Academic literature on the topic 'Runoff Australia Mathematical models'
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Journal articles on the topic "Runoff Australia Mathematical models"
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Wasko, Conrad. "Review: Can temperature be used to inform changes to flood extremes with global warming?" Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379, no. 2195 (March 2021): 20190551. http://dx.doi.org/10.1098/rsta.2019.0551.
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As climate change alters flood risk, there is a need to project changes in flooding for water resource management, infrastructure design and planning. The use of observed temperature relationships for informing changes in hydrologic extremes takes many forms, from simple proportional change approaches to conditioning stochastic rainfall generation on observed temperatures. Although generally focused on understanding changes to precipitation, there is an implied transfer of information gained from precipitation-temperature sensitivities to flooding as extreme precipitation is often responsible for flooding. While reviews of precipitation-temperature sensitivities and the non-stationarity of flooding exist, little attention has been given to the intersection of these two topics. Models which use temperature as a covariate to assess the non-stationarity of extreme precipitation outperform both stationary models and those using a temporal trend as a covariate. But care must be taken when projecting changes in flooding on the basis on precipitation-temperature sensitivities, as antecedent conditions modify the runoff response. Although good agreement is found between peak flow-temperature sensitivities and historical trends across Australia, there remains little evaluation of flood projections using temperature sensitivities globally. Significant work needs to be done before the use of temperature as a covariate for flood projection can be adopted with confidence. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.
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D L Prasanna, S. V. S. N., K. Sandeep Reddy, Chandrasekhar, S. Sai Shivani, and E. Divya. "Prediction and Comparison of Rainfall-Runoff Using Mathematical Model." IOP Conference Series: Earth and Environmental Science 1130, no. 1 (January 1, 2023): 012044. http://dx.doi.org/10.1088/1755-1315/1130/1/012044.
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Abstract The Runoff assessment is a crucial parameter in understanding the urban flooding scenario. This estimation becomes the deciding factor because of the uneven distribution of rainfall. Physics-based models for simulation of Runoff from catchments are composite models based on learning algorithms. The application of models to water resource problems is complex due to the incredible spatial variability of the characteristics of watershed and precipitation forms — the pattern-learning algorithms. Fuzzy-based algorithms, Artificial Neural Networks (ANNs), etc., have gained wide recognition in simulating the Rainfall-Runoff (RR), producing a comparable accuracy. In the present study, RR modeling is carried out targeting the application and estimation of Runoff using mathematical modeling. The investigations were carried out for the Malkajgiri catchment adopting 16 years of daily data from 2005 to 2021. The statistical learning theory-based pattern-learning algorithm is further utilized to evaluate the value of Runoff for the year 2021. The results were found to have fair accordance with the analytical outcomes.
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Hughes, Justin, Nick Potter, Lu Zhang, and Robert Bridgart. "Conceptual Model Modification and the Millennium Drought of Southeastern Australia." Water 13, no. 5 (March 1, 2021): 669. http://dx.doi.org/10.3390/w13050669.
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Long-term droughts observed in southern Australia have changed relationships between annual rainfall and runoff and tested some of the assumptions implicit in rainfall–runoff models used in these areas. Predictive confidence across these periods is when low using the more commonly used rainfall–runoff models. Here we modified the GR4J model to better represent surface water–groundwater connection and its role in runoff generation. The modified model (GR7J) was tested in 137 catchments in south-east Australia. Models were calibrated during “wetter” periods and simulation across drought periods was assessed against observations. GR7J performed better than GR4J in evaluation during drought periods where bias was significantly lower and showed improved fit across the flow duration curve especially at low flows. The largest improvements in predictive performance were for catchments where there were larger changes in the annual rainfall–runoff relationship. The predictive performance of the GR7J model was more sensitive to objective function used than GR4J. The use of an objective function that combined daily and annual error produced a better goodness of fit when measured against 80, 50 and 20 percent excedance flow quantiles and reduced evaluation bias, especially for the GR7J model.
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Vaze, J., F. H. S. Chiew, J. M. Perraud, N. Viney, D. Post, J. Teng, B. Wang, J. Lerat, and M. Goswami. "Rainfall-Runoff Modelling Across Southeast Australia: Datasets, Models and Results." Australasian Journal of Water Resources 14, no. 2 (January 2011): 101–16. http://dx.doi.org/10.1080/13241583.2011.11465379.
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Fraser, G. W., and G. S. Stone. "The effect of soil and pasture attributes on rangeland infiltration rates in northern Australia." Rangeland Journal 38, no. 3 (2016): 245. http://dx.doi.org/10.1071/rj15099.
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Surface runoff is an important factor affecting rangeland pasture productivity and off-site sediment transportation. The application of rangeland biophysical models including sub-models of runoff and erosion provides one method to assess how management and climate variability affect the frequency and quantity of surface runoff events. However, there is often limited confidence in extrapolating runoff models developed from site-specific, hillslope field experiments to other locations due to variation in soil types and land condition states. To improve rangeland runoff models, we investigated three potentially important components at 18 paired land condition sites: (1) the importance of a variety of pasture attributes such as biomass and cover on infiltration rates; (2) the impact of surface soil texture on infiltration rates; and (3) whether soil carbon and/or soil bulk density provide valuable indicators of a site’s infiltration rates. The study found that surface soil texture was important when aboveground biomass was low and was found to have a ‘broken-stick’ relationship with infiltration rates (i.e. lowest infiltration occurred at the pivot point of 64% sand). Aboveground biomass, (which included standing grass, grass litter and tree litter) was the best soil or pasture attribute for predicting a plot’s infiltration capacity accounting for 68% of the variability. Plots with surface soil sand content greater than 60% and which had been exclosed for between 4 and 24 years had higher average surface soil carbon mass and concentration (~10%) than adjacent grazed plots. The exclosed plots also had higher surface soil porosity, which was associated with very high infiltration rates.
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Teng, J., F. H. S. Chiew, J. Vaze, S. Marvanek, and D. G. C. Kirono. "Estimation of Climate Change Impact on Mean Annual Runoff across Continental Australia Using Budyko and Fu Equations and Hydrological Models." Journal of Hydrometeorology 13, no. 3 (June 1, 2012): 1094–106. http://dx.doi.org/10.1175/jhm-d-11-097.1.
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Abstract This paper presents the climate change impact on mean annual runoff across continental Australia estimated using the Budyko and Fu equations informed by projections from 15 global climate models and compares the estimates with those from extensive hydrological modeling. The results show runoff decline in southeast and far southwest Australia, but elsewhere across the continent there is no clear agreement between the global climate models in the direction of future precipitation and runoff change. Averaged across large regions, the estimates from the Budyko and Fu equations are reasonably similar to those from the hydrological models. The simplicity of the Budyko equation, the similarity in the results, and the large uncertainty in global climate model projections of future precipitation suggest that the Budyko equation is suitable for estimating climate change impact on mean annual runoff across large regions. The Budyko equation is particularly useful for data-limited regions, for studies where only estimates of climate change impact on long-term water availability are needed, and for investigative assessments prior to a detailed hydrological modeling study. The Budyko and Fu equations are, however, limited to estimating the change in mean annual runoff for a given change in mean annual precipitation and potential evaporation. The hydrological models, on the other hand, can also take into account potential changes in the subannual and other climate characteristics as well as provide a continuous simulation of daily and monthly runoff, which is important for many water availability studies.
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Mańko, Robert, and Norbert Laskowski. "Comparative analysis of the effectiveness of the conceptual rainfall-runoff hydrological models on the selected rivers in Odra and Vistula basins." ITM Web of Conferences 23 (2018): 00025. http://dx.doi.org/10.1051/itmconf/20182300025.
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Identification of physical processes occurred in the watershed is one of the main tasks in hydrology. Currently the most efficient hydrological processes describing and forecasting tool are mathematical models. They can be defined as a mathematical description of relations between specified attributes of analysed object. It can be presented by: graphs, arrays, equations describing functioning of the object etc. With reference to watershed a mathematical model is commonly defined as a mathematical and logical relations, which evaluate quantitative dependencies between runoff characteristics and factors, which create it. Many rainfall-runoff linear reservoirs conceptual models have been developed over the years. The comparison of effectiveness of Single Linear Reservoir model, Nash model, Diskin model and Wackermann model is presented in this article.
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Teng, Jin, Jai Vaze, Francis H. S. Chiew, Biao Wang, and Jean-Michel Perraud. "Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff." Journal of Hydrometeorology 13, no. 1 (February 1, 2012): 122–39. http://dx.doi.org/10.1175/jhm-d-11-058.1.
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Abstract This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.
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Ebrahimian, H., and A. Liaghat. "Field evaluation of various mathematical models for furrow and border irrigation systems." Soil and Water Research 6, No. 2 (May 30, 2011): 91–101. http://dx.doi.org/10.17221/34/2010-swr.
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In this study, three mathematical models in the SIRMOD package including the hydrodynamic (HD), zero inertia (ZI), and kinematic wave (KW) models were tested using the data from several field experiments for both border and furrow irrigation systems. Five data sets for borders and seven data sets for furrows were used in this assessment. The results indicated that the performance of all models was satisfactory for the prediction of the advance and recession times. There was no difference in the prediction of the advance and recession times and infiltrated and runoff volumes between the hydrodynamic and zero-inertia approaches of the SIRMOD software. The HD, ZI, and KW models predicted the recession times better than the advance times for both the experimental borders and furrows. The predicted advance and recession times were estimated by these models more accurately than the infiltrated and runoff volumes. Also the accuracy of these models for the prediction of the advance and recession times was better for the experimental furrows in comparison with the experimental borders.
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Petheram, Cuan, Paul Rustomji, Tim R. McVicar, WenJu Cai, Francis H. S. Chiew, Jamie Vleeshouwer, Thomas G. Van Niel, et al. "Estimating the Impact of Projected Climate Change on Runoff across the Tropical Savannas and Semiarid Rangelands of Northern Australia." Journal of Hydrometeorology 13, no. 2 (April 1, 2012): 483–503. http://dx.doi.org/10.1175/jhm-d-11-062.1.
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Abstract The majority of the world’s population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall–runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%) and half resulted in a decrease (by up to 26%). However, ~70% of the GCMES resulted in a difference of within ±5% of the historical rainfall (1930–2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES (for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet–dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall–runoff modeling.
Dissertations / Theses on the topic "Runoff Australia Mathematical models"
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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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Sorooshian, Soroosh, and Vijai Kumar Gupta. "Improving the Reliability of Compartmental Models: Case of Conceptual Hydrologic Rainfall-Runoff Models." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1986. http://hdl.handle.net/10150/614011.
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Hendrickson, Jene Diane, and Soroosh Sorooshian. "CALIBRATION OF RAINFALL-RUNOFF MODELS USING GRADIENT-BASED ALGORITHMS AND ANALYTIC DERIVATIVES." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1987. http://hdl.handle.net/10150/614186.
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In the past, derivative-based optimization algorithms have not
frequently been used to calibrate conceptual rainfall -riff (CRR)
models, partially due to difficulties associated with obtaining the
required derivatives. This research applies a recently- developed
technique of analytically computing derivatives of a CRR model to a
complex, widely -used CRR model. The resulting least squares response
surface was found to contain numerous discontinuities in the surface
and derivatives. However, the surface and its derivatives were found
to be everywhere finite, permitting the use of derivative -based
optimization algorithms. Finite difference numeric derivatives were
computed and found to be virtually identical to analytic derivatives.
A comparison was made between gradient (Newton- Raphsoz) and
direct (pattern search) optimization algorithms. The pattern search
algorithm was found to be more robust. The lower robustness of the
Newton-Raphsoi algorithm was thought to be due to discontinuities and a
rough texture of the response surface.
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Kapangaziwiri, Evison. "Revised parameter estimation methods for the Pitman monthly rainfall-runoff model." Thesis, Rhodes University, 2008. http://hdl.handle.net/10962/d1006172.
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In recent years, increased demands have been placed on hydrologists to find the most effective methods of making predictions of hydrologic variables in ungauged basins. A huge part of the southern African region is ungauged and, in gauged basins, the extent to which observed flows represent natural flows is unknown, given unquantified upstream activities. The need to exploit water resources for social and economic development, considered in the light of water scarcity forecasts for the region, makes the reliable quantification of water resources a priority. Contemporary approaches to the problem of hydrological prediction in ungauged basins in the region have relied heavily on calibration against a limited gauged streamflow database and somewhat subjective parameter regionalizations using areas of assumed hydrological similarity. The reliance of these approaches on limited historical records, often of dubious quality, introduces uncertainty in water resources decisions. Thus, it is necessary to develop methods of estimating model parameters that are less reliant on calibration. This thesis addresses the question of whether physical basin properties and the role they play in runoff generation processes can be used directly in the estimation of parameter values of the Pitman monthly rainfall-runoff model. A physically-based approach to estimating the soil moisture accounting and runoff parameters of a conceptual, monthly time-step rainfall-runoff model is proposed. The study investigates the physical meaning of the model parameters, establishes linkages between parameter values and basin physical properties and develops relationships and equations for estimating the parameters taking into account the spatial and temporal scales used in typical model applications. The estimationmethods are then tested in selected gauged basins in southern Africa and the results of model simulations evaluated against historical observed flows. The results of 71 basins chosen from the southern African region suggest that it is possible to directly estimate hydrologically relevant parameters for the Pitman model from physical basin attributes. For South Africa, the statistical and visual fit of the simulations using the revised parameters were at least as good as the current regional sets, albeit the parameter sets being different. In the other countries where no regionalized parameter sets currently exist, simulations were equally good. The availability, within the southern African region, of the appropriate physical basin data and the disparities in the spatial scales and the levels of detail of the data currently available were identified as potential sources of uncertainty. GIS and remote sensing technologies and a widespread use of this revised approach are expected to facilitate access to these data.
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Luckemeier, Richard Ewald 1948. "A rainfall-runoff model for an urban watershed in Tucson, Arizona." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277165.
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The U.S. Geological Survey and the City of Tucson, Arizona, have been collecting rainfall and runoff data on several watersheds in the Tucson area for several years. Among the purposes of this project is to use the data to test rainfall-runoff models in an effort to find one to successfully simulate flood flows in Tucson. One such model, the Distributed Routing Rainfall-Runoff Model (DR3M), was tested using data collected on Rob Wash in Tucson. It was found DR3M performs about as well as it does in other parts of the United States, although it tends to underestimate flood flows for large storms and overestimate flows for smaller storms. Unique features with regard to the hydrology of urban Tucson require special attention when using DR3M; these features are associated with the nature of dry washes and summer rainfall in Tucson. Experience indicates DR3M is not truly a deterministic model.
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Powell, Robert. "Industry value at risk in Australia." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2007. https://ro.ecu.edu.au/theses/297.
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Value at Risk (VaR) models have gained increasing momentum in recent years. Market VaR is an important issue for banks since its adoption as a primary risk metric in the Basel Accords and the requirement that it is calculated on a daily basis. Credit risk modelling has become increasingly important to banks since the advent of Basel 11 which allows banks with sophisticated modelling techniques to use internal models for the purpose of calculating capital requirements. A high level of credit risk is often the key reason behind banks failing or experiencing severe difficulty. Conditional Value at Risk (CVaR) measures extreme risk, and is gaining popularity with the recognition that high losses are often impacted by a small number of extreme events.
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Koterba, Michael T. "Differential influences of storm and watershed characteristics on runoff from ephemeral streams in southeastern Arizona." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/191126.
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Relationships between thunderstorm and watershed variables and runoff from or within semiarid watersheds at Walnut Gulch, Arizona were examined. Variables showing greater sensitivity to basin and storm size were better flow predictors. Stepwise regression with three increasingly nonlinear algebraic models showed mean storm depth was the best simple predictor of runoff. Predictions improved using storm volume, a product of storm depth and areal extent. Initial runoff to streams was best described as a highly nonlinear function of storm and watershed variables. Runoff from a basin was a more linearized function of similar variables. The above differences were ascribed to channel transmission losses, reductions in runoff moving down initially dry channels. For a given basin and small storms, loss to runoff ratios exceeded 10:1 and were highly variable. Ratios were similar and less than 0.5:1 for storms centrally located over a basin and generating sufficient initial runoff to minimize flow variation due to losses. Losses increased disproportionately with basin size. Antecedent rainfall and first summer flows also affected rainfall runoff relationships in a differential manner. Wet conditions enhanced runoff more from larger versus smaller storms. First summer flows were less than expected probably because of higher soil infiltration and channel losses at the onset of summer storms. Overall, as storm size decreased or basin area increased, initial runoff was more often a localized phenomenon and downstream flow more dependent on storm depth, extent, location, and seasonal timing and basin channel losses, but less dependent on antecedent rainfall. Consequently, storm depth accounted for only 60% to 70% of the variation in flows while storm volume, antecedent rainfall, channel losses, and first summer flows explained 80% to 90%. Finally, oversimplifying storm or watershed variables or analytical methods led to errors in assessing their affect on runoff. It was also determined that current arguments supporting a recommendation to delete smaller, frequent annual floods to better fit remaining data to flood frequency curves were oversimplified. Distributed rainfall - runoff models with channel losses and regional storm depth - area - frequency data may be the way to develope flood curves for semiarid basins with short runoff records.
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Kapangaziwiri, Evison. "Regional application of the Pitman monthly rainfall-runoff model in Southern Africa incorporating uncertainty." Thesis, Rhodes University, 2011. http://hdl.handle.net/10962/d1006178.
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Climate change and a growing demand for freshwater resources due to population increases and socio-economic changes will make water a limiting factor (in terms of both quantity and quality) in development. The need for reliable quantitative estimates of water availability cannot be over-emphasised. However, there is frequently a paucity of the data required for this quantification as many basins, especially in the developing world, are inadequately equipped with monitoring networks. Existing networks are also shrinking due mainly to shortages in human and financial resources. Over the past few decades mathematical models have been used to bridge the data gap by generating datasets for use in management and policy making. In southern Africa, the Pitman monthly rainfall-runoff model has enjoyed relatively popular use as a water resources estimation tool. However, it is acknowledged that models are abstractions of reality and the data used to drive them is imperfect, making the model outputs uncertain. While there is acknowledgement of the limitations of modelled data in the southern African region among water practitioners, there has been little effort to explicitly quantify and account for this uncertainty in water resources estimation tools and explore how it affects the decision making process. Uncertainty manifests itself in three major areas of the modelling chain; the input data used to force the model, the parameter estimation process and the model structural errors. A previous study concluded that the parameter estimation process for the Pitman model contributed more to the global uncertainty of the model than other sources. While the literature abounds with uncertainty estimation techniques, many of these are dependent on observations and are therefore unlikely to be easily applicable to the southern African region where there is an acute shortage of such data. This study focuses on two aspects of making hydrologic predictions in ungauged basins. Firstly, the study advocates the development of an a priori parameter estimation process for the Pitman model and secondly, uses indices of hydrological functional behaviour to condition and reduce predictive uncertainty in both gauged and ungauged basins. In this approach all the basins are treated as ungauged, while the historical records in the gauged basins are used to develop regional indices of expected hydrological behaviour and assess the applicability of these methods. Incorporating uncertainty into the hydrologic estimation tools used in southern Africa entails rethinking the way the uncertain results can be used in further analysis and how they will be interpreted by stakeholders. An uncertainty framework is proposed. The framework is made up of a number of components related to the estimation of the prior distribution of the parameters, used to generate output ensembles which are then assessed and constrained using regionalised indices of basin behavioural responses. This is premised on such indices being based on the best available knowledge covering different regions. This framework is flexible enough to be used with any model structure to ensure consistent and comparable results. While the aim is to eventually apply the uncertainty framework in the southern African region, this study reports on the preliminary work on the development and testing of the framework components based on South African basins. This is necessitated by the variations in the availability and quality of the data across the region. Uncertainty in the parameter estimation process was incorporated by assuming uncertainty in the physical and hydro-meteorological data used to directly quantify the parameter. This uncertainty was represented by the range of variability of these basin characteristics and probability distribution functions were developed to account for this uncertainty and propagate it through the estimation process to generate posterior distributions for the parameters. The results show that the framework has a great deal of potential but can still be improved. In general, the estimated uncertain parameters managed to produce hydrologically realistic model outputs capturing the expected regimes across the different hydro-climatic and geo-physical gradients examined. The regional relationships for the three indices developed and tested in this study were in general agreement with existing knowledge and managed to successfully provide a multi-criteria conditioning of the model output ensembles. The feedback loop included in the framework enabled a systematic re-examination of the estimation procedures for both the parameters and the indices when inconsistencies in the results were identified. This improved results. However, there is need to carefully examine the issues and problems that may arise within other basins outside South Africa and develop guidelines for the use of the framework.iText 1.4.6 (by lowagie.com)
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Price, Myra Ann. "Seasonal Variation in Runoff Curve Number." Thesis, The University of Arizona, 1998. http://hdl.handle.net/10150/225411.
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The seasonal variation in rainfall - runoff response is investigated for about 300 small watersheds throughout the United States. Data from USDA research watersheds were used to define runoff Curve Number for ordered data sets by months. Three major patterns of cyclic variation are found and investigated: 1) distinct and well - defined seasonal variations as typified by forested watersheds in heavy rainfall zones; 2) mildly cyclic variation found typically in meadows and grasslands, and 3) non - cyclic or unidentifiable patterns, including those with insufficient seasonal data. The only pattern that may be present is the well-defined seasonal variation found so far only in forested watersheds. Regional characteristics were found for individual crop types. For the watersheds studied there seemed to be no difference in the variation between crops except for meadow during the summer. Some associated background factors are explored, including long-term and short-term antecedent rainfall.
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Bouraoui, Faycal. "Development of a continuous, physically-based distributed parameter, nonpoint source model." Diss., This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-10192006-115604/.
Full textBooks on the topic "Runoff Australia Mathematical models"
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Organization, World Meteorological. Intercomparison of models of snowmelt runoff. Geneva, Switzerland: Secretariat of the World Meteorological Organization, 1986.
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Beven, K. J. Rainfall-runoff modelling: The primer. 2nd ed. Hoboken: Wiley, 2011.
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J, Martinec, ed. Remote sensing in snow hydrology: Runoff modelling, effect of climate change. Berlin: Springer ; Chichester, UK, 2004.
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B, Vinogradov I͡U. Matematicheskoe modelirovanie prot͡sessov formirovanii͡a stoka: Opyt kriticheskogo analiza. Moskva: Gidrometeoizdat, 1988.
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Zarriello, Phillip J. Measured and simulated runoff to the lower Charles River, Massachusetts, October 1999-September 2000. Northborough, Mass: U.S. Dept. of the Interior, U.S. Geological Survey, 2002.
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Kuhn, Gerhard. Application of the U.S. Geological Survey's precipitation-runoff modeling system to Williams Draw and Bush Draw basins, Jackson County, Colorado. Denver, Colo: Dept. of the Interior, U.S. Geological Survey, 1988.
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Vitvar, Tomás̆. Water residence times and runoff generation in a small prealpine catchment. Zürich: Geographisches Institut ETH, 1998.
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Bower, David E. Evaluation of the precipitation-runoff modeling system, Beaver Creek basin, Kentucky. Louisville, Ky: U.S. Dept. of the Interior, Geological Survey, 1985.
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Kuhn, Gerhard. Application of the U.S. Geological Survey's precipitation-runoff modeling system to Williams Draw and Bush Draw basins, Jackson County, Colorado. Denver, Colo: Dept. of the Interior, U.S. Geological Survey, 1988.
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Kuhn, Gerhard. Application of the U.S. Geological Survey's precipitation-runoff modeling system to Williams Draw and Bush Draw basins, Jackson County, Colorado. Denver, Colo: Dept. of the Interior, U.S. Geological Survey, 1988.
Find full textBook chapters on the topic "Runoff Australia Mathematical models"
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Zeman, E., and J. Spatka. "Evaluation of Impacts of Control Measures, Applied in the Source Catchments, by Mathematical Models." In Advances in Urban Stormwater and Agricultural Runoff Source Controls, 181–94. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0532-6_16.
Full textConference papers on the topic "Runoff Australia Mathematical models"
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Ivankova, T. V., and V. A. Volosukhin. "CALCULATION OF THE PASSAGE OF FLOODS THROUGH THE WATERWORKS BALANOVSKY RESERVOIR." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. DSTU-PRINT, 2020. http://dx.doi.org/10.23947/interagro.2020.1.545-550.
Full textAbstract:
The characteristic of the Crimean rivers for which the flood regime is characteristic is given. In 1974, the Balanovskoye reservoir was built on the Zuya river to meet the needs of the district's agriculture. The data on the calculation of the passage of floods through the hydroelectric Balanovsky reservoir, belonging to the II class of danger. Calibration of the maximum rate, according to the SP and 0.1% of the EAP. The assessment and 0.01% of the EAP of the flood pass by the existing structures of the hydroelectric facility was carried out. It is recommended to organize continuous observations of all parameters on the network of automatic stations, which will most fully characterize the entire situation in the basin and in its various sections, as well as provide information to a set of mathematical models for hydrodynamic modeling of surface runoff and channel runoff to intermediate branches, to assess the risks of dangerous hydrological phenomena in various parts of the basin with sufficient advance.
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Lučić, Sonja. "VEŠTAČKA INTELIGENCIJA I PATENTNO PRAVO." In XVIII Majsko savetovanje. University of Kragujevac, Faculty of Law, 2022. http://dx.doi.org/10.46793/xviiimajsko.479l.
Full textAbstract:
Artificial intelligence is a field of technology that is developing intensively. Along with the development of artificial intelligence, the issue of its patent protection has become topical. Artificial intelligence systems are based on highly developed algorithms and mathematical models, phenomena with which patent law is traditionally in conflict. This issue is not just a national or European problem. There is also an intensive debate in the United States about the patentability of artificially intelligent systems. The author deals with the question of whether artificially intelligent systems can enjoy patent protection. The paper analyzes the case of "DABUS" which refers to an international patent application in which the artificially intelligent system DABUS is listed as the inventor. Numerous intellectual property offices around the world (eg American, British, German, Australian, EPO) have rejected such a patent application. On the other hand, the Federal Court of Australia has ruled that under the Australian Patent Act AI could be listed as the inventor. Recognition of AI as the inventor (not the owner) of inventions generated by artificial intelligence can have certain consequences, including in the field of copyright.