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Abstract. High-frequency, long-term and multisolute measurements are required to assess the impact of human pressures on water quality due to (i) the high temporal and spatial variability of climate and human activity and (ii) the fact that chemical solutes combine short-and long-term dynamics. Such data series are scarce. This study, based on an original and unpublished time series from the Kervidy-Naizin headwater catchment (Brittany, France), aims to determine solute transfer processes and dynamics that characterise this strongly human-impacted catchment.The Kervidy-Naizin catchment is a temperate, intensive agricultural catchment, hydrologically controlled by shallow groundwater. Over 10 yr, five solutes (nitrate, sulphate, chloride, and dissolved organic and inorganic carbon) were monitored daily at the catchment outlet and roughly every four months in the shallow groundwater.The concentrations of all five solutes showed seasonal variations but the patterns of the variations differed from one solute to another. Nitrate and chloride exhibit rather smooth variations. In contrast, sulphate as well as organic and inorganic carbon is dominated by flood flushes. The observed nitrate and chloride patterns are typical of an intensive agricultural catchment hydrologically controlled by shallow groundwater. Nitrate and chloride originating mainly from organic fertilisers accumulated over several years in the shallow groundwater. They are seasonally exported when upland groundwater connects with the stream during the wet season. Conversely, sulphate as well as organic and inorganic carbon patterns are not specific to agricultural catchments. These solutes do not come from fertilisers and do not accumulate in soil or shallow groundwater; instead, they are biogeochemically produced in the catchment. The results allowed development of a generic classification system based on the specific temporal patterns and source locations of each solute. It also considers the stocking period and the dominant process that limits transport to the stream, i.e. the connectivity of the stocking compartment. This mechanistic classification can be applied to any chemical solute to help assess its origin, storage or production location and transfer mechanism in similar catchments.

Multi-Criteria Decision Analysis (MCDA) needs tools to enable citizen participation 43 reviewed water-related serious games reveal diverse approaches and uses Serious games in MCDA entail communicating about and with models (behavioral OR) No existing serious game allows MCDA-compatible preference elicitation

Recently developed measurement technologies can monitor surface water quality almost continuously, creating high-frequency multiparameter time series and raising the question of how best to extract insights from such rich data sets. Here we use spectral analysis to characterize the variability of water quality at the AgrHys observatory (Western France) over time scales ranging from 20 min to 12 years. Three years of daily sampling at the intensively farmed Kervidy-Naizin watershed reveal universal 1/f scaling for all 36 solutes, yielding spectral slopes of 1.05 ± 0.11 (mean ± standard deviation). These 36 solute concentrations show varying degrees of annual cycling, suggesting different controls on watershed export processes. Twelve years of daily samples of SO4, NO3, and dissolved organic carbon (DOC) show that 1/f scaling does not continue at frequencies below 1/year in those constituents, whereas a 12-year daily record of Cl shows a general 1/f trend down to the lowest measurable frequencies. Conversely, approximately 12 months of 20 min NO3 and DOC measurements show that at frequencies higher than 1/day, the spectra of these solutes steepen to slopes of roughly 3, and at time scales shorter than 2-3 h, the spectra flatten to slopes near zero, reflecting analytical noise. These results confirm and extend the recent discovery of universal fractal 1/f scaling in water quality at the relatively pristine Plynlimon watershed in Wales, further demonstrating the importance of advective-dispersive transport mixing in catchments. However, the steeper scaling at subdaily time scales suggests additional short-term damping of solute concentrations, potentially due to in-stream or riparian processes.

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The recent development of in-situ monitoring devices, such as UV-spectrometers, makes the study of short-term stream chemistry variation relevant, especially the study of diurnal cycles, which are not yet fully understood. Our study is based on high-frequency data from an agricultural catchment (Studienlandschaft Schwingbachtal, Germany). We propose a novel approach, i.e. the combination of cluster analysis and Linear Discriminant Analysis, to mine from these data nitrate behavior patterns. As a result, we observe a seasonality of nitrate diurnal cycles, that differs from the most common cycle seasonality described in the literature, i.e. pre-dawn peaks in spring. Our cycles appear in summer and the maximum and minimum shift to a later time in late summer/autumn. This is observed both for water- and energy-limited years, thus potentially stressing the role of evapotranspiration. This concluding hypothesis on the role of evapotranspiration on nitrate stream concentration, which was obtained through data mining, broadens the perspective on the diurnal cycling of stream nitrate concentrations.

No abstract

Multi-Criteria Decision Analysis (MCDA) requires a critical step, namely to elicit individual preferences. On the basis of learning theories, we formalize preference construction as learning about facts and values, and as a process; we also conceptualize an online preference elicitation survey that offers learning loops to increase factual learning and support preference construction. Another originality is gamification. Game elements (a narrative and non-player characters as motivational affordance) keep respondents engaged in the demanding task of weight elicitation. Our tool enables broad public participation in MCDA, allowing reliable online preference elicitation. The survey concept was tested with 107 students and a control treatment. Quantitative and qualitative data indicate that the concept works. Participants' factual knowledge increased. The survey helped students to learn about their own preferences concerning the importance of objectives. The practical implication is that weighting can be reliably elicited by online surveys. Participants reported a positive experience; further ways to improve it are thoroughly discussed.