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.     

Investigation of Lushan earthquake ionosphere VTEC anomalies based on GPS data

Vertical total electron content （VTEC） time series were obtained from 22 GPS stations near the epicenter of the Lushan earthquake. In this paper, we have adopted a sliding average method to detect and analyze anomalous VTEC associated with the earthquake. The results show that signif- icant, negative ionosphere VTEC anomalies appeared over the 5 days before the earthquake, and on the day when earthquake occurred. The maximum value of VTEC anoma- lies that exceeded the lower bound reached 20 TECU. The spatial distribution of VTEC anomalies showed a conjugate structure, which shifted to the magnetic equator, and subse- quently moved westwards.     

Modelling stream flow for use in ecological studies in a large,arid zone river,central Australia

Australian arid zone ephemeral rivers are typically unregulated and maintain a high level of biodiversity and ecological health. Understanding the ecosystem functions of these rivers requires an understanding of their hydrology. These rivers are typified by highly variable hydrological regimes and a paucity, often a complete absence, of hydrological data to describe these flow regimes. A daily time‐step, grid‐based, conceptual rainfall–runoff model was developed for the previously uninstrumented Neales River in the arid zone of northern South Australia. Hourly, logged stage data provided a record of stream‐flow events in the river system. In conjunction with opportunistic gaugings of stream‐flow events, these data were used in the calibration of the model. The poorly constrained spatial variability of rainfall distribution and catchment characteristics (e.g. storage depths) limited the accuracy of the model in replicating the absolute magnitudes and volumes of stream‐flow events. In particular, small but ecologically important flow events were poorly modelled. Model performance was improved by the application of catchment‐wide processes replicating quick runoff from high intensity rainfall and improving the area inundated versus discharge relationship in the channel sections of the model. Representing areas of high and low soil moisture storage depths in the hillslope areas of the catchment also improved the model performance. The need for some explicit representation of the spatial variability of catchment characteristics (e.g. channel/floodplain, low storage hillslope and high storage hillslope) to effectively model the range of stream‐flow events makes the development of relatively complex rainfall–runoff models necessary for multisite ecological studies in large, ungauged arid zone catchments. Grid‐based conceptual models provide a good balance between providing the capacity to easily define land types with differing rainfall–runoff responses, flexibility in defining data output points and a parsimonious water‐balance–routing model. Copyright © 2004 John Wiley & Sons, Ltd.     

Sensitivity of the Weather Research and Forecasting (WRF) model to downscaling ratios and storm types in rainfall simulation

Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd.     

Use of the Connectivity of Runoff Model (CRUM) to investigate the influence of storm characteristics on runoff generation and connectivity in semi‐arid areas

Much attention has been given to the surface controls on the generation and transmission of runoff in semi‐arid areas. However, the surface controls form only one part of the system; hence, it is important to consider the effect that the characteristics of the storm event have on the generation of runoff and the transmission of flow across the slope. The impact of storm characteristics has been investigated using the Connectivity of Runoff Model (CRUM). This is a distributed, dynamic hydrology model that considers the hydrological processes relevant to semi‐arid environments at the temporal scale of a single storm event. The key storm characteristics that have been investigated are the storm duration, rainfall intensity, rainfall variability and temporal structure. This has been achieved through the use of a series of defined storm hydrographs and stochastic rainfall. Results show that the temporal fragmentation of high‐intensity rainfall is important for determining the travel distances of overland flow and, hence, the amount of runoff that leaves the slope as discharge. If the high‐intensity rainfall is fragmented, then the runoff infiltrates a short distance downslope. Longer periods of high‐intensity rainfall allow the runoff to travel further and, hence, become discharge. Therefore, storms with similar amounts of high‐intensity rainfall can produce very different amounts of discharge depending on the storm characteristics. The response of the hydrological system to changes in the rainfall characteristics can be explained using a four‐stage model of the runoff generation process. These stages are: (1) all water infiltrating, (2) the surface depression store filling or emptying without runoff occurring, (3) the generation and transmission of runoff and (4) the transmission of runoff without new runoff being generated. The storm event will move the system between the four stages and the nature of the rainfall required to move between the stages is determined by the surface characteristics. This research shows the importance of the variable‐intensity rainfall when modelling semi‐arid runoff generation. The amount of discharge may be greater or less than the amount that would have been produced if constant rainfall intensity is used in the model. Copyright © 2006 John Wiley & Sons, Ltd.     

Hedgerow impacts on soil-water transfer due to rainfall interception and root-water uptake

Hedgerow is one of the most important rural landscapes in the world, especially in Europe. Knowledge about the hydrological role of hedgerows is useful in many fields of study, such as hydrological modelling and rural landscape management. The aim of this study was to investigate the impact of a hedgerow on rainfall distribution, soil-water potential gradient, lateral water transfer and water balance. A hillslope with a hedgerow perpendicular to the slope was monitored. To evaluate hedgerow rainfall interception, rainfall was measured (hourly, daily, and by rainfall event) both next to and up to 16 m upslope and 12 m downslope perpendicularly away from the hedgerow. The strongest correlation between rainfall next to the hedgerow and rainfall at more distant points was obtained using data measured per rainfall event. The average percentage of rainfall intercepted equalled 28% for the leafed period and 12% for the leafless period. The impact of the hedgerow on spatial rainfall distribution was related to distance from the hedgerow and rainfall amount. Annual distribution of soil-water potential showed that the hedgerow influenced it up to 9 m upslope and 6 m downslope, the area in which most of the hedgerow's roots were observed. The soil was driest at the end of summer, which delayed soil rewetting during autumn in areas surrounding the hedgerow. Annual groundwater dynamics exhibited three distinct periods due to temporal rainfall distribution and, especially at the end of summer, root-water uptake. In addition, the total potential gradient showed that unsaturated flow was directed towards the hedgerow in summer and autumn. These results indicate that at the local scale hedgerows influences (1) spatial rainfall distribution, (2) soil rewetting, and (3) groundwater recharge, often at distances well beyond the hedgerow's drip line. Consequently, the processes involved in soil-water dynamics around hedgerows should be integrated into relevant hydrological models, especially for catchments with a dense hedgerow network. Copyright © 2008 John Wiley & Sons, Ltd.     

A numerical procedure for predicting rainfall‐induced movements of active landslides along pre‐existing slip surfaces

A numerical model to predict landslide movements along pre‐existing slip surfaces from rainfall data is presented. The model comprises: a transient seepage finite‐element analysis to compute the variations of pore water pressures due to rainfall; a limit equilibrium stability analysis to compute the factors of safety along the slip surface associated with transient pore pressure conditions; an empirical relationship between the factor of safety and the rate of displacement of the slide along the slip surface; an optimization algorithm for the calibration of analyses and relationships based on available monitoring data. The model is validated with reference to a well‐monitored active slide in central Italy, characterized by very slow movements occurring within a narrow band of weathered bedrock overlaid by a clayey silt colluvial cover. The model is conveniently divided and presented in two parts: a groundwater model and a kinematic model. In the first part, monthly recorded rainfall data are used as time‐dependent flow boundary conditions of the transient seepage analysis, while piezometric levels are used to calibrate the analysis by minimizing the errors between monitoring data and computed pore pressures. In the second part, measured inclinometric movements are used to calibrate the empirical relationship between the rate of displacement along the slip surface and the factor of safety, whose variation with time is computed by a time‐dependent stability analysis. Copyright © 2007 John Wiley & Sons, Ltd.     

Space–time rainfall variability in the Paute basin,Ecuadorian Andes

Despite the importance of mountain ranges as water providers, knowledge of their climate variability is still limited, mostly due to a combination of data scarcity and heterogeneous orography. The tropical Andes share many of the main features of mountain ranges in general, and are subject to several climatic influences that have an effect on rainfall variability. Although studies have addressed the large-scale variation, the basin scale has received little attention. Thus, the purpose of this study was to obtain a better understanding of rainfall variability in the tropical Andes at the basin scal, utilizing the Paute River basin of southern Ecuador as a case study. Analysis of 23 rainfall stations revealed a high spatial variability in terms of: (i) large variations of mean annual precipitation in the range 660–3400 mm; (ii) the presence of a non-monotonic relation between annual precipitation and elevation; and (iii) the existence of four, sometimes contrasting, rainfall regimes. Data from seven stations for the period 1964–1998 was used to study seasonality and trends in annual, seasonal and monthly precipitation. Seasonality is less pronounced at higher elevations, confirming that in the páramo region, the main water source for Andean basins, rainfall is well distributed year round. Additionally, during the period of record, no station has experienced extreme concentrations of annual rainfall during the wet season, which supports the concept of mountains as reliable water providers. Although no regional or basin-wide trends are found for annual precipitation, positive (negative) trends during the wet (dry) season found at four stations raises the likelihood of both water shortages and the risk of precipitation-triggered disasters. The study demonstrates how variable the precipitation patterns of the Andean mountain range are, and illustrates the need for improved monitoring. Copyright © 2007 John Wiley & Sons, Ltd.     

Modelling crop canopy and residue rainfall interception effects on soil hydrological components for semi‐arid agriculture

Crop canopies and residues have been shown to intercept a significant amount of rainfall. However, rainfall or irrigation interception by crops and residues has often been overlooked in hydrologic modelling. Crop canopy interception is controlled by canopy density and rainfall intensity and duration. Crop residue interception is a function of crop residue type, residue density and cover, and rainfall intensity and duration. We account for these controlling factors and present a model for both interception components based on Merriam's approach. The modified Merriam model and the current modelling approaches were examined and compared with two field studies and one laboratory study. The Merriam model is shown to agree well with measurements and was implemented within the Agricultural Research Service's Root Zone Water Quality Model (RZWQM). Using this enhanced version of RZWQM, three simulation studies were performed to examine the quantitative effects of rainfall interception by corn and wheat canopies and residues on soil hydrological components. Study I consisted of 10 separate hypothetical growing seasons (1991–2000) for canopy effects and 10 separate non‐growing seasons (1991–2000) for residue effects for eastern Colorado conditions. For actual management practices in a no‐till wheat–corn–fallow cropping sequence at Akron, Colorado (study II), a continuous 10‐year RZWQM simulation was performed to examine the cumulative changes on water balance components and crop growth caused by canopy and residue rainfall interception. Finally, to examine a higher precipitation environment, a hypothetical, no‐till wheat–corn–fallow rotation scenario at Corvallis, Oregon, was simulated (study III). For all studies, interception was shown to decrease infiltration, runoff, evapotranspiration from soil, deep seepage of water and chemical transport, macropore flow, leaf area index, and crop/grain yield. Because interception decreased both infiltration and soil evapotranspiration, no significant change in soil water storage was simulated. Nonetheless, these findings and the new interception models are significant new contributions for hydrologists. Published in 2006 John Wiley & Sons, Ltd.     

The relationship between rainfall inputs and flood generation in south–east Spain

Rainfall and flood data are relatively sparse in semi‐arid areas; hence there have been relatively few investigations into the relationships between rainfall inputs and flood generation in these environments. Previous work has shown that flood properties are influenced by a combination of precipitation characteristics including amount, intensity, duration and spatial distribution. Therefore floods may be produced by high intensity, short duration storms, or longer duration, low intensity rainfall. Most of this research has been undertaken in small catchments in either hyper‐arid or relatively high rainfall Mediterranean climates. This paper presents results from a 6 year data record in south‐east Spain from research conducted in two basins, the Rambla Nogalte (171 km²) and the Rambla de Torrealvilla (200 km²). Data cover an area of approximately 500 km² and an annual average rainfall of 300 mm. At coarse temporal resolutions gauges spread over large areas record similar patterns of rainfall, although spells of rain show much more complexity; pulses of rain within storms can vary considerably in total rainfall, intensity and duration over the same area. The analysis for south‐east Spain shows that most storms occur over a period of less than 24 h, but that the number of rainfall events declines as the duration exceeds 8 h. This is at odds with data on floods for the study area suggesting that they are produced by storms lasting longer than 18 h. However, one flood event was produced by a very short (15 min) storm with high intensity rainfall. Most floods tended to occur in May/June or September, which coincides with wetter months of the year (September, October, December and May). Floods are also more highly related to the total rainfall occurring in a spell of rain, than to intensity. The complexity of storm rainfall increases with the storm total, which makes it difficult to generalize on the importance of rainfall intensity for flood generation. Copyright © 2007 John Wiley & Sons, Ltd.