scholarly journals Water budget, performance of evapotranspiration formulations, and their impact on hydrological modeling of a small boreal peatland-dominated watershed

2018 ◽  
Vol 55 (2) ◽  
pp. 206-220 ◽  
Author(s):  
Pierre-Erik Isabelle ◽  
Daniel F. Nadeau ◽  
Alain N. Rousseau ◽  
François Anctil
Keyword(s):  
Water Budget ◽  
Hydrological Modeling ◽  
Distributed Model ◽  
Model Parameters ◽  
Taylor Models ◽  
Physically Based ◽  
Model Efficiency ◽  
The Impact ◽  
Substantial Drop

Peatlands occupy around 13% of the land cover of Canada, and thus they play a key role in the water balance at high latitudes. They are well known for having substantial water loss due to evapotranspiration. Since measurements of evapotranspiration are scarce over these environments, hydrologists generally rely on models of varying complexity to evaluate these water exchanges in the global watershed balance. This study quantifies the water budget of a small boreal peatland-dominated watershed. We assess the performance of three evapotranspiration models in comparison with in situ observations and the impact of using these models in the hydrological modeling of the watershed. The study site (∼1 km2) is located in the eastern James Bay lowlands, Québec, Canada. During summer 2012, an eddy flux tower measured evapotranspiration continuously, while a trapezoidal flume monitored streamflow at the watershed outlet. We estimated evapotranspiration with a combinational model (Penman), a radiation-based model (Priestley–Taylor), and a temperature-based model (Hydro-Québec), and performed the hydrological modeling of the watershed with HYDROTEL, a physically based semi-distributed model. Our results show that the Penman and Priestley–Taylor models reproduce the observations with the highest precision, while a substantial drop in performance occurs with the Hydro-Québec model. However, these discrepancies did not appear to reduce the hydrological model efficiency, at least from what can be concluded from a 3-month modeling period. HYDROTEL appears sensitive to evapotranspiration inputs, but calibration of model parameters can compensate for the differences. These findings still need to be confirmed with longer modeling periods.

scholarly journals In-Situ Measurement of Power Loss for Crystalline Silicon Modules Undergoing Thermal Cycling and Mechanical Loading Stress Testing

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 72
Author(s):  
Sergiu Spataru ◽  
Peter Hacke ◽  
Dezso Sera
Keyword(s):  
Thermal Cycling ◽  
Power Loss ◽  
Stress Testing ◽  
Series Resistance ◽  
Short Circuit ◽  
In Situ Measurement ◽  
Mechanical Degradation ◽  
Model Parameters ◽  
The Impact

An in-situ method is proposed for monitoring and estimating the power degradation of mc-Si photovoltaic (PV) modules undergoing thermo-mechanical degradation tests that primarily manifest through cell cracking, such as mechanical load tests, thermal cycling and humidity freeze tests. The method is based on in-situ measurement of the module’s dark current-voltage (I-V) characteristic curve during the stress test, as well as initial and final module flash testing on a Sun simulator. The method uses superposition of the dark I-V curve with final flash test module short-circuit current to account for shunt and junction recombination losses, as well as series resistance estimation from the in-situ measured dark I-Vs and final flash test measurements. The method is developed based on mc-Si standard modules undergoing several stages of thermo-mechanical stress testing and degradation, for which we investigate the impact of the degradation on the modules light I-V curve parameters, and equivalent solar cell model parameters. Experimental validation of the method on the modules tested shows good agreement between the in-situ estimated power degradation and the flash test measured power loss of the modules, of up to 4.31 % error (RMSE), as the modules experience primarily junction defect recombination and increased series resistance losses. However, the application of the method will be limited for modules experiencing extensive photo-current degradation or delamination, which are not well reflected in the dark I-V characteristic of the PV module.

scholarly journals Incremental model breakdown to assess the multi-hypotheses problem

2018 ◽  
Vol 22 (8) ◽  
pp. 4565-4581 ◽  
Author(s):  
Florian U. Jehn ◽  
Lutz Breuer ◽  
Tobias Houska ◽  
Konrad Bestian ◽  
Philipp Kraft
Keyword(s):  
Hydrological Modeling ◽  
Model Performance ◽  
Complex Model ◽  
Model Parameters ◽  
Objective Functions ◽  
Final Model ◽  
Incremental Model ◽  
Model Efficiency ◽  
Improved Model ◽  
Model Structures

Abstract. The ambiguous representation of hydrological processes has led to the formulation of the multiple hypotheses approach in hydrological modeling, which requires new ways of model construction. However, most recent studies focus only on the comparison of predefined model structures or building a model step by step. This study tackles the problem the other way around: we start with one complex model structure, which includes all processes deemed to be important for the catchment. Next, we create 13 additional simplified models, where some of the processes from the starting structure are disabled. The performance of those models is evaluated using three objective functions (logarithmic Nash–Sutcliffe; percentage bias, PBIAS; and the ratio between the root mean square error and the standard deviation of the measured data). Through this incremental breakdown, we identify the most important processes and detect the restraining ones. This procedure allows constructing a more streamlined, subsequent 15th model with improved model performance, less uncertainty and higher model efficiency. We benchmark the original Model 1 and the final Model 15 with HBV Light. The final model is not able to outperform HBV Light, but we find that the incremental model breakdown leads to a structure with good model performance, fewer but more relevant processes and fewer model parameters.

scholarly journals The Impact of Error Accounting in a Bayesian Approach to Calibrating Modeled Turbulent Fluxes in an Open-Canopy Forest

2017 ◽  
Vol 18 (7) ◽  
pp. 2029-2042
Author(s):  
Tony E. Wong ◽  
William Kleiber ◽  
David C. Noone
Keyword(s):  
Markov Chain ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Soil Layer ◽  
Turbulent Fluxes ◽  
Surface Model ◽  
Model Parameters ◽  
Top Soil ◽  
The Impact ◽  
Calibration Approach

Abstract Land surface models are notorious for containing many parameters that control the exchange of heat and moisture between land and atmosphere. Properly modeling the partitioning of total evapotranspiration (ET) between transpiration and evaporation is critical for accurate hydrological modeling, but depends heavily on the treatment of turbulence within and above canopies. Previous work has constrained estimates of evapotranspiration and its partitioning using statistical approaches that calibrate land surface model parameters by assimilating in situ measurements. These studies, however, are silent on the impacts of the accounting of uncertainty within the statistical calibration framework. The present study calibrates the aerodynamic, leaf boundary layer, and stomatal resistance parameters, which partially control canopy turbulent exchange and thus the evapotranspiration flux partitioning. Using an adaptive Metropolis–Hastings algorithm to construct a Markov chain of draws from the joint posterior distribution of these resistance parameters, an ensemble of model realizations is generated, in which latent and sensible heat fluxes and top soil layer temperature are optimized. A set of five calibration experiments demonstrate that model performance is sensitive to the accounting of various sources of uncertainty in the field observations and model output and that it is critical to account for model structural uncertainty. After calibration, the modeled fluxes and top soil layer temperature are largely free from bias, and this calibration approach successfully informs and characterizes uncertainty in these parameters, which is essential for model improvement and development. The key points of this paper are 1) a Markov chain Monte Carlo calibration approach successfully improves modeled turbulent fluxes; 2) ET partitioning estimates hinge on the representation of uncertainties in the model and data; and 3) despite these inherent uncertainties, constrained posterior estimates of ET partitioning emerge.

scholarly journals The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1703 ◽  
Author(s):  
Shakti P. C. ◽  
Tsuyoshi Nakatani ◽  
Ryohei Misumi
Keyword(s):  
River Basin ◽  
Spatial Resolution ◽  
Hydrological Modeling ◽  
Distribution Patterns ◽  
Rainfall Data ◽  
Model Parameters ◽  
Radar Rainfall ◽  
Rain Events ◽  
The Impact ◽  
Hydrological Applications

Recently, the use of gridded rainfall data with high spatial resolutions in hydrological applications has greatly increased. Various types of radar rainfall data with varying spatial resolutions are available in different countries worldwide. As a result of the variety in spatial resolutions of available radar rainfall data, the hydrological community faces the challenge of selecting radar rainfall data with an appropriate spatial resolution for hydrological applications. In this study, we consider the impact of the spatial resolution of radar rainfall on simulated river runoff to better understand the impact of radar resolution on hydrological applications. Very high-resolution polarimetric radar rainfall (XRAIN) data are used as input for the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) to simulate runoff from the Tsurumi River Basin, Japan. A total of 20 independent rainfall events from 2012–2015 were selected and categorized into isolated/convective and widespread/stratiform events based on their distribution patterns. First, the hydrological model was established with basin and model parameters that were optimized for each individual rainfall event; then, the XRAIN data were rescaled at various spatial resolutions to be used as input for the model. Finally, we conducted a statistical analysis of the simulated results to determine the optimum spatial resolution for radar rainfall data used in hydrological modeling. Our results suggest that the hydrological response was more sensitive to isolated or convective rainfall data than it was to widespread rain events, which are best simulated at ≤1 km and ≤5 km, respectively; these results are applicable in all sub-basins of the Tsurumi River Basin, except at the river outlet.

scholarly journals The significance of spatial variability of rainfall on simulated runoff: an evaluation based on the Upper Lee catchment, UK

2016 ◽  
Vol 48 (4) ◽  
pp. 1118-1130 ◽  
Author(s):  
I. G. Pechlivanidis ◽  
N. McIntyre ◽  
H. S. Wheater
Keyword(s):  
Spatial Variability ◽  
Distributed Model ◽  
Model Parameters ◽  
Rainfall Time Series ◽  
Catchment Scale ◽  
Rainfall Events ◽  
Spatial Properties ◽  
Antecedent Conditions ◽  
Parameter Uncertainty Analysis ◽  
The Impact

The significance of spatial variability of rainfall on runoff is explored as a function of catchment scale and type, and antecedent conditions via the continuous time, semi-distributed probability distributed model (PDM) hydrological model applied to the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments, and further assessed by artificially changing the catchment characteristics and translating these to model parameters (MPs) with uncertainty using model regionalisation. Dry and wet antecedent conditions are represented by ‘warming up’ the model under different rainfall time series. Synthetic rainfall events are introduced to directly relate the change in simulated runoff to the spatial variability of rainfall. Results show that runoff volume and peak are more sensitive to the spatial rainfall for more impermeable catchments; however, this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on runoff varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Parameter uncertainty analysis highlights the importance of accurately representing the spatial variability of the catchment properties and their translation to MPs when investigating the effects of spatial properties of rainfall on runoff.

Satellite Data Application to Cover Lack of In-situ Observations for Mapping Precipitation and Direct Runoff in Semi-arid Basin

2020 ◽  
Author(s):  
Mahdi Akbari ◽  
Ali Torabi Haghighi
Keyword(s):  
Hydrological Modeling ◽  
Rain Gauge ◽  
Model Parameters ◽  
Lake Basin ◽  
Lake Urmia ◽  
Direct Runoff ◽  
Rain Gauges ◽  
High Elevations ◽  
Semi Arid

<div> <p>Hydrological modeling in arid basins located in developing countries often lacks sufficient hydrological data because, e.g., rain gauges are typically absent at high elevations and inflow to ungauged areas around large closed lakes such as Lake Urmia is difficult to estimate. We tried to improve precipitation and runoff estimation in Lake Urmia, Iran as an arid basin using satellite-based data. We estimated precipitation using interpolation of rain gauge data by kriging, downscaling Tropical Rainfall Measuring Mission (TRMM), and cokriging interpolation of in-situ records with Remote Sensing (RS)-based data. Using RS-based data in estimations gave more precise results, by compensating for lack of data at high elevations. Cokriging interpolation of rain gauges by TRMM and Digitized Elevation Model (DEM) gave 4–9 mm lower Root Mean Square Error (RMSE) in different years compared with kriging. Downscaling TRMM improved its accuracy by 14 mm. Using the most accurate precipitation model, we modeled annual direct runoff with Kennessey and Soil Conservation Service Curve Number (SCS-CN) models. These models use land use, permeability, slope maps and climatic parameter (Ia) to represent the annual climatic condition of modeled basin in sense of wetness or dryness. In runoff modeling, Kennessey gave higher accuracy in annual scale. It was found that classification of years to wet, dry and normal states in Kennessey by default assumptions on Ia is not accurate enough for semi-arid basins so by solving this issue and calibration Kennessey model parameters, we made this model applicable for Urmia Lake basin. Calibrating Kennessey reduced the Normalized RMSE (NRMSE) from 1 in the standard model to 0.44. Direct runoff coefficient map by 1 km spatial resolution was generated by calibrated Kennessey. Validation by the closest gauges to the lake gave a NRMSE of 0.41 which approved the accuracy of modeling.</p> </div>

scholarly journals Evaluation of the effects of underlying surface change on catchment hydrological response using the HEC-HMS model

2014 ◽  
Vol 364 ◽  
pp. 145-150 ◽  
Author(s):  
C. Yao ◽  
L. Chang ◽  
J. Ding ◽  
Z. Li ◽  
D. An ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Rapid Development ◽  
Land Use Changes ◽  
Underlying Surface ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Hydrological Response ◽  
Surface Change ◽  
Distributed Models ◽  
The Impact

Abstract. Due to rapid population growth, China, and urbanization, the Dongwan catchment, with a drainage area of 2856 km2 and located in Henan Province, has been subjected to considerable land-use changes since the 1990s. Distributed or semi-distributed models have been widely used in catchment hydrological modeling, along with the rapid development of computer and GIS technologies. The objective of this study is to assess the impact of underlying surface change on catchment hydrological response using the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS), which is a distributed hydrological model. Specifically, 21 flood events were selected for calibrating and validating the model parameters. The satisfactory results show that the HEC-HMS model can be used to simulate the rainfall–runoff response in the Dongwan catchment. In light of the analyses of simulation results, it is shown that the flood peaks and runoff yields after 1990 moderately decrease in comparison with that before 1990 at the same precipitation level. It is also indicated that the underlying surface change leads to the increased flood storage capacity after 1990 in this region.

scholarly journals Agent-based modelling of complex factors impacting malaria prevalence

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Miracle Amadi ◽  
Anna Shcherbacheva ◽  
Heikki Haario
Keyword(s):  
Malaria Transmission ◽  
Field Data ◽  
Control Measures ◽  
Model Parameters ◽  
Economic Factors ◽  
Agent Based ◽  
Wide Range ◽  
The Impact ◽  
Socio Economic Factors

Abstract Background Increasingly complex models have been developed to characterize the transmission dynamics of malaria. The multiplicity of malaria transmission factors calls for a realistic modelling approach that incorporates various complex factors such as the effect of control measures, behavioural impacts of the parasites to the vector, or socio-economic variables. Indeed, the crucial impact of household size in eliminating malaria has been emphasized in previous studies. However, increasing complexity also increases the difficulty of calibrating model parameters. Moreover, despite the availability of much field data, a common pitfall in malaria transmission modelling is to obtain data that could be directly used for model calibration. Methods In this work, an approach that provides a way to combine in situ field data with the parameters of malaria transmission models is presented. This is achieved by agent-based stochastic simulations, initially calibrated with hut-level experimental data. The simulation results provide synthetic data for regression analysis that enable the calibration of key parameters of classical models, such as biting rates and vector mortality. In lieu of developing complex dynamical models, the approach is demonstrated using most classical malaria models, but with the model parameters calibrated to account for such complex factors. The performance of the approach is tested against a wide range of field data for Entomological Inoculation Rate (EIR) values. Results The overall transmission characteristics can be estimated by including various features that impact EIR and malaria incidence, for instance by reducing the mosquito–human contact rates and increasing the mortality through control measures or socio-economic factors. Conclusion Complex phenomena such as the impact of the coverage of the population with long-lasting insecticidal nets (LLINs), changes in behaviour of the infected vector and the impact of socio-economic factors can be included in continuous level modelling. Though the present work should be interpreted as a proof of concept, based on one set of field data only, certain interesting conclusions can already be drawn. While the present work focuses on malaria, the computational approach is generic, and can be applied to other cases where suitable in situ data is available.

scholarly journals Testing the Efficiency of Parameter Disaggregation for Distributed Rainfall-Runoff Modelling

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 972
Author(s):  
Sotirios Moustakas ◽  
Patrick Willems
Keyword(s):  
Spatial Data ◽  
Distributed Model ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Natural Processes ◽  
Reliable Model ◽  
Physically Based ◽  
Lumped Models ◽  
Uniform Model ◽  
Modelling Approach

A variety of hydrological models is currently available. Many of those employ physically based formulations to account for the complexity and spatial heterogeneity of natural processes. In turn, they require a substantial amount of spatial data, which may not always be available at sufficient quality. Recently, a top-down approach for distributed rainfall-runoff modelling has been developed, which aims at combining accuracy and simplicity. Essentially, a distributed model with uniform model parameters (base model) is derived from a calibrated lumped conceptual model. Subsequently, selected parameters are disaggregated based on links with the available spatially variable catchment properties. The disaggregation concept is now adjusted to better account for non-linearities and extended to incorporate more model parameters (and, thus, larger catchment heterogeneity). The modelling approach is tested for a catchment including several flow gauging stations. The disaggregated model is shown to outperform the base model with respect to internal catchment dynamics, while performing similarly at the catchment outlet. Moreover, it manages to bridge on average 44% of the Nash–Sutcliffe efficiency difference between the base model and the lumped models calibrated for the internal gauging stations. Nevertheless, the aforementioned improvement is not necessarily sufficient for reliable model results.

scholarly journals Avaliação de Impactos de Mudanças no Uso e Manejo do Solo Sobre as Vazões da Bacia Hidrográfica do Ribeirão José Pereira, Utilizando o Modelo Swat.

2021 ◽  
Vol 14 (2) ◽  
pp. 619
Author(s):  
Filipe Otávio Passos ◽  
Benedito Cláudio Da Silva ◽  
Fernando Das Graças Braga da Silva
Keyword(s):  
Land Use ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Water Source ◽  
Distributed Model ◽  
Small Scale ◽  
The Impact ◽  
Water Assessment ◽  
Soil And Water

Diversos processos naturais podem causar mudanças nos fluxos hidrológicos dentro de bacias hidrográficas, sendo estas ainda mais afetadas devido a ações antrópicas que mudem as suas características físicas, principalmente, o tipo e o uso do solo. Neste contexto, este trabalho apresenta uma calibração de um modelo de transformação chuva x vazão e posterior simulação para a estimativa das vazões na bacia hidrográfica do ribeirão José Pereira, em Itajubá, sul de Minas Gerais, utilizando o modelo distribuído Soil and Water Assessment Tool (Swat). Foram gerados cinco cenários de uso e ocupação do solo, que foram idealizados a partir de características observadas na bacia ou de tendências futuras de ocupação, a saber, o cenário do estado atual, de manejo do solo, de recuperação das áreas de preservação permanente (APPs) de margens de rios, de substituição total por floresta e de crescimento urbano. Os resultados indicam que o modelo Swat pode ser utilizado na simulação das componentes hidrológicas de bacias hidrográficas de pequeno porte, e ainda que o manejo agrícola e o reflorestamento da bacia são mais eficientes na diminuição do escoamento superficial do que a recuperação das APPs, chegando a uma diminuição de aproximadamente 40% nas vazões máximas simuladas. Impact Assessment of Changes in Land Use and Management on the Losses of the Water Source of the José Pereira Stream, Using the SWAT Model A B S T R A C TSeveral natural processes can cause changes in hydrological flows within hydrographic basins, which are even more affected due to anthropic actions that change their physical characteristics, mainly, the type and use of the soil. In this context, this work carries out an analysis of the impact on the flows of a small-scale hydrographic basin (River José Pereira) due to changes in land use and occupation, using the distributed model Soil and Water Assessment Tool (SWAT). Five land use and occupation scenarios were generated, which were designed based on characteristics observed in the basin or future occupation trends, namely, the current state scenario, soil management, recovery of permanent preservation areas (APPs) of river banks, total replacement by forest and urban growth. The results indicate that the SWAT model can be used in the simulation of the hydrological components of small hydrographic basins, and that agricultural management and reforestation of the basin are more efficient in reducing runoff than the recovery of APPs, reaching a decrease of approximately 40% in the maximum simulated flows.Keywords: hydrological modeling, rainfall, SWAT, land use and occupation.

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