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  • Open Access English
    Authors: 
    J. Janapati; B. K. Seela; P.-L. Lin; P.-L. Lin; P.-L. Lin; M.-T. Lee; E. Joseph; E. Joseph;
    Publisher: Copernicus Publications

    Information about the raindrop size distribution (RSD) is vital for comprehending the precipitation microphysics, improving the rainfall estimation algorithms, and appraising the rainfall erosivity. Previous research has revealed that the RSD exhibits diversity with geographical location and weather type, which leads to the assessment of the region and weather-specific RSDs. Based on long-term (2004 to 2016) disdrometer measurements in northern Taiwan, this study attempts to demonstrate the RSD aspects of summer seasons that were bifurcated into two weather conditions, namely typhoon (TY) and non-typhoon (NTY) rainfall. The results show a higher concentration of small drops and a lower concentration of large-sized drops in TY compared to NTY rainfall, and this behavior persisted even after characterizing the RSDs into different rainfall rate classes. RSDs expressed in gamma parameters show higher mass-weighted mean diameter (Dm) and lower normalized intercept parameter (Nw) values in NTY than TY rainfall. Moreover, sorting these two weather conditions (TY and NTY rainfall) into stratiform and convective regimes revealed a larger Dm in NTY than in TY rainfall. The RSD empirical relations used in the valuation of rainfall rate (Z–R, Dm–R, and Nw–R) and rainfall kinetic energy (KE–R and KE–Dm) were enumerated for TY and NTY rainfall, and they exhibited profound diversity between these two weather conditions. Attributions of RSD variability between the TY and NTY rainfall to the thermodynamical and microphysical processes are elucidated with the aid of reanalysis, remote sensing, and ground-based data sets.

  • Publication . Other literature type . Article . Preprint . 2016
    Open Access
    Authors: 
    S. Saffarpour; Andrew W. Western; Russell Adams; Jeffrey J. McDonnell;
    Publisher: Copernicus GmbH
    Project: ARC | An integrated investigati... (DP0987738)

    Abstract. Thresholds and hydrologic connectivity associated with runoff processes are a critical concept for understanding catchment hydrologic response at the event timescale. To date, most attention has focused on single runoff response types, and the role of multiple thresholds and flow path connectivities has not been made explicit. Here we first summarise existing knowledge on the interplay between thresholds, connectivity and runoff processes at the hillslope–small catchment scale into a single figure and use it in examining how runoff response and the catchment threshold response to rainfall affect a suite of runoff generation mechanisms in a small agricultural catchment. A 1.37 ha catchment in the Lang Lang River catchment, Victoria, Australia, was instrumented and hourly data of rainfall, runoff, shallow groundwater level and isotope water samples were collected. The rainfall, runoff and antecedent soil moisture data together with water levels at several shallow piezometers are used to identify runoff processes in the study site. We use isotope and major ion results to further support the findings of the hydrometric data. We analyse 60 rainfall events that produced 38 runoff events over two runoff seasons. Our results show that the catchment hydrologic response was typically controlled by the Antecedent Soil Moisture Index and rainfall characteristics. There was a strong seasonal effect in the antecedent moisture conditions that led to marked seasonal-scale changes in runoff response. Analysis of shallow well data revealed that streamflows early in the runoff season were dominated primarily by saturation excess overland flow from the riparian area. As the runoff season progressed, the catchment soil water storage increased and the hillslopes connected to the riparian area. The hillslopes transferred a significant amount of water to the riparian zone during and following events. Then, during a particularly wet period, this connectivity to the riparian zone, and ultimately to the stream, persisted between events for a period of 1 month. These findings are supported by isotope results which showed the dominance of pre-event water, together with significant contributions of event water early (rising limb and peak) in the event hydrograph. Based on a combination of various hydrometric analyses and some isotope and major ion data, we conclude that event runoff at this site is typically a combination of subsurface event flow and saturation excess overland flow. However, during high intensity rainfall events, flashy catchment flow was observed even though the soil moisture threshold for activation of subsurface flow was not exceeded. We hypothesise that this was due to the activation of infiltration excess overland flow and/or fast lateral flow through preferential pathways on the hillslope and saturation overland flow from the riparian zone.

  • Publication . Article . Other literature type . 2018
    Open Access English
    Authors: 
    Shawn J. Marshall;
    Publisher: Copernicus Publications
    Project: NSERC

    Abstract. Observations of high-elevation meteorological conditions, glacier mass balance, and glacier run-off are sparse in western Canada and the Canadian Rocky Mountains, leading to uncertainty about the importance of glaciers to regional water resources. This needs to be quantified so that the impacts of ongoing glacier recession can be evaluated with respect to alpine ecology, hydroelectric operations, and water resource management. In this manuscript the seasonal evolution of glacier run-off is assessed for an alpine watershed on the continental divide in the Canadian Rocky Mountains. The study area is a headwaters catchment of the Bow River, which flows eastward to provide an important supply of water to the Canadian prairies. Meteorological, snowpack, and surface energy balance data collected at Haig Glacier from 2002 to 2013 were analysed to evaluate glacier mass balance and run-off. Annual specific discharge from snow- and ice-melt on Haig Glacier averaged 2350 mm water equivalent from 2002 to 2013, with 42% of the run-off derived from melting of glacier ice and firn, i.e. water stored in the glacier reservoir. This is an order of magnitude greater than the annual specific discharge from non-glacierized parts of the Bow River basin. From 2002 to 2013, meltwater derived from the glacier storage was equivalent to 5–6% of the flow of the Bow River in Calgary in late summer and 2–3% of annual discharge. The basin is typical of most glacier-fed mountain rivers, where the modest and declining extent of glacierized area in the catchment limits the glacier contribution to annual run-off.

  • Open Access English
    Authors: 
    Hartmut Holländer; Helge Bormann; Theresa Blume; Wouter Buytaert; Giovanni Battista Chirico; Jean-François Exbrayat; David Gustafsson; H. Hölzel; T. Krauße; Philipp Kraft; +3 more
    Publisher: Copernicus Publications
    Countries: Switzerland, Germany

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers – using the model of their choice – for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements. Hydrology and Earth System Sciences, 18 (6) ISSN:1027-5606 ISSN:1607-7938

  • Open Access English
    Authors: 
    H. Cai; H. Cai; P. Zhang; P. Zhang; E. Garel; P. Matte; S. Hu; S. Hu; F. Liu; F. Liu; +2 more
    Country: Portugal

    Assessing the impacts of both natural (e.g., tidal forcing from the ocean) and human-induced changes (e.g., dredging for navigation, land reclamation) on estuarine morphology is particularly important for the protection and management of the estuarine environment. In this study, a novel analytical approach is proposed for the assessment of estuarine morphological evolution in terms of tidally averaged depth on the basis of the observed water levels along the estuary. The key lies in deriving a relationship between wave celerity and tidal damping or amplification. For given observed water levels at two gauging stations, it is possible to have a first estimation of both wave celerity (distance divided by tidal travelling time) and tidal damping or amplification rate (tidal range difference divided by distance), which can then be used to predict the morphological changes via an inverse analytical model for tidal hydrodynamics. The proposed method is applied to the Lingdingyang Bay of the Pearl River Estuary, located on the southern coast of China, to analyse the historical development of the tidal hydrodynamics and morphological evolution. The analytical results show surprisingly good correspondence with observed water depth and volume in this system. The merit of the proposed method is that it provides a simple approach for understanding the decadal evolution of the estuarine morphology through the use of observed water levels, which are usually available and can be easily measured. National Key R&D of China (Grant No. 2016YFC0402601), National Natural Science Foundation of China (Grant No. 51979296, 51709287, 41706088, 41476073), Fundamental Research Funds for the Central Universities (No.18lgpy29) and from the Water Resource Science and Technology Innovation Program of Guangdong Province (Grant No. 2016-20, 2016-21). The work of the second author was supported by FCT research contracts IF/00661/2014/CP1234. info:eu-repo/semantics/submittedVersion

  • Open Access English
    Authors: 
    C. Scudeler; C. Scudeler; L. Pangle; D. Pasetto; G.-Y. Niu; G.-Y. Niu; T. Volkmann; C. Paniconi; M. Putti; P. Troch; +1 more
    Publisher: Copernicus Publications
    Countries: Italy, Switzerland
    Project: NSF | COLLABORATIVE RESEARCH: C... (1417097), NSF | Collaborative Research: H... (1344552)

    Abstract. This paper explores the challenges of model parameterization and process representation when simulating multiple hydrologic responses from a highly controlled unsaturated flow and transport experiment with a physically based model. The experiment, conducted at the Landscape Evolution Observatory (LEO), involved alternate injections of water and deuterium-enriched water into an initially very dry hillslope. The multivariate observations included point measures of water content and tracer concentration in the soil, total storage within the hillslope, and integrated fluxes of water and tracer through the seepage face. The simulations were performed with a three-dimensional finite element model that solves the Richards and advection–dispersion equations. Integrated flow, integrated transport, distributed flow, and distributed transport responses were successively analyzed, with parameterization choices at each step supported by standard model performance metrics. In the first steps of our analysis, where seepage face flow, water storage, and average concentration at the seepage face were the target responses, an adequate match between measured and simulated variables was obtained using a simple parameterization consistent with that from a prior flow-only experiment at LEO. When passing to the distributed responses, it was necessary to introduce complexity to additional soil hydraulic parameters to obtain an adequate match for the point-scale flow response. This also improved the match against point measures of tracer concentration, although model performance here was considerably poorer. This suggests that still greater complexity is needed in the model parameterization, or that there may be gaps in process representation for simulating solute transport phenomena in very dry soils.

  • Open Access English
    Authors: 
    A. Maclean; Bryan A. Tolson; Frank Seglenieks; Eric D. Soulis;

    Abstract. The spatially distributed MESH hydrologic model (Pietroniro et al., 2007) was successfully calibrated and then validated for the prediction of snow water equivalent (SWE) and streamflow in the Reynolds Creek Experimental Watershed in Idaho, USA. The tradeoff between fitting to SWE versus streamflow data was assessed and showed that both could be simultaneously predicted with good quality by the MESH model. Not surprisingly, calibrating to only one objective (e.g. SWE) yielded poor simulation results for the other objective (e.g. streamflow). The multiobjective calibration problem in this study was efficiently solved via a simple weighted objective function approach and analyses showed that the approach yielded a balanced solution between the objectives. Our approach therefore eliminated the need to rely on a potentially more computationally intensive evolutionary multiobjective algorithm to approximate the entire tradeoff surface between objectives. Additional calibration experiments showed that for our calibration computational budget (2000 model evaluations), the autocalibration procedure would fail without being initialized to a model parameter set carefully determined for this specific case study. This study serves as a benchmark for MESH model simulation accuracy which can be compared with future versions of MESH.

  • Open Access
    Authors: 
    Chunwei Liu; Ge Sun; Steven G. McNulty; Asko Noormets; Yuan Fang;
    Publisher: Copernicus GmbH
    Project: NSERC

    The evapotranspiration / potential evapotranspiration (AET / PET) ratio is traditionally termed as the crop coefficient (Kc) and has been generally used as ecosystem evaporative stress index. In the current hydrology literature, Kc has been widely used as a parameter to estimate crop water demand by water managers but has not been well examined for other types of ecosystems such as forests and other perennial vegetation. Understanding the seasonal dynamics of this variable for all ecosystems is important for projecting the ecohydrological responses to climate change and accurately quantifying water use at watershed to global scales. This study aimed at deriving monthly Kc for multiple vegetation cover types and understanding its environmental controls by analyzing the accumulated global eddy flux (FLUXNET) data. We examined monthly Kc data for seven vegetation covers, including open shrubland (OS), cropland (CRO), grassland (GRA), deciduous broad leaf forest (DBF), evergreen needle leaf forest (ENF), evergreen broad leaf forest (EBF), and mixed forest (MF), across 81 sites. We found that, except for evergreen forests (EBF and ENF), Kc values had large seasonal variation across all land covers. The spatial variability of Kc was well explained by latitude, suggesting site factors are a major control on Kc. Seasonally, Kc increased significantly with precipitation in the summer months, except in EBF. Moreover, leaf area index (LAI) significantly influenced monthly Kc in all land covers, except in EBF. During the peak growing season, forests had the highest Kc values, while croplands (CRO) had the lowest. We developed a series of multivariate linear monthly regression models for Kc by land cover type and season using LAI, site latitude, and monthly precipitation as independent variables. The Kc models are useful for understanding water stress in different ecosystems under climate change and variability as well as for estimating seasonal ET for large areas with mixed land covers.

  • Open Access English
    Authors: 
    Anaïs Barella-Ortiz; Jan Polcher; Patricia de Rosnay; Maria Piles; Emiliano Gelati;
    Publisher: Copernicus Publications
    Countries: Spain, France, Spain
    Project: EC | EARTH2OBSERVE (603608)

    L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled sets were estimated using a radiative transfer model and state variables from two land-surface models: (i) ORCHIDEE and (ii) H-TESSEL. The radiative transfer model used is the CMEM. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations at the moment. Further hypotheses are proposed and will be explored in a forthcoming paper. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies This work contributes to the FP7 Earth2Observe project under grant agreement no. 603608 19 pges, 10 figures, 6 tables Peer Reviewed

  • Publication . Other literature type . Article . Preprint . 2010
    Open Access
    Authors: 
    Xing Fang; John W. Pomeroy; Cherie J. Westbrook; Xulin Guo; A. G. Minke; T. Brown;
    Publisher: Copernicus GmbH

    Abstract. The eastern Canadian Prairies are dominated by cropland, pasture, woodland and wetland areas. The region is characterized by many poor and internal drainage systems and large amounts of surface water storage. Consequently, basins here have proven challenging to hydrological model predictions which assume good drainage to stream channels. The Cold Regions Hydrological Modelling platform (CRHM) is an assembly system that can be used to set up physically based, flexible, object oriented models. CRHM was used to create a prairie hydrological model for the externally drained Smith Creek Research Basin (~400 km2), east-central Saskatchewan. Physically based modules were sequentially linked in CRHM to simulate snow processes, frozen soils, variable contributing area and wetland storage and runoff generation. Five "representative basins" (RBs) were used and each was divided into seven hydrological response units (HRUs): fallow, stubble, grassland, river channel, open water, woodland, and wetland as derived from a supervised classification of SPOT 5 imagery. Two types of modelling approaches calibrated and uncalibrated, were set up for 2007/08 and 2008/09 simulation periods. For the calibrated modelling, only the surface depression capacity of upland area was calibrated in the 2007/08 simulation period by comparing simulated and observed hydrographs; while other model parameters and all parameters in the uncalibrated modelling were estimated from field observations of soils and vegetation cover, SPOT 5 imagery, and analysis of drainage network and wetland GIS datasets as well as topographic map based and LiDAR DEMs. All the parameters except for the initial soil properties and antecedent wetland storage were kept the same in the 2008/09 simulation period. The model performance in predicting snowpack, soil moisture and streamflow was evaluated and comparisons were made between the calibrated and uncalibrated modelling for both simulation periods. Calibrated and uncalibrated predictions of snow accumulation were very similar and compared fairly well with the distributed field observations for the 2007/08 period with slightly poorer results for the 2008/09 period. Soil moisture content at a point during the early spring was adequately simulated and very comparable between calibrated and uncalibrated results for both simulation periods. The calibrated modelling had somewhat better performance in simulating spring streamflow in both simulation periods, whereas the uncalibrated modelling was still able to capture the streamflow hydrographs with good accuracy. This suggests that prediction of prairie basins without calibration is possible if sufficient data on meteorology, basin landcover and physiography are available.

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Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
433 Research products, page 1 of 44
  • Open Access English
    Authors: 
    J. Janapati; B. K. Seela; P.-L. Lin; P.-L. Lin; P.-L. Lin; M.-T. Lee; E. Joseph; E. Joseph;
    Publisher: Copernicus Publications

    Information about the raindrop size distribution (RSD) is vital for comprehending the precipitation microphysics, improving the rainfall estimation algorithms, and appraising the rainfall erosivity. Previous research has revealed that the RSD exhibits diversity with geographical location and weather type, which leads to the assessment of the region and weather-specific RSDs. Based on long-term (2004 to 2016) disdrometer measurements in northern Taiwan, this study attempts to demonstrate the RSD aspects of summer seasons that were bifurcated into two weather conditions, namely typhoon (TY) and non-typhoon (NTY) rainfall. The results show a higher concentration of small drops and a lower concentration of large-sized drops in TY compared to NTY rainfall, and this behavior persisted even after characterizing the RSDs into different rainfall rate classes. RSDs expressed in gamma parameters show higher mass-weighted mean diameter (Dm) and lower normalized intercept parameter (Nw) values in NTY than TY rainfall. Moreover, sorting these two weather conditions (TY and NTY rainfall) into stratiform and convective regimes revealed a larger Dm in NTY than in TY rainfall. The RSD empirical relations used in the valuation of rainfall rate (Z–R, Dm–R, and Nw–R) and rainfall kinetic energy (KE–R and KE–Dm) were enumerated for TY and NTY rainfall, and they exhibited profound diversity between these two weather conditions. Attributions of RSD variability between the TY and NTY rainfall to the thermodynamical and microphysical processes are elucidated with the aid of reanalysis, remote sensing, and ground-based data sets.

  • Publication . Other literature type . Article . Preprint . 2016
    Open Access
    Authors: 
    S. Saffarpour; Andrew W. Western; Russell Adams; Jeffrey J. McDonnell;
    Publisher: Copernicus GmbH
    Project: ARC | An integrated investigati... (DP0987738)

    Abstract. Thresholds and hydrologic connectivity associated with runoff processes are a critical concept for understanding catchment hydrologic response at the event timescale. To date, most attention has focused on single runoff response types, and the role of multiple thresholds and flow path connectivities has not been made explicit. Here we first summarise existing knowledge on the interplay between thresholds, connectivity and runoff processes at the hillslope–small catchment scale into a single figure and use it in examining how runoff response and the catchment threshold response to rainfall affect a suite of runoff generation mechanisms in a small agricultural catchment. A 1.37 ha catchment in the Lang Lang River catchment, Victoria, Australia, was instrumented and hourly data of rainfall, runoff, shallow groundwater level and isotope water samples were collected. The rainfall, runoff and antecedent soil moisture data together with water levels at several shallow piezometers are used to identify runoff processes in the study site. We use isotope and major ion results to further support the findings of the hydrometric data. We analyse 60 rainfall events that produced 38 runoff events over two runoff seasons. Our results show that the catchment hydrologic response was typically controlled by the Antecedent Soil Moisture Index and rainfall characteristics. There was a strong seasonal effect in the antecedent moisture conditions that led to marked seasonal-scale changes in runoff response. Analysis of shallow well data revealed that streamflows early in the runoff season were dominated primarily by saturation excess overland flow from the riparian area. As the runoff season progressed, the catchment soil water storage increased and the hillslopes connected to the riparian area. The hillslopes transferred a significant amount of water to the riparian zone during and following events. Then, during a particularly wet period, this connectivity to the riparian zone, and ultimately to the stream, persisted between events for a period of 1 month. These findings are supported by isotope results which showed the dominance of pre-event water, together with significant contributions of event water early (rising limb and peak) in the event hydrograph. Based on a combination of various hydrometric analyses and some isotope and major ion data, we conclude that event runoff at this site is typically a combination of subsurface event flow and saturation excess overland flow. However, during high intensity rainfall events, flashy catchment flow was observed even though the soil moisture threshold for activation of subsurface flow was not exceeded. We hypothesise that this was due to the activation of infiltration excess overland flow and/or fast lateral flow through preferential pathways on the hillslope and saturation overland flow from the riparian zone.

  • Publication . Article . Other literature type . 2018
    Open Access English
    Authors: 
    Shawn J. Marshall;
    Publisher: Copernicus Publications
    Project: NSERC

    Abstract. Observations of high-elevation meteorological conditions, glacier mass balance, and glacier run-off are sparse in western Canada and the Canadian Rocky Mountains, leading to uncertainty about the importance of glaciers to regional water resources. This needs to be quantified so that the impacts of ongoing glacier recession can be evaluated with respect to alpine ecology, hydroelectric operations, and water resource management. In this manuscript the seasonal evolution of glacier run-off is assessed for an alpine watershed on the continental divide in the Canadian Rocky Mountains. The study area is a headwaters catchment of the Bow River, which flows eastward to provide an important supply of water to the Canadian prairies. Meteorological, snowpack, and surface energy balance data collected at Haig Glacier from 2002 to 2013 were analysed to evaluate glacier mass balance and run-off. Annual specific discharge from snow- and ice-melt on Haig Glacier averaged 2350 mm water equivalent from 2002 to 2013, with 42% of the run-off derived from melting of glacier ice and firn, i.e. water stored in the glacier reservoir. This is an order of magnitude greater than the annual specific discharge from non-glacierized parts of the Bow River basin. From 2002 to 2013, meltwater derived from the glacier storage was equivalent to 5–6% of the flow of the Bow River in Calgary in late summer and 2–3% of annual discharge. The basin is typical of most glacier-fed mountain rivers, where the modest and declining extent of glacierized area in the catchment limits the glacier contribution to annual run-off.

  • Open Access English
    Authors: 
    Hartmut Holländer; Helge Bormann; Theresa Blume; Wouter Buytaert; Giovanni Battista Chirico; Jean-François Exbrayat; David Gustafsson; H. Hölzel; T. Krauße; Philipp Kraft; +3 more
    Publisher: Copernicus Publications
    Countries: Switzerland, Germany

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers – using the model of their choice – for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements. Hydrology and Earth System Sciences, 18 (6) ISSN:1027-5606 ISSN:1607-7938

  • Open Access English
    Authors: 
    H. Cai; H. Cai; P. Zhang; P. Zhang; E. Garel; P. Matte; S. Hu; S. Hu; F. Liu; F. Liu; +2 more
    Country: Portugal

    Assessing the impacts of both natural (e.g., tidal forcing from the ocean) and human-induced changes (e.g., dredging for navigation, land reclamation) on estuarine morphology is particularly important for the protection and management of the estuarine environment. In this study, a novel analytical approach is proposed for the assessment of estuarine morphological evolution in terms of tidally averaged depth on the basis of the observed water levels along the estuary. The key lies in deriving a relationship between wave celerity and tidal damping or amplification. For given observed water levels at two gauging stations, it is possible to have a first estimation of both wave celerity (distance divided by tidal travelling time) and tidal damping or amplification rate (tidal range difference divided by distance), which can then be used to predict the morphological changes via an inverse analytical model for tidal hydrodynamics. The proposed method is applied to the Lingdingyang Bay of the Pearl River Estuary, located on the southern coast of China, to analyse the historical development of the tidal hydrodynamics and morphological evolution. The analytical results show surprisingly good correspondence with observed water depth and volume in this system. The merit of the proposed method is that it provides a simple approach for understanding the decadal evolution of the estuarine morphology through the use of observed water levels, which are usually available and can be easily measured. National Key R&D of China (Grant No. 2016YFC0402601), National Natural Science Foundation of China (Grant No. 51979296, 51709287, 41706088, 41476073), Fundamental Research Funds for the Central Universities (No.18lgpy29) and from the Water Resource Science and Technology Innovation Program of Guangdong Province (Grant No. 2016-20, 2016-21). The work of the second author was supported by FCT research contracts IF/00661/2014/CP1234. info:eu-repo/semantics/submittedVersion

  • Open Access English
    Authors: 
    C. Scudeler; C. Scudeler; L. Pangle; D. Pasetto; G.-Y. Niu; G.-Y. Niu; T. Volkmann; C. Paniconi; M. Putti; P. Troch; +1 more
    Publisher: Copernicus Publications
    Countries: Italy, Switzerland
    Project: NSF | COLLABORATIVE RESEARCH: C... (1417097), NSF | Collaborative Research: H... (1344552)

    Abstract. This paper explores the challenges of model parameterization and process representation when simulating multiple hydrologic responses from a highly controlled unsaturated flow and transport experiment with a physically based model. The experiment, conducted at the Landscape Evolution Observatory (LEO), involved alternate injections of water and deuterium-enriched water into an initially very dry hillslope. The multivariate observations included point measures of water content and tracer concentration in the soil, total storage within the hillslope, and integrated fluxes of water and tracer through the seepage face. The simulations were performed with a three-dimensional finite element model that solves the Richards and advection–dispersion equations. Integrated flow, integrated transport, distributed flow, and distributed transport responses were successively analyzed, with parameterization choices at each step supported by standard model performance metrics. In the first steps of our analysis, where seepage face flow, water storage, and average concentration at the seepage face were the target responses, an adequate match between measured and simulated variables was obtained using a simple parameterization consistent with that from a prior flow-only experiment at LEO. When passing to the distributed responses, it was necessary to introduce complexity to additional soil hydraulic parameters to obtain an adequate match for the point-scale flow response. This also improved the match against point measures of tracer concentration, although model performance here was considerably poorer. This suggests that still greater complexity is needed in the model parameterization, or that there may be gaps in process representation for simulating solute transport phenomena in very dry soils.

  • Open Access English
    Authors: 
    A. Maclean; Bryan A. Tolson; Frank Seglenieks; Eric D. Soulis;

    Abstract. The spatially distributed MESH hydrologic model (Pietroniro et al., 2007) was successfully calibrated and then validated for the prediction of snow water equivalent (SWE) and streamflow in the Reynolds Creek Experimental Watershed in Idaho, USA. The tradeoff between fitting to SWE versus streamflow data was assessed and showed that both could be simultaneously predicted with good quality by the MESH model. Not surprisingly, calibrating to only one objective (e.g. SWE) yielded poor simulation results for the other objective (e.g. streamflow). The multiobjective calibration problem in this study was efficiently solved via a simple weighted objective function approach and analyses showed that the approach yielded a balanced solution between the objectives. Our approach therefore eliminated the need to rely on a potentially more computationally intensive evolutionary multiobjective algorithm to approximate the entire tradeoff surface between objectives. Additional calibration experiments showed that for our calibration computational budget (2000 model evaluations), the autocalibration procedure would fail without being initialized to a model parameter set carefully determined for this specific case study. This study serves as a benchmark for MESH model simulation accuracy which can be compared with future versions of MESH.

  • Open Access
    Authors: 
    Chunwei Liu; Ge Sun; Steven G. McNulty; Asko Noormets; Yuan Fang;
    Publisher: Copernicus GmbH
    Project: NSERC

    The evapotranspiration / potential evapotranspiration (AET / PET) ratio is traditionally termed as the crop coefficient (Kc) and has been generally used as ecosystem evaporative stress index. In the current hydrology literature, Kc has been widely used as a parameter to estimate crop water demand by water managers but has not been well examined for other types of ecosystems such as forests and other perennial vegetation. Understanding the seasonal dynamics of this variable for all ecosystems is important for projecting the ecohydrological responses to climate change and accurately quantifying water use at watershed to global scales. This study aimed at deriving monthly Kc for multiple vegetation cover types and understanding its environmental controls by analyzing the accumulated global eddy flux (FLUXNET) data. We examined monthly Kc data for seven vegetation covers, including open shrubland (OS), cropland (CRO), grassland (GRA), deciduous broad leaf forest (DBF), evergreen needle leaf forest (ENF), evergreen broad leaf forest (EBF), and mixed forest (MF), across 81 sites. We found that, except for evergreen forests (EBF and ENF), Kc values had large seasonal variation across all land covers. The spatial variability of Kc was well explained by latitude, suggesting site factors are a major control on Kc. Seasonally, Kc increased significantly with precipitation in the summer months, except in EBF. Moreover, leaf area index (LAI) significantly influenced monthly Kc in all land covers, except in EBF. During the peak growing season, forests had the highest Kc values, while croplands (CRO) had the lowest. We developed a series of multivariate linear monthly regression models for Kc by land cover type and season using LAI, site latitude, and monthly precipitation as independent variables. The Kc models are useful for understanding water stress in different ecosystems under climate change and variability as well as for estimating seasonal ET for large areas with mixed land covers.

  • Open Access English
    Authors: 
    Anaïs Barella-Ortiz; Jan Polcher; Patricia de Rosnay; Maria Piles; Emiliano Gelati;
    Publisher: Copernicus Publications
    Countries: Spain, France, Spain
    Project: EC | EARTH2OBSERVE (603608)

    L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled sets were estimated using a radiative transfer model and state variables from two land-surface models: (i) ORCHIDEE and (ii) H-TESSEL. The radiative transfer model used is the CMEM. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations at the moment. Further hypotheses are proposed and will be explored in a forthcoming paper. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies This work contributes to the FP7 Earth2Observe project under grant agreement no. 603608 19 pges, 10 figures, 6 tables Peer Reviewed

  • Publication . Other literature type . Article . Preprint . 2010
    Open Access
    Authors: 
    Xing Fang; John W. Pomeroy; Cherie J. Westbrook; Xulin Guo; A. G. Minke; T. Brown;
    Publisher: Copernicus GmbH

    Abstract. The eastern Canadian Prairies are dominated by cropland, pasture, woodland and wetland areas. The region is characterized by many poor and internal drainage systems and large amounts of surface water storage. Consequently, basins here have proven challenging to hydrological model predictions which assume good drainage to stream channels. The Cold Regions Hydrological Modelling platform (CRHM) is an assembly system that can be used to set up physically based, flexible, object oriented models. CRHM was used to create a prairie hydrological model for the externally drained Smith Creek Research Basin (~400 km2), east-central Saskatchewan. Physically based modules were sequentially linked in CRHM to simulate snow processes, frozen soils, variable contributing area and wetland storage and runoff generation. Five "representative basins" (RBs) were used and each was divided into seven hydrological response units (HRUs): fallow, stubble, grassland, river channel, open water, woodland, and wetland as derived from a supervised classification of SPOT 5 imagery. Two types of modelling approaches calibrated and uncalibrated, were set up for 2007/08 and 2008/09 simulation periods. For the calibrated modelling, only the surface depression capacity of upland area was calibrated in the 2007/08 simulation period by comparing simulated and observed hydrographs; while other model parameters and all parameters in the uncalibrated modelling were estimated from field observations of soils and vegetation cover, SPOT 5 imagery, and analysis of drainage network and wetland GIS datasets as well as topographic map based and LiDAR DEMs. All the parameters except for the initial soil properties and antecedent wetland storage were kept the same in the 2008/09 simulation period. The model performance in predicting snowpack, soil moisture and streamflow was evaluated and comparisons were made between the calibrated and uncalibrated modelling for both simulation periods. Calibrated and uncalibrated predictions of snow accumulation were very similar and compared fairly well with the distributed field observations for the 2007/08 period with slightly poorer results for the 2008/09 period. Soil moisture content at a point during the early spring was adequately simulated and very comparable between calibrated and uncalibrated results for both simulation periods. The calibrated modelling had somewhat better performance in simulating spring streamflow in both simulation periods, whereas the uncalibrated modelling was still able to capture the streamflow hydrographs with good accuracy. This suggests that prediction of prairie basins without calibration is possible if sufficient data on meteorology, basin landcover and physiography are available.