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1
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.
Повний текст джерелаАнотація:
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’.
2
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.
Повний текст джерелаАнотація:
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.
3
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.
Повний текст джерелаАнотація:
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.
4
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.
Повний текст джерела
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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.
Повний текст джерелаАнотація:
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.
6
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.
Повний текст джерелаАнотація:
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.
7
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.
Повний текст джерелаАнотація:
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.
Повний текст джерелаАнотація:
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.
Повний текст джерелаАнотація:
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.
10
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.
Повний текст джерелаАнотація:
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.
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Hughes, J. D., and J. Vaze. "Non-stationarity driven by long-term change in catchment storage: possibilities and implications." Proceedings of the International Association of Hydrological Sciences 371 (June 12, 2015): 7–12. http://dx.doi.org/10.5194/piahs-371-7-2015.
Повний текст джерелаАнотація:
Abstract. "Non-stationarity" with reference to hydrology is a term applied to many situations (Milly et al., 2008). While climate change non-stationarity is often examined, these effects can provide a test for assumptions of runoff generation process impliedin rainfall–runoff (RR) models. Observations from South-western Australia (SWA) over the past 40 years show a decline in rainfall and reductions in runoff. Runoff and rainfall relationships in SWA show a significant shift over the past 40 years suggesting a change in runoff generation and catchment state. This has challenged the nature of assumed runoff generation process in SWA as well as the veracity of conceptual RR model structure. We expand on some of the lessons learned from SWA and discuss the climatic and geomorphic conditions that may make reasonable predictions of runoff very difficult with RR models calibrated in traditional ways. Catchment storage has a significant interaction with runoff generation and we examine the situations where these may change in the longer term. We suggest some strategies in terms of model structure and calibration that may improve predictive performance in such situations.
12
Zhang, Yongqiang, Francis H. S. Chiew, Lu Zhang, and Hongxia Li. "Use of Remotely Sensed Actual Evapotranspiration to Improve Rainfall–Runoff Modeling in Southeast Australia." Journal of Hydrometeorology 10, no. 4 (August 1, 2009): 969–80. http://dx.doi.org/10.1175/2009jhm1061.1.
Повний текст джерелаАнотація:
Abstract This paper explores the use of the Moderate Resolution Imaging Spectroradiometer (MODIS), mounted on the polar-orbiting Terra satellite, to determine leaf area index (LAI), and use actual evapotranspiration estimated using MODIS LAI data combined with the Penman–Monteith equation [remote sensing evapotranspiration (ERS)] in a lumped conceptual daily rainfall–runoff model. The model is a simplified version of the HYDROLOG (SIMHYD) model, which is used to estimate runoff in ungauged catchments. Two applications were explored: (i) the calibration of SIMHYD against both the observed streamflow and ERS, and (ii) the modification of SIMHYD to use MODIS LAI data directly. Data from 2001 to 2005 from 120 catchments in southeast Australia were used for the study. To assess the modeling results for ungauged catchments, optimized parameter values from the geographically nearest gauged catchment were used to model runoff in the ungauged catchment. The results indicate that the SIMHYD calibration against both the observed streamflow and ERS produced better simulations of daily and monthly runoff in ungauged catchments compared to the SIMHYD calibration against only the observed streamflow data, despite the modeling results being assessed solely against the observed streamflow data. The runoff simulations were even better for the modified SIMHYD model that used the MODIS LAI directly. It is likely that the use of other remotely sensed data (such as soil moisture) and smarter modification of rainfall–runoff models to use remotely sensed data directly can further improve the prediction of runoff in ungauged catchments.
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Yu, B., and C. J. Rosewell. "Evaluation of WEPP for runoff and soil loss prediction at Gunnedah, NSW, Australia." Soil Research 39, no. 5 (2001): 1131. http://dx.doi.org/10.1071/sr00091.
Повний текст джерелаАнотація:
It is important to use historical data to test physically based runoff and soil erosion prediction models as well as the method to estimate model parameters. WEPP (Water Erosion Prediction Project) was validated for bare fallow and annual wheat treatments at Gunnedah, New South Wales, Australia. Wheat stubble was either burned or mulched. Climate, soil, management, and runoff and soil loss data were collected for the period 1980–87 for 3 bare fallow plots, and 1950–74 for 10 annual wheat plots. Three slope lengths from 21 to 62 m were established for the treatment with stubble burned. Slope steepness varied from 8% to 9% at the site. Effective saturated hydraulic conductivity and soil erodibility parameters were estimated from measured soil properties. No further calibration of these parameters was attempted in order to assess the true potential of the model for runoff and soil loss predictions. WEPP worked well for the bare fallow plots with prediction efficiency of 0.97 for event runoff and soil losses. WEPP generally over-predicted the runoff, and consequently, the soil loss for annual wheat treatments for the site. WEPP was able to predict the effect of slope length on sediment concentration and soil loss for the site. CLIGEN, which provides the continuous climate input to WEPP, was found to produce adequately the mean daily rainfall, but produced higher than expected peak rainfall intensity, resulting in higher runoff and soil loss for all treatments.
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Wittmanová, R., I. Makro, J. Hrudka, M. Šutús, and Š. Stanko. "Modelling of Stormwater runoff and Wastewater Flow in the Sewer Network." IOP Conference Series: Materials Science and Engineering 1252, no. 1 (September 1, 2022): 012068. http://dx.doi.org/10.1088/1757-899x/1252/1/012068.
Повний текст джерелаАнотація:
Abstract The purpose of mathematical modelling of sewer networks is mainly to assess the hydraulic capacity and monitor its behaviour under different conditions to predict the future state. Sewerage network models are also part of the design process. Their advantage is the possibility of simulating the future state of the network and the precipitation and runoff process in the context of climate change. With the help of simulations, it is possible to anticipate future conditions in urban catchments and thus effectively design new networks. The aim of this paper is to summarize mathematical simulation models that are used to model sewer networks.
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Bennett, J. C., F. L. N. Ling, D. A. Post, M. R. Grose, S. P. Corney, B. Graham, G. K. Holz, J. J. Katzfey, and N. L. Bindoff. "High-resolution projections of surface water availability for Tasmania, Australia." Hydrology and Earth System Sciences 16, no. 5 (May 7, 2012): 1287–303. http://dx.doi.org/10.5194/hess-16-1287-2012.
Повний текст джерелаАнотація:
Abstract. Changes to streamflows caused by climate change may have major impacts on the management of water for hydro-electricity generation and agriculture in Tasmania, Australia. We describe changes to Tasmanian surface water availability from 1961–1990 to 2070–2099 using high-resolution simulations. Six fine-scale (∼10 km2) simulations of daily rainfall and potential evapotranspiration are generated with the CSIRO Conformal Cubic Atmospheric Model (CCAM), a variable-resolution regional climate model (RCM). These variables are bias-corrected with quantile mapping and used as direct inputs to the hydrological models AWBM, IHACRES, Sacramento, SIMHYD and SMAR-G to project streamflows. The performance of the hydrological models is assessed against 86 streamflow gauges across Tasmania. The SIMHYD model is the least biased (median bias = −3%) while IHACRES has the largest bias (median bias = −22%). We find the hydrological models that best simulate observed streamflows produce similar streamflow projections. There is much greater variation in projections between RCM simulations than between hydrological models. Marked decreases of up to 30% are projected for annual runoff in central Tasmania, while runoff is generally projected to increase in the east. Daily streamflow variability is projected to increase for most of Tasmania, consistent with increases in rainfall intensity. Inter-annual variability of streamflows is projected to increase across most of Tasmania. This is the first major Australian study to use high-resolution bias-corrected rainfall and potential evapotranspiration projections as direct inputs to hydrological models. Our study shows that these simulations are capable of producing realistic streamflows, allowing for increased confidence in assessing future changes to surface water variability.
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Loveridge, Melanie, and Ataur Rahman. "Effects of Probability-Distributed Losses on Flood Estimates Using Event-Based Rainfall-Runoff Models." Water 13, no. 15 (July 27, 2021): 2049. http://dx.doi.org/10.3390/w13152049.
Повний текст джерелаАнотація:
Probability distributions of initial losses are investigated using a large dataset of catchments throughout Australia. The variability in design flood estimates caused by probability-distributed initial losses and associated uncertainties are investigated. Based on historic data sets in Australia, the Gamma and Beta distributions are found to be suitable for describing initial loss data. It has also been found that the central tendency of probability-distributed initial loss is more important in design flood estimation than the form of the probability density function. Findings from this study have notable implications on the regionalization of initial loss data, which is required for the application of Monte Carlo methods for design flood estimation in ungauged catchments.
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Sun, H., and P. S. Cornish. "A catchment-based approach to recharge estimation in the Liverpool Plains, NSW, Australia." Australian Journal of Agricultural Research 57, no. 3 (2006): 309. http://dx.doi.org/10.1071/ar04015.
Повний текст джерелаАнотація:
This study investigated drainage and shallow groundwater change in a headwater catchment of the Liverpool Plains in north-western New South Wales. A catchment model, SWAT (Soil and Water Assessment Tool), was used to explore rain-fed drainage to shallow groundwater and its relationship to land use. Drainage was predicted along with the prediction of runoff on a catchment and land-use basis over a simulation period of 44 years. Predicted drainage in the catchment was 8 mm/year for the 44 years, which essentially matched estimates derived from bore data observed in the catchment over a 22-year period. These estimates of drainage are much lower than published estimates based on scaling up to the catchment using estimates of drainage derived from point-scale models for different land uses. Estimates of drainage for the different land uses, derived from the catchment model, were also generally lower than simulated drainages from other studies in the area using point-scale models. The investigation demonstrates a place for catchment-based modelling for estimating drainage at the catchment scale. This is mainly because observed catchment runoff is used as an error controller in catchment recharge modelling, whereas scaled-up point-scale modelling generally does not use observed catchment runoff to derive the catchment drainage. Modelling on the Liverpool Plains catchment also suggests that some of the drainage entering the vadose zone and groundwater is later lost via evapotranspiration, a process not generally simulated in crop models, and requiring further investigation to improve understanding of recharge processes and accuracy of modelling.
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Voronov, Yuri P. "DIGITAL TERRAIN MODELS IN SIBERIAN CITIES AND UTILITY NETWORKS DESIGN." Interexpo GEO-Siberia 3, no. 1 (May 21, 2021): 152–61. http://dx.doi.org/10.33764/2618-981x-2021-3-1-152-161.
Повний текст джерелаАнотація:
The article considers one of the important directions of innovative technologies in the urban economy, application of digital terrain models in the design, development and operation of utility networks. The author considers the five tasks of using the digital model sequentially: ) development of a digital terrain model, 2) allocation of watersheds and facies, 3) plotting contours (ridges) for all facies, 4) two-level modeling of surface runoff and storm sewer, 5) solving practical problems of determining silting zones and optimizing snow removal. The original principle proposed in the article is a multi-funnel model of surface runoff, in which each facies (local catchment) is replaced by an equivalent inclined funnel. This greatly simplifies the calculations, and also allows you to combine mathematical modeling with physical modeling.
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Farkas, Csilla, Sigrun H. Kværnø, Alexander Engebretsen, Robert Barneveld, and Johannes Deelstra. "Applying profile- and catchment-based mathematical models for evaluating the run-off from a Nordic catchment." Journal of Hydrology and Hydromechanics 64, no. 3 (September 1, 2016): 218–25. http://dx.doi.org/10.1515/johh-2016-0022.
Повний текст джерелаАнотація:
AbstractKnowledge of hydrological processes and water balance elements are important for climate adaptive water management as well as for introducing mitigation measures aiming to improve surface water quality. Mathematical models have the potential to estimate changes in hydrological processes under changing climatic or land use conditions. These models, indeed, need careful calibration and testing before being applied in decision making. The aim of this study was to compare the capability of five different hydrological models to predict the runoff and the soil water balance elements of a small catchment in Norway. The models were harmonised and calibrated against the same data set. In overall, a good agreement between the measured and simulated runoff was obtained for the different models when integrating the results over a week or longer periods. Model simulations indicate that forest appears to be very important for the water balance in the catchment, and that there is a lack of information on land use specific water balance elements. We concluded that joint application of hydrological models serves as a good background for ensemble modelling of water transport processes within a catchment and can highlight the uncertainty of models forecast.
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Bennett, J. C., F. L. N. Ling, D. A. Post, M. R. Grose, S. C. Corney, B. Graham, G. K. Holz, J. J. Katzfey, and N. L. Bindoff. "High-resolution projections of surface water availability for Tasmania, Australia." Hydrology and Earth System Sciences Discussions 9, no. 2 (February 8, 2012): 1783–825. http://dx.doi.org/10.5194/hessd-9-1783-2012.
Повний текст джерелаАнотація:
Abstract. Changes to streamflows caused by climate change may have major impacts on the management of water for hydro-electric generation and agriculture in Tasmania, Australia. We present high-resolution projections of Tasmanian surface water availability between 1961–1990 and 2070–2099. Six fine-scale (10 km) simulations of daily rainfall and potential evapotranspiration are generated with the CSIRO Conformal Cubic Atmospheric Model (CCAM), a variable-resolution regional climate model (RCM). These variables are bias-corrected with quantile mapping and used as direct inputs to the hydrological models AWBM, IHACRES, Sacramento, SIMHYD and SMAR-G to project streamflows. The performance of the hydrological models is assessed against 86 streamflow gauges across Tasmania. The SIMHYD model is the least biased (median bias = −3%) while IHACRES has the largest bias (median bias = −22%). We find the hydrological models that best simulate observed streamflows produce similar streamflow projections. In contrast, the poorly performing IHACRES model amplifies changes more than the other hydrological models. There is much more variation in projections between RCM simulations than between hydrological models. This shows that it is more important to consider the range of RCM simulations than the range of hydrological models used here to adequately describe uncertainty in the projections. We use the SIMHYD model to describe future changes to streamflow in eight rivers. Changes to streamflows are projected to vary by region. Marked decreases of up to 30% are projected for annual runoff in central Tasmania, while runoff is generally projected to increase in the east. Daily streamflow variability is projected to increase for most of Tasmania, consistent with increases in rainfall intensity. Inter-annual variability of streamflows is projected to increase across most of Tasmania. This is the first major Australian study to use high-resolution bias-corrected rainfall and potential evapotranspiration projections as direct inputs to hydrological models. Our study shows that these simulations are capable of producing realistic streamflows, allowing for increased confidence in assessing future changes to surface water variability.
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Hossain, Sharif, Guna Alankarage Hewa, and Subhashini Wella-Hewage. "A Comparison of Continuous and Event-Based Rainfall–Runoff (RR) Modelling Using EPA-SWMM." Water 11, no. 3 (March 24, 2019): 611. http://dx.doi.org/10.3390/w11030611.
Повний текст джерелаАнотація:
This study investigates the comparative performance of event-based and continuous simulation modelling of a stormwater management model (EPA-SWMM) in calculating total runoff hydrographs and direct runoff hydrographs. Myponga upstream and Scott Creek catchments in South Australia were selected as the case study catchments and model performance was assessed using a total of 36 streamflow events from the period of 2001 to 2004. Goodness-of-fit of the EPA-SWMM models developed using automatic calibration were assessed using eight goodness-of-fit measures including Nash–Sutcliff efficiency (NSE), NSE of daily high flows (ANSE), Kling–Gupta efficiency (KGE), etc. The results of this study suggest that event-based modelling of EPA-SWMM outperforms the continuous simulation approach in producing both total runoff hydrograph (TRH) and direct runoff hydrograph (DRH).
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Copper, J. K., and A. B. Sproul. "Comparative study of mathematical models in estimating solar irradiance for Australia." Renewable Energy 43 (July 2012): 130–39. http://dx.doi.org/10.1016/j.renene.2011.11.050.
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SHENTZIS, I. D. "Mathematical models for long-term prediction of mountainous river runoff: methods, information and results." Hydrological Sciences Journal 35, no. 5 (October 1990): 487–500. http://dx.doi.org/10.1080/02626669009492453.
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Kanso, A., B. Tassin, and G. Chebbo. "A benchmark methodology for managing uncertainties in urban runoff quality models." Water Science and Technology 51, no. 2 (January 1, 2005): 163–70. http://dx.doi.org/10.2166/wst.2005.0044.
Повний текст джерелаАнотація:
In this paper we present a benchmarking methodology, which aims at comparing urban runoff quality models, based on the Bayesian theory. After choosing the different configurations of models to be tested, this methodology uses the Metropolis algorithm, a general MCMC sampling method, to estimate the posterior distributions of the models' parameters. The analysis of these posterior distributions allows a quantitative assessment of the parameters' uncertainties and their interaction structure, and provides information about the sensitivity of the probability distribution of the model output to parameters. The effectiveness and efficiency of this methodology are illustrated in the context of 4 configurations of pollutants' accumulation/erosion models, tested on 4 street subcatchments. Calibration results demonstrate that the Metropolis algorithm produces reliable inferences of parameters thus, helping on the improvement of the mathematical concept of model equations.
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Wang, Shaobo, Wanhua Yuan, and Jiawei Zhou. "Analysis of Runoff Coefficient Prediction Based on LM-BP Neural Network." Journal of Physics: Conference Series 2333, no. 1 (August 1, 2022): 012020. http://dx.doi.org/10.1088/1742-6596/2333/1/012020.
Повний текст джерелаАнотація:
Abstract Runoff coefficients are affected by many factors, and their complex nonlinear relationships make it difficult to calculate accurate runoff coefficients using experimental physical models. In this paper, we improved the traditional BP neural network model based on the Levenberg-Marquardt method and established an S-type/S-type mathematical model of the relationship between runoff coefficients and influencing factors to predict each surface runoff coefficient under different rainfall conditions and different subsurface conditions, and compared it with other methods. The results calculated after the actual case simulation showed that the error of LM-BP neural network simulation was within the range of 0.03~0.09, the error was smaller, the calculation results were more accurate, and the prediction of runoff coefficient had the advantages of strong generalization ability and high prediction accuracy, which was a great improvement to the traditional rainfall-runoff coefficient best-fit relational fitting relationship method. Besides, in order to reduce the problem of sample overtraining, the more detailed the hydrological information, the better.
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Chiew, FHS, and TA Mcmahon. "Assessing the adequacy of catchment streamflow yield estimates." Soil Research 31, no. 5 (1993): 665. http://dx.doi.org/10.1071/sr9930665.
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Rainfall-runoff models are frequently used by hydrologists to estimate runoff from rainfall and climate data, with the model adequacy assessed by comparing the level of agreement between flows simulated by the model and the recorded flows. This paper describes simple methods (visual plots, statistical parameters and dimensionless coefficients) which are commonly used to compare estimated and recorded streamflow time series and discusses their advantages and limitations. Results of a survey conducted to ascertain the required quality of flow estimates before they are considered to be satisfactory, as well as to identify preferred methods used by hydrologists in Australia to determine the adequacy of streamflow estimates, are also discussed in this paper. Information from the survey is also used to suggest objective criteria based on dimensionless coefficients that can be used as guides in assessing the adequacy of flows estimated by rainfall-runoff models. In particular, the coefficient of efficiency is a very useful indicator in assessing model adequacy.
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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.
Повний текст джерелаАнотація:
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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James, William, and Boregowda Shivalingaiah. "Storm water pollution modelling: buildup of dust and dirt on surfaces subject to runoff." Canadian Journal of Civil Engineering 12, no. 4 (December 1, 1985): 906–15. http://dx.doi.org/10.1139/l85-103.
Повний текст джерелаАнотація:
Many runoff models are currently in use to predict both the quantity and quality of storm water runoff. In most models, the quality algorithms need further development to gain the confidence of model users. The writers have attempted to disaggregate the accumulation process and to develop improved algorithms for pollutant buildup. The factors and processes that affect buildup include atmospheric dustfall due to plumes of dust-laden air, wind effects, vehicles, intentional removals (e.g., street cleaning), special activities (such as construction and demolition), biological decomposition, and population-related activities (e.g., vegetation density, insecticides, herbicides, fertilizers, and lawn cutting). Mathematical expressions for each of these mechanisms are presented and utilized to develop algorithms in the RUNOFF module of the SWMM3 package.A separate multiregression model is used to generate atmospheric dustfall from meteorological information; this is input to the new program (NEWBLD) to calculate pollutant accumulation on individual subcatchments. NEWBLD is interfaced with the RUNOFF block of SWMM3. A sensitivity analysis is carried out using data for the Chedoke Creek catchment in Hamilton, Ontario. The modified version of the SWMM3 RUNOFF block developed herein by incorporating the new water quality algorithms is called CHGQUAL. It is applied to an urban catchment in Hamilton, Ontario. Key words: storm water models, dust and dirt buildup, storm water pollution, urban hydrology, air pollution.
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Bennett, J. C. "Assessment of the Impact of Land Use on Recreational Waters Using Mathematical Models." Water Science and Technology 21, no. 2 (February 1, 1989): 223–28. http://dx.doi.org/10.2166/wst.1989.0054.
Повний текст джерелаАнотація:
Mathematical models were used to assist in quantifying the impact of changing land use on the recreational waters of Pumicestone Passage. Runoff, washoff, hydrodynamic and water quality models were firstly calibrated and then used to predict levels of dissolved oxygen, total nitrogen, total phosphorus and E.coli in the Passage for two future land development scenarios. The models provided valuable tools for understanding the system response to non-point source pollutant loadings and assessing alternative scenarios. They indicated that planned development to the year 2000 would not result in significant water quality deterioration while extreme development is likely to do so to the extent of prejudicing some water uses.
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Liang, Jing, Wenzhe Li, Scott Bradford, and Jiří Šimůnek. "Physics-Informed Data-Driven Models to Predict Surface Runoff Water Quantity and Quality in Agricultural Fields." Water 11, no. 2 (January 24, 2019): 200. http://dx.doi.org/10.3390/w11020200.
Повний текст джерелаАнотація:
Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models (PBMs), which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with PBMs, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. Here we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport. A large number of numerical simulations was then carried out to develop a database containing information about the impact of various relevant factors on surface runoff quantity and quality, such as different weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices. Finally, the resulting database was used to train data-driven models. Several Machine Learning techniques were explored to find input-output functional relations. The results indicate that the Neural Network model with two hidden layers performed the best among selected data-driven models, accurately predicting runoff water quantity and quality over a wide range of parameters.
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Yang, Xiazi, Balati Maihemuti, Zibibula Simayi, Muattar Saydi, and Lu Na. "Prediction of Glacially Derived Runoff in the Muzati River Watershed Based on the PSO-LSTM Model." Water 14, no. 13 (June 24, 2022): 2018. http://dx.doi.org/10.3390/w14132018.
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The simulation and prediction of glacially derived runoff are significant for water resource management and sustainable development in water-stressed arid regions. However, the application of a hydrological model in such regions is typically limited by the intricate runoff production mechanism, which is associated with snow and ice melting, and sparse monitoring data over glacierized headwaters. To address these limitations, this study develops a set of mathematical models with a certain physical significance and an efficient particle swarm optimization algorithm by applying long- and short-term memory networks on the glacierized Muzati River basin. First, the trends in the runoff, precipitation, and air temperature are analyzed from 1990 to 2015, and differences in their correlations in this period are exposed. Then, Particle Swarm Optimization–Long Short-Term Memory (PSO-LSTM) and Bi-directional Long Short-Term Memory (BiLSTM) models are combined and applied to the precipitation and air temperature data to predict the glacially derived runoff. The prediction accuracy is validated by the observed runoff at the river outlet at the Pochengzi hydrological station. Finally, two other types of models, the RF (Random Forest) and LSTM (Long Short-Term Memory) models, are constructed to verify the prediction results. The results indicate that the glacially derived runoff is strongly correlated with air temperature and precipitation. However, in the study region over the past 26 years, the air temperature was not obviously increasing, and the precipitation and glacially derived runoff were significantly decreasing. The test results show that the PSO-LSTM and BiLSTM runoff prediction models perform better than the RF and LSTM models in the glacierized Muzati River basin. In the validation period, among all models, the PSO-LSTM model has the smallest mean absolute error and root-mean-square error and the largest coefficient of determination of 6.082, 8.034, and 0.973, respectively. It is followed by the BiLSTM model having a mean absolute error, root-mean-square error, and coefficient of determination of 6.751, 9.083, and 0.972, respectively. These results imply that both the particle swarm optimization algorithm and the bi-directional structure can effectively enhance the prediction accuracy of the baseline LSTM model. The results presented in this study can provide a deeper understanding and a more appropriate method of predicting the glacially derived runoff in glacier-fed river basins.
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Ponomarenko, I., A. Nemtsova, and T. Dmytrenko. "WATER QUALITY FORECASTING UNDER THE INFLUENCE OF RUNOFF BASED ON A MATHEMATICAL MODEL." Municipal economy of cities 6, no. 166 (November 30, 2021): 44–49. http://dx.doi.org/10.33042/2522-1809-2021-6-166-44-49.
Повний текст джерелаАнотація:
Runoff is one of the main sources of diffuse pollution of surface water. Suspended solids are the most typical contaminants of runoff. Suspended solids have a great influence on water quality and ecological status of water bodies. The content of suspended solids in water bodies is determined not only by their receipt from external sources, but also by the ability to transport sediments by flow. There is a permanent exchange of suspended solids between water bodies and bottom deposits. This fact stimulates specific requirements for modeling the transfer of suspended solids. For the most cases, models which describe the transfer of suspensions in a turbulent flow are based on the three-dimensional equation of turbulent diffusion or its two-dimensional simplification, which allows to take into account the spatial distribution of substances or it’s distribution to the width of stream. The use of such models requires a significant amount of initial data to determine the parameters of the models and is associated with a significant amount of calculations. At the same time, one-dimensional interpretation of processes is common and practically sufficient for shallow watercourses. It is more important to take into account the dynamics of the exchange of suspended solids between water mass and bottom deposits. The article is devoted to the development of a mathematical model for estimating the influence of non - point sources of pollution on the content of suspended solids in narrow watercourses. The model is based on the principle of mass balance of substances entering the flow section and takes into account the processes of sedimentation and resedimentation of suspended solids. A mathematical model in the form of a differential equation for the case of normal and overloaded flow is developed. Analytical solutions of equations for both cases are obtained. The influence of hydraulic size of the suspension on the content of suspended solids in watercourses and its distribution along the flow length is analyzed. The developed model was used for estimation of the impact of runoff from the urban area of Kharkiv city (Ukraine) on the river Lopan. The model demonstrated satisfactory compliance with field data.
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Mpelasoka, Freddie S., and Francis H. S. Chiew. "Influence of Rainfall Scenario Construction Methods on Runoff Projections." Journal of Hydrometeorology 10, no. 5 (October 1, 2009): 1168–83. http://dx.doi.org/10.1175/2009jhm1045.1.
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Abstract The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell rainfall data. The daily scaling and daily translation methods generally give higher extreme and annual runoff than the constant scaling method because they take into account the increase in extreme daily rainfall (which generates significant runoff) simulated by the large majority of the GCMs. However, the difference between the mean annual runoff simulated with future daily rainfall series obtained using the constant versus daily scaling methods is generally less than 5%, which is relatively smaller than the range of runoff results from the different GCMs of 30%–40%.
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Islam, S. A., M. A. Bari, and A. H. M. F. Anwar. "Hydrologic impact of climate change on Murray Hotham catchment of Western Australia: a projection of rainfall-runoff for future water resources planning." Hydrology and Earth System Sciences Discussions 10, no. 10 (October 2, 2013): 12027–76. http://dx.doi.org/10.5194/hessd-10-12027-2013.
Повний текст джерелаАнотація:
Abstract. Reduction of rainfall and runoff in recent years across South West Western Australia (SWWA) has drawn attention about climate change impact on water resources and its availability in this region. In this paper, hydrologic impact of climate change on Murray Hotham catchment in SWWA is investigated using multi-model ensemble approach. The Land Use Change Incorporated Catchment (LUCICAT) model was used for hydrologic modelling. Model calibration was performed using (5 km) grid rainfall data from Australian Water Availability Project (AWAP). Downscaled and bias corrected rainfall data from 11 General Circulation Models (GCMs) for Intergovernmental Panel on Climate Change (IPCC) emission scenarios A2 and B1 was used in LUCICAT model to derive rainfall and runoff scenarios for 2046–2065 (mid this century) and 2081–2100 (late this century). The results of climate scenarios were compared with observed past (1961–1980) climate. The mean annual rainfall averaged over the catchment during recent time (1981–2000) was reduced by 2.3% with respect to observed past (1961–1980) and resulting runoff reduction was found 14%. Compared to the past, the mean annual rainfall reductions, averaged over 11 ensembles and over the period for the catchment for A2 scenario are 13.6 and 23.6% for mid and late this century respectively while the corresponding runoff reductions are 36 and 74%. For B1 scenario, the rainfall reductions were 11.9 and 11.6% for mid and late this century and corresponding runoff reductions were 31 and 38%. Spatial distribution of rainfall and runoff changes showed that the rate of changes were higher in high rainfall part compared to the low rainfall part. Temporal distribution of rainfall and runoff indicate that high rainfall in the catchment reduced significantly and further reductions are projected resulting significant runoff reductions. A catchment scenario map has been developed through plotting decadal runoff reduction against corresponding rainfall reduction at four gauging stations for observed and projected period. This could be useful for planning future water resources in the catchment. Projection of rainfall and runoff made based on the GCMs varied significantly for the time periods and emission scenarios. Hence, considerable uncertainty involved in this study though ensemble mean was used to explain the findings.
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Hobday, Alistair J., and Janice M. Lough. "Projected climate change in Australian marine and freshwater environments." Marine and Freshwater Research 62, no. 9 (2011): 1000. http://dx.doi.org/10.1071/mf10302.
Повний текст джерелаАнотація:
Changes in the physical environment of aquatic systems consistent with climate change have been reported across Australia, with impacts on many marine and freshwater species. The future state of aquatic environments can be estimated by extrapolation of historical trends. However, because the climate is a complex non-linear system, a more process-based approach is probably required, in particular the use of dynamical projections using climate models. Because global climate models operate on spatial scales that typically are too coarse for aquatic biologists, statistical or dynamical downscaling of model output is proposed. Challenges in using climate projections exist; however, projections for some marine and freshwater systems are possible. Higher oceanic temperatures are projected around Australia, particularly for south-eastern Australia. The East Australia Current is projected to transport greater volumes of water southward, whereas the Leeuwin Current on the western coast may weaken. On land, projections suggest that air temperatures will rise and rainfall will decline across much of Australia in coming decades. Together, these changes will result in reduced runoff and hence reduced stream flow and lake storage. Present climate models are particularly limited with regard to coastal and freshwater systems, making the models challenging to use for biological-impact and adaptation studies.
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Islam, S. A., M. A. Bari, and A. H. M. F. Anwar. "Hydrologic impact of climate change on Murray–Hotham catchment of Western Australia: a projection of rainfall–runoff for future water resources planning." Hydrology and Earth System Sciences 18, no. 9 (September 12, 2014): 3591–614. http://dx.doi.org/10.5194/hess-18-3591-2014.
Повний текст джерелаАнотація:
Abstract. Reduction of rainfall and runoff in recent years across southwest Western Australia (SWWA) has attracted attention to the climate change impact on water resources and water availability in this region. In this paper, the hydrologic impact of climate change on the Murray–Hotham catchment in SWWA has been investigated using a multi-model ensemble approach through projection of rainfall and runoff for the periods mid (2046–2065) and late (2081–2100) this century. The Land Use Change Incorporated Catchment (LUCICAT) model was used for hydrologic modelling. Model calibration was performed using (5 km) grid rainfall data from the Australian Water Availability Project (AWAP). Downscaled and bias-corrected rainfall data from 11 general circulation models (GCMs) for Intergovernmental Panel on Climate Change (IPCC) emission scenarios A2 and B1 was used in LUCICAT model to derive rainfall and runoff scenarios for 2046–2065 (mid this century) and 2081–2100 (late this century). The results of the climate scenarios were compared with observed past (1961–1980) climate. The mean annual rainfall averaged over the catchment during recent time (1981–2000) was reduced by 2.3% with respect to the observed past (1961–1980) and the resulting runoff reduction was found to be 14%. Compared to the past, the mean annual rainfall reductions, averaged over 11 ensembles and over the period for the catchment for A2 scenario are 13.6 and 23.6% for mid and late this century respectively while the corresponding runoff reductions are 36 and 74%. For B1 scenario, the rainfall reductions were 11.9 and 11.6% for mid and late this century and the corresponding runoff reductions were 31 and 38%. Spatial distribution of rainfall and runoff changes showed that the rate of changes were higher in high rainfall areas compared to low rainfall areas. Temporal distribution of rainfall and runoff indicate that high rainfall events in the catchment reduced significantly and further reductions are projected, resulting in significant runoff reductions. A catchment scenario map has been developed by plotting decadal runoff reduction against corresponding rainfall reduction at four gauging stations for the observed and projected periods. This could be useful for planning future water resources in the catchment. Projection of rainfall and runoff made based on the GCMs varied significantly for the time periods and emission scenarios. Hence, the considerable uncertainty involved in this study though ensemble mean was used to explain the findings.
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Dinu, Cristian, Radu Drobot, Claudiu Pricop, and Tudor Viorel Blidaru. "Genetic Programming Technique Applied for Flash-Flood Modelling Using Radar Rainfall Estimates." Mathematical Modelling in Civil Engineering 13, no. 4 (December 20, 2017): 27–38. http://dx.doi.org/10.1515/mmce-2017-0012.
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AbstractThe rainfall-runoff transformation is a highly complex dynamic process and the development of fast and robust modelling instruments has always been one of the most important topics for hydrology. Over time, a significant number of hydrological models have been developed with a clear trend towards a process-based approach. The downside of these types of models is the significant amount of data required for building the model and for the calibration process: in practice, the collection of all necessary data for such models proves to be a difficult task. In order to cope with this issue, various data-driven modelling techniques have been introduced for hydrological modelling as an alternative to more traditional approaches, on the basis of their capacity of mapping out complex relationships from observation data. Having the capacity to generate meaningful mathematical structures as results, genetic programming (GP) presents a high potential for rainfall-runoff modelling as a data-driven method. Using ground and radar rainfall observation, the aim of this study is to investigate the GP technique capability for modelling the rainfall-runoff process, taking into consideration a flash-flood event.
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Li, Tilai, Xiangyu Gao, Xinzhou Zhang, and Yinshuang Wang. "IMPACT OF RUNOFF ON SALT INTRUSION OF YANGTZE ESTUARY." Coastal Engineering Proceedings 1, no. 32 (February 2, 2011): 49. http://dx.doi.org/10.9753/icce.v32.management.49.
Повний текст джерелаАнотація:
Based on one-dimensional and two-dimensional mathematical coupling models of tidal current and salinity from Datong to Yangtze estuary, the impacting scope of salt intrusion are calculated when the runoff of Datong from 4,500m3/s to 30,000m3/s, and the maximum and average value of salinity at each representative point of the estuary are given. When flow of Datong is less than 10,000 m3/s, if projects of water transfer, pumping and diversion are not taken into account at the lower reaches of Datong, the maximum salinity at the downstream reaches of Xuliujing and the average salinity at the downstream reaches of Baimaosha will exceed drinking water criteria.
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Montanari, L., M. Sivapalan, and A. Montanari. "Investigation of dominant hydrological processes in a tropical catchment in a monsoonal climate via the downward approach." Hydrology and Earth System Sciences Discussions 3, no. 1 (February 20, 2006): 159–200. http://dx.doi.org/10.5194/hessd-3-159-2006.
Повний текст джерелаАнотація:
Abstract. This study explores the dominant processes that may be responsible for the observed streamflow response in Seventeen Mile Creek, a tropical catchment located in a monsoonal climate in Northern Territory, Australia. The hydrology of this vast region of Australia is little understood due to the low level of information and gauging that is available. Any insights that can be gained from the few well gauged catchments that exist can be valuable for predictions and water resource assessments in other poorly gauged or ungauged catchments in the region. To this end, the available rainfall and runoff data from Seventeen Mile Creek catchment are analyzed through the systematic and progressive development and testing of rainfall-runoff models of increasing complexity, by following the "downward" or "top-down" approach. At the end a multiple bucket model (4 buckets in parallel) is developed. Modelling results suggest that the catchment's soils and the landscape in general have a high storage capacity, generating a significant fraction of delayed runoff, whereas saturation excess overland flow occurs only after heavy rainfall events. The sensitivity analyses carried out with the model with regard to soil depth and temporal rainfall variability reveal that total runoff from the catchment is more sensitive to rainfall variations than to soil depth variations, whereas the partitioning into individual components of runoff appears to be more influenced by soil depth variations. The catchment exhibits considerable inter-annual variability in runoff volumes and the greatest determinant of this variability turns out to be the seasonality of the climate, the timing of the wet season, and temporal patterns of the rainfall. The water balance is also affected by the underlying geology, nature of the soils and the landforms, and the type, density and dynamics of vegetation, although, information pertaining to these is lacking.
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Montanari, L., M. Sivapalan, and A. Montanari. "Investigation of dominant hydrological processes in a tropical catchment in a monsoonal climate via the downward approach." Hydrology and Earth System Sciences 10, no. 5 (October 19, 2006): 769–82. http://dx.doi.org/10.5194/hess-10-769-2006.
Повний текст джерелаАнотація:
Abstract. This study explores the dominant processes that may be responsible for the observed streamflow response in Seventeen Mile Creek, a tropical catchment located in a monsoonal climate in Northern Territory, Australia. The hydrology of this vast region of Australia is poorly understood due to the low level of information and gauging that are available. Any insights that can be gained from the few well gauged catchments that do exist can be valuable for predictions and water resource assessments in other poorly gauged or ungauged catchments in the region. To this end, the available rainfall and runoff data from Seventeen Mile Creek catchment are analyzed through the systematic and progressive development and testing of rainfall-runoff models of increasing complexity, by following the "downward" or "top-down" approach. This procedure resulted in a multiple bucket model (4 buckets in parallel). Modelling results suggest that the catchment's soils and the landscape in general have a high storage capacity, generating a significant fraction of delayed runoff, whereas saturation excess overland flow occurs only after heavy rainfall events. The sensitivity analyses carried out with the model with regard to soil depth and temporal rainfall variability revealed that total runoff from the catchment is more sensitive to rainfall variations than to soil depth variations, whereas the partitioning into individual components of runoff appears to be more influenced by soil depth variations. The catchment exhibits considerable inter-annual variability in runoff volumes and the greatest determinant of this variability turns out to be the seasonality of the climate, the timing of the wet season, and temporal patterns of the rainfall. The water balance is also affected by the underlying geology, nature of the soils and the landforms, and the type, density and dynamics of vegetation, although information pertaining to these is lacking.
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Asadi, Haniyeh, Kaka Shahedi, Ben Jarihani, and Roy Sidle. "Rainfall-Runoff Modelling Using Hydrological Connectivity Index and Artificial Neural Network Approach." Water 11, no. 2 (January 26, 2019): 212. http://dx.doi.org/10.3390/w11020212.
Повний текст джерелаАнотація:
The input selection process for data-driven rainfall-runoff models is critical because input vectors determine the structure of the model and, hence, can influence model results. Here, hydro-geomorphic and biophysical time series inputs, including Normalized Difference Vegetation Index (NDVI) and Index of Connectivity (IC; a type of hydrological connectivity index), in addition to climatic and hydrologic inputs were assessed. Selected inputs were used to develop Artificial Neural Networks (ANNs) in the Haughton River catchment and the Calliope River catchment, Queensland, Australia. Results show that incorporating IC as a hydro-geomorphic parameter and remote sensing NDVI as a biophysical parameter, together with rainfall and runoff as hydro-climatic parameters, can improve ANN model performance compared to ANN models using only hydro-climatic parameters. Comparisons amongst different input patterns showed that IC inputs can contribute to further improvement in model performance, than NDVI inputs. Overall, ANN model simulations showed that using IC along with hydro-climatic inputs noticeably improved model performance in both catchments, especially in the Calliope catchment. This improvement is indicated by a slight increase (9.77% and 11.25%) in the Nash–Sutcliffe efficiency and noticeable decrease (24.43% and 37.89%) in the root mean squared error of monthly runoff from Haughton River and Calliope River, respectively. Here, we demonstrate the significant effect of hydro-geomorphic and biophysical time series inputs for estimating monthly runoff using ANN data-driven models, which are valuable for water resources planning and management.
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Zafari, Najibullah, Ashok Sharma, Dimuth Navaratna, Varuni M. Jayasooriya, Craig McTaggart, and Shobha Muthukumaran. "A Comparative Evaluation of Conceptual Rainfall–Runoff Models for a Catchment in Victoria Australia Using eWater Source." Water 14, no. 16 (August 16, 2022): 2523. http://dx.doi.org/10.3390/w14162523.
Повний текст джерелаАнотація:
Hydrological modelling at a catchment scale was conducted to investigate the impact of climate change and land-use change individually and in combination with the available streamflow in the Painkalac catchment using an eWater Source hydrological model. This study compares the performance of three inbuilt conceptual models within eWater Source, such as the Australian water balance model (AWBM), Sacramento and GR4J for streamflow simulation. The three-model performance was predicted by bivariate statistics (Nash–Sutcliff efficiency) and univariate (mean, standard deviation) to evaluate the efficiency of model runoff predictions. Potential evapotranspiration (PET) data, daily rainfall data and observed streamflow measured from this catchment are the major inputs to these models. These models were calibrated and validated using eight objective functions while further comparisons of these models were made using objective functions of a Nash–Sutcliffe efficiency (NSE) log daily and an NSE log daily bias penalty. The observed streamflow data were split into three sections. Two-thirds of the data were used for calibration while the remaining one-third of the data was used for validation of the model. Based on the results, it was observed that the performance of the GR4J model is more suitable for the Painkalac catchment in respect of prediction and computational efficiency compared to the Sacramento and AWBM models. Further, the impact of climate change, land-use change and combined scenarios (land-use and climate change) were evaluated using the GR4J model. The results of this study suggest that the higher climate change for the year 2065 will result in approximately 45.67% less streamflow in the reservoir. In addition, the land-use change resulted in approximately 42.26% less flow while combined land-use and higher climate change will produce 48.06% less streamflow compared to the observed flow under the existing conditions.
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Patel, Ajaykumar Bhagubhai, and Geeta S. Joshi. "Modeling of Rainfall-Runoff Correlations Using Artificial Neural Network-A Case Study of Dharoi Watershed of a Sabarmati River Basin, India." Civil Engineering Journal 3, no. 2 (February 28, 2017): 78–87. http://dx.doi.org/10.28991/cej-2017-00000074.
Повний текст джерелаАнотація:
The use of an Artificial Neural Network (ANN) is becoming common due to its ability to analyse complex nonlinear events. An ANN has a flexible, convenient and easy mathematical structure to identify the nonlinear relationships between input and output data sets. This capability could efficiently be employed for the different hydrological models such as rainfall-runoff models, which are inherently nonlinear in nature. Artificial Neural Networks (ANN) can be used in cases where the available data is limited. The present work involves the development of an ANN model using Feed-Forward Back Propagation algorithm for establishing monthly and annual rainfall runoff correlations. The hydrologic variables used were monthly and annual rainfall and runoff for monthly and annual time period of monsoon season. The ANN model developed in this study is applied to Dharoi reservoir watersheds of Sabarmati river basin of India. The hydrologic data were available for twenty-nine years at Dharoi station at Dharoi dam project. The model results yielding into the least error is recommended for simulating the rainfall-runoff characteristics of the watersheds. The obtained results can help the water resource managers to operate the reservoir properly in the case of extreme events such as flooding and drought.
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Bennett, James C., Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael. "Assessment of an ensemble seasonal streamflow forecasting system for Australia." Hydrology and Earth System Sciences 21, no. 12 (November 30, 2017): 6007–30. http://dx.doi.org/10.5194/hess-21-6007-2017.
Повний текст джерелаАнотація:
Abstract. Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean–land–atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall–runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall–runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall–runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.
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Ratnayake, Dinesh C., Guna A. Hewa, and David J. Kemp. "Challenges in Quantifying Losses in a Partly Urbanised Catchment: A South Australian Case Study." Water 14, no. 8 (April 18, 2022): 1313. http://dx.doi.org/10.3390/w14081313.
Повний текст джерелаАнотація:
Quantifying hydrological losses in a catchment is crucial for developing an effective flood forecasting system and estimating design floods. This can be a complicated and challenging task when the catchment is urbanised as the interaction of pervious and impervious (both directly connected and indirectly connected) areas makes responses to rainfall hard to predict. This paper presents the challenges faced in estimating initial losses (IL) and proportional losses (PL) of the partly urbanised Brownhill Creek catchment in South Australia. The loss components were calculated for 57 runoff generating rainfall events using the non-parametric IL-PL method and parametric method based on two runoff routing models, Runoff Routing Burroughs (RORB) and Rainfall-Runoff Routing (RRR). The analysis showed that the RORB model provided the most representative median IL and PL for the rural portion of the study area as 9 mm and 0.81, respectively. However, none of the methods can provide a reliable loss value for the urban portion because there is no runoff contribution from unconnected areas for each event. However, the estimated non-parametric IL of 1.37 mm can be considered as IL of EIA of the urban portion. Several challenges were identified in the loss estimation process, mainly when selecting appropriate storm events, collecting data with the available temporal resolution, extracting baseflow, and determining the main-stream transmission losses, which reduced the urban flow by 5.7%. The effect of hydrograph shape in non-parametric loss estimation and how combined runoff from the effective impervious area and unconnected (combined indirectly connected impervious and pervious) areas affects the loss estimation process using the RORB and RRR models are further discussed. We also demonstrate the importance of identifying the catchment specific conditions appropriately when quantifying baseflow and runoff of selected events for loss estimation.
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Zhou, Y., Y. Zhang, J. Vaze, P. Lane, and S. Xu. "Impact of bushfire and climate variability on streamflow from forested catchments in southeast Australia." Hydrology and Earth System Sciences Discussions 10, no. 4 (April 5, 2013): 4397–437. http://dx.doi.org/10.5194/hessd-10-4397-2013.
Повний текст джерелаАнотація:
Abstract. Most of the surface water for natural environmental and human water uses in southeast Australia is sourced from forested catchments located in the higher rainfall areas. Water yield of these catchments is mainly affected by climatic conditions, but it is also greatly affected by vegetation cover change. Bushfires are a major natural disturbance in forested catchments and potentially modify the water yield of the catchments through changes to evapotranspiration (ET), interception and soil moisture storage. This paper quantifies the impacts of bushfire and climate variability on streamflow from three southeast Australian catchments where Ash Wednesday bushfires occurred in February 1983. The hydrological models used here include AWRA-L, Xinanjiang and GR4J. The three models are first calibrated against streamflow data from the pre-bushfire period and they are used to simulate runoff for the post-bushfire period with the calibrated parameters. The difference between the observed and model simulated runoff for the post-bushfire period provides an estimate of the impact of bushfire on streamflow. The hydrological modelling results for the three catchments indicate that there is a substantial increase in streamflow in the first 15 yr after the 1983 bushfires. The increase in streamflow is attributed to initial decreases in ET and interception resulting from the fires, followed by logging activity. After 15 yr, streamflow dynamics are more heavily influenced by climate effects, although some impact from fire and logging regeneration may still occur. It is shown that hydrological models provide reasonable consistent estimates of forest disturbance and climate impacts on streamflow for the three catchments. The results might be used by forest managers to understand the relationship between forest disturbance and climate variability impacts on water yield in the context of climate change.
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HRISSANTHOU, V., and A. PSILOVIKOS. "Distributed modeling of soil erosion and sediment transport." Bulletin of the Geological Society of Greece 34, no. 2 (August 1, 2018): 763. http://dx.doi.org/10.12681/bgsg.17354.
Повний текст джерелаАнотація:
A mathematical model is used for the estimation of the annual sediment yield resulting from rainfall and runoff at the outlet of Nestos River basin (Toxotes, Thrace, Greece), where the ecologically interesting Nestos delta exists. The model is applied to that part of Nestos River basin (838 km2) which lies downstream of three dams. Two dams (Thissavros and Platanovryssi) have been already constructed, while the third one (Temenos) is under construction. The model consists of three sub-models: a rainfall-runoff sub-model, a surface erosion sub-model and a sediment transport sub-model for streams. This model is also capable of computing the annual erosion amount and sediment yield in the individual sub-basins
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Post, David A. "Regionalizing rainfall–runoff model parameters to predict the daily streamflow of ungauged catchments in the dry tropics." Hydrology Research 40, no. 5 (October 1, 2009): 433–44. http://dx.doi.org/10.2166/nh.2009.036.
Повний текст джерелаАнотація:
A methodology has been derived which allows an estimate to be made of the daily streamflow at any point within the Burdekin catchment in the dry tropics of Australia. The input data requirements are daily rainfall (to drive the rainfall–runoff model) and mean average wet season rainfall, total length of streams, percent cropping and percent forest in the catchment (to regionalize the parameters of the rainfall–runoff model). The method is based on the use of a simple, lumped parameter rainfall–runoff model, IHACRES (Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data). Of the five parameters in the model, three have been set to constants to reflect regional conditions while the other two have been related to physio-climatic attributes of the catchment under consideration. The parameter defining total catchment water yield (c) has been estimated based on the mean average wet season rainfall, while the streamflow recession time constant (τ) has been estimated based on the total length of streams, percent cropping and percent forest in the catchment. These relationships have been shown to be applicable over a range of scales from 68–130,146 km2. However, three separate relationships were required to define c in the three major physiographic regions of the Burdekin: the upper Burdekin, Bowen and Suttor/lower Burdekin. The invariance of the relationships with scale indicates that the dominant processes may be similar across a range of scales. The fact that different relationships were required for each of the three major regions indicates the geographic limitations of this regionalization approach. For most of the 24 gauged catchments within the Burdekin the regionalized rainfall–runoff models were nearly as good as or better than the rainfall–runoff models calibrated to the observed streamflow. In addition, models often performed better over the simulation period than the calibration period. This indicates that future improvements in regionalization should focus on improving the quality of input data and rainfall–runoff model conceptualization rather than on the regionalization procedure per se.
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Tillman, Pei, Jonathan Dixon, Yue-Cong Wang, and Merran Griffith. "HYDRODYNAMIC AND WATER QUALITY MODELLING IN SYDNEY HARBOUR." Coastal Engineering Proceedings, no. 36v (December 31, 2020): 58. http://dx.doi.org/10.9753/icce.v36v.papers.58.
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The Sydney Harbour waterway modelling suite examines the changes in water quality in the harbour estuary and its tributaries associated with stormwater runoff and wet weather sewage overflows from the upstream catchments, in Sydney Australia. This paper discusses the development and performance of the numerical models. The models have been used to investigate the spatial variability of catchment pollutant loads and the impacts of sewer overflows on the water quality in the Sydney Harbour estuary. The scenario modelling results demonstrate that sewer overflows have a minimal impact on the Sydney Harbour estuary water quality, with stormwater dominating most changes in water quality.
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Taylor, K., J. A. D. Ranga Niroshan Appuhamy, J. Dijkstra, and E. Kebreab. "Development of mathematical models to predict calcium, magnesium and selenium excretion from lactating Holstein cows." Animal Production Science 58, no. 3 (2018): 489. http://dx.doi.org/10.1071/an16307.
Повний текст джерелаАнотація:
The aim of this study was to develop and evaluate mathematical models that predict mineral excretion, particularly calcium (Ca), magnesium (Mg) and selenium (Se), from lactating dairy cows. Mineral excretion can be affected by several dietary factors. A deficiency in Ca or Mg application to pasture, among other factors, can contribute to grass tetany or wheat pasture poisoning in cows, whereas an excess can cause runoff into water supplies. Manure application with high Se concentration can also result in runoff, causing the bioaccumulation of selenium in aquatic ecosystems, wetland habitats and estuaries, leading to toxic levels in fish. A database composed of studies relating to mineral utilisation in lactating dairy cows conducted after and including the year 2000 was compiled. A meta-analysis was conducted with the aim of creating multiple empirical equations to predict Ca, Mg and Se excretion from lactating dairy cows. Calcium intake, feed Ca content, milk yield, milk protein content and acid detergent fibre content in diet were positively and linearly related to Ca excretion. Dietary crude protein content and milk fat content were negatively related to Ca excretion. Magnesium intake, feed Mg content and milk yield were positively and linearly related to Mg excretion. Selenium content of diet and dry matter intake were linearly and positively related to Se excretion. Two sets of models were developed using or excluding the intake variable and both sets of models were evaluated with independent data originating from commercial herd or individual animals. In general, intake measurements improved prediction when evaluated with independent datasets (root mean square prediction error = 8% to 19% vs 14% to 26% of the average observed value). There were substantial mean biases, particularly those evaluated with data from a commercial farm, perhaps due to inaccurate feed intake measurements. Although there was generally good agreement between predicted and observed mineral excretion, model development and evaluation would benefit from an expanded database.