scholarly journals EcH<sub>2</sub>O-iso 1.0: Water isotopes and age tracking in a process-based, distributed ecohydrological model

2018 ◽  
Author(s):  
Sylvain Kuppel ◽  
Doerthe Tetzlaff ◽  
Marco P. Maneta ◽  
Chris Soulsby
Keyword(s):  
Stream Water ◽  
Model Development ◽  
Runoff Generation ◽  
Energy Propagation ◽  
Isotopic Tracers ◽  
Physically Based ◽  
Spatially Distributed ◽  
Hydraulic Gradients ◽  
Ecohydrological Model ◽  
Spatio Temporal

Abstract. We introduce EcH2O-iso, a new development of the physically-based, fully-distributed ecohydrological model EcH2O where the tracking of water isotopic tracers (2H and 18O) and age has been incorporated. EcH2O-iso is evaluated at a montane, low-energy experimental catchment in eastern Scotland using 16 independent isotope time series from various landscape positions and compartments; encompassing soil water, groundwater, stream water, and plant xylem. We find a good model-observation match in most cases, despite having only calibrated the model using hydrometric data and energy fluxes. These results provide further validation of the physical basis of the model for successfully capturing catchment hydrological functioning, both in terms of the celerity in energy propagation (e.g. runoff generation under prevailing hydraulic gradients) and flow velocities of water molecules (e.g., in consistent tracer concentrations at given locations and times). We also show that the spatially-distributed formulation of EcH2O-iso provides a powerful tool for quantitatively linking water stores and fluxes with spatio-temporal patterns of isotopes ratios and water ages. Finally, our study highlights some model development and benchmarking needs, refined using isotope-based calibration, for hypothesis testing and improved simulations of catchment dynamics that is transferable beyond the catchment landscape studied here.

scholarly journals Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

2012 ◽  
Vol 16 (2) ◽  
pp. 357-373 ◽  
Author(s):  
M. Liu ◽  
A. Bárdossy ◽  
J. Li ◽  
Y. Jiang
Keyword(s):  
Soil Moisture ◽  
Model Development ◽  
Topographic Effects ◽  
Runoff Generation ◽  
Humid Region ◽  
Swap Model ◽  
Physically Based ◽  
Spatially Distributed ◽  
Significant Spatial Variation ◽  
Limited Process

Abstract. In this paper, simulations with the Soil Water Atmosphere Plant (SWAP) model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET), and soil moisture content (SMC) caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

scholarly journals EcH<sub>2</sub>O-iso 1.0: water isotopes and age tracking in a process-based, distributed ecohydrological model

2018 ◽  
Vol 11 (7) ◽  
pp. 3045-3069 ◽  
Author(s):  
Sylvain Kuppel ◽  
Doerthe Tetzlaff ◽  
Marco P. Maneta ◽  
Chris Soulsby
Keyword(s):  
Soil Water ◽  
Water Use ◽  
Stream Water ◽  
Plant Water ◽  
Model Data ◽  
Energy Propagation ◽  
Isotopic Tracers ◽  
Landscape Characteristics ◽  
Plant Water Use ◽  
Ecohydrological Model

Abstract. We introduce EcH2O-iso, a new development of the physically based, fully distributed ecohydrological model EcH2O where the tracking of water isotopic tracers (2H and 18O) and age has been incorporated. EcH2O-iso is evaluated at a montane, low-energy experimental catchment in northern Scotland using 16 independent isotope time series from various landscape positions and compartments, encompassing soil water, groundwater, stream water, and plant xylem. The simulation results show consistent isotopic ranges and temporal variability (seasonal and higher frequency) across the soil profile at most sites (especially on hillslopes), broad model–data agreement in heather xylem, and consistent deuterium dynamics in stream water and in groundwater. Since EcH2O-iso was calibrated only using hydrometric and energy flux datasets, tracking water composition provides a truly independent validation of the physical basis of the model for successfully capturing catchment hydrological functioning, both in terms of the celerity in energy propagation shaping the hydrological response (e.g. runoff generation under prevailing hydraulic gradients) and flow velocities of water molecules (e.g. in consistent tracer concentrations at given locations and times). Additionally, we show that the spatially distributed formulation of EcH2O-iso has the potential to quantitatively link water stores and fluxes with spatiotemporal patterns of isotope ratios and water ages. However, our case study also highlights model–data discrepancies in some compartments, such as an over-dampened variability in groundwater and stream water lc-excess, and over-fractionated riparian topsoils. The adopted minimalistic framework, without site-specific parameterisation of isotopes and age tracking, allows us to learn from these mismatches in further model development and benchmarking needs, while taking into account the idiosyncracies of our study catchment. Notably, we suggest that more advanced conceptualisation of soil water mixing and of plant water use would be needed to reproduce some of the observed patterns. Balancing the need for basic hypothesis testing with that of improved simulations of catchment dynamics for a range of applications (e.g. plant water use under changing environmental conditions, water quality issues, and calibration-derived estimates of landscape characteristics), further work could also benefit from including isotope-based calibration.

The role of precipitation in hydrological model uncertainty

2020 ◽  
Author(s):  
András Bárdossy ◽  
Chris Kilsby ◽  
Faizan Anwar ◽  
Ning Wang
Keyword(s):  
Conceptual Models ◽  
Spatial Scales ◽  
State Variables ◽  
Rainfall Runoff ◽  
Physically Based ◽  
Spatially Distributed ◽  
Spatio Temporal ◽  
Step Care ◽  
Model Approach

&lt;p&gt;Rainfall-runoff models produce outputs which differ from observations due to uncertainties in process description, process parametrization, uncertainties in observations and changing spatio-temporal variability of input and state variables. Traditionally, attention has been focused mostly on process parameters to quantify runoff uncertainty using e.g. GLUE.&lt;/p&gt;&lt;p&gt;Here we have focused on the role of precipitation uncertainty relating to discharge. For this purpose, we used an inverse model approach. We generated time series of daily precipitation with high spatial resolution &amp;#160;using a modified version of Random Mixing and the Shannon-Whittaker interpolation to improve simulated runoff using the SHETRAN (physically-based) and HBV (conceptual) models, both spatially distributed for various sub-catchments of the Neckar River in Germany. &amp;#160;HBV was initially calibrated using interpolated precipitation, while SHETRAN uses pre-defined parameters. The modelling goal was to find a spatio-temporal series of precipitation which improved the predicted runoff,&amp;#160; under the constraints that the precipitation values be the same at the measurement locations and share their spatial variability with the observations at a given step. Care was taken to select subsequent days for improvement such that the previously improved step considered the effect of the previous steps.&lt;/p&gt;&lt;p&gt;We asked the questions: i) does improving precipitation inputs for one sub-catchment bring runoff improvement for the others? ii) Can the improved precipitation using SHETRAN be used for HBV and still get runoff improvements as compared to the interpolated precipitation and vice versa?&lt;/p&gt;&lt;p&gt;Results showed that overall runoff errors were reduced by 40 to 50% for all sub-catchments. For the peaks, a reduction of 70 to 90% was observed. As compared with the interpolated fields, new fields showed similar overall distribution but different details at finer spatial scales. Swapping improved precipitations between SHETRAN and HBV showed improvement as compared with the discharge from interpolated precipitation.&lt;/p&gt;

scholarly journals Runoff generation at the small permafrost river basin in Eastern Siberia: data analysis and hydrological modeling

2020 ◽  
Vol 163 ◽  
pp. 01006
Author(s):  
Andrey Kalugin ◽  
Liudmila Lebedeva
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Snow Water Equivalent ◽  
Runoff Generation ◽  
Water Release ◽  
Complex Interactions ◽  
Monthly Streamflow ◽  
Physically Based ◽  
Spatially Distributed

The study aims at the analysis of the long-term hydrometeorological data and hydrological modelling at the small permafrost Shestakovka river basin. The basin has postponed reaction to precipitation on different time scales from days to years. Annual, seasonal and monthly streamflow has higher correlation with precipitation sum for corresponding and antecedent time intervals than for the corresponding period only. It suggests importance of water storage and slow water release in the runoff generation that could be related to the suprapermafrost talik aquifers found in the river basin. A spatially distributed physically-based ECOMAG model was applied to the Shestakovka River basin. Evaluation of the simulated river runoff, soil moisture and snow water equivalent was carried out over a period 1990-2014. Obtained NSE 0.59 and BIAS 3% could be considered as satisfactory modelling results taking into account high inter annual and seasonal observed streamflow variability under much less variable meteorological conditions. Better understanding and modelling of the complex interactions between permafrost and hydrological processes is important for development of reliable flood forecasts and long-term future projections under changing climate and growing economical interests to cold regions.

scholarly journals Spatio-Temporal Hydrological Model Structure and Parametrization Analysis

2021 ◽  
Vol 9 (5) ◽  
pp. 467
Author(s):  
Mostafa Farrag ◽  
Gerald Corzo Perez ◽  
Dimitri Solomatine
Keyword(s):  
Hydrological Modeling ◽  
Model Building ◽  
Model Performance ◽  
Model Description ◽  
Generation Model ◽  
Model Structure ◽  
Runoff Generation ◽  
Spatial Sensitivity ◽  
Spatio Temporal ◽  
Set Up

Many grid-based spatial hydrological models suffer from the complexity of setting up a coherent spatial structure to calibrate such a complex, highly parameterized system. There are essential aspects of model-building to be taken into account: spatial resolution, the routing equation limitations, and calibration of spatial parameters, and their influence on modeling results, all are decisions that are often made without adequate analysis. In this research, an experimental analysis of grid discretization level, an analysis of processes integration, and the routing concepts are analyzed. The HBV-96 model is set up for each cell, and later on, cells are integrated into an interlinked modeling system (Hapi). The Jiboa River Basin in El Salvador is used as a case study. The first concept tested is the model structure temporal responses, which are highly linked to the runoff dynamics. By changing the runoff generation model description, we explore the responses to events. Two routing models are considered: Muskingum, which routes the runoff from each cell following the river network, and Maxbas, which routes the runoff directly to the outlet. The second concept is the spatial representation, where the model is built and tested for different spatial resolutions (500 m, 1 km, 2 km, and 4 km). The results show that the spatial sensitivity of the resolution is highly linked to the routing method, and it was found that routing sensitivity influenced the model performance more than the spatial discretization, and allowing for coarser discretization makes the model simpler and computationally faster. Slight performance improvement is gained by using different parameters’ values for each cell. It was found that the 2 km cell size corresponds to the least model error values. The proposed hydrological modeling codes have been published as open-source.

Runoff generation processes in permafrost-influenced area of the Heihe River Headwater

2021 ◽  
Author(s):  
Fan Zhang ◽  
Xiong Xiao ◽  
Guanxing Wang
Keyword(s):  
Soil Water ◽  
Stream Water ◽  
Hydrological Regime ◽  
Summer Rainfall ◽  
Frozen Soil ◽  
Heihe River ◽  
The Tibetan Plateau ◽  
Permafrost Degradation ◽  
Runoff Generation ◽  
Spring Snowmelt

&lt;p&gt;Permafrost degradation under global warming may change the hydrological regime of the headwater catchments in alpine area such as the Tibetan Plateau (TP). In this study, he runoff generation processes in permafrost-influenced area of the Heihe River Headwater were investigated with the following results: 1) The observed stable isotope values of various water types on average was roughly in the order of snowfall and snowmelt &lt; bulk soil water (BSW) &lt; rainfall , stream water, mobile soil water (MSW) , and lateral subsurface flow. The depleted spring snowmelt and enriched summer rainfall formed tightly bound soil water and MSW, respectively. The dynamic mixing between tightly bound soil water and MSW resuted in BSW with more depleted and variable stable isotopic feature than MSW. 2) Along with the thawing of the frozen soil, surface runoff and shallowsubsurface flow (SSF) at 30&amp;#8722;60 cm was the major flow pathway in the permafrost influenced alpine meadow hillslope during spring snowmelt and summer rainfall period, reapectively, with the frozen soil maintaining supra-permafrost water level. 3) Comparison between two neighouring catchments under similar precipitation conditions indicated that streamflow of the lower catchment with less permafrost proportion and earlier thawing time has larger SSF and higher based flow component, indicating the potential changes of hydrological regims subject to future warming.&lt;/p&gt;

scholarly journals A Comprehensive Review of Low Impact Development Models for Research, Conceptual, Preliminary and Detailed Design Applications

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1541 ◽  
Author(s):  
Sahereh Kaykhosravi ◽  
Usman Khan ◽  
Amaneh Jadidi
Keyword(s):  
Spatial Data ◽  
Spatial Scales ◽  
Low Impact Development ◽  
Model Development ◽  
Point Of View ◽  
Tree Canopy ◽  
Balance Model ◽  
Runoff Generation ◽  
Development Models ◽  
Model Features

This review compares and evaluates eleven Low Impact Development (LID) models on the basis of: (i) general model features including the model application, the temporal resolution, the spatial data visualization, the method of placing LID within catchments; (ii) hydrological modelling aspects including: the type of inbuilt LIDs, water balance model, runoff generation and infiltration; and (iii) hydraulic modelling methods with a focus on the flow routing method. Results show that despite the recent updates of existing LID models, several important features are still missing and need improvement. These features include the ability to model: multi-layer subsurface media, tree canopy and processes associated with vegetation, different spatial scales, snowmelt and runoff calculations. This review provides in-depth insight into existing LID models from a hydrological and hydraulic point of view, which will facilitate in selecting the best-suited model. Recommendations on further studies and LID model development are also presented.

A Comparative Study of Data and Physically Based Gas Turbine Modeling for Long-Term Monitoring Scenarios: Part II — Emission Prediction Utilizing Different Levels of Design Information

2018 ◽  
Author(s):  
Moritz Lipperheide ◽  
Thomas Bexten ◽  
Manfred Wirsum ◽  
Martin Gassner ◽  
Stefano Bernero
Keyword(s):  
Gas Turbine ◽  
A Priori ◽  
Model Development ◽  
Fine Tuning ◽  
Plant Operator ◽  
Engine Model ◽  
Physically Based ◽  
Design Type ◽  
The Impact

Reliable engine and emission models allow for an online monitoring of commercial gas turbine operation and help the plant operator and the original equipment manufacturer (OEM) to ensure emission compliance of the aging engine. However, model development and validation require fine-tuning on the particular engines, which may differ in a fleet of a single design type by production, assembly and aging status. For this purpose, Artificial Neural Networks (ANN) offer a good and fast alternative to traditional physically-based engine modeling, because the model creation and adaption is merely an automatized process in commercially available software environments. However, ANN performance depends strongly on the availability of suitable data and a-priori data processing. The present work investigates the impact of specific engine information from the OEM’s design tools on ANN performance. As an alternative to a strictly data-based benchmark approach, engine characteristics were incorporated into ANNs by a pre-processing of the raw measurements with a simplified engine model. The resulting ‘virtual’ measurements, i.e. hot gas temperatures, then served as inputs to ANN training and application during long-term gas turbine operation. When processed input parameters were used for ANNs, overall long-term NOx prediction improved by 55%, and CO prediction by 16% in terms of RMSE, yielding comparable overall RMSE values to the physically-based model.

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