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358 results on '"Rubin, Y"'

1. Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO2 and N2

Author

Newcomer, ME, Hubbard, SS, Fleckenstein, JH, Maier, U, Schmidt, C, Thullner, M, Ulrich, C, Flipo, N, and Rubin, Y

Subjects
nutrient dynamics, hyporheic biogenic gas, water table fluctuations, dynamic permeability, losing rivers, Mediterranean climate, Geophysics
Abstract

Rivers in climatic zones characterized by dry and wet seasons often experience periodic transitions between losing and gaining conditions across the river-aquifer continuum. Infiltration shifts can stimulate hyporheic microbial biomass growth and cycling of riverine carbon and nitrogen leading to major exports of biogenic CO2 and N2 to rivers. In this study, we develop and test a numerical model that simulates biological-physical feedback in the hyporheic zone. We used the model to explore different initial conditions in terms of dissolved organic carbon availability, sediment characteristics, and stochastic variability in aerobic and anaerobic conditions from water table fluctuations. Our results show that while highly losing rivers have greater hyporheic CO2 and N2 production, gaining rivers allowed the greatest fraction of CO2 and N2 production to return to the river. Hyporheic aerobic respiration and denitrification contributed 0.1–2 g/m2/d of CO2 and 0.01–0.2 g/m2/d of N2; however, the suite of potential microbial behaviors varied greatly among sediment characteristics. We found that losing rivers that consistently lacked an exit pathway can store up to 100% of the entering C/N as subsurface biomass and dissolved gas. Our results demonstrate the importance of subsurface feedbacks whereby microbes and hydrology jointly control fate of C and N and are strongly linked to wet-season control of initial sediment conditions and hydrologic control of seepage direction. These results provide a new understanding of hydrobiological and sediment-based controls on hyporheic zone respiration, including a new explanation for the occurrence of anoxic microzones and large denitrification rates in gravelly riverbeds.

Published
2018

2. Simulating bioclogging effects on dynamic riverbed permeability and infiltration

Author

Newcomer, ME, Hubbard, SS, Fleckenstein, JH, Maier, U, Schmidt, C, Thullner, M, Ulrich, C, Flipo, N, and Rubin, Y

Subjects
Environmental Engineering, Physical Geography and Environmental Geoscience, Civil Engineering
Abstract

Bioclogging in rivers can detrimentally impact aquifer recharge. This is particularly so in dry regions, where losing rivers are common, and where disconnection between surface water and groundwater (leading to the development of an unsaturated zone) can occur. Reduction in riverbed permeability due to biomass growth is a time-variable parameter that is often neglected, yet permeability reduction from bioclogging can introduce order of magnitude changes in seepage fluxes from rivers over short (i.e.; monthly) timescales. To address the combined effects of bioclogging and disconnection on infiltration, we developed numerical representations of bioclogging processes within a one-dimensional, variably saturated flow model representing losing-connected and losing-disconnected rivers. We tested these formulations using a synthetic case study informed with biological data obtained from the Russian River, California, USA. Our findings show that modeled biomass growth reduced seepage for losing-connected and losing-disconnected rivers. However, for rivers undergoing disconnection, infiltration declines occurred only after the system was fully disconnected. Before full disconnection, biologically induced permeability declines were not significant enough to offset the infiltration gains introduced by disconnection. The two effects combine to lead to a characteristic infiltration curve where peak infiltration magnitude and timing is controlled by permeability declines relative to hydraulic gradient gains. Biomass growth was found to hasten the onset of full disconnection; a condition we term 'effective disconnection'. Our results show that river infiltration can respond dynamically to bioclogging and subsequent permeability declines that are highly dependent on river connection status.

Published
2016

4. Understanding local and macroscopic electron mobilities in the fullerene network of conjugated polymer-based solar cells: Time-resolved microwave conductivity and theory

Author

Aguirre, JC, Arntsen, C, Hernandez, S, Huber, R, Nardes, AM, Halim, M, Kilbride, D, Rubin, Y, Tolbert, SH, Kopidakis, N, Schwartz, BJ, and Neuhauser, D

Subjects
electron mobility, solar cells, conjugated polymers, fullerene networks, Materials, Chemical Sciences, Engineering, Physical Sciences
Abstract

The efficiency of bulk heterojunction (BHJ) organic photovoltaics is sensitive to the morphology of the fullerene network that transports electrons through the device. This sensitivity makes it difficult to distinguish the contrasting roles of local electron mobility (how easily electrons can transfer between neighboring fullerene molecules) and macroscopic electron mobility (how well-connected is the fullerene network on device length scales) in solar cell performance. In this work, a combination of density functional theory (DFT) calculations, flash-photolysis time-resolved microwave conductivity (TRMC) experiments, and space-charge-limit current (SCLC) mobility estimates are used to examine the roles of local and macroscopic electron mobility in conjugated polymer/fullerene BHJ photovoltaics. The local mobility of different pentaaryl fullerene derivatives (so-called 'shuttlecock' molecules) is similar, so that differences in solar cell efficiency and SCLC mobilities result directly from the different propensities of these molecules to self-assemble on macroscopic length scales. These experiments and calculations also demonstrate that the local mobility of phenyl-C60 butyl methyl ester (PCBM) is an order of magnitude higher than that of other fullerene derivatives, explaining why PCBM has been the acceptor of choice for conjugated polymer BHJ devices even though it does not form an optimal macroscopic network. The DFT calculations indicate that PCBM's superior local mobility comes from the near-spherical nature of its molecular orbitals, which allow strong electronic coupling between adjacent molecules. In combination, DFT and TRMC techniques provide a tool for screening new fullerene derivatives for good local mobility when designing new molecules that can improve on the macroscopic electron mobility offered by PCBM. The roles of local and macroscopic electron mobility in conjugated polymer/fullerene BHJ photovoltaics are examined via a combination of density functional theory, flash-photolysis time-resolved microwave conductivity, and space-charge-limit current (SCLC) mobility estimates. The local mobility of different fullerene derivatives ('shuttlecock' molecules) is similar, so differences in solar cell efficiency and SCLC mobilities result directly from the different propensities of these molecules to self-assemble on macroscopic length scales. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Published
2014

5. Panoramic view of electrochemical pseudocapacitor and organic solar cell research in molecularly engineered energy materials (MEEM)

Author

Aguirre, JC, Ferreira, A, Ding, H, Jenekhe, SA, Kopidakis, N, Asta, M, Pilon, L, Rubin, Y, Tolbert, SH, Schwartz, BJ, Dunn, B, and Ozolins, V

Subjects
Physical Chemistry, Engineering, Chemical Sciences, Technology
Abstract

Our program on capacitive energy storage is a comprehensive one that combines experimental and computational components to achieve a fundamental understanding of charge storage processes in redox-based materials, specifically transition metal oxides. Some of the highlights of this program are the identification of intercalation pseudocapacitance in Nb2O 5, which enables high energy density to be achieved at high rates, and the development of a new route for synthesizing mesoporous films in which preformed nanocrystal building blocks are used in combination with polymer templating. The resulting material architectures have large surface areas and enable electrolyte access to the redox active pore walls, while the interconnected mesoporous film provides good electronic conductivity. Select first-principles density-functional theory studies of prototypical pseudocapacitor materials are reviewed, providing insight into the key physical and chemical features involved in charge transfer and ion diffusion. Rigorous multiscale physical models and numerical tools have been developed and used to reproduce electrochemical properties of carbon-based electrochemical capacitors with the ultimate objective of facilitating the optimization of electrode design. For the organic photovoltaic (OPV) program, our focus has been ongoing beyond the trial-and-error Edisonian approaches that have been responsible for the increase in power conversion efficiency of blend-cast (BC) bulk heterojunction blends of polymers and fullerenes. Our first approach has been to use molecular self-assembly to create the ideal nanometer-scale architecture using thermodynamics rather than relying on the kinetics of spontaneous phase segregation. We have created fullerenes that self-assemble into one-dimensional stacks and have shown that use of these self-assembled fullerenes lead to dramatically enhanced OPV performance relative to fullerenes that do not assemble. We also have created self-assembling conjugated polymers that form gels based on electrically continuous cross-linked micelles in solution, opening the possibility for water-processable "green" production of OPVs based on these materials. Our second approach has been to avoid kinetic control over phase separation by using a sequential processing (SqP) technique to deposit the polymer and fullerene materials in separate deposition steps. The polymer layer is deposited first, using solvents and deposition conditions that optimize the polymer crystallinity for swelling and hole mobility. The fullerene layer is then deposited in a second step from a solvent that swells the polymer but does not dissolve it, allowing the fullerene to penetrate into the polymer underlayer to the desired degree. Careful comparison of composition- and thickness-matched BC and SqP devices shows that SqP not only produces more efficient devices but also leads to devices that behave more consistently. © 2014 American Chemical Society.

Published
2014

10. Defining hydrogeological site similarity with hierarchical agglomerative clustering

Author

Kawa, N., Cucchi, K., Rubin, Y., Attinger, Sabine, Heße, Falk, Kawa, N., Cucchi, K., Rubin, Y., Attinger, Sabine, and Heße, Falk

Abstract

Hydrogeological information about an aquifer is difficult and costly to obtain, yet essential for the efficient management of groundwater resources. Transferring information from sampled sites to a specific site of interest can provide information when site-specific data is lacking. Central to this approach is the notion of site similarity, which is necessary for determining relevant sites to include in the data transfer process. In this paper, we present a data-driven method for defining site similarity. We apply this method to selecting groups of similar sites from which to derive prior distributions for the Bayesian estimation of hydraulic conductivity measurements at sites of interest. We conclude that there is now a unique opportunity to combine hydrogeological expertise with data-driven methods to improve the predictive ability of stochastic hydrogeological models.

Published
2022

22. Contributory presentations/posters

Author

Gries, A., Singh, Balwinder, Nakazawal, Chicko, Genest, D., Getzoff, E. D., Matsuo, H., Kaur, Harpreet, Borst, J. W., Chadha, K. C., Tingyun, Kuang, Jagannadham, M. V., Leijon, Mikael, Sato, S., Bhakuni, Vlnod, Vijayan, M., Surolia, A., Suguna, K., Manoj, N., Srinivas, V. R., Ravishankar, R., Laggner, P., Prassl, R., Schwarzenbacher, R., Zeth, K., Kostner, G. M., Taylor, Susan S., Xuong, Nguyen-huu, Akamine, Pearl, Sagar, Bidva M., Saikrishnan, K., Purnapatre, K., Handa, P., Roy, S., Varshney, U., Biswal, B. K., Sukumar, N., Rao, J. K. Mohana, Johnson, A., Pattabhi, Vasantha, Murthy, M. R. N., Krishna, Sri S., Savithri, H. S., Sastri, Mira, Hosur, M. V., Pillai, Bindu, Kannan, K. K., Kumar, Mukesh, Patwardhan, Swati, Padmanabhaa, B., Sasaki-Sugio, S., Matsuzaki, T., Nukaga, M., Singh, T. P., Sharma, A. K., Srinivasan, A., Khan, J. A., Paramasivam, M., Kumar, P., Karthikevan, S., Sharma, S., Yadav, S., Srintvasan, A., Alam, Neelima, Gourinath, S., Kaur, Punit, Chandra, Vikas, Betzel, Ch., Ghosh, S., Bera, A. K., Pal, A. K., Baneriee, Asok, Mukhopadhyay, B. P., Bhattacharya, S., Chakraborty, S., Haldar, U., Dey, I., Solovicova, Adriana, Sevcik, Jozef, Sekar, K., Sundaralingam, M., Genov, N., Liang, Dong-cai, Zhang, Ji-ping, Jiang, Tao, Chang, Wen-rui, Blommers, Marcel, Jahnke, Wolfgang, Hosur, R. V., Panchal, S. C., Pillay, Bindu, Jaganathan, N. R., Mathur, Puniti, Srivatsun, S., Joshi, Ratan Mani, Chauhan, V. S., Govil, Girjesh, Atreya, H. S., Sahu, S. C., Quinjou, Éric, Adjadj, Elisabeth, Mispelter, Joël, Izadi-Pruneyre, Nadia, Blouquit, Yves, Heyd, Bernadette, Lerat, Guilhem, Desmadreil, Michel, Milnard, Philippe, Lin, Y., Rao, B. D. Nageswara, Raghunathan, Vidva, Chau, Mei H., Coutinho, Evans, Pesais, Prashant, Srivastava, Sudha, Saran, Anil, Srikrishnan, Thamarapu, Lijima, Herbert, Gesme, Jayson, Sapico, Leizl F., Paxton, Raymond, Grace, C. R., Nagenagowda, G., Lynn, A. M., Cowsik, Sudha M., Govil, G., Sahu, Sarata C., Bhattacharya, A., Chauhan, S., Kumar, Anil, Zuiderweg, Erik R. P., Pellecchia, Maurizio, Nitta, Katsutoshi, Ohnishi, Atsushi, Kawano, Keiichi, Hikichi, Kunio, Fujitani, Naoki, Ohkubo, Tadayasu, Aizawa, Tomoyasu, Kumaki, Yasuhiro, Hayakawa, Yoichi, Parvathy, Rani V., Kini, R. M., Nakagawa, Astushi, Tanaka, Isao, Demura, Makoto, Yao, Min, Koshiba, Takumi, Kobashigawa, Yoshihiro, Kuwajima, Kunihiro, Linge, Jens, Nilges, Michael, Donoghue, Seán O., Chakshusmathi, G., Ratnaparkhi, Girish S., Madhu, P. K., Varadarajan, R., Tetreau, C., Tourbez, M., Lavalette, D., Bulone, D., Manno, M., Emanuele, A., Palma-Vittorelli, M. B., Palma, M. U., Vaiana, S. M., Martorana, V., Biagio, P. L. San, Chang, D. K., Cheng, S. F., Yang, S. H., Francis, S., Trivedi, V. D., Chien, W. J., Manstein, Dietmar J., Batra, Renn, Geeves, Michael A., Geller, Maciej, Trvlska, Joanna, Grochowski, Pawel, Lesyng, B., Ginalski, K., Grochowski, P., Lavalette, P., Blouquit, Y., Roccatano, D., Berendsen, H. J. C., Amadei, A., Nola, Di A., Ho, Bosco, Curmi, P. M. G., Berry, H., Pelta, J., Pauthe, E., Lairez, D., Srinivasan, M., Sahi, Shakti, Kothekar, V., Madhusudnan, Kartha S., Nandel, Fateh S., Jain, D. V. S., Berendsen, Herman J. C., Feenstra, Anton K., Tama, F., Sanejouand, Y.-H., Go, N., Sharma, Deepak, Pasha, Santosh, Sharma, Sunita, Brahmachari, Samir K., Makker, Jyoti, Viiavaraghavan, R., Kumar, S., Dey, Sharmisllia, Krishnamoorthy, G., Lakshmikanth, G. S., Zaitseva, E. M., Mazhul, V. M., Kierdaszuk, Borys, Widengren, J., Rigler, R., Terry, B., Mets, Ü., Swaminathan, R., Yathindra, N., Thamotharan, S., Chosrowjan, H., Mataga, N., Shibata, Y., Morisima, I., Xiao, Ming, Selvin, Paul, Chakraharty, Tania, Cooke, Roger, Faraone, A., Branca, C., Maisano, G., Migliardo, P., Magazù, S., Villari, V., Behere, Digambar V., Deva, Sharique Zahida Waheed M., Vallone, B., Savino, C., Travaglini-Allocatelli, C., Cutruzzolà, F., Brunori, M., Gibson, Q. H., Mazumdar, Shyamalava, Mitra, Samaresh, Prasad, Swati, Soto, P., Fayad, R., Tyulkova, N. A., Sukovataya, I. E., Mamedov, Sh. V., Aksakal, B., Canturk, M., Aktas, B., Yilgin, R., Bogutska, K. I., Miroshnichenko, N. S., Wein, A. J., Hypolite, J. A., DiSanto, M., Chacko, S., Zheng, Y-M., Antosiewicz, J., Wojciechowski, M., Grycuk, T., Di Nola, Alfredo, Ceruso, Marc A., Chatterjee, Bishnu P., Bandvopadhvay, Subhasis, Choudhury, Devapriva, Khight, Stefan, Thompson, Andrew, Stojanoff, Vivian, Pinkner, Jerome, Hultgren, Scott, Flatters, Delphine, Goodfellow, Julia, Takazawatt, Fumi, Kanehisa, Minoru, Sasai, Masaki, Nakamura, Hironori, Wang, Bao Han, Pan, xin Min, Zheng, Yuan, Wang, Zhi Xin, Ahmad, Atta, Kulkarni, Sangeeta, Prakash, Koodathingal, Prajapati, Shashi, Surin, Alexey, Kihara, Hiroshi, Yang, Li, Matsumoto, Tomoharu, Nakagawa, Yuki, Semisotnov, Gennady V., Kimura, Kazumoto, Amemiya, Yoshiyuki, Tayyab, Saad, Muzammil, Salman, Kumar, Yogesh, Bhakuni, Vinod, Sundd, Monica, Kundu, Suman, Jagannadham, Medicherla V., Chandani, Bina, Warrier, Deepti, Sinha, Lalankumar, Dhar, Ruby, Mehrotra, Sonam, Khandelwal, Purnima, Seth, Subhendu, Gidwani, Arun, Prabha, Ratna C., Sasidhar, Y. U., Madhusudan, K. P., Nishikawa, Ken, Kinjo, Akira R., Varadarajan, Raghavan, Chakravarty, Suvobrata, Van Dael, H., Noyelle, K., Joniau, M., Haezebrouck, P., Jha, Indra Brata, Bhat, Rajiv, Dash, Sheffali, Mohanty, Prasanna, Bandyopadhyay, A. K., Sonawat, H. M., Rao, Ch. Mohan, Datta, Siddhartha, Raman, B., Rajaraman, K., Ramakrishna, T., Pande, A., Benedek, G., King, J., Betts, S., Pande, J., Asherie, N., Ogun, O., Kalacheva, G. S., Sokolova, I. V., Mitaku, Shigeki, Sonoyama, Masashi, Taira, Kunihiro, Yokoyama, Yasunori, Sasakil, Takanori, Kamo, Naoki, Mukai, Yuri, Dalal, Seema, Regan, Lynne, Mituku, Shigeki, Kumar, Devesh, Roychoudhury, Mihir, Lőrinczv, Dénes, Könczöl, Franciska, Farkas, László, Belagyi, Joseph, Schick, Christoph, Thomson, Christy A., Ananthanarayanan, Vettai S., Alirzayeva, E. G., Baba-Zade, S. N., Sarai, A., Kono, H., Uedaira, H., An, J., Gromiha, Michael M., Oobatake, M., Yutani, Katsuhide, Takano, Kazufumi, Yamagata, Yuriko, Jas, Gouri S., Hofrichter, James, Muñoz, Victor, Eaton, William A., Penoyar, Jonathan, Lo Verde, Philip T., Bódi, Á., Venekei, I., Kardos, J., Gráf, L., Závodszky, P., Szilágyi, András, Závodszky, Péter, Woolfson, D. N., Walshaw, J., Allan, R. D., Funahashi, Jun, Gupta, Savan, Di Nola, A., Mangoni, M., Roccatano, P., Ramachandraiah, Gosu, Chandra, Nagasuma R., Ciani, Barbara, Woolfson, Derek N., Nair, Usha B., Salunke, Dinakar M., Kaur, Kanwal J., Swaminathan, Chittoor P., Surolia, Avadhesha, Pramanik, A., Jörnvall, H., Nygren, P.-Å., Jonasson, P., Ståhl, S., Johansson, B.-L., Kratz, G., Wahren, J., Ekberg, K., Uhlén, M., Jansson, O. T., Uhlén, S., Misselwitz, Rolf, Welfle, Heinz, Welfle, Karin, Höhne, Wolfgang, Kurganov, B. I., Mitskevich, L. G., Fedurkina, N. V., Jarori, Gotam K., Maity, Haripada, Guharay, J., Sengupta, P. K., Sengupta, B., Sridevi, K., Kasturi, S. R., Gupta, S. P., Agarwal, Gunjan, Briehl, Robin W., Kwong, Suzanne, Tyulkova, N A., Ismailova, O. I., Parola, A. H., Yayon, A., Hariharan, C., Pines, D., Pines, E., Zamai, M., Cohen-Luria, R., Woolfeon, D. N., Spooner, G. A., Padya, M. J., Bharadwaj, D. K., Bakshi, Panchan, Jagannathan, N. R., Sharma, U., Srivastava, N., Barthwal, R., Matsuda, Keiko, Nishioka, Takaaki, Go, Nobuhiro, Urata, S., Aita, T., Husimi, Y., Majumder, Mainak, Subirana, Juan A., Malinina, Lucy, Abrescia, Nicola G. A., Aymami, Juan, Coll, Miquel, Eritxa, Ramón, Premraj, B. J., Thenmalarchelvi, R., Gautham, N., Kumar, Satheesh P., Kan, Lou-Sing, Hou, Ming, Lin, Shwu-Bin, Roy, Kanal B., Sana, Tapas, Bruant, N., Flatters, D., Lavery, R., Sklenar, Heinz, Rons, Remo, Lavery, Richard, Thakur, Ashoke Ranjan, Kundu, Sudip, Bandyopadhyay, Debashree, Bhattacharyya, Dhananjay, Majumdar, Rabi, Barceló, F., Portugal, J., Rao, B. J., Ramanathan, Sunita, Gliosli, Mahua, Varshney, Umesh, Kumar, Vinay N., Pataskar, Shashank S., Sarojini, R., Selvasekarapandian, S., Kolandaivel, P., Sukumar, S., Kolmdaivel, P., Maiti, Motilal, Das, Suman, Sen, Anjana, Xodo, Luigi, Suraci, Chiara, Del Terra, Elisa, Quadrifoglio, Franco, Diviacco, Silvia, Ray, Arghya, Rao, Basuthkar J., Karthikeyan, G., Chary, Kandala V. R., Mujeeb, Anwer, James, Thomas L., Bogdanov, A., Zanina, A., Haya, E. E. F., Kasyanenko, N., Cornélio, M. L., Bugs, M. R., Tolstorukov, Ye. M., Sanval, Nitish K., Tiwari, S. N., Sanyal, Nitish K., Choudhury, Mihir Roy, Patel, P. K., Bhavesh, Neel S., Gabrielian, Anna, Rigler, Rudolf, Edman, Lars, Wennmalm, Stefan, Constantinescu, B., Gazdaru, D., Radulcscu, I., Radu, L., Wärmländer, Sebastian, Aoki, Setsuyuki, Ishiura, Masahiro, Kondo, Takao, Pashinskaya, V. A., Kosevich, M. V., Shelkovsky, V. S., Blagoy, Yu. P., Wang, Ji-hua, Malathi, R., Chandrasekhar, K., Kandimalla, E. R., Agrawal, S., Rastogi, V. K., Palafox, Alcolea M., Singh, Chatar, Beniaminov, A. D., Minyat, E. E., Zdobnov, E. M., Ulyanov, N. B., Bondarenko, S. A., Ivanov, V. I., Singh, J. S., Tewari, Ravindra, Sonawane, Kailas D., Grosjean, Henri, Sonavane, Uddhavesh B., Morin, Annie, Doherty, Elizabeth A., Doudna, Jennifer A., Tochio, H., Shirakawa, M., Kyogoku, Y., Das, Achintya, Javaram, B., Kalra, Parul, Shukla, Piyush, Dixit, Surjit B., Beveridge, David L., McConnell, Kevin, Davidson, B. E., Chan, R. Y. S., Sawyer, W. H., Eccelston, J. F., Yan, Yuling, Norden, Bengt, Tuite, Eimer, Nielsen, Peter, Takahashi, Masayuki, Ghosh, Anirban, Bansal, Manju, Pingoud, Alfred, Christ, Frauke, Thole, Hubert, Pingoud, Vera, Wende, Wolfgang, Luthra, Pratibha Mehta, Chandra, Ramesh, Sen, Ranjan, Weisberg, Robert, King, Rodney, Gobets, Bas, van Amerongen, Herbert, van Stokkum, Ivo H. M., Larsen, Olaf F. A., van Grondelle, Rienk, Hilbers, Cornelis W., Heus, Hans A., Berends, Jos, Sngrvan, H E., Khudaverdian, N. V., Babayan, Yu. S., Pichierri, F., Gromiha, M., Prabakaran, P., Aida, M., Sayano, K., Merkienė, Eglė, Vilkaitis, Giedrius, Klimašauskas, Saulius, Serva, Saulius, Weinhold, Elmar, Bandiera, Antonella, Marsich, Eleonora, Manzini, Giorgio, Potikyan, G., Arakelyan, V., Babayan, Yu., Ninaber, Alex, Goodfellow, Julia M., Ohta, Shigeru, Ito, Yoichiro, Husimi, Yuzuru, Usukura, J., Aiba, H., Tagami, H., Nunes, Elia, Suarez, Mougli, Candreva, Carmen E., Keszenman, Deborah, Thyberg, Per, Földes-Papp, Zeno, Joshi, Amita, Singh, Dinesh, Rajeswari, M. R., Amenitsch, H., Pregetter, M., Chapman, J., Mishra, K. P., Pandev, B. N., Tonevitsky, A. G., Pohl, E. E., Agapov, I. I., Sun, J., Pohl, P., Dennison, S. M., Gorbeako, G. P., Dynbko, T. S., Mishra, A. K., Pappavee, N., Luis, Loura, Rodrigo, Almeida, Manuel, Prieto, Gendel, Ya. L., Kleszczyńska, H., Kuczera, J., Przestalski, S., Kral, T., Chernitsky, E. A., Senkovich, O. A., Rosin, V. V., Gasanov, R. A., Allakhverdieva, Y. M., Papageorgiou, G. C., Savopol, Tudor, Apetrei, Calin, Balea, Marius, Cucu, D., Mihailescu, D., Ramanathan, K. V., Bačić, Goran, Genest, Monique, Sajot, Nicolas, Garnier, Norbert, Crouzy, Serge, Zsiros, O., Várkonyi, Z. S., Combos, Z., Farkas, T., Cribier, Sophie, de Paula, F., Fraceto, I. F., Schreier, S., Spisni, A., Sevšek, F., Žekš, B., Gomišček, G., Svetina, S., Arrigler, V., Hotani, Hirokazu, Nomura, Fumimasa, Takiguchi, Kingo, Nagata, Miki, Panicker, Lata, Parvathanathan, P. S., Hotani, H., Takiguchi, K., Ishino, A., Saitoh, A., Afonin, S., Takahashi, A., Takizawa, T., Nakato, Y., Marathe, Dipti, Jørgensen, Kent, Chattopadhyay, Amitabha, Rukmini, R., Rawat, Satinder S., Pečar, S., Štrancar, J., Šentiurc, M., Stolič, Z., Filipin, K., Biswas, S. C., Samanta, Anunay, Sana, Satyen, Kinoshita, Koji, Yamazaki, Masahito, Ohki, Kazuo, Goto, Akira, Kiuchi, Tai, Kumeta, Takaaki, Ohba, Tetsuhiko, Sugar, I. P., Thompson, K. K., Biltonen, R. L., Thompson, T. E., Ichinose, H., Suezaki, Y., Akivama, M., Matuoka, S., Tsuchihashi, K., Gasa, S., Pike, H. M., Mattjus, P., Brown, R. E., Molotkovsky, J. G., Arora, Ashish, Kleinschmidt, Jörg H., Tamm, Lukas K., Kruglyakova, K. E., Luneva, O. G., Fedin, V. A., Kuptsoya, O. S., Visser, A. J. W. G., Visser, N. V., Dyubko, T. S., Ogihara, Toshihiko, Mishima, Kiyoshi, Shvaleva, A. L., Radenović, Č. N., Jeremić, M. G., Radenović, N. Č., Minić, P. M., Salakhutdinov, B. A., Aripov, T. F., Tadjibaeva, E. T., Zamaraeva, M. V., Vagina, O. N., Basak, A. K., Cole, A., Naylor, C., Poppofl, M., Titball, R., Naylor, C. E., Moss, D. S., Eaton, J. T., Justin, N., Titball, R. W., Nomura, F., Nagata, M., Ishjkawa, S., Takahashi, S., Obuchi, Kaoru, Staudegger, Erich, Lohner, Karl, Kriechbaum, Manfred, Waring, Alan J., Lehrer, Robert I., Mayer, Bernd, Köhler, Gottfried, Gangl, Susanne, Shobini, J., Hu, B., Lortz, B., Sackmann, E., Guttenberg, Z., Antonovich, A. N., Slobozhanina, E. I., Lukyanenko, L. M., Kozlova, N. M., Krylov, Andrey V., Kotova, Elena A., Antonenko, Yuri N., Yaroslavov, Alexander A., Ghosh, Subhendu, Bera, Amal K., Das, Sudipto, Urbánková, Eva, Freeman, Karl, Jelokhani-Niaraki, Masood, Jezek, Petr, Usmanov, P. B., Tonkikh, A. K., Ongarbaev, A., Pohl, Peter, Saparov, Sapar M., Harikumar, P., Reeves, J. P., Sikdar, S. K., Rao, S., Ghatpande, A. S., Corsso, C., Varanda, W. A., ElHamel, C., Dé, E., Molle, G., Saint, N., Varshney, Anurae, Mathew, M. K., Isacoff, E. Y., Loots, E., Kasai, Michiki, Yamaguchi, Naohiro, Ghosh, Paramita, Tigyi, Joseph, Miledi, Ricardo, Tigyi, Gabor, Liliom, Karoly, Djurisic, Maja R., Andjus, Pavle R., Shrivastava, Indira H., Sansom, M. S. P., Barrias, C., Oliveira, P. F., Lopes, I. A., Mauricio, A. C., Fedorovich, S. V., Konev, S. V., Sholukh, M. V., Chubanov, V. S., Klevets, M., Fedirko, N., Shvinka, N., Manko, V., Prabhananda, B. S., Kombrabail, Mamata H., Aravamudhan, S., Venegas-Cotero, Berenice, Blake, Ivan Ortega, Zhou, Han-qing, Hu, Xiao-jian, Zhang, Zhi-hong, Feng, Hang-fang, Cheng, Wei-ying, Zalyvsky, I. A., Dubitsky, L. O., Vovkanvch, L. S., Savio-Galimberti, E., Ponce-Homos, J. E., Bonazzola, P., Capurro, Claudia, Parisi, Mario, Toriano, Roxana, Thomas, David D., Ready, Laxma G., Jones, Larry R., Tashmukhamedov, B. A., Sagdullaev, B. T., Heitzmann, D., Bleich, M., Warth, R., Ferreira, H. G., Ferreira, K. T. G., Greger, R., Parola, Abraham H., Alfahel, Essa, Zagoory, Orna, Priel, Zvi, Hama-Inaba, H., Ohyama, H., Hayata, I., Choi, K., Haginoya, K., Mori, M., Wang, R., Yukawa, O., Nakajima, T., Joshi, Nanda B., Kannurpatti, Sridhar K., Sinha, Mau, Joshi, Preeti G., Bei, Ling, Hu, Tianhui, Shen, Xun, Knetsch, Menno L. W., Schäfers, Nicole, Sandblom, John, Galvanovskis, Juris, Kovacs, Eugenia, Dinu, Alexandra, Pologea-Moraru, Roxana, Sanghvi, S. H., Jazbinšek, V., Tronteli, Z., Thiel, G., Wübeller, G., Müller, W., Brumen, Milan, Fajmut, Leš, Marhl, Marko, Volotovski, I. D., Sokolovski, S. G., Knight, M. R., Chalyi, Alexander V., Vasilʼev, Alexei N., Sharma, P., Pant, H. C., Sharma, M., Amin, N. D., Albers, R. W., Steinbach, P. J., Barchir, J., Balasubramanyam, M., Gardner, J. P., Condrescu, M., Pilarczyk, Gotz, Greulich, K. O., Monajembashi, Shamci, El-Awadi, A. I., El-Refaei, F. M., Talaat, M. M., Ali, F. M., Zahradniková, Alexandra, Tahradník, Ivan, Pavelková, Jana, Zhorov, Boris S., Ananthanaravanan, Vettai S., Weiss, D. G., Martin, D., Gornik, E., Neu, E., Michailov, Ch. M., Welscher, U., Seidenbusch, W., Jellali, A., Pattnaik, B. R., Hicks, D., Dreyfus, H., Sahel, J., Picaud, S., Forster, V., Wang, Hong-Wei, Sui, Sen-fang, Luther, Pradeep K., Morris, Ed, Barry, John, Squire, John, Sundari, Sivakama C., Balasubramanian, D., Christlet, Hema Thanka T., Veluraia, K., Suresh, Xavier M., Laretta-Garde, V., Krilov, Dubravka, Herak, Janko N., Stojanović, Nataša, Ferrone, Frank A., Ivanova, Maria, Jasuja, Ravi, Mirchev, Rossen, Stopar, David, Wolfs, Cor J. A. M., Hemminga, Marcus A., Spruijt, Ruud B., Arcovito, G., De Spirito, M., Frank, Joachim, Heagle, Amy B., Grassucci, Robert, Penczek, Pawel, Agrawal, Rajendra K., Sharma, Manjuli R., Wagenknecht, Terence, Jeyakumar, Loice H., Fleischer, Sidney, Knupp, Carlo, Squire, John M., Ezra, Eric, Munro, Peter M. G., Kitazawa, Hidefumi, Ichihara, Koji, Itoh, Tomohiko J., Iguchi, Yusuke, Pifat, Greta, Kveder, Marina, Pečar, Slavko, Schara, Milan, Nair, Deepak, Singh, Kavita, Rao, Kanury V. S., Sundaravadivel, B., Jain, Deepti, Kaur, Kanwaljeet, Salunke, D. M., Goel, Manisha, Kovalenko, E. I., Semenkova, G. N., Cherenkevich, S. N., Loganathan, D., Lakshmanan, T., Sriram, D., Srinivasan, S., Lebrón, J. A., Bjorkman, P. J., Ramalingam, T. S., Singh, A. K., Gayatri, T. N., Bisch, Paulo M., Caffarena, Ernesto R., Grigera, Raul J., Fromherz, P., Kiessling, V., Suresh, C. G., Rao, K. N., Khan, M. I., Gaikwad, S. M., Elanthiraiyan, M., Kaliannan, P., Payne, J., Chadha, K., Ambrus, J. L., Nair, M. P. N., Nair, Madhavan P. N., Hewitt, R., Schwartz, S. A., Mahajan, S., Macherel, D., Bourguignon, J., Neuburger, M., Douce, R., Cohen-Addad, C., Faure, M., Ober, R., Sieker, L., Gurumurthy, D. S., Velmurugan, S., Lobo, Z., Phadke, Ratna S., Desai, Prashant, Alieva, D. R., Guseinova, I. M., Zulfugarov, I. S., Aliev, J. A., Ismayilov, M. A., Novruzova, S. N., Savchenko, T. V., Suleimanov, Yu. S., Bartošková, Hana, Nauš, Jan, Ilík, Petr, Kouřil, Roman, Vidyasagar, P. B., Thomas, Sarah, Gaikwad, Jvoti U., Cseh, Z., Mustárdy, L., Garab, G., Simidjiev, I., Rajagopal, S., Várkonyi, Zs., Holzenburg, A., Stoylova, S., Papp, E., Millar, D. P., Bruder, R., Woo, T. T., Genick, U. K., Gerwert, K., Jávorfí, Tamás, Garab, Győző, Naqvi, Razi K., Gaikwad, Jyoti, Kalimullah, Md., Semwal, Manoj, Naus, Man, Ilik, Petr, Kouril, Roman, Horváth, Gábor, Bernard, Gary D., Pomozi, István, Wehner, Rüdiger, Damjanović, Ana, Schulten, Klaus, Ritz, Thorsten, Yandao, Gong, Jushuo, Wang, Nanming, Zhao, Jixiu, Shan, Freiberg, Arvi, Timpmann, Kõu, Woodbury, Neal W., Ruus, Rein, Nemtseva, E. V., Kudryasheva, N. S., Sizykh, A. G., Tikhomirov, A. A., Nesterenko, T. V., Shikhov, V. N., Forti, Giorgio, Furia, Alberto, Finazzi, Giovanni, Barbagallo, Romina Paola, Agalarov, R., Gasanov, R., Iskenderova, S., Nobuhiro, G. O., Osamu, Miyashita, Ramrakhiani, M., Soni, R. K., Yoshida, Masasuke, Akutsu, Hideo, Yagi, Hiromasa, Tozawa, Kacko, Sekino, Nobuaki, Iwabuchi, Tomoyuki, Kaulen, A. D., Avetisyan, A. V., Feniouk, B. A., Skulachev, V. P., Breyton, Cécile, Kühlbrandt, Werner, Gräslund, Astrid, Assarsson, Maria, Libisch, B., Horváth, G., Gombos, Z., Budagovskaya, N. V., Kudryasheva, N., Fukunishi, Arima, Harada, Erisa, Fukuoka, Yuki, Ohmura, Tomoaki, Kawai, Gota, Watanabe, Kimitsuna, Žekš, Boštjan, Božič, Bojan, Derganc, Jure, Svetina, Saša, Hoh, J. F. Y., Li, Z. B., Rossmanith, G. H., Frederix, P. L. T. M., de Beer, E. L., Treijtel, B. W., Blangè, T., Galtet, F., Hénon, S., Isabey, D., Planus, E., Laurent, V., Rath, L. S., Raval, M. K., Dash, P. K., Ramakrishnan, C., Balaram, R., Basak, Kanika, Balaban, Alexandra T., Nandy, Ashesh, Grunwald, Gregory D., Vracko, Marjan, Randic, Milan, Basak, Subhash C., Amic, Dragan, Beslo, Drago, Trinajstic, Nenad, Nikolic, Sonja, Walahaw, J., Lensink, Marc F. J., Reddy, Boojala V. B., Shindylov, Ilya N., Bourne, Philip E., Grigera, J. R., de Xammar Oro, J., Donnamaria, M. C., Neagu, Monica, Neagu, Adrian, Janežič, Dušanka, Praprotnik, Matej, Nilsson, Lennart, Mark, Pekka, Fata, La L., Dardenne, Laurent E., Werneck, Araken S., Neto, Marçal de O., Kannan, N., Vishveshwara, S., Veluraja, K., Opitz, David, Balasubramanian, Krishnan, Gute, Brian D., Mills, Denise, Lungeanu, Diana, Mihalas, G. I., Macovievici, G., Gruia, Raluca, Dalcin, B., Cortez-Maghelly, C., Passos, E. P., Ljubisavljevic, M., Blesic, S., Milosevic, S., Stratimirovic, D. J., Bachhawat, Nandita, Mande, Shekhar C., Nandy, A., Nishigaki, Koichi, Saito, Ayumu, Naimuddin, Mohammed, Takaesu, Hirotomo, Ono, Mitsuo, Hirokawa, Takatsugu, Eissa, A. M., Ahmed, Abdalla S., El Gohary, M. I., Nakashima, Hiroshi, Raghava, G. P. S., Kurgalvuk, N., Goryn, O., Gerstman, Bernard S., Kratasyuk, V. A., Esimbekova, E. N., Gritsenko, E. V., Remmel, N. N., Maznyak, O. M., German, A., Tikhonov, A., Tchitchkan, D., Koulchitsky, S., Pashkevich, S., Pletnev, S., Kulchitsky, V., Pesotskaya, Y., Shapiro, Erik M., Borthakur, Arijitt, Dimitrov, Ivan, Leigh, John S., Rizi, Rahim, Reddy, Ravinder, Charagundla, Sridhar, Duvvuri, Umamaheswar, Degaonkar, M., Khubchandani, M., Kumar, Mahesh, Jagannathan, N R., Raghunathan, P., Jayasundar, Rama, Coshic, O., Rath, O. K., Julka, P. K., Iliescu, Karina Roxana, Sajin, Maria, Petcu, Ileana, Moisoi, Nicolcta, Kuzmenko, A. I., Donchenko, G. V., Nikolenko, I. A., Morozova, R. P., Rahman, M. K., Ahmed, M. M., Watanabe, Takehiro, Uretzky, G., Ammar, R., Sharony, R., Rubin, Y., Gilboa, H., Mallick, H. N., Kumar, Mohan V., Begum, Gulnaz M., Degaonkar, Mahaveer N., Govindasamy, S., Kumosani, T. A., Lupusoru, C., Titescu, G., Haulica, I., Stefanescu, I., Iliescu, R., Nastasa, V., Bild, W., Khetawat, Gopal, Nealen, M., Faraday, N., Bray, P. F., Noga, S., Lycholat, E. A., Ananieva, T. V., Kosevich, M V., Stepanyan, S. G., Antonyuk, S. V., Khachatryan, A., Kumar, A., Arakelian, H., Khachatryan, R., Agadjanyan, S., Ayrapetyan, S., Mkheyan, V., Rajan, S. S., Kabaleeswaran, V., Gopalakrishnan, Geetha, Govindachari, T. R., Ramrakhiani, Meera, Cullen, David C., Lowe, Phillip, Badley, Andrew, Hermel, H., Möhwald, H., Schmahl, W., Singh, Anil K., Das, Joydip, Majumdar, Nirmalya, Dér, András, Oroszi, László, Kelemen, Loránd, Ormos, Pál, Hámori, András, Ramsden, Jeremy J., Mitra, Chanchal K., Savitri, D., Yanagida, Toshio, Esaki, Seiji, Sowa, Yosiyuki, Nishida, Tomoyuki, Kimura, Yuji, Radu, M., Laukhina, E. E., Kasumova, L. A., Koltover, V. K., Bubnov, V. P., Estrin, Ya. I., Dotta, Rajiv, Zahradník, Ivan, Marko, Milan, Novák, Pavel, Miyata, Hidetake, Hirata, Hiroaki, Sengupta, P., Maiti, S., Balaji, J., Banerjee, S., Barker, A. L., Winlove, C. P., OʼHare, D., Macpherson, J. V., Gonsalves, M., Unwin, P. R., Phillip, R., Kumar, Ravindra G., Murata, K., Nagayaka, K., Danev, R., Sugitani, S., Gősch, Michael, Thyberg, P., Földes-Papp, Z., Björk, G., Blom, H., Holm, J., Heino, T., Inagaki, Fuyuhiko, Yokochi, Masashi, Kusunoki, Masami, Matthews, E. K., Pines, J., Chukova, Yu. P., Koltover, Vitaly K., Kang, B. P. S., Bansal, Geetanjali, Bansal, M. P., Singh, U., Singh, Uma, Nakata, Kotoko, Nakano, Tastuya, Kaminuma, Tsuguchika, Kirn, Bonn, Potocnik, Neja, Stare, Vito, Shukla, Latal, Sastry, M. D., Natarajan, V., Devasagayam, T. P. A., Kesavan, P. C., Sayfutdinov, R., Degermendzhy, A. G., Adamovich, V. V., Rogozin, Yu. D., Khetrapal, C. L., Gowda, G. A. Nagana, Ghimire, Kedar Nath, Masaru, Ishida, Fujita, H., Ishiwata, S., Suzuki, M., Kawahara, S., Kirino, Y., Kishimoto, Y., Mori, H., Mishina, M., Ohshima, H., Dukhin, A. S., Goetz, P. J., Shilov, V. N., and Mishra, R. K.

Published
1999
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23. Hydrogeological modeling and water resources management: Improving the link between data, prediction, and decision making

Author

Harken, B., Chang, C.-F., Dietrich, Peter, Kalbacher, Thomas, Rubin, Y., Harken, B., Chang, C.-F., Dietrich, Peter, Kalbacher, Thomas, and Rubin, Y.

Abstract

A risk‐based decision‐making mechanism capable of accounting for uncertainty regarding local conditions is crucial to water resources management, regulation, and policy making. Despite the great potential of hydrogeological models in supporting water resources decisions, challenges remain due to the many sources of uncertainty as well as making and communicating decisions mindful of this uncertainty. This paper presents a framework that utilizes statistical hypothesis testing and an integrated approach to the planning of site characterization, modeling prediction, and decision making. Benefits of this framework include aggregated uncertainty quantification and risk evaluation, simplified communication of risk between stakeholders, and improved defensibility of decisions. The framework acknowledges that obtaining absolute certainty in decision making is impossible; rather, the framework provides a systematic way to make decisions in light of uncertainty and determine the amount of information required. In this manner, quantitative evaluation of a field campaign design is possible before data are collected, beginning from any knowledge state, which can be updated as more information becomes available. We discuss the limitations of this approach by the types of uncertainty that can be recognized and make suggestions for addressing the rest. This paper presents the framework in general and then demonstrates its application in a synthetic case study. Results indicate that the effectiveness of field campaigns depends not only on the environmental performance metric being predicted but also on the threshold value in decision‐making processes. The findings also demonstrate that improved parameter estimation does not necessarily lead to better decision making, thus reemphasizing the need for goal‐oriented characterization.

Published
2019

24. Is Unique Scaling of Aquifer Macrodispersivity supported by Field Data?

Author

Zech, A., Attinger, S., Cvetkovic, V., Dagan, G., Dietrich, P., FIORI, ALDO, Rubin, Y., Teutsch, G., Zech A, Attinger S, Cvetkovic V, Dagan G, Dietrich P, Fiori A, Rubin Y, Teutsch, Zech, A, Attinger, S, Cvetkovic, V, Dagan, G, Dietrich, P, Fiori, Aldo, Rubin, Y, Teutsch, Zech, A., Attinger, S., Cvetkovic, V., Dagan, G., Dietrich, P., Rubin, Y., and Teutsch, G.

Published
2015

26. Analysis of Mixing in Corotating Twin Screw Extruders through Numerical Simulation

Author

Avalosse, T. and Rubin, Y.

Abstract

Mixing is a major ingredient in many industrial processes to obtain desired and uniform material properties. Nowadays, many materials, pigments, additives, gas or reactants, are mixed to create new products combining the characteristics of different raw materials to obtain specific product properties. The quality of the mixing, i.e. the uniformity of the mixture, is a key issue that will determine the morphology and the properties of the resulting compound [1, 2]. An insight in the physics of mixing is therefore necessary in order to achieve a good quality of mixing or maintain it when scaling equipment, for example.

Published
2022
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27. Mutual insurance of transport infrastructure construction risks as an inherent part of competitive environment

Author

Logvinova, I. L., Rubin, Y. B., and Sherstiuk, A. E.

Subjects
Investments -- Management, Infrastructure (Economics) -- Finance, Competition -- Russia, Infrastructure (Economics) -- Russia, Infrastructure (Economics) -- Evaluation, Financial risk management -- Russia, Insurance -- Finance, Transportation -- Finance -- Russia -- Evaluation
Abstract

In this article we introduce mutual insurance as an inherent part of competitive environment in the field of insurance of the transport infrastructure construction risks. The competitive environment makes a great impact on the market behavior of the actors. The monopolization creates the environment, which does not prevent the negative steps of the firm in different directions. The article shows, that mutual insurance is a significant factor which can prevent the monopolization of the insurance market. This is a specific factor that is inherent only to this kind of the market. The competitive advantages of the mutual insurance organizations, their attractiveness to the clients (the insured) are conditioned with the specific relations between the insured and the insurance organization, such as the decision of the main questions of the financial activity of the insurer on the meeting of all the insured or their representatives, the possibility to insure the risks, which the commercial insurers do not insure and some others., peer-reviewed

Published
2018

30. Stochastic hydrogeology's biggest hurdles analyzed and its big blind spot

Author

Rubin, Y., Chang, C.-F., Chen, J., Cucchi, K., Harken, B., Heße, Falk, Savoy, H., Rubin, Y., Chang, C.-F., Chen, J., Cucchi, K., Harken, B., Heße, Falk, and Savoy, H.

Abstract

This paper considers questions related to the adoption of stochastic methods in hydrogeology. It looks at factors affecting the adoption of stochastic methods including environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We begin by evaluating two previous paper series appearing in the stochastic hydrogeology literature, one in 2004 and one in 2016, and identifying the current thinking on the topic, including the perceived data needs of stochastic methods, the attitude in regulations and the court system regarding stochastic methods, education of the workforce, and the availability of software tools needed for implementing stochastic methods in practice. Comparing the state of adoption in hydrogeology to petroleum reservoir engineering allowed us to identify quantitative metrics on which to base our analysis. For impediments to the adoption of stochastic hydrology, we identified external factors as well as self-inflicted wounds. What emerges is a picture much broader than current views. Financial incentives and regulations play a major role in stalling adoption. Stochastic hydrology's blind spot is in confusing between uncertainty with risk and ignoring uncertainty. We show that stochastic hydrogeology comfortably focused on risk while ignoring uncertainty, to its own detriment and to the detriment of its potential clients. The imbalance between the treatment on risk on one hand and uncertainty on the other is shown to be common to multiple disciplines in hydrology that interface with risk and uncertainty.

Published
2018

31. Influence of hydrological perturbations and riverbed sediment characteristics on hyporheic zone respiration of CO2 and N2

Author

Newcomer, M.E., Hubbard, S.S., Fleckenstein, Jan, Maier, U., Schmidt, Christian, Thullner, Martin, Ulrich, C., Flipo, F., Rubin, Y., Newcomer, M.E., Hubbard, S.S., Fleckenstein, Jan, Maier, U., Schmidt, Christian, Thullner, Martin, Ulrich, C., Flipo, F., and Rubin, Y.

Abstract

Rivers in climatic zones characterized by dry and wet seasons often experience periodic transitions between losing and gaining conditions across the river‐aquifer continuum. Infiltration shifts can stimulate hyporheic microbial biomass growth and cycling of riverine carbon and nitrogen leading to major exports of biogenic CO2 and N2 to rivers. In this study, we develop and test a numerical model that simulates biological‐physical feedback in the hyporheic zone. We used the model to explore different initial conditions in terms of dissolved organic carbon availability, sediment characteristics, and stochastic variability in aerobic and anaerobic conditions from water table fluctuations. Our results show that while highly losing rivers have greater hyporheic CO2 and N2 production, gaining rivers allowed the greatest fraction of CO2 and N2 production to return to the river. Hyporheic aerobic respiration and denitrification contributed 0.1–2 g/m2/d of CO2 and 0.01–0.2 g/m2/d of N2; however, the suite of potential microbial behaviors varied greatly among sediment characteristics. We found that losing rivers that consistently lacked an exit pathway can store up to 100% of the entering C/N as subsurface biomass and dissolved gas. Our results demonstrate the importance of subsurface feedbacks whereby microbes and hydrology jointly control fate of C and N and are strongly linked to wet‐season control of initial sediment conditions and hydrologic control of seepage direction. These results provide a new understanding of hydrobiological and sediment‐based controls on hyporheic zone respiration, including a new explanation for the occurrence of anoxic microzones and large denitrification rates in gravelly riverbeds.

Published
2018

36. Geological heterogeneity: Goal-oriented simplification of structure and characterization needs

Author

Savoy, H., Kalbacher, Thomas, Dietrich, Peter, Rubin, Y., Savoy, H., Kalbacher, Thomas, Dietrich, Peter, and Rubin, Y.

Abstract

Geological heterogeneity, i.e. the spatial variability of discrete hydrogeological units, is investigated in an aquifer analog of glacio-fluvial sediments to determine how such a geological structure can be simplified for characterization needs. The aquifer analog consists of ten hydrofacies whereas the scarcity of measurements in typical field studies precludes such detailed spatial models of hydraulic properties. Of particular interest is the role of connectivity of the hydrofacies structure, along with its effect on the connectivity of mass transport, in site characterization for predicting early arrival times. Transport through three realizations of the aquifer analog is modeled with numerical particle tracking to ascertain the fast flow channel through which early arriving particles travel. Three simplification schemes of two-facies models are considered to represent the aquifer analogs, and the velocity within the fast flow channel is used to estimate the apparent hydraulic conductivity of the new facies. The facies models in which the discontinuous patches of high hydraulic conductivity are separated from the rest of the domain yield the closest match in early arrival times compared to the aquifer analog, but assuming a continuous high hydraulic conductivity channel connecting these patches yields underestimated early arrivals times within the range of variability between the realizations, which implies that the three simplification schemes could be advised but pose different implications for field measurement campaigns. Overall, the results suggest that the result of transport connectivity, i.e. early arrival times, within realistic geological heterogeneity can be conserved even when the underlying structural connectivity is modified.

Published
2017

37. anchoredDistr: a Package for the Bayesian inversion of geostatistical parameters with multi-type and multi-scale data

Author

Savoy, H., Heße, Falk, Rubin, Y., Savoy, H., Heße, Falk, and Rubin, Y.

Abstract

The Method of Anchored Distributions (MAD) is a method for Bayesian inversion designed for inferring both local (e.g. point values) and global properties (e.g. mean and variogram parameters) of spatially heterogenous fields using multi-type and multi-scale data. Software implementations of MAD exist in C++ and C# to import data, execute an ensemble of forward model simulations, and perform basic post-processing of calculating likelihood and posterior distributions for a given application. This article describes the R package anchoredDistr that has been built to provide an R based environment for this method. In particular, anchoredDistr provides a range of post-processing capabilities for MAD software by taking advantage of the statistical capabilities and wide use of the R language. Two examples from stochastic hydrogeology are provided to highlight the features of the package for MAD applications in inferring anchored distributions of local parameters (e.g. point values of transmissivity) as well as global parameters (e.g. the mean of the spatial random function for hydraulic conductivity).

Published
2017

42. Identifying the influential aquifer heterogeneity factor on nitrate reduction processes by numerical simulation

Author

Jang, Eunseon, He, Wenkui, Savoy, H., Dietrich, Peter, Kolditz, Olaf, Rubin, Y., Schüth, C., Kalbacher, Thomas, Jang, Eunseon, He, Wenkui, Savoy, H., Dietrich, Peter, Kolditz, Olaf, Rubin, Y., Schüth, C., and Kalbacher, Thomas

Abstract

Nitrate reduction reactions in groundwater systems are strongly influenced by various aquifer heterogeneity factors that affect the transport of chemical species, spatial distribution of redox reactive substances and, as a result, the overall nitrate reduction efficiency. In this study, we investigated the influence of physical and chemical aquifer heterogeneity, with a focus on nitrate transport and redox transformation processes. A numerical modeling study for simulating coupled hydrological-geochemical aquifer heterogeneity was conducted in order to improve our understanding of the influence of the aquifer heterogeneity on the nitrate reduction reactions and to identify the most influential aquifer heterogeneity factors throughout the simulation. Results show that the most influential aquifer heterogeneity factors could change over time. With abundant presence of electron donors in the high permeable zones (initial stage), physical aquifer heterogeneity significantly influences the nitrate reduction since it enables the preferential transport of nitrate to these zones and enhances mixing of reactive partners. Chemical aquifer heterogeneity plays a comparatively minor role. Increasing the spatial variability of the hydraulic conductivity also increases the nitrate removal efficiency of the system. However, ignoring chemical aquifer heterogeneity can lead to an underestimation of nitrate removals in long-term behavior. With the increase of the spatial variability of the electron donor, i.e. chemical heterogeneity, the number of the “hot spots” i.e. zones with comparably higher reactivity, should also increase. Hence, nitrate removal efficiencies will also be spatially variable but overall removal efficiency will be sustained if longer time scales are considered and nitrate fronts reach these high reactivity zones.

Published
2016

44. Simulating bioclogging effects on dynamic riverbed permeability and infiltration

Author

Newcomer, Michelle, Hubbard, S.S., Fleckenstein, Jan, Maier, Ulrich, Schmidt, Christian, Thullner, Martin, Ulrich, C., Flipo, N., Rubin, Y., Newcomer, Michelle, Hubbard, S.S., Fleckenstein, Jan, Maier, Ulrich, Schmidt, Christian, Thullner, Martin, Ulrich, C., Flipo, N., and Rubin, Y.

Abstract

Bioclogging in rivers can detrimentally impact aquifer recharge. This is particularly so in dry regions, where losing rivers are common, and where disconnection between surface water and groundwater (leading to the development of an unsaturated zone) can occur. Reduction in riverbed permeability due to biomass growth is a time-variable parameter that is often neglected, yet permeability reduction from bioclogging can introduce order of magnitude changes in seepage fluxes from rivers over short (i.e., monthly) timescales. To address the combined effects of bioclogging and disconnection on infiltration, we developed numerical representations of bioclogging processes within a one-dimensional, variably saturated flow model representing losing-connected and losing-disconnected rivers. We tested these formulations using a synthetic case study informed with biological data obtained from the Russian River, California, USA. Our findings show that modeled biomass growth reduced seepage for losing-connected and losing-disconnected rivers. However, for rivers undergoing disconnection, infiltration declines occurred only after the system was fully disconnected. Before full disconnection, biologically induced permeability declines were not significant enough to offset the infiltration gains introduced by disconnection. The two effects combine to lead to a characteristic infiltration curve where peak infiltration magnitude and timing is controlled by permeability declines relative to hydraulic gradient gains. Biomass growth was found to hasten the onset of full disconnection; a condition we term ‘effective disconnection’. Our results show that river infiltration can respond dynamically to bioclogging and subsequent permeability declines that are highly dependent on river connection status.

Published
2016

46. Characterizing the impact of roughness and connectivity features of aquifer conductivity using Bayesian inversion

Author

Heße, Falk, Savoy, H., Osorio-Murillo, C.A., Sege, J., Attinger, Sabine, Rubin, Y., Heße, Falk, Savoy, H., Osorio-Murillo, C.A., Sege, J., Attinger, Sabine, and Rubin, Y.

Abstract

The conductivity of an aquifer is usually difficult to represent in a precise manner due to having both a high degree of spatial variability combined with a scarcity of information. As a result, the conductivity is commonly modeled as a spatial random field, defined by its expected value and a covariance function. This covariance is usually parameterized by fitting a model function to experimental data derived from point measurements of the conductivity.In this study, we investigated the two features that are often difficult to discern when using such classic characterization schemes: roughness and connectivity. These two features both share the fact that, based on point measurements of the conductivity alone, they are difficult to discern. It therefore stands to reason that the use of additional data could alleviate this problem.To that end, we used the Method of Anchored Distributions (MAD), which is a novel Bayesian tool for the inverse characterization of spatial random fields. MAD is versatile with respect to the used data, it has a modular structure and it does not assume any formal relationship between the target variable, i.e. the log hydraulic conductivity, and the data used for the inversion process, e.g. head measurements, draw-down from pumping tests or breakthrough curves. With respect to the characterization of the aforementioned features, we investigated the impact of several factors, such as different data types on the characterization process.Our findings suggest that both roughness and connectivity have only a limited impact on flow predictions, suggesting that the choice of such features is of lesser relevance if one is mainly interested in flow simulations. In case of roughness, this limited sensitivity was also seen for transport predictions if the solute had already travelled some distance. Connectivity however, can be a decisive factor for such simulations

Published
2015

47. Is unique scaling of aquifer macrodispersivity supported by field data?

Author

Zech, Alraune, Attinger, Sabine, Cvetkovic, V., Dietrich, Peter, Fiori, A., Rubin, Y., Teutsch, Georg, Zech, Alraune, Attinger, Sabine, Cvetkovic, V., Dietrich, Peter, Fiori, A., Rubin, Y., and Teutsch, Georg

Abstract

Spreading of conservative solutes in groundwater due to aquifer heterogeneity is quantified by the macrodispersivity, which was found to be scale dependent. It increases with travel distance, stabilizing eventually at a constant value. However, the question of its asymptotic behavior at very large scale is still a matter of debate. It was surmised in the literature that macrodispersivity scales up following a unique scaling law. Attempts to define such a law were made by fitting a regression line in the log-log representation of an ensemble of macrodispersivities from multiple experiments. The functional relationships differ among the authors, based on the choice of data. Our study revisits the data basis, used for inferring unique scaling, through a detailed analysis of literature marcodispersivities. In addition, values were collected from the most recent tracer tests reported in the literature. We specified a system of criteria for reliability and reevaluated the reliability of the reported values. The final collection of reliable estimates of macrodispersivity does not support a unique scaling law relationship. On the contrary, our results indicate, that the field data can be explained as a collection of macrodispersivities of aquifers with varying degree of heterogeneity where each exhibits its own constant asymptotic value. Our investigation concludes that transport, and particularly the macrodispersivity, is formation-specific, and that modeling of transport cannot be relegated to a unique scaling law. Instead, transport requires characterization of aquifer properties, e.g., spatial distribution of hydraulic conductivity, and the use of adequate models.

Published
2015

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