Bibliografías temáticas / Hydrologic models

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Literatura académica sobre el tema "Hydrologic models"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Hydrologic models"

1

Sahu, Chinmayee, and Surendra Kumar Chandniha. "A Brief Review on Hydrological Modelling." International Journal of Environment and Climate Change 15, no. 1 (2025): 352–68. https://doi.org/10.9734/ijecc/2025/v15i14697.

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The interaction between water, climate, soil and land use is primary to the hydrological modelling concept. Hydrological models include spatial and temporal features. Hydrologists utilize hydrologic models as a primary tool for a variety of tasks including managing water resources, managing urban and rural areas, modelling ground water and more. In order to implement hydrologic models with ease, it is necessary to thoroughly comprehend their properties which have been developed and improved through the years. It is difficult to categorize hydrologic models precisely and various hydrologists ma
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Guilpart, Etienne, Vahid Espanmanesh, Amaury Tilmant, and François Anctil. "Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models." Hydrology and Earth System Sciences 25, no. 8 (2021): 4611–29. http://dx.doi.org/10.5194/hess-25-4611-2021.

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Abstract. The impacts of climate and land-use changes make the stationary assumption in hydrology obsolete. Moreover, there is still considerable uncertainty regarding the future evolution of the Earth’s climate and the extent of the alteration of flow regimes. Climate change impact assessment in the water sector typically involves a modelling chain in which a hydrological model is needed to generate hydrologic projections from climate forcings. Considering the inherent uncertainty of the future climate, it is crucial to assess the performance of the hydrologic model over a wide range of clima
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Mendoza, Pablo A., Martyn P. Clark, Naoki Mizukami, et al. "Effects of Hydrologic Model Choice and Calibration on the Portrayal of Climate Change Impacts." Journal of Hydrometeorology 16, no. 2 (2015): 762–80. http://dx.doi.org/10.1175/jhm-d-14-0104.1.

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Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located
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Sarker, Shiblu, and Olkeba Tolessa Leta. "Review of Watershed Hydrology and Mathematical Models." Eng 6, no. 6 (2025): 129. https://doi.org/10.3390/eng6060129.

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This study provides a comprehensive overview of watershed hydrology and mathematical models, focusing on its hydrological features and the implementation of hydrological modeling for effective water resource modeling and assessment, planning, and management. The study presents a thorough review of the primary transport mechanisms of water within a watershed, particularly the river network, and examines its physical and stochastic characteristics. It also discusses the derivation of governing equations for various hydrological processes within a watershed, including evaluating their applicabili
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Ganoulis, J. "Modeling Hydrologic Phenomena [Free opinion]." Revue des sciences de l'eau 9, no. 4 (2005): 421–34. http://dx.doi.org/10.7202/705260ar.

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With the aim of suggesting some practical rules for the use of hydrological models, G. De MARSILY in his "free opinion" (Rev. Sci. Eau 1994, 7(3): 219-234) proposes a classification of hydrologic models into two categories: - models built on data (observable phenomena) and ; - models without any available observations (unobservable phenomena). He claims that for the former group of observable phenomena, models developed through a learning process as well as those based on the underlying physical laws are of the black box type. For the latter group of unobservable phenomena, he suggests that ph
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Abbas, Ather, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho. "AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods." Geoscientific Model Development 15, no. 7 (2022): 3021–39. http://dx.doi.org/10.5194/gmd-15-3021-2022.

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Abstract. Machine learning has shown great promise for simulating hydrological phenomena. However, the development of machine-learning-based hydrological models requires advanced skills from diverse fields, such as programming and hydrological modeling. Additionally, data pre-processing and post-processing when training and testing machine learning models are a time-intensive process. In this study, we developed a python-based framework that simplifies the process of building and training machine-learning-based hydrological models and automates the process of pre-processing hydrological data a
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7

Naik, M. Ravi, and Dr MVSS Giridhar. "Spatial Variability of Rainfall and Classification of Peninsular Indian Catchments." International Journal of Advanced Engineering and Nano Technology 10, no. 12 (2023): 8–15. http://dx.doi.org/10.35940/ijaent.f4214.12101223.

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The strength and success of hydrological analysis depend upon the quantity and quality of observed data. In the recent past, the availability of advanced computing facilities and measurement techniques had a great impact on the field of hydrology, especially in hydrologic analysis and hydrologic modeling. In spite of such growth, the present hydrologic modeling has certain challenges: complexity (involving a large number of parameters), applicability to a specific region (difficult to generalize for other regions), and lack of understanding of the connection between model theories and the actu
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8

Pawitan, Hidayat, and Muh Taufik. "Non-linear Routing Scheme at Grid Cell Level for Large Scale Hydrologic Models: A Review." Agromet 35, no. 2 (2021): 60–72. http://dx.doi.org/10.29244/j.agromet.35.2.60-72.

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New tools and concepts in the form of mathematical models, remote sensing and Geographic Information System (GIS), communication and telemetering have been developed for the complex hydrologic systems that permit a different analysis of processes and allow watershed to be considered as an integrated planning and management unit. Hydrological characteristics can be generated through spatial analysis, and ready for input into a distributed hydrologic models to define adequately the hydrological response of a watershed that can be related back to the specific environmental, climatic, and geomorph
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Perra, Enrica, Monica Piras, Roberto Deidda, et al. "Multimodel assessment of climate change-induced hydrologic impacts for a Mediterranean catchment." Hydrology and Earth System Sciences 22, no. 7 (2018): 4125–43. http://dx.doi.org/10.5194/hess-22-4125-2018.

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Abstract. This work addresses the impact of climate change on the hydrology of a catchment in the Mediterranean, a region that is highly susceptible to variations in rainfall and other components of the water budget. The assessment is based on a comparison of responses obtained from five hydrologic models implemented for the Rio Mannu catchment in southern Sardinia (Italy). The examined models – CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and Integration (TOPKAPI), TIN-based Real time Integrated Basin Simulator (tRIBS), and WAter bala
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Ravi, Naik. "Spatial Variability of Rainfall and Classification of Peninsular Indian Catchments." International Journal of Advanced Engineering and Nano Technology (IJAENT) 10, no. 12 (2023): 8–15. https://doi.org/10.35940/ijaent.F4214.12101223.

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<strong>Abstract: </strong>The strength and success of hydrological analysis depend upon the quantity and quality of observed data. In the recent past, the availability of advanced computing facilities and measurement techniques had a great impact on the field of hydrology, especially in hydrologic analysis and hydrologic modeling. In spite of such growth, the present hydrologic modeling has certain challenges: complexity (involving a large number of parameters), applicability to a specific region (difficult to generalize for other regions), and lack of understanding of the connection between
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Tesis sobre el tema "Hydrologic models"

1

Boyle, Douglas Patrick. "Multicriteria calibration of hydrologic models." Diss., The University of Arizona, 2001. http://hdl.handle.net/10150/290657.

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The level of spatial and vertical detail of important hydrologic processes within a watershed that needs to be represented by a conceptual rainfall-runoff (CRR) model in order to accurately simulate the streamflow is not well understood. The paucity of high-resolution hydrologic information in the past guided the direction of model development to more accurately represent processes directly related to the vertical movement of moisture within the watershed rather than the spatial variability of these processes. As a result, many of the CRR models currently available are so complex (vertically),
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Thoms, R. Brad. "Simulating fully coupled overland and variably saturated subsurface flow using MODFLOW /." Full text open access at:, 2003. http://content.ohsu.edu/u?/etd,16.

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Loaiza, Usuga Juan Carlos. "Soil hydrology in the Ribera Salada Catchment (Catalan PrePyrenees): application of hydrologic models for the estimation of hydrologic transitional regimes." Doctoral thesis, Universitat de Lleida, 2007. http://hdl.handle.net/10803/8235.

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El principal objectiu d'aquesta investigació és estudiar la dinàmica hidrològica d'una conca Mediterrània<br/>afectada per canvis d'ús del sòl, mitjançant el monitoreig d'aquest i de l'aigua superficial. Aquest<br/>objectiu s'ha treballat a partir mesuraments de components del balanç hídric pels diferents tipus de<br/>cobertura i sòl, amb règims d'humitat i temperatura de transició.<br/>Aquest estudi s'ha realitzat a la conca de la Ribera Salada (Prepirineu meridional Català, al NE<br/>d'Espanya), amb una extensió de 222.5 km2, i un interval altitudinal de 420 a 2385 m i predomini de<br/>pende
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Shamir, Eylon. "Use of streamflow indices in hydrologic modeling." Diss., The University of Arizona, 2003. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_2003_396_sip1_w.pdf&type=application/pdf.

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Chen, Mi. "Using an integrated linkage method to predict hydrological responses of a mixed land use watershed." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu.

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Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xvi, 378 p.; also includes graphics (some col.). Includes bibliographical references (p. 229-252). Available online via OhioLINK's ETD Center
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Wang, Ying. "Uncertainty analysis of geomorphologic instantaneous unit hydrograph for hydrosystems reliability evaluation /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202005%20WANG.

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Miller, Scott N. "Scale effects of geometric complexity, misclassification error and land cover change in distributed hydrologic modeling." Diss., The University of Arizona, 2002. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_2002_216_sip1_w.pdf&type=application/pdf.

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Furman, Alexander. "Steps towards the implementation of ERT for monitoring of transient hydrological processes." Diss., The University of Arizona, 2003. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_2003_271_sip1_w.pdf&type=application/pdf.

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Choi, Chi Chi. "Coupled Hydrologic And Hydraulic Models And Applications." Thesis, University of Iowa, 2013. https://ir.uiowa.edu/etd/4955.

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Cherkauer, Keith Aric. "Understanding the hydrologic effects of frozen soil /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/10164.

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Libros sobre el tema "Hydrologic models"

1

United States. Bureau of Reclamation. and Global Climate Change Response Program (U.S.), eds. Inventory of hydrologic models. U.S. Dept. of the Interior, Bureau of Reclamation, 1991.

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P, Singh V. Hydrologic systems. Prentice Hall, 1988.

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P, Singh V. Hydrologic systems. Prentice Hall, 1989.

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Singh, Vijay P. Hydrologic systems. Prentice Hall, 1989.

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5

Hromadka, Theodore V. Hydrologic modeling for the arid southwest United States. Lighthouse Publications, 1996.

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United States. Soil Conservation Service. Hydrologic analysis report: Hatchie River Basin Special Study, Tennessee and Mississippi. The Service, 1986.

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Hans-B, Kleeberg, and Deutsche Forschungsgemeinschaft, eds. Hydrologie und Regionalisierung: Ergebnisse eines Schwerpunktprogramms (1992 bis 1998) : Forschungsbericht. Wiley-VCH, 1999.

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Ward, R. C. The catchwater drain experimental catchment: FORTRAN listing of a hydrological model. Dept. of Geography, University of Hull, 1986.

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Ladislav, Kašpárek, ed. Water resources of the Intra-Sudeten Basin: Results of the Czech-Polish co-operation in monitoring and modelling (1975-2004). Ministry of the Environment of the Czech Republic, 2006.

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Omar, Mhirit, and Mhamdi Allal, eds. L'essentiel des méthodes et instrumentation en écophysiologie. Zaouia, 2007.

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Capítulos de libros sobre el tema "Hydrologic models"

1

Makboul, Omar, Abdelazim Negm, Saleh Mesbah, and Mohamed Mohasseb. "Assessment of Different Bathymetry Statistical Models Using Landsat-8 Multispectral Images." In Hydrologic Modeling. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5801-1_20.

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Adamala, Sirisha, N. S. Raghuwanshi, and Ashok Mishra. "Development of Generalized Higher-Order Neural Network-Based Models for Estimating Pan Evaporation." In Hydrologic Modeling. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5801-1_5.

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Boyle, Douglas P., Hoshin V. Gupta, and Soroosh Sorooshian. "Multicriteria calibration of hydrologic models." In Water Science and Application. American Geophysical Union, 2003. http://dx.doi.org/10.1029/ws006p0185.

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Cunnane, Conleth. "Review of Statistical Models for Flood Frequency Estimation." In Hydrologic Frequency Modeling. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3953-0_4.

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Nissan, Edward. "Statistical Models for Flood Frequency Estimation of the Mississippi and Yazoo Rivers." In Hydrologic Frequency Modeling. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3953-0_6.

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Park, Hotaek, Yonas Dibike, Fengge Su, and John Xiaogang Shi. "Cold Region Hydrologic Models and Applications." In Arctic Hydrology, Permafrost and Ecosystems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50930-9_26.

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Keller, Carl. "FLUTe Calculational Models." In Hydrologic Measurements with Flexible Liners and Other Applications. CRC Press, 2022. http://dx.doi.org/10.1201/9781003268376-16.

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Sorooshian, Soroosh. "Parameter Estimation, Model Identification, and Model Validation: Conceptual-Type Models." In Recent Advances in the Modeling of Hydrologic Systems. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3480-4_20.

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Cherian, M. P., and Prabir Kumar Pal. "Transfer Function Models for Hydrologic Flood Routing." In Water Science and Technology Library. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-011-0389-3_21.

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Smith, R. E., and V. A. Ferreira. "Comparative Evaluation of Unsaturated Flow Methods in Selected USDA Simulation Models." In Unsaturated Flow in Hydrologic Modeling. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2352-2_14.

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Actas de conferencias sobre el tema "Hydrologic models"

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Meselhe, E. A., E. Habib, O. C. Oche, and S. Gautam. "Performance Evaluation of Physically Based Distributed Hydrologic Models and Lumped Hydrologic Models." In World Water and Environmental Resources Congress 2004. American Society of Civil Engineers, 2004. http://dx.doi.org/10.1061/40737(2004)211.

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Cleveland, Theodore G., William Botkins, and David B. Thompson. "Small Watershed Response Models: Hydrologic or Hydraulic?" In World Environmental and Water Resources Congress 2008. American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)59.

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Hoblit, Brian C., and David C. Curtis. "Integration of Radar Rainfall into Hydrologic Models." In Ninth International Conference on Urban Drainage (9ICUD). American Society of Civil Engineers, 2002. http://dx.doi.org/10.1061/40644(2002)229.

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Tripathi, Shivam, and Rao S. Govindaraju. "Statistical Feature Selection for Hydrologic Prediction Models." In World Environmental and Water Resources Congress 2007. American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40927(243)420.

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Watkins, Jr., David W., Hebi Li, Kenneth A. Thiemann, and Thomas E. Adams, III. "Radar Rainfall Estimates for Great Lakes Hydrologic Models." In World Water and Environmental Resources Congress 2003. American Society of Civil Engineers, 2003. http://dx.doi.org/10.1061/40685(2003)217.

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Clar, M. L., and C. Smith. "Using Field Bankfull Measurements to Calibrate Hydrologic Models." In Protection and Restoration of Urban and Rural Streams Symposium. American Society of Civil Engineers, 2004. http://dx.doi.org/10.1061/40695(2004)48.

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Bao, Tianshu, Taylor Thomas Johnson, and Xiaowei Jia. "Transfer Learning Using Inaccurate Physics Rule for Streamflow Prediction." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/793.

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Accurate streamflow prediction is critical for ensuring water supply and detecting floods, while also providing essential hydrological inputs for other scientific models in fields such as climate and agriculture. Recently, deep learning models have been shown to achieve state-of-the-art regionalization performance by building a global hydrologic model. These models predict streamflow given catchment physical characteristics and weather forcing data. However, these models are only focused on gauged basins and cannot adapt to ungaugaed basins, i.e., basins without training data. Prediction in Un
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Gabriel G Vazquez-Amabile, Pablo A Mercuri, Fernanda J Gaspari, and Bernard A Engel. "Construction of a Digital Hydrologic Soil Group Map for Argentina to Simulate Runoff Using GIS - Hydrologic Models." In 21st Century Watershed Technology: Improving Water Quality and Environment Conference Proceedings, 29 March - 3 April 2008, Concepcion, Chile. American Society of Agricultural and Biological Engineers, 2008. http://dx.doi.org/10.13031/2013.24333.

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Ackerman, Cameron T., Matthew J. Fleming, and Gary W. Brunner. "Hydrologic and Hydraulic Models for Performing Dam Break Studies." In World Environmental and Water Resources Congress 2008. American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)285.

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Ebtehaj, Mohammad, and Hamid Moradkhani. "Parameter Uncertainty Estimation of Hydrologic Models Using Bootstrap Resampling." In World Environmental and Water Resources Congress 2009. American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41036(342)632.

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Informes sobre el tema "Hydrologic models"

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Gutenson, Joseph, Kent Sparrow, Stephen Brown, Mark Wahl, and Kyle Gordon. Case study of continental-scale hydrologic modeling’s ability to predict daily streamflow percentiles for regulatory application. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49371.

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Regulatory practitioners use hydroclimatic data to provide context to observations typically collected through field site visits and aerial imagery analysis. In the absence of site-specific data, regulatory practitioners must use proxy hydroclimatic data and models to assess a stream's hydroclimatology. One intent of current-generation continental-scale hydrologic models is to provide such hydrologic context to ungaged watersheds. In this study, the ability of two state-of-the-art, operational, continental-scale hydrologic modeling frameworks, the National Water Model and the Group on Earth Ob
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Pruitt, Bruce. Readily available hydrologic models : pertinence to regulatory application. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/38031.

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Hamill, Daniel D., Jeremy J. Giovando, Chandler S. Engel, Travis A. Dahl, and Michael D. Bartles. Application of a Radiation-Derived Temperature Index Model to the Willow Creek Watershed in Idaho, USA. U.S. Army Engineer Research and Development Center, 2021. http://dx.doi.org/10.21079/11681/41360.

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The ability to simulate snow accumulation and melting processes is fundamental to developing real-time hydrological models in watersheds with a snowmelt-dominated flow regime. A primary source of uncertainty with this model development approach is the subjectivity related to which historical periods to use and how to combine parameters from multiple calibration events. The Hydrologic Engineering Center, Hydrological Modeling System, has recently implemented a hybrid temperature index (TI) snow module that has not been extensively tested. This study evaluates a radiatative temperature index (RT
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Zhang, Zhonglong, and Billy E. Johnson. Aquatic Contaminant and Mercury Simulation Modules Developed for Hydrologic and Hydraulic Models. Defense Technical Information Center, 2016. http://dx.doi.org/10.21236/ad1013220.

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King, Ryan, Ariel Miara, Andrew Glaws, and Jordan Macknick. Improving Short Term Predictability of Hydrologic Models with Deep Learning. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769722.

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Hasan, Abdulghani. Flood Modelling Tool : an integrated GIS and hydrological modelling tool for planning nature-based solutions in the urban environment. Faculty of Landscape Architecture, Horticulture and Crop Production Science, Swedish University of Agricultural Sciences, 2024. http://dx.doi.org/10.54612/a.5s9t2ca774.

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The risk of pluvial flooding is going to increase as climate change causes an increase in intense precipitation along with urbanisation leading to an increase in impermeable surfaces. In the last decade, cities such as Malmö and Copenhagen have already experienced severe pluvial flooding that has caused extensive damage. Adapting to climate change by creating flood resilient urban areas is therefore important and blue-green infrastructure (BGI) may be one measure to accomplish this. A hydrological model called TFM-DYN has been used to investigate whether BGI can aid the mitigation of pluvial f
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Pradhan, Nawa Raj, Ian Floyd, and Charles Downer. User guidelines on catchment post-wildfire hydrological modeling. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49800.

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Wildfires significantly alter watershed hydrology by increasing runoff due to reduced infiltration from soil-water repellency. To predict long-term wildfire impacts, a coupled framework was developed to simulate postfire changes in soil hydraulic properties, infiltration, and hydrological response. This framework integrates Wildfire-Induced Soil Hydraulic (WISH) Factors with a Soil-Moisture Threshold (SMT) formulation in the Green and Ampt infiltration model, representing reduced infiltration due to water repellency. Postfire inputs, including burn severity, soil type, and land use, are format
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Shen, Chaopeng, Forrest Hoffman, and Chonggang Xu. Integrated parameter and process learning for hydrologic and biogeochemical modules in Earth System Models. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769724.

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Lettenmaier, Dennis P. Hydrologic Extremes in a changing climate: how much information can regional climate models provide? Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1111419.

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Matus, Sean, and Daniel Gambill. Automation of gridded HEC-HMS model development using Python : initial condition testing and calibration applications. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46126.

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The US Army Corps of Engineers’s (USACE) Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) rainfall-runoff model is widely used within the research community to develop both event-based and continuous rainfall-runoff models. The soil moisture accounting (SMA) algorithm is commonly used for long-term simulations. Depending on the final model setup, 12 to 18 parameters are needed to characterize the modeled watershed’s canopy, surface, soil, and routing processes, all of which are potential calibration parameters. HEC-HMS includes optimization tools to facilitate model calibrati
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