A large proportion of nutrients and sediment is mobilised in catchments during storm events. Therefore understanding a catchment's hydrological behaviour during storms and how this acts to mobilise ...and transport nutrients and sediment to nearby watercourses is extremely important for effective catchment management. The expansion of available in-situ sensors is allowing a wider range of water quality parameters to be monitored and at higher temporal resolution, meaning that the investigation of hydrochemical behaviours during storms is increasingly feasible. Studying the relationship between discharge and water quality parameters in storm events can provide a valuable research tool to infer the likely source areas and flow pathways contributing to nutrient and sediment transport. Therefore, this paper uses 2years of high temporal resolution (15/30min) discharge and water quality (nitrate-N, total phosphorus (TP) and turbidity) data to examine hysteretic behaviour during storm events in two contrasting catchments, in the Hampshire Avon catchment, UK. This paper provides one of the first examples of a study which comprehensively examines storm behaviours for up to 76 storm events and three water quality parameters. It also examines the observational uncertainties using a non-parametric approach. A range of metrics was used, such as loop direction, loop area and a hysteresis index (HI) to characterise and quantify the storm behaviour. With two years of high resolution information it was possible to see how transport mechanisms varied between parameters and through time. This study has also clearly shown the different transport regimes operating between a groundwater dominated chalk catchment versus a surface-water dominated clay catchment. This information, set within an uncertainty framework, means that confidence can be derived that the patterns and relationships thus identified are statistically robust. These insights can thus be used to provide information regarding transport processes and biogeochemical processing within river catchments.
Display omitted
•Hysteretic storm behaviour was analysed in 3 water quality parameters at 2 sites•Storms were analysed within an observational uncertainty framework•Range of metrics were used, including a new index, to quantify storm hysteresis•Differences in transport mechanisms shown between nitrate and TP in chalk system.•Behaviour was complex but provides insight into catchment processes in landscapes.
Analysis of hydrochemical behaviour during storm events can provide new insights into the process controls on nutrient transport in catchments. The examination of storm behaviours using hysteresis ...analysis has increased in recent years, partly due to the increased availability of high temporal resolution data sets for discharge and water quality parameters. A number of these analyses involve the use of an index to describe the characteristics of a hysteresis loop in order to compare storm behaviours both within and between catchments. This technical note reviews the methods for calculation of the hysteresis index (HI) and explores a new more effective methodology. Each method is systematically tested and the impact of the chosen calculation on the results is examined. Recommendations are made regarding the most effective method of calculating a HI which can be used for comparing data between storms and between different water quality parameters and catchments.
The choice of hydrological model structure, that is, a model's selection of states and fluxes and the equations used to describe them, strongly controls model performance and realism. This work ...investigates differences in performance of 36 lumped conceptual model structures calibrated to and evaluated on daily streamflow data in 559 catchments across the United States. Model performance is compared against a benchmark that accounts for the seasonality of flows in each catchment. We find that our model ensemble struggles to beat the benchmark in snow‐dominated catchments. In most other catchments model structure equifinality (i.e., cases where different models achieve similar high efficiency scores) can be very high. We find no relation between the number of model parameters and performance during either calibration or evaluation periods nor evidence of increased risk of overfitting for models with more parameters. Instead, the choice of model parametrization (i.e., which equations are used and how parameters are used within them) dictates the model's strengths and weaknesses. Results suggest that certain model structures are inherently better suited for certain objective functions and thus for certain study purposes. We find no clear relationships between the catchments where any model performs well and descriptors of those catchments' geology, topography, soil, and vegetation characteristics. Instead, model suitability seems to relate strongest to the streamflow regime each catchment generates, and we have formulated several tentative hypotheses that relate commonalities in model structure to similarities in model performance. Modeling results are made publicly available for further investigation.
Key Points
Conceptual model structure uncertainty is high across different catchments and objective functions
There is no evidence of systematic overfitting for models with up to 15 calibrated parameters
Model performance relates more to streamflow signatures than to climate or catchment descriptors
Phosphorus losses from land to water will be impacted by climate change and land management for food production, with detrimental impacts on aquatic ecosystems. Here we use a unique combination of ...methods to evaluate the impact of projected climate change on future phosphorus transfers, and to assess what scale of agricultural change would be needed to mitigate these transfers. We combine novel high-frequency phosphorus flux data from three representative catchments across the UK, a new high-spatial resolution climate model, uncertainty estimates from an ensemble of future climate simulations, two phosphorus transfer models of contrasting complexity and a simplified representation of the potential intensification of agriculture based on expert elicitation from land managers. We show that the effect of climate change on average winter phosphorus loads (predicted increase up to 30% by 2050s) will be limited only by large-scale agricultural changes (e.g., 20-80% reduction in phosphorus inputs).The impact of climate change on phosphorus (P) loss from land to water is unclear. Here, the authors use P flux data, climate simulations and P transfer models to show that only large scale agricultural change will limit the effect of climate change on average winter P loads in three catchments across the UK.
The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23–25 ...October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community. Editor D. Koutsoyiannis Citation Hrachowitz, M., Savenije, H.H.G., Blöschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., and Cudennec, C., 2013. A decade of Predictions in Ungauged Basins (PUB)—a review. Hydrological Sciences Journal , 58 (6), 1198–1255.
A traditional metric used in hydrology to summarize model
performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an
alternative metric, the Kling–Gupta efficiency (KGE), is used instead. ...When
NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark
predictor. The same reasoning is applied in various studies that use KGE as
a metric: negative KGE values are viewed as bad model performance, and only
positive values are seen as good model performance. Here we show that using
the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41
indicate that a model improves upon the mean flow benchmark – even if the
model's KGE value is negative. NSE and KGE values cannot be directly
compared, because their relationship is non-unique and depends in part on
the coefficient of variation of the observed time series. Therefore,
modellers who use the KGE metric should not let their understanding of NSE
values guide them in interpreting KGE values and instead develop new
understanding based on the constitutive parts of the KGE metric and the
explicit use of benchmark values to compare KGE scores against. More
generally, a strong case can be made for moving away from ad hoc use of
aggregated efficiency metrics and towards a framework based on
purpose-dependent evaluation metrics and benchmarks that allows for more
robust model adequacy assessment.
•Highlights principle data issues for change detection in hydrochemistry.•An extensive assessment of detection methods and their assumptions is presented.•Provides an evaluation of statistical power ...of the change detection methods.•Conceptual framework for choosing a robust change detection methodology is proposed.
Detecting changes in catchment hydrochemistry driven by targeted pollutant mitigation is high on the scientific agenda, following the introduction of the European Union Water Framework Directive. Previous research has shown that understanding natural variability in hydrochemistry time series is vital if changes due to mitigation are to be detected. In order for change to be detected in a statistically robust manner, the data analysis methods need careful consideration. Previous work has shown that erroneous results have often been obtained when statistical analyses have been carried out despite the associated test assumptions not being met. This paper discusses the principal data issues which must be considered when analysing hydrochemical datasets, including non-normality and non-stationarity. A range of statistical techniques is discussed which could be used to detect gradual or abrupt changes in hydrochemistry, including parametric, non-parametric and signal decomposition methods. The statistical power of these techniques as well as their suitability for identifying change is discussed. Using the uniquely detailed hydrochemical datasets generated under the Demonstration Test Catchments programme in England, the efficacy and robustness of change detection methods for hydrochemical data series is assessed. A conceptual framework for choosing a change detection method is proposed, based on this analysis, in order to raise awareness of the types of questions a researcher should consider in order to perform robust statistical analyses, for informing river catchment management and policy support decisions.
A history of TOPMODEL Beven, Keith J; Kirkby, Mike J; Freer, Jim E ...
Hydrology and earth system sciences,
02/2021, Letnik:
25, Številka:
2
Journal Article
Recenzirano
Odprti dostop
The theory that forms the basis of TOPMODEL (a topography-based hydrological model) was first outlined by Mike Kirkby some 45 years ago. This paper recalls some of the early developments, the ...rejection of the first journal paper, the early days of digital terrain analysis, model calibration and validation, the various criticisms of the simplifying assumptions, and the relaxation of those assumptions in the dynamic forms of TOPMODEL. A final section addresses the question of what might be done now in seeking a simple, parametrically parsimonious model of hillslope and small catchment processes if we were starting again.
PDF
