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Showing 1 - 200 of 3089 Journals sorted alphabetically
A Practical Logic of Cognitive Systems     Full-text available via subscription   (Followers: 7)
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 25, SJR: 1.402, h-index: 51)
Academic Radiology     Hybrid Journal   (Followers: 22, SJR: 1.008, h-index: 75)
Accident Analysis & Prevention     Partially Free   (Followers: 86, SJR: 1.109, h-index: 94)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.612, h-index: 27)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 30, SJR: 2.515, h-index: 90)
Achievements in the Life Sciences     Open Access   (Followers: 4)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 5, SJR: 0.338, h-index: 19)
Acta Astronautica     Hybrid Journal   (Followers: 363, SJR: 0.726, h-index: 43)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Biomaterialia     Hybrid Journal   (Followers: 25, SJR: 2.02, h-index: 104)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 1)
Acta de Investigación Psicológica     Open Access   (Followers: 2)
Acta Ecologica Sinica     Open Access   (Followers: 8, SJR: 0.172, h-index: 29)
Acta Haematologica Polonica     Free   (SJR: 0.123, h-index: 8)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.604, h-index: 38)
Acta Materialia     Hybrid Journal   (Followers: 229, SJR: 3.683, h-index: 202)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.615, h-index: 21)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.442, h-index: 21)
Acta Oecologica     Hybrid Journal   (Followers: 10, SJR: 0.915, h-index: 53)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription   (Followers: 1)
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.311, h-index: 16)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1)
Acta Poética     Open Access   (Followers: 4)
Acta Psychologica     Hybrid Journal   (Followers: 24, SJR: 1.365, h-index: 73)
Acta Sociológica     Open Access  
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.059, h-index: 77)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 4)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 3)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 4, SJR: 0.383, h-index: 19)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 2)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 5, SJR: 0.141, h-index: 3)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 4, SJR: 0.112, h-index: 2)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 4)
Acute Pain     Full-text available via subscription   (Followers: 13)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.967, h-index: 57)
Addictive Behaviors     Hybrid Journal   (Followers: 15, SJR: 1.514, h-index: 92)
Addictive Behaviors Reports     Open Access   (Followers: 6)
Additive Manufacturing     Hybrid Journal   (Followers: 7, SJR: 1.039, h-index: 5)
Additives for Polymers     Full-text available via subscription   (Followers: 21)
Advanced Cement Based Materials     Full-text available via subscription   (Followers: 3)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 133, SJR: 5.2, h-index: 222)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.265, h-index: 53)
Advanced Powder Technology     Hybrid Journal   (Followers: 17, SJR: 0.739, h-index: 33)
Advances in Accounting     Hybrid Journal   (Followers: 9, SJR: 0.299, h-index: 15)
Advances in Agronomy     Full-text available via subscription   (Followers: 15, SJR: 2.071, h-index: 82)
Advances in Anesthesia     Full-text available via subscription   (Followers: 26, SJR: 0.169, h-index: 4)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 3)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 6, SJR: 1.054, h-index: 35)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 0.801, h-index: 26)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 22, SJR: 1.286, h-index: 49)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 16, SJR: 3.31, h-index: 42)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.277, h-index: 43)
Advances in Botanical Research     Full-text available via subscription   (Followers: 3, SJR: 0.619, h-index: 48)
Advances in Cancer Research     Full-text available via subscription   (Followers: 25, SJR: 2.215, h-index: 78)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 0.9, h-index: 30)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 2.139, h-index: 42)
Advances in Cell Aging and Gerontology     Full-text available via subscription   (Followers: 4)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 12)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 27, SJR: 0.183, h-index: 23)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.665, h-index: 29)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 9, SJR: 1.268, h-index: 45)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 29, SJR: 0.938, h-index: 33)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 18, SJR: 2.314, h-index: 130)
Advances in Computers     Full-text available via subscription   (Followers: 16, SJR: 0.223, h-index: 22)
Advances in Dermatology     Full-text available via subscription   (Followers: 12)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 7)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 22)
Advances in Ecological Research     Full-text available via subscription   (Followers: 45, SJR: 3.25, h-index: 43)
Advances in Engineering Software     Hybrid Journal   (Followers: 26, SJR: 0.486, h-index: 10)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 43, SJR: 5.465, h-index: 64)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 3)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 8)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 51, SJR: 0.674, h-index: 38)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 15, SJR: 2.558, h-index: 54)
Advances in Genome Biology     Full-text available via subscription   (Followers: 11)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 2.325, h-index: 20)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22, SJR: 0.906, h-index: 24)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 0.497, h-index: 31)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 26)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.396, h-index: 27)
Advances in Immunology     Full-text available via subscription   (Followers: 36, SJR: 4.152, h-index: 85)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 1.132, h-index: 42)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 3, SJR: 1.274, h-index: 27)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 6)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 4)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.764, h-index: 15)
Advances in Lipobiology     Full-text available via subscription   (Followers: 2)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Marine Biology     Full-text available via subscription   (Followers: 16, SJR: 1.645, h-index: 45)
Advances in Mathematics     Full-text available via subscription   (Followers: 10, SJR: 3.261, h-index: 65)
Advances in Medical Sciences     Hybrid Journal   (Followers: 6, SJR: 0.489, h-index: 25)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.44, h-index: 51)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 22)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 10)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 8, SJR: 0.324, h-index: 8)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 4)
Advances in Oncobiology     Full-text available via subscription   (Followers: 3)
Advances in Organ Biology     Full-text available via subscription   (Followers: 2)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 15, SJR: 2.885, h-index: 45)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.148, h-index: 11)
Advances in Parasitology     Full-text available via subscription   (Followers: 7, SJR: 2.37, h-index: 73)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.4, h-index: 28)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 13)
Advances in Pharmacology     Full-text available via subscription   (Followers: 15, SJR: 1.718, h-index: 58)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.384, h-index: 26)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.248, h-index: 11)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 8)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 17)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 1.5, h-index: 62)
Advances in Psychology     Full-text available via subscription   (Followers: 62)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 5, SJR: 0.478, h-index: 32)
Advances in Radiation Oncology     Open Access  
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 2, SJR: 0.1, h-index: 2)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 5)
Advances in Space Research     Full-text available via subscription   (Followers: 361, SJR: 0.606, h-index: 65)
Advances in Structural Biology     Full-text available via subscription   (Followers: 8)
Advances in Surgery     Full-text available via subscription   (Followers: 7, SJR: 0.823, h-index: 27)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 30, SJR: 1.321, h-index: 56)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 16)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 1.878, h-index: 68)
Advances in Water Resources     Hybrid Journal   (Followers: 44, SJR: 2.408, h-index: 94)
Aeolian Research     Hybrid Journal   (Followers: 5, SJR: 0.973, h-index: 22)
Aerospace Science and Technology     Hybrid Journal   (Followers: 331, SJR: 0.816, h-index: 49)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.318, h-index: 36)
African J. of Emergency Medicine     Open Access   (Followers: 5, SJR: 0.344, h-index: 6)
Ageing Research Reviews     Hybrid Journal   (Followers: 8, SJR: 3.289, h-index: 78)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 417, SJR: 1.385, h-index: 72)
Agri Gene     Hybrid Journal  
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 16, SJR: 2.18, h-index: 116)
Agricultural Systems     Hybrid Journal   (Followers: 30, SJR: 1.275, h-index: 74)
Agricultural Water Management     Hybrid Journal   (Followers: 40, SJR: 1.546, h-index: 79)
Agriculture and Agricultural Science Procedia     Open Access  
Agriculture and Natural Resources     Open Access   (Followers: 2)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 55, SJR: 1.879, h-index: 120)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.434, h-index: 14)
Air Medical J.     Hybrid Journal   (Followers: 5, SJR: 0.234, h-index: 18)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.285, h-index: 3)
Alcohol     Hybrid Journal   (Followers: 11, SJR: 0.922, h-index: 66)
Alcoholism and Drug Addiction     Open Access   (Followers: 8)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.436, h-index: 12)
Alexandria J. of Medicine     Open Access   (Followers: 1)
Algal Research     Partially Free   (Followers: 8, SJR: 2.05, h-index: 20)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 3)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.46, h-index: 29)
Allergology Intl.     Open Access   (Followers: 4, SJR: 0.776, h-index: 35)
Alpha Omegan     Full-text available via subscription   (SJR: 0.121, h-index: 9)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 9, SJR: 0.158, h-index: 9)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 46, SJR: 4.289, h-index: 64)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 5)
American Heart J.     Hybrid Journal   (Followers: 49, SJR: 3.157, h-index: 153)
American J. of Cardiology     Hybrid Journal   (Followers: 48, SJR: 2.063, h-index: 186)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 40, SJR: 0.574, h-index: 65)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 9, SJR: 1.091, h-index: 45)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.653, h-index: 93)
American J. of Human Genetics     Hybrid Journal   (Followers: 32, SJR: 8.769, h-index: 256)
American J. of Infection Control     Hybrid Journal   (Followers: 26, SJR: 1.259, h-index: 81)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 32, SJR: 2.313, h-index: 172)
American J. of Medicine     Hybrid Journal   (Followers: 46, SJR: 2.023, h-index: 189)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 199, SJR: 2.255, h-index: 171)
American J. of Ophthalmology     Hybrid Journal   (Followers: 59, SJR: 2.803, h-index: 148)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 6)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.249, h-index: 88)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, h-index: 45)
American J. of Pathology     Hybrid Journal   (Followers: 27, SJR: 2.653, h-index: 228)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 25, SJR: 2.764, h-index: 154)
American J. of Surgery     Hybrid Journal   (Followers: 35, SJR: 1.286, h-index: 125)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.653, h-index: 70)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 6)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.066, h-index: 51)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 58, SJR: 0.124, h-index: 9)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 12)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 2, SJR: 0.209, h-index: 27)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription   (SJR: 0.104, h-index: 3)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4, SJR: 2.577, h-index: 7)
Analytica Chimica Acta     Hybrid Journal   (Followers: 37, SJR: 1.548, h-index: 152)
Analytical Biochemistry     Hybrid Journal   (Followers: 167, SJR: 0.725, h-index: 154)
Analytical Chemistry Research     Open Access   (Followers: 8, SJR: 0.18, h-index: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 12)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 1)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 22, SJR: 0.421, h-index: 40)
Angiología     Full-text available via subscription   (SJR: 0.124, h-index: 9)
Angiologia e Cirurgia Vascular     Open Access  

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Journal Cover Advances in Water Resources
  [SJR: 2.408]   [H-I: 94]   [44 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0309-1708
   Published by Elsevier Homepage  [3049 journals]
  • Release of Escherichia coli under raindrop impact: The role of clay
    • Authors: C. Wang; J.-Y. Parlange; R.L. Schneider; E.W. Rasmussen; X. Wang; M. Chen; H.E. Dahlke; A.M. Truhlar; M.T. Walter
      Pages: 1 - 5
      Abstract: Publication date: January 2018
      Source:Advances in Water Resources, Volume 111
      Author(s): C. Wang, J.-Y. Parlange, R.L. Schneider, E.W. Rasmussen, X. Wang, M. Chen, H.E. Dahlke, A.M. Truhlar, M.T. Walter
      A recent paper by Wang et al. (2017) showed that the release of Escherichia coli (E. coli) from soil into overland flow under raindrop impact and the release of clay follow identical temporal patterns. This raised the question: what is the role of clay, if any, in E. coli transfer from soil to overland flow, e.g., does clay facilitate E. coli transfer' Using simulated rainfall experiments over soil columns with and without clay in the matrix, we found there was significantly more E. coli released from the non-clay soil because raindrops penetrated more deeply than into the soil with clay.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.028
      Issue No: Vol. 111 (2017)
  • Modeling non-Fickian pollutant mixing in open channel flows using
           two-dimensional particle dispersion model
    • Authors: Inhwan Park; Il Won Seo
      Pages: 105 - 120
      Abstract: Publication date: January 2018
      Source:Advances in Water Resources, Volume 111
      Author(s): Inhwan Park, Il Won Seo
      The non-Fickian particle dispersion model was developed in this study to model two-dimensional pollutant mixing in open channel flows. The proposed model represents shear dispersion using step-by-step arithmetic calculations, which consist of horizontal transport and vertical mixing steps, instead of using Fick's law. In the sequential calculations, the model directly applied the effect of vertical variations of both longitudinal and transverse velocities, whereas the Fickian dispersion model incorporates the effect of shear flow in the dispersion coefficients. Furthermore, in order to avoid the numerical diffusion errors induced by the grid tracking method of previously developed non-Fickian dispersion models, this model adopted the particle tracking technique to trace each particle. The simulation results in the straight channel show that the proposed model reproduced the anomalous mixing, which shows a non-linear increase of variance with time and large skewness coefficient in the initial period. However, in the Taylor period, the variance and skewness of the concentration curves approached the Fickian mixing. The simulation results in the meandering channel reveal that the proposed model adequately reproduced the skewed concentration–time curves of the experimental results whereas the Fickian dispersion model, CTM-2D, generated symmetrical curves. Further comparison between the simulation results and the tracer test results conducted in the Hongcheon River shows that the proposed model properly demonstrated the two-dimensional mixing without adopting Fick's law.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.035
      Issue No: Vol. 111 (2017)
  • Analytical analysis of the temporal asymmetry between seawater intrusion
           and retreat
    • Authors: Saubhagya Singh Rathore; Yue Zhao; Chunhui Lu; Jian Luo
      Pages: 121 - 131
      Abstract: Publication date: January 2018
      Source:Advances in Water Resources, Volume 111
      Author(s): Saubhagya Singh Rathore, Yue Zhao, Chunhui Lu, Jian Luo
      The quantification of timescales associated with the movement of the seawater-freshwater interface is useful for developing effective management strategies for controlling seawater intrusion (SWI). In this study, for the first time, we derive an explicit analytical solution for the timescales of SWI and seawater retreat (SWR) in a confined, homogeneous coastal aquifer system under the quasi-steady assumption, based on a classical sharp-interface solution for approximating freshwater outflow rates into the sea. The flow continuity and hydrostatic equilibrium across the interface are identified as two primary mechanisms governing timescales of the interface movement driven by an abrupt change in discharge rates or hydraulic heads at the inland boundary. Through theoretical analysis, we quantified the dependence of interface-movement timescales on porosity, hydraulic conductivity, aquifer thickness, aquifer length, density ratio, and boundary conditions. Predictions from the analytical solution closely agreed with those from numerical simulations. In addition, we define a temporal asymmetry index (the ratio of the SWI timescale to the SWR timescale) to represent the resilience of the coastal aquifer in response to SWI. The developed analytical solutions provide a simple tool for the quick assessment of SWI and SWR timescales and reveal that the temporal asymmetry between SWI and SWR mainly relies on the initial and final values of the freshwater flux at the inland boundary, and is weakly affected by aquifer parameters. Furthermore, we theoretically examined the log-linearity relationship between the timescale and the freshwater flux at the inland boundary, and found that the relationship may be approximated by two linear functions with a slope of -2 and -1 for large changes at the boundary flux for SWI and SWR, respectively.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.001
      Issue No: Vol. 111 (2017)
  • Untenable nonstationarity: An assessment of the fitness for purpose of
           trend tests in hydrology
    • Authors: Francesco Serinaldi; Chris G. Kilsby; Federico Lombardo
      Pages: 132 - 155
      Abstract: Publication date: January 2018
      Source:Advances in Water Resources, Volume 111
      Author(s): Francesco Serinaldi, Chris G. Kilsby, Federico Lombardo
      The detection and attribution of long-term patterns in hydrological time series have been important research topics for decades. A significant portion of the literature regards such patterns as ‘deterministic components’ or ‘trends’ even though the complexity of hydrological systems does not allow easy deterministic explanations and attributions. Consequently, trend estimation techniques have been developed to make and justify statements about tendencies in the historical data, which are often used to predict future events. Testing trend hypothesis on observed time series is widespread in the hydro-meteorological literature mainly due to the interest in detecting consequences of human activities on the hydrological cycle. This analysis usually relies on the application of some null hypothesis significance tests (NHSTs) for slowly-varying and/or abrupt changes, such as Mann-Kendall, Pettitt, or similar, to summary statistics of hydrological time series (e.g., annual averages, maxima, minima, etc.). However, the reliability of this application has seldom been explored in detail. This paper discusses misuse, misinterpretation, and logical flaws of NHST for trends in the analysis of hydrological data from three different points of view: historic-logical, semantic-epistemological, and practical. Based on a review of NHST rationale, and basic statistical definitions of stationarity, nonstationarity, and ergodicity, we show that even if the empirical estimation of trends in hydrological time series is always feasible from a numerical point of view, it is uninformative and does not allow the inference of nonstationarity without assuming a priori additional information on the underlying stochastic process, according to deductive reasoning. This prevents the use of trend NHST outcomes to support nonstationary frequency analysis and modeling. We also show that the correlation structures characterizing hydrological time series might easily be underestimated, further compromising the attempt to draw conclusions about trends spanning the period of records. Moreover, even though adjusting procedures accounting for correlation have been developed, some of them are insufficient or are applied only to some tests, while some others are theoretically flawed but still widely applied. In particular, using 250 unimpacted stream flow time series across the conterminous United States (CONUS), we show that the test results can dramatically change if the sequences of annual values are reproduced starting from daily stream flow records, whose larger sizes enable a more reliable assessment of the correlation structures.

      PubDate: 2017-11-18T18:09:00Z
      DOI: 10.1016/j.advwatres.2017.10.015
      Issue No: Vol. 111 (2017)
  • A comparison of discrete versus continuous adjoint states to invert
           groundwater flow in heterogeneous dual porosity systems
    • Authors: Frederick Delay; Hamid Badri; Marwan Fahs; Philippe Ackerer
      Pages: 1 - 18
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Frederick Delay, Hamid Badri, Marwan Fahs, Philippe Ackerer
      Dual porosity models become increasingly used for simulating groundwater flow at the large scale in fractured porous media. In this context, model inversions with the aim of retrieving the system heterogeneity are frequently faced with huge parameterizations for which descent methods of inversion with the assistance of adjoint state calculations are well suited. We compare the performance of discrete and continuous forms of adjoint states associated with the flow equations in a dual porosity system. The discrete form inherits from previous works by some of the authors, as the continuous form is completely new and here fully differentiated for handling all types of model parameters. Adjoint states assist descent methods by calculating the gradient components of the objective function, these being a key to good convergence of inverse solutions. Our comparison on the basis of synthetic exercises show that both discrete and continuous adjoint states can provide very similar solutions close to reference. For highly heterogeneous systems, the calculation grid of the continuous form cannot be too coarse, otherwise the method may show lack of convergence. This notwithstanding, the continuous adjoint state is the most versatile form as its non-intrusive character allows for plugging an inversion toolbox quasi-independent from the code employed for solving the forward problem.

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.09.022
      Issue No: Vol. 110 (2017)
  • Dendrohydrogeology in paleohydrogeologic studies
    • Authors: V. Gholami; J. Torkaman; M.R. Khaleghi
      Pages: 19 - 28
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): V. Gholami, J. Torkaman, M.R. Khaleghi
      Dendrohydrogeology can be used to simulate historical groundwater depth, water table drawdown, groundwater recharge and piezometric lines. We simulated paleohydrogeologic conditions via tree-rings and vessel chronologies using an artificial neural network (ANN) in the alluvial aquifer of the Caspian southern coast of Iran during the past century. Tree-ring width, vessel features, secondary piezometric well data, and precipitation from different sites within the study area were evaluated. After cross-dating, standardization and time series analysis, the relationships between tree-rings and vessel chronologies with groundwater depth were defined and simulated. Additionally, paleohydrogeologic records during the past century were simulated. The results generally demonstrate that tree-ring width is a better index than vessel features. However, we obtained the most exact groundwater depth modeling results by using the combination of tree-rings and earlywood vessel diameter from periods of low precipitation and groundwater fluctuations and significant temperature fluctuations. We also found that dendrohydrogeology has more applicability in groundwater modeling in areas where groundwater depth fluctuates 10–20 m below ground surface (based on root depth and water access). Moreover, using the simulated groundwater depths, piezometric lines in 1927 and 2000 (the years with maximum natural recharge and maximum drawdown respectively) were extracted using an interpolation technique and Geographic Information System (GIS). Finally, we suggest applying dendrohydrogeology for paleohydrogeologic modeling in alluvial aquifers.

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.10.004
      Issue No: Vol. 110 (2017)
  • Vortex-induced suspension of sediment in the surf zone
    • Authors: Junichi Otsuka; Ayumi Saruwatari; Yasunori Watanabe
      Pages: 59 - 76
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Junichi Otsuka, Ayumi Saruwatari, Yasunori Watanabe
      A major mechanism of sediment suspension by organized vortices produced under violent breaking waves in the surf zone was identified through physical and computational experiments. Counter-rotating flows within obliquely descending eddies produced between adjacent primary roller vortices induce transverse convergent near-bed flows, driving bed load transport to form regular patterns of transverse depositions. The deposited sediment is then rapidly ejected by upward carrier flows induced between the vortices. This mechanism of vortex-induced suspension is supported by experimental evidence that coherent sediment clouds are ejected where the obliquely descending eddies reach the sea bed after the breaking wave front has passed. In addition to the effects of settling and turbulent diffusion caused by breaking waves, the effect of the vortex-induced flows was incorporated into a suspension model on the basis of vorticity dynamics and parametric characteristics of transverse flows in breaking waves. The model proposed here reasonably predicts an exponential attenuation of the measured sediment concentration due to violent plunging waves and significantly improves the underprediction of the concentration produced by previous models.

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.08.021
      Issue No: Vol. 110 (2017)
  • Multi-parametric variational data assimilation for hydrological
    • Authors: R. Alvarado-Montero; D. Schwanenberg; P. Krahe; P. Helmke; B. Klein
      Pages: 182 - 192
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): R. Alvarado-Montero, D. Schwanenberg, P. Krahe, P. Helmke, B. Klein
      Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

      PubDate: 2017-10-29T11:41:33Z
      DOI: 10.1016/j.advwatres.2017.09.026
      Issue No: Vol. 110 (2017)
  • Design and development of bio-inspired framework for reservoir operation
    • Authors: M. Sakthi Asvini; T. Amudha
      Pages: 193 - 202
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): M. Sakthi Asvini, T. Amudha
      Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as “strawberry optimization” and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

      PubDate: 2017-10-29T11:41:33Z
      DOI: 10.1016/j.advwatres.2017.10.007
      Issue No: Vol. 110 (2017)
  • A comparison of methods to estimate future sub-daily design rainfall
    • Authors: J. Li; F. Johnson; J. Evans; A. Sharma
      Pages: 215 - 227
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): J. Li, F. Johnson, J. Evans, A. Sharma
      Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.020
      Issue No: Vol. 110 (2017)
  • The environmental cost of a reference withdrawal from surface waters:
           Definition and geography
    • Authors: Irene Soligno; Luca Ridolfi; Francesco Laio
      Pages: 228 - 237
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Irene Soligno, Luca Ridolfi, Francesco Laio
      World freshwater ecosystems are significantly deteriorating at a faster rate than other ecosystems. Water withdrawals are recognized as one of the main drivers of growing water stress in river basins worldwide. Over the years, much effort has been devoted to quantify water withdrawals at a global scale; however, comparisons are not simple because the uneven spatiotemporal distribution of surface water resources entails that the same amount of consumed water does not have the same environmental cost in different times or places. In order to account for this spatiotemporal heterogeneity, this work proposes a novel index to assess the environmental cost of a withdrawal from a generic river section. The index depends on (i) the environmental relevance of the impacted fluvial ecosystem (e.g., bed-load transport capacity, width of the riparian belt, biodiversity richness) and (ii) the downstream river network affected by the water withdrawal. The environmental cost has been estimated in each and every river section worldwide considering a reference withdrawal. Being referred to a unitary reference withdrawal that can occur in any river section worldwide, our results can be suitably arranged for describing any scenario of surface water consumption (i.e., as the superposition of the actual pattern of withdrawals). The index aims to support the interpretation of the volumetric measure of surface water withdrawal with a perspective that takes into account the fluvial system where the withdrawal actually occurs. The application of the index highlights the river regions where withdrawals can cause higher environmental costs, with the challenge of weighting each water withdrawal considering the responsibilities that it has on downstream freshwater ecosystems.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.016
      Issue No: Vol. 110 (2017)
  • Spatiotemporal monitoring of soil water content profiles in an irrigated
           field using probabilistic inversion of time-lapse EMI data
    • Authors: Davood Moghadas; Khan Zaib Jadoon; Matthew F. McCabe
      Pages: 238 - 248
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Davood Moghadas, Khan Zaib Jadoon, Matthew F. McCabe
      Monitoring spatiotemporal variations of soil water content (θ) is important across a range of research fields, including agricultural engineering, hydrology, meteorology and climatology. Low frequency electromagnetic induction (EMI) systems have proven to be useful tools in mapping soil apparent electrical conductivity (σa ) and soil moisture. However, obtaining depth profile water content is an area that has not been fully explored using EMI. To examine this, we performed time-lapse EMI measurements using a CMD mini-Explorer sensor along a 10 m transect of a maize field over a 6 day period. Reference data were measured at the end of the profile via an excavated pit using 5TE capacitance sensors. In order to derive a time-lapse, depth-specific subsurface image of electrical conductivity (σ), we applied a probabilistic sampling approach, DREAM ( Z S ) , on the measured EMI data. The inversely estimated σ values were subsequently converted to θ using the Rhoades et al. (1976) petrophysical relationship. The uncertainties in measured σa , as well as inaccuracies in the inverted data, introduced some discrepancies between estimated σ and reference values in time and space. Moreover, the disparity between the measurement footprints of the 5TE and CMD Mini-Explorer sensors also led to differences. The obtained θ permitted an accurate monitoring of the spatiotemporal distribution and variation of soil water content due to root water uptake and evaporation. The proposed EMI measurement and modeling technique also allowed for detecting temporal root zone soil moisture variations. The time-lapse θ monitoring approach developed using DREAM ( Z S ) thus appears to be a useful technique to understand spatiotemporal patterns of soil water content and provide insights into linked soil moisture vegetation processes and the dynamics of soil moisture/infiltration processes.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.019
      Issue No: Vol. 110 (2017)
  • Classification and prediction of river network ephemerality and its
           relevance for waterborne disease epidemiology
    • Authors: Javier Perez-Saez; Theophile Mande; Joshua Larsen; Natalie Ceperley; Andrea Rinaldo
      Pages: 263 - 278
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Javier Perez-Saez, Theophile Mande, Joshua Larsen, Natalie Ceperley, Andrea Rinaldo
      The transmission of waterborne diseases hinges on the interactions between hydrology and ecology of hosts, vectors and parasites, with the long-term absence of water constituting a strict lower bound. However, the link between spatio-temporal patterns of hydrological ephemerality and waterborne disease transmission is poorly understood and difficult to account for. The use of limited biophysical and hydroclimate information from otherwise data scarce regions is therefore needed to characterize, classify, and predict river network ephemerality in a spatially explicit framework. Here, we develop a novel large-scale ephemerality classification and prediction methodology based on monthly discharge data, water and energy availability, and remote-sensing measures of vegetation, that is relevant to epidemiology, and maintains a mechanistic link to catchment hydrologic processes. Specifically, with reference to the context of Burkina Faso in sub-Saharan Africa, we extract a relevant set of catchment covariates that include the aridity index, annual runoff estimation using the Budyko framework, and hysteretical relations between precipitation and vegetation. Five ephemerality classes, from permanent to strongly ephemeral, are defined from the duration of 0-flow periods that also accounts for the sensitivity of river discharge to the long-lasting drought of the 70’s-80’s in West Africa. Using such classes, a gradient-boosted tree-based prediction yielded three distinct geographic regions of ephemerality. Importantly, we observe a strong epidemiological association between our predictions of hydrologic ephemerality and the known spatial patterns of schistosomiasis, an endemic parasitic waterborne disease in which infection occurs with human-water contact, and requires aquatic snails as an intermediate host. The general nature of our approach and its relevance for predicting the hydrologic controls on schistosomiasis occurrence provides a pathway for the explicit inclusion of hydrologic drivers within epidemiological models of waterborne disease transmission.
      Graphical abstract image

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.003
      Issue No: Vol. 110 (2017)
  • Improved methods for estimating local terrestrial water dynamics from
           GRACE in the Northern High Plains
    • Authors: Wondwosen M. Seyoum; Adam M. Milewski
      Pages: 279 - 290
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Wondwosen M. Seyoum, Adam M. Milewski
      Investigating terrestrial water cycle dynamics is vital for understanding the recent climatic variability and human impacts in the hydrologic cycle. In this study, a downscaling approach was developed and tested, to improve the applicability of terrestrial water storage (TWS) anomaly data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission for understanding local terrestrial water cycle dynamics in the Northern High Plains region. A non-parametric, artificial neural network (ANN)–based model, was utilized to downscale GRACE data by integrating it with hydrological variables (e.g. soil moisture) derived from satellite and land surface model data. The downscaling model, constructed through calibration and sensitivity analysis, was used to estimate TWS anomaly for watersheds ranging from 5000 to 20,000 km2 in the study area. The downscaled water storage anomaly data were evaluated using water storage data derived from an (1) integrated hydrologic model, (2) land surface model (e.g. Noah), and (3) storage anomalies calculated from in-situ groundwater level measurements. Results demonstrate the ANN predicts monthly TWS anomaly within the uncertainty (conservative error estimate = 34 mm) for most of the watersheds. Seasonal derived groundwater storage anomaly (GWSA) from the ANN correlated well (r = ∼0.85) with GWSAs calculated from in-situ groundwater level measurements for a watershed size as small as 6000 km2. ANN downscaled TWSA matches closely with Noah-based TWSA compared to standard GRACE extracted TWSA at a local scale. Moreover, the ANN-downscaled change in TWS replicated the water storage variability resulting from the combined effect of climatic and human impacts (e.g. abstraction). The implications of utilizing finer resolution GRACE data for improving local and regional water resources management decisions and applications are clear, particularly in areas lacking in-situ hydrologic monitoring networks.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.021
      Issue No: Vol. 110 (2017)
  • Inherent relevance of MRMT models to concentration variance and
           mixing-induced reactivity
    • Authors: Tristan Babey; Jean-Raynald de Dreuzy; Alain Rapaport; Alejandro Rojas-Palma
      Pages: 291 - 298
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Tristan Babey, Jean-Raynald de Dreuzy, Alain Rapaport, Alejandro Rojas-Palma
      Several anomalous transport approaches have been developed to model the interaction between fast advectively-dominated transport in well-connected porosity and fracture structures and slow diffusively-dominated transport in poorly-connected or low-permeability ones. Among them, the Multi-Rate Mass Transfer approach (MRMT) represents the anomalous dispersion along the main flow paths (mobile zone) induced by a large distribution of first-order exchanges with immobile zones. Even though MRMTs have been developed for conservative transport processes in the mobile zone, we demonstrate that they also conserve the variance of the concentration distribution in the immobile zones, and, hence, pertain to mixing induced reactivity. This property is established whatever the organization of the immobile zones and whatever the injection and sampling conditions in the mobile zone. It inherently derives from the symmetry properties of the diffusion operator in the immobile zones, but cannot be directly extended to heterogeneous dispersive processes in the mobile zone.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.09.024
      Issue No: Vol. 110 (2017)
  • Multivariate missing data in hydrology – Review and applications
    • Authors: Mohamed-Aymen Ben Aissia; Fateh Chebana; Taha B.M.J. Ouarda
      Pages: 299 - 309
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Mohamed-Aymen Ben Aissia, Fateh Chebana, Taha B.M.J. Ouarda
      Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.002
      Issue No: Vol. 110 (2017)
  • Optimal estimation and scheduling in aquifer management using the rapid
           feedback control method
    • Authors: Hojat Ghorbanidehno; Amalia Kokkinaki; Peter K. Kitanidis; Eric Darve
      Pages: 310 - 318
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Hojat Ghorbanidehno, Amalia Kokkinaki, Peter K. Kitanidis, Eric Darve
      Management of water resources systems often involves a large number of parameters, as in the case of large, spatially heterogeneous aquifers, and a large number of “noisy” observations, as in the case of pressure observation in wells. Optimizing the operation of such systems requires both searching among many possible solutions and utilizing new information as it becomes available. However, the computational cost of this task increases rapidly with the size of the problem to the extent that textbook optimization methods are practically impossible to apply. In this paper, we present a new computationally efficient technique as a practical alternative for optimally operating large-scale dynamical systems. The proposed method, which we term Rapid Feedback Controller (RFC), provides a practical approach for combined monitoring, parameter estimation, uncertainty quantification, and optimal control for linear and nonlinear systems with a quadratic cost function. For illustration, we consider the case of a weakly nonlinear uncertain dynamical system with a quadratic objective function, specifically a two-dimensional heterogeneous aquifer management problem. To validate our method, we compare our results with the linear quadratic Gaussian (LQG) method, which is the basic approach for feedback control. We show that the computational cost of the RFC scales only linearly with the number of unknowns, a great improvement compared to the basic LQG control with a computational cost that scales quadratically. We demonstrate that the RFC method can obtain the optimal control values at a greatly reduced computational cost compared to the conventional LQG algorithm with small and controllable losses in the accuracy of the state and parameter estimation.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.011
      Issue No: Vol. 110 (2017)
  • Dynamic effects of root system architecture improve root water uptake in
           1-D process-based soil-root hydrodynamics
    • Authors: Martin Bouda; James E. Saiers
      Pages: 319 - 334
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Martin Bouda, James E. Saiers
      Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, descriptions of RSA have not been included because of their three-dimensional complexity, which makes them generally too computationally costly. Here we demonstrate a new, process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA under different soil moisture conditions: the RSA stencil. Using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, we show that the RSA stencil predicts plant water potentials within 2% to the outputs of a full 3D model, under the same assumptions on soil moisture heterogeneity, despite its trivial computational cost, resulting in improved predictions of water uptake and soil moisture compared to a model without RSA in a transient simulation. Our results suggest that LSM predictions of soil moisture dynamics and dependent variables can be improved by the implementation of this model, calibrated for individual PFTs using field observations.
      Graphical abstract image

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.018
      Issue No: Vol. 110 (2017)
  • A discrete fracture model for two-phase flow in fractured porous media
    • Authors: Dennis Gläser; Rainer Helmig; Bernd Flemisch; Holger Class
      Pages: 335 - 348
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Dennis Gläser, Rainer Helmig, Bernd Flemisch, Holger Class
      A discrete fracture model on the basis of a cell-centered finite volume scheme with multi-point flux approximation (MPFA) is presented. The fractures are included in a d-dimensional computational domain as ( d − 1 )-dimensional entities living on the element facets, which requires the grid to have the element facets aligned with the fracture geometries. However, the approach overcomes the problem of small cells inside the fractures when compared to equi-dimensional models. The system of equations considered is solved on both the matrix and the fracture domain, where on the prior the fractures are treated as interior boundaries and on the latter the exchange term between fracture and matrix appears as an additional source/sink. This exchange term is represented by the matrix-fracture fluxes, computed as functions of the unknowns in both domains by applying adequate modifications to the MPFA scheme. The method is applicable to both low-permeable as well as highly conductive fractures. The quality of the results obtained by the discrete fracture model is studied by comparison to an equi-dimensional discretization on a simple geometry for both single- and two-phase flow. For the case of two-phase flow in a highly conductive fracture, good agreement in the solution and in the matrix-fracture transfer fluxes could be observed, while for a low-permeable fracture the discrepancies were more pronounced. The method is then applied two-phase flow through a realistic fracture network in two and three dimensions.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.031
      Issue No: Vol. 110 (2017)
  • Soil moisture prediction with the ensemble Kalman filter: Handling
           uncertainty of soil hydraulic parameters
    • Authors: N. Brandhorst; D. Erdal; I. Neuweiler
      Pages: 360 - 370
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): N. Brandhorst, D. Erdal, I. Neuweiler
      For predicting flow in the unsaturated zone, an adequate choice of the model parameters, especially the soil hydraulic parameters, is essential. It is difficult to determine these parameters, as the parameter estimation problem easily becomes ill-posed, e.g. due to pseudo-correlations among two or more of the unknown parameters. In the field, this problem is strongly related to the available observations which, in monitoring networks, are not optimized to be used for parameter estimation. In this paper, we investigate the potential of data assimilation using the ensemble Kalman filter (EnKF) with unsaturated zone models under conditions where model parameters are highly uncertain and not identifiable. Different ways of dealing with the parameter uncertainty, such as parameter updates and bias correction, are discussed and compared. It is shown that jointly updating all uncertain parameters and states is the best method to account for the error induced by parameter uncertainty.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.022
      Issue No: Vol. 110 (2017)
  • Inversion using a new low-dimensional representation of complex binary
           geological media based on a deep neural network
    • Authors: Eric Laloy; Romain Hérault; John Lee; Diederik Jacques; Niklas Linde
      Pages: 387 - 405
      Abstract: Publication date: December 2017
      Source:Advances in Water Resources, Volume 110
      Author(s): Eric Laloy, Romain Hérault, John Lee, Diederik Jacques, Niklas Linde
      Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional base model parameterization of complex binary geological media. For inversion purposes, it has the attractive feature that random draws from an uncorrelated standard normal distribution yield model realizations with spatial characteristics that are in agreement with the training set. In comparison with the most commonly used parametric representations in probabilistic inversion, we find that our dimensionality reduction (DR) approach outperforms principle component analysis (PCA), optimization-PCA (OPCA) and discrete cosine transform (DCT) DR techniques for unconditional geostatistical simulation of a channelized prior model. For the considered examples, important compression ratios (200–500) are achieved. Given that the construction of our parameterization requires a training set of several tens of thousands of prior model realizations, our DR approach is more suited for probabilistic (or deterministic) inversion than for unconditional (or point-conditioned) geostatistical simulation. Probabilistic inversions of 2D steady-state and 3D transient hydraulic tomography data are used to demonstrate the DR-based inversion. For the 2D case study, the performance is superior compared to current state-of-the-art multiple-point statistics inversion by sequential geostatistical resampling (SGR). Inversion results for the 3D application are also encouraging.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.09.029
      Issue No: Vol. 110 (2017)
  • Understanding and Managing the Food-Energy-Water Nexus – Opportunities
           for Water Resources Research
    • Authors: Ximing Cai; Kevin Wallington Majid Shafiee-Jood Landon Marston
      Abstract: Publication date: Available online 14 November 2017
      Source:Advances in Water Resources
      Author(s): Ximing Cai, Kevin Wallington, Majid Shafiee-Jood, Landon Marston
      Studies on the food, energy, and water (FEW) nexus lay a shared foundation for researchers, policy makers, practitioners, and stakeholders to understand and manage linked production, utilization, and security of FEW systems. The FEW nexus paradigm provides water communities specific channels to move forward in interdisciplinary research where integrated water resources management (IWRM) has fallen short. Here, we help water researchers identify, articulate, utilize, and extend our disciplinary strengths within the broader FEW communities, while informing scientists in the food and energy domains about our unique skillset. This paper explores the relevance of existing and ongoing scholarship within the water community, as well as current research needs, for understanding FEW processes and systems and implementing FEW solutions through innovations in technologies, infrastructures, and policies. Following the historical efforts in IWRM, hydrologists, water resources engineers, economists, and policy analysts are provided opportunities for interdisciplinary studies among themselves and in collaboration with energy and food communities, united by a common path to achieve common sustainability development goals.

      PubDate: 2017-11-18T18:09:00Z
  • Enhancing Hydrologic Data Assimilation by Evolutionary Particle Filter and
           Markov Chain Monte Carlo
    • Authors: Peyman Abbaszadeh; Hamid Moradkhani Hongxiang Yan
      Abstract: Publication date: Available online 13 November 2017
      Source:Advances in Water Resources
      Author(s): Peyman Abbaszadeh, Hamid Moradkhani, Hongxiang Yan
      Particle Filters (PFs) have received increasing attention by researchers from different disciplines including the hydro-geosciences, as an effective tool to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation using the PFs in hydrology has evolved since 2005 from the PF-SIR (sampling importance resampling) to PF-MCMC (Markov Chain Monte Carlo), and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and MCMC, the so-called EPFM. In this framework, the prior distribution undergoes an evolutionary process based on the designed mutation and crossover operators of GA. The merit of this approach is that the particles move to an appropriate position by using the GA optimization and then the number of effective particles is increased by means of MCMC, whereby the particle degeneracy is avoided and the particle diversity is improved. In this study, the usefulness and effectiveness of the proposed EPFM is investigated by applying the technique on a conceptual and highly nonlinear hydrologic model over four river basins located in different climate and geographical regions of the United States. Both synthetic and real case studies demonstrate that the EPFM improves both the state and parameter estimation more effectively and reliably as compared with the PF-MCMC.

      PubDate: 2017-11-18T18:09:00Z
  • Accounting for model error in Bayesian solutions to hydrogeophysical
           inverse problems using a local basis approach
    • Authors: Corinna Köpke; James Irving; Ahmed H. Elsheikh
      Abstract: Publication date: Available online 13 November 2017
      Source:Advances in Water Resources
      Author(s): Corinna Köpke, James Irving, Ahmed H. Elsheikh
      Bayesian solutions to geophysical and hydrological inverse problems are dependent upon a forward model linking subsurface physical properties to measured data, which is typically assumed to be perfectly known in the inversion procedure. However, to make the stochastic solution of the inverse problem computationally tractable using methods such as Markov-chain-Monte-Carlo (MCMC), fast approximations of the forward model are commonly employed. This gives rise to model error, which has the potential to significantly bias posterior statistics if not properly accounted for. Here, we present a new methodology for dealing with the model error arising from the use of approximate forward solvers in Bayesian solutions to hydrogeophysical inverse problems. Our approach is geared towards the common case where this error cannot be (i) effectively characterized through some parametric statistical distribution; or (ii) estimated by interpolating between a small number of computed model-error realizations. To this end, we focus on identification and removal of the model-error component of the residual during MCMC using a projection-based approach, whereby the orthogonal basis employed for the projection is derived in each iteration from the K-nearest-neighboring entries in a model-error dictionary. The latter is constructed during the inversion and grows at a specified rate as the iterations proceed. We demonstrate the performance of our technique on the inversion of synthetic crosshole ground-penetrating radar travel-time data considering three different subsurface parameterizations of varying complexity. Synthetic data are generated using the eikonal equation, whereas a straight-ray forward model is assumed for their inversion. In each case, our developed approach enables us to remove posterior bias and obtain a more realistic characterization of uncertainty.

      PubDate: 2017-11-18T18:09:00Z
      DOI: 10.1016/j.advwatres.2017.11.013
  • Investigating the Settling Dynamics of Cohesive Silt Particles With
           Particle-Resolving Simulations
    • Authors: Rui Sun; Heng Xiao; Honglei Sun
      Abstract: Publication date: Available online 13 November 2017
      Source:Advances in Water Resources
      Author(s): Rui Sun, Heng Xiao, Honglei Sun
      The settling of cohesive sediment is ubiquitous in aquatic environments, and the study of the settling process is important for both engineering and environmental reasons. In the settling process, the silt particles show behaviors that are different from non-cohesive particles due to the influence of inter-particle cohesive force. For instance, the flocs formed in the settling process of cohesive silt can loosen the packing, and thus the structural densities of cohesive silt beds are much smaller than that of non-cohesive sand beds. While there is a consensus that cohesive behaviors depend on the characteristics of sediment particles (e.g., Bond number, particle size distribution), little is known about the exact influence of these characteristics on the cohesive behaviors. In addition, since the cohesive behaviors of the silt are caused by the inter-particle cohesive forces, the motions of and the contacts among silt particles should be resolved to study these cohesive behaviors in the settling process. However, studies of the cohesive behaviors of silt particles in the settling process based on particle-resolving approach are still lacking. In the present work, three-dimensional settling process is investigated numerically by using CFD–DEM (Computational Fluid Dynamics–Discrete Element Method). The inter-particle collision force, the van der Waals force, and the fluid–particle interaction forces are considered. The numerical model is used to simulate the hindered settling process of silt based on the experimental setup in the literature. The results obtained in the simulations, including the structural densities of the beds, the characteristic lines, and the particle terminal velocity, are in good agreement with the experimental observations in the literature. To the authors’ knowledge, this is the first time that the influences of non-dimensional Bond number and particle polydispersity on the structural densities of silt beds have been investigated separately. The results demonstrate that the cohesive behavior of silt in the settling process is attributed to both the cohesion among silt particles themselves and the particle polydispersity. To guide to the macro-scale modeling of cohesive silt sedimentation, the collision frequency functions obtained in the numerical simulations are also presented based on the micromechanics of particles. The results obtained by using CFD–DEM indicate that the binary collision theory over-estimated the particle collision frequency in the flocculation process at high solid volume fraction.

      PubDate: 2017-11-18T18:09:00Z
      DOI: 10.1016/j.advwatres.2017.11.012
  • Generation of Net Sediment Transport by Velocity Skewness in Oscillatory
           Sheet Flow
    • Authors: Xin Chen; Yong Li; Genfa Chen; Fujun Wang; Xuelin Tang
      Abstract: Publication date: Available online 11 November 2017
      Source:Advances in Water Resources
      Author(s): Xin Chen, Yong Li, Genfa Chen, Fujun Wang, Xuelin Tang
      This study utilizes a qualitative approach and a two-phase numerical model to investigate net sediment transport caused by velocity skewness beneath oscillatory sheet flow and current. The qualitative approach is derived based on the pseudo-laminar approximation of boundary layer velocity and exponential approximation of concentration. The two-phase model can obtain well the instantaneous erosion depth, sediment flux, boundary layer thickness, and sediment transport rate. It can especially illustrate the difference between positive and negative flow stages caused by velocity skewness, which is considerably important in determining the net boundary layer flow and sediment transport direction. The two-phase model also explains the effect of sediment diameter and phase-lag to sediment transport by comparing the instantaneous-type formulas to better illustrate velocity skewness effect. In previous studies about sheet flow transport in pure velocity-skewed flows, net sediment transport is only attributed to the phase-lag effect. In the present study with the qualitative approach and two-phase model, phase-lag effect is shown important but not sufficient for the net sediment transport beneath pure velocity-skewed flow and current, while the asymmetric wave boundary layer development between positive and negative flow stages also contributes to the sediment transport.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.006
  • Ecological and soil hydraulic implications of microbial responses to
           stress - A modeling analysis
    • Authors: Albert C. Brangarí; Daniel Fernàndez-Garcia; Xavier Sanchez-Vila; Stefano Manzoni
      Abstract: Publication date: Available online 7 November 2017
      Source:Advances in Water Resources
      Author(s): Albert C. Brangarí, Daniel Fernàndez-Garcia, Xavier Sanchez-Vila, Stefano Manzoni
      A better understanding of microbial dynamics in porous media may lead to improvements in the design and management of a number of technological applications, ranging from the degradation of contaminants to the optimization of agricultural systems. To this aim, there is a recognized need for predicting the proliferation of soil microbial biomass (often organized in biofilms) under different environments and stresses. We present a general multi-compartment model to account for physiological responses that have been extensively reported in the literature. The model is used as an explorative tool to elucidate the ecological and soil hydraulic consequences of microbial responses including the production of extracellular polymeric substances (EPS), the induction of cells into dormancy, and the allocation and reuse of resources between biofilm compartments. The mechanistic model is equipped with indicators allowing the microorganisms to monitor environmental and biological factors and react according to the current stress pressures. The feedbacks of biofilm accumulation on the soil water retention are also described. Model runs simulating different degrees of substrate and water shortage show that adaptive responses to the intensity and type of stress provide a clear benefit to microbial colonies. Results also demonstrate that the model may effectively predict qualitative patterns in microbial dynamics supported by empirical evidence, thereby improving our understanding of the effects of pore-scale physiological mechanisms on the soil macroscale phenomena.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.005
  • Groundwater dynamics in subterranean estuaries of coastal unconfined
           aquifers: Controls on submarine groundwater discharge and chemical inputs
           to the ocean
    • Authors: Clare E. Robinson; Pei Xin; Isaac R. Santos; Matthew A. Charette; Ling Li; D.A. Barry
      Abstract: Publication date: Available online 7 November 2017
      Source:Advances in Water Resources
      Author(s): Clare E. Robinson, Pei Xin, Isaac R. Santos, Matthew A. Charette, Ling Li, D.A. Barry
      Sustainable coastal resource management requires sound understanding of interactions between coastal unconfined aquifers and the ocean as these interactions influence the flux of chemicals to the coastal ocean and the availability of fresh groundwater resources. The importance of submarine groundwater discharge in delivering chemical fluxes to the coastal ocean and the critical role of the subterranean estuary (STE) in regulating these fluxes is well recognized. STEs are complex and dynamic systems exposed to various physical, hydrological, geological, and chemical conditions that act on disparate spatial and temporal scales. This paper provides a review of the effect of factors that influence flow and salt transport in STEs, evaluates current understanding on the interactions between these influences, and synthesizes understanding of drivers of nutrient, carbon, greenhouse gas, metal and organic contaminant fluxes to the ocean. Based on this review, key research needs are identified. While the effects of density and tides are well understood, episodic and longer-period forces as well as the interactions between multiple influences remain poorly understood. Many studies continue to focus on idealized nearshore aquifer systems and future work needs to consider real world complexities such as geological heterogeneities, and non-uniform and evolving alongshore and cross-shore morphology. There is also a significant need for multidisciplinary research to unravel the interactions between physical and biogeochemical processes in the STE, as most existing studies treat these processes in isolation. Better understanding of this complex and dynamic system can improve sustainable management of coastal water resources under the influence of anthropogenic pressures and climate change.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.10.041
  • Stochastic, Goal-oriented Rapid Impact Modeling of Uncertainty and
           Environmental Impacts in Poorly-Sampled Sites Using Ex-Situ Priors
    • Authors: Xiaojun Li; Yandong Li; Ching-Fu Chang; Benjamin Tan; Ziyang Chen; Jon Sege; Changhong Wang; Yoram Rubin
      Abstract: Publication date: Available online 7 November 2017
      Source:Advances in Water Resources
      Author(s): Xiaojun Li, Yandong Li, Ching-Fu Chang, Benjamin Tan, Ziyang Chen, Jon Sege, Changhong Wang, Yoram Rubin
      Modeling of uncertainty associated with subsurface dynamics has long been a major research topic. Its significance is widely recognized for real-life applications. Despite the huge effort invested in the area, major obstacles still remain on the way from theory and applications. Particularly problematic here is the confusion between modeling uncertainty and modeling spatial variability, which translates into a (mis)conception, in fact an inconsistency, in that it suggests that modeling of uncertainty and modeling of spatial variability are equivalent, and as such, requiring a lot of data. This paper investigates this challenge against the backdrop of a major, deep 7 km underground tunnel in China, where environmental impacts are of major concern. We approach the data challenge by pursuing a new concept for Rapid Impact Modeling (RIM), which bypasses altogether the need to estimate posterior distributions of model parameters, focusing instead on detailed stochastic modeling of impacts, conditional to all information available, including prior, ex-situ information and in-situ measurements as well. A foundational element of RIM is the construction of informative priors for target parameters using ex-situ data, relying on ensembles of well-documented sites, pre-screened for geological and hydrological similarity to the target site. The ensembles are built around two sets of similarity criteria: a physically-based set of criteria and an additional set covering epistemic criteria. In another variation to common Bayesian practice, we update the priors to obtain conditional distributions of the target (environmental impact) dependent variables and not the hydrological variables. This recognizes that concept of goal-oriented characterization is in many cases more useful in applications compared to detailed characterization.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.008
  • Erratum to “Polynomial-based approximate solutions to the Boussinesq
           equations near a well” [Adv. Water Resour. 96 (2016) 68-73]
    • Authors: Phillip A. Pratt; Aleksey S. Telyakovskiy; Satoko Kurita; Myron B. Allen
      Abstract: Publication date: Available online 4 November 2017
      Source:Advances in Water Resources
      Author(s): Phillip A. Pratt, Aleksey S. Telyakovskiy, Satoko Kurita, Myron B. Allen

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.004
  • Measurement and Modeling of CO2 Mass Transfer in Brine at Reservoir
    • Authors: Z. Shi; B. Wen; M. Hesse; T.T. Tsotsis; K. Jessen
      Abstract: Publication date: Available online 4 November 2017
      Source:Advances in Water Resources
      Author(s): Z. Shi, B. Wen, M. Hesse, T.T. Tsotsis, K. Jessen
      In this work, we combine measurements and modeling to investigate the application of pressure-decay experiments towards delineation and interpretation of CO2 solubility, uptake and mass transfer in water/brine systems at elevated pressures of relevance to CO2 storage operations in saline aquifers. Accurate measurements and modeling of mass transfer in this context are crucial to an improved understanding of the longer-term fate of CO2 that is injected into the subsurface for storage purposes. Pressure-decay experiments are presented for CO2/water and CO2/brine systems with and without the presence of unconsolidated porous media. We demonstrate, via high-resolution numerical calculations in 2-D, that onset of natural convection will complicate the interpretation of the experimental observations if the particle size is not sufficiently small. In such settings, we demonstrate that simple 1-D interpretations can result in an overestimation of the uptake (diffusivity) by two orders of magnitude. Furthermore, we demonstrate that high-resolution numerical calculations agree well with the experimental observations for settings where natural convection contributes substantially to the overall mass transfer process.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.002
  • Comparison of different assimilation methodologies of groundwater levels
           to improve predictions of root zone soil moisture with an integrated
           terrestrial system model
    • Authors: Hongjuan Zhang; Wolfgang Kurtz; Stefan Kollet; Harry Vereecken; Harrie-Jan Hendricks Franssen
      Abstract: Publication date: Available online 4 November 2017
      Source:Advances in Water Resources
      Author(s): Hongjuan Zhang, Wolfgang Kurtz, Stefan Kollet, Harry Vereecken, Harrie-Jan Hendricks Franssen
      The linkage between root zone soil moisture and groundwater is either neglected or simplified in most land surface models. The fully-coupled subsurface-land surface model TerrSysMP including variably saturated groundwater dynamics is used in this work. We test and compare five data assimilation methodologies for assimilating groundwater level data via the ensemble Kalman filter (EnKF) to improve root zone soil moisture estimation with TerrSysMP. Groundwater level data are assimilated in the form of pressure head or soil moisture (set equal to porosity in the saturated zone) to update state vectors. In the five assimilation methodologies, the state vector contains either (i) pressure head, or (ii) log-transformed pressure head, or (iii) soil moisture, or (iv) pressure head for the saturated zone only, or (v) a combination of pressure head and soil moisture, pressure head for the saturated zone and soil moisture for the unsaturated zone. These methodologies are evaluated in synthetic experiments which are performed for different climate conditions, soil types and plant functional types to simulate various root zone soil moisture distributions and groundwater levels. The results demonstrate that EnKF cannot properly handle strongly skewed pressure distributions which are caused by extreme negative pressure heads in the unsaturated zone during dry periods. This problem can only be alleviated by methodology (iii), (iv) and (v). The last approach gives the best results and avoids unphysical updates related to strongly skewed pressure heads in the unsaturated zone. If groundwater level data are assimilated by methodology (iii), EnKF fails to update the state vector containing the soil moisture values if for (almost) all the realizations the observation does not bring significant new information. Synthetic experiments for the joint assimilation of groundwater levels and surface soil moisture support methodology (v) and show great potential for improving the representation of root zone soil moisture.

      PubDate: 2017-11-12T02:01:08Z
      DOI: 10.1016/j.advwatres.2017.11.003
  • On the assimilation set-up of ASCAT soil moisture data for improving
           streamflow catchment simulation
    • Authors: Javier Loizu; Christian Massari; Jesús Álvarez-Mozos; Angelica Tarpanelli; Luca Brocca; Javier Casalí
      Abstract: Publication date: Available online 3 November 2017
      Source:Advances in Water Resources
      Author(s): Javier Loizu, Christian Massari, Jesús Álvarez-Mozos, Angelica Tarpanelli, Luca Brocca, Javier Casalí

      PubDate: 2017-11-05T09:20:00Z
      DOI: 10.1016/j.advwatres.2017.10.034
  • Hydrological change: Towards a consistent approach to assess changes on
           both floods and droughts
    • Authors: Beatriz Quesada-Montano; Giuliano Di Baldassarre; Sally Rangecroft; Anne F. Van Loon
      Abstract: Publication date: Available online 31 October 2017
      Source:Advances in Water Resources
      Author(s): Beatriz Quesada-Montano, Giuliano Di Baldassarre, Sally Rangecroft, Anne F. Van Loon
      Several studies have found that the frequency, magnitude and spatio-temporal distribution of droughts and floods have significantly increased in many regions of the world. Yet, most of the methods used in detecting trends in hydrological extremes 1) focus on either floods or droughts, and/or 2) base their assessment on characteristics that, even though useful for trend identification, cannot be directly used in decision making, e.g. integrated water resources management and disaster risk reduction. In this paper, we first discuss the need for a consistent approach to assess changes on both floods and droughts, and then propose a method based on the theory of runs and threshold levels. Flood and drought changes were assessed in terms of frequency, length and surplus/deficit volumes. This paper also presents an example application using streamflow data from two hydrometric stations along the Po River basin (Italy), Piacenza and Pontelagoscuro, and then discuss opportunities and challenges of the proposed method.

      PubDate: 2017-11-05T09:20:00Z
      DOI: 10.1016/j.advwatres.2017.10.038
  • Analysis and generation of groundwater concentration time series
    • Authors: Maria Crăciun; Călin Vamoş; Nicolae Suciu
      Abstract: Publication date: Available online 31 October 2017
      Source:Advances in Water Resources
      Author(s): Maria Crăciun, Călin Vamoş, Nicolae Suciu
      Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in Probability Density Function approaches. The well-known Interaction by Exchange with the Mean mixing model is a special case consisting of a linear regression with constant coefficients.

      PubDate: 2017-11-05T09:20:00Z
      DOI: 10.1016/j.advwatres.2017.10.039
  • Direct pore-scale reactive transport modelling of dynamic wettability
           changes induced by surface complexation
    • Authors: Julien Maes; Sebastian Geiger
      Abstract: Publication date: Available online 26 October 2017
      Source:Advances in Water Resources
      Author(s): Julien Maes, Sebastian Geiger
      Laboratory experiments have shown that oil production from sandstone and carbonate reservoirs by waterflooding could be significantly increased by manipulating the composition of the injected water (e.g. by lowering the ionic strength). Recent studies suggest that a change of wettability induced by a change in surface charge is likely to be one of the driving mechanism of the so-called low-salinity effect. In this case, the potential increase of oil recovery during waterflooding at low ionic strength would be strongly impacted by the inter-relations between flow, transport and chemical reaction at the pore-scale. Hence, a new numerical model that includes two-phase flow, solute reactive transport and wettability alteration is implemented based on the Direct Numerical Simulation of the Navier-Stokes equations and surface complexation modelling. Our model is first used to match experimental results of oil droplet detachment from clay patches. We then study the effect of wettability change on the pore-scale displacement for simple 2D calcite micro-models and evaluate the impact of several parameters such as water composition and injected velocity. Finally, we repeat the simulation experiments on a larger and more complex pore geometry representing a carbonate rock. Our simulations highlight two different effects of low-salinity on oil production from carbonate rocks: a smaller number of oil clusters left in the pores after invasion, and a greater number of pores invaded.

      PubDate: 2017-10-29T11:41:33Z
      DOI: 10.1016/j.advwatres.2017.10.032
  • Solute Transport in Aquifers: the Comeback of the Advection Dispersion
           Equation and the First Order Approximation
    • Authors: A. Fiori; A. Zarlenga; I. Jankovic; G. Dagan
      Abstract: Publication date: Available online 20 October 2017
      Source:Advances in Water Resources
      Author(s): A. Fiori, A. Zarlenga, I. Jankovic, G. Dagan
      Natural gradient steady flow of mean velocity U takes place in heterogeneous aquifers of random logconductivity Y = ln K , characterized by the normal univariate PDF f(Y) and autocorrelation ρY , of variance σ Y 2 and horizontal integral scale I. Solute transport is quantified by the Breakthrough Curve (BTC) M at planes at distance x from the injection plane. The study builds on the extensive 3D numerical simulations of flow and transport of [Jankovic, I., M. Maghrebi, A. Fiori, G. Dagan (2017), When good statistical models of aquifer heterogeneity go right: The impact of aquifer permeability structures on 3D ow and transport. Adv. Water Resour.] for different conductivity structures. The present study further explores the preditive capabilities of the Advection Dispersion Equation (ADE), with macrodispersivity αL given by the First Order Approximation (FOA), by checking in a quantitative manner its applicability. After a discussion on the suitable boundary conditions for ADE, we find that the ADE-FOA solution is a sufficiently accurate predictor for applications, the many other sources of uncertainty prevailing in practice notwithstanding. We checked by least squares and by comparison of travel time of quantiles of M that indeed the analytical Inverse Gaussian M with α L = σ Y 2 I , is able to fit well the bulk of the simulated BTCs. It tends to underestimate the late arrival time of the thin and persistent tail. The tail is better reproduced by the semi-analytical MIMSCA model, which also allows for a physical explanation of the success of the Inverse Gaussian solution. Examination of the pertinent longitudinal mass distribution shows that it is different from the commonly used Gaussian one in the analysis of field experiments, and it captures the main features of the plume measurements of the MADE experiment. The results strengthen the confidence in the applicability of the ADE and the FOA to predicting longitudinal spreading in solute transport through heterogeneous aquifers of stationary random structure.

      PubDate: 2017-10-21T22:55:26Z
      DOI: 10.1016/j.advwatres.2017.10.025
  • A Multi-Scale Ensemble-based Framework for Forecasting Compound
           Coastal-Riverine Flooding: The Hackensack-Passaic Watershed and Newark Bay
    • Authors: Saleh Ramaswamy; Wang Georgas Blumberg Pullen
      Abstract: Publication date: Available online 20 October 2017
      Source:Advances in Water Resources
      Author(s): F. Saleh, V. Ramaswamy, Y. Wang, N. Georgas, A. Blumberg, J. Pullen
      Estuarine regions can experience compound impacts from coastal storm surge and riverine flooding. The challenges in forecasting flooding in such areas are multi-faceted due to uncertainties associated with meteorological drivers and interactions between hydrological and coastal processes. The objective of this work is to evaluate how uncertainties from meteorological predictions propagate through an ensemble-based flood prediction framework and translate into uncertainties in simulated inundation extents. A multi-scale framework, consisting of hydrologic, coastal and hydrodynamic models, was used to simulate two extreme flood events at the confluence of the Passaic and Hackensack rivers and Newark Bay. The events were Hurricane Irene (2011), a combination of inland flooding and coastal storm surge, and Hurricane Sandy (2012) where coastal storm surge was the dominant component. The hydrodynamic component of the framework was first forced with measured streamflow and ocean water level data to establish baseline inundation extents with the best available forcing data. The coastal and hydrologic models were then forced with meteorological predictions from 21 ensemble members of the Global Ensemble Forecast System (GEFS) to retrospectively represent potential future conditions up to 96 hours prior to the events. Inundation extents produced by the hydrodynamic model, forced with the 95th percentile of the ensemble-based coastal and hydrologic boundary conditions, were in good agreement with baseline conditions for both events. The USGS reanalysis of Hurricane Sandy inundation extents was encapsulated between the 50th and 95th percentile of the forecasted inundation extents, and that of Hurricane Irene was similar but with caveats associated with data availability and reliability. This work highlights the importance of accounting for meteorological uncertainty to represent a range of possible future inundation extents at high resolution (∼m).

      PubDate: 2017-10-21T22:55:26Z
  • ANOVA-based transformed probabilistic collocation method for Bayesian
           data-worth analysis
    • Authors: Jun Man; Qinzhuo Liao; Lingzao Zeng; Laosheng Wu
      Abstract: Publication date: Available online 16 October 2017
      Source:Advances in Water Resources
      Author(s): Jun Man, Qinzhuo Liao, Lingzao Zeng, Laosheng Wu
      Bayesian theory provides a coherent framework in quantifying the data worth of measurements and estimating unknown parameters. Nevertheless, one common problem in Bayesian methods is the considerably high computational cost since a large number of model evaluations is required in the likelihood evaluation. To address this issue, a new surrogate modeling method, i.e., ANOVA (analysis of variance)-based transformed probabilistic collocation method (ATPCM), is developed in this work. To cope with the strong nonlinearity, the model responses are transformed to the arrival times, which are then approximated with a set of low-order ANOVA components. The validity of the proposed method is demonstrated by synthetic numerical cases involving water and heat transport in the vadose zone. It is shown that, the ATPCM is more efficient than the existing surrogate modeling methods (e.g., PCM, ANOVA-based PCM and TPCM). At a very low computational cost, the ATPCM-based Bayesian data-worth analysis provides a quantitative metric in comparing different monitoring plans, and helps to improve the parameter estimation. Although the flow and heat transport in vadose zone is considered in this work, the proposed method can be equally applied in any other hydrologic problems.

      PubDate: 2017-10-21T22:55:26Z
      DOI: 10.1016/j.advwatres.2017.10.001
  • On Uncertainty Quantification in Hydrogeology and Hydrogeophysics
    • Authors: Niklas Linde; David Ginsbourger; James Irving; Fabio Nobile; Arnaud Doucet
      Abstract: Publication date: Available online 16 October 2017
      Source:Advances in Water Resources
      Author(s): Niklas Linde, David Ginsbourger, James Irving, Fabio Nobile, Arnaud Doucet
      Recent advances in sensor technologies, field methodologies, numerical modeling, and inversion approaches have contributed to unprecedented imaging of hydrogeological properties and detailed predictions at multiple temporal and spatial scales. Nevertheless, imaging results and predictions will always remain imprecise, which calls for appropriate uncertainty quantification (UQ). In this paper, we outline selected methodological developments together with pioneering UQ applications in hydrogeology and hydrogeophysics. The applied mathematics and statistics literature is not easy to penetrate and this review aims at helping hydrogeologists and hydrogeophysicists to identify suitable approaches for UQ that can be applied and further developed to their specific needs. To bypass the tremendous computational costs associated with forward UQ based on full-physics simulations, we discuss proxy-modeling strategies and multi-resolution (Multi-level Monte Carlo) methods. We consider Bayesian inversion for non-linear and non-Gaussian state-space problems and discuss how Sequential Monte Carlo may become a practical alternative. We also describe strategies to account for forward modeling errors in Bayesian inversion. Finally, we consider hydrogeophysical inversion, where petrophysical uncertainty is often ignored leading to overconfident parameter estimation. The high parameter and data dimensions encountered in hydrogeological and geophysical problems make UQ a complicated and important challenge that has only been partially addressed to date.

      PubDate: 2017-10-21T22:55:26Z
      DOI: 10.1016/j.advwatres.2017.10.014
    • Authors: Harpreet Singh; Nicolas J. Huerta
      Abstract: Publication date: Available online 12 October 2017
      Source:Advances in Water Resources
      Author(s): Harpreet Singh, Nicolas J. Huerta
      CO2 injection into geologic formations for either enhanced oil recovery or carbon storage introduces a risk for undesired fluid leakage into overlying groundwater or to the surface. Despite decades of subsurface CO2 production and injection, the technologies and methods for detecting CO2 leaks are still costly and prone to large uncertainties. This is especially true for pressure-based monitoring methods, which require the use of simplified geological and reservoir flow models to simulate the pressure behavior as well as background noise affecting pressure measurements. In this study, we propose a method to detect the time and volume of fluid leakage based on real-time measurements of well injection and production rates. The approach utilizes analogies between fluid flow and capacitance-resistance modeling. Unlike other leak detection methods (e.g. pressure-based), the proposed method does not require geological and reservoir flow models to simulate the behavior that often carry significant sources of uncertainty; therefore, with our approach the leak can be detected with greater certainty. The method can be applied to detect when a leak begins by tracking a departure in fluid production rate from the expected pattern. The method has been tuned to detect the effect of boundary conditions and fluid compressibility on leakage. To highlight the utility of this approach we use our method to detect leaks for two scenarios. The first scenario simulates a fluid leak from the storage formation into an above-zone monitoring interval. The second scenario simulates intra-reservoir migration between two compartments. We illustrate this method to detect fluid leakage in three different reservoirs with varying levels of geological and structural complexity. The proposed leakage detection method has three novelties: i) requires only readily-available data (injection and production rates), ii) accounts for fluid compressibility and boundary effects, and iii) in addition to detecting the time when a leak is activated and the volume of that leakage, this method provides an insight about the leak location, and reservoir connectivity. We are proposing this as a complementary method that can be used with other, more expensive, methods early on in the injection process. This will allow an operator to conduct more expensive surveys less often because the proposed method can show if there are no leaks on a monthly basis that is cheap and fast.

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.10.012
  • Toward Direct Pore-Scale Modeling of Three-Phase Displacements
    • Authors: Peyman Mohammadmoradi; Apostolos Kantzas
      Abstract: Publication date: Available online 11 October 2017
      Source:Advances in Water Resources
      Author(s): Peyman Mohammadmoradi, Apostolos Kantzas
      A stable spreading film between water and gas can extract a significant amount of bypassed non-aqueous phase liquid (NAPL) through immiscible three-phase gas/water injection cycles. In this study, the pore-scale displacement mechanisms by which NAPL is mobilized are incorporated into a three-dimensional pore morphology-based model under water-wet and capillary equilibrium conditions. The approach is pixel-based and the sequence of invasions is determined by the fluids’ connectivity and the threshold capillary pressure of the advancing interfaces. In addition to the determination of three-phase spatial saturation profiles, residuals, and capillary pressure curves, dynamic finite element simulations are utilized to predict the effective permeabilities of the rock microtomographic images as reasonable representations of the geological formations under study. All the influential features during immiscible fluid flow in pore-level domains including wetting and spreading films, saturation hysteresis, capillary trapping, connectivity, and interface development strategies are taken into account. The capabilities of the model are demonstrated by the successful prediction of saturation functions for Berea sandstone and the accurate reconstruction of three-phase fluid occupancies through a micromodel.
      Graphical abstract image

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.10.010
  • Investigation of CO2 dissolution via mass transfer inside a porous medium
    • Authors: Anindityo Patmonoaji; Tetsuya Suekane
      Abstract: Publication date: Available online 10 October 2017
      Source:Advances in Water Resources
      Author(s): Anindityo Patmonoaji, Tetsuya Suekane
      The dissolution of trapped carbon dioxide (CO2) gas under various water flow rate inside a porous medium was experimentally studied using X-ray microtomography. Image processing techniques were used to determine the morphologies, CO2 fractions, and interfacial areas of the trapped bubbles. Based on fractal dimension analysis, the bubble morphology was classified into single-pore bubbles and multi-pore bubbles. Different dissolution phenomena with liquid-liquid systems were observed. First, the calculated mass transfer coefficient was lower than one order of magnitude. Second, two consecutive dissolution fronts appeared. These two fronts were not triggered by a difference in solute concentration because they occurred at CO2 concentrations far from saturated conditions. However, velocity-dependent mass transfer indicated a power function with a power value similar with liquid-liquid system dissolution experiment.

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.10.008
  • Scaling of Dissolved Organic Carbon Removal in River Networks
    • Authors: Enrico Bertuzzo; Ashley M. Helton; Robert O. Hall; ; Tom J. Battin
      Abstract: Publication date: Available online 10 October 2017
      Source:Advances in Water Resources
      Author(s): Enrico Bertuzzo, Ashley M. Helton, Robert O. Hall , Tom J. Battin
      Streams and rivers play a major role in the global carbon cycle as they collect, transform and deliver terrestrial organic carbon to the ocean. The rate of dissolved organic carbon (DOC) removal depends on hydrological factors (primarily water depth and residence time) that change predictably within the river network and local DOC concentration and composition is the result of transformation and removal processes in the whole upstream catchment. We thus combine theory of the form and scaling of river networks with a model of DOC removal from streamwater to investigate how the structure of river networks and the related hydrological drivers control DOC dynamics. We find that minimization of energy dissipation, the physical process that shapes the topological and metric properties of river networks, leads to structures that are more efficient in terms of total DOC removal per unit of streambed area. River network structure also induces a scaling of the DOC mass flux with the contributing area that does not depend on the particular network used for the simulation and is robust to spatial heterogeneity of model parameters. Such scaling enables the derivation of removal patterns across a river network in terms of clearly identified biological, hydrological and geomorphological factors. In particular, we derive how the fraction of terrestrial DOC load removed by the river network scales with the catchment area and with the area of a region drained by multiple river networks. Such results further our understanding of the impact of streams and rivers on carbon cycling at large scales.

      PubDate: 2017-10-14T08:39:26Z
      DOI: 10.1016/j.advwatres.2017.10.009
  • Numerical simulations of Holocene salt-marsh dynamics under the hypothesis
           of large soil deformations
    • Authors: Zoccarato Teatini
      Abstract: Publication date: Available online 7 October 2017
      Source:Advances in Water Resources
      Author(s): C. Zoccarato, P. Teatini
      Salt marshes are vulnerable environments hosting complex interactions between physical and biological processes. The prediction of the elevation dynamics of a salt-marsh platform is crucial to forecast its future behaviour under potential changing scenarios. An original finite-element (FE) numerical model accounting for the long-term marsh accretion and compaction linked to relative sea level rise is proposed. The accretion term considers the material sedimentation over the marsh surface, whereas the compaction reflects the progressive consolidation of the porous medium under the increasing load of the overlying younger deposits. The modelling approach is based on a 2D groundwater flow simulator coupled to a 1D vertical geomechanical module, where the soil properties may vary with the effective intergranular stress. The model takes also into account the geometric non-linearity arising from the consideration of large solid grain movements by using a Lagrangian approach with an adaptive FE mesh. The numerical experiments show the potentiality of the proposed 2D model, which consistently integrates in modelling framework the behaviour of spatially distributed model parameters. High sedimentation rates and low permeabilities largely impact on the mechanism of soil compaction following the overpressure dissipation.

      PubDate: 2017-10-08T20:13:28Z
  • A Framework to Simulate Small Shallow Inland Water Bodies in Semi-arid
    • Authors: Ali Abbasi; Frank Ohene Annor Nick van Giesen
      Abstract: Publication date: Available online 5 October 2017
      Source:Advances in Water Resources
      Author(s): Ali Abbasi, Frank Ohene Annor, Nick van de Giesen
      In this study, a framework for simulating the flow field and heat transfer processes in small shallow inland water bodies has been developed. As the dynamics and thermal structure of these wat er bodies are crucial in studying the quality of stored water , and in assessing the heat fluxes from their surfaces as well, the heat transfer and temperature simulations were modeled. The proposed model is able to simulate the full 3-D water flow and heat transfer in the water body by applying complex and time varying boundary conditions. In this model, the continuity, momentum and temperature equations together with the turbulence equations, which comprise the buoyancy effect, have been solved. This model is built on the Reynolds Averaged Navier Stokes (RANS) equations with the widely used Boussinesq approach to solve the turbulence issues of the flow field. Micrometeorological data were obtained from an Automatic Weather Station (AWS) installed on the site and combined with field bathymetric measurements for the model. In the framework developed, a simple, applicable and generalizable approach is proposed for preparing the geometry of small shallow water bodies using coarsely measured bathymetry. All parts of the framework are based on open-source tools, which is essential for developing countries.

      PubDate: 2017-10-08T20:13:28Z
  • Effect of river flow fluctuations on riparian vegetation dynamics:
           processes and models
    • Authors: Riccardo Vesipa; Carlo Camporeale; Luca Ridolfi
      Abstract: Publication date: Available online 3 October 2017
      Source:Advances in Water Resources
      Author(s): Riccardo Vesipa, Carlo Camporeale, Luca Ridolfi
      Several decades of field observations, laboratory experiments and mathematical modelings have demonstrated that the riparian environment is a disturbance-driven ecosystem, and that the main source of disturbance is river flow fluctuations. The focus of the present work has been on the key role that flow fluctuations play in determining the abundance, zonation and species composition of patches of riparian vegetation. To this aim, the scientific literature on the subject, over the last 20 years, has been reviewed. First, the most relevant ecological, morphological and chemical mechanisms induced by river flow fluctuations are described from a process-based perspective. The role of flow variability is discussed for the processes that affect the recruitment of vegetation, the vegetation during its adult life, and the morphological and nutrient dynamics occurring in the riparian habitat. Particular emphasis has been given to studies that were aimed at quantifying the effect of these processes on vegetation, and at linking them to the statistical characteristics of the river hydrology. Second, the advances made, from a modeling point of view, have been considered and discussed. The main models that have been developed to describe the dynamics of riparian vegetation have been presented. Different modeling approaches have been compared, and the corresponding advantages and drawbacks have been pointed out. Finally, attention has been paid to identifying the processes considered by the models, and these processes have been compared with those that have actually been observed or measured in field/laboratory studies.

      PubDate: 2017-10-08T20:13:28Z
      DOI: 10.1016/j.advwatres.2017.09.028
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