Journal articles on the topic 'Rainfall-runoff'
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1
Bartlett, M. S., E. Daly, J. J. McDonnell, A. J. Parolari, and A. Porporato. "Stochastic rainfall-runoff model with explicit soil moisture dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2183 (November 2015): 20150389. http://dx.doi.org/10.1098/rspa.2015.0389.
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Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF.
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Zhou, Ke. "A comparative study on rainfall runoff control indicators of green roof." Water Supply 20, no. 6 (May 4, 2020): 2036–42. http://dx.doi.org/10.2166/ws.2020.076.
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Abstract The rainfall runoff reduction effect on green roofs was analyzed and tested by comparative rainfall runoff monitoring on impermeable roofs (sloping, plane). The evaluation index of rainfall runoff interception benefit (relative runoff reduction rate, rainfall control rate) on green roofs was studied. The results show that compared with sloping and level roofs, the change range of green roof runoff reduction rate relative to level and sloping roofs is 20.0–98.3% and 3.8–92.3%, and the mean value is 48.4% and 34.3% respectively. It is obvious that the green roof has better rainfall runoff reduction effect. It can be seen from the single rainfall control effect that the variation range of green roof rainfall runoff control rate is 36.0% to 99.0%, and the total rainfall control rate is 57.6%, which reflects that the green roof has the better rainfall control effect. Through comparative study, it can be concluded that the rainfall runoff control rate is more suitable for the design index of green roofs.
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Buchtele, Josef. "Runoff changes simulated using a rainfall-runoff model." Water Resources Management 7, no. 4 (1993): 273–87. http://dx.doi.org/10.1007/bf00872285.
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Máca, P., and P. Torfs. "The influence of temporal rainfall distribution in the flood runoff modelling." Soil and Water Research 4, Special Issue 2 (March 19, 2010): S102—S110. http://dx.doi.org/10.17221/471-swr.
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The rainfall input is one of the main factors influencing the magnitude of the runoff response during a flood event. Its temporal and spatial distribution significantly contributes to the formation of hydrograph shape, peak discharge and flood volume. A novel approach to the evaluation of the role of the temporal rainfall pattern of hydrograph is presented in this contribution. The methodology shown is based on the coupling of the deterministic event based runoff model with the stochastic rainfall disaggregation model. The rainfall model simulates the hyetograph ensemble, which is the direct input to the calibrated event based runoff model. The event based runoff model calibration is based on the evaluation of real flood events. The rainfall ensemble is simulated according to the preservation of important statistical properties, which are estimated from the real rainfall data inputs. The proposed combination of two simulation techniques enables to generate the hydrograph ensemble upon a single flood event. The evaluation of the temporal rainfall distribution impact on the flood runoff response is performed through the determination of the selected rainfall runoff characteristics of the simulated hydrograph ensemble. The main result confirms the importance of the rainfall volume inputs and its temporal distribution on the flood runoff generation. The methodology shown enables to evaluate the potential of the real flood event to generate the flood event within the conditions of the small catchment scale.
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Herrnegger, M., H. P. Nachtnebel, and K. Schulz. "From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution." Hydrology and Earth System Sciences 19, no. 11 (November 23, 2015): 4619–39. http://dx.doi.org/10.5194/hess-19-4619-2015.
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Abstract. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall–runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.
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Herrnegger, M., H. P. Nachtnebel, and K. Schulz. "From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution." Hydrology and Earth System Sciences Discussions 11, no. 12 (December 5, 2014): 13259–309. http://dx.doi.org/10.5194/hessd-11-13259-2014.
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Abstract. This paper presents a novel technique to calculate mean areal rainfall in a high temporal resolution of 60 min on the basis of an inverse conceptual rainfall–runoff model and runoff observations. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. The most reliable hydrological information available refers to runoff, which in the presented work is used as input for a rainfall–runoff model. Thereby a conceptual, HBV-type model is embedded in an iteration algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value that corresponds to the observation. To verify the existence, uniqueness and stability of the inverse rainfall, numerical experiments with synthetic hydrographs as inputs into the inverse model are carried out successfully. The application of the inverse model with runoff observations as driving input is performed for the Krems catchment (38.4 km2), situated in the northern Austrian Alpine foothills. Compared to station observations in the proximity of the catchment, the inverse rainfall sums and time series have a similar goodness of fit, as the independent INCA rainfall analysis of Austrian Central Institute for Meteorology and Geodynamics (ZAMG). Compared to observations, the inverse rainfall estimates show larger rainfall intensities. Numerical experiments show, that cold state conditions in the inverse model do not influence the inverse rainfall estimates, when considering an adequate spin-up time. The application of the inverse model is a feasible approach to obtain improved estimates of mean areal rainfall. These can be used to enhance interpolated rainfall fields, e.g. for the estimation of rainfall correction factors, the parameterisation of elevation dependency or the application in real-time flood forecasting systems.
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ADHIKARI, RN, S. CHATTARAJAN, US PATTNAIK, and MM SRJVASTAVA. "Rainfall-runoff relationship based on the model of runoff formation at the natural storage." MAUSAM 40, no. 3 (April 28, 2022): 81–84. http://dx.doi.org/10.54302/mausam.v40i3.2132.
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An attempt is mad~ to establish a relationship between rainfall and runoff. The basic input data are (i) rainfall, (ii) run off and (iii) evapotranspiration. The moisture content prior to rainfall under consideration and after the termination of rainfall is computed by water balance technique this method is applied in small agricultural catchments in Soil Conservation Research Farm at Ballary, Karnataka, which is categorised its semiarid zone of black soil region. The relationship between rainfall and runoff under different initial moisture content and rainfall intensities are found out. Attempts are also made to get relationship between moisture condition of the catchment after the end of rainfall and runoff with rainfall intensities as an additional factor. The estimated runoff obtained from various equations are compared with the observed runoff. The rainfall-runoff relationship with initial moisture content as third parameter gives encouraging results for estimation of runoff.
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Ma, Ying, He Hai Xie, and Chun Li. "Experimental Analysis on Runoff and Sediment from Sloping Lands in Karst Region." Advanced Materials Research 1073-1076 (December 2014): 1624–29. http://dx.doi.org/10.4028/www.scientific.net/amr.1073-1076.1624.
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In order to study the features of Mountainous watershed runoff and erosion in karst region, , on the basis of design of experiment of the the big pore, slope runoff and erosion, artificial rainfall runoff experiment is made, by establishing artificial rainfall, slope runoff test plot. Large quantities of data were obtained through the artificial rainfall test. According to the experimental data, under different rainfall intensity, rainfall, under the pad surface and rainfall process, regularity of slope runoff and sediment yield in karst area is studied to provide data validation for the development of slope runoff and sediment yield model in karst region.
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Liang, Rui, Qiao Zhu, Huan Lian Ren, and Hua Jin. "Analysis on Characteristics of the Rainfall-Runoff in Beizhangdian Watershed." Applied Mechanics and Materials 90-93 (September 2011): 2578–82. http://dx.doi.org/10.4028/www.scientific.net/amm.90-93.2578.
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Beizhangdian watershed is a typical semi-dry and semi-humid region, where human activities have little effect on the hydrological cycle. Based on a 30-year hydrological observation data, the precipitation, runoff, and rainfall-runoff relationship were researched by the hydrology statistics analysis methods. The results indicated that the inter-annual change of rainfall-runoff of the watershed is remarkable, the annual distribution of rainfall-runoff is extremely uneven, and rainfall-runoff mainly occurred in flood season (June ~ September). There is a good uniformity between the variation tendency of annual rainfall and annual runoff in time and amount, the correlation coefficient of rainfall and runoff is 0.74, the value of the F-test is 4.23.
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Lee, Kang, Joo, Kim, Kim, and Lee. "Hydrological Modeling Approach Using Radar-Rainfall Ensemble and Multi-Runoff-Model Blending Technique." Water 11, no. 4 (April 23, 2019): 850. http://dx.doi.org/10.3390/w11040850.
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The purpose of this study is to reduce the uncertainty in the generation of rainfall data and runoff simulations. We propose a blending technique using a rainfall ensemble and runoff simulation. To create rainfall ensembles, the probabilistic perturbation method was added to the deterministic raw radar rainfall data. Then, we used three rainfall-runoff models that use rainfall ensembles as input data to perform a runoff analysis: The tank model, storage function model, and streamflow synthesis and reservoir regulation model. The generated rainfall ensembles have increased uncertainty when the radar is underestimated, due to rainfall intensity and topographical effects. To confirm the uncertainty, 100 ensembles were created. The mean error between radar rainfall and ground rainfall was approximately 1.808–3.354 dBR. We derived a runoff hydrograph with greatly reduced uncertainty by applying the blending technique to the runoff simulation results and found that uncertainty is improved by more than 10%. The applicability of the method was confirmed by solving the problem of uncertainty in the use of rainfall radar data and runoff models.
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Lee, Hyo-Sang, Min-Woo Jeon, Daniela Balin, and Michael Rode. "Application of Rainfall Runoff Model with Rainfall Uncertainty." Journal of Korea Water Resources Association 42, no. 10 (October 30, 2009): 773–83. http://dx.doi.org/10.3741/jkwra.2009.42.10.773.
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Chou, Chien-ming. "Random Modeling of Daily Rainfall and Runoff Using a Seasonal Model and Wavelet Denoising." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/917365.
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Instead of Fourier smoothing, this study applied wavelet denoising to acquire the smooth seasonal mean and corresponding perturbation term from daily rainfall and runoff data in traditional seasonal models, which use seasonal means for hydrological time series forecasting. The denoised rainfall and runoff time series data were regarded as the smooth seasonal mean. The probability distribution of the percentage coefficients can be obtained from calibrated daily rainfall and runoff data. For validated daily rainfall and runoff data, percentage coefficients were randomly generated according to the probability distribution and the law of linear proportion. Multiplying the generated percentage coefficient by the smooth seasonal mean resulted in the corresponding perturbation term. Random modeling of daily rainfall and runoff can be obtained by adding the perturbation term to the smooth seasonal mean. To verify the accuracy of the proposed method, daily rainfall and runoff data for the Wu-Tu watershed were analyzed. The analytical results demonstrate that wavelet denoising enhances the precision of daily rainfall and runoff modeling of the seasonal model. In addition, the wavelet denoising technique proposed in this study can obtain the smooth seasonal mean of rainfall and runoff processes and is suitable for modeling actual daily rainfall and runoff processes.
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Xiao, Pei Qing, Wen Yi Yao, and Chang Gao Wang. "Soil Erosion Process in Sloped Shrub Plots under Simulated Rainfall." Advanced Materials Research 347-353 (October 2011): 2094–97. http://dx.doi.org/10.4028/www.scientific.net/amr.347-353.2094.
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Runoff, sediment yield and infiltration process of shrub plots were studied under rainfall intensities of 45, 87 and 127 mm/h with 20° slope gradient using simulated rainfall experiment. The results showed that cumulative runoff and cumulative sediment yield of shrub plot had an obvious positive correlation with rainfall time. Under rainfall intensity of 45 mm/h, runoff and sediment yield of shrub plot kept a constant level. Under rainfall intensity of 87 mm/h, runoff kept a fluctuant increase, whereas sediment yield basically kept steady. Under rainfall intensity of 127 mm/h, runoff and sediment yield of shrub plot increased evidently due to the formation of erosion pits. Infiltration rate of shrub plot had a negative relation with runoff as well as sediment yield.
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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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Mo, Chongxun, Guiyan Mo, Junkai Qin, Ming Zhou, Qing Yang, Ya Huang, and Yunchuan Yang. "Rainfall and runoff characteristics in a karstic basin of China." Journal of Water and Climate Change 10, no. 1 (June 29, 2018): 117–29. http://dx.doi.org/10.2166/wcc.2018.073.
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Abstract This paper examines the rainfall and runoff characteristics in a karstic basin of China. The results indicated that the inner-annual distributions of rainfall and runoff were uneven and slightly different, as the concentration period of rainfall (from April to October) was earlier; there was a delay of about a month before the runoff (from May to September), and the concentrated volume accounted for 87% of annual precipitation or annual streamflow. Interannually, rainfall changed more significantly than runoff, the wet years lasted longer than the dry years (rainfall), while the high and low flow years were equal for runoff. In addition, judging from the value of the Mann-Kendall test, the average annual change of rainfall (−2.36) was more significant than that of runoff (−2.05), and the seasonal pattern of runoff maintained an opposite tendency in autumn and winter before 1990. The changes in runoff were mainly associated with rainfall and the formation conditions in the karstic area, and the reservoir in this basin should be operated with different flood limiting water levels, and the vegetation coverage should be improved.
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Moore, R. J. "The PDM rainfall-runoff model." Hydrology and Earth System Sciences 11, no. 1 (January 17, 2007): 483–99. http://dx.doi.org/10.5194/hess-11-483-2007.
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Abstract. The Probability Distributed Model, or PDM, has evolved as a toolkit of model functions that together constitute a lumped rainfall-runoff model capable of representing a variety of catchment-scale hydrological behaviours. Runoff production is represented as a saturation excess runoff process controlled by the absorption capacity (of the canopy, surface and soil) whose variability within the catchment is characterised by a probability density function of chosen form. Soil drainage to groundwater is controlled by the water content in excess of a tension threshold, optionally inhibited by the water content of the receiving groundwater store. Alternatively, a proportional split of runoff to fast (surface storage) and slow (groundwater) pathways can be invoked with no explicit soil drainage function. Recursive solutions to the Horton-Izzard equation are provided for routing flows through these pathways, conveniently considered to yield the surface runoff and baseflow components of the total flow. An alternative routing function employs a transfer function that is discretely-coincident to a cascade of two linear reservoirs in series. For real-time flow forecasting applications, the PDM is complemented by updating methods based on error prediction and state-correction approaches. The PDM has been widely applied throughout the world, both for operational and design purposes. This experience has allowed the PDM to evolve to its current form as a practical toolkit for rainfall-runoff modelling and forecasting.
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IWAGAMI, Sho. "Ideas for Rainfall-Runoff Research." JOURNAL OF JAPAN SOCIETY OF HYDROLOGY AND WATER RESOURCES 31, no. 3 (May 5, 2018): 200–201. http://dx.doi.org/10.3178/jjshwr.31.200.
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O'Loughlin, Geoffrey, Wayne Huber, and Bernard Chocat. "Rainfall-runoff processes and modelling." Journal of Hydraulic Research 34, no. 6 (November 1996): 733–51. http://dx.doi.org/10.1080/00221689609498447.
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Wong, Tommy S. W. "Rainfall-Runoff Processes And Modelling." Journal of Hydraulic Research 36, no. 2 (March 1998): 281–83. http://dx.doi.org/10.1080/00221689809498638.
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Todini, E. "The ARNO rainfall—runoff model." Journal of Hydrology 175, no. 1-4 (February 1996): 339–82. http://dx.doi.org/10.1016/s0022-1694(96)80016-3.
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Özelkan, Ertunga C., and Lucien Duckstein. "Fuzzy conceptual rainfall–runoff models." Journal of Hydrology 253, no. 1-4 (November 2001): 41–68. http://dx.doi.org/10.1016/s0022-1694(01)00430-9.
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Hromadka, T. V. "Rainfall-runoff models: A review." Environmental Software 5, no. 2 (June 1990): 82–103. http://dx.doi.org/10.1016/0266-9838(90)90005-q.
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Basha, H. A. "Simple Nonlinear Rainfall-Runoff Model." Journal of Hydrologic Engineering 5, no. 1 (January 2000): 25–32. http://dx.doi.org/10.1061/(asce)1084-0699(2000)5:1(25).
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FARQUHARSON, F. A. K., D. T. PLINSTON, and J. V. SUTCLIFFE. "Rainfall and runoff in Yemen." Hydrological Sciences Journal 41, no. 5 (October 1996): 797–811. http://dx.doi.org/10.1080/02626669609491546.
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Dai, Q., Z. Liu, H. Shao, and Z. Yang. "Karst bare slope soil erosion and soil quality: a simulation case study." Solid Earth 6, no. 3 (July 31, 2015): 985–95. http://dx.doi.org/10.5194/se-6-985-2015.
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Abstract. The influence on soil erosion by different bedrock bareness ratios, different rainfall intensities, different underground pore fissure degrees and rainfall duration are researched through manual simulation of microrelief characteristics of karst bare slopes and underground karst crack construction in combination with artificial simulation of rainfall experiment. The results show that firstly, when the rainfall intensity is small (30 and 50 mm h−1), no bottom load loss is produced on the surface, and surface runoff, underground runoff and sediment production are increased with the increasing of rainfall intensity. Secondly, surface runoff and sediment production reduced with increased underground pore fissure degree, while underground runoff and sediment production increased. Thirdly, raindrops hit the surface, forming a crust with rainfall duration. The formation of crusts increases surface runoff erosion and reduces soil infiltration rate. This formation also increases surface-runoff-erosion-damaged crust and increased soil seepage rate. Raindrops continued to hit the surface, leading the formation of crust. Soil permeability showed volatility which was from reduction to increases, reduction, and so on. Surface and subsurface runoff were volatile with rainfall duration. Fourthly, when rock bareness ratio is 50 % and rainfall intensities are 30 and 50 mm h−1, runoff is not produced on the surface, and the slope runoff and sediment production present a fluctuating change with increased rock bareness ratio. Fifthly, the correlation degree between the slope runoff and sediment production and all factors are as follows: rainfall intensity-rainfall duration-underground pore fissure degree–bedrock bareness ratio.
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Das, P., K. Mahmud, and S. Karmaker. "Surface-Runoff Characteristics under Simulated Rainfall Conditions." Progressive Agriculture 24, no. 1-2 (June 17, 2014): 219–27. http://dx.doi.org/10.3329/pa.v24i1-2.19175.
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This paper describes a rainfall-runoff simulation study, conducted in a laboratory to investigate surface runoff characteristics, verify unit hydrograph assumption and investigate the nature of the recession constant. A hydrology bench consisting of a metallic tray with an over head sprinkler system was used for this study. The metallic tray with soil bed and a river network acted as a small catchment. The over head sprinkler system consisting of spray nozzles acted as rainfall simulator. Different rainfall intensities and durations were taken as the treatments for the experiments. Surface runoff volume was collected at 10 secondly pulses of time in each experiment. Collected data were then processed and analyzed to explain the results. Unit hydrographs were developed from the surface runoff hydrographs for different rainfall durations and intensities. Recession constant K was calculated from the recession limb of each surface runoff hydrograph by optimization. Investigations show that runoff volume, runoff generation rate and peak runoff rate increase with the increasing rainfall duration. However, the peak runoff rate per sec of effective rainfall decreases with the increasing rainfall duration. There is also an evidence of the effects of rainfall intensity on runoff characteristics but no specific trend is identified. This study also reveals that the assumption of linearity between runoff volume and hydrograph ordinates is partially valid with some error which may be attributed to the non-uniform distributions of rainfall. Nature of recession constant suggests that the recession hydrograph is not only a function of catchment characteristics but also depends on rainfall intensities.DOI: http://dx.doi.org/10.3329/pa.v24i1-2.19175 Progress. Agric. 24(1&2): 219 - 227, 2013
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Yoo, Chulsang, and Jooyoung Park. "Rainfall-runoff analysis based on competing linear impulse responses: decomposition of rainfall-runoff processes." Hydrological Processes 22, no. 5 (2008): 660–69. http://dx.doi.org/10.1002/hyp.6633.
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Vaze, J., D. A. Post, F. H. S. Chiew, J. M. Perraud, J. Teng, and N. R. Viney. "Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs." Journal of Hydrometeorology 12, no. 5 (October 1, 2011): 1100–1112. http://dx.doi.org/10.1175/2011jhm1340.1.
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Abstract Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.
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K. N., Vidya. "Runoff assessment by Storm water management model (SWMM)- A new approach." Journal of Applied and Natural Science 13, SI (July 19, 2021): 142–48. http://dx.doi.org/10.31018/jans.v13isi.2813.
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The present study investigated the storm wise runoff collected in farm pond with the runoff estimated by Storm Water Management Model (SWMM) and Soil Conservation Service (SCS-CN) models. The SWMM and SCS-CN models estimated runoff depth storm wise. The runoff depths correspond to the catchment area given the runoff volume from the catchment. The runoff depth estimated from the Storm Water Management Model and Soil Conservation Service model was compared against the depth of runoff estimated from the Water balance model. For small rainfall depths, the runoff estimated from the Storm Water Management Model was at par with the actual runoff volume stored at the pond. It is necessary to know the watershed runoff contribution to the river or streams due to rainfall in order to determine environmental risk or flood potential. In larger rainfall depth, the runoff volume estimated from the SWMM model was less than the stored runoff volume at Farm Pond. The Soil Conservation Service Model gave better results for larger rainfall depth compared to Storm Water Management Model. SWMM was able to simulate runoff depth for small rainfall depths of 2mm. The peak runoff depths were produced by rainfall depths of 35.5mm. Initial abstractions of the study area for antecedent moisture content i.e. AMC I, AMCII and AMCIII are 53.2, 23.91 and 10.43mm, respectively. The comparison showed that both SWMM and SCS-CN models gave better runoff quantification results.
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Dai, Q., Z. Liu, H. Shao, and Z. Yang. "Karst bare slope soil erosion and soil quality: a simulation case study." Solid Earth Discussions 7, no. 2 (June 5, 2015): 1639–71. http://dx.doi.org/10.5194/sed-7-1639-2015.
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Abstract. The influence on soil erosion by different bedrock bareness ratios, different rainfall intensities, different underground pore fissure degrees and rainfall duration are researched through manual simulation of microrelief characteristics of karst bare slopes and underground karst crack construction in combination with artificial simulation of rainfall experiment. The results show that firstly, when the rainfall intensity is small (30 and 50 mm h−1), no bottom load loss is produced on the surface, and surface and underground runoff and sediment production is increased with the increasing of rainfall intensity; secondly, surface runoff and sediment production reduced with increased underground pore fissure degree, while underground runoff and sediment production increased; thirdly, raindrops hit the surface, forming a crust with rainfall duration. The formation of crusts increases surface runoff erosion and reduces soil infiltration rate. Increasing of surface runoff erosion damaged crust and increased soil seepage rate. Raindrops continued to hit the surface, leading the formation of crust. Soil permeability showed volatility which were from reduction to increases and reduction, and so on. Surface and subsurface runoff were volatility with rainfall duration; fourthly, when rock bareness ratio is 50% and rainfall intensities are 30 and 50 mm h−1, runoff is not produced on the surface, and the slope runoff and sediment production presents a fluctuating change with increased rock bareness ratio; fifthly, the correlation degree between the slope runoff and sediment production and all factors are as follows: rainfall intensity > rainfall duration > underground pore fissure degree > bed rock bareness ratio.
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Ajmal, Muhammad, Muhammad Waseem, Jae-Hyun Ahn, and Tae-Woong Kim. "Improved Runoff Estimation Using Event-Based Rainfall-Runoff Models." Water Resources Management 29, no. 6 (January 29, 2015): 1995–2010. http://dx.doi.org/10.1007/s11269-015-0924-z.
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Xu, Jiajia, Jianjun Zhang, Minyi Li, and Fenzhong Wang. "Effect of Rain Peak Morphology on Runoff and Sediment Yield in Miyun Water Source Reserve in China." Water 11, no. 12 (November 20, 2019): 2429. http://dx.doi.org/10.3390/w11122429.
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The research on the impact of rainfall patterns on runoff and sediment yield is still insufficient, especially under natural rainfall conditions. We analyzed the influence of rain peak morphology on runoff and sediment yield based on the data of rainfall, runoff, and sediment in the bare runoff plot of Shixia, a small watershed in the Miyun district of Beijing, from 2007 to 2016. We took 0.4 mm min−1 as the standard of rain peak classification and the peak width, peak number, peak value, peak position and multi-peak continuity as the indexes of rain peak morphology. The results showed that: (1) Peak number, peak value, and peak width were significantly correlated with runoff and sediment yield, while peak position was irrelevant. The order of correlation between rain peak morphology indexes and runoff yield was peak width (0.71) > peak number (0.69) > peak value (0.33) > peak position (0.05). The order of correlation between rain peak morphological indexes and sediment yield was peak width (0.62) > peak value (0.36) > peak number (0.36) > peak position (−0.09). The multi-peak continuity was not correlated with runoff (0.12) and sediment yield (0.45). (2) When the number of rain peaks was greater than one in a single rainfall, the amount of runoff and sediment production increased significantly. (3) For multi-peak rainfall, 90 min was the boundary point of the rain peak interval, and the sediment yield formed by rainfall with a rain peak continuity >1/90 min−1 was significantly larger than the rainfall of ≤1/90 min−1. (4) Covariance analysis showed that the runoff caused by rainfall with a peak at the middle positions was obviously more than rainfall with a peak at the front position. However, the peak position had no significant effect on the sediment yield. (5) The peak rainfall amount of a rainfall (TPR) was a comprehensive index reflecting peak number, peak value and peak width, and the correlation between it and the sediment yield and runoff reached 0.60 and 0.71, respectively. Statistical rainfall characteristic indexes included rainfall amount, average rainfall intensity, rainfall duration, I5 (maximum 5-min rainfall intensity), I10, I15, I20, I30, and I60, among which I60 had the strongest correlation with runoff and sediment yield (0.69, 0.60), which were much larger than other rainfall indexes (0.08~0.47, 0.14~0.48) except rainfall amount (0.75, 0.37). By establishing a regression equation, it was found that both TPR and I60 had good explanatory power for runoff and weak explanatory power for sediment yield.
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Zhou, Yan, Zhongmin Liang, Binquan Li, Yixin Huang, Kai Wang, and Yiming Hu. "Seamless Integration of Rainfall Spatial Variability and a Conceptual Hydrological Model." Sustainability 13, no. 6 (March 23, 2021): 3588. http://dx.doi.org/10.3390/su13063588.
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Rainfall is an important input to conceptual hydrological models, and its accuracy would have a considerable effect on that of the model simulations. However, traditional conceptual rainfall-runoff models commonly use catchment-average rainfall as inputs without recognizing its spatial variability. To solve this, a seamless integration framework that couples rainfall spatial variability with a conceptual rainfall-runoff model, named the statistical rainfall-runoff (SRR) model, is built in this study. In the SRR model, the exponential difference distribution (EDD) is proposed to describe the spatial variability of rainfall for traditional rain gauging stations. The EDD is then incorporated into the vertically mixed runoff (VMR) model to estimate the statistical runoff component. Then, the stochastic differential equation is adopted to deal with the flow routing under stochastic inflow. To test the performance, the SRR model is then calibrated and validated in a Chinese catchment. The results indicate that the EDD performs well in describing rainfall spatial variability, and that the SRR model is superior to the Xinanjiang model because it provides more accurate mean simulations. The seamless integration framework considering rainfall spatial variability can help build a more reasonable statistical rainfall-runoff model.
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Zhang, Min, Rui Qiang Zhang, Te Qi, Yun Hu Xie, Cong Cong Cheng, and Chun Xing Hai. "Research on Xilamuren Desert-Steppe Rainfall Experiment Segmentation Regular Pattern – Based on Rainfall Simulation Experiment." Advanced Materials Research 830 (October 2013): 403–10. http://dx.doi.org/10.4028/www.scientific.net/amr.830.403.
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The rainfall is the main soil water supply to the soil of desert-steppe. It divides into three parts, evaporation, infiltration and runoff, after falling on to the surface. Those three parts are affected by many factors. Studies of rainfall division in desert-steppe were rare, the proportions of evaporation, infiltration and runoff are uncertain. So Under the condition of different vegetation, we conduct six times rainfall simulation experiment under different rainfall intensity. Simulation shows that rainfall process, the surface coverage and soil condition affect division. The evaporation section of rainfall accounted for 1/2 ~ 2/3. Infiltration section accounted for 30% ~ 50%. Runoff is the smallest. The rainfall intensity plays a decisive role on the runoff. Different vegetation coverage, division proportion is different. The interception and delay function of vegetation main effect evaporation and runoff, it can make the evaporation increased to more than 70%, reduce runoff to a third. Water content of soil profile before rainfall is the main factors affecting infiltration volume. The soil moisture before rain affects the infiltration rate at the beginning of rainfall. If rainfall duration is long enough, infiltration capacity is almost a constant.
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Brocca, L., S. Liersch, F. Melone, T. Moramarco, and M. Volk. "Application of a model-based rainfall-runoff database as efficient tool for flood risk management." Hydrology and Earth System Sciences 17, no. 8 (August 6, 2013): 3159–69. http://dx.doi.org/10.5194/hess-17-3159-2013.
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Abstract. A framework for a comprehensive synthetic rainfall-runoff database was developed to study catchment response to a variety of rainfall events. The framework supports effective flood risk assessment and management and implements simple approaches. It consists of three flexible components, a rainfall generator, a continuous rainfall-runoff model, and a database management system. The system was developed and tested at two gauged river sections along the upper Tiber River (central Italy). One of the main questions was to investigate how simple such approaches can be applied without impairing the quality of the results. The rainfall-runoff model was used to simulate runoff on the basis of a large number of rainfall events. The resulting rainfall-runoff database stores pre-simulated events classified on the basis of the rainfall amount, initial wetness conditions and initial discharge. The real-time operational forecasts follow an analogue method that does not need new model simulations. However, the forecasts are based on the simulation results available in the rainfall-runoff database (for the specific class to which the forecast belongs). Therefore, the database can be used as an effective tool to assess possible streamflow scenarios assuming different rainfall volumes for the following days. The application to the study site shows that magnitudes of real flood events were appropriately captured by the database. Further work should be dedicated to introduce a component for taking account of the actual temporal distribution of rainfall events into the stochastic rainfall generator and to the use of different rainfall-runoff models to enhance the usability of the proposed procedure.
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Sang, Xiuli, Jianxin Xu, Kun Zhang, and Hua Wang. "Analysis and Modeling of Time-Correlated Characteristics of Rainfall-Runoff Similarity in the Upstream Red River Basin." Advances in Meteorology 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/579764.
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We constructed a similarity model (based on Euclidean distance between rainfall and runoff) to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.
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Zhao, Na Na, Fu Liang Yu, Chuan Zhe Li, Jia Liu, and Hao Wang. "An Experimental Study on the Rainfall-Runoff Progress of Wheat under Different Slope Angle." Advanced Materials Research 912-914 (April 2014): 1986–94. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1986.
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Rainfall-runoff process plays an important role in hydrological cycle, and the study on the rainfall-runoff will provide foundation and basis for research on basin hydrology and flood forecasting. In this paper, the surface runoff and subsurface flow of wheat were observed in the laboratory by artificial rainfall, and analyzed the cumulated surface runoff and recession process of subsurface flow by regression analysis. In addition, the factors affected the runoff and response of soil moisture on the runoff coefficients was also discussed. Results showed that the rainfall intensity, soil coverage and slope had important influence on the surface runoff generation, and the surface runoff was observed when the total rainfall amount exceeded 32mm and 13mm for 5°and 15° slope respectively. The cumulative surface runoff could be expressed as a power function, which had higher determination coefficient R2 (0.92~0.999). The subsurface flow was only observed at the ripening period and wheat stubble treatment, and mainly affected by slope angle and initial soil moisture, whereas rainfall intensity showed little impact. The recession curve of subsurface flow can be described as a simple exponential expression or power function, which the determination coefficient was 0.88 and 0.94 by regression analysis, respectively. Moreover, there was an obvious threshold (approximately 30%) between the average initial soil moisture and runoff coefficients, which the runoff increased significantly as above the threshold.
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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.
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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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Man, Zihao, Qinghua Luan, Dan Xu, Congwu Sun, and Yongzhen Niu. "The Design and Check of Regional Typical Rainfall Processes: A Case Study of Yongnian District, China." MATEC Web of Conferences 246 (2018): 01009. http://dx.doi.org/10.1051/matecconf/201824601009.
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Observing and analyzing runoff process is an important method to study the principle of runoff yield and concentration. However, natural rainfall is random and difficult to monitor the related runoff process timely, so most of the runoff processes analysis is based on the artificial rainfall experiments. In this study, the selected test site is located in Yongnian district, Hebei Province, China. Rainfall volume, rainfall peak, rainfall duration and peak ratio were considered as the key factors of designed rainfall type. Based on regional historical observed rainfall data from 1980 to 2012, the two mainly representative processes which was in flood season and non-flood season respectively, were calculated. The most typical rainfall process in each period was screened through two methods of characteristic frequency distribution. Furthermore, accuracy of rainfall intensity and uniformity of spatial and temporal distribution were selected as the criteria for correcting the artificial rainfall devices. This research is the foundation of the artificial runoff experiment and provide reference to regional climate change research and local water resources assessment.
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Ji, Gui Xia, Chun Lei Xu, Huan Zhang, Da Wei Si, and Yi Cheng Lu. "Change Law Research and Characteristic Analysis of Urban Pavement Runoff Pollution." Advanced Materials Research 518-523 (May 2012): 2418–22. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.2418.
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Through the pavement runoff monitoring of USST（the University of Shanghai for Science and Technology） courtyard pavement runoff and JunGong road runoff, the analysis of main influence factors and pollution degree, this article indicate that underling surface, rainfall duration, rainfall intensity and rainfall are important influencing factors of initial runoff water quality. Organic and suspended solid are the main pollutants of urban runoff. COD, SS and turbidity are the main pollution index, and they present exponential change law and finally achieved stability along with the delay of rainfall. The more heavily it rains, the more quickly water quality become stabilization. Stable water quality are influenced by rainfall character and pavement character. The more heavily it rains, the better stable water quality is. The more dust pavement contain, the worse stable water quality is. Stable water quality of courtyard pavement runoff are better than street runoff.
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Guan, Hongjie, and Rongjiang Cao. "Effects of biocrusts and rainfall characteristics on runoff generation in the Mu Us Desert, northwest China." Hydrology Research 50, no. 5 (August 30, 2019): 1410–23. http://dx.doi.org/10.2166/nh.2019.046.
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Abstract How the presence of biocrusts regulates runoff generation in the Mu Us Desert is not well known. Runoff experiments under natural and artificial rainfalls and numerical simulations were conducted in semiarid environments to evaluate the effects of biocrust type and rainfall characteristics on runoff. The experimental results showed that the water drop penetration time (WDPT) of the moss-dominated biocrusts was 68.7% higher than that of lichen-dominated biocrusts. Nevertheless, the saturated hydraulic conductivity (Ks) for moss-dominated biocrusts was 72.7% lower than that for the lichen-dominated biocrusts. Runoff yield for moss-dominated biocrusts was significantly higher than that for lichen-dominated biocrusts. Runoff yield was mainly explained by rainfall amount (or maximum 5-min rainfall intensity, I5max) (P < 0.001) and WDPT (P = 0.001). The influences of biocrust type, rainfall intensity, and their interaction on runoff coefficient were significant at the probability level of 0.01. The results of numerical simulations concluded that surface runoff was generated for lichen- and moss-dominated biocrusts when rainfall intensity reached 73.5 and 49 mm h–1, respectively. Runoff coefficient in the moss-covered soil increased obviously when rainfall intensity changed from 49 to 73.5 mm h–1. The results suggest that runoff could be changed substantially under increasing trends in rainfall intensity in the Mu Us Desert.
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Wang, Lei, Yan Li, Jiajun Wu, Zhizhuang An, Linna Suo, Jianli Ding, Shuo Li, Dan Wei, and Liang Jin. "Effects of the Rainfall Intensity and Slope Gradient on Soil Erosion and Nitrogen Loss on the Sloping Fields of Miyun Reservoir." Plants 12, no. 3 (January 17, 2023): 423. http://dx.doi.org/10.3390/plants12030423.
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Environmental loss is primarily caused by soil, water, and nutrient loss, and runoff is associated with nutrient transport and sediment loss. Most existing studies have focused on one influencing factor, namely slope gradient or rainfall intensity, for slope erosion and nutrient loss, but the joint effects of the two factors have rarely been researched. In this context, the impact of slope gradients (0°, 5°, 10°, and 15°) and rainfall intensities (30, 40, 50, 60, 70, and 80 mm/h) on soil erosion and nutrient loss on the sloping fields of Miyun Reservoir were explored using the indoor artificial rainfall simulation testing system. Based on the results of the study, the variation of runoff coefficient with slope gradient was not noticeable for rainfall intensities <40 mm/h; however, for rainfall intensities >40 mm/h, the increased range of runoff coefficient doubled, and the increase was the fastest under 0° among the four slope gradients. The slope surface runoff depth and runoff rate showed positive correlations with the rainfall intensity (r = 0.875, p < 0.01) and a negative correlation with the slope gradient. In addition, the cumulative sediment yield was positively related to the slope gradient and rainfall intensity (r > 0.464, p < 0.05). Moreover, the slope surface runoff-associated and sediment-associated loss rates of total nitrogen (TN) rose as the rainfall intensity or slope gradient increased, and significant linear positive correlations were found between the runoff-associated TN loss rate (NLr) and the runoff intensity and between the sediment-associated NLr and the erosion intensity. In addition, there were positive linear correlations between slope runoff-associated or sediment-associated TN loss volumes and rainfall intensity, surface runoff, and sediment loss volumes, which were highly remarkable. The slope gradient had a significant positive correlation with the slope surface runoff-associated TN loss at 0.05 (r = 0.452) and a significant positive correlation with the sediment-associated TN loss at the level of 0.01 (r = 0.591). The rainfall intensity exhibited extremely positive correlations with the slope surface runoff-associated and sediment-associated TN loss at 0.01 (r = 0.717 and 0.629) Slope gradients have less effect on nitrogen loss on sloped fields than rainfall intensity, mainly because rainfall intensity affects runoff depth. Based on the findings of this study, Miyun Reservoir may be able to improve nitrogen loss prevention and control.
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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.
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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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Kim, Changhwan, and Dae-Hong Kim. "Effects of Rainfall Spatial Distribution on the Relationship between Rainfall Spatiotemporal Resolution and Runoff Prediction Accuracy." Water 12, no. 3 (March 17, 2020): 846. http://dx.doi.org/10.3390/w12030846.
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We studied how rainfall spatial distribution affects the relationship between rainfall spatiotemporal resolution and runoff prediction accuracy under real field conditions. We gathered radar rainfall and discharge data for three rainfall events. These rainfall-runoff events were then reproduced using a kinematic wave model. Modeling accuracy was estimated quantitatively using the Nash–Sutcliffe model efficiency coefficient and peak discharge ratio. Normalized root-mean-square error ( nRMSE ), skewness ( S k ), and second scaled spatial moment of catchment rainfall ( δ 2 ) were employed to quantify rainfall spatial distribution characteristics. By relating the accuracy of modeling results to the rainfall spatial characteristics using various rainfall spatiotemporal resolutions, we found that the modeling results converged to a value as the nRMSE , | S k | and | 1 − δ 2 | decreased. That is, rainfall spatial distributions affect the relationship between lower limit of rainfall spatiotemporal resolution for runoff models and runoff prediction accuracy.
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Whyte, J. M., A. Plumridge, and A. V. Metcalfe. "Comparison of predictions of rainfall-runoff models for changes in rainfall in the Murray-Darling Basin." Hydrology and Earth System Sciences Discussions 8, no. 1 (January 24, 2011): 917–55. http://dx.doi.org/10.5194/hessd-8-917-2011.
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Abstract. Management of water resources requires an appreciation for how climate change, in particular changes in rainfall, affects the volume of water available in runoff. While there are many studies that use hydrological models for this purpose, comparisons of predictions appear much less commonly in the literature. This paper aims to contribute to this discussion by proposing methods for evaluating the effect on daily runoff projections of rainfall-runoff models when historical daily rainfall inputs are scaled by factors that increase and decrease the rainfall. Considered are the widely used lumped conceptual model SIMHYD and a selection of time series models which feature lagged runoff and rainfall terms. In particular these are AutoRegressive with eXogenous input (ARX), a variant containing nonlinear autoregressive runoff terms (NARX), a model for the log transform of runoff, a finite impulse response model (FIR) and a two regime threshold autoregressive model with exogenous input (TARX). Results show that SIMHYD and the single regime time series models considered have very different behaviour under scaled input rainfall. Reasons for the discrepancy are discussed. The amplification of the rainfall change observed for SIMHYD is consistent with claims that a 1% change in rainfall leads to a 2–3% change in runoff in the Murray-Darling Basin.
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El‐Jabi, N., and S. Sarraf. "Effect of Maximum Rainfall Position on Rainfall‐Runoff Relationship." Journal of Hydraulic Engineering 117, no. 5 (May 1991): 681–85. http://dx.doi.org/10.1061/(asce)0733-9429(1991)117:5(681).
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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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Sishah, Shimelis. "Rainfall runoff estimation using GIS and SCS-CN method for awash river basin, Ethiopia." International Journal of Hydrology 5, no. 1 (March 22, 2021): 33–37. http://dx.doi.org/10.15406/ijh.2021.05.00263.
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Understanding hydrological behavior is an important part of effective watershed management and planning. Runoff resulted from rainfall is a component of hydrological behavior that is needed for efficient water resource planning. In this paper, GIS based SCS-CN runoff simulation model was applied to estimate rainfall runoff in Awash river basin. Global Curve Number (GCN250), Maximum Soil Water Retention (S) and Rainfall was used as an input for SCS-CN runoff simulation model. The final surface runoff values for the Awash river basin were generated on the basis of total annual rainfall and maximum soil water retention potential (S) of the year 2020. Accordingly, a runoff variation that range from 83.95 mm/year to a maximum of 1,416.75 mm/year were observed in the study region. Conversely, recently developed Global Curve Number (GCN250) data was tested with Pearson correlation coefficient to be used as an input for SCS-CN runoff simulation model. In doing so, predicted runoff generated in SCS-CN using GCN250 as a model input was validated with observed runoff obtained from station gauges in the study region. The results of validation show that, predicted runoff was well correlated with observed runoff with correlation coefficient of 0.9253. From this stand point, it is observed that the new GCN250 data can be used as an input for SCS-CN model to estimate rainfall runoff at basin level. Furthermore, correlation analysis was performed to explain the relationship between mean annual rainfall and surface runoff. The relationship between these two variables indicates a strong linear relationship with correlation coefficient of 0.9873.
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Raju R., Siddi, Sudarsana Raju G., and Rajasekhar M. "Estimation of Rainfall Runoff using SCS-CN Method with RS and GIS Techniques for Mandavi Basin in YSR Kadapa District of Andhra Pradesh, India." Hydrospatial Analysis 2, no. 1 (May 31, 2018): 1–15. http://dx.doi.org/10.21523/gcj3.18020101.
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The study aims to estimate the surface runoff in the semi-arid crystalline rock terrain of Mandavi basin using Remote Sensing (RS) and Geographical Information System (GIS) techniques. The rainfall is the only source of water in this basin drains off and little amount percolates into the ground. The study area experiences rigorous groundwater scarcity despite having high rainfall -runoff. Consequently, integrated RS and GIS techniques are used for estimation of the runoff. The weighted curve number (CN) is resolute based on AMC-II (Antecedent Moisture Condition) with the combination of HSGs (hydrologic soil groups) and LU/LC (land use and land cover) categories. The outcomes of study showed 52.292 (CNII) of normal condition, 31.506(CNI) of dry condition and 71.583 (CNIII) of wet condition. The ungauged watershed exhibits an annual average of rainfall, runoff, runoff volume and runoff coefficients for 20 years are 688.82 mm, 478.06 mm, 699.75 m3 and 0.69, respectively. The annual rainfall-runoff relationship during 1995 to 2014 is indicating the overall increase in runoff with the rainfall in the study area.
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Wang, Le, Hui Cao, Yurong Li, Baofei Feng, Hui Qiu, and Hairong Zhang. "Attribution Analysis of Runoff in the Upper Reaches of Jinsha River, China." Water 14, no. 17 (September 5, 2022): 2768. http://dx.doi.org/10.3390/w14172768.
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The upper Jinsha River is an important ecological reserve and hydropower energy base in China. This paper uses relative importance analysis to analyze the causes of runoff changes from the perspectives of early runoff, rainfall, snowfall, evaporation and soil water content. The results show that the factors influencing runoff in the upper Jinsha River are complex and have significant spatial and temporal heterogeneity. From November to March, the main factor is the runoff in the preceding month, the contribution of which can be more than 85%; from April to May, the runoff is significantly affected by snow, and its contribution in May is more than 65%. The snow affecting the runoff is mainly located near Gangtuo station and Batang station, and its influence has a time lag of about one month, In June, the influence factors of the runoff are quite complicated, and the contribution of the early runoff, rainfall, snow, evaporation and soil water content is relatively close; from July to September, the runoff is mainly influenced by the rainfall above Batang station, its average contribution being more than 50% and higher than 80% in August. Runoff in July and August is mainly affected by the rainfall in the same period, and in September is mainly affected by the rainfall in the preceding month. In October, the main influence factors are runoff and rainfall of the preceding month, and their contributions are more than 70%.