A conceptual investigation of process controls upon flood frequency: role of thresholds

Abstract. While the correspondence of rainfall return period T P and flood return period T Q 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 T Q can be much higher than T P of the associated storm. The ratio T Q /T P depends on the average wetness of the system. In a dry system, T Q can be of the order of hundreds of times of T P . 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 T Q /T P 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.

Section: Results: Comparison Between Systemsmentioning

confidence: 99%

Section: Non-linear Relationship Between Flood Runoff Coefficients Anmentioning

confidence: 99%

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

Viglione

Merz

Blöschl

2009

“…Kusumastuti et al (2007) focused on catchment storage and derived the flood frequency distributions by Monte Carlo simulations, using a non-linear conceptual rainfall-runoff model. Struthers and Sivapalan (2007) analysed the influence on flood frequency of spatial heterogeneity in non-linear thresholds, seasonal variability in storms, and space-time variability in the storage-discharge relationship associated with the rainfall-runoff process. They observed that temporal variability in seasonal storms increases the frequency of threshold exceedence and the magnitude of the flood response associated with a given runoff process.…”

Section: Introductionmentioning

confidence: 99%

Runoff thresholds in derived flood frequency distributions

Gioia

Iacobellis

Manfreda

et al. 2008

Abstract.In general, different mechanisms may be identified as responsible of runoff generation during ordinary events or extraordinary events at the basin scale. In a simplified scheme these mechanisms may be represented by different runoff thresholds. In this context, the derived flood frequency model, based on the effect of partial contributing areas on peak flow, proposed by Iacobellis and Fiorentino (2000), was generalized by providing a new formulation of the derived distribution where two runoff components are explicitly considered. The model was tested on a group of basins in Southern Italy characterized by annual maximum flood distributions highly skewed. The application of the proposed model provided good results in terms of descriptive ability. Model parameters were also found to be well correlated with geomorphological basin descriptors. Two different threshold mechanisms, associated respectively to ordinary and extraordinary events, were identified. In fact, we found that ordinary floods are mostly due to rainfall events exceeding a threshold infiltration rate in a small source area, while the so-called outlier events, responsible of the high skewness of flood distributions, are triggered when severe rainfalls exceed a threshold storage in a large portion of the basin.

“…Hortonian overland flow (Horton, 1933) or preferential flow (Beven and Germann, 2013). These mechanisms are not controlled by storage capacity but by infiltrability and conductivity of the subsurface (Struthers and Sivapalan, 2007). dDMC segments with slopes close to one may however also indicate fast responding catchments e.g.…”

Section: Derivation Of Dimensionless Double Mass Curvesmentioning

confidence: 99%

Unravelling abiotic and biotic controls on the seasonal water balance using data-driven dimensionless diagnostics

Seibert

Jackisch

Ehret

et al. 2017

Abstract. The baffling diversity of runoff generation processes, alongside our sketchy understanding of how physiographic characteristics control fundamental hydrological functions of water collection, storage, and release, continue to pose major research challenges in catchment hydrology. Here, we propose innovative data-driven diagnostic signatures for overcoming the prevailing status quo in catchment inter-comparison. More specifically, we present dimensionless double mass curves (dDMC) which allow inference of information on runoff generation and the water balance at the seasonal and annual timescales. By separating the vegetation and winter periods, dDMC furthermore provide information on the role of biotic and abiotic controls in seasonal runoff formation.A key aspect we address in this paper is the derivation of dimensionless expressions of fluxes which ensure the comparability of the signatures in space and time. We achieve this by using the limiting factors of a hydrological process as a scaling reference. We show that different references result in different diagnostics. As such we define two kinds of dDMC which allow us to derive seasonal runoff coefficients and to characterize dimensionless streamflow release as a function of the potential renewal rate of the soil storage. We expect these signatures for storage controlled seasonal runoff formation to remain invariant, as long as the ratios of release over supply and supply over storage capacity develop similarly in different catchments.We test the proposed methods by applying them to an operational data set comprising 22 catchments (12-166 km 2 ) from different environments in southern Germany and hydrometeorological data from 4 hydrological years. The diagnostics are used to compare the sites and to reveal the dominant controls on runoff formation.The key findings are that dDMC are meaningful signatures for catchment runoff formation at the seasonal to annual scale and that the type of scaling strongly influences the diagnostic potential of the dDMC. Adding discrimination between growing season and winter period was of fundamental importance and easy to implement by means of a temperatureindex model. More specifically, temperature aggregates explain over 70 % of the variability of the seasonal summer runoff coefficients. The results also show that the soil topographic index, i.e. the product of topographic gradient and saturated hydraulic conductivity, is significantly correlated with winter runoff coefficients, whereas the topographic gradient and the hydraulic conductivity alone are not. We conclude that proxies for gradients and resistances should be interpreted as a pair. Lastly, the dDMC concept reveals memory effects between summer and winter runoff regimes that are not relevant in spring between the transition from winter to summer.