Rainfall–runoff modelling of railway embankment steep slopes

Abstract

A distributed 1D rainfall–runoff model is presented. It consists of the Saint Venant continuity and momentum equations for overland flow and a modified Green-Ampt model for the infiltration on railway embankment steep slopes. The model is applied to adjacent 10-m-wide erosion control experimental plots with different percentages of grass cover. A relationship between the 2-day antecedent rainfall and initial moisture content was established and used to predict the saturated hydraulic conductivity (Ks). Average values of Ks for 0, 50 and 100% grass cover were found to be 0.1, 1.19 and 2.56 mm/h, respectively. For the majority of cases, the model simulated runoff with acceptable accuracy, 68% having Nash-Sutcliffe efficiency (NSE) values above 0.50. The average NSE value varied between 0.60 and 0.80, with 0% grass-covered plots yielding the highest values. As expected, the runoff volume decreased with increasing percentage of grass cover.

Citation Sajjan, A.K., Gyasi-Agyei, Y., and Sharma, R.H., 2013. Rainfall–runoff modelling of railway embankment steep slopes. Hydrological Sciences Journal, 58 (5), 1162–1176.

Editor D. Koutsoyiannis     

Rainfall–runoff simulation using a normalized antecedent precipitation index

Abstract

The normalized antecedent precipitation index (NAPI) model by Heggen for the prediction of runoff yield is analytically derived from the water balance equation. Heggen's model has been simplified further to a rational form and its performance verified with the Soil Conservation Service Curve Number (SCS-CN) model. The simplified model has three coefficients specific to a watershed, and requires two inputs: rainfall and the derived parameter, NAPI. The characteristic behaviour of the NAPI has resonance with the curve number (CN) of the SCS model. The proposed NAPI model was applied to three watersheds in the semi-arid region of India to simulate runoff yield. The model showed improved correlation between the observed and predicted runoff data compared to the SCS-CN model. The F test and paired t test also confirmed the reliability of the model with significance levels of 0.01 and 0.001%, respectively. The proposed model could be used successfully for rainfall–runoff modelling in a watershed.

Citation Ali, S., Ghosh, N. C. & Singh, R. (2010) Rainfall–runoff simulation using a normalized antecedent precipitation index. Hydrol. Sci. J. 55(2), 266–274.     

Rainfall—runoff response,event-based runoff coefficients and hydrograph separation

Abstract

Event-based runoff coefficients can provide information on watershed response. They are useful for catchment comparison to understand how different landscapes “filter” rainfall into event-based runoff and to explain the observed differences with catchment characteristics and related runoff mechanisms. However, the big drawback of this important parameter is the lack of a standard hydrograph separation method preceding its calculation. Event-based runoff coefficients determined with four well-established separation methods, as well as a newly developed separation method, are compared and are shown to differ considerably. This signifies that runoff coefficients reported in the literature often convey less information than required to allow for catchment classification. The new separation technique (constant-k method) is based on the theory of linear storage. Its advantages are that it is theoretically based in determining the end point of an event and that it can also be applied to events with multiple peaks. Furthermore, it is shown that event-based runoff coefficients in combination with simple statistical models improve our understanding of rainfall—runoff response of catchments with sparse data.     

Estimating Flood Quantiles on the Basis of Multi-Event Rainfall Simulation — Case Study

This paper presents an approach to estimating the probability distribution of annual discharges Q based on rainfall-runoff modelling using multiple rainfall events. The approach is based on the prior knowledge about the probability distribution of annual maximum daily totals of rainfall P in a natural catchment, random disaggregation of the totals into hourly values, and rainfall-runoff modelling. The presented Multi-Event Simulation of Extreme Flood method (MESEF) combines design event method based on single-rainfall event modelling, and continuous simulation method used for estimating the maximum discharges of a given exceedance probability using rainfall-runoff models. In the paper, the flood quantiles were estimated using the MESEF method, and then compared to the flood quantiles estimated using classical statistical method based on observed data.     

Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain)

Abstract

The hydrological response of a small agroforestry catchment in northwest Spain (Corbeira catchment, 16 km²) is analysed, with particular focus on rainfall events. Fifty-four rainfall–runoff events, from December 2004 to September 2007, were used to analyse the principal hydrological patterns and show which factors best explain the hydrological response. The nonlinearity between rainfall and runoff showed that the variability in the hydrological response of the catchment was linked to the seasonal dynamics of the rainfall and, to a lesser extent, to evapotranspiration. The runoff coefficient, estimated as the ratio between direct runoff and rainfall volume, on an event basis, was analysed as a function of rainfall characteristics (amount and intensity) and the initial catchment state conditions prior to an event, such as pre-event baseflow and antecedent rainfall index. The results revealed that the hydrological response depends both on the soil humidity conditions at the start of the event and on rainfall amount, whereas rainfall intensity presented only a significant correlation with discharge increment. The antecedent conditions seem to be a key point in runoff production, and they explain much of the response. The hydrographs are characterized by a steep rising limb, a relatively narrow peak discharge and slow recession limb. These data and the observations suggest that the subsurface flow is the dominant runoff process.

Editor Z.W. Kundzewicz; Associate editor T. Wagener

Citation Rodríguez-Blanco, M.L., Taboada-Castro, M.M. and Taboada-Castro, M.T., 2012. Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain). Hydrological Sciences Journal, 57 (3), 445–459.     

Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin

Abstract

Pakistan has suffered a devastating flood disaster in 2010. In the Kabul River basin (92 605 km²), large-scale riverine and flash floods caused destructive damage with more than 1100 casualties. This study analysed rainfall–runoff and inundation in the Kabul River basin with a newly developed model that simulates the processes of rainfall–runoff and inundation simultaneously based on two-dimensional diffusion wave equations. The simulation results showed a good agreement with an inundation map produced based on MODIS for large-scale riverine flooding. In addition, the simulation identified flash flood-affected areas, which were confirmed to be severely damaged based on a housing damage distribution map. Since the model is designed to be used even immediately after a disaster, it can be a useful tool for analysing large-scale flooding and to provide supplemental information to agencies for relief operations.

Editor Z.W. Kundzewicz

Citation Sayama, T., Ozawa, G., Kawakami, T., Nabesaka, S. and Fukami, K., 2012. Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin. Hydrological Sciences Journal, 57 (2), 298–312.     

Parameter Uncertainty Propagation in a Rainfall–Runoff Model; Case Study: Karoon-III River Basin

Conceptual hydrological models are popular tools for simulating land phase of hydrological cycle. Uncertainty arises from a variety of sources such as input error, calibration and parameters. Hydrologic modeling researches indicate that parametric uncertainty has been considered as one of the most important source. The objective of this study was to evaluate parameter uncertainty and its propagation in rainfall-runoff modeling. This study tried to model daily flows and calculate uncertainty bounds for Karoon-III basin, Southwest of Iran, using HEC-HMS (SMA). The parameters were represented by probability distribution functions (PDF), and the effect on simulated runoff was investigated using Latin Hypercube Sampling (LHS) on Monte Carlo (MC). Three chosen parameters, based on sensitivity analysis, were saturated-hydraulic-conductivity (Ks), Clark storage coefficient (R) and time of concentration (t _c ). Uncertainty associated with parameters were accounted for, by representing each with a probability distribution. Uncertainty bounds was calculated, using parameter sets captured from LHS on parameters PDF of sub-basins and propagating to the model. Results showed that maximum reliability (11%) resulted from Ks propagating. For three parameters, underestimation was more than overestimation. Maximum sharpness and standard deviation (STD) was resulted from propagating Ks. Cumulative Distribution Function (CDF) of flow and uncertainty bounds showed that as flow increased, the width of uncertainty bounds increased for all parameters.     

Rainfall–interception–evaporation–runoff relationships in a semi-arid catchment,northern Limpopo basin,Zimbabwe

Abstract

Two types of monthly water balance models at basin scale are used: PE models use precipitation and potential evapotranspiration (PET) as their observed input data, whereas P models need only precipitation. Calibration proceeds by comparing model runoff and observed runoff. Calibration is entirely automatic with the exclusion of subjective elements. All models differ only by their actual evapotranspiration equations. PE models from previous papers are generalized essentially by replacing the constant evapotranspiration parameter by a periodic one, thus increasing the number of parameters by two (a “parameter” is an unknown constant to be estimated, and which is a characteristic of the river basin to be described). P models use a periodic “driving force”, which is intended to represent periodicity of hydrological phenomena, normally originating in the (unavailable) PET time series. These eight PE models and three P models are then applied to 55 river basins in 10 countries with widely diverging climates and soil conditions. A marked improvement of model performance in about one third of the basins is due to the introduction of the above mentioned periodic functions. Even when PET data are available it is sometimes useful to consider P models. P models scarcely perform less well than PE models. An engineer, wanting to try out as few models as possible on a given river basin, can restrict his attention to the optimization of two or three models. The paper is an extension of a long effort towards monthly water balance models, and is believed to give a solution in most circumstances.     

Rainfall and streamflow response to El Niño Southern Oscillation: a case study in a semiarid catchment,Australia

Abstract

This paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0–3 month lead time, compared to rainfall distribution.     

Rainfall–runoff,flood inundation and sensitivity analysis of the 2014 Pakistan flood in the Jhelum and Chenab river basin

ABSTRACT

The major flood of 2014 in the two eastern, transboundary rivers, the Jhelum and Chenab in Punjab, Pakistan, was simulated using the two-dimensional rainfall–runoff model. The simulated hydrograph showed good agreement with the observed discharge at the model outlet and intervening barrages, with a Nash-Sutcliffe efficiency of 0.86 at the basin outlet. Further, simulated flood inundation extent showed good agreement with the MODIS imagery with a fit (%) of 0.87. For some affected areas that experienced short-duration flooding, local housing damage data confirmed the simulated results. Besides the rainfall–runoff and flood inundation modelling, parameter sensitivity analysis was undertaken to identify the influence of various river and floodplain parameters. The analysis showed that the river channel geometric parameters and the roughness coefficients exerted the primary influence over flood extent and peak flow.     

A Method for Direct Assessment of the “Non Rainfall” Atmospheric Water Cycle: Input and Evaporation From the Soil

“Non rainfall” atmospheric water (dew, fog, vapour adsorption) supplies a small amount of water to the soil surface that may be important for arid soil micro-hydrology and ecology. Research into the direct effects of this water on soil is, however, lacking due to instrument and technical constraints. We report on the design, development, construction and findings of an automated microlysimeter instrument to directly measure this soil water cycle in Stellenbosch, South Africa during winter. Performance of the microlysimeter was satisfactory and results obtained were compared to literature and fell within the expected range. “Non rainfall” atmospheric water input into bare soil (river sand) was between 0.88 and 1.10?mm per night while evaporation was between 1.39 and 2.71?mm per day. The study also attempted to differentiate the composition of “non rainfall” atmospheric water and results showed that vapour adsorption contributed the bulk of this input.