Relevant bibliographies by topics / Hydrologic Method

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  1. Journal articles

Academic literature on the topic 'Hydrologic Method'

Author: Grafiati
Published: 6 September 2023
Last updated: 7 September 2023

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Journal articles on the topic "Hydrologic Method"

1

Vu, T. T., J. Kiesel, B. Guse, and N. Fohrer. "Towards an improved understanding of hydrological change – linking hydrologic metrics and multiple change point tests." Journal of Water and Climate Change 10, no. 4 (2018): 743–58. http://dx.doi.org/10.2166/wcc.2018.068.

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Abstract Understanding the connections between climate, anthropogenic impacts, and hydrology is fundamental for assessing future climate change. However, a comprehensive methodology is lacking to understand significant changes in the discharge regime and their causes. We propose an approach that links change point tests with hydrologic metrics applied to two Vietnamese catchments where both climatic and anthropogenic changes are observed. The change points in discharge series are revealed by six widely used change point tests. Then, 171 hydrologic metrics are investigated to evaluate all possible hydrological changes that occurred between the pre- and post-change point period. The tests showed sufficient capabilities to detect hydrological changes caused by precipitation alterations and damming. Linking the change point tests to the hydrological metrics had three benefits: (1) the significance of each detected change point was evaluated, (2) we found which test responds to which hydrologic metric, and (3) we were able to disentangle the hydrological impacts of the climatic and anthropogenic changes. Due to its objectivity, the presented method can improve the interpretation of anthropogenic changes and climate change impacts on the hydrological system.
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2

Meng, Xiao, Wu Qun Cheng, and Xian Bing Wu. "Application of Progressive Teaching Model in Engineering Hydrology and Hydrologic Calculation." Advanced Materials Research 919-921 (April 2014): 2185–88. http://dx.doi.org/10.4028/www.scientific.net/amr.919-921.2185.

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Engineering hydrology and hydrologic calculation is a core professional course of agricultural hydrologic engineering, in order to realize the implementation of quality education in higher school teaching purposes, with the teaching practice of engineering hydrology and hydrologic calculation, puts forward the progressive teaching mode of engineering hydrology and hydrologic calculation, and applied in teaching activities. The conception of progressive teaching mode and practice was summarized from four aspects of progressive teaching objective, teaching content, gradual progressive teaching method, and progressive ability.
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3

Zuo, Q., and S. Liang. "Effects of dams on river flow regime based on IHA/RVA." Proceedings of the International Association of Hydrological Sciences 368 (May 7, 2015): 275–80. http://dx.doi.org/10.5194/piahs-368-275-2015.

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Abstract. The river hydrologic regime is a driving force of the river ecosystem. Operation of dams and sluices has significant impacts on rivers’ hydrological situation. Taking the example of the Shaying River, the Jieshou hydrologic section was selected to study the influence of the sluice and all its upstream dams on the hydrologic regime. Using 55 years of measured daily flows at Jieshou hydrologic station, the hydrological date were divided into two series as pre- and post-impact periods. Based on the IHA, the range of variability in 33 flow parameters was calculated, and the hydrologic alteration associated with dams and sluices operation was quantified. Using the RVA method, hydrologic alteration at the stream gauge site was assessed to demonstrate the influence of dams on the hydrological condition. The results showed that dams have a strong influence on the regime; the river eco-hydrological targets calculated in this study can afford some support for water resources and ecosystem management of Shaying River.
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Bauser, Hannes H., Daniel Berg, Ole Klein, and Kurt Roth. "Inflation method for ensemble Kalman filter in soil hydrology." Hydrology and Earth System Sciences 22, no. 9 (2018): 4921–34. http://dx.doi.org/10.5194/hess-22-4921-2018.

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Abstract. The ensemble Kalman filter (EnKF) is a popular data assimilation method in soil hydrology. In this context, it is used to estimate states and parameters simultaneously. Due to unrepresented model errors and a limited ensemble size, state and parameter uncertainties can become too small during assimilation. Inflation methods are capable of increasing state uncertainties, but typically struggle with soil hydrologic applications. We propose a multiplicative inflation method specifically designed for the needs in soil hydrology. It employs a Kalman filter within the EnKF to estimate inflation factors based on the difference between measurements and mean forecast state within the EnKF. We demonstrate its capabilities on a small soil hydrologic test case. The method is capable of adjusting inflation factors to spatiotemporally varying model errors. It successfully transfers the inflation to parameters in the augmented state, which leads to an improved estimation.
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5

Javadinejad, Safieh. "A review on homogeneity across hydrological regions." Resources Environment and Information Engineering 3, no. 1 (2021): 124–37. http://dx.doi.org/10.25082/reie.2021.01.004.

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Hydrologic classification is the method of scientifically arranging streams, rivers or catchments into groups with the most similarity of flow regime features and use it to recognize hydrologically homogenous areas. Previous homogeneous attempts were depended on overabundance of hydrologic metrics that considers features of variability of flows that are supposed to be meaningful in modelling physical progressions in the basins. This research explains the techniques of hydrological homogeneity through comparing past and existing methods; in addition it provides a practical framework for hydrological homogeneity that illustrates serious elements of the classification process.
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6

Herman, J. D., J. B. Kollat, P. M. Reed, and T. Wagener. "Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models." Hydrology and Earth System Sciences 17, no. 7 (2013): 2893–903. http://dx.doi.org/10.5194/hess-17-2893-2013.

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Abstract. The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) over a six-month period in the Blue River watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly screen the most and least sensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. The method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.
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7

Herman, J. D., J. B. Kollat, P. M. Reed, and T. Wagener. "Technical note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models." Hydrology and Earth System Sciences Discussions 10, no. 4 (2013): 4275–99. http://dx.doi.org/10.5194/hessd-10-4275-2013.

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Abstract. The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) model over a six-month period in the Blue River Watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly identify sensitive and insensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. Method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.
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8

Wang, Jie, Guoqing Wang, Amgad Elmahdi, et al. "Comparison of hydrological model ensemble forecasting based on multiple members and ensemble methods." Open Geosciences 13, no. 1 (2021): 401–15. http://dx.doi.org/10.1515/geo-2020-0239.

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Abstract Ensemble hydrologic forecasting which takes advantages of multiple hydrologic models has made much contribution to water resource management. In this study, four hydrological models (the Xin’anjiang model (XAJ), Simhyd, GR4J, and artificial neural network (ANN) models) and three ensemble methods (the simple average, black box-based, and binomial-based methods) were applied and compared to simulate the hydrological process during 1979–1983 in three representative catchments (Daixi, Hengtangcun, and Qiaodongcun). The results indicate that for a single model, the XAJ model and the GR4J model performed relatively well with averaged Nash and Sutcliffe efficiency coefficient (NSE) values of 0.78 and 0.83, respectively. For the ensemble models, the results show that the binomial-based ensemble method (dynamic weight) outperformed with water volume error reduced by 0.8% and NSE value increased by 0.218. The best performance on runoff forecasting occurs in the Hengtang catchment by integrating four hydrologic models based on binomial ensemble method, achieving the water volume error of 2.73% and NSE value of 0.923. Finding would provide scientific support to water engineering design and water resources management in the study areas.
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9

He, Shaokun, Shenglian Guo, Zhangjun Liu, Jiabo Yin, Kebing Chen, and Xushu Wu. "Uncertainty analysis of hydrological multi-model ensembles based on CBP-BMA method." Hydrology Research 49, no. 5 (2018): 1636–51. http://dx.doi.org/10.2166/nh.2018.160.

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Abstract Quantification of the inherent uncertainty in hydrologic forecasting is essential for flood control and water resources management. The existing approaches, such as Bayesian model averaging (BMA), hydrologic uncertainty processor (HUP), copula-BMA (CBMA), aim at developing reliable probabilistic forecasts to characterize the uncertainty induced by model structures. In the probability forecast framework, these approaches either assume the probability density function (PDF) to follow a certain distribution, or are unable to reduce bias effectively for complex hydrological forecasts. To overcome these limitations, a copula Bayesian processor associated with BMA (CBP-BMA) method is proposed with ensemble lumped hydrological models. Comparing with the BMA and CBMA methods, the CBP-BMA method relaxes any assumption on the distribution of conditional PDFs. Several evaluation criteria, such as containing ratio, average bandwidth and average deviation amplitude of probabilistic application, are utilized to evaluate the model performance. The case study results demonstrate that the CBP-BMA method can improve hydrological forecasting precision with higher cover ratios more than 90%, which are increased by 4.4% and 3.2%, 2.2% and 1.7% over those of BMA and CBMA during the calibration and validation periods, respectively. The proposed CBP-BMA method provides an alternative approach for uncertainty estimation of hydrological multi-model forecasts.
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10

Patil, Vaishnavi Kiran, Vidya R. Saraf, Omkesh V. Karad, Swapnil B. Ghodke, Dnyanesvar Gore, and Shweta S. Dhekale. "Simulation of Rainfall Runoff Process Using HEC-HMS Model for Upper Godavari Basin Maharashtra, India." European Journal of Engineering Research and Science 4, no. 4 (2019): 102–7. http://dx.doi.org/10.24018/ejers.2019.4.4.927.

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The Hydrologic Engineering Centers Hydrologic Modeling System (HEC-HMS) is a popularly used watershed model to simulate rainfall- runoff process. Hydrological modeling is a commonly used tool to estimate the basin’s hydrological response due to precipitation. It allows to predict the hydrologic response to various watershed management practices and to have a better understanding of the impacts of these practices. It is evident from the extensive review of the literature that the studies on comparative assessment of watershed models for hydrologic simulations are very much limited in developing countries including India. In this study, modified SCS Curve Number method is applied to determine loss model as a major component in rainfall-runoff modeling. The study of HEC-HMS model is used to simulate rainfallrunoff process in Nashik region (Upper Godavari basin), Maharashtra. To compute runoff volume, peak runoff rate, and flow routing methods SCS curve number, SCS unit hydrograph, Exponential recession and Muskingum routing methods are chosen, respectively. The results of the present study indicate that HEC-HMS tool applied to watershed proved to be useful in achieving the various objectives. The study confirmed a significant increase in runoff as a result of urbanization. It is a powerful tool for flood forecasting Index
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