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  • 1. Brangari, Albert C.
    et al.
    Fernandez-Garcia, Daniel
    Sanchez-Vila, Xavier
    Manzoni, Stefano
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Ecological and soil hydraulic implications of microbial responses to stress - A modeling analysis2018In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 116, p. 178-194Article in journal (Refereed)
    Abstract [en]

    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.

  • 2. Breuer, L.
    et al.
    Huisman, J. A.
    Willems, P.
    Bormann, H.
    Bronstert, A.
    Croke, B. F. W.
    Frede, H. G.
    Graff, T.
    Hubrechts, L.
    Jakeman, A. J.
    Kite, G.
    Lanini, J.
    Leavesley, G.
    Lettenmaier, D. P.
    Lindstrom, G.
    Seibert, Jan
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Sivapalan, M.
    Viney, N. R.
    Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use2009In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 32, no 2, p. 129-146Article in journal (Refereed)
    Abstract [en]

    This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. in this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment. Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations.

  • 3.
    Frampton, A.
    et al.
    Department of Water Resources Engineering, Royal Institute of Technology.
    Cvetkovic, V.
    Department of Water Resources Engineering, Royal Institute of Technology.
    Significance of injection modes and heterogeneity on spatial and temporal dispersion of advecting particles in two-dimensional discrete fracture networks2009In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 32, no 5, p. 649-658Article in journal (Refereed)
  • 4. Gephart, Jessica A.
    et al.
    Troell, Max
    Stockholm University, Faculty of Science, Stockholm Resilience Centre. Royal Swedish Academy of Sciences, Sweden.
    Henriksson, Patrik J. G.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre. WorldFish, Penang, Malaysia.
    Beveridge, Malcolm C. M.
    Verdegem, Marc
    Metian, Marc
    Mateos, Lara D.
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Deutsch, Lisa
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    The 'seafood gap' in the food-water nexus literature-issues surrounding freshwater use in seafood production chains2017In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 110, p. 505-514Article in journal (Refereed)
    Abstract [en]

    Freshwater use for food production is projected to increase substantially in the coming decades with population growth, changing demographics, and shifting diets. Ensuring joint food-water security has prompted efforts to quantify freshwater use for different food products and production methods. However, few analyses quantify freshwater use for seafood production, and those that do use inconsistent water accounting. This inhibits water use comparisons among seafood products or between seafood and agricultural/livestock products. This 'seafood gap' in the food-water nexus literature will become increasingly problematic as seafood consumption is growing globally and aquaculture is one of the fastest growing animal food sectors in the world. Therefore, the present study 1) reviews freshwater use concepts as they relate to seafood production; 2) provides three cases to highlight the particular water use concerns for aquaculture, and; 3) outlines future directions to integrate seafood into the broader food-water nexus discussion. By revisiting water use concepts through a focus on seafood production systems, we highlight the key water use processes that should be considered for seafood production and offer a fresh perspective on the analysis of freshwater use in food systems more broadly. This is an open access article under the CC BY-NC-ND license.

  • 5. Grenier, Christophe
    et al.
    Anbergen, Hauke
    Bense, Victor
    Chanzy, Quentin
    Coon, Ethan
    Collier, Nathaniel
    Costard, Francois
    Ferry, Michel
    Frampton, Andrew
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Frederick, Jennifer
    Goncalves, Julio
    Holmen, Johann
    Jost, Anne
    Kokh, Samuel
    Kurylyk, Barret
    McKenzie, Jeffrey
    Molson, John
    Mouche, Emmanuel
    Orgogozo, Laurent
    Pannetier, Romain
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Riviere, Agnes
    Roux, Nicolas
    Ruehaak, Wolfram
    Scheidegger, Johanna
    Selroos, Jan-Olof
    Therrien, Rene
    Vidstrand, Patrik
    Voss, Clifford
    Groundwater flow and heat transport for systems undergoing freeze-thaw: Intercomparison of numerical simulators for 2D test cases2018In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 114, p. 196-218Article in journal (Refereed)
    Abstract [en]

    In high-elevation, boreal and arctic regions, hydrological processes and associated water bodies can be strongly influenced by the distribution of permafrost. Recent field and modeling studies indicate that a fully-coupled multidimensional thermo-hydraulic approach is required to accurately model the evolution of these permafrost-impacted landscapes and groundwater systems. However, the relatively new and complex numerical codes being developed for coupled non-linear freeze-thaw systems require verification. This issue is addressed by means of an intercomparison of thirteen numerical codes for two-dimensional test cases with several performance metrics (PMs). These codes comprise a wide range of numerical approaches, spatial and temporal discretization strategies, and computational efficiencies. Results suggest that the codes provide robust results for the test cases considered and that minor discrepancies are explained by computational precision. However, larger discrepancies are observed for some PMs resulting from differences in the governing equations, discretization issues, or in the freezing curve used by some codes.

  • 6. Hui, Rui
    et al.
    Herman, Jonathan
    Lund, Jay
    Madani, Kaveh
    Stockholm University, Faculty of Science, Department of Physical Geography. Imperial College London, U.K..
    Adaptive water infrastructure planning for nonstationary hydrology2018In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 118, p. 83-94Article in journal (Refereed)
    Abstract [en]

    The uncertainty of a changing climate raises challenges for water infrastructure planning and design. Not accounting for nonstationarity may result in under-designed structures that fail too frequently, or over-designed structures that are economically inefficient. This concern is magnified by uncertainty in the long-term frequency and magnitude of future extreme events. Planning strategies that allow adaptations over a structure's life could improve both reliability and economic efficiency. This study develops a method to inform adaptive water infrastructure planning with uncertain hydrologic and other forms of nonstationarity, applied to levee system planning. A stochastic dynamic programming model including a Markov process is developed for infrastructure planning with uncertain nonstationarity in flood frequency. Bayes' theorem is used to update peak flow probabilities conditioned on observed past peak flows and to update expected residual flood damages over time. A levee system planning problem with a numerical example from California illustrates the approach to derive optimal levee heights over time, and economic values of adapting to uncertain nonstationary flood risk. The projected range of probabilistic hydrology scenarios affects the optimal results, particularly in later planning stages as hydrology scenarios diverge with time. Adaptive planning strategies allowing more levee upgrades over time slightly lowers the overall cost and provides better flood protection than one-time construction under nonstationary hydrology for any climate in the example. Compared to a known future nonstationary hydrology, incorporating uncertain nonstationary climate results in higher levees being planned for observed severe hydrology scenarios in later stages. The overall present value cost with uncertain nonstationary climate depends on rates of change in peak flow distribution parameters in future hydrology scenarios.

  • 7. Huisman, J. A.
    et al.
    Breuer, L.
    Bormann, H.
    Bronstert, A.
    Croke, B. F. W.
    Frede, H. G.
    Graff, T.
    Hubrechts, L.
    Jakeman, A. J.
    Kite, G.
    Lanini, J.
    Leavesley, G.
    Lettenmaier, D. P.
    Lindström, G.
    Seibert, Jan
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Sivapalan, M.
    Viney, N. R.
    Willems, P.
    Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III: Scenario analysis2009In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 32, no 2, p. 159-170Article in journal (Refereed)
    Abstract [en]

    An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.

  • 8.
    Manzoni, Stefano
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Vico, G.
    Thompson, S.
    Beyer, F.
    Weih, M.
    Contrasting leaf phenological strategies optimize carbon gain under droughts of different duration2015In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 84, p. 37-51Article in journal (Refereed)
    Abstract [en]

    In most ecosystems, plants face periods with limited water availability, during which stomatal conductance is reduced to maintain hydration. However, prolonged dry spells might require more drastic strategies to conserve water, such as drought-deciduousness. If drought-related changes in leaf area are adaptive, it can be hypothesized that leaf area is optimized to maximize the growing-season carbon (C) gain. Different phenological strategies during drought have been proposed: (i) leaf area index (L) declines when net photosynthetic rates (A(net)) reach zero to maintain a non-negative A(net); (ii) L adjusts to avoid water potentials with negative impacts on A(net); (iii) a constant leaf water potential is maintained (isohydric behavior); and (iv) leaf area remains unaltered (i.e., summer-evergreen leaf habit). However, whether these strategies are optimal in terms of growing season C gains has not been assessed. Here we consider these theories in a unified framework using the same set of equations to describe gas exchanges and water transport in the soil plant atmosphere continuum, and quantify the effect of the leaf phenological strategy on plant C gain over the entire growing season in different climates. Longer dry periods tend to favor drought-deciduous rather than summer-evergreen habit. Deciduous plants that allow leaf water potential to fluctuate (anisohydric) while preventing negative A(net) assimilate more carbon than deciduous plants with fixed leaf water potentials (isohydric). Increased rooting depth allows evergreens to more effectively compete with drought-deciduous species. Moreover, increasing leaf nitrogen concentrations and thus photosynthetic capacity can be an effective acclimation strategy when dry periods are relatively short.

  • 9. Viney, N. R.
    et al.
    Bormann, H.
    Breuer, L.
    Bronstert, A.
    Croke, B. F. W.
    Frede, H.
    Graff, T.
    Hubrechts, L.
    Huisman, J. A.
    Jakeman, A. J.
    Kite, G. W.
    Lanini, J.
    Leavesley, G.
    Lettenmaier, D. P.
    Lindström, G.
    Seibert, Jan
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Sivapalan, M.
    Willems, P.
    Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions2009In: Advances in Water Resources, ISSN 0309-1708, E-ISSN 1872-9657, Vol. 32, no 2, p. 147-158Article in journal (Refereed)
    Abstract [en]

    This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles. in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non-stationarity of the climate series and possible cross-correlations between models.

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