenv.2015.11.028
46. Evaluation of sampling frequency impact on the accuracy of water quality status as determined considering different water quality monitoring objectives C. Torres et al. https://doi.org/10.1007/s10661-022-10169-7
47. Spatio-temporal analysis of phosphorus concentrations in a North-Eastern German lowland watershed S. Koch et al. https://doi.org/10.1016/j.ejrh.2018.02.001
48. Assessing the potential impacts of a revised set of on-farm nutrient and sediment ‘basic’ control measures for reducing agricultural diffuse pollution across England A. Collins et al. https://doi.org/10.1016/j.scitotenv.2017.10.078
49. High-frequency monitoring reveals seasonal and event-scale water quality variation in a temporally frozen river M. Kämäri et al. https://doi.org/10.1016/j.jhydrol.2018.07.037
50. The challenges of modelling phosphorus in a headwater catchment: Applying a ‘limits of acceptability’ uncertainty framework to a water quality model M. Hollaway et al. https://doi.org/10.1016/j.jhydrol.2018.01.063
51. Bayesian inference of uncertainty in freshwater quality caused by low-resolution monitoring T. Krueger https://doi.org/10.1016/j.watres.2017.02.061
52. Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data M. Miller et al. https://doi.org/10.1002/2015WR017753
53. Controls for multi-temporal patterns of riverine nitrogen and phosphorus export to lake: Implications for catchment management by high-frequency observations H. Xie et al. https://doi.org/10.1016/j.jenvman.2022.115858
54. Multipoint High-Frequency Sampling System to Gain Deeper Insights on the Fate of Nitrate in Artificially Drained Fields W. Liu et al. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001438
55. Simulating high frequency water quality monitoring data using a catchment runoff attenuation flux tool (CRAFT) R. Adams et al. https://doi.org/10.1016/j.scitotenv.2016.01.045
56. River Water‐Quality Concentration and Flux Estimation Can be Improved by Accounting for Serial Correlation Through an Autoregressive Model Q. Zhang & R. Hirsch https://doi.org/10.1029/2019WR025338
57. Impacts of changing weather patterns on the dynamics of water pollutants in agricultural catchments: Insights from 11-year high temporal resolution data analysis G. Ezzati et al. https://doi.org/10.1016/j.jhydrol.2024.132122
58. Hysteresis between groundwater and surface water levels indicates the states of hydrological turnover affecting solute transport and redox processes L. Bäthke & T. Schuetz https://doi.org/10.5194/hess-30-4889-2026
59. Spatial variation of event-based suspended sediment dynamics in the middle Yellow River basin, China B. Wang et al. https://doi.org/10.1016/j.geomorph.2022.108115
60. Monitoring the riverine pulse: Applying high‐frequency nitrate data to advance integrative understanding of biogeochemical and hydrological processes D. Burns et al. https://doi.org/10.1002/wat2.1348
61. Carbon and nutrient export regimes from headwater catchments to downstream reaches R. Dupas et al. https://doi.org/10.5194/bg-14-4391-2017
62. Is a simple model based on two mixing reservoirs able to reproduce the intra-annual dynamics of DOC and NO3 stream concentrations in an agricultural headwater catchment? L. Strohmenger et al. https://doi.org/10.1016/j.scitotenv.2021.148715
63. Technical Note: Testing an improved index for analysing storm discharge–concentration hysteresis C. Lloyd et al. https://doi.org/10.5194/hess-20-625-2016
64. Incidental nutrient transfers: Assessing critical times in agricultural catchments using high-resolution data M. Shore et al. https://doi.org/10.1016/j.scitotenv.2016.02.085
65. Real-time monitoring of water quality to identify pollution pathways in small and middle scale rivers A. Meyer et al. https://doi.org/10.1016/j.scitotenv.2018.10.069
66. Uncertainty assessment of a dominant-process catchment model of dissolved phosphorus transfer R. Dupas et al. https://doi.org/10.5194/hess-20-4819-2016
67. Water quality responses to hydrological droughts can be predicted from long-term concentration–discharge relationships R. Dupas et al. https://doi.org/10.1088/3033-4942/adb906
68. Export Coefficient Modelling of Nutrient Neutrality to Protect Aquatic Habitats in the River Wensum Catchment, UK K. Hiscock et al. https://doi.org/10.3390/environments10100168
69. A geospatial framework to support integrated biogeochemical modelling in the United Kingdom S. Greene et al. https://doi.org/10.1016/j.envsoft.2015.02.012
70. Rainfall increases the abundance of antibiotic resistance genes within a riverine microbial community A. Di Cesare et al. https://doi.org/10.1016/j.envpol.2017.04.036
71. Interpretation of river water quality data is strongly controlled by measurement time and frequency I. Elfferich et al. https://doi.org/10.1016/j.scitotenv.2024.176626
72. Challenges of Reducing Phosphorus Based Water Eutrophication in the Agricultural Landscapes of Northwest Europe R. Bol et al. https://doi.org/10.3389/fmars.2018.00276
73. Groundwater contributions of flow and nitrogen in a headwater agricultural watershed B. Redder et al. https://doi.org/10.1002/hyp.14179
74. Linking soils and streams during events: response of stream water K+ concentration to soil exchangeable K+ concentration in small catchments with fragipan soils (Carpathian Foothills, Poland) J. Siwek et al. https://doi.org/10.2478/johh-2020-0037
75. Antecedent conditions, hydrological connectivity and anthropogenic inputs: Factors affecting nitrate and phosphorus transfers to agricultural headwater streams F. Outram et al. https://doi.org/10.1016/j.scitotenv.2015.12.025
76. Diel turbidity cycles in a headwater stream: evidence of nocturnal bioturbation? R. Cooper et al. https://doi.org/10.1007/s11368-016-1372-y
77. Detecting the drivers of suspended sediment transport in an intermittent river: An event-based analysis R. Di Pillo et al. https://doi.org/10.1016/j.catena.2022.106881
78. Modeling the effect of land use/land cover on nitrogen, phosphorous and dissolved oxygen loads in the Velhas River using the concept of exclusive contribution area L. de Oliveira et al. https://doi.org/10.1007/s10661-016-5323-2
79. High-resolution monitoring of nutrients in groundwater and surface waters: process understanding, quantification of loads and concentrations, and management applications F. van Geer et al. https://doi.org/10.5194/hess-20-3619-2016
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81. Assessing the farm-scale impacts of cover crops and non-inversion tillage regimes on nutrient losses from an arable catchment R. Cooper et al. https://doi.org/10.1016/j.agee.2016.12.034
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