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.     

Using a rainfall stochastic generator to detect trends in extreme rainfall

An original approach is proposed to estimate the impacts of climate change on extreme events using an hourly rainfall stochastic generator. The considered generator relies on three parameters. These parameters are estimated by average, not by extreme, values of daily climatic characteristics. Since climate changes should result in parameters instability in time, the paper focuses on testing the presence of linear trends in the generator parameters. Maximum likelihood tests are used under a Poisson–Pareto-Peak-Over-Threshold model. A general regionalization procedure is also proposed which offers the possibility to work on both local and regional scales. From the daily information of 139 rain gauge stations between 1960 and 2003, changes in heavy precipitations in France and their impacts on quantile predictions are investigated. It appears that significant changes occur mainly between December and May for the rainfall occurrence which increased during the four last decades, except in the Mediterranean area. Using the trend estimates, one can deduced that these changes, up to now, do not affect quantile estimations.     

Constructing rainfall depth-frequency curves considering a linear trend in rainfall observations

Comprehensive flood prevention plans are established in large basins to cope with recent abnormal floods in South Korea. In order to make economically effective plans, appropriate design rainfalls are critically determined from the rainfall depth-frequency curves which take the occurrence of abnormal floods into consideration. Conventional approaches to construct the rainfall depth-frequency curves are based on the stationarity assumption. However, this assumption has a critical weak aspect in that it cannot reflect non-stationarities in rainfall observations. As an alternative, this study suggests the non-stationary Gumbel model (NSGM) which incorporates a linear trend of rainfall observations into rainfall frequency analysis to construct the rainfall depth-frequency curves. A comparison of various schemes employed in the model found that the proposed NSGM permits the estimation of the distribution parameters even when shifted in the future by using linear relationships between rainfall statistics and distribution parameters, and produces more acceptable estimates of design rainfalls in the future than the conventional model. The NSGM was applied at several stations in South Korea and then expected the design rainfalls to increase by up to 15–30% in 2050.     

Volcanism on Io: the view from Galileo

Io, Jupiter's innermost Galilean satellite, is the most volcanically active body in the solar system. Ashley Gerard Davies reviews the wealth of data returned by NASA's veteran spacecraft Galileo, that has led to a better understanding of the volcanic processes wracking Io.
Jupiter's moon Io is the only other body in the solar system known to have active, high-temperature volcanism like that found on Earth. The Galileo spacecraft has been observing Io regularly since June 1996, and the data that it has returned have led to many new insights into the volcanic processes that have shaped not only Io, but Earth in its distant past.     

Using data-derived perturbations to incorporate uncertainty in generating stochastic areal rainfall from point rainfall

Abstract

Raingauge measurements are commonly used to estimate daily areal rainfall for catchment modelling. The variation of rainfall between the gauges is usually inadequately captured and areal rainfall estimates are therefore very uncertain. A method of quantifying these uncertainties and incorporating them into ensembles of areal rainfall is demonstrated and tested. The uncertainties are imposed as perturbations based on the differences in areal rainfall that result when half of the raingauges are alternately omitted. Also included is a method of: (a) estimating the proportion rainfall that falls on areas where no gauges are located that are consequently computed as having zero rain, and (b) replacing them with plausible non-zero rainfalls. The model is tested using daily rainfall from two South African catchments and is found to exhibit the expected behaviour. One of the two parameters of the model is obtained from the rainfall data, while the other has direct physical interpretation.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Ndiritu, J., 2013. Using data-derived perturbations to incorporate uncertainty in generating stochastic areal rainfall from point rainfall. Hydrological Sciences Journal, 58 (8), 1704–1717.     

Interception losses of rainfall from Cashew trees

The rainfall interception losses from Cashew trees were quantified, based on the records of 105 selected storms within the range 25.0 mm, occurring in a humid tropical region at Kottamparamba, India.

The storage capacity of the Cashew trees was worked out as 0.8 mm and the throughfall coefficient as 0.391. The trees under observation were 15–20 years of age with a leaf area index of 1.0–1.25.

About 31% of the storm rainfall for storms 25.0 mm was intercepted by the Cashew trees and lost to the atmosphere.

The measured interception losses from the trees were compared with the estimated interception losses using the analytical model of Gash (1979). The predicted interception losses from the Cashew trees were within ± 10% for storms with total rainfall 10.0 mm and within ± 22% for storms with a rainfall of 10.1–25.0 mm.     

Automated rainfall simulator for variable rainfall on urban green areas

Rainfall simulators can enhance our understanding of the hydrologic processes affecting the total runoff to urban drainage systems. This knowledge can be used to improve urban drainage designs. In this study, a rainfall simulator is developed to simulate rainfall on urban green surfaces. The rainfall simulator is controlled by a microcomputer programmed to replicate the temporal variations in rainfall intensity of both historical and synthetic rainfall events with constant rainfall intensity on an area of 1 m². The performance of the rainfall simulator is tested under laboratory conditions with regard to spatial uniformity of the rainfall, the kinetic energy of the raindrops, and the ability to replicate historical and synthetic rainfall events with temporally varying intensity. The rainfall simulator is applied in the field to evaluate its functionality under field conditions and the influence of wind on simulated rainfall. Finally, a field study is carried out on the relationship between runoff, soil volumetric water content, and surface slope. Performance and field tests show that the simulated rainfall has a uniform spatial distribution, whereas the kinetic energy of the raindrops is slightly higher than that of other comparable rainfall simulators. The rainfall simulator performs best in low wind speed conditions. The simulator performs well in replicating historical and synthetic rainfall events by matching both intensity variations and accumulated rainfall depth. The field study shows good correlation between rainfall, runoff, infiltration, soil water content, and surface slope.     

Spatial rainfall model using a pattern classifier for estimating missing daily rainfall data

Missing data in daily rainfall records are very common in water engineering practice. However, they must be replaced by proper estimates to be reliably used in hydrologic models. Presented herein is an effort to develop a new spatial daily rainfall model that is specifically intended to fill in gaps in a daily rainfall dataset. The proposed model is different from a convectional daily rainfall generation scheme in that it takes advantage of concurrent measurements at the nearby sites to increase the accuracy of estimation. The model is based on a two-step approach to handle the occurrence and the amount of daily rainfalls separately. This study tested four neural network classifiers for a rainfall occurrence processor, and two regression techniques for a rainfall amount processor. The test results revealed that a probabilistic neural network approach is preferred for determining the occurrence of daily rainfalls, and a stepwise regression with a log-transformation is recommended for estimating daily rainfall amounts.     

On predicting upland erosion losses from rainfall depth

Point rainfall triggers the complex processes of overland flow and surface erosion. The probability density functions of rainfall duration and intensity are coupled with a physically based dynamic formulation of rainfall-runoff-sediment transport relationships for upland areas. When considering a single storm, rainfall depth alone is a poor predictor of sediment transport because of the dispersion introduced by the effect of rainfall intensity. On a long terms basis, however, the total amount of rainfall can be used to predict total erosion losses.     

Modelling forest transpiration from different perspectives

Forest transpiration models have been developed in different disciplines such as plant physiology, ecology, meteorology, hydrology and soil science. In the present study, three different types of model perspectives for transpiration control are used: leaf cooling, CO₂ assimilation and the combined energy and water balance. All three process‐orientated models are calibrated on measurements in a Douglas fir stand in the Netherlands. The performances of these models are equally good, although they have different complexities, different numbers of calibration parameters (ranging from 1 to 6) and the models are calibrated on different measurements (eddy correlation at canopy level or CO₂ measurements at leaf level). The resemblance of the model results is caused by the calibration procedure and by the high impact of radiation in all three cases. Significant discrepancies become apparent when differences between model responses are examined and when specific (short) periods are selected when input variables are uncoupled. The main differences between the models are caused by another formulation of leaf area index and vapour pressure deficit (VPD). Considerable differences in simulated transpiration occur in the afternoon as a result of the diurnal hysteresis between VPD and radiation. Copyright © 2000 John Wiley & Sons, Ltd.     

V: Daily catchment rainfall estimated from meteosat

Meteosat data for 1986 to 1988 have been used to estimate the daily rainfall over catchments of tributaries of the river Senegal in Mail and Guinea. The technique uses the methodology of the TAMSAT group of the University of Reading, which involves the selection of an appropriate cloud top temperature threshold to determine whether the cloud is producing rain and the rainfall is estimated from the period during which storm clouds remain over a site. After calibration against all available raingauges in the catchments, the daily rainfall estimates derived by this technique were used as inputs to rainfall-runoff models. The results indicate that the streamflow models, which had themselves been calibrated using raingauge data, performed as well or better when the satellite derived estimates were used as inputs than when gauge data were used. An economical, automated operational system is described.     

Relating hydrograph components to rainfall and streamflow: a case study from northern Taiwan

Abstract

This study investigates the characteristics of hydrograph components from a watershed in Taiwan. Hydrograph components were modelled by using a model of three serial reservoirs with one parallel reservoir. Mean rainfall was calculated by using the block kriging method. The model parameters for 38 events were calibrated by using the shuffled complex evolution optimization algorithm. The model verification was made using 18 events. Based on the study results, the following findings were obtained: (1) for single-peak events, times to peak of hydrograph components are an increasing power function of the peak time of rainfall; (2) peak discharges of hydrograph components are linearly proportional to that of total runoff, and the ratios of quick and slow runoff are approximately 83% and 17% of total runoff, respectively; and (3) the total volume of quick runoff component is 52% of total runoff and that of slow runoff is 27%.

Editor D. Koutsoyiannis

Citation Li, Y.-J., Cheng, S.-J. Pao, T.-L. and Bi, Y.-J., 2012. Relating hydrograph components to rainfall and streamflow: a case study from northern Taiwan. Hydrological Sciences Journal, 57 (5), 861–877.     

Crusting effects on erosion processes under simulated rainfall on a tropical Alfisol

Sealing and crusting of soil surfaces have dramatic effects on water infiltration into and runoff from soils, thereby greatly influencing erosion processes. This study focused on the effect of the initial stage of crusting on inter-rill erosion processes for a crust-prone Alfisol sampled from south-central India. Soil aggregates ranging from 2·4 to 8 mm collected from ploughed (PL) and naturally vegetated (NV) treatments were subjected to rainfall simulation under laboratory conditions. Runoff from PL soil aggregates was 2–2·5 times higher, while percolation was 20–100% lower, than for NV aggregates. Soil wash and splash losses were 0·5–3 times greater for PL than for NV soil. Runoff and inter-rill erosion were significantly higher during the wet simulation run compared with the dry run. The results indicated that NV soil aggregates were more resistant to breakdown from raindrop impact and slaking, and subject to less rapid sealing, than PL soil. Total soil loss was influenced most by initial aggregate stability and the extent of seal development. Splash and wash losses of soil both increased as a result of surface sealing regardless of soil condition for short (30–60 min) rainfall durations. High drying rates resulted in the highest crust bulk densities. Increased crust strength for PL soil compared with NV soil reflected the greater susceptibility of cultivated soil to surface sealing and crusting. © 1998 John Wiley & Sons, Ltd.     

雨量计加热装置研制

雨量计是地震监测中的辅助仪器,用于测量大气降水量。北方冬季严寒,固态降水不能被及时有效记录,且在融化过程中可能会凝结在雨量计传感器中,造成传感器不能记录甚至被冻坏。为此设计一种加热装置,通过加装智能识别、桶内加热器、延时等装置,对现有非融雪式雨量计进行改造,将固态降水有效转化为液态降水,从而得到降水量的真实记录。     

走出浑沌开创地震预报事业的新局面

本文针对当前地震预报中可能存在的浑沌问题,提出了走出浑沌所应采取的预报战略和战术建议。     

Spatial variability of rainfall on a sub‐kilometre scale

The variability of rainfall in space and time is an essential driver of many processes in nature but little is known about its extent on the sub‐kilometre scale, despite many agricultural and environmental experiments on this scale. A network of 13 tipping‐bucket rain gauges was operated on a 1·4 km² test site in southern Germany for four years to quantify spatial trends in rainfall depth, intensity, erosivity, and predicted runoff. The random measuring error ranged from 10% to 0·1% in case of 1 mm and 100 mm rainfall, respectively. The wind effects could be well described by the mean slope of the horizon at the stations. Except for one station, which was excluded from further analysis, the relative differences due to wind were in maximum ±5%. Gradients in rainfall depth representing the 1‐km² scale derived by linear regressions were much larger and ranged from 1·0 to 15·7 mm km^?1 with a mean of 4·2 mm km^?1 (median 3·3 mm km^?1). They mainly developed during short bursts of rain and thus gradients were even larger for rain intensities and caused a variation in rain erosivity of up to 255% for an individual event. The trends did not have a single primary direction and thus level out on the long term, but for short‐time periods or for single events the assumption of spatially uniform rainfall is invalid on the sub‐kilometre scale. The strength of the spatial trend increased with rain intensity. This has important implications for any hydrological or geomorphologic process sensitive to maximum rain intensities, especially when focusing on large, rare events. These sub‐kilometre scale differences are hence highly relevant for environmental processes acting on short‐time scales like flooding or erosion. They should be considered during establishing, validating and application of any event‐based runoff or erosion model. Copyright © 2009 John Wiley & Sons, Ltd.     

Vegetation response to rainfall intermittency in drylands: Results from a simple ecohydrological box model

Vegetation in arid and semi-arid regions is affected by intermittent water availability. We discuss a simple stochastic model describing the coupled dynamics of soil moisture and vegetation, and study the effects of rainfall intermittency. Soil moisture dynamics is described by a ecohydrological box model, while vegetation is represented by site occupancy dynamics in a spatially-implicit model. We show that temporal rainfall intermittency allows for vegetation persistence at low values of annual rainfall volume, whereas it would go extinct if rainfall were constant. Rainfall intermittency also generates long-term fluctuations in vegetation cover, even in the absence of significant inter-annual variations in the statistical properties of precipitation.