Probabilistic rainfall thresholds for flood forecasting: evaluating different methodologies for modelling rainfall spatial correlation (or dependence)

Rainfall threshold (RT) method is one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the threshold rainfall curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall impacts the flood peak discharge and the time to peak. To revisit a previous study conducted by the authors, in which spatially independent rainfall pattern was assumed, the spatial distribution of rainfall was simulated following a Monte Carlo approach. The structure of the spatial dependence among sub‐watersheds' rainfalls was taken into account under three different scenarios, namely independent, bivariate copula (2copula) and multivariate Gaussian copula (MGC). For each set of generated random dimensionless rainfalls, the probabilistic RT curves were derived for dry moisture condition. Results were evaluated with both historical and simulated events. For the simulated events, threshold curves were assessed by means of categorical statistics, such as hit rate, false rate and critical success index (CSI). Results revealed that the best performance based on the CSI criterion corresponded to 50% curve in 2copula and MGC scenarios as well as 90% curve in the independent scenario. The recognition of 50% curve in 2copula and MGC scenarios is in agreement with our expectations that the mean probable curve should have the best performance. Moreover, the proposed inclusion of spatially dependent rainfall scenario improved the performance of RT curves by about 25% in comparison with the presumed spatially uniform rainfall scenario. Copyright © 2011 John Wiley & Sons, Ltd.     

近50a淮河流域汛期降水日数和强度的分布与变化特征

选用1961-2010年淮河流域145个地面气象站的观测资料,分析淮河流域汛期(5-9月)降水的时空变化规律.结果表明:淮河流域汛期降水的空间分布不仅受到地理位置和地形的影响,而且与湿度和风速的空间分布具有较好的相关性;在时间变化上,雨日出现频率有下降的趋势,但暴雨日比重和暴雨日平均降水量均有升高的趋势.淮河流域汛期暴雨日出现频率以及各类型雨日的平均降水量均有上升的趋势,强降水时空变化呈现局地性和频发性.     

Flood simulation using the gauge‐adjusted radar rainfall and physics‐based distributed hydrologic model

This paper reports the results of an investigation into flood simulation by areal rainfall estimated from the combination of gauged and radar rainfalls and a rainfall–runoff model on the Anseong‐cheon basin in the southern part of Korea. The spatial and temporal characteristics and behaviour of rainfall are analysed using various approaches combining radar and rain gauges: (1) using kriging of the rain gauge alone; (2) using radar data alone; (3) using mean field bias (MFB) of both radar and rain gauges; and (4) using conditional merging technique (CM) of both radar and rain gauges. To evaluate these methods, statistics and hyetograph for rain gauges and radar rainfalls were compared using hourly radar rainfall data from the Imjin‐river, Gangwha, rainfall radar site, Korea. Then, in order to evaluate the performance of flood estimates using different rainfall estimation methods, rainfall–runoff simulation was conducted using the physics‐based distributed hydrologic model, Vflo^?. The flood runoff hydrograph was used to compare the calculated hydrographs with the observed one. Results show that the rainfall field estimated by CM methods improved flood estimates, because it optimally combines rainfall fields representing actual spatial and temporal characteristics of rainfall. Copyright © 2008 John Wiley & Sons, Ltd.     

Influence of rainfall and soil properties spatial aggregation on extreme flash flood response modelling: An evaluation based on the Sesia river basin,North Western Italy

High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flood and flash flood simulations to spatial aggregation of rainfall and soil properties at catchment scales ranging from 75 to 983 km². Hydrologic modeling is based on a Hortonian infiltration model and a network-based representation of hillslope and channel flow. The investigation focuses on three extreme flood and flash flood events occurred on the Sesia river basin, North Western Italy, which are analysed by using four aggregation lengths ranging from 1 to 16 km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space–time rainfall. The effects of reduced and distorted rainfall spatial variability on peak discharge have been found particularly severe for the flash flood events, with peak errors up to 35% for rainfall aggregation of 16 km and at 983 km² catchment size. Effects are particularly remarkable when significant structured rainfall variability combines with relatively important infiltration volumes due to dry initial conditions, as this emphasises the non-linear character of the rainfall–runoff relationship. In general, these results confirm that the correct estimate of rainfall volume is not enough for the accurate reproduction of flash flood events characterised by large and structured rainfall spatial variability, even at catchment scales around 250 km². However, accurate rainfall volume estimation may suffice for less spatially variable flood events. Increasing the soil properties aggregation length exerts similar effects on peak discharge errors as increasing the rainfall aggregation length, for the cases considered here and after rescaling to preserve the rainfall volume. Moreover, peak discharge errors are roughly proportional to runoff volume errors, which indicates that the shape of the flood wave is influenced in a limited way by modifying the detail of the soil property spatial representation. Conversely, rainfall aggregation may exert a pronounced influence on the discharge peak by reshaping the spatial organisation of the runoff volumes and without a comparable impact on the runoff volumes.     

GIS-supported modelling of areal rainfall in a mountainous river basin with monsoon climate in southern India

Abstract

Spatial rainfall patterns and seasonal variability were assessed for a mountainous river basin with monsoon climate. Factors were identified that could explain this variability, and a GIS-supported method to determine the areal distribution of precipitation was developed. To find acceptable regression equations, a division had to be made between rainfall stations dominated by the southwest-monsoons and the northeast-monsoons, respectively. Distance to the southwestern border was the main explaining factor for precipitation at southwest-monsoon dominated stations. For northeast-monsoon dominated stations, altitude and slope were the most important factors. The basin was divided into pixels with characteristics typical for northeast- or southwest-monsoon dominated rainfall stations to allow calculation of spatial rainfall. The difference when comparing regression-based estimates with Thiessen-based estimates was small when considering the annual estimates for the whole basin. However, when analysing seasonal rainfall or sub-catchments, the differences between Thiessen-based and regression-based estimates were significant.     

Hydrometeorological controls and erosive response of an extreme alpine debris flow

On 29 August, 2003, an intense convective storm system affected the Fella River basin, in the eastern Italian Alps, producing rainfall peaks of approximately 390 mm in 12 h. The storm triggered an unusually large debris flow in the ungauged Rio Cucco basin (0·65 km²), with a volume of approximately 78 000 m³. The analysis of the time evolution of the rainstorm over the basin has been based on rainfall estimates from radar observations and data recorded by a raingauge network. Detailed geomorphological field surveys, carried out both before and after the flood of August 2003, and the application of a distributed hydrological model have enabled assessment of flood response, estimation of erosion volumes and sediment supply to the channel network. The accounts of two eyewitnesses have provided useful elements for reconstructing the time evolution and the flow processes involved in the event. Liquid peak discharge estimates cluster around 20 m³ s^?1 km^?2, placing this event on the flood envelope curve for the eastern Italian Alps. The hydrological analysis has shown that the major controls of the flood response were the exceptional cumulated rainfall amount, required to exceed the large initial losses, and the large rainfall intensities at hourly temporal scales, required to generate high flood response at the considered basin scale. Observations on the deposits accumulated on the alluvial fan indicate that, although the dominant flow process was a debris flow, sheetflood also contributed to fan aggradation and fluvial reworking had an important role in winnowing debris‐flow lobes and redistributing sediment on the fan surface. This points out to the large discharge values during the recession phase of the flood, implying an important role for subsurface flow on runoff generation of this extreme flash flood event. Copyright © 2009 John Wiley & Sons, Ltd.     

Changes in flood regime by use of the modified curve number method

Abstract

This paper describes the use of a simple two stage rainfall-runoff model in which a curve number (CN) principle is used to calculate the soil water content and, subsequently, the rainfall contribution to direct runoff and groundwater flow. The maximum soil water retention, S, is used to express various characteristics of a catchment (infiltration rate, soil cover and land use, as in the CN method) relevant to flood formation. Using historical flood events, the model is calibrated, and the statistical distribution parameters of peak flows determined. With the same historical input data scenarios (rainfall), sets of flood hydrographs are simulated for various values of the parameter S, and corresponding distribution parameters of peak flows are determined. This procedure is used to demonstrate possible changes in flood regime to be expected due to changes of the catchment soil properties and its vegetation cover. A case study is presented for the River Hron catchment, area 582 km², in the mountainous region of central Slovakia.     

1993年太湖流域的洪涝灾害及水利工程的作用

1993年汛期太湖最高水位高居建国以来的第3位,仅次于1991年和1954年,达到4.51m(平均水位,下同),局部地区发生了洪涝灾害。本文对1993年太湖流域汛期的雨情和水情做了论述,并对1993、1991、1954年三个典型大水年的降雨和洪水特征作了比较。同时,还对洪涝灾害和水利工程的作用进行分析。太湖流域的雨季一般为5—7月,但是1993年汛期的降雨在时间上的分布有些异常。降雨集中在8月,而河道最高水位则出现在8月下旬。降雨的空间分布有以下3个特征:(1)上游地区的降雨集中在浙西山区;(2)太湖湖区的降雨量很大;(3)下游地区的降雨集中在淀泖和杭嘉湖地区。淀泖和杭嘉湖地区一些水位站的实测河道水位,比发生大洪水的1991年还要高。发生洪涝灾害的原因可归纳为,上游地区洪水来量大,当地的降雨强度高,以及下游河道排水不畅通。为了改进防汛调度和完善治理规划,需要对不同典型洪水年份的降雨和洪水模式做进一步研究。     

Modelling impacts of agricultural practice on flood peaks in upland catchments: An application of the distributed TOPMODEL

Upland agricultural land management activities such as grazing, vegetation burning, and bare ground restoration impact hydrological elements of headwater catchments, many of which may be important for downstream flood peaks (e.g., overland flow and soil water storage). However, there is poor understanding of how these management practices affect river flow peaks during high magnitude rainfall events. Using the distributed TOPMODEL, spatial configurations of land management were modelled to predict flood response in an upland catchment, which contains different regions operating subsidized agricultural stewardship schemes. Heavy grazing leading to soil compaction and loss of vegetation cover in stewardship regions covering 79.8% of the catchment gave a 42‐min earlier flow peak, which was 82.2% higher (under a 1‐hr 15‐mm storm) than the current simulated hydrograph. Light grazing over the same regions of the catchment had much less influence on river flow peaks (18 min earlier and 32.9% increase). Rotational burning (covering 8.8% of the catchment), most of which is located in the headwater areas, increased the peak by 3.2% in the same rainfall event. Vegetation restoration with either Eriophorum or Sphagnum (higher density) in bare areas (5.8%) of the catchment provided a reduction of flood peak (3.9% and 5.2% in the 15‐mm storm event), whereas the same total area revegetated with Sphagnum in riparian regions delivered a much larger decrease (15.0%) in river flow peaks. We show that changes of vegetation cover in highly sensitive areas (e.g., near‐stream zones) generate large impacts on flood peaks. Thus, it is possible to design spatially distributed management systems for upland catchments, which reduce flood peaks while at the same time ensuring economic viability for upland farmers.     

Comparison of different methods describing the peak runoff contributing areas during floods

In the last few years, the scientific community has developed several hydrological models aimed at the simulation of hydrological processes acting at the basin scale. In this context, the portion of peak runoff contributing areas represents a critical variable for a correct estimate of surface runoff. Such areas are strongly influenced by the saturated portion of a river basin (influenced by antecedent conditions) but may also evolve during a specific rainfall event. In the recent years, we have developed 2 theoretically derived probability distributions that attempt to interpret these 2 processes adopting daily runoff and flood‐peak time series. The probability density functions (PDFs) obtained by these 2 schematisations were compared for humid river basins in southern Italy. Results highlighted that the PDFs of the peak runoff contributing areas can be interpreted by a gamma distribution and that the PDF of the relative saturated area provides a good interpretation of such process that can be used for flood prediction.     

Assessment of flooding in urbanized ungauged basins: a case study in the Upper Tiber area,Italy

The reliability of a procedure for investigation of flooding into an ungauged river reach close to an urban area is investigated. The approach is based on the application of a semi‐distributed rainfall–runoff model for a gauged basin, including the flood‐prone area, and that furnishes the inlet flow conditions for a two‐dimensional hydraulic model, whose computational domain is the urban area. The flood event, which occurred in October 1998 in the Upper Tiber river basin and caused significant damage in the town of Pieve S. Stefano, was used to test the approach. The built‐up area, often inundated, is included in the gauged basin of the Montedoglio dam (275 km²), for which the rainfall–runoff model was adapted and calibrated through three flood events without over‐bank flow. With the selected set of parameters, the hydrological model was found reasonably accurate in simulating the discharge hydrograph of the three events, whereas the flood event of October 1998 was simulated poorly, with an error in peak discharge and time to peak of −58% and 20%, respectively. This discrepancy was ascribed to the combined effect of the rainfall spatial variability and a partial obstruction of the bridge located in Pieve S. Stefano. In fact, taking account of the last hypothesis, the hydraulic model reproduced with a fair accuracy the observed flooded urban area. Moreover, incorporating into the hydrological model the flow resulting from a sudden cleaning of the obstruction, which was simulated by a ‘shock‐capturing’ one‐dimensional hydraulic model, the discharge hydrograph at the basin outlet was well represented if the rainfall was supposed to have occurred in the region near the main channel. This was simulated by reducing considerably the dynamic parameter, the lag time, of the instantaneous unit hydrograph for each homogeneous element into which the basin is divided. The error in peak discharge and time to peak decreased by a few percent. A sensitivity analysis of both the flooding volume involved in the shock wave and the lag time showed that this latter parameter requires a careful evaluation. Moreover, the analysis of the hydrograph peak prediction due to error in rainfall input showed that the error in peak discharge was lower than that of the same input error quantity. Therefore, the obtained results allowed us to support the hypothesis on the causes which triggered the complex event occurring in October 1998, and pointed out that the proposed procedure can be conveniently adopted for flood risk evaluation in ungauged river basins where a built‐up area is located. The need for a more detailed analysis regarding the processes of runoff generation and flood routing is also highlighted. Copyright © 2005 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.     

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.     

Flood simulation using different sources of rainfall in the Huong River,Vietnam / Simulation d'inondation à l'aide de différentes sources d'information pluviométrique dans le bassin de la Rivière Huong,Vietnam

Abstract

The possibility of simulating flooding in the Huong River basin, Vietnam, was examined using quantitative precipitation forecasts at regional and global scales. Raingauge and satellite products were used for observed rainfall. To make maximum use of the spatial heterogeneity of the different types of rainfall data, a distributed hydrological model was set up to represent the hydrological processes. In this way, streamflow simulated using the rainfall data was compared with that observed in situ. The forecast on a global scale showed better performance during normal flow peak simulations than during extreme events. In contrast, it was found that during an extreme flood peak, the use of regional forecasts and satellite data gives results that are in close agreement with results using raingauge data. Using the simulated overflow volumes recorded at the control point downstream, inundation areas were then estimated using topographic characteristics. This study is the first step in developing a future efficient early warning system and evacuation strategy.     

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.     

Spatial,inter and intra‐annual variability of the Upper Blue Nile Basin rainfall

In this study, monthly and annual Upper Blue Nile Basin rainfall data were analyzed to learn the rainfall statistics and its temporal and spatial distribution. Frequency analysis and spatial characterization of rainfall in the Upper Blue Nile Basin are presented. Frequency analysis was performed on monthly basin rainfall. Monthly basin average rainfall data were computed from a network of 32 gauges with varying lengths of records. Monthly rainfall probability distribution varies from month to month fitting Gamma‐2, Normal, Weibull and Log‐Normal distributions. The January, July, October and November basin rainfall fit the Gamma‐2 probability distribution. The February, June and December ones fit Weibull distribution. The March, April, May and August rainfall fit Normal distribution. The September rainfall fits Log‐Normal distribution. Upper Blue Nile Basin is relatively wet with a mean annual rainfall of 1423 mm (1960–2002) with a standard deviation of 125 mm. The annual rainfall has a Normal probability distribution. The 100‐year‐drought basin annual rainfall is 1132 mm and the 100‐year‐wet basin annual rainfall is 1745 mm. The dry season is from November through April. The wet season runs from June through September with 74% of the annual rainfall. October and May are transition months. Monthly and annual rainfalls for return periods 2‐, 5‐, 10‐, 25‐, 50‐ and 100‐year dry and wet patterns are presented. Spatial distribution of annual rainfall over the basin is mapped and shows high variation with the southern tip receiving as high as 2049 mm and the northeastern tip as low as 794 mm annual average rainfall. Copyright © 2009 John Wiley & Sons, Ltd.     

Peak runoff contributing area as hydrological signature of the probability distribution of floods

For the analysis of hydrological extremes and particularly in flood prediction, deeper investigation is needed on the relative effects of different hydrological processes acting at the basin scale in different hydroclimatic areas of the world. In this framework, the theoretical derivation of flood distribution shows a great potential for development and knowledge advancement. In addition, another promising path of investigation is represented by the use of distributed hydrological models via simulation modelling (including Monte Carlo, discrete event and continuous simulation). In this paper results of a theoretically derived flood frequency distribution are analyzed and compared with the results of a simulation scheme that uses a distributed hydrological model (DREAM) in cascade with a rainfall generator (IRP). The numerical simulation allows the reproduction of a large number of extreme events and provides insight into the main control for flood generation mechanisms with particular emphasis to the peak runoff contributing areas, highlighting the relevance of soil texture and morphology in different climatic environments. The proposed methodology is applied here to the Agri and the Bradano basin, in Southern Italy.     

A comparison of three methods for regional flood frequency analysis in Saudi Arabia

The objective of the study was to compare the relative accuracy of three methodologies of regional flood frequency analysis in areas of limited flood records. Thirty two drainage basins of different characteristics, located mainly in the southwest region of Saudi Arabia, were selected for the study. In the first methodology, region curves were developed and used together with the mean annual flood, estimated from the characteristics of drainage basin, to estimate flood flows at a location in the basin. The second methodology was to fit probability distribution functions to annual maximum rainfall intensity in a drainage basin. The best fitted probability function was used together with common peak flow models to estimate the annual maximum flood flows in the basin. In the third methodology, duration reduction curves were developed and used together with the average flood flow in a basin to estimate the peak flood flows in the basin. The results obtained from each methodology were compared to the flood records of the selected stations using three statistical measures of goodness-of-fit. The first methodology was found best in a case of having short length of record at a drainage basin. The second methodology produced satisfactory results. Thus, it is recommended in areas where data are not sufficient and/or reliable to utilise the first methodology.     

Study on snowmelt runoff simulation in the Kaidu River basin

Alpine snowmelt is an important generation mode for runoff in the source region of the Tarim River basin, which covers four subbasins characterized by large area, sparse gauge stations, mixed runoff supplied by snowmelt and rainfall, and remarkably spatially heterogeneous precipitation. Taking the Kaidu River basin as a research area, this study analyzes the influence of these characteristics on the variables and parameters of the Snow Runoff Model and discusses the corresponding determination strategy to improve the accuracy of snowmelt simulation and forecast. The results show that: (i) The temperature controls the overall tendency of simulated runoff and is dominant to simulation accuracy, as the measured daily mean temperature cannot represent the average level of the same elevation in the basin and that directly inputting it to model leads to inaccurate simulations. Based on the analysis of remote sensing snow maps and simulation results, it is reasonable to approximate the mean temperature with 0.5 time daily maximum temperature. (ii) For the conflict between the limited gauge station and remarkably spatial heterogeneity of rainfall, it is not realistic to compute rainfall for each elevation zone. After the measured rainfall is multiplied by a proper coefficient and adjusted with runoff coefficient for rainfall, the measured rainfall data can satisfy the model demands. (iii) Adjusting time lag according to the variation of snowmelt and rainfall position can improve the simulation precision of the flood peak process. (iv) Along with temperature, the rainfall increases but cannot be completely monitored by limited gauge stations, which results in precision deterioration.     

Study on snowmelt runoff simulation in the Kaidu River basin

Alpine snowmelt is an important generation mode for runoff in the source region of the Tarim River basin, which covers four subbasins characterized by large area, sparse gauge stations, mixed runoff supplied by snowmelt and rainfall, and remarkably spatially heterogeneous precipitation. Taking the Kaidu River basin as a research area, this study analyzes the influence of these characteristics on the variables and parameters of the Snow Runoff Model and discusses the corresponding determination strategy to improve the accuracy of snowmelt simulation and forecast. The results show that: (i) The temperature controls the overall tendency of simulated runoff and is dominant to simulation accuracy, as the measured daily mean temperature cannot represent the average level of the same elevation in the basin and that directly inputting it to model leads to inaccurate simulations. Based on the analysis of remote sensing snow maps and simulation results, it is reasonable to approximate the mean temperature with 0.5 time daily maximum temperature. (ii) For the conflict between the limited gauge sta-tion and remarkably spatial heterogeneity of rainfall, it is not realistic to compute rainfall for each elevation zone. After the measured rainfall is multiplied by a proper coefficient and adjusted with runoff coefficient for rainfall, the measured rainfall data can satisfy the model demands. (iii) Adjusting time lag according to the variation of snowmelt and rainfall position can improve the simulation precision of the flood peak process. (iv) Along with temperature, the rainfall increases but cannot be completely monitored by limited gauge stations, which results in precision deterioration.