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1
Tian, Yifei, Lihua Xiong, Bin Xiong, and Ruodan Zhuang. "A Prior Estimation of the Spatial Distribution Parameter of Soil Moisture Storage Capacity Using Satellite-Based Root-Zone Soil Moisture Data." Remote Sensing 11, no. 21 (November 3, 2019): 2580. http://dx.doi.org/10.3390/rs11212580.
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Integration of satellite-based data with hydrological modelling was generally conducted via data assimilation or model calibration, and both approaches can enhance streamflow predictions. In this study, we assessed the feasibility of another approach that uses satellite-based soil moisture data to directly estimate the parameter β to represent the degree of the spatial distribution of soil moisture storage capacity in the semi-distributed Hymod model. The impact of using historical root-zone soil moisture data from the Soil Moisture Active Passive (SMAP) mission on the prior estimation of the parameter β was explored. Two different ways to incorporate the root-zone soil moisture data to estimate the parameter β are proposed, i.e., one is to derive a priori distribution of β , and the other is to derive a fixed value for β . The simulations of the Hymod models employing the two ways to estimate β are compared with the results produced by the original model, i.e., the one without employing satellite-based data to estimate the parameter β , at three study catchments (the Upper Hanjiang River catchment, the Xiangjiang River catchment, and the Ganjiang River catchment). The results illustrate that the two ways to incorporate the SMAP root-zone soil moisture data in order to predetermine the parameter β of the semi-distributed Hymod model both perform well in simulating streamflow during the calibration period, and a slight improvement was found during the validation period. Notably, deriving a fixed β value from satellite soil moisture data can provide better performance for ungauged catchments despite reducing the model freedom degrees due to fixing the β value. It is concluded that the robustness of the Hymod model in predicting the streamflow can be improved when the spatial information of satellite-based soil moisture data is utilized to estimate the parameter β .
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Quan, Z., J. Teng, W. Sun, T. Cheng, and J. Zhang. "Evaluation of the HYMOD model for rainfall–runoff simulation using the GLUE method." Proceedings of the International Association of Hydrological Sciences 368 (May 6, 2015): 180–85. http://dx.doi.org/10.5194/piahs-368-180-2015.
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Abstract. The Yalong River is the third largest base of the 13 hydropower bases in China. Long-time series of river discharge records are essential for the design of hydropower stations and water resource management. The existing monitoring network is scarce and cannot provide sufficient hydrological information for the basin. Rainfall–runoff models are popular tools for extending hydrological data in both space and time. In this paper, the feasibility of applying a conceptual rainfall–runoff model, HYdrological MODel (HYMOD), to the upper Yalong River basin was evaluated. The generalized likelihood uncertainty estimation (GLUE) was employed for model calibration and uncertainty analysis. The results show that simulated discharge matches the observations satisfactorily, indicating the hydrological model performs well and the application of HYMOD to estimate long time-series of river discharge in the study area is feasible.
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Pathiraja, Sahani, Daniela Anghileri, Paolo Burlando, Ashish Sharma, Lucy Marshall, and Hamid Moradkhani. "Time-varying parameter models for catchments with land use change: the importance of model structure." Hydrology and Earth System Sciences 22, no. 5 (May 16, 2018): 2903–19. http://dx.doi.org/10.5194/hess-22-2903-2018.
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Abstract. Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
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Markou, George, Christos Mourlas, and Manolis Papadrakakis. "Computationally Efficient and Robust Nonlinear 3D Cyclic Modeling of RC Structures Through a Hybrid Finite Element Model (HYMOD)." International Journal of Computational Methods 16, no. 01 (November 21, 2018): 1850125. http://dx.doi.org/10.1142/s0219876218501256.
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A computationally efficient and robust simulation method is presented in this work, for the cyclic modeling of reinforced concrete (RC) structures. The proposed hybrid modeling (HYMOD) approach alleviates numerical limitations regarding the excessive computational cost during the cyclic analysis and provides a tool for the detailed simulation of the 3D cyclic nonlinear behavior of full-scale RC structures. The simplified HYMOD approach is integrated in this work with a computationally efficient cyclic concrete material model so as to investigate its numerical performance under extreme cyclic loading conditions. The proposed approach adopts a hybrid modeling concept that combines hexahedral and beam-column finite elements (FEs), in which the coupling between them is achieved through the implementation of kinematic constraints. A parametric investigation is performed through the use of the Del Toro Rivera frame joint and two RC frames with a shear wall. The proposed modeling method managed to decrease the computational cost in all numerical tests performed in this work, while it induced additional numerical stability during the cyclic analysis, in which the required number of internal iterations per displacement increment was found to be always smaller compared with the unreduced (hexahedral) model. The HYMOD provides for the first time with the required 3D detailed FE solution tools in order to simulate the nonlinear cyclic response of full-scale RC structures without hindering the numerical accuracy of the derived model nor the need of developing computationally expensive models that practically cannot be solved through the use of standard computer systems.
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Markou, George, and Manolis Papadrakakis. "A simplified and efficient hybrid finite element model (HYMOD) for non-linear 3D simulation of RC structures." Engineering Computations 32, no. 5 (July 6, 2015): 1477–524. http://dx.doi.org/10.1108/ec-11-2013-0269.
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Purpose – The purpose of this paper is to present a simplified hybrid modeling (HYMOD) approach which overcomes limitations regarding computational cost and permits the simulation and prediction of the nonlinear inelastic behavior of full-scale RC structures. Design/methodology/approach – The proposed HYMOD formulation was integrated in a research software ReConAn FEA and was numerically studied through the use of different numerical implementations. Then the method was used to model a full-scale two-storey RC building, in an attempt to demonstrate its numerical robustness and efficiency. Findings – The numerical results performed demonstrate the advantages of the proposed hybrid numerical simulation for the prediction of the nonlinear ultimate limit state response of RC structures. Originality/value – A new numerical modeling method based on finite element method is proposed for simulating accurately and with computational efficiency, the mechanical behavior of RC structures. Currently 3D detailed methods are used to model single structural members or small parts of RC structures. The proposed method overcomes the above constraints.
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Yin, Zhaokai, Weihong Liao, Xiaohui Lei, Hao Wang, and Ruojia Wang. "Comparing the Hydrological Responses of Conceptual and Process-Based Models with Varying Rain Gauge Density and Distribution." Sustainability 10, no. 9 (September 7, 2018): 3209. http://dx.doi.org/10.3390/su10093209.
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Precipitation provides the most crucial input for hydrological modeling. However, rain gauge networks, the most common precipitation measurement mechanisms, are sometimes sparse and inadequately distributed in practice, resulting in an imperfect representation of rainfall spatial variability. The objective of this study is to analyze the sensitivity of different model structures to the different density and distribution of rain gauges and evaluate their reliability and robustness. Based on a rain gauge network of 20 gauges in the Jinjiang River Basin, south-eastern China, this study compared the performance of two conceptual models (the hydrologic model (HYMOD) and Xinanjiang) and one process-based distributed model (the water and energy transfer between soil, plants and atmosphere model (WetSpa)) with different rain gauge distributions. The results show that the average accuracy for the three models is generally stable as the number of rain gauges decreases but is sensitive to changes in the network distribution. HYMOD has the highest calibration uncertainty, followed by Xinanjiang and WetSpa. Differing model responses are consistent with changes in network distribution, while calibration uncertainties are more related to model structures.
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Kim, Kue Bum, and Dawei Han. "Exploration of sub-annual calibration schemes of hydrological models." Hydrology Research 48, no. 4 (August 30, 2016): 1014–31. http://dx.doi.org/10.2166/nh.2016.296.
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This study compared hydrological model performances under different sub-annual calibration schemes using two conceptual models, IHACRES and HYMOD. In several publications regarding sub-annual calibration, the authors showed that such an approach generally performed better than the conventional whole period method. Hence, there are advantages in dividing the data into sub-annual periods for calibration. However, little attention has been paid to the issue of how to calibrate the non-continuous sub-annual period. Unlike the conventional calibration which assumes time-invariant parameters for the calibration period, the model parameters vary in sub-annual calibration. We have explored two sub-annual calibration schemes, serial calibration scheme (SCS) and parallel calibration scheme (PCS). We assume that the relationships between the rainfall and runoff could be different for each sub-annual period and consider intra-annual variations of the system. The models are then evaluated for a different validation period to avoid over-fitting and the optimal sub-annual calibration period is explored. Overall, we have found that PCS performed slightly better than SCS and the optimal calibration periods are seasonal and bimonthly for IHACRES and biannual for HYMOD. Since there are pros and cons in both SCS and PCS, we recommend choosing the method depending on the purpose of the model usage.
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Zhang, Shiyan, and Khalid Al-Asadi. "Evaluating the Effect of Numerical Schemes on Hydrological Simulations: HYMOD as A Case Study." Water 11, no. 2 (February 14, 2019): 329. http://dx.doi.org/10.3390/w11020329.
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The importance of numerical schemes in hydrological models has been increasingly recognized in the hydrological community. However, the relationship between model performance and the properties of numerical schemes remains unclear. In this study, we employed two types of numerical schemes (i.e., explicit Runge-Kutta schemes with different orders of accuracy and partially implicit Euler schemes with different implicit factors) in the hydrological model (HYMOD) to simulate the flow hydrograph of the Leaf River basin from 1948 to 1988. Results computed by different numerical schemes were compared and the relationships between model performance and two scheme properties (i.e., the order of accuracy and the implicit factor) were discussed. Results showed that the more explicit schemes generally lead to the overestimation of flow hydrographs, whereas the more implicit schemes lead to underestimation. In addition, the numerical error tended to decrease with increasing orders of accuracy. As a result, the optimal parameter sets found by low-order schemes significantly deviated from those found by the analytical solution. The findings of this study can provide useful implications for designing suitable numerical schemes for hydrological models.
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Gharari, S., M. Hrachowitz, F. Fenicia, and H. H. G. Savenije. "An approach to identify time consistent model parameters: sub-period calibration." Hydrology and Earth System Sciences 17, no. 1 (January 17, 2013): 149–61. http://dx.doi.org/10.5194/hess-17-149-2013.
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Abstract. Conceptual hydrological models rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of testing model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time-consistent parameter sets. The approach is applied to a case study in Luxembourg using the HyMod hydrological model as an example.
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Gharari, S., M. Hrachowitz, F. Fenicia, and H. H. G. Savenije. "Moving beyond traditional model calibration or how to better identify realistic model parameters: sub-period calibration." Hydrology and Earth System Sciences Discussions 9, no. 2 (February 13, 2012): 1885–918. http://dx.doi.org/10.5194/hessd-9-1885-2012.
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Abstract. Conceptual hydrological models often rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of confronting model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time consistent parameter sets. The approach is demonstrated in a case study where we illustrate the multi-objective calibration of the HyMod hydrological model to a Luxembourgish catchment.
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Massmann, Carolina. "Supporting M5 model trees with sensitivity information derived from conceptual hydrological models." Journal of Hydroinformatics 17, no. 6 (August 6, 2015): 943–58. http://dx.doi.org/10.2166/hydro.2015.111.
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The main objective of this paper is assessing the usefulness of parameter sensitivity information from conceptual hydrological models for data-driven models, an approach which might allow us to take advantage of the strengths of both data-based and process-based models. This study uses the parameter sensitivity of three widely used conceptual hydrological models (GR4J, Hymod and SAC-SMA) and combines them with M5 model trees. The study was carried out for three case studies dealing with different problems to which model trees are applied: one using model trees as error correctors and two case studies in which model trees were used as rainfall–runoff models and which differ in how the sensitivity information is used. The results show that sensitivity time series can improve the predictions of M5 model trees, especially when they do not include the time series of previous discharge as predictor variables. The use of parameter sensitivity information for clustering the time series resulted in model trees that had a structure consistent with the hydrological processes that were taking place in the considered cluster, indicating that the use of sensitivity indices could be a viable way of introducing hydrological knowledge into data-based models.
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Bastola, Satish, and Conor Murphy. "Sensitivity of the performance of a conceptual rainfall–runoff model to the temporal sampling of calibration data." Hydrology Research 44, no. 3 (November 22, 2012): 484–94. http://dx.doi.org/10.2166/nh.2012.061.
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The effect of the time step of calibration data on the performance of a hydrological model is examined through a numerical experiment where HYMOD, a rainfall–runoff model, is calibrated with data of varying temporal resolution. A simple scaling relationship between the parameters of the model and modelling time step is derived which enables information from daily hydrological records to be used in modelling at time steps much shorter than daily. Model parameters were found to respond differently depending upon the degree of aggregation of calibration data. A loss in performance, especially in terms of the Nash–Sutcliffe measure, is evident when behavioural simulators derived with one modelling time step are used for simulation at another time step. The loss in performance is greater when parameters derived from a longer time step were used for simulating flow with a shorter time step. The application of a simple scaling relationship derived from a multi-time step model calibration significantly decreased the loss in model performance. Such an approach may offer the prospect of conducting higher temporal resolution flood frequency analysis when finer scale data for model calibration are not available or limited.
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Jiang, Shanhu, Liliang Ren, Chong-Yu Xu, Shuya Liu, Fei Yuan, and Xiaoli Yang. "Quantifying multi-source uncertainties in multi-model predictions using the Bayesian model averaging scheme." Hydrology Research 49, no. 3 (April 6, 2017): 954–70. http://dx.doi.org/10.2166/nh.2017.272.
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Abstract This study focuses on a quantitative multi-source uncertainty analysis of multi-model predictions. Three widely used hydrological models, i.e., Xinanjiang (XAJ), hybrid rainfall–runoff (HYB), and HYMOD (HYM), were calibrated by two parameter optimization algorithms, namely, shuffled complex evolution (SCE-UA) method and shuffled complex evolution metropolis (SCEM-UA) method on the Mishui basin, south China. The input uncertainty was quantified by utilizing a normally distributed error multiplier. The ensemble simulation sets calculated from the three models were combined using the Bayesian model averaging (BMA) method. Results indicate the following. (1) Both SCE-UA and SCEM-UA resulted in good and comparable streamflow simulations. Specifically, the SCEM-UA implied parameter uncertainty and provided the posterior distribution of the parameters. (2) In terms of the precipitation input uncertainty, precision of streamflow simulations did not improve remarkably. (3) The BMA combination not only improved the precision of streamflow prediction, but also quantified the uncertainty bounds of the simulation. (4) The prediction interval calculated using the SCEM-UA-based BMA combination approach appears superior to that calculated using the SCE-UA-based BMA combination for both high flows and low flows. Results suggest that the comprehensive uncertainty analysis by using the SCEM-UA algorithm and BMA method is superior for streamflow predictions and flood forecasting.
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Markou, George, Christos Mourlas, Hussein Bark, and Manolis Papadrakakis. "Simplified HYMOD non-linear simulations of a full-scale multistory retrofitted RC structure that undergoes multiple cyclic excitations – An infill RC wall retrofitting study." Engineering Structures 176 (December 2018): 892–916. http://dx.doi.org/10.1016/j.engstruct.2018.08.002.
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Wang, S., G. H. Huang, B. W. Baetz, and W. Huang. "Probabilistic Inference Coupled with Possibilistic Reasoning for Robust Estimation of Hydrologic Parameters and Piecewise Characterization of Interactive Uncertainties." Journal of Hydrometeorology 17, no. 4 (April 1, 2016): 1243–60. http://dx.doi.org/10.1175/jhm-d-15-0131.1.
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Abstract This paper presents a factorial possibilistic–probabilistic inference (FPI) framework for estimation of hydrologic parameters and characterization of interactive uncertainties. FPI is capable of incorporating expert knowledge into the parameter adjustment procedure for enhancing the understanding of the nature of the calibration problem. As a component of the FPI framework, a Monte Carlo–based fractional fuzzy–factorial analysis (MFA) method is also proposed to identify the best parameter set and its underlying probability distributions in a fuzzy probability space. Factorial analysis of variance (ANOVA) coupled with its multivariate extensions are performed to explore potential interactions among model parameters and among hydrological metrics in a systematic manner. The proposed methodology is applied to the Xiangxi River watershed by using the conceptual hydrological model (HYMOD) to demonstrate its validity and applicability. Results reveal that MFA is capable of deriving probability density functions (PDFs) of hydrologic model parameters. Moreover, the sequential inferences derived from the F test and its multivariate approximations disclose the statistical significance of parametric interactions affecting individual and multiple hydrological metrics, respectively. The findings presented here indicate that parametric interactions are complex in a fuzzy stochastic environment, and the magnitude and direction of interaction effects vary in different regions of the parameter space as well as vary temporally because of the dynamic behavior of hydrologic systems.
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Slimani, Camélia, Stéphane Rubini, and Jalil Boukhobza. "HyMAD." ACM SIGBED Review 16, no. 3 (November 25, 2019): 45–50. http://dx.doi.org/10.1145/3373400.3373407.
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Jiang, S., L. Ren, X. Yang, M. Ma, and Y. Liu. "Multi-model ensemble hydrologic prediction and uncertainties analysis." Proceedings of the International Association of Hydrological Sciences 364 (September 16, 2014): 249–54. http://dx.doi.org/10.5194/piahs-364-249-2014.
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Abstract. Modelling uncertainties (i.e. input errors, parameter uncertainties and model structural errors) inevitably exist in hydrological prediction. A lot of recent attention has focused on these, of which input error modelling, parameter optimization and multi-model ensemble strategies are the three most popular methods to demonstrate the impacts of modelling uncertainties. In this paper the Xinanjiang model, the Hybrid rainfall–runoff model and the HYMOD model were applied to the Mishui Basin, south China, for daily streamflow ensemble simulation and uncertainty analysis. The three models were first calibrated by two parameter optimization algorithms, namely, the Shuffled Complex Evolution method (SCE-UA) and the Shuffled Complex Evolution Metropolis method (SCEM-UA); next, the input uncertainty was accounted for by introducing a normally-distributed error multiplier; then, the simulation sets calculated from the three models were combined by Bayesian model averaging (BMA). The results show that both these parameter optimization algorithms generate good streamflow simulations; specifically the SCEM-UA can imply parameter uncertainty and give the posterior distribution of the parameters. Considering the precipitation input uncertainty, the streamflow simulation precision does not improve very much. While the BMA combination not only improves the streamflow prediction precision, it also gives quantitative uncertainty bounds for the simulation sets. The SCEM-UA calculated prediction interval is better than the SCE-UA calculated one. These results suggest that considering the model parameters' uncertainties and doing multi-model ensemble simulations are very practical for streamflow prediction and flood forecasting, from which more precision prediction and more reliable uncertainty bounds can be generated.
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Wi, S., Y. C. E. Yang, S. Steinschneider, A. Khalil, and C. M. Brown. "Calibration approaches for distributed hydrologic models using high performance computing: implication for streamflow projections under climate change." Hydrology and Earth System Sciences Discussions 11, no. 9 (September 17, 2014): 10273–317. http://dx.doi.org/10.5194/hessd-11-10273-2014.
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Abstract. This study utilizes high performance computing to test the performance and uncertainty of calibration strategies for a spatially distributed hydrologic model in order to improve model simulation accuracy and understand prediction uncertainty at interior ungaged sites of a sparsely-gaged watershed. The study is conducted using a distributed version of the HYMOD hydrologic model (HYMOD_DS) applied to the Kabul River basin. Several calibration experiments are conducted to understand the benefits and costs associated with different calibration choices, including (1) whether multisite gaged data should be used simultaneously or in a step-wise manner during model fitting, (2) the effects of increasing parameter complexity, and (3) the potential to estimate interior watershed flows using only gaged data at the basin outlet. The implications of the different calibration strategies are considered in the context of hydrologic projections under climate change. Several interesting results emerge from the study. The simultaneous use of multisite data is shown to improve the calibration over a step-wise approach, and both multisite approaches far exceed a calibration based on only the basin outlet. The basin outlet calibration can lead to projections of mid-21st century streamflow that deviate substantially from projections under multisite calibration strategies, supporting the use of caution when using distributed models in data-scarce regions for climate change impact assessments. Surprisingly, increased parameter complexity does not substantially increase the uncertainty in streamflow projections, even though parameter equifinality does emerge. The results suggest that increased (excessive) parameter complexity does not always lead to increased predictive uncertainty if structural uncertainties are present. The largest uncertainty in future streamflow results from variations in projected climate between climate models, which substantially outweighs the calibration uncertainty.
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Wi, S., Y. C. E. Yang, S. Steinschneider, A. Khalil, and C. M. Brown. "Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change." Hydrology and Earth System Sciences 19, no. 2 (February 10, 2015): 857–76. http://dx.doi.org/10.5194/hess-19-857-2015.
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Abstract. This study tests the performance and uncertainty of calibration strategies for a spatially distributed hydrologic model in order to improve model simulation accuracy and understand prediction uncertainty at interior ungaged sites of a sparsely gaged watershed. The study is conducted using a distributed version of the HYMOD hydrologic model (HYMOD_DS) applied to the Kabul River basin. Several calibration experiments are conducted to understand the benefits and costs associated with different calibration choices, including (1) whether multisite gaged data should be used simultaneously or in a stepwise manner during model fitting, (2) the effects of increasing parameter complexity, and (3) the potential to estimate interior watershed flows using only gaged data at the basin outlet. The implications of the different calibration strategies are considered in the context of hydrologic projections under climate change. To address the research questions, high-performance computing is utilized to manage the computational burden that results from high-dimensional optimization problems. Several interesting results emerge from the study. The simultaneous use of multisite data is shown to improve the calibration over a stepwise approach, and both multisite approaches far exceed a calibration based on only the basin outlet. The basin outlet calibration can lead to projections of mid-21st century streamflow that deviate substantially from projections under multisite calibration strategies, supporting the use of caution when using distributed models in data-scarce regions for climate change impact assessments. Surprisingly, increased parameter complexity does not substantially increase the uncertainty in streamflow projections, even though parameter equifinality does emerge. The results suggest that increased (excessive) parameter complexity does not always lead to increased predictive uncertainty if structural uncertainties are present. The largest uncertainty in future streamflow results from variations in projected climate between climate models, which substantially outweighs the calibration uncertainty.
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Wang, Anqi, and Dimitri P. Solomatine. "Practical Experience of Sensitivity Analysis: Comparing Six Methods, on Three Hydrological Models, with Three Performance Criteria." Water 11, no. 5 (May 22, 2019): 1062. http://dx.doi.org/10.3390/w11051062.
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Currently, practically no modeling study is expected to be carried out without some form of Sensitivity Analysis (SA). At the same time, there is a large number of various methods and it is not always easy for practitioners to choose one. The aim of this paper is to briefly review main classes of SA methods, and to present the results of the practical comparative analysis of applying them. Six different global SA methods: Sobol, eFAST (extended Fourier Amplitude Sensitivity Test), Morris, LH-OAT, RSA (Regionalized Sensitivity Analysis), and PAWN are tested on three conceptual rainfall-runoff models with varying complexity: (GR4J, Hymod, and HBV) applied to the case study of Bagmati basin (Nepal). The methods are compared with respect to effectiveness, efficiency, and convergence. A practical framework of selecting and using the SA methods is presented. The result shows that, first of all, all the six SA methods are effective. Morris and LH-OAT methods are the most efficient methods in computing SI and ranking. eFAST performs better than Sobol, and thus it can be seen as its viable alternative for Sobol. PAWN and RSA methods have issues of instability, which we think are due to the ways Cumulative Distribution Functions (CDFs) are built, and using Kolmogorov–Smirnov statistics to compute Sensitivity Indices. All the methods require sufficient number of runs to reach convergence. Difference in efficiency of different methods is an inevitable consequence of the differences in the underlying principles. For SA of hydrological models, it is recommended to apply the presented practical framework assuming the use of several methods, and to explicitly take into account the constraints of effectiveness, efficiency (including convergence), ease of use, and availability of software.
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Formetta, G., R. Mantilla, S. Franceschi, A. Antonello, and R. Rigon. "The JGrass-NewAge system for forecasting and managing the hydrological budgets at the basin scale: models of flow generation and propagation/routing." Geoscientific Model Development 4, no. 4 (November 4, 2011): 943–55. http://dx.doi.org/10.5194/gmd-4-943-2011.
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Abstract. This paper presents a discussion of the predictive capacity of the implementation of the semi-distributed hydrological modeling system JGrass-NewAge. This model focuses on the hydrological budgets of medium scale to large scale basins as the product of the processes at the hillslope scale with the interplay of the river network. The part of the modeling system presented here deals with the: (i) estimation of the space-time structure of precipitation, (ii) estimation of runoff production; (iii) aggregation and propagation of flows in channel; (v) estimation of evapotranspiration; (vi) automatic calibration of the discharge with the method of particle swarming. The system is based on a hillslope-link geometrical partition of the landscape, combining raster and vectorial treatment of hillslope data with vector based tracking of flow in channels. Measured precipitation are spatially interpolated with the use of kriging. Runoff production at each channel link is estimated through a peculiar application of the Hymod model. Routing in channels uses an integrated flow equation and produces discharges at any link end, for any link in the river network. Evapotranspiration is estimated with an implementation of the Priestley-Taylor equation. The model system assembly is calibrated using the particle swarming algorithm. A two year simulation of hourly discharge of the Little Washita (OK, USA) basin is presented and discussed with the support of some classical indices of goodness of fit, and analysis of the residuals. A novelty with respect to traditional hydrological modeling is that each of the elements above, including the preprocessing and the analysis tools, is implemented as a software component, built upon Object Modelling System v3 and jgrasstools prescriptions, that can be cleanly switched in and out at run-time, rather than at compiling time. The possibility of creating different modeling products by the connection of modules with or without the calibration tool, as for instance the case of the present modeling chain, reduces redundancy in programming, promotes collaborative work, enhances the productivity of researchers, and facilitates the search for the optimal modeling solution.
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Wakamatsu, Hideyuki. "HYMO TWINS SYSTEM." JAPAN TAPPI JOURNAL 56, no. 8 (2002): 1158–64. http://dx.doi.org/10.2524/jtappij.56.1158.
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Dhamge, N. R., A. M. Badar, and N. Z. Baiswarey. "CROP WATER REQUIREMENT BY MODIFIED PENMAN METHOD USING HYMOS." ISH Journal of Hydraulic Engineering 14, no. 3 (January 2008): 28–42. http://dx.doi.org/10.1080/09715010.2008.10514920.
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Voisin, T., A. Erriguible, and C. Aymonier. "A new solvent system: Hydrothermal molten salt." Science Advances 6, no. 17 (April 2020): eaaz7770. http://dx.doi.org/10.1126/sciadv.aaz7770.
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This work proposes a new solvent system composed of a molten salt in pressurized water, so-called hydrothermal molten salt (HyMoS). This system changes the paradigm of the solubility of inorganics in supercritical water. Using as an example NaOH, a low melting temperature salt, we show the possibility to precipitate it at a temperature above its melting one, leading to the instantaneous formation of the HyMoS. The molten salt is then capable of dissolving a large amount of inorganic salt, as exemplified with Na2SO4. This solvent system opens innovative ways with a potential to impact applications in many fields including materials synthesis, biomass conversion, recycling, green chemistry, catalysis, sustainable manufacturing and others. Beyond the impact on the hydrothermal community, this work also offers previously unexplored opportunities for the molten salt field with access to flow chemistry and insights regarding salt precipitation mechanism.
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Whitbeck, John, and Vania Conan. "HYMAD: Hybrid DTN-MANET routing for dense and highly dynamic wireless networks." Computer Communications 33, no. 13 (August 2010): 1483–92. http://dx.doi.org/10.1016/j.comcom.2010.03.005.
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Schroeter, H. O., and R. P. Epp. "Muskingum-Cunge: A Practical Alternative to the HYMO VSC Method for Channel Routing." Canadian Water Resources Journal 13, no. 4 (January 1988): 68–79. http://dx.doi.org/10.4296/cwrj1304068.
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Konradt, Matthias. "Eidenai hekaston hymon to eautou skeuos ktasthai … Zu Paulus' sexualethischer Weisung in 1Thess 4,4 f." Zeitschrift für die Neutestamentliche Wissenschaft und Kunde der Älteren Kirche 92, no. 1-2 (April 2001): 128–35. http://dx.doi.org/10.1515/zntw.92.1-2.128.
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Atanacković, Ana, Ferdinand Šporka, Vanja Marković, Jaroslav Slobodnik, Katarina Zorić, Bela Csányi, and Momir Paunović. "Aquatic Worm Assemblages along the Danube: A Homogenization Warning." Water 12, no. 9 (September 18, 2020): 2612. http://dx.doi.org/10.3390/w12092612.
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In this study, we analyzed the impacts of different environmental conditions on aquatic worm communities along the Danube River, based on two longitudinal surveys, the Joint Danube Surveys 2 and 3 (JDS; 2007 and 2013). We identified the most important environmental factors (among analyzed groups) that shape worm communities: hydromorphlogical alterations, flow velocity and substrate (HYMO group), dissolved oxygen, nitrates and nitrites (physico-chemical parameters), zinc and nickel (metals), monobutyltin cation, benzo(b) fluoranthene and benzo(k)fluoranthene, polychlorinated biphenyls PCB 77 and PCB 118 (selected chemical determinants—organotin compounds, Polycyclic aromatic hydrocarbons—PAHs and PCBs). A homogenization of species composition of Oligochaeta assemblages along the Danube was confirmed. As one of main factors related to biotic homogenization, hydromorphological alterations represented by similar changes in flow velocity and substrates along Danube’s course could be singled out. Our results indicate that Oligochaeta could be used for the identification of the level of hydromorphological degradation in large rivers (homogenization), rather than for stressors classified as nutrient and organic pollutants. Our results provide additional evidence in risk assessment of the environment, contributing in water management and monitoring of the ecological status as proposed by the Water Framework Directive.
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Aleksova, Aneta, Federico Ferro, Giulia Gagno, Laura Padoan, Riccardo Saro, Daniela Santon, Elisabetta Stenner, et al. "Diabetes Mellitus and Vitamin D Deficiency: Comparable Effect on Survival and a Deadly Association after a Myocardial Infarction." Journal of Clinical Medicine 9, no. 7 (July 6, 2020): 2127. http://dx.doi.org/10.3390/jcm9072127.
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Survivors after a myocardial infarction (MI), especially those with diabetes mellitus (DM), remain at high risk of further events. Identifying and treating factors that may influence survival may open new therapeutic strategies. We assessed the impact on prognosis of DM and hypovitaminosis D (hypovitD), alone or combined. In this prospective, observational study, 1081 patients were enrolled surviving an MI and divided into four groups according to their diabetic and VitD status. The primary end-point was composite of all-cause mortality, angina/MI and heart failure (HF). Secondary outcomes were mortality, HF and angina/MI. During a follow-up of 26.1 months (IQR 6.6–64.5), 391 subjects experienced the primary end-point. Patients with DM or hypovitD had similar rate of the composite end-point. Patients with only hypovitD or DM did not differ regarding components of composite end-point (angina p = 0.97, HF p = 0.29, mortality p = 0.62). DM and VitD deficiency had similarly adjusted risks for primary end-point (HR 1.3, 95%CI 1.05–1.61; HR 1.3, 95% CI 1.04–1.64). The adjusted HR for primary composite end-point for patients with hypovitD and DM was 1.69 (95%CI 1.25–2.29, p = 0.001) in comparison to patients with neither hypoD nor DM. In conclusion, DM and hypovitD, individually and synergistically, are associated with a worse outcome after MI.
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Griffiths, Jeremy, Sally Bamber, Graham French, Bethan Hulse, Gwyn Jones, Rhys C. Jones, Susan Jones, Gwawr Maelor Williams, Hazel Wordsworth, and J. Carl Hughes. "Datblygu Athrawon Yfory Gyda'n Gilydd: Partneriaeth Addysg Gychwynnol i Athrawon CaBan." Cylchgrawn Addysg Cymru / Wales Journal of Education 22, no. 1 (March 1, 2020): 209–32. http://dx.doi.org/10.16922/wje.22.1.10.
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Yn y papur hwn rydym yn amlinellu'r athroniaeth a'r gwaith ymchwil sy'n sylfaen i ddatblygiad CaBan – Partneriaeth Addysg Gychwynnol i Athrawon (AGA) a ddatblygwyd er mwyn addysgu athrawon yfory yng ngogledd Cymru. Mae CaBan yn 'bartneriaeth ddysgu' uchelgeisiol sy'n cynnwys pum partner – ysgolion rhanbarthol, Prifysgol Bangor, Prifysgol Caer, y gwasanaeth gwella ysgolion rhanbarthol (GwE), a'r Sefydliad Cydweithredol dros Ymchwil Addysg, Tystiolaeth ac Effaith (CIEREI). Mae pob partner yn gwneud cyfraniad allweddol at wireddu ein huchelgais i gyfrannu at Genhadaeth Ein Cenedl a chyflawni ein gweledigaeth i 'Ddatblygu Athrawon Yfory Gyda'n Gilydd.' Nod sylfaenol CaBan yw cynorthwyo ein Hathrawon Cyswllt newydd i fod yn athrawon creadigol, hynod fedrus sy'n ysbrydoli, a fydd yn cyfrannu at y gwaith o gyflwyno Cwricwlwm i Gymru – cwricwlwm am oes (Llywodraeth Cymru, 2015). Mae'r papur hwn yn amlinellu: (i) ein gweledigaeth a chenhadaeth sylfaenol fel partneriaeth ddysgu; (ii) y dystiolaeth i gefnogi ein saf bwynt addysgegol strategol ar gyfer datblygu athrawon yfory; (iii) cyfraniad hanfodol mentora at ddatblygiad ein Hathrawon Cyswllt fel ymarferwyr adfyfyriol beirniadol; (iv) sut rydym yn integreiddio ymchwil fel elfen hanfodol o'n holl waith; (v) sut mae dyluniad ein rhaglen yn seiliedig ar y cysyniad o ymholiad proffesiynol a dysgu proffesiynol gydol gyrfa yr unigolyn; (vi) y dulliau dysgu penodol sy'n meithrin ymdeimlad Athrawon Cyswllt o'u 'hunaniaeth addysgu'; a (vii) pwysigrwydd diwylliant Cymru a'r iaith Gymraeg mewn addysg, a chyfraniad partneriaeth CaBan at ddatblygu gallu er mwyn helpu i wireddu gweledigaeth Llywodraeth Cymru o filiwn o siaradwyr Cymraeg erbyn 2050.
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Bum Kim, Kue, Hyun-Han Kwon, and Dawei Han. "Bias-correction schemes for calibrated flow in a conceptual hydrological model." Hydrology Research, January 4, 2021. http://dx.doi.org/10.2166/nh.2021.043.
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Abstract We explore post-processing methods that can reduce biases in simulated flow in a hydrological model (HYMOD). Here, three bias-correction methods are compared using a set of calibrated parameters as a baseline (Cases 1 and 5). The proposed bias-correction methods are based on a flow duration curve (Case 2), an autoregressive model based on residuals obtained from simulated flows (Case 3), and a rating curve (Case 4). A clear seasonality representing a more substantial variability in winter than summer was evident in all cases. The extended range of residuals was usually observed in winter, indicating that the HYMOD model may not reproduce high flows appropriately. This study confirmed that bias-corrected flows are more effective than the baseline model in terms of correcting a systematic error in the simulated flow. Moreover, a comparison of root mean square error over different flow regimes demonstrates that Case 3 is the most effective at correcting systematic biases over the entire flow regime. Finally, monthly water balances for all cases are evaluated and compared during both calibration and validation periods. The water balance in Case 3 is also closer to the observed values. The effects of different post-processing approaches on the performance of bias-correction are examined and discussed.
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"HYMO CORPORATION." JAPAN TAPPI JOURNAL 69, no. 12 (2015): 1339–44. http://dx.doi.org/10.2524/jtappij.69.1339.
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"Three new products from the hymed group." Journal of Equine Veterinary Science 18, no. 11 (November 1998): 757. http://dx.doi.org/10.1016/s0737-0806(98)80514-5.
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