@article{SarrazinKumarBasuetal.2022, author = {Sarrazin, Fanny J. and Kumar, Rohini and Basu, Nandita B. and Musolff, Andreas and Weber, Michael and Van Meter, Kimberly J. and Attinger, Sabine}, title = {Characterizing catchment-scale nitrogen legacies and constraining their uncertainties}, series = {Water resources research}, volume = {58}, journal = {Water resources research}, number = {4}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2021WR031587}, pages = {32}, year = {2022}, abstract = {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.}, language = {en} } @article{MtilatilaBronstertShresthaetal.2020, author = {Mtilatila, Lucy Mphatso Ng'ombe and Bronstert, Axel and Shrestha, Pallav and Kadewere, Peter and Vormoor, Klaus Josef}, title = {Susceptibility of water resources and hydropower production to climate change in the tropics}, series = {Hydrology : open access journal}, volume = {7}, journal = {Hydrology : open access journal}, number = {3}, publisher = {MDPI}, address = {Basel}, issn = {2306-5338}, doi = {10.3390/hydrology7030054}, pages = {26}, year = {2020}, abstract = {The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17\%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5\% (-5\%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20\% (-15\%). The study further projects a reduction in annual hydropower production between 1\% (RCP8.5) and 2.5\% (RCP4.5) during 2021-2050 and between 5\% (RCP4.5) and 24\% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.}, language = {en} } @article{WagenerReineckePianosi2022, author = {Wagener, Thorsten and Reinecke, Robert and Pianosi, Francesca}, title = {On the evaluation of climate change impact models}, series = {Wiley interdisciplinary reviews : Climate change}, volume = {13}, journal = {Wiley interdisciplinary reviews : Climate change}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {1757-7780}, doi = {10.1002/wcc.772}, pages = {13}, year = {2022}, abstract = {In-depth understanding of the potential implications of climate change is required to guide decision- and policy-makers when developing adaptation strategies and designing infrastructure suitable for future conditions. Impact models that translate potential future climate conditions into variables of interest are needed to create the causal connection between a changing climate and its impact for different sectors. Recent surveys suggest that the primary strategy for validating such models (and hence for justifying their use) heavily relies on assessing the accuracy of model simulations by comparing them against historical observations. We argue that such a comparison is necessary and valuable, but not sufficient to achieve a comprehensive evaluation of climate change impact models. We believe that a complementary, largely observation-independent, step of model evaluation is needed to ensure more transparency of model behavior and greater robustness of scenario-based analyses. This step should address the following four questions: (1) Do modeled dominant process controls match our system perception? (2) Is my model's sensitivity to changing forcing as expected? (3) Do modeled decision levers show adequate influence? (4) Can we attribute uncertainty sources throughout the projection horizon? We believe that global sensitivity analysis, with its ability to investigate a model's response to joint variations of multiple inputs in a structured way, offers a coherent approach to address all four questions comprehensively. Such additional model evaluation would strengthen stakeholder confidence in model projections and, therefore, into the adaptation strategies derived with the help of impact models. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change}, language = {en} } @article{TalukderSenMetzleretal.2013, author = {Talukder, Srijeeta and Sen, Shrabani and Metzler, Ralf and Banik, Suman K. and Chaudhury, Pinaki}, title = {Stochastic optimization-based study of dimerization kinetics}, series = {JOURNAL OF CHEMICAL SCIENCES}, volume = {125}, journal = {JOURNAL OF CHEMICAL SCIENCES}, number = {6}, publisher = {INDIAN ACAD SCIENCES}, address = {BANGALORE}, issn = {0974-3626}, pages = {1619 -- 1627}, year = {2013}, abstract = {We investigate the potential of numerical algorithms to decipher the kinetic parameters involved in multi-step chemical reactions. To this end, we study dimerization kinetics of protein as a model system. We follow the dimerization kinetics using a stochastic simulation algorithm and combine it with three different optimization techniques (genetic algorithm, simulated annealing and parallel tempering) to obtain the rate constants involved in each reaction step. We find good convergence of the numerical scheme to the rate constants of the process. We also perform a sensitivity test on the reaction kinetic parameters to see the relative effects of the parameters for the associated profile of the monomer/dimer distribution.}, language = {en} }