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The Great Plains of eastern Nebraska occupy a distinctive hydroclimatological niche, characterized by a high frequency of organized thunderstorm systems. A consequence of the hydroclimatology of these systems is a sharp seasonal peak in the regional flood frequency in late June. Pebble Creek and Maple Creek are adjacent drainage basins in the Great...
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... distance to the outlet. Values of D t close to 0 indicate that rainfall is concentrated near the outlet of the basin. Values near 1 correspond to rainfall distribution concentrated at the far periphery of the basin. The spatial and temporal variability of rainfall for the 20±21 June storm is illustrated through a storm total rainfall map ( Fig. 7(a)), tracking-based representations of storm structure and motion ( Fig. 8; the ellipses represent the minimal ellipse that contains the 45 dBZ boundary of the storm), and time series of M t, Z t and D t for Maple Creek and Pebble Creek (Fig. 9). The storm total rainfall distribution ( Fig. 7(a)) re¯ects southeast motion of the four ...
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... is illustrated through a storm total rainfall map ( Fig. 7(a)), tracking-based representations of storm structure and motion ( Fig. 8; the ellipses represent the minimal ellipse that contains the 45 dBZ boundary of the storm), and time series of M t, Z t and D t for Maple Creek and Pebble Creek (Fig. 9). The storm total rainfall distribution ( Fig. 7(a)) re¯ects southeast motion of the four storm elements and southwest shift of the tracks of the storms. Maximum rainfall accumulations were located just to the east of Pebble Creek and were produced principally by storms (a) and (b) (Fig. 8). The rainfall maximum for Pebble Creek occurred at approximately 23:30 of June 20 and was ...
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... analyses for the 4±5 August 1996 storm are summarized in Figs. 7(b), 10 and 11 through analyses similar to those for the 20±21 June storm. The storm total rainfall distribution ( Fig. ...
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... the Maple Creek±Pebble Creek region. The duration of ¯ood producing rainfall for the Maple Creek± Pebble Creek region was approximately 4 h for the 20±21 June storm and 6 h for the 4±5 August storm. Contrasting storm structure and direction of motion between the two storm systems resulted in dierent patterns of storm total rainfall distribution (Fig. 7(a) and (b)) and dierences in fractional coverage and motion relative to the drainage network (Figs. 9 and 11). Of particular importance for the 4±5 August storm was explosive growth of an elongated region of extreme ...
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... response properties of the August 1996 ¯ood event in Maple Creek contrast not only with those in Pebble Creek, but also with the other four events in Maple Creek. The rainfall maximum in the upper basin of Maple Creek for the 4±5 August storm (Fig. 7(b)) contributed to the attenuated response of Maple Creek for the August 1996 ¯ood. The dominant role, however, is likely due to valley bottom storage in the lower 8 km reach of Maple Creek. As shown in Fig. 1, the lower portion of the basin is characterized by a striking expansion of the valley bottom. The discharge range from The ...
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... envelope curve for the 4±5 August storm decreases from greater than 15 m 3 s À1 km À2 at basin scales less than 2 km 2 to less than 2 m 3 s À1 km À2 at basin scales greater than 500 km 2 . The region of peak storm total accumulation in the upper portion of Pebble Creek for the 4±5 August storm (Fig. 7(b)) is the location of the largest model discharge at small drainage areas. The small-basin peak discharges result principally from storm (b) (Fig. 10, top). For basin scales between 5 and 25 km 2 , the 20±21 June storm results in ¯ood peaks of comparable to larger magnitude to those from the 4±5 August storm. Storms (a) and (b) (Fig. 8) ...
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Citations
... The next variable is the ETR-Centroid of precipitation. Many papers in literature (e.g., (Borga et al., 2008;Woods and Sivapalan, 1999;Woods, 1999;Smith et al., 2004Smith et al., , 2005Smith et al., , 2002Zhang et al., 2001)highlighted the relationship between the centroid of precipitation and runoff production. Most works showed that, for example, the position of the storm centroid relative to the watershed outlet is an important driver of runoff: storms having a precipitation centroid positioned in the central 545 portion of the watershed tend to produce a higher runoff than storms having a centroid near the outlet or the head of the watershed. ...
Due to global climate change, flooding is predicted to become more frequent in the coming decades. Recent literature has highlighted the importance of river morphodynamics in controlling flood hazards at the local scale. Abrupt and short-term geomorphic changes can occur after major storms. However, our ability to foresee where and when substantial changes will happen is still limited, hindering our understanding of their ramifications on future flood hazards. This study sought to understand the implications of major storm events for future flood hazards. For this purpose, we developed self-organizing maps (SOMs) to predict post-storm changes in stage‐discharge relationships, based on storm characteristics and watershed properties at 3,101 stream gages across the continental United States (CONUS). We tested and verified a machine learning (ML) model and its feasibility for (1) mapping the variability of geomorphic impacts of extreme storm events and (2) representing the effects of these changes on stage‐discharge relationships at gaged sites as a proxy for changes in flood hazard. The established model allows us to select rivers with stage-discharge relationships that are more prone to change after severe storms, for which flood frequency analysis should be revised on a regular basis so that hazard assessment can be up to date with the changing conditions. Results from the model show that, even though post-storm changes in channel conveyance are widespread, the impacts on flood hazard vary across CONUS. The influence of channel conveyance variability on flood risk depends on various parameters characterizing a particular landscape or storm. The proposed framework can serve as a basis for incorporating channel conveyance adjustments into flood hazard assessment.
... Such difference should be due to the faster response of Puerto Rico watershed than CFRB, which is tied to their difference in topographic gradients. At sub-basin scales, in consistent with what is reported by previous studies (Lininger and Latrubesse, 2016;Sturdevant-Rees et al., 2001;Zhang et al., 2001), land use, soil type, coastal flood plain storage as well as the river network could exert secondary important influence on flood response. Re-infiltration process, similar with that reported by Zhang et al., (2020), was superior to local infiltration. ...
Hurricanes are the major flood generating mechanism dominating the upper tail of the peak discharge distribution over the Cape Fear River Basin (CFRB). In 2018, Hurricane Florence swamped CFRB as the ninth-most-destructive hurricane ever hit the United States and set new records of peak discharges over the main river channel and three out of five of its major tributaries. In this study, we examined the hydrometeorology and hydrology of this flood via combined observation and numerical experiment analyses. Our results suggest that the slow-motion in combination to the “L-shaped” path was the most distinctive feature of the hurricane that incurred catastrophic and widespread rainfall and flooding over CFRB. The total rainfall from the storm played a controlling role in the magnitude and spatial distribution of the flood peaks at basin scale. Above that, the spatial heterogeneities of rainfall distribution and hydrologic characteristics was responsible for the distinctive flood responses within the basin. The bi-peak shape of the flood hydrograph for the Deep River was due to the combined effects of rainfall distribution, land cover, and topographic gradient. The exceptional unit peak discharge over the Black River basin was associated with its drainage network structure, topographic gradient and rainfall distribution. The floodplain downstream of the Cape Fear River temporarily stored flood water and attenuated both the riverine floods from upstream and the compound flood over the coastal area. Furthermore, numerical analyses found that re-infiltration accounted for 76% of the total infiltration on average. Re-infiltration was superior to local infiltration over CFRB during Hurricane Florence.
... Therefore, studying the occurrence rule and formation mechanism of flood is of significant social significance to preventing and predicting flood. The lognormal distribution model is a data analysis method used in cases where there are random variables (Martinezgoytre et al., 1994;Xin and Venkataramana, 2012;Zhang et al., 2001). In the analysis of the formation and development of watershed flood peaks and their effects on the regional hydrological conditions, there are a series of random variables such as peak discharge and confluence area. ...
... The total precipitation amounts exceeding 30 mm/day which occur in 4 or more provinces of the country are considered to be risky for floods in Bulgaria [6]. In the Great Plains of Eastern Nebraska, the hydrology and hydrometeorology of extreme floods are discussed [7]. Nyeko-Ogiramoi et al. [8] found that hydrometeorological extremes in the Lake Victoria basin are experiencing positive linear trends. ...
Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin.
... This is related to the type of vegetation and depth of its roots, which influence the soil hydraulic behavior. Hence, changes in land use induce changes in the soil infiltration capacity, which determines the hydrological response of the catchments (Zhang et al., 2001) and alters the flow variability pattern (Hopmans et al., 2002). ...
Changes in land use within a catchment are among the causes of non-stationarity in the flood regime, as they modify the upper soil physical structure and its runoff production capacity. This paper analyzes the relation between the variation of the upper soil hydraulic properties due to changes in land use and its effect on the magnitude of peak flows: (1) incorporating fractal scaling properties to relate the effect of the static storage capacity (the sum of capillary water storage capacity in the root zone, canopy interception and surface puddles) and the upper soil vertical saturated hydraulic conductivity on the flood regime; (2) describing the effect of the spatial organization of the upper soil hydraulic properties at catchment scale; (3) examining the scale properties in the parameters of the Generalized Extreme Value (GEV) probability distribution function, in relation to the upper soil hydraulic properties. This study considered the historical changes of land use in the Combeima River catchment in South America, between 1991 and 2007, using distributed hydrological modeling of daily discharges to describe the hydrological response. Through simulation of land cover scenarios, it was demonstrated that it is possible to quantify the magnitude of peak flows in scenarios of land cover changes through its Wide-Sense Simple Scaling with the upper soil hydraulic properties.
... Some hypotheses have been put forward to identify the mechanisms through which rainfall spatial variability may affect catchment response, with an emphasis on hydrologic partitioning processes (Anquetin et al., 2010;Brath and Montanari, 2003;Gabellani et al., 2007;Shah et al., 1996;Winchell et al., 1998). Several works have focused on the relation between the spatial rainfall organization and the heterogeneities embedded in the basin geomorphic structure, mostly by examining the rainfall variability relative to a distance metric imposed by the drainage network (Lobligeois et al., 2014;Smith et al., 2005;Smith et al., 2002;Zhang et al., 2001). Nicótina et al. (2008) focused on the effects of transport processes along the hillslopes and the channel network as a key element to clarify the extent of the possible influence of rainfall spatial variability on the hydrologic response. ...
... A number of papers have focused on the interaction between rainfall spatial organisation and flow distance, i.e. the distance along the runoff flow path from a given point to the outlet, to predict the impact of spatial and temporal variability of precipitation on the flood hydrograph (Emmanuel et al., 2012a;Emmanuel et al., 2012b;Smith et al., 2002;Viglione et al., 2010;Woods and Sivapalan, 1999;Zhang et al., 2001). Based on these works, Zoccatelli et al. (2011) proposed a series of statistics, termed 'spatial moments of catchment rainfall', which are able to isolate the effect of rainfall spatial variability on mean and variance of runoff time. ...
This paper introduces a new methodology and a rainfall spatial organisation index to examine the relative role of hillslope and channel residence times in the analysis of the significance of spatial rainfall representation in catchment flood response modelling. The relationship between the flood response, the hillslope and channel residence time representation and the spatial organisation of the rainfall fields is obtained by extending the 'spatial moments of catchment rainfall' statistics (Zoccatelli et al., 2011) to the hillslope system. The flood prediction error generated by assuming spatially uniform rainfall is related to the spatial organisation of the rainfall fields by means of the scaled spatial moment of order one for the channel network and the hillslope system. The methodology provides a basis for a more general consideration of the relationship between the flood response dependence to spatial rainfall organisation and catchment size. The methodology is illustrated based on data from five extreme flash floods occurred in various European regions in the period 2002-2007. Discharge data are available either from streamgauges or from post-flood surveys for 27 catchments, ranging in size between 36 and 982km2. High space-time resolution radar rainfall fields are also available for the analyses. These data are used to implement a distributed hydrological model simulating the runoff generation by infiltration excess and explicitly representing the surface flow paths across both the hillslopes and the river network. The hydrological model is alternatively forced with spatially-distributed and spatially-uniform rainfall input, to analyse the factors controlling the sensitivity of the model output to the spatial rainfall data. Our results show that the spatial variability of the rainfall can influence the flash-flood hydrographs for catchments as small as 50km2, and that the dependence of flood hydrograph shape to spatial rainfall variability cannot be treated as scale dependent relative to the size of the catchment.The rainfall index can be exploited as similarity index for classifying catchments and flood events according to the hillslopes/channel residence times and to provide guidance on the space and time resolution of the rainfall monitoring system required to predict the flood response.
... As shown in a number of works (Smith et al., 2005Smith et al., , 2002 Woods and Sivapalan, 1999), the river network geometry plays an essential role in the structure of the catchment smoothing properties. Therefore a flow distance coordinate, i.e. the coordinate defined by the distance along the runoff flow path to the basin outlet, has been introduced with the aim of providing information on rainfall spatial organization relative to the basin network structure as represented by the routing time (Borga et al., 2007; Smith et al., 2005; Zhang et al., 2001). Similar works (Smith et al., 2005Smith et al., , 2002 ) have developed dimensionless normalized indicators based on the flow distance coordinate in terms of either routing time or length of flow path (e.g. ...
... Aiming at understanding the interaction between the catchment morphological properties and rainfall organization, Viglione et al. (2010a) (referred as V2010 hereafter) relaxed the assumption the multiplicative space-time separation for rainfall for stationary rainfall, which permitted to analyze the effect of storm motion on flood response. Zoccatelli et al. (2011) (Z2011 hereafter) showed how the analytical approach developed in V2010 was consistent with earlier statistics proposed by Zhang et al. (2001) and Smith et al. (2005). The Z2011 method is linked with two quantities of the hydrograph: (a) the mean runoff time (i.e., the time of the center of mass of the runoff hydrograph at a catchment outlet), and (b) the variance of the timing of runoff (i.e., the temporal dispersion of the runoff hydrograph). ...
... As shown in a number of works (Smith et al., 2005Smith et al., , 2002 Woods and Sivapalan, 1999), the river network geometry plays an essential role in the structure of the catchment smoothing properties. Therefore a flow distance coordinate, i.e. the coordinate defined by the distance along the runoff flow path to the basin outlet, has been introduced with the aim of providing information on rainfall spatial organization relative to the basin network structure as represented by the routing time (Borga et al., 2007; Smith et al., 2005; Zhang et al., 2001). Similar works (Smith et al., 2005Smith et al., , 2002 ) have developed dimensionless normalized indicators based on the flow distance coordinate in terms of either routing time or length of flow path (e.g. ...
... Aiming at understanding the interaction between the catchment morphological properties and rainfall organization, Viglione et al. (2010a) (referred as V2010 hereafter) relaxed the assumption the multiplicative space-time separation for rainfall for stationary rainfall, which permitted to analyze the effect of storm motion on flood response. Zoccatelli et al. (2011) (Z2011 hereafter) showed how the analytical approach developed in V2010 was consistent with earlier statistics proposed by Zhang et al. (2001) and Smith et al. (2005). The Z2011 method is linked with two quantities of the hydrograph: (a) the mean runoff time (i.e., the time of the center of mass of the runoff hydrograph at a catchment outlet), and (b) the variance of the timing of runoff (i.e., the temporal dispersion of the runoff hydrograph). ...
... As shown in a number of works (Smith et al., 2005(Smith et al., , 2002Woods and Sivapalan, 1999), the river network geometry plays an essential role in the structure of the catchment smoothing properties. Therefore a flow distance coordinate, i.e. the coordinate defined by the distance along the runoff flow path to the basin outlet, has been introduced with the aim of providing information on rainfall spatial organization relative to the basin network structure as represented by the routing time (Borga et al., 2007;Smith et al., 2005;Zhang et al., 2001). Similar works (Smith et al., 2005(Smith et al., , 2002 have developed dimensionless normalized indicators based on the flow distance coordinate in terms of either routing time or length of flow path (e.g. ...
... Aiming at understanding the interaction between the catchment morphological properties and rainfall organization, Viglione et al. (2010a) (referred as V2010 hereafter) relaxed the assumption the multiplicative space-time separation for rainfall for stationary rainfall, which permitted to analyze the effect of storm motion on flood response. Zoccatelli et al. (2011 showed how the analytical approach developed in V2010 was consistent with earlier statistics proposed by Zhang et al. (2001) and Smith et al. (2005). The Z2011 method is linked with two quantities of the hydrograph: (a) the mean runoff time (i.e., the time of the center of mass of the runoff hydrograph at a catchment outlet), and (b) the variance of the timing of runoff (i.e., the temporal dispersion of the runoff hydrograph). ...
... 한국방재학회논문집, 제13권 2호 2013년 4월 산정하였다. 도시유역의 지형특성을 이용하여 단위도를 산정 한 연구로 Zhang et al.(2001) 와 Smith et al.(2005) Rodriguez et al.(2003Rodriguez et al.( , 2005 ...
Although urban area is composed of street, pipes and channels, hydraulic elements is included by hydraulic routing at downstream subcatchment in urban stormwater model but the hydraulic elements is ignored and frequently greatly simplified at upstream headwater subcatchment. In this study, we construct a UGMcIUH(Urban Grid based geoMorpho-Climatic Instantaneous Unit Hydrograph), which defines the IUH as the probability density function of the travel time including hydraulic elements in a urban area and evaluate the application for Onchun River. Flow paths are extracted from a spatially processed digital elevation model that incorporates hillslopes, pipes and channels, and travel times are computed in each grid using the average wave celerity from kinematic wave theory. Hydraulic elements in urban catchments has a significant role in determining the travel times and hydrologic response of the watershed.
