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  • Hydrology and Earth System Sciences...

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: R. Baatz; H.-J. Hendricks Franssen; X. Han; T. Hoar; +2 Authors

    Land surface models describe biogeophysical and biogeochemical processes at the land surface, and represent thelower boundary condition of atmospheric circulation models. Their key role is the quantification of mass and energyfluxes between the land surface and the atmosphere. Predictions with land surface models are affected by manyunknown parameters, uncertain meteorological forcings and incomplete process understanding. Measurement data(e.g., soil moisture) can help to improve land surface model predictions. However, soil moisture products obtainedfrom satellite remote sensing are normally available at a very coarse resolution and give information on the upperfew centimetres of the soil only. Therefore, the recently developed Cosmic Ray Neutron Sensors (CRNS) areof high interest for predictions by land surface models, because they measure neutron count intensity, which isrelated to integral soil moisture content at the field scale (about 20 hectares). High resolution land surface modelsare also able to provide solutions at the same scale. In this study, we investigated whether the assimilation ofsoil moisture retrievals from CRNS data measured by a network of nine CRNS located in the Rur catchmentin Germany (2354 km2) can improve land surface model prediction. The assimilation of soil moisture retrievalsfrom neutron count intensity data was used to update model states and parameters of the land surface modelCLM 4.5 over a two year time period, followed by a one year evaluation period without updates. This updatingwas done with the local ensemble transform Kalman filter. The real world experiment tested the value of CRNSusing jackknifing experiments and three different initial soil maps. During the assimilation period, soil moisturepredictions generally improved, for a biased soil map from an RMSE of 0.11 cm3/cm3 in the open loop run to0.03 cm3/cm3 while during the evaluation period soil moisture predictions improved from 0.12 cm3/cm3 to 0.06cm3/cm3. Improved soil parameters showed also an impact on latent heat and sensible heat flux, particularly duringthe summer period when evapotranspiration was soil moisture limited. The main conclusion from this study is thata network of CRNS is helpful to improve soil moisture predictions with a land surface model, in spite of the factthat in this study only nine CRNS were available for a catchment of size 2354 km2.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hydrology and Earth ...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DOAJ
    Article . 2017
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    Copernicus Publications
    Other literature type . 2018
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DOAJ
      Article . 2017
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Copernicus Publications
      Other literature type . 2018
      addClaim

      This Research product is the result of merged Research products in OpenAIRE.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dubois, Emmanuel; Doummar, Joanna; Pistre, Séverin; Larocque, Marie;

    Flow in complex karst aquifers is challenging to conceptualize and model, especially in poorly investigated areas, in semiarid climates, and under changing climatic conditions; however, it is necessary in order to implement long-term sustainable water management practices. Thus, the objectives of this work were to propose a calibration approach based on time series analyses for a karst aquifer and to assess the impact of climate change on spring discharge. Based on more than 3 years of high-resolution continuous monitoring, a semi-distributed lumped model was calibrated and validated for the Qachqouch karst spring, north of Beirut (Lebanon). Time series analyses and decomposition of spring hydrographs revealed that the system has a high regulatory function, with considerable storage capacity providing stable flow (minimum flow of 0.2 m3 s−1) during the dry season and with flow rates exceeding 10 m3 s−1 during the wet season, which is similar to other karst aquifers in the region. Based on this detailed understanding of the hydrodynamics of the system, the model geometry and parameters were validated. Three linear reservoirs were implemented to reproduce the combined contribution of the different flow components of the system. A satisfactory simulation (Nash–Sutcliffe efficiency coefficient, NSE, of 0.72) of the measured spring flow rates was obtained after calibration. Climate change conditions (+1 to +3 ∘C warming, −10 % to −30 % less precipitation annually, and the intensification of rain events) were added to a baseline climatic year to produce scenarios of expected spring flow responses. Results show that the Qachqouch karst aquifer is sensitive to decreasing rainfall, which is associated with more pronounced recessions, with flow rates decreasing by 34 % and 1-month longer dry periods. Because of the limited influence of snow on the spring flow rate, a warming climate has less impact on spring flow conditions than a reduction in precipitation. Although the model shows that increasing rainfall intensity induces larger floods, recessions, and shorter low-flow periods, the real impact of high-intensity precipitation events remains uncertain, as the model does not account for complex unsaturated and epikarstic processes. This work shows that calibrating a semi-distributed lumped model using time series analyses can be an efficient approach to improve simulations of complex karst aquifers, thereby providing useful models for long-term sustainable water management.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DOAJarrow_drop_down
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    DOAJ
    Article . 2020
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Article . 2020
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    Authors: Dance, S. L.; Zou, Q. P.;

    Ensemble predictions are being used more frequently to model the propagation of uncertainty through complex, coupled meteorological, hydrological and coastal models, with the goal of better characterising flood risk. In this paper, we consider the issues that we judge to be important when designing and evaluating ensemble predictions, and make recommendations for the guidance of future research.

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    Copernicus Publications
    Other literature type . 2018
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      Copernicus Publications
      Other literature type . 2018
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    Authors: Xiao, Shangbin; Liu, Liu; Wang, Wei; Lorke, Andreas; +2 Authors

    Biogenic greenhouse gas emissions, e.g., of methane (CH4) and carbon dioxide (CO2) from inland waters, contribute substantially to global warming. In aquatic systems, dissolved greenhouse gases are highly heterogeneous in both space and time. To better understand the biological and physical processes that affect sources and sinks of both CH4 and CO2, their dissolved concentrations need to be measured with high spatial and temporal resolution. To achieve this goal, we developed the Fast-Response Automated Gas Equilibrator (FaRAGE) for real-time in situ measurement of dissolved CH4 and CO2 concentrations at the water surface and in the water column. FaRAGE can achieve an exceptionally short response time (t95 %=12 s when including the response time of the gas analyzer) while retaining an equilibration ratio of 62.6 % and a measurement accuracy of 0.5 % for CH4. A similar performance was observed for dissolved CO2 (t95 %=10 s, equilibration ratio 67.1 %). An equilibration ratio as high as 91.8 % can be reached at the cost of a slightly increased response time (16 s). The FaRAGE is capable of continuously measuring dissolved CO2 and CH4 concentrations in the nM-to-sub mM (10−9–10−3 mol L−1) range with a detection limit of sub-nM (10−10 mol L−1), when coupling with a cavity ring-down greenhouse gas analyzer (Picarro GasScouter). FaRAGE allows for the possibility of mapping dissolved concentration in a “quasi” three-dimensional manner in lakes and provides an inexpensive alternative to other commercial gas equilibrators. It is simple to operate and suitable for continuous monitoring with a strong tolerance for suspended particles. While the FaRAGE is developed for inland waters, it can be also applied to ocean waters by tuning the gas–water mixing ratio. The FaRAGE is easily adapted to suit other gas analyzers expanding the range of potential applications, including nitrous oxide and isotopic composition of the gases.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Fachrepositorium Leb...arrow_drop_down
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    Authors: Olarinoye, Tunde; Gleeson, Tom; Hartmann, Andreas;

    Analysis of karst spring recession hydrographs is essential for determining hydraulic parameters, geometric characteristics, and transfer mechanisms that describe the dynamic nature of karst aquifer systems. The extraction and separation of different fast- and slow-flow components constituting a karst spring recession hydrograph typically involve manual and subjective procedures. This subjectivity introduces a bias that exists, while manual procedures can introduce errors into the derived parameters representing the system. To provide an alternative recession extraction procedure that is automated, fully objective, and easy to apply, we modified traditional streamflow extraction methods to identify components relevant for karst spring recession analysis. Mangin's karst-specific recession analysis model was fitted to individual extracted recession segments to determine matrix and conduit recession parameters. We introduced different parameter optimization approaches into Mangin's model to increase the degree of freedom, thereby allowing for more parameter interaction. The modified recession extraction and parameter optimization approaches were tested on three karst springs under different climate conditions. Our results showed that the modified extraction methods are capable of distinguishing different recession components and derived parameters that reasonably represent the analyzed karst systems. We recorded an average Kling–Gupta efficiency KGE > 0.85 among all recession events simulated by the recession parameters derived from all combinations of recession extraction methods and parameter optimization approaches. While there are variabilities among parameters estimated by different combinations of extraction methods, optimization approaches, and seasons, we found much higher variability among individual recession events. We provided suggestions to reduce the uncertainty among individual recession events and raised questions about how to improve confidence in the system's attributes derived from recession parameters.

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    Authors: Zhu, G. F.; Li, X.; Su, Y. H.; Huang, C. L.;

    The following two models were combined to simultaneously predict CO2 and H2O gas exchange at the leaf scale of Populus euphratica: a Farquhar et al. type biochemical sub-model of photosynthesis (Farquhar et al., 1980) and a Ball et al. type stomatal conductance sub-model (Ball et al., 1987). The photosynthesis parameters [including maximum carboxylation rate allowed by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (Vcmax), potential light-saturated electron transport rate (Jmax), triose phosphate utilization (TPU) and day respiration (Rd)] were determined by using the genetic algorithm (GA) method based on A/Ci data. Values of Vcmax and Jmax standardized at 25 °C were 75.09±1.36 (mean ± standard error), 117.27±2.47, respectively. The stomatal conductance sub-model was calibrated independently. Prediction of net photosynthesis by the coupled model agreed well with the validation data, but the model tended to underestimate transpiration rates. Overall, the combined model generally captured the diurnal patterns of CO2 and H2O exchange resulting from variation in temperature and irradiation.

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    Authors: Weerasinghe, H.; Schneider, U. A.; Löw, A.;

    This study describes a globally applicable method to determine the local suitability to implement water supply management strategies within the context of a river catchment. We apply this method, and develop a spatial analysis model named Geographic Water Management Potential (GWAMP). We retrieve input data from global data repositories and rescale these data to 1km spatial resolution to obtain a set of manageable input data. Potential runoff is calculated as an intermediate input using the Soil Conservation Service Curve Number (SCS-CN) equation. Multi Criteria Evaluation techniques are used to determine the suitability levels and relative importance of input parameters for water supply management. Accordingly, the model identifies, potential water harvesting- and storage sites for on-farm water storage, regional dams, and soil moisture conservation. We apply the model to two case-study locations, the Sao-Francisco and Nile catchments, which differ in their geographic and climatic conditions. The model results are validated against existing data on hydrologic networks, reservoir capacities and runoff. On average, GWAMP predictions of sites with high rain water storage suitability correlate well (83%) with the locations of existing regional dams and farm tanks. According to the results from testing and validation of the GWAMP we point out that the GWAMP can be used identify potential sites for rain water harvesting and storage technologies in a given catchment.

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    Authors: Shaughnessy, Andrew R.; Gu, Xin; Wen, Tao; Brantley, Susan L.;

    Endmember mixing analysis (EMMA) is often used by hydrogeochemists to interpret the sources of stream solutes, but variations in stream concentrations and discharges remain difficult to explain. We discovered that machine learning can be used to highlight patterns in stream chemistry that reveal information about sources of solutes and subsurface groundwater flowpaths. The investigation has implications, in turn, for the balance of CO2 in the atmosphere. For example, CO2-driven weathering of silicate minerals removes carbon from the atmosphere over ∼106-year timescales. Weathering of another common mineral, pyrite, releases sulfuric acid that in turn causes dissolution of carbonates. In that process, however, CO2 is released instead of sequestered from the atmosphere. Thus, understanding long-term global CO2 sequestration by weathering requires quantification of CO2- versus H2SO4-driven reactions. Most researchers estimate such weathering fluxes from stream chemistry, but interpreting the reactant minerals and acids dissolved in streams has been fraught with difficulty. We apply a machine-learning technique to EMMA in three watersheds to determine the extent of mineral dissolution by each acid, without pre-defining the endmembers. The results show that the watersheds continuously or intermittently sequester CO2, but the extent of CO2 drawdown is diminished in areas heavily affected by acid rain. Prior to applying the new algorithm, CO2 drawdown was overestimated. The new technique, which elucidates the importance of different subsurface flowpaths and long-timescale changes in the watersheds, should have utility as a new EMMA for investigating water resources worldwide.

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    Authors: Riedl, Andreas; id_orcid0000-0001-9806-7315; Li, Yafei; Eugster, Jon; Buchmann, Nina; id_orcid0000-0003-0826-2980; +1 Authors

    Non-rainfall water (NRW), defined here as dew, hoar frost, fog, rime, and water vapour adsorption, might be a relevant water source for ecosystems, especially during summer drought periods. These water inputs are often not considered in ecohydrological studies, because water amounts of NRW events are rather small and therefore difficult to measure. Here we present a novel micro-lysimeter (ML) system and its application which allows us to quantify very small water inputs from NRW during rain-free periods with an unprecedented high accuracy of ±0.25 g, which corresponds to ±0.005 mm water input. This is possible with an improved ML design paired with individual ML calibrations in combination with high-frequency measurements at 3.3 Hz and an efficient low-pass filtering to reduce noise level. With a set of ancillary sensors, the ML system furthermore allows differentiation between different types of NRW inputs, i.e. dew, hoar frost, fog, rime, and the combinations among these, but also additional events when condensation on leaves is less probable, such as water vapour adsorption events. In addition, our ML system design allows one to minimize deviations from natural conditions in terms of canopy and soil temperatures, plant growth, and soil moisture. This is found to be a crucial aspect for obtaining realistic NRW measurements in short-statured grasslands. Soil temperatures were higher in the ML compared to the control, and thus further studies should focus on improving the thermal soil regime of ML. Our ML system has proven to be useful for high-accuracy, long-term measurements of NRW on short-statured vegetation-like grasslands. Measurements with the ML system at a field site in Switzerland showed that NRW input occurred frequently, with 127 events over 12 months with a total NRW input of 15.9 mm. Drainage-water flow of the ML was not measured, and therefore the NRW inputs might be conservative estimates. High average monthly NRW inputs were measured during summer months, suggesting a high ecohydrological relevance of NRW inputs for temperate grasslands. Hydrology and Earth System Sciences, 26 (1) ISSN:1027-5606 ISSN:1607-7938

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    Article . 2022
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    ETH Zürich Research Collection
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    Authors: Bernard-Jannin, Léonard; Binet, Stéphane; Gogo, Sébastien; Leroy, Fabien; +5 Authors

    Hydrological disturbances could increase dissolved organic carbon (DOC) exports through runoff and leaching, reducing the potential carbon sink function of peatlands. The objective of this study was to assess the impact of hydrological restoration 15 on hydrological processes and DOC dynamics in a rehabilitated Sphagnum–dominated peatland. A conceptual hydrological model calibrated on the water table and coupled with a biogeochemical module was applied to La Guette peatland (France), which experienced a rewetting action on February 2014. The model (ten calibrated parameters) reproduced water table and pore water DOC concentration time series (01/04/2014 to 15/07/2017) in two contrasted locations (rewetted and control) of the peatland. Hydrological restoration was found to impact the water balance through a decrease in slow deep drainage and 20 an increase in fast superficial runoff. Observed DOC concentrations were higher in summer in the rewetted location compared to the control and were linked with a difference in dissolved organic matter composition analyzed by fluorescence. Hydrological conditions, especially the severity of the water table drawdown, were identified as the major factors controlling DOC concentration dynamics. The results of the simulation suggest that the hydrological restoration did not affect DOC loads, at least on a short-term period (3 years). However, it impacted the temporal dynamics of DOC exports, which were the 25 most episodic and mainly transported through fast surface runoff in the area affected by the restoration while slow deep drainage dominated DOC exports in the control area. In relation with dominant hydrological processes, exported DOC is expected to be derived from more recent organic matter of the top peat layer in the rewetted area than in the control area. Since it is calibrated on water table and DOC concentration, the model presented in this study proved to be a relevant tool to identify the main hydrological processes and factors controlling DOC dynamics in different areas of the same peatland. It is 30 also a suitable alternative to a discharge calibrated catchment model when the outlet is not easily identifiable. Hydrol. Earth Syst. Sci. Discuss., https://doi. International audience

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    Authors: R. Baatz; H.-J. Hendricks Franssen; X. Han; T. Hoar; +2 Authors

    Land surface models describe biogeophysical and biogeochemical processes at the land surface, and represent thelower boundary condition of atmospheric circulation models. Their key role is the quantification of mass and energyfluxes between the land surface and the atmosphere. Predictions with land surface models are affected by manyunknown parameters, uncertain meteorological forcings and incomplete process understanding. Measurement data(e.g., soil moisture) can help to improve land surface model predictions. However, soil moisture products obtainedfrom satellite remote sensing are normally available at a very coarse resolution and give information on the upperfew centimetres of the soil only. Therefore, the recently developed Cosmic Ray Neutron Sensors (CRNS) areof high interest for predictions by land surface models, because they measure neutron count intensity, which isrelated to integral soil moisture content at the field scale (about 20 hectares). High resolution land surface modelsare also able to provide solutions at the same scale. In this study, we investigated whether the assimilation ofsoil moisture retrievals from CRNS data measured by a network of nine CRNS located in the Rur catchmentin Germany (2354 km2) can improve land surface model prediction. The assimilation of soil moisture retrievalsfrom neutron count intensity data was used to update model states and parameters of the land surface modelCLM 4.5 over a two year time period, followed by a one year evaluation period without updates. This updatingwas done with the local ensemble transform Kalman filter. The real world experiment tested the value of CRNSusing jackknifing experiments and three different initial soil maps. During the assimilation period, soil moisturepredictions generally improved, for a biased soil map from an RMSE of 0.11 cm3/cm3 in the open loop run to0.03 cm3/cm3 while during the evaluation period soil moisture predictions improved from 0.12 cm3/cm3 to 0.06cm3/cm3. Improved soil parameters showed also an impact on latent heat and sensible heat flux, particularly duringthe summer period when evapotranspiration was soil moisture limited. The main conclusion from this study is thata network of CRNS is helpful to improve soil moisture predictions with a land surface model, in spite of the factthat in this study only nine CRNS were available for a catchment of size 2354 km2.

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    Authors: Dubois, Emmanuel; Doummar, Joanna; Pistre, Séverin; Larocque, Marie;

    Flow in complex karst aquifers is challenging to conceptualize and model, especially in poorly investigated areas, in semiarid climates, and under changing climatic conditions; however, it is necessary in order to implement long-term sustainable water management practices. Thus, the objectives of this work were to propose a calibration approach based on time series analyses for a karst aquifer and to assess the impact of climate change on spring discharge. Based on more than 3 years of high-resolution continuous monitoring, a semi-distributed lumped model was calibrated and validated for the Qachqouch karst spring, north of Beirut (Lebanon). Time series analyses and decomposition of spring hydrographs revealed that the system has a high regulatory function, with considerable storage capacity providing stable flow (minimum flow of 0.2 m3 s−1) during the dry season and with flow rates exceeding 10 m3 s−1 during the wet season, which is similar to other karst aquifers in the region. Based on this detailed understanding of the hydrodynamics of the system, the model geometry and parameters were validated. Three linear reservoirs were implemented to reproduce the combined contribution of the different flow components of the system. A satisfactory simulation (Nash–Sutcliffe efficiency coefficient, NSE, of 0.72) of the measured spring flow rates was obtained after calibration. Climate change conditions (+1 to +3 ∘C warming, −10 % to −30 % less precipitation annually, and the intensification of rain events) were added to a baseline climatic year to produce scenarios of expected spring flow responses. Results show that the Qachqouch karst aquifer is sensitive to decreasing rainfall, which is associated with more pronounced recessions, with flow rates decreasing by 34 % and 1-month longer dry periods. Because of the limited influence of snow on the spring flow rate, a warming climate has less impact on spring flow conditions than a reduction in precipitation. Although the model shows that increasing rainfall intensity induces larger floods, recessions, and shorter low-flow periods, the real impact of high-intensity precipitation events remains uncertain, as the model does not account for complex unsaturated and epikarstic processes. This work shows that calibrating a semi-distributed lumped model using time series analyses can be an efficient approach to improve simulations of complex karst aquifers, thereby providing useful models for long-term sustainable water management.

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    Authors: Dance, S. L.; Zou, Q. P.;

    Ensemble predictions are being used more frequently to model the propagation of uncertainty through complex, coupled meteorological, hydrological and coastal models, with the goal of better characterising flood risk. In this paper, we consider the issues that we judge to be important when designing and evaluating ensemble predictions, and make recommendations for the guidance of future research.

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    Authors: Xiao, Shangbin; Liu, Liu; Wang, Wei; Lorke, Andreas; +2 Authors

    Biogenic greenhouse gas emissions, e.g., of methane (CH4) and carbon dioxide (CO2) from inland waters, contribute substantially to global warming. In aquatic systems, dissolved greenhouse gases are highly heterogeneous in both space and time. To better understand the biological and physical processes that affect sources and sinks of both CH4 and CO2, their dissolved concentrations need to be measured with high spatial and temporal resolution. To achieve this goal, we developed the Fast-Response Automated Gas Equilibrator (FaRAGE) for real-time in situ measurement of dissolved CH4 and CO2 concentrations at the water surface and in the water column. FaRAGE can achieve an exceptionally short response time (t95 %=12 s when including the response time of the gas analyzer) while retaining an equilibration ratio of 62.6 % and a measurement accuracy of 0.5 % for CH4. A similar performance was observed for dissolved CO2 (t95 %=10 s, equilibration ratio 67.1 %). An equilibration ratio as high as 91.8 % can be reached at the cost of a slightly increased response time (16 s). The FaRAGE is capable of continuously measuring dissolved CO2 and CH4 concentrations in the nM-to-sub mM (10−9–10−3 mol L−1) range with a detection limit of sub-nM (10−10 mol L−1), when coupling with a cavity ring-down greenhouse gas analyzer (Picarro GasScouter). FaRAGE allows for the possibility of mapping dissolved concentration in a “quasi” three-dimensional manner in lakes and provides an inexpensive alternative to other commercial gas equilibrators. It is simple to operate and suitable for continuous monitoring with a strong tolerance for suspended particles. While the FaRAGE is developed for inland waters, it can be also applied to ocean waters by tuning the gas–water mixing ratio. The FaRAGE is easily adapted to suit other gas analyzers expanding the range of potential applications, including nitrous oxide and isotopic composition of the gases.

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    Authors: Olarinoye, Tunde; Gleeson, Tom; Hartmann, Andreas;

    Analysis of karst spring recession hydrographs is essential for determining hydraulic parameters, geometric characteristics, and transfer mechanisms that describe the dynamic nature of karst aquifer systems. The extraction and separation of different fast- and slow-flow components constituting a karst spring recession hydrograph typically involve manual and subjective procedures. This subjectivity introduces a bias that exists, while manual procedures can introduce errors into the derived parameters representing the system. To provide an alternative recession extraction procedure that is automated, fully objective, and easy to apply, we modified traditional streamflow extraction methods to identify components relevant for karst spring recession analysis. Mangin's karst-specific recession analysis model was fitted to individual extracted recession segments to determine matrix and conduit recession parameters. We introduced different parameter optimization approaches into Mangin's model to increase the degree of freedom, thereby allowing for more parameter interaction. The modified recession extraction and parameter optimization approaches were tested on three karst springs under different climate conditions. Our results showed that the modified extraction methods are capable of distinguishing different recession components and derived parameters that reasonably represent the analyzed karst systems. We recorded an average Kling–Gupta efficiency KGE > 0.85 among all recession events simulated by the recession parameters derived from all combinations of recession extraction methods and parameter optimization approaches. While there are variabilities among parameters estimated by different combinations of extraction methods, optimization approaches, and seasons, we found much higher variability among individual recession events. We provided suggestions to reduce the uncertainty among individual recession events and raised questions about how to improve confidence in the system's attributes derived from recession parameters.

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    Authors: Zhu, G. F.; Li, X.; Su, Y. H.; Huang, C. L.;

    The following two models were combined to simultaneously predict CO2 and H2O gas exchange at the leaf scale of Populus euphratica: a Farquhar et al. type biochemical sub-model of photosynthesis (Farquhar et al., 1980) and a Ball et al. type stomatal conductance sub-model (Ball et al., 1987). The photosynthesis parameters [including maximum carboxylation rate allowed by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (Vcmax), potential light-saturated electron transport rate (Jmax), triose phosphate utilization (TPU) and day respiration (Rd)] were determined by using the genetic algorithm (GA) method based on A/Ci data. Values of Vcmax and Jmax standardized at 25 °C were 75.09±1.36 (mean ± standard error), 117.27±2.47, respectively. The stomatal conductance sub-model was calibrated independently. Prediction of net photosynthesis by the coupled model agreed well with the validation data, but the model tended to underestimate transpiration rates. Overall, the combined model generally captured the diurnal patterns of CO2 and H2O exchange resulting from variation in temperature and irradiation.

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    Article . 2010
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