Relevant bibliographies by topics / Rainfall runoff model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Rainfall runoff model'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Rainfall runoff model"

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Bartlett, M. S., E. Daly, J. J. McDonnell, A. J. Parolari, and A. Porporato. "Stochastic rainfall-runoff model with explicit soil moisture dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2183 (November 2015): 20150389. http://dx.doi.org/10.1098/rspa.2015.0389.

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Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF.
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Moore, R. J. "The PDM rainfall-runoff model." Hydrology and Earth System Sciences 11, no. 1 (January 17, 2007): 483–99. http://dx.doi.org/10.5194/hess-11-483-2007.

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Abstract. The Probability Distributed Model, or PDM, has evolved as a toolkit of model functions that together constitute a lumped rainfall-runoff model capable of representing a variety of catchment-scale hydrological behaviours. Runoff production is represented as a saturation excess runoff process controlled by the absorption capacity (of the canopy, surface and soil) whose variability within the catchment is characterised by a probability density function of chosen form. Soil drainage to groundwater is controlled by the water content in excess of a tension threshold, optionally inhibited by the water content of the receiving groundwater store. Alternatively, a proportional split of runoff to fast (surface storage) and slow (groundwater) pathways can be invoked with no explicit soil drainage function. Recursive solutions to the Horton-Izzard equation are provided for routing flows through these pathways, conveniently considered to yield the surface runoff and baseflow components of the total flow. An alternative routing function employs a transfer function that is discretely-coincident to a cascade of two linear reservoirs in series. For real-time flow forecasting applications, the PDM is complemented by updating methods based on error prediction and state-correction approaches. The PDM has been widely applied throughout the world, both for operational and design purposes. This experience has allowed the PDM to evolve to its current form as a practical toolkit for rainfall-runoff modelling and forecasting.
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Todini, E. "The ARNO rainfall—runoff model." Journal of Hydrology 175, no. 1-4 (February 1996): 339–82. http://dx.doi.org/10.1016/s0022-1694(96)80016-3.

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Basha, H. A. "Simple Nonlinear Rainfall-Runoff Model." Journal of Hydrologic Engineering 5, no. 1 (January 2000): 25–32. http://dx.doi.org/10.1061/(asce)1084-0699(2000)5:1(25).

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Buchtele, Josef. "Runoff changes simulated using a rainfall-runoff model." Water Resources Management 7, no. 4 (1993): 273–87. http://dx.doi.org/10.1007/bf00872285.

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Swathi, V., K. Srinivasa Raju, Murari R. R. Varma, and S. Sai Veena. "Automatic calibration of SWMM using NSGA-III and the effects of delineation scale on an urban catchment." Journal of Hydroinformatics 21, no. 5 (July 18, 2019): 781–97. http://dx.doi.org/10.2166/hydro.2019.033.

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Abstract The study aims at calibration of the storm water management model (SWMM) with non-dominated sorting genetic algorithm-III (NSGA-III) for urban catchment in Hyderabad, India. The SWMM parameters calibrated were Manning's roughness coefficient (N), depression storage for pervious and impervious areas (DP and Di), sub-catchment width (W), curve number (CN), drying time (dry) of soil and percentage of imperviousness (I). The efficacy of calibration was evaluated by comparing the observed and simulated peak flows and runoff using goodness-of-fit indices. The calibration takes into consideration eight event rainfalls resulting in eight calibrated sets. Weights of goodness-of-fit indices were estimated and the best calibrated set was further validated for five continuous rainfalls/runoffs. Simulated runoff volume and peak runoff over the five continuous rainfalls deviated by 7–22% and 2–20% with respect to observed data. Results indicated that parameters calibrated for an event rainfall could be used for continuous rainfall-runoff modelling. The effect of catchment delineation scale on runoff was also studied. The study indicated that output of the model was sensitive to variation in parameter values of infiltration and imperviousness.
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Furumai, H., H. K. P. K. Jinadasa, M. Murakami, F. Nakajima, and R. K. Aryal. "Model description of storage and infiltration functions of infiltration facilities for urban runoff analysis by a distributed model." Water Science and Technology 52, no. 5 (September 1, 2005): 53–60. http://dx.doi.org/10.2166/wst.2005.0108.

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Although there have been simulation researches focusing on reduction of stormwater peak flow by introduced infiltration facilities, model simulation of dynamic runoff behavior is still limited for frequently occurring rainfall events with weak intensity. Therefore, dynamic simulation was carried out in two urban drainages with infiltration facilities incorporated with a distributed model using two methods for describing functions of infiltration facilities. A method adjusting effective rainfall model gave poor simulation of runoff behavior in light rainfalls. Another method considering dynamic change of storage capacity as well as infiltration rate gave satisfactory estimation of the runoff in both drainages. In addition, assumption of facility clogging improved the agreement between measured and simulated hydrographs in small and medium-sized rainfall. Therefore, the proposed method might be useful for quantifying the secondary effects of the infiltration facilities on groundwater recharge and urban non-point pollutant trapping as well as runoff reduction.
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Vaze, J., D. A. Post, F. H. S. Chiew, J. M. Perraud, J. Teng, and N. R. Viney. "Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs." Journal of Hydrometeorology 12, no. 5 (October 1, 2011): 1100–1112. http://dx.doi.org/10.1175/2011jhm1340.1.

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Abstract Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.
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Lee, Kang, Joo, Kim, Kim, and Lee. "Hydrological Modeling Approach Using Radar-Rainfall Ensemble and Multi-Runoff-Model Blending Technique." Water 11, no. 4 (April 23, 2019): 850. http://dx.doi.org/10.3390/w11040850.

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The purpose of this study is to reduce the uncertainty in the generation of rainfall data and runoff simulations. We propose a blending technique using a rainfall ensemble and runoff simulation. To create rainfall ensembles, the probabilistic perturbation method was added to the deterministic raw radar rainfall data. Then, we used three rainfall-runoff models that use rainfall ensembles as input data to perform a runoff analysis: The tank model, storage function model, and streamflow synthesis and reservoir regulation model. The generated rainfall ensembles have increased uncertainty when the radar is underestimated, due to rainfall intensity and topographical effects. To confirm the uncertainty, 100 ensembles were created. The mean error between radar rainfall and ground rainfall was approximately 1.808–3.354 dBR. We derived a runoff hydrograph with greatly reduced uncertainty by applying the blending technique to the runoff simulation results and found that uncertainty is improved by more than 10%. The applicability of the method was confirmed by solving the problem of uncertainty in the use of rainfall radar data and runoff models.
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Lee, Hyo-Sang, Min-Woo Jeon, Daniela Balin, and Michael Rode. "Application of Rainfall Runoff Model with Rainfall Uncertainty." Journal of Korea Water Resources Association 42, no. 10 (October 30, 2009): 773–83. http://dx.doi.org/10.3741/jkwra.2009.42.10.773.

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Dissertations / Theses on the topic "Rainfall runoff model"

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Marshall, Lucy Amanda Civil &amp Environmental Engineering Faculty of Engineering UNSW. "Bayesian analysis of rainfall-runoff models: insights to parameter estimation, model comparison and hierarchical model development." Awarded by:University of New South Wales. Civil and Environmental Engineering, 2006. http://handle.unsw.edu.au/1959.4/32268.

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One challenge that faces hydrologists in water resources planning is to predict the catchment???s response to a given rainfall. Estimation of parameter uncertainty (and model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference, with computations carried out via Markov Chain Monte Carlo (MCMC) methods, offers an attractive approach to model specification, allowing for the combination of any pre-existing knowledge about individual models and their respective parameters with the available catchment data to assess both parameter and model uncertainty. This thesis develops and applies Bayesian statistical tools for parameter estimation, comparison of model performance and hierarchical model aggregation. The work presented has three main sections. The first area of research compares four MCMC algorithms for simplicity, ease of use, efficiency and speed of implementation in the context of conceptual rainfall-runoff modelling. Included is an adaptive Metropolis algorithm that has characteristics that are well suited to hydrological applications. The utility of the proposed adaptive algorithm is further expanded by the second area of research in which a probabilistic regime for comparing selected models is developed and applied. The final area of research introduces a methodology for hydrologic model aggregation that is flexible and dynamic. Rigidity in the model structure limits representation of the variability in the flow generation mechanism, which becomes a limitation when the flow processes are not clearly understood. The proposed Hierarchical Mixtures of Experts (HME) model architecture is designed to do away with this limitation by selecting individual models probabilistically based on predefined catchment indicators. In addition, the approach allows a more flexible specification of the model error to better assess the risk of likely outcomes based on the model simulations. Application of the approach to lumped and distributed rainfall runoff models for a variety of catchments shows that by assessing different catchment predictors the method can be a useful tool for prediction of catchment response.
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Hundecha, Hirpa Yeshewatesfa. "Regionalization of parameters of a conceptual rainfall-runoff model." Stuttgart : Inst. für Wasserbau, 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=975655469.

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Fionda, Alexander Peter Anthony. "Rainfall-runoff model application in ungauged catchments in Scotland." Thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-162181.

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The conceptual rainfall-runoff model Hysim is used to estimate the flow in ungauged catchments in Scotland by Scottish Water. However, there are non-quantified uncertainties associated with the outcomes of the modelling strategy used. In order to identify and quantify these uncertainties it was necessary to use the framework of proxy-basin validation in order to evaluate the performance of different modelling strategies.   The proxy-basin validation test requires hydrologically analogous catchments for the evaluation of models, a Region Of Influence regionalisation method was used in order group selected catchments by Q95(%MF). Four groups of four catchments were established, which covered Q95(%MF) 5-7%, 7-9%, 9-11% and 11-13%.   The allocation of “donor catchment” and “target catchment” for each Q95(%MF) group was accomplished through discussion with Scottish Water with respect to existing Scottish Water modelled catchments. A single donor catchment and three target catchments were therefore indicated for each group.   Two modelling strategies were developed by the study; the first full transposition method used the entire optimised parameter-set from the donor catchment with the exception of the target catchment’s “catchment area” parameter. The second partial transposition method used the entire optimal parameter-set with the exception of the target catchment’s “interception storage”, “time to peak”, “rooting depth” and “catchment area” parameters.    It was found that the full transposition method had the least uncertainty associated its use for flow estimation when the parameter-set was derived from a donor catchment calibration that was excellent. Contrarily, it was found that the partial transposition model method had the least uncertainty associated with flow estimation for parameter-sets that were derived from a relatively poor donor catchment calibration.   Encouraged by this testing framework, this study has suggested the use of catalogue of donor parameter-sets that can be used to estimate flow for catchments that are hydrologically similar. This strategy of hydrological modelling has been recommended to improve existing Scottish Water Hysim methodology.
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Hundecha, Hirpa Yeshewatesfa. "Regionalization of parameters of a conceptual rainfall-runoff model." Stuttgart Inst. für Wasserbau, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?idn=975655469.

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Ndiritu, John G. "An improved genetic algorithm for rainfall-runoff model calibration /." Title page, contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09PH/09phn337.pdf.

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Tecle, Aregai, Paul Heinrich, John Leeper, and Jolene Tallsalt-Robertson. "Rainfall-Runoff Model for Black Creek Watershed, Navajo Nation." Arizona-Nevada Academy of Science, 2012. http://hdl.handle.net/10150/301297.

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From the Proceedings of the 2012 Meetings of the Hydrology Section - Arizona-Nevada Academy of Science - April 14,2012, Glendale Community College, Glendale, Arizona
This paper develops a rainfall-runoff model for estimating surface and peak flow rates from precipitation storm events on the Black Creek watershed in the Navajo Nation. The Black Creek watershed lies in the southern part of the Navajo Nation between the Defiance Plateau on the west and the Chuska Mountains on the east. The area is in the semiarid part of the Colorado Plateau on which there is about 10 inches of precipitation a year. We have two main purposes for embarking on the study. One is to determine the amount of runoff and peak flow rate generated from rainfall storm events falling on the 655 square mile watershed and the second is to provide the Navajo Nation with a method for estimating water yield and peak flow in the absence of adequate data. Two models, Watershed Modeling System (WMS) and the Hydrologic Engineering Center (HEC) Hydrological Modeling System (HMS) that have Geographic Information System (GIS) capabilities are used to generate stream hydrographs. The latter show peak flow rates and total amounts of stream flows produced from rainfall storm events. Two 24-hour rainfall amounts, 1.1 inches and 0.6 inches, are imputed into the WMS and HEC HMS modeling system and evaluated to produce 1770 cfs and 3.9 cfs of peak flows and 1106.5 acre feet and 2.7 acre feet of total flow volumes, respectively. Even though the first one seems to be a little high compared to historical peak flows from the watershed, the outcomes seem to be quite appropriate for the study area when compared with gauging site flows at other times as well as with flows from well-instrumented nearby watersheds.
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Smith, Paul James. "Probabilistic flood forecasting using a distributed rainfall-runoff model." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/143966.

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Kyoto University (京都大学)
0048
新制・課程博士
博士(工学)
甲第12267号
工博第2596号
新制||工||1366(附属図書館)
24103
UT51-2006-J260
京都大学大学院工学研究科都市社会工学専攻
(主査)教授 小尻 利治, 教授 池淵 周一, 教授 中北 英一
学位規則第4条第1項該当
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Palanisamy, Bakkiyalakshmi. "Evaluation of SWAT model - subdaily runoff prediction in Texas watersheds." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5921.

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Spatial variability of rainfall is a significant factor in hydrologic and water quality modeling. In recent years, characterizing and analyzing the effect of spatial variability of rainfall in hydrologic applications has become vital with the advent of remotely sensed precipitation estimates that have high spatial resolution. In this study, the effect of spatial variability of rainfall in hourly runoff generation was analyzed using the Soil and Water Assessment Tool (SWAT) for Big Sandy Creek and Walnut Creek Watersheds in North Central Texas. The area of the study catchments was 808 km2 and 196 km2 for Big Sandy Creek and Walnut Creek Watersheds respectively. Hourly rainfall measurements obtained from raingauges and weather radars were used to estimate runoff for the years 1999 to 2003. Results from the study indicated that generated runoff from SWAT showed enormous volume bias when compared against observed runoff. The magnitude of bias increased as the area of the watershed increased and the spatial variability of rainfall diminished. Regardless of high spatial variability, rainfall estimates from weather radars resulted in increased volume of simulated runoff. Therefore, weather radar estimates were corrected for various systematic, range-dependent biases using three different interpolation methods: Inverse Distance Weighting (IDW), Spline, and Thiessen polygon. Runoff simulated using these bias adjusted radar rainfall estimates showed less volume bias compared to simulations using uncorrected radar rainfall. In addition to spatial variability of rainfall, SWAT model structures, such as overland flow, groundwater flow routing, and hourly evapotranspiration distribution, played vital roles in the accuracy of simulated runoff.
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Goodrich, David Charles. "Basin Scale and Runoff Model Complexity." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/614028.

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Distributed Rainfall-Runoff models are gaining widespread acceptance; yet, a fundamental issue that must be addressed by all users of these models is definition of an acceptable level of watershed discretization (geometric model complexity). The level of geometric model complexity is a function of basin and climatic scales as well as the availability of input and verification data. Equilibrium discharge storage is employed to develop a quantitative methodology to define a level of geometric model complexity commensurate with a specified level of model performance. Equilibrium storage ratios are used to define the transition from overland to channel -dominated flow response. The methodology is tested on four subcatchments in the USDA -ARS Walnut Gulch Experimental Watershed in Southeastern Arizona. The catchments cover a range of basins scales of over three orders of magnitude. This enabled a unique assessment of watershed response behavior as a function of basin scale. High quality, distributed, rainfall -runoff data was used to verify the model (KINEROSR). Excellent calibration and verification results provided confidence in subsequent model interpretations regarding watershed response behavior. An average elementary channel support area of roughly 15% of the total basin area is shown to provide a watershed discretization level that maintains model performance for basins ranging in size from 1.5 to 631 hectares. Detailed examination of infiltration, including the role and impacts of incorporating small scale infiltration variability in a distribution sense, into KINEROSR, over a range of soils and climatic scales was also addressed. The impacts of infiltration and channel losses on runoff response increase with increasing watershed scale as the relative influence of storms is diminished in a semiarid environment such as Walnut Gulch. In this semiarid environment, characterized by ephemeral streams, watershed runoff response does not become more linear with increasing watershed scale but appears to become more nonlinear.
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Young, Andrew Richard. "Regionalising a daily rainfall runoff model within the United Kingdom." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340664.

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Books on the topic "Rainfall runoff model"

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Wong, Tommy S. W. Kinematic-wave rainfall-runoff formulas. Hauppauge, NY: Nova Science Publishers, 2009.

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Rankl, James G. A point-infiltration model for estimating runoff from rainfall on small basins in semiarid areas of Wyoming. [Washington, D.C.]: U.S. G.P.O., 1990.

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Rientjes, Thomas Henricus Maria. Inverse modelling of the rainfall-runoff relation: A multi objective model calibration approach. Delft: Delft University Press, 2004.

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Boorman, D. B. A review of the flood studies report rainfall-runoff model parameter estimation equations. [s.l.]: Institute of Hydrology, 1985.

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Fulton, James L. Application of a distributed-routing rainfall-runoff model to flood-frequency estimation in Somerset County, New Jersey. West Trenton, N.J: U.S. Dept. of the Interior, U.S. Geological Survey, 1990.

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Yu, Pao-Shan. Real-time grid based distributed rainfall-runoff model for flood forecasting with weather radar. Birmingham: University of Birmingham, 1989.

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Ryan, Thomas P. Development and application of a physically based distributed parameter rainfall runoff model in the Gunnison River Basin. Denver, Colo. (P.O. Box 25007, Denver 80225-0007): U.S. Dept. of the Interior, Bureau of Reclamation, Denver Office, 1996.

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Nakama, Lenore Y. Use of a rainfall-runoff model for simulating effects of forest management on streamflow in the east fork Lobster Creek Basin, Oregon. Portland, Or: U.S. Geological Survey, 1993.

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C, Risley John. Use of a precipitation-runoff model for simulating effects of forest management on streamflow in 11 small drainage basins, Oregon coast range. Portland, Or: U.S. Dept. of the Interior, U.S. Geological Survey, 1994.

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Risley, John C. Use of a precipitation-runoff model for simulating effects of forest management on streamflow in 11 small drainage basins, Oregon coast range. Portland, Or: U.S. Dept. of the Interior, U.S. Geological Survey, 1994.

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Book chapters on the topic "Rainfall runoff model"

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Naresh, Aadhi, Harish Gupta, Mudavath Gopal Naik, Sandeep Hamsa, Manne Mohan Raju, and Dinesh C. S. Bisht. "Rainfall-runoff modeling using SWAT model." In Advances in Mathematical and Computational Modeling of Engineering Systems, 183–201. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003367420-8.

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Hromadka, Theodore V., and Robert J. Whitley. "Rainfall-Runoff Model Criterion Variable Frequency Distributions." In Stochastic Integral Equations and Rainfall-Runoff Models, 262–325. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_5.

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Niemi, Tero J., Gerald Krebs, and Teemu Kokkonen. "Automated Approach for Rainfall-Runoff Model Generation." In New Trends in Urban Drainage Modelling, 597–602. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99867-1_103.

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Hromadka, Theodore V., and Robert J. Whitley. "Stochastic Integral Equations Applied to a Multi-Linear Rainfall-Runoff Model." In Stochastic Integral Equations and Rainfall-Runoff Models, 215–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_4.

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Belarbi, Halima, Bénina Touaibia, Nadir Boumechra, Chérifa Abdelbaki, and Sakina Amiar. "Analysis of the Hydrological Behavior of Watersheds in the Context of Climate Change (Northwestern Algeria)." In Natural Disaster Science and Mitigation Engineering: DPRI reports, 143–79. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2904-4_5.

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AbstractThe aim of this work is to study the temporal evolution of the rainfall-runoff relations of four basins in northwestern Algeria: the Tafna Maritime, Isser Sikkak, downstream Mouilah and Upper Tafna basins. The adopted approach consists of analyzing hydroclimatic variables using statistical methods and testing the nonstationarity of the rainfall-runoff relation by the cross-simulation method using the GR2M model. The results of the different statistical methods applied to the series of rainfall and hydrometric variables show a decrease due to a break in stationarity detected since the mid-1970s and the beginning of the 1980s. The annual rainfall deficits reached average values of 34.6% during the period of 1941–2006 and 29.1% during the period of 1970–2010. The average annual wadi flows showed average deficits of 61.1% between 1912 and 2000 and 53.1% between 1973 and 2009. The GR2M conceptual model simulated the observed hydrographs in an acceptable manner by providing calculated runoff values in the calibration and validation periods greater or less than the observed runoff values. The application of the cross-simulation method highlighted the nonstationarity of the rainfall-runoff relations in three of the four studied basins, indicating downward trends of monthly runoff.
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Andraos, Cynthia, and Wajdi Najem. "Multi-model Approach for Reducing Uncertainties in Rainfall-Runoff Models." In Advances in Hydroinformatics, 545–57. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5436-0_43.

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Ling, Lloyd, and Zulkifli Yusop. "The Collective Visual Representation of Rainfall-Runoff Difference Model." In Advances in Visual Informatics, 271–82. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25939-0_24.

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Tan, Wen Jia, Lloyd Ling, Zulkifli Yusop, and Yuk Feng Huang. "Claim Assessment of a Rainfall Runoff Model with Bootstrap." In Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017), 287–93. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7279-7_35.

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Kadłubowski, Andrzej, Małgorzata Mierkiewicz, and Halina Budzyńska. "Operational Rainfall/Snowmelt-Runoff Model for Upper Narew River." In Modelling of Hydrological Processes in the Narew Catchment, 1–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19059-9_1.

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Kardhana, Hadi, and Akira Mano. "Uncertainty on a Short-Term Flood Forecast with Rainfall-Runoff Model." In Advances in Water Resources and Hydraulic Engineering, 88–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89465-0_17.

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Conference papers on the topic "Rainfall runoff model"

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Gibbs, Matthew S., Graeme C. Dandy, and Holger R. Maier. "Calibration of Rainfall Runoff Models in Ungauged Catchments: Regionalization Relationships for a Rainfall Runoff Model." In World Environmental and Water Resources Congress 2008. Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)377.

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Hapsari, R. I., M. Syarifuddin, R. I. Putri, R. Sasongko, and G. Aponno. "SATELLITE SOIL MOISTURE DOWNSCALING USING RAINFALL RUNOFF MODEL." In 18th Annual Meeting of the Asia Oceania Geosciences Society (AOGS 2021). WORLD SCIENTIFIC, 2022. http://dx.doi.org/10.1142/9789811260100_0023.

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Zhu, Qiang, Min Sun, Xiuwan Chen, Zimin Zhang, Xi Mao, and Yun Wen. "Rainfall Runoff Simulation Based on Dynamic Digital Terrain Model." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5163278.

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Liong, Shie-Yui, V. T. Van Nguyen, Tirtha Raj Gautam, and Loong Wee. "Alternative Well Calibrated Rainfall-Runoff Model: Genetic Programming Scheme." In Specialty Symposium on Urban Drainage Modeling at the World Water and Environmental Resources Congress 2001. Reston, VA: American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40583(275)73.

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MUTTIL, NITIN, and SHIE-YUI LIONG. "SEA: A ROBUST EVOLUTIONARY ALGORITHM FOR RAINFALL-RUNOFF MODEL CALIBRATION." In Proceedings of the 13th IAHRߝ;APD Congress. World Scientific Publishing Company, 2002. http://dx.doi.org/10.1142/9789812776969_0126.

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"Neural Networks and Rainfall-Runoff Model, its Calibration and Validation." In 1st International Workshop on Artificial Neural Networks: data preparation techniques and application development. SciTePress - Science and and Technology Publications, 2004. http://dx.doi.org/10.5220/0001150000600066.

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Kim, Chung-Soo, and Cho-rong Kim. "Parameter Estimation of Rainfall-Runoff Model Using Hydrograph Section Separation." In Green and Smart Technology 2015. Science & Engineering Research Support soCiety, 2015. http://dx.doi.org/10.14257/astl.2015.120.124.

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"Estimating rainfall-runoff model parameters using the iterative ensemble smoother." In 24th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2021. http://dx.doi.org/10.36334/modsim.2021.l1.bennett.

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Knoppová, Kateřina, Daniel Marton, and Petr Štěpánek. "APPLICATION OF RAINFALL-RUNOFF MODEL: CLIMATE CHANGE IMPACTS ON RESERVOIR INFLOW." In XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management. Nika-Tsentr, 2020. http://dx.doi.org/10.15407/uhmi.conference.01.11.

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The impacts of climate change are beginning to be felt in the Czech Republic. In recent years, we were challenging a dry period, which threatens to continue affecting Czech economy, agriculture and personal comfort of local people. The need to adapt to climate change is obvious. The groundwater resources are in continuous decline, consequently, the surface water supplies are increasing in importance. How would the quantity of available water change in the future? How much water would we be able to store within the year to manage it during the dry seasons? Rainfall-runoff models enable us to simulate future changes in hydrological conditions based on climate projections. One of such tools is Runoff Prophet, the conceptual lumped model being developed at the Institute of Landscape Water Management at Brno University of Technology. It is used to simulate time series of monthly river flow in a catchment outlet without the need to describe the morphological characteristics of the catchment. Runoff Prophet produced good results of calibration and proved its suitability for conceptual hydrological modelling in variable hydrological conditions of the Czech Republic. The aim of the paper was to assess the possible impact of climate change on future inflow into Vír I. Reservoir, one of the drinking water resources for Brno, a city of 380 000 inhabitants. The recently developed software Runoff Prophet was used to simulate future river flow time series. The model was calibrated on the catchment of gauging station Dalečín on Svratka River as the reservoir inflow. Prognoses of future river flow were performed using climate scenarios prepared by Global Change Research Institute of Czech Academy of Sciences. These scenarios (RCP types) are based on the outcomes from different regional climate models of Euro-CORDEX initiative. Characteristics of possible future air temperature and precipitation in the basin were evaluated in terms of its impact on reservoir management. The results of hydrological modelling gave the perspective of expected changes in Vír I. inflow yield. The options of using Vír I. Reservoir as a drinking water supply for Brno in coming decades were assessed.
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Sapkota, Aashis, and Claudio I. Meier. "A Parsimonious Rainfall-Runoff Model for Flood Forecasting: Incorporating Spatially Varied Rainfall and Soil Moisture." In Watershed Management Conference 2020. Reston, VA: American Society of Civil Engineers, 2020. http://dx.doi.org/10.1061/9780784483060.017.

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Reports on the topic "Rainfall runoff model"

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Hawkins, R. H., and A. Barreto-Munoz. Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2016. http://dx.doi.org/10.2737/rmrs-gtr-334.

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Hawkins, R. H., and A. Barreto-Munoz. Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2016. http://dx.doi.org/10.2737/rmrs-gtr-334.

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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.), November 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 calibration, but only initial conditions (ICs) can be calibrated when using the gridded SMA algorithm. Calibrating a continuous SMA HEC-HMS model is an iterative process that can require hundreds of simulations, a time intensive process requiring automation. HEC-HMS is written in Java and is predominantly run through a graphical user interface (GUI). As such, conducting a long-term gridded SMA calibration is infeasible using the GUI. USACE Construction Engineering Research Laboratory (CERL) has written a workflow that utilizes the existing Jython application programming interface (API) to batch run HEC-HMS simulations with Python. The workflow allows for gridded SMA HEC-HMS model sensitivity and calibration analyses to be conducted in a timely manner.
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Agassi, Menahem, Michael J. Singer, Eyal Ben-Dor, Naftaly Goldshleger, Donald Rundquist, Dan Blumberg, and Yoram Benyamini. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7586479.bard.

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The objective of this one-year project was to show whether a significant correlation can be established between the decreasing infiltration rate of the soil, during simulated rainstorm, and a following increase in the reflectance of the crusting soil. The project was supposed to be conducted under laboratory conditions, using at least three types of soils from each country. The general goal of this work was to develop a method for measuring the soil infiltration rate in-situ, solely from the reflectance readings, using a spectrometer. Loss of rain and irrigation water from cultivated fields is a matter of great concern, especially in arid, semi-arid regions, e.g. much of Israel and vast area in US, where water is a limiting factor for crop production. A major reason for runoff of rain and overhead irrigation water is the structural crust that is generated over a bare soils surface during rainfall or overhead irrigation events and reduces its infiltration rate (IR), considerably. IR data is essential for predicting the amount of percolating rainwater and runoff. Available information on in situ infiltration rate and crust strength is necessary for the farmers to consider: when it is necessary to cultivate for breaking the soil crust, crust strength and seedlings emergence, precision farming, etc. To date, soil IR is measured in the laboratory and in small-scale field plots, using rainfall simulators. This method is tedious and consumes considerable resources. Therefore, an available, non-destructive-in situ methods for soil IR and soil crusting levels evaluations, are essential for the verification of infiltration and runoff models and the evaluation of the amount of available water in the soil. In this research, soil samples from the US and Israel were subjected to simulated rainstorms of increasing levels of cumulative energies, during which IR (crusting levels) were measured. The soils from the US were studied simultaneously in the US and in Israel in order to compare the effect of the methodology on the results. The soil surface reflectance was remotely measured, using laboratory and portable spectrometers in the VIS-NIR and SWIR spectral region (0.4-2.5mm). A correlation coefficient spectra in which the wavelength, consisting of the higher correlation, was selected to hold the highest linear correlation between the spectroscopy and the infiltration rate. There does not appear to be a single wavelength that will be best for all soils. The results with the six soils in both countries indeed showed that there is a significant correlation between the infiltration rate of crusted soils and their reflectance values. Regarding the wavelength with the highest correlation for each soil, it is likely that either a combined analysis with more then one wavelength or several "best" wavelengths will be found that will provide useful data on soil surface condition and infiltration rate. The product of this work will serve as a model for predicting infiltration rate and crusting levels solely from the reflectance readings. Developing the aforementioned methodologies will allow increased utilization of rain and irrigation water, reduced runoff, floods and soil erosion hazards, reduced seedlings emergence problems and increased plants stand and yields.
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Howard, Heidi, Chad Helmle, Raina Dwivedi, and Daniel Gambill. Stormwater Management and Optimization Toolbox. Engineer Research and Development Center (U.S.), January 2021. http://dx.doi.org/10.21079/11681/39480.

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As stormwater regulations for hydrologic and water quality control become increasingly stringent, Department of Defense (DoD) facilities are faced with the daunting task of complying with multiple laws and regulations. This often requires facilities to plan, design, and implement structural best management practices (BMPs) to capture, filter, and/or infiltrate runoff—requirements that can be complicated, contradictory, and difficult to plan. This project demonstrated the Stormwater Management Optimization Toolbox (SMOT), a spreadsheet-based tool that effectively analyzes and plans for compliance to the Energy Independence and Security Act (EISA) of 2007 pre-hydrologic conditions through BMP implementation, resulting in potential cost savings by reducing BMP sizes while simultaneously achieving compliance with multiple objectives. SMOT identifies the most cost-effective modeling method based on an installation’s local conditions (soils, rainfall patterns, drainage network, and regulatory requirements). The work first demonstrated that the Model Selection Tool (MST) recommendation accurately results in the minimum BMP cost for 45 facilities of widely varying climatic and regional conditions, and then demonstrated SMOT at two facilities.
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Real-time rainfall-runoff model of the Carraizo-reservoir basin in Puerto Rico. US Geological Survey, 1996. http://dx.doi.org/10.3133/wri954235.

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A point-infiltration model for estimating runoff from rainfall on small basins in semiarid areas of Wyoming. US Geological Survey, 1990. http://dx.doi.org/10.3133/wsp2366.

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Application of a distributed-routing rainfall-runoff model to flood-frequency estimation in Somerset County, New Jersey. US Geological Survey, 1990. http://dx.doi.org/10.3133/wri894210.

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Use of a rainfall-runoff model for simulating effects of forest management on streamflow in the east fork Lobster Creek basin, Oregon. US Geological Survey, 1993. http://dx.doi.org/10.3133/wri934040.

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Comparison of conceptually based and regression rainfall-runoff models, Denver Metropolitan area, Colorado, and potential applications in urban areas. US Geological Survey, 1987. http://dx.doi.org/10.3133/wri874104.

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