TY  - JOUR
A1  - Sarrazin, Fanny J.
A1  - Kumar, Rohini
A1  - Basu, Nandita B.
A1  - Musolff, Andreas
A1  - Weber, Michael
A1  - Van Meter, Kimberly J.
A1  - Attinger, Sabine
T1  - Characterizing catchment-scale nitrogen legacies and constraining their uncertainties
JF  - Water resources research
N2  - Improving nitrogen (N) status in European water bodies is a pressing issue. N levels depend not only on current but also past N inputs to the landscape, that have accumulated through time in legacy stores (e.g., soil, groundwater). 
Catchment-scale N models, that are commonly used to investigate in-stream N levels, rarely examine the magnitude and dynamics of legacy components. 

This study aims to gain a better understanding of the long-term fate of the N inputs and its uncertainties, using a legacy-driven N model (ELEMeNT) in Germany's largest national river basin (Weser; 38,450 km(2)) over the period 1960-2015. 
We estimate the nine model parameters based on a progressive constraining strategy, to assess the value of different observational data sets. 
We demonstrate that beyond in-stream N loading, soil N content and in-stream N concentration allow to reduce the equifinality in model parameterizations. 
We find that more than 50% of the N surplus denitrifies (1480-2210 kg ha(-1)) and the stream export amounts to around 18% (410-640 kg ha(-1)), leaving behind as much as around 230-780 kg ha(-1) of N in the (soil) source zone and 10-105 kg ha(-1) in the subsurface. 

A sensitivity analysis reveals the importance of different factors affecting the residual uncertainties in simulated N legacies, namely hydrologic travel time, denitrification rates, a coefficient characterizing the protection of organic N in source zone and N surplus input. 

Our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce the equifinality in water quality modeling.
KW  - nitrogen legacies
KW  - water quality modeling
KW  - equifinality
KW  - parameter
KW  - estimation
KW  - sensitivity analysis
Y1  - 2022
U6  - https://doi.org/10.1029/2021WR031587
SN  - 0043-1397
SN  - 1944-7973
VL  - 58
IS  - 4
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - Xu, Pengbo
A1  - Deng, Weihua
A1  - Sandev, Trifce
T1  - Levy walk with parameter dependent velocity
BT  - hermite polynomial approach and numerical simulation
JF  - Journal of physics : A, Mathematical and theoretical
N2  - To analyze stochastic processes, one often uses integral transform (Fourier and Laplace) methods. However, for the time-space coupled cases, e.g. the Levy walk, sometimes the integral transform method may fail. Here we provide a Hermite polynomial expansion approach, being complementary to the integral transform method, to the Levy walk. Two approaches are compared for some already known results. We also consider the generalized Levy walk with parameter dependent velocity. Namely, we consider the Levy walk with velocity which depends on the walking length or on the duration of each step. Some interesting features of the generalized Levy walk are observed, including the special shapes of the probability density function, the first passage time distributions, and various diffusive behaviors of the mean squared displacement.
KW  - Hermite polynomial expansion
KW  - Levy walk
KW  - anomalous diffusion
KW  - parameter
KW  - dependent velocity
Y1  - 2020
U6  - https://doi.org/10.1088/1751-8121/ab7420
SN  - 1751-8113
SN  - 1751-8121
VL  - 53
IS  - 11
PB  - IOP Publ. Ltd.
CY  - Bristol
ER  - 
TY  - JOUR
A1  - Weigend, Michael
T1  - How Things Work
BT  - Recognizing and Describing Functionality
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
N2  - Recognizing and defining functionality is a key competence
adopted in all kinds of programming projects. This study investigates
how far students without specific informatics training are able to identify
and verbalize functions and parameters. It presents observations
from classroom activities on functional modeling in high school chemistry
lessons with altogether 154 students. Finally it discusses the potential
of functional modelling to improve the comprehension of scientific
content.
KW  - Function
KW  - programming
KW  - parameter
KW  - competence
KW  - abstraction
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82814
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 285
EP  - 298
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  -