scholarly journals Hydrometeorological analysis of the 12 and 13 September 2019 widespread flash flooding in eastern Spain

2021 ◽  
Author(s):  
Arnau Amengual
Keyword(s):  
Heavy Precipitation ◽  
Flood Frequency ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Flash Flooding ◽  
Flood Peak ◽  
Convective Structures ◽  
Flood Response ◽  
Infiltration Excess ◽  
Cumulative Precipitation

Abstract. On 12 and 13 September 2019, a long-lasting heavy precipitation episode (HPE) affected the València, Murcia and Almería regions in eastern Spain. Observed rainfall amounts were close to 500 mm in 48 h, being the highest cumulative precipitation registered in some rain-gauges for the last century. Subsequent widespread flash flooding caused seven fatalities and estimated economical losses above 425 million EUR. High-resolution precipitation estimates from weather radar observations and flood response from stream-gauges are used in combination with a fully-distributed hydrological model to examine the main hydrometeorological processes within the HyMeX program. This HPE was characterized by successive, well-organized convective structures that impacted a spatial extent of 7500 km2, with rainfall amounts equal or larger than 200 mm. The main factors driving the flood response were quasi-stationarity of heavy precipitation, very dry initial soil moisture conditions and large storage capacities. Most of the examined catchments exhibited a dampened and delayed hydrological response to cumulative precipitation: Until runoff thresholds were exceeded, infiltration-excess runoff generation did not start. This threshold-based hydrological behaviour may impact the shape of flood peak distributions, hindering strict flood frequency statistical analysis due to the generally limited lengths of data records in arid and semi-arid catchments. As an alternative, simple scaling theory between flood magnitude and total rainfall amount is explored.

scholarly journals Exploring the application of flood scaling property in hydrological model calibration

2021 ◽  
Author(s):  
Yanchen Zheng ◽  
Jianzhu Li ◽  
Ting Zhang ◽  
Youtong Rong ◽  
Ping Feng
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Flood Frequency ◽  
Efficiency Coefficient ◽  
Distributed Hydrological Model ◽  
Flood Peak ◽  
Scaling Property ◽  
Streamflow Data

Abstract Model calibration has always been one major challenge in hydrological community. Flood scaling property (FS) is often used to estimate the flood quantiles for data-scarce catchments based on the statistical relationship between flood peak and contributing areas. This paper investigates the potential of applying FS and multivariate flood scaling property (MLR) as constraints in model calibration. Based on the assumption that the scaling property of flood exists in four study catchments in Northern China, eight calibration scenarios are designed with adopting different combination of traditional indicators and FS or MLR as objective functions. The performance of the proposed method is verified by employing a distributed hydrological model, namely Soil and Water Assessment Tool (SWAT) model. The results indicate that reasonable performance could be obtained in FS with less requirements of observed streamflow data, exhibiting better simulation on flood peak than Nash-Sutcliffe efficiency coefficient calibration scenario. The observed streamflow data or regional flood information are required in MLR calibration scenario to identify the dominant catchment descriptors, and MLR achieve better performance on catchment interior points, especially for the events with uneven distribution of rainfall. On account of the improved performance on hydrographs and flood frequency curve at watershed outlet, adopting the statistical indicators and flood scaling property simultaneously as model constraints is suggested. The proposed methodology enhances the physical connection of flood peak among sub-basins and considers watershed actual conditions and climatic characteristics for each flood event, facilitating a new calibration approach for both gauged catchments and data-scarce catchments.

scholarly journals Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China

2013 ◽  
Vol 17 (2) ◽  
pp. 679-689 ◽  
Author(s):  
J. J. Lian ◽  
K. Xu ◽  
C. Ma
Keyword(s):  
Flood Risk ◽  
Joint Probability ◽  
Heavy Precipitation ◽  
River Network ◽  
Flood Frequency ◽  
Combined Effect ◽  
Multiple Sources ◽  
Tidal Level ◽  
Sea Levels ◽  
Coastal Cities

Abstract. Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms. The combined effect of multiple sources and the joint probability of extremes should be considered to assess and manage flood risk better. This paper aims to study the combined effect of rainfall and the tidal level of the receiving water body on flood probability and severity in Fuzhou City, which has a complex river network. Flood severity under a range of precipitation intensities, with return periods (RPs) of 5 yr to 100 yr, and tidal levels was assessed through a hydrodynamic model verified by data observed during Typhoon Longwang in 2005. According to the percentages of the river network where flooding occurred, the threshold conditions for flood severity were estimated in two scenarios: with and without working pumps. In Fuzhou City, working pumps efficiently reduce flood risk from precipitation within a 20-yr RP. However, the pumps may not work efficiently when rainfall exceeds a 100-yr RP because of the limited conveyance capacity of the river network. Joint risk probability was estimated through the optimal copula. The joint probability of rainfall and tidal level both exceeding their threshold values is very low, and the greatest threat in Fuzhou comes from heavy rainfall. However, the tidal level poses an extra risk of flood. Given that this extra risk is ignored in the design of flood defense in Fuzhou, flood frequency and severity may be higher than understood during design.

scholarly journals Diagnostic calibration of a hydrological model in an alpine area

2014 ◽  
Vol 11 (1) ◽  
pp. 1253-1300 ◽  
Author(s):  
Z. He ◽  
F. Tian ◽  
H. C. Hu ◽  
H. V. Gupta ◽  
H. P. Hu
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Generation Mechanism ◽  
Spatiotemporal Variability ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Alpine Area ◽  
Long Time ◽  
Tailan River Basin

Abstract. Hydrological modeling depends on single- or multiple-objective strategies for parameter calibration using long time sequences of observed streamflow. Here, we demonstrate a diagnostic approach to the calibration of a hydrological model of an alpine area in which we partition the hydrograph based on the dominant runoff generation mechanism (groundwater baseflow, glacier melt, snowmelt, and direct runoff). The partitioning reflects the spatiotemporal variability in snowpack, glaciers, and temperature. Model parameters are grouped by runoff generation mechanism, and each group is calibrated separately via a stepwise approach. This strategy helps to reduce the problem of equifinality and, hence, model uncertainty. We demonstrate the method for the Tailan River basin (1324 km2) in the Tianshan Mountains of China with the help of a semi-distributed hydrological model (THREW).

scholarly journals On the asymptotic behavior of flood peak distributions

2006 ◽  
Vol 10 (2) ◽  
pp. 233-243 ◽  
Author(s):  
E. Gaume
Keyword(s):  
Frequency Distribution ◽  
Return Period ◽  
Asymptotic Properties ◽  
Flood Frequency ◽  
Point Of View ◽  
Rainfall Runoff ◽  
New Approach ◽  
Flood Peak ◽  
Flood Quantiles ◽  
The Impact

Abstract. This paper presents some analytical results and numerical illustrations on the asymptotic properties of flood peak distributions obtained through derived flood frequency approaches. It confirms and extends the results of previous works: i.e. the shape of the flood peak distributions are asymptotically controlled by the rainfall statistical properties, given limited and reasonable assumptions concerning the rainfall-runoff process. This result is partial so far: the impact of the rainfall spatial heterogeneity has not been studied for instance. From a practical point of view, it provides a general framework for analysis of the outcomes of previous works based on derived flood frequency approaches and leads to some proposals for the estimation of very large return-period flood quantiles. This paper, focussed on asymptotic distribution properties, does not propose any new approach for the extrapolation of flood frequency distribution to estimate intermediate return period flood quantiles. Nevertheless, the large distance between frequent flood peak values and the asymptotic values as well as the simulations conducted in this paper help quantifying the ill condition of the problem of flood frequency distribution extrapolation: it illustrates how large the range of possibilities for the shapes of flood peak distributions is.

Nonstationary Flood Frequency Analysis for Annual Flood Peak and Volume Series in Both Univariate and Bivariate Domain

2018 ◽  
Vol 32 (13) ◽  
pp. 4239-4252 ◽  
Author(s):  
Jianzhu Li ◽  
Yuming Lei ◽  
Senming Tan ◽  
Colin D. Bell ◽  
Bernard A. Engel ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Flood Peak

scholarly journals Trends, change points and spatial variability in extreme precipitation events from 1961 to 2017 in China

2020 ◽  
Vol 51 (3) ◽  
pp. 484-504 ◽  
Author(s):  
Linchao Li ◽  
Yufeng Zou ◽  
Yi Li ◽  
Haixia Lin ◽  
De Li Liu ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Extreme Event ◽  
Heavy Precipitation ◽  
Kendall Test ◽  
Temporal Variations ◽  
Change Points ◽  
Monthly Precipitation ◽  
Flood Peak ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract Extreme precipitation events vary with different sub-regions, sites and years and show complex characteristics. In this study, the temporal variations, trends with significance and change points in the annual time series of 10 extreme precipitation indices (EPIs) at 552 sites and in seven sub-regions were analyzed using the modified Mann–Kendall test and sequential Mann–Kendall analysis. Three representative (extremely wet, normal and extremely dry) years from 1961 to 2017 were selected by the largest, 50%, and smallest empirical frequency values in China. The spatiotemporal changes in the EPIs during the three representative years were analyzed in detail. The results showed that during 1961–2017, both the consecutive wet or dry days decreased significantly, while the number of heavy precipitation days had no significant trend, and the other seven wet EPIs increased insignificantly. The abrupt change years of the 10 EPIs occurred 32 and 40 times from 1963 to 1978 and from 1990 to 2016, respectively, regardless of sub-region. The extremely dry (or wet) events mainly occurred in western (or southwestern) China, implying a higher extreme event risk. The extremely wet, normal and extremely dry events from 1961 to 2017 occurred in 2016, 1997 and 2011 with empirical frequencies of 1.7%, 50% and 98.3%, respectively. In addition, 1998 was the second-most extremely wet year (empirical frequency was 3.7%). The monthly precipitation values were larger from February to August in 1998, forming a much earlier flood peak than that of 2016. The 10 EPIs had close connections with Normalized Difference Vegetation Indexes during the 12 months of 1998 and 2016. This study provides useful references for disaster prevention in China.

scholarly journals Integration of hillslope hydrology and 2D hydraulic modelling for natural flood management

2019 ◽  
Vol 50 (6) ◽  
pp. 1535-1548 ◽  
Author(s):  
Barry Hankin ◽  
Peter Metcalfe ◽  
Keith Beven ◽  
Nick A. Chappell
Keyword(s):  
Spatial Data ◽  
Flood Management ◽  
Flow Equation ◽  
Tree Planting ◽  
Spatial Data Analysis ◽  
Generation Model ◽  
Runoff Generation ◽  
Complex Behaviour ◽  
Flood Peak ◽  
Antecedent Moisture

Abstract Natural flood management (NFM) has recently invigorated the hydrological community into redeploying its process understanding of hydrology and hydraulics to try to quantify the impacts of many distributed, ‘nature-based’ measures on the whole-catchment response. Advances in spatial data analysis, distributed hydrological modelling and fast numerical flow equation solvers mean that whole-catchment modelling including computationally intensive uncertainty analyses are now possible, although perhaps the community has not yet converged on the best overall parsimonious framework. To model the effects of tree-planting, we need to understand changes to wet canopy evaporation, surface roughness and infiltration rates; to model inline storage created by ‘leaky barriers’ or offline storage, we need accurate channel hydraulics to understand the changes to attenuation; to model the complex behaviour of the whole network of NFM measures, and the possibility of flood peak synchronisation effects, we need efficient realistic routing models, linked to key flow pathways that take into account the main physical processes in soils and the antecedent moisture conditions for a range of different rainfall events. This paper presents a new framework to achieve this, based on a cascade of the Dynamic Topmodel runoff generation model and the JFlow or HEC-RAS 2D hydraulic models, with an application to the Swindale Catchment in Cumbria, UK. We demonstrate the approach to quantify both the effectiveness of a relatively large ‘runoff attenuation feature’ in the landscape and the uncertainty in the calculation given model parameter uncertainty.

scholarly journals Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 903-920 ◽  
Author(s):  
W. Qi ◽  
C. Zhang ◽  
G. Fu ◽  
C. Sweetapple ◽  
H. Zhou
Keyword(s):  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Precipitation Product ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Discharge Simulation ◽  
Fine Resolution

Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash–Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

scholarly journals On the role of the runoff coefficient in the mapping of rainfall to flood return periods

2009 ◽  
Vol 13 (5) ◽  
pp. 577-593 ◽  
Author(s):  
A. Viglione ◽  
R. Merz ◽  
G. Blöschl
Keyword(s):  
Monte Carlo ◽  
Return Period ◽  
Threshold Effect ◽  
Flood Frequency ◽  
Runoff Coefficient ◽  
Return Periods ◽  
Runoff Generation ◽  
Design Storm ◽  
Shed Light

Abstract. While the correspondence of rainfall return period TP and flood return period TQ is at the heart of the design storm procedure, their relationship is still poorly understood. The purpose of this paper is to shed light on the controls on this relationship examining in particular the effect of the variability of event runoff coefficients. A simplified world with block rainfall and linear catchment response is assumed and a derived flood frequency approach, both in analytical and Monte-Carlo modes, is used. The results indicate that TQ can be much higher than TP of the associated storm. The ratio TQ /TP depends on the average wetness of the system. In a dry system, TQ can be of the order of hundreds of times of TP. In contrast, in a wet system, the maximum flood return period is never more than a few times that of the corresponding storm. This is because a wet system cannot be much worse than it normally is. The presence of a threshold effect in runoff generation related to storm volume reduces the maximum ratio of TQ /TP since it decreases the randomness of the runoff coefficients and increases the probability to be in a wet situation. We also examine the relation between the return periods of the input and the output of the design storm procedure when using a pre-selected runoff coefficient and the question which runoff coefficients produce a flood return period equal to the rainfall return period. For the systems analysed here, this runoff coefficient is always larger than the median of the runoff coefficients that cause the maximum annual floods. It depends on the average wetness of the system and on the return period considered, and its variability is particularly high when a threshold effect in runoff generation is present.

scholarly journals Deriving Design Flood Hydrograph Based on Conditional Distribution: A Case Study of Danjiangkou Reservoir in Hanjiang Basin

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Changjiang Xu ◽  
Jiabo Yin ◽  
Shenglian Guo ◽  
Zhangjun Liu ◽  
Xingjun Hong
Keyword(s):  
Joint Probability ◽  
Flood Frequency ◽  
Peak Discharge ◽  
Flood Frequency Analysis ◽  
Design Flood ◽  
Copula Functions ◽  
Danjiangkou Reservoir ◽  
Flood Peak ◽  
Flood Hydrograph

Design flood hydrograph (DFH) for a dam is the flood of suitable probability and magnitude adopted to ensure safety of the dam in accordance with appropriate design standards. Estimated quantiles of peak discharge and flood volumes are necessary for deriving the DFH, which are mutually correlated and need to be described by multivariate analysis methods. The joint probability distributions of peak discharge and flood volumes were established using copula functions. Then the general formulae of conditional most likely composition (CMLC) and conditional expectation composition (CEC) methods that consider the inherent relationship between flood peak and volumes were derived for estimating DFH. The Danjiangkou reservoir in Hanjiang basin was selected as a case study. The design values of flood volumes and 90% confidence intervals with different peak discharges were estimated by the proposed methods. The performance of CMLC and CEC methods was also compared with conventional flood frequency analysis, and the results show that CMLC method performs best for both bivariate and trivariate distributions which has the smallest relative error and root mean square error. The proposed CMLC method has strong statistical basis with unique design flood composition scheme and provides an alternative way for deriving DFH.

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