Unterschiede

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--- thesis:demoarbeit [2021/02/10 16:24] – r.schwemmle
+++ thesis:demoarbeit [2021/02/11 10:07] (aktuell) – r.schwemmle
@@ Zeile 1: / Zeile 1: @@
-===== Linking specific evaluation metrics to hydrologic processes =====
+===== Vorlage =====
 == Motivation ==
-Hydrologic models provide the ability to simulate hydrologic fluxes. However,
-these simulated fluxes may deviate from observed fluxes. Therefore, assessing
-the process realism of these hydrologic models require process-specific metrics.
-Hydrologic processes can be captured by hydrologic signatures. Including these
-hydrologic signatures into the evaluation process may improve the assessment of
-process realism of hydrologic models.
-== Research objectives ==
-The aim of this MSc thesis is to define new process-specific metrics and test their applicability. Optionally, the model error quantified by the metric
-may be linked to model parameters or input data by statistical analysis (e.g.
-correlation, random forest).
-== Methodology ==
+== Ziele der Arbeit ==
-McMillan (2020) provide an extensive summary on hydrologic signatures. Suitable
-hydrologic signatures have to be selected to define process-specific evaluation
-metrics (Schwemmle et al., 2020) for specific processes (e.g. baseflow). In the
-following, these newly defined metrics can be calculated using the CAMELS US
-data set (Newman et al., 2015).
-== Supervision ==
-Robin Schwemmle, Markus Weiler
-== Further notes ==
+== Methode ==
-The CAMELS US data set (Addor et al., 2017; Newman et al., 2015) is publicly
-available and must be downloaded by the student. The data set contains observed
-streamflow time series and catchment attributes for each catchment. Moreover, simulated
-streamflow time series (coupled Snow-17 snow model and the Sacramento
-Soil Moisture Accounting Model) and the accompanying parameters and
-input data are available for each catchment. The catchments span over a wide
-range of hydroclimatic conditions.
-== Contact ==
-Robin Schwemmle
-[[robin.schwemmle@hydrology.uni-freiburg.de]]
-== Skills and challenges ==
+== Betreuung ==
-Handling large data sets, advanced programming skills, knowledge in the
-programming language Python, (bivariate or multivariate statistics)
-== Sprache ==
-English (or German)
-== Literatur ==
+== Zusätzliche Hinweise ==
-Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293-5313, 10.5194/hess-21-5293-2017, 2017.
-Gnann, S. J., Coxon, G., Woods, R. A., Howden, N. J. K., and McMillan, H. K.: TOSSH: A Toolbox for Streamflow Signatures in Hydrology, Environmental Modelling & Software, 138, 104983, 10.1016/j.envsoft.2021.104983, 2021.
-McMillan, H.: Linking hydrologic signatures to hydrologic processes: A review, Hydrological Processes, 34, 1393-1409, 10.1002/hyp.13632, 2020.
+== Kontakt ==
+Name
+[[name@hydrology.uni-freiburg.de]]
-Newman, A. J., Clark, M. P., Sampson, K., Wood, A., Hay, L. E., Bock, A., Viger, R. J., Blodgett, D., Brekke, L., Arnold, J. R., Hopson, T., and Duan, Q.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19, 209-223, 10.5194/hess-19-209-2015, 2015.
+== Herausforderungen ==
+== Sprache ==
+== Literatur ==
-Schwemmle, R., Demand, D., and Weiler, M.: Technical note: Diagnostic efficiency – specific evaluation of model performance, Hydrol. Earth Syst. Sci. Discuss. [preprint], 10.5194/hess-2020-237, in review, 2020.
-Yilmaz, K. K., Gupta, H. V., and Wagener, T.: A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model, Water Resources Research, 44, 10.1029/2007wr006716, 2008.
+{{tag>}}
-{{tag>master daten offen}}