Incorporating rainfall intensity into daily rainfall records for simulating runoff and infiltration into soil profiles

Hydrological modelling often implies the use of rainfall data. Its quality and resolution directly affect the accuracy of the simulation results. This study illustrates that a simple approach of incorporating rainfall intensity information in daily rainfall records significantly improves the simulation of surface runoff and rainfall infiltration into soil profiles. The procedure is developed using a frequency analysis on rainfall data of the Royal Meteorological Institute of Belgium, collected with a resolution of 10 min and for a consecutive period of 61 years. The frequency analysis of the data allowed the incorporation of rainfall intensity information into daily rainfall records. To test the effect of this approach the surface runoff and water flow into three different soil types was simulated using the HYDRUS‐1D model for a typical dry, normal and wet year. The simulation results whereby the observed 10‐min rainfall data was used as input were considered as the reference. Comparative analysis revealed that the simulations using the 10 min rainfall data deducted from the incorporation of rainfall intensity into daily rainfall records, deviate a maximum 1·2% from the reference and produce much better results than the Soil Conservation Service (SCS) runoff curve‐number method because rainfall intensity is considered in the procedure presented. The SCS curve‐number method typical overestimates surface runoff during periods of low rainfall intensity (winter) and underestimate runoff during periods of high rainfall intensities (summer). Copyright © 2002 John Wiley & Sons, Ltd.     

Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils,Fowlers Gap,Australia

Small plots and a dripper rainfall simulator were used to explore the significance of the intensity fluctuations (‘event profile’) within simulated rainfall events on infiltration and runoff from bare, crusted dryland soils. Rainfall was applied at mean rain rates of 10 mm/h. Fourteen simulated rainfall events each involved more than 5000 changes of intensity and included multipeak events with a 25‐mm/h peak of intensity early in the event or late in the event and an event that included a temporary cessation of rain. These are all event profiles commonly seen in natural rain but rarely addressed in rainfall simulation. A rectangular event profile of constant intensity, as commonly used in rainfall simulation experiments, was also adopted for comparative purposes. Results demonstrate that event profile exerts an important effect on infiltration and runoff for these soils and rainfall event profiles. ‘Uniform’ events of unvarying intensity yielded the lowest total runoff, the lowest peak runoff rate and the lowest runoff ratio (0.13). These parameters increased for ‘early peak’ profiles (runoff ratio 0.24) and reached maxima for ‘late peak’ profiles (runoff ratio 0.50). Differences in runoff ratio and peak runoff rate between the ‘uniform’ event profile and those of varying intensity were all statistically significant at p ≤ 0.01. Compared with ‘uniform’ runs, the varying intensity runs yielded larger runoff ratios and peak runoff rates, exceeding those of the ‘uniform’ events by 85%–570%. These results suggest that for small‐plot studies of infiltration and erosion, the continued use of constant rainfall intensity simulations may be sacrificing important information and misrepresenting the mechanisms involved in runoff generation. The implications of these findings for the ecohydrology of the research site, an area of contour‐aligned banded vegetation in which runoff and runon are of critical importance, are highlighted. Copyright © 2011 John Wiley & Sons, Ltd.     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Temporal and spatial variability of annual and seasonal rainfall over Ethiopia

Abstract

Characterization of the seasonal and inter-annual spatial and temporal variability of rainfall in a changing climate is vital to assess climate-induced changes and suggest adequate future water resources management strategies. Trends in annual, seasonal and maximum 30-day extreme rainfall over Ethiopia are investigated using 0.5° latitude?×?0.5° longitude gridded monthly precipitation data. The spatial coherence of annual rainfall among contiguous rainfall grid points is also assessed for possible spatial similarity across the country. The correlation between temporally coinciding North Atlantic Multidecadal Oscillation (AMO) index and annual rainfall variability is examined to understand the underlying coherence. In total 381 precipitation grid points covering the whole of Ethiopia with five decades (1951–2000) of precipitation data are analysed using the Mann-Kendall test and Moran spatial autocorrelation method. Summer (July–September) seasonal and annual rainfall data exhibit significant decreasing trends in northern, northwestern and western parts of the country, whereas a few grid points in eastern areas show increasing annual rainfall trends. Most other parts of the country exhibit statistically insignificant trends. Regions with high annual and seasonal rainfall distribution exhibit high temporal and spatial correlation indices. Finally, the country is sub-divided into four zones based on annual rainfall similarity. The association of the AMO index with annual rainfall is modestly good for northern and northeastern parts of the country; however, it is weak over the southern region.

Editor Z.W. Kundzewicz; Associate editor S. Uhlenbrook

Citation Wagesho, N., Goel, N.K., and Jain, M.K. 2013. Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrological Sciences Journal, 58 (2), 354–373.     

Variation in curve numbers derived from plot runoff data for New South Wales (Australia)

The curve number method is a simple one parameter (the curve number) rainfall runoff model. While its theoretical underpinning has been questioned it remains a powerful hydrological tool in the absence of detailed data and is therefore used extensively in hydrological models. This study aims to characterize the variation in maximum retention values (S), which underlie curve numbers, for a range of agricultural treatments across a large spatial area in New South Wales (NSW), Australia. The data used for the analysis spans several decades of rainfall runoff observations. A range of different derivation methods result in variation in mean and variance of S. In particular, methods that emphasize the larger storms result in greater S and thus lower runoff. For larger spatial scales, emphasis on larger storms gives more reliable estimates of S. Systematic variation in S arises from variations in treatment, pre‐runoff soil moisture, rainfall depth, and variations in cover. On the basis of the analysis, a table of curve number values for different land uses found in NSW is presented. The resulting distributions of S and curve numbers provide guidance for rainfall runoff modelling studies in the agricultural important areas of NSW. Copyright © 2011 John Wiley & Sons, Ltd.     

Application of an artificial neural network to typhoon rainfall forecasting

A neural network with two hidden layers is developed to forecast typhoon rainfall. First, the model configuration is evaluated using eight typhoon characteristics. The forecasts for two typhoons based on only the typhoon characteristics are capable of showing the trend of rainfall when a typhoon is nearby. Furthermore, the influence of spatial rainfall information on rainfall forecasting is considered for improving the model design. A semivariogram is also applied to determine the required number of nearby rain gauges whose rainfall information will be used as input to the model. With the typhoon characteristics and the spatial rainfall information as input to the model, the forecasting model can produce reasonable forecasts. It is also found that too much spatial rainfall information cannot improve the generalization ability of the model, because the inclusion of irrelevant information adds noise to the network and undermines the performance of the network. Copyright © 2005 John Wiley & Sons, Ltd.     

Distributed rainfall‐runoff modelling for flood frequency estimation and flood forecasting

Nowadays, in the scientific literature many rainfall‐runoff (RR) models are available ranging from simpler ones, with a limited number of parameters, to highly complex ones, with many parameters. Therefore, the selection of the best structure and parameterisation for a model is not straightforward as it is dependent on a number of factors: climatic conditions, catchment characteristics, temporal and spatial resolution, model objectives, etc. In this study, the structure of a continuous semi‐distributed RR model, named MISDc (‘Modello Idrologico Semi‐Distribuito in continuo’) developed for flood simulation in the Upper Tiber River (central Italy) is presented. Most notably, the methodology employed to detect the more relevant processes involved in the modelling of high floods, and hence, to build the model structure and its parameters, is developed. For this purpose, an intense activity of monitoring soil moisture and runoff in experimental catchments was carried out allowing to derive a parsimonious and reliable continuous RR model operating at an hourly (or smaller) time scale. Specifically, in order to determine the catchment hydrological response, the important role of the antecedent wetness conditions is emphasized. The application of MISDc both for design flood estimation and for flood forecasting is reported here demonstrating its reliability and also its computational efficiency, another important factor in hydrological practice. As far as the flood forecasting applications are concerned, only the accuracy of the model in reproducing discharge hydrographs by assuming rainfall correctly known throughout the event is investigated indepth. In particular, the MISDc has been implemented in the framework of Civil Protection activities for the Upper Tiber River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Propagation of uncertainty from rainfall to runoff: A case study with a stochastic rainfall generator

We explore the impact of uncertainties in the spatial–temporal distribution of rainfall on the prediction of peak discharge in a typical mountain basin. To this end, we use a stochastic generator previously developed for rainfall downscaling, and we estimate the basin response by adopting a semi-distributed hydrological model. The results of the analysis provide information on the minimum rainfall resolution needed for operational flood forecasting, and confirm the sensitivity of peak discharge estimates to errors in the determination of the power spectrum of the precipitation field.     

Development of a portable field rainfall simulator for use in hillside vineyard runoff and erosion studies

An inexpensive, mobile field rainfall simulator and runoff plot frame were developed for use on hillside vineyards. The simulator framework and components were lightweight, readily available and easily manageable such that they can be handled by one person during transport, set–up and operation. The vineyard rainfall simulator was simpler than many of the machines in recent use for similar studies, yet offered equal or improved performance for small‐plot studies. The system developed consistent sized 2·58 mm raindrops at intensities ranging from 20 to 90 mm/h. The average distribution uniformity coefficient at an intensity of 60 mm/h was 91·7%, with a deviation of only 2·2%. This coefficient was similar to the range reported for a more complex rotating disk simulator, and was notably greater than that obtained for other similar devices. The system water capacity of 40 l allowed for 1‐h storm durations at 60 mm/h, usually sufficient time for commencement of erosion and runoff. The runoff plot frame was designed to be quickly installed, and to discourage sediment deposition in the routing of runoff to collect containers. Copyright © 2000 John Wiley & Sons, Ltd.     

Improving global rainfall forecasting with a weather type approach in Japan

An automated version of the weather type classification scheme was performed over Japan to characterize daily circulation conditions. A daily gridded field of mean sea-level pressure (MSLP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis dataset (ERA-interim) and the THORPEX Interactive Grand Global Ensemble (TIGGE) daily forecast dataset were used. The weather type is advantageous as it provides an opportunity to improve global rainfall prediction by refining statistical bias correction. We distinguished 11 weather types: anticyclone, cyclone, hybrid and eight purely wind directions. The results indicate that the main weather types contributing to the total volume of rainfall are cyclone, hybrid, purely westerly and northwest winds. A gamma-based bias correction decreases the global rainfall forecast root mean square by 10%, while specific weather type gamma bias correction accounts for 5–10% root mean square error reduction, with a total decrease of errors up to a maximum of 20%. Both global and weather type bias corrections improve the extreme dependency scores (EDS), but for different extreme rainfall thresholds. The study advocates the use of weather type bias-correction methods for extreme event rainfall intensity corrections higher than 100 mm/d.

EDITOR

A. Castellarin

ASSOCIATE EDITOR

A. Jain     

Estimation of rainfall elasticity of streamflow in Australia

Abstract

Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (? _P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ? _P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions.     

An analysis of the impact of spatial variability in rainfall on runoff and sediment predictions from a distributed model

This paper investigates the effect of introducing spatially varying rainfall fields to a hydrological model simulating runoff and erosion. Pairs of model simulations were run using either spatially uniform (i.e. spatially averaged) or spatially varying rainfall fields on a 500‐m grid. The hydrological model used was a simplified version of Thales which enabled runoff generation processes to be isolated from hillslope averaging processes. Both saturation excess and infiltration excess generation mechanisms were considered, as simplifications of actual hillslope processes. A 5‐year average recurrence interval synthetic rainfall event typical of temperate climates (Melbourne, Australia) was used. The erosion model was based on the WEPP interrill equation, modified to allow nonlinear terms relating the erosion rate to rainfall or runoff‐squared. The model results were extracted at different scales to investigate whether the effects of spatially varying rainfall were scale dependent. A series of statistical metrics were developed to assess the variability due to introducing the spatially varying rainfall field. At the catchment (approximately 150 km²) scale, it was found that particularly for saturation excess runoff, model predictions of runoff were insensitive to the spatial resolution of the rainfall data. Generally, erosion processes at smaller sub‐catchment scales, particularly when the sediment generation equation had non linearity, were more sensitive to spatial rainfall variability. Introducing runon infiltration reduced the total runoff and sediment yield at all scales, and this process was also most sensitive to the rainfall resolution. Copyright © 2011 John Wiley & Sons, Ltd.     

Laboratory examination of linearity in rainfall–runoff relationships

ABSTRACT

Certain rainfall–runoff models, e.g. the unit hydrograph, assume linear relationships between the variables. These are proportionality of runoff discharges to (net) rainfall depth and linear summations of discharges resulting from (net) rainfalls during different time intervals or over different sectors of a watershed. This study examines the validity of these assumptions by use of an extensive two-dimensional laboratory experimentation. The results indicate that proportionality would be found under high rainfall intensity through a long duration. Spatial summations would more likely yield correct discharges in cases where rainfall duration is equal to, or is longer than, the time of concentration. Temporal summations may yield correct discharges when rainfall duration is longer than one half of the time of concentration. Here, the time of concentration is determined at the beginning of gradual approach of the discharge towards the equilibrium state.     

The role of rainfall temporal and spatial averaging in seasonal simulations of the terrestrial water balance

The partitioning of rainfall into surface runoff and infiltration influences many other aspects of the hydrologic cycle including evapotranspiration, deep drainage and soil moisture. This partitioning is an instantaneous non-linear process that is strongly dependent on rainfall rate, soil moisture and soil hydraulic properties. Though all rainfall datasets involve some degree of spatial or temporal averaging, it is not understood how this averaging affects simulated partitioning and the land surface water balance across a wide range of soil and climate types. We used a one-dimensional physics-based model of the near-surface unsaturated zone to compare the effects of different rainfall discretization (5-min point-scale; hourly point-scale; hourly 0.125° gridded) on the simulated partitioning of rainfall for many locations across the United States. Coarser temporal resolution rainfall data underpredicted seasonal surface runoff for all soil types except those with very high infiltration capacities (i.e., sand, loamy sand). Soils with intermediate infiltration capacities (i.e., loam, sandy loam) were the most affected, with less than half of the expected surface runoff produced in most soil types when the gridded rainfall dataset was used as input. The impact of averaging on the water balance was less extreme but non-negligible, with the hourly point-scale predictions exhibiting median evapotranspiration, drainage and soil moisture values within 10% of those predicted using the higher resolution 5-min rainfall. Water balance impacts were greater using the gridded hourly dataset, with average underpredictions of ET up to 27% in fine-grained soils. The results suggest that “hyperresolution” modelling at continental to global scales may produce inaccurate predictions if there is not parallel effort to produce higher resolution precipitation inputs or sub-grid precipitation parameterizations.     

Evidence of large rainfall partitioning patterns by banana and impact on surface runoff generation

In this article the effect of redistribution of rainfall by banana on local water fluxes and the possible impact of these fluxes on surface runoff has been studied. First the water redistribution by a banana canopy at three development stages (vegetative, flowering, and bunch stage) was measured. The results showed a considerable stemflow, proportional to the leaf area index (LAI), which represented 18 to 26% of the incident rainfall volume according to the age of the crop. Consequently, the rainfall rate was 28‐fold higher at the plant collar for a fully developed banana canopy. For the throughfall, on average, the higher the LAI, the lower the mean throughfall. In addition, the spatial distribution of the throughfall varied according to the distance from the pseudostem. Notably, for the earlier stages, the area between the pseudostem and 0·5 m from it received weak throughfall. Secondly, simulations were carried out with a simple two‐compartment model simulating the total surface runoff volume. The simulations showed stemflow combined with the agronomical practice of furrowing has an effect on runoff compared to bare soil. A relative increase in surface runoff volume of three‐fold was encountered on a plot with a fully developed banana and a infiltration rate of 60 mm h^?1. However, the absolute increase was only a few percentage of the incident rainfall volume, although it represented large water volumes given the tropical rains. These features must be taken into account for hydrological management of such systems. Copyright © 2007 John Wiley & Sons, Ltd.     

Analysis of surface roughness in relation to soil loss and runoff at high rainfall intensities

The decay of roughness is an important factor governing surface processes such as infiltration and soil erosion. Thus the decay of surface roughness under different surface conditions was investigated and related to quantitative amounts of soil loss, runoff and sediment concentration in a laboratory experiment. Rainfall with an intensity of 128 mm/h was applied to a bare or mulched surfaces of a sandy loam soil with known surface roughness at specified time intervals. The decay of roughness as expressed by roughness ratio, in this experiment, was better predicted when related to an exponential function of the square root of cumulative kinetic energy of rainfall rather than with the cumulative rainfall. The roughness decay equations in literature did not predict breakdown under mulched surfaces accurately. Thus the exponent parameters of the roughness decay equations were adjusted to reflect the reduced decay occurring under mulched surfaces. In a bare soil, regression equations expressing the dependent variables as a function of initial roughness index were significant, but with low coefficients of determination, being 0·39 for soil loss, 0·12 for runoff and 0·36 for sediment concentration. In addition to initial roughness index, cumulative kinetic energy of rainfall was further included in the regressions. This led to an increase in coefficients of determination, which was 0·81 for soil loss, 0·74 for runoff and 0·49 for sediment concentration. The coefficients of determination (0·87 for soil loss, 0·85 for runoff and 0·51 for sediment concentration) were further increased when the final roughness index was included in addition to initial roughness index and cumulative kinetic energy in the regressions. This work shows that soil loss and runoff could be predicted from bare soil surface provided the initial roughness and the energy of rainfall is known. However, field verifications of these relationships are needed under different tillage tools and under natural rainfall. Copyright © 2002 John Wiley & Sons, Ltd.     

On the identification of ENSO-induced rainfall and runoff variability: a comparison of methods and indices

Abstract

It is known that the El Niño Southern Oscillation (ENSO) phenomenon induces marked climate variability across many parts of the world. However, in seeking useful relationships between ENSO and climate, several indices are available. In addition to the choice of index, previous studies assessing ENSO effects have employed a range of different methods to classify periods as El Niño, La Niña or Neutral. It is therefore clear that significant subjectivity exists in the adoption of ENSO classification schemes. In this study, several ENSO classification methods are applied to a range of ENSO indices. Each method-index combination is investigated to determine which provides the strongest relationship with rainfall and runoff in the Williams River catchment, New South Wales, Australia. The results demonstrate substantial differences between the methods and indices. The Multivariate ENSO Index (or MEI) is found to provide the best classification irrespective of method. The potential for forecasting ENSO-related effects on rainfall, runoff and river abstractions is then investigated. A “rise rule” to account for dynamic ENSO trends is also assessed. Strong relationships were found to exist with runoff (rainfall) up to nine (eight) months in advance of the Summer/autumn period. Implications for improved forecasting of potential river abstractions are apparent.     

Trends in rainfall and runoff in the Blue Nile Basin: 1964–2003

Most of the water from the Nile originates in Ethiopia but there is no agreement on how land degradation or climate change affects the future flow in downstream countries. The objective of this paper is to improve the understanding of future conditions by analysing historical trends. During the period 1964–2003, the average monthly basin‐wide precipitation and monthly discharge data were collected and analysed statistically for two stations in the upper 30% of the Blue Nile Basin and monthly and 10‐day discharge data of one station at the Sudan–Ethiopia border. A rainfall–runoff model examined the causes for observed trends. The results show that, while there was no significant trend in the seasonal and annual basin‐wide average rainfall, significant increases in discharge during the long rainy season (June to September) were observed at all three stations. In the upper Blue Nile, the short rainy season flow (March to May) increased, while the dry season flow (October to February) stayed the same. At the Sudan border, the dry season flow decreased significantly with no change in the short rainy season flow. The difference in response was likely due to the construction of weir in the 1990s at the Lake Tana outlet that affected the upper Blue Nile discharge significantly but affected less than 10% of the discharge at the Sudan border. The rainfall–runoff model reproduced the observed trends, assuming that an additional 10% of the hillsides were eroded in the 40‐year time span and generated overland flow instead of interflow and base flow. Models concerning future trends in the Nile cannot assume that the landscape runoff processes will remain static. Copyright © 2010 John Wiley & Sons, Ltd.     

The effect of estimating areal rainfall using self‐similarity topography method on the simulation accuracy of runoff prediction

Rainfall input for hydrologic modelling is assumed uniformly distributed over the entire catchment. This can lead to significant errors. Investigations of areal rainfall in mountain areas are typically limited by a lack of adequate meteorological and hydrogeological records. This study focuses on areal rainfall in mountain areas within the Kaidu River Basin, China, with the aim of analyzing the influence of areal rainfall on the simulation accuracy of runoff prediction. We conducted a simulation using MIKE 11/NAM rainfall‐runoff model over 92 days of the rain season and compared the simulation error in different methods. On the basis of properties of self‐similarity degree (SSD) in analyzing the detailed characteristics of terrain, areal rainfall was calculated to model the runoff. The results of the model simulations are generally consistent with observed data, indicating that the self‐similarity topography method is able to reflect the spatial change of rainfall. This indicates that the proposed methodology is applicable for the management of water resources in mountain area. The modelling and self‐similarity topography method study allowed quantification of the spatial rainfall and provided an insight into their implications in hydrological forecasting. Copyright © 2011 John Wiley & Sons, Ltd.