Bayesian comparison of different rainfall depth–duration–frequency relationships     

Aurélie Muller  Jean-Noël Bacro  Michel Lang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(1):33-46

Depth–duration–frequency curves estimate the rainfall intensity patterns for various return periods and rainfall durations. An empirical model based on the generalized extreme value distribution is presented for hourly maximum rainfall, and improved by the inclusion of daily maximum rainfall, through the extremal indexes of 24 hourly and daily rainfall data. The model is then divided into two sub-models for the short and long rainfall durations. Three likelihood formulations are proposed to model and compare independence or dependence hypotheses between the different durations. Dependence is modelled using the bivariate extreme logistic distribution. The results are calculated in a Bayesian framework with a Markov Chain Monte Carlo algorithm. The application to a data series from Marseille shows an improvement of the hourly estimations thanks to the combination between hourly and daily data in the model. Moreover, results are significantly different with or without dependence hypotheses: the dependence between 24 and 72 h durations is significant, and the quantile estimates are more severe in the dependence case.  相似文献   

Vegetation response to rainfall seasonality and interannual variability in tropical dry forests          下载免费PDF全文

Rodolfo Souza  Xue Feng  Antonio Antonino  Suzana Montenegro  Eduardo Souza  Amilcare Porporato 《水文研究》2016,30(20):3583-3595

Projected changes in rainfall seasonality and interannual variability are expected to have severe impacts on arid and semi‐arid tropical vegetation, which is characterized by a fine‐tuned adaptation to extreme rainfall seasonality. To study the response of these ecosystems and the related changes in hydrological processes to changes in the amount and seasonality of rainfall, we focused on the caatinga biome, the typical seasonally dry forest in semi‐arid Northeast Brazil. We selected four sites across a gradient of rainfall amount and seasonality and analysed daily rainfall and biweekly Normalized Difference Vegetation Index (NDVI) data for hydrological years 2000 to 2014. Rainfall seasonal and interannual statistics were characterized by recently proposed metrics describing duration, timing and intensity of the wet season and compared to similar metrics of NDVI time series. The results show that the caatinga tends to have a more stable response with longer and less variable growing seasons (3.1 ± 0.1 months) compared to the duration wet seasons (2.0 ± 0.5 months). The ecosystem ability to buffer the interannual variability of rainfall is also evidenced by the stability in the timing of the growing season compared to the wet season, which results in variable delays (ranging from 0 to 2 months) between the peak of the rainfall season and the production of leaves by the ecosystem. The analyses show that the shape and size of the related hysteresis loops in the rainfall–NDVI relations are linked to the buffering effects of soil moisture and plant growth dynamics. Finally, model projections of vegetation response to different rainfall scenarios reveal the existence of a maximum in ecosystem productivity at intermediate levels of rainfall seasonality, suggesting a possible trade‐off in the effects of intensity (i.e. amount) and duration of the wet season on vegetation growth and related soil moisture dynamics and transpiration rates. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

Assessment of the impact of climate change on the flow regime of the Han River basin using indicators of hydrologic alteration     

Byung‐Sik Kim  Bo‐Kyung Kim  Hyun‐Han Kwon 《水文研究》2011,25(5):691-704

Most natural disasters are caused by water‐/climate‐related hazards, such as floods, droughts, typhoons, and landslides. In the last few years, great attention has been paid to climate change, and especially the impact of climate change on water resources and the natural disasters that have been an important issue in many countries. As climate change increases the frequency and intensity of extreme rainfall, the number of water‐related disasters is expected to rise. In this regard, this study intends to analyse the changes in extreme weather events and the associated flow regime in both the past and the future. Given trend analysis, spatially coherent and statistically significant changes in the extreme events of temperature and rainfall were identified. A weather generator based on the non‐stationary Markov chain model was applied to produce a daily climate change scenario for the Han River basin for a period of 2001–2090. The weather generator mainly utilizes the climate change SRES A2 scenario driven by input from the regional climate model. Following this, the SLURP model, which is a semi‐distributed hydrological model, was applied to produce a long‐term daily runoff ensemble series. Finally, the indicator of hydrologic alteration was applied to carry out a quantitative analysis and assessment of the impact of climate change on runoff, the river flow regime, and the aquatic ecosystem. It was found that the runoff is expected to decrease in May and July, while no significant changes occur in June. In comparison with historical evidence, the runoff is expected to increase from August to April. A remarkable increase, which is about 40%, in runoff was identified in September. The amount of the minimum discharge over various durations tended to increase when compared to the present hydrological condition. A detailed comparison for discharge and its associated characteristics was discussed. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Assessment of GCM simulations of annual and seasonal rainfall and daily rainfall distribution across south‐east Australia     

J. Vaze  J. Teng  F. H. S. Chiew 《水文研究》2011,25(9):1486-1497

Global warming can potentially lead to changes in future rainfall and runoff and can significantly impact the regional hydrology and future availability of water resources. All the large‐scale climate impact studies use the future climate projections from global climate models (GCMs) to estimate the impact on future water availability. This paper presents results from a detailed assessment to investigate the capability of 15 GCMs to reproduce the observed historical annual and seasonal mean rainfalls, the observed annual rainfall series and the observed daily rainfall distribution across south‐east Australia. The assessment shows that the GCMs can generally reproduce the spatial patterns of mean seasonal and annual rainfalls. However, there can be considerable differences between the mean rainfalls simulated by the GCMs and the observed rainfall. The results clearly show that none of the GCMs can simulate the actual annual rainfall time series or the trend in the annual rainfall. The GCMs can also generally reproduce the observed daily (ranked) rainfall distribution at the GCM scale. The GCMs are ranked against their abilities to reproduce the observed historical mean annual rainfall and daily rainfall distribution, and, based on the combined score, the better GCMs include MPI‐ECHAM5, MIUB, CCCMA_T47, INMCM, CSIRO‐MK3·0, CNRM, CCCMA_T63 and GFDL 2·0 and those with poorer performances are MRI, IPSL, GISS‐AOM, MIROC‐M, NCAR‐PCM1, IAP and NCAR‐CCSM. However, the reduction in the combined score as we move from the best‐ to the worst‐performing GCMs is gradual, and there is no evident cut‐off point or threshold to remove GCMs from climate impact studies. There is some agreement between the results here and many similar studies comparing the performance of GCMs in Australia, but the results are not always consistent and do significantly disagree with several of the studies. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Estimation and spatial interpolation of rainfall intensity distribution from the effective rate of precipitation   总被引：1，自引：0，他引：1  

Ming Li  Quanxi Shao  Luigi Renzullo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(1):117-130

Great emphasis is being placed on the use of rainfall intensity data at short time intervals to accurately model the dynamics of modern cropping systems, runoff, erosion and pollutant transport. However, rainfall data are often readily available at more aggregated level of time scale and measurements of rainfall intensity at higher resolution are available only at limited stations. A distribution approach is a good compromise between fine-scale (e.g. sub-daily) models and coarse-scale (e.g. daily) rainfall data, because the use of rainfall intensity distribution could substantially improve hydrological models. In the distribution approach, the cumulative distribution function of rainfall intensity is employed to represent the effect of the within-day temporal variability of rainfall and a disaggregation model (i.e. a model disaggregates time series into sets of higher solution) is used to estimate distribution parameters from the daily average effective precipitation. Scaling problems in hydrologic applications often occur at both space and time dimensions and temporal scaling effects on hydrologic responses may exhibit great spatial variability. Transferring disaggregation model parameter values from one station to an arbitrary position is prone to error, thus a satisfactory alternative is to employ spatial interpolation between stations. This study investigates the spatial interpolation of the probability-based disaggregation model. Rainfall intensity observations are represented as a two-parameter lognormal distribution and methods are developed to estimate distribution parameters from either high-resolution rainfall data or coarse-scale precipitation information such as effective intensity rates. Model parameters are spatially interpolated by kriging to obtain the rainfall intensity distribution when only daily totals are available. The method was applied to 56 pluviometer stations in Western Australia. Two goodness-of-fit statistics were used to evaluate the skill—daily and quantile coefficient of efficiency between simulations and observations. Simulations based on cross-validation show that kriging performed better than other two spatial interpolation approaches (B-splines and thin-plate splines).  相似文献   

Variation in canopy conductance of Cunninghamia lanceolata forest and its response to environmental factors after an extreme rainfall event     

Wanqiu Xing  You Cheng  Lilin Yang  Weiguang Wang 《水文研究》2024,38(3):e15121

Canopy conductance (g_c) is a crucial parameter in simulating evapotranspiration and modulating water exchange, but its variation mechanism has regional uncertainties and complex environmental co-controls. In addition, the effect of extreme rainfall on g_c cannot be ignored under the changing climate. Here, we investigated the variation and environmental controls on g_c and the effect of extreme rainfall events in a Cunninghamia lanceolata forest across the subtropical area of Southern China. In July 2020, an extreme rainstorm hit the source area of the Xin'an River, with the cumulative rainfall on July 7 and 8 reaching 216.6 mm. The thermal diffusion probe method was used to measure the density of sap flow, and the environmental factors such as air temperature (T_a), net solar radiation (R_n) and soil water content (SWC) were monitored during the growing seasons of 2020 and 2021. Ultimately, g_c obtained by the Penman-Monteith equation was adopted since the result from the Köstner equation was overestimated. g_c showed a unimodal curve on the diurnal scale, and this characteristic was more obvious after the extreme rainfall. Daily g_c appeared a fluctuating pattern with a maximum in summer. g_c was simultaneously affected by T_a, R_n, water vapour pressure difference (VPD), SWC, among which T_a was the most significant driving factor at both the diurnal and daily timescales. The regulation of T_a, VPD and SWC on g_c had obvious thresholds, and the most definite response mode was VPD (2020: 1.25 kPa; 2021: 0.95 kPa). SWC and T_a were the dominant factors after the rainfall period, and the promotion effect of VPD on post-rainy days turned to inhibition effect on typical sunny days. These findings will further reveal the water exchange mechanism between atmosphere and vegetation and impacts of environmental factors in subtropical coniferous forests, especially after the extreme rainfall events.  相似文献   

Non-stationary frequency analysis of heavy rainfall events in southern France     

Yves Tramblay  Luc Neppel  Julie Carreau  Kenza Najib 《水文科学杂志》2013,58(2):280-294

Abstract

Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area.

Editor Z.W. Kundzewicz; Associate editor K. Hamed

Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294.  相似文献   

Statistical identification of orographic effects in the regional analysis of extreme rainfall          下载免费PDF全文

Pierluigi Furcolo  Anna Pelosi  Fabio Rossi 《水文研究》2016,30(9):1342-1353

Regional models of extreme rainfall must address the spatial variability induced by orographic obstacles. However, the proper detection of orographic effects often depends on the availability of a well‐designed rain gauge network. The aim of this study is to investigate a new method for identifying and characterizing the effects of orography on the spatial structure of extreme rainfall at the regional scale, including where rainfall data are lacking or fail to describe rainfall features thoroughly. We analyse the annual maxima of daily rainfall data in the Campania region, an orographically complex region in Southern Italy, and introduce a statistical procedure to identify spatial outliers in a low order statistic (namely the mean). The locations of these outliers are then compared with a pattern of orographic objects that has been a priori identified through the application of an automatic geomorphological procedure. The results show a direct and clear link between a particular set of orographic objects and a local increase in the spatial variability of extreme rainfall. This analysis allowed us to objectively identify areas where orography produces enhanced variability in extreme rainfall. It has direct implications for rain gauge network design criteria and has led to promising developments in the regional analysis of extreme rainfall. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

Extreme rainfall events over the Himalayas between 1871 and 2007     

S. Nandargi  O. N. Dhar 《水文科学杂志》2013,58(6):930-945

Abstract

Currently there is much discussion regarding the impact of climate change and the vagaries of the weather, in particular extreme weather events. The Himalayas form the main natural water resource of the major river systems of the Indian region. We present a brief review of the available information and data for extreme rainfall events that were experienced in different sectors of the Himalayas during the last 137 years (1871–2007). Across the entire Himalayas, from east to west, there are now 822 rainfall stations. There was an increase in the rainfall station network from 1947 onwards, especially in the Nepal and Bhutan Himalayas. Extreme one-day rainfall has been picked out for each station irrespective of the period for which data are available. The decadal distribution of these extreme one-day rainfalls shows that there is a considerable increase in the frequencies during the decades 1951–1960 to 1991–2000, whereas there is a sudden decrease in the frequencies in the present decade during 2001–2007, indicating the need to understand the response of the systems to global change and the associated physical and climatological changes. This is essential in terms of preserving this natural resource and to encourage environmental management and sustainable development of mountain regions.

Citation Nandargi, S. & Dhar, O. N. (2011) Extreme rainfall events over the Himalayas between 1871 and 2007. Hydrol. Sci. J. 56(6), 930–945.  相似文献   

New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 2. Future estimates and use in impact studies   总被引：1，自引：0，他引：1  

M. Ekstrm  H.J. Fowler  C.G. Kilsby  P.D. Jones 《Journal of Hydrology》2005,300(1-4):234-251

Under enhanced greenhouse conditions, climate models suggest an increase in rainfall intensities in the northern Hemisphere. Major flood events in the UK during autumn 2000 and central Europe in August 2002, have focussed attention on the dramatic impacts these changes may have on many sectors of society. In the companion paper [Fowler et al., J. Hydrol. (2004) this issue], we suggested that the HadRM3H model may be used with some confidence to estimate extreme rainfall distributions, showing good predictive skill in estimating statistical properties of extreme rainfall during the baseline period, 1961–1990. In this study, we use results from the future integration of HadRM3H (following the IPCC SRES scenario A2 for 2070–2100) to assess possible changes in extreme rainfall across the UK using two methods: regional frequency analysis and individual grid box analysis. Results indicate that for short duration events (1–2 days), event magnitude at a given return period will increase by 10% across the UK. For longer duration events (5–10 days), event magnitudes at given return periods show large increases in Scotland (up to +30%), with greater relative change at higher return periods (25–50 years). In the rest of the UK, there are small increases in the magnitude of more frequent events (up to +10%) but reductions at higher return periods (up to −20%). These results provide information to alter design storm depths to examine climate change impacts on various structures. The uncertainty bounds of the estimated changes and a ‘scaling’ methodology are additionally detailed. This allows the estimation of changes for the 2020s, 2050s and 2080s, and gives some confidence in the use of these estimates in impact studies.  相似文献   

Dynamic characteristics of monthly rainfall in the Korean Peninsula under climate change   总被引：3，自引：1，他引：2  

Min Soo Kyoung  Hung Soo Kim  Bellie Sivakumar  Vijay P. Singh  Kyung Soo Ahn 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(4):613-625

Global climate change is one of the most serious issues we are facing today. While its exact impacts on our water resources are hard to predict, there is a general consensus among scientists that it will result in more frequent and more severe hydrologic extremes (e.g. floods, droughts). Since rainfall is the primary input for hydrologic and water resource studies, assessment of the effects of climate change on rainfall is essential for devising proper short-term emergency measures as well as long-term management strategies. This is particularly the case for a region like the Korean Peninsula, which is susceptible to both floods (because of its mountainous terrain and frequent intense rainfalls during the short rainy season) and droughts (because of its smaller area, long non-rainy season, and lack of storage facilities). In view of this, an attempt is made in the present study to investigate the potential impacts of climate change on rainfall in the Korean Peninsula. More specifically, the dynamics of ‘present rainfall’ and ‘future rainfall’ at the Seoul meteorological station in the Han River basin are examined and compared; monthly scale is considered in both cases. As for ‘present rainfall,’ two different data sets are used: (1) observed rainfall for the period 1971–1999; and (2) rainfall for the period 1951–1999 obtained through downscaling of coarse-scale climate outputs produced by the Bjerknes Center for Climate Research-Bergen Climate Model Version 2 (BCCR-BCM2.0) climate model with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) 20th Century Climate in Coupled Models (20C3M) scenario. The ‘future rainfall’ (2000–2099) is obtained through downscaling of climate outputs projected by the BCCR-BCM2.0 with the A2 emission scenario. For downscaling of coarse-scale climate outputs to basin-scale rainfall, a K-nearest neighbor (K-NN) technique is used. Examination of the nature of rainfall dynamics is made through application of four methods: autocorrelation function, phase space reconstruction, correlation dimension, and close returns plot. The results are somewhat mixed, depending upon the method, as to whether the rainfall dynamics are chaotic or stochastic; however, the dynamics of the future rainfall seem more on the chaotic side than on the stochastic side, and more so when compared to that of the present rainfall.  相似文献