An analytical solution for rapidly predicting post-fire peak streamflow for small watersheds in southern California

Following wildfires, the probability of flooding and debris flows increase, posing risks to human lives, downstream communities, infrastructure, and ecosystems. In southern California (USA), the Rowe, Countryman, and Storey (RCS) 1949 methodology is an empirical method that is used to rapidly estimate post-fire peak streamflow. We re-evaluated the accuracy of RCS for 33 watersheds under current conditions. Pre-fire peak streamflow prediction performance was low, where the average R² was 0.29 and average RMSE was 1.10 cms/km² for the 2- and 10-year recurrence interval events, respectively. Post-fire, RCS performance was also low, with an average R² of 0.26 and RMSE of 15.77 cms/km² for the 2- and 10-year events. We demonstrated that RCS overgeneralizes watershed processes and does not adequately represent the spatial and temporal variability in systems affected by wildfire and extreme weather events and often underpredicted peak streamflow without sediment bulking factors. A novel application of machine learning was used to identify critical watershed characteristics including local physiography, land cover, geology, slope, aspect, rainfall intensity, and soil burn severity, resulting in two random forest models with 45 and five parameters (RF-45 and RF-5, respectively) to predict post-fire peak streamflow. RF-45 and RF-5 performed better than the RCS method; however, they demonstrated the importance and reliance on data availability. The important parameters identified by the machine learning techniques were used to create a three-dimensional polynomial function to calculate post-fire peak streamflow in small catchments in southern California during the first year after fire (R² = 0.82; RMSE = 6.59 cms/km²) which can be used as an interim tool by post-fire risk assessment teams. We conclude that a significant increase in data collection of high temporal and spatial resolution rainfall intensity, streamflow, and sediment loading in channels will help to guide future model development to quantify post-fire flood risk.     

Infiltration and runoff generation processes in fire‐affected soils

Post‐wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire‐affected soils to predict time‐to‐start of runoff and peak runoff rate at the plot scale (1 m²). Time series of soil‐water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one‐dimensional post‐wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high‐resolution (1 mm) estimates of the soil‐water profile and water fluxes within the unsaturated zone. Field and model estimates of the wetting‐front depth indicated that post‐wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, K_s, near the soil surface ranged from 0.1 to 5.2 mm h^?1. Because of the relatively small values of K_s, the time‐to‐start of runoff (measured from the start of rainfall), t_p, was found to depend only on the initial soil‐water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of t_p, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that t_p in fire‐affected soils (which often have low values of K_s) is probably controlled more by the storm profile and the initial soil‐water saturation deficit than by soil hydraulic properties. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

Simple generalization approach for intensity–duration–frequency relationships

Rainfall intensity–duration–frequency (IDF) relationships describe rainfall intensity as a function of duration and return period, and they are significant for water resources planning, as well as for the design of hydraulic constructions. In this study, the two‐parameter lognormal (LN2) and Gumbel distributions are used as parent distribution functions. Derivation of the IDF relationship by this approach is quite simple, because it only requires an appropriate function of the mean of annual maximum rainfall intensity as a function of rainfall duration. It is shown that the monotonic temporal trend in the mean rainfall intensity can successfully be described by this parametric function which comprises a combination of the parameters of the quantile function a(T) and completely the duration function b(d) of the separable IDF relationship. In the case study of Aegean Region (Turkey), the IDF relationships derived through this simple generalization procedure (SGP) may produce IDF relationships as successfully as does the well‐known robust estimation procedure (REP), which is based on minimization of the nonparametric Kruskal–Wallis test statistic with respect to the parameters θ and η of the duration function. Because the approach proposed herein is based on lower‐order sample statistics, risks and uncertainties arising from sampling errors in higher‐order sample statistics were significantly reduced. The authors recommend to establish the separable IDF relationships by the SGP for a statistically favorable two‐parameter parent distribution, because it uses the same assumptions as the REP does, it maintains the observed temporal trend in the mean additionally, it is easy to handle analytically and requires considerably less computational effort. Copyright © 2012 John Wiley & Sons, Ltd.     

Flood hydrograph reconstruction from the peak flow value in ephemeral streams using a simplified robust single‐parameter model

Flood hydrographs from ephemeral streams in arid areas provide valuable information for assessing run‐off and groundwater recharge. However, such data are often scarce or incomplete, especially in hyper‐arid regions. The hypothesis of this study was that it is possible to reconstruct a hydrograph of a specific point along an ephemeral stream with the knowledge of only the peak flow rate of a flood event at that point and that this can be done at almost every point along the stream. The feasibility of this approach lies in the shape of the recession stage of the flood hydrograph, which is known to be a repeating phenomenon. The recession stage comes immediately after the peak flow rate, when it begins its decline, and lasts until the flood is extinguished. A general shape of the flood recession stage can be provided. Because the recession stage represents ~80% of the duration of a flood event, it can provide a general idea of the flood hydrograph's shape. A simple model based on geometric progression is suggested to describe the repeating recession stage of a flood. The advantage of the proposed model is that it requires only one parameter: the recession characteristic at a fixed point along the ephemeral stream, termed recession coefficient q. By knowing the recession coefficient of a fixed point and the peak flow rate of a flood event at that point, one can plot the flood hydrograph. A good agreement is shown between the observed and computed values of the recession stage. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model

The record length and quality of instantaneous peak flows (IPFs) have a great influence on flood design, but these high resolution flow data are not always available. The primary aim of this study is to compare different strategies to derive frequency distributions of IPFs using the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrologic model. The model is operated on a daily and an hourly time step for 18 catchments in the Aller‐Leine basin, Germany. Subsequently, general extreme value (GEV) distributions are fitted to the simulated annual series of daily and hourly extreme flows. The resulting maximum mean daily flow (MDF) quantiles from daily simulations are transferred into IPF quantiles using a multiple regression model, which enables a direct comparison with the simulated hourly quantiles. As long climate records with a high temporal resolution are not available, the hourly simulations require a disaggregation of the daily rainfall. Additionally, two calibrations strategies are applied: (1) a calibration on flow statistics; (2) a calibration on hydrographs. The results show that: (1) the multiple regression model is capable of predicting IPFs with the simulated MDFs; (2) both daily simulations with post‐correction of flows and hourly simulations with pre‐processing of precipitation enable a reasonable estimation of IPFs; (3) the best results are achieved using disaggregated rainfall for hourly modelling with calibration on flow statistics; and (4) if the IPF observations are not sufficient for model calibration on flow statistics, the transfer of MDFs via multiple regressions is a good alternative for estimating IPFs. Copyright © 2015 John Wiley & Sons, Ltd.     

13e SESSION DU COMITÉ CONSULTATIF KARACHI 4–15 NOVEMBRE 1957

Abstract

Event-based methods are used in flood estimation to obtain the entire flood hydrograph. Previously, such methods adopted in the UK have relied on pre-determined values of the input variables (e.g. rainfall and antecedent conditions) to a rainfall–runoff model, which is expected to result in an output flood of a particular return period. In contrast, this paper presents a method that allows all the input variables to take on values across the full range of their individual distributions. These values are then brought together in all possible combinations as input to an event-based rainfall–runoff model in a Monte Carlo simulation approach. Further, this simulation strategy produces a long string of events (on average 10 per year), where dependencies from one event to the next, as well as between different variables within a single event, are accounted for. Frequency analysis is then applied to the annual maximum peak flows and flow volumes.

Citation Svensson, C., Kjeldsen, T.R., and Jones, D.A., 2013. Flood frequency estimation using a joint probability approach within a Monte Carlo framework. Hydrological Sciences Journal, 58 (1), 1–20.     

关于琼东南盆地始新统地层研究的思考

始新统湖相地层是琼东南盆地原油勘探领域的主力烃源岩,历年来各轮资源评价结果均显示具有较好的石油勘探前景,但自1987年Ying9井首次钻遇油层至今,琼东南盆地原油勘探领域一直未取得重大突破。近年来寄予厚望的S3X井钻探失利具有一定典型性,笔者等以S3X井钻后分析为契机,通过与珠江口和北部湾盆地始新统地层对比研究,提出了不同于以往的看法。分析显示琼东南盆地已发现原油中,源于低等水生生物的C304 甲基甾烷含量,以及反映氧化还原条件的姥植比（Pr/Ph）参数,均弱于珠江口和北部湾盆地半深湖相优质烃源岩;琼东南盆地“低频—连续—强振幅”地震相特征与珠江口盆地钻井证实的半深湖相优质烃源岩地震反射特征差异较大;琼东南盆地在区域位置、构造演化与沉积充填模式方面与珠江口和北部湾盆地也存在明显差异,使得始新统湖相地层的分布规模和优质烃源岩的发育条件等方面,均弱于珠江口和北部湾盆地。因此,建议在与周缘盆地始新统地层的对比研究过程中应适度审慎,尤其是以陵水凹陷为代表的中央坳陷带始新统湖相烃源岩分布规模不宜过于乐观。同时,指出受地貌格局影响,不同凹陷海侵进程并不同步,琼东南盆地除始新统发育湖相地层外,渐新统崖城组早期部分凹陷也具有发育湖相地层和油型烃源岩的条件,这一新观点在一定程度可扩展琼东南盆地原油勘探研究的局面和思路。     

温度对土壤介电常数的影响规律研究北大核心CSCD

介电常数是频域反射法测定土样含水率的关键参数之一。为获取温度对土壤介电常数的影响规律,利用矢量网络分析仪测得不同含水率、含盐量的试样在不同试验温度下的介电常数。通过分析土样介电常数随不同因素的变化规律,最后建立了介电常数与温度的关系。结果表明:温度对土样介电常数的影响主要表现在冰水剧烈相变阶段。当温度低于某一温度或者高于冻结温度后,介电常数受温度的影响较小。负温条件下,土样介电常数随含盐量增大而增大。引入阶梯函数建立的三阶段模型,可有效描述土样介电常数随温度的变化规律。     

超大型离心机基础自振特性研究

某超大型离心机基础埋置于复杂软土地基中,自振特性研究十分关键。分别建立离心机基础的等效土弹簧模型和实体地基模型,对比分析不同地基模拟方法下的模态分析结果;开展基于白噪声激励的动力时程分析,分析地基参振质量对自振特性的影响。结果表明：超大型离心机基础前两阶模态振型分别为水平横向和纵向的摆动;基于不同的地基模拟方法计算得到的振型结果一致,自振频率相差在10%以内;超大型离心机基础结构的前两阶地基参振质量分别为1.376倍和0.998倍的基础总质量,地基参振质量使得结构的振动响应幅值下降50%左右,频谱峰值频率减小约2 Hz。结论对大型埋置式动力机器基础的自振特性研究具有指导和参考意义。     

基于HEC-RAS及GIS的川西叠溪古滑坡堰塞湖溃决洪水重建

青藏高原东南缘岷江上游地区地质环境条件十分复杂,滑坡堵江灾害及堰塞湖溃决事件频发,重建其灾害演化过程对于地区性防灾减灾和风险控制具有重要指导意义。以川西岷江上游叠溪古滑坡堰塞湖为研究对象,首先利用高精度DEM和ArcGIS软件重建了叠溪古堰塞湖的原始规模,其原始最大湖水面积为1.1×10⁷ m²,相应的湖容量为2.9×10⁹ m³;然后采用经验公式法和HEC-RAS一维水力学模型重建叠溪古堰塞湖溃决洪水的水力学特征。计算结果表明,HEC-RAS模拟的最大溃决洪水洪峰流量为73 060 m³/s,与经验公式法计算结果(74 500~76 800 m³/s,平均值76 000 m³/s)非常接近,误差小于5%。对应的最大洪水深度和流速分别为70.1 m和16.78 m/s,模拟河段的洪水淹没范围约为6.08 km²。综合误差分析推测的溃决洪峰流量误差范围为69 000~81 000 m³/s。叠溪古滑坡堰塞湖溃决洪水在世界范围内是十分罕见的,其最直接的影响是在下游数公里范围的河谷内形成大量带状或台阶状的溃坝堆积体和巨砾石堆积“阶地”,且这种影响仍延续至今,这与前人关于高能洪水水文特征和沉积特征的研究认识高度一致,证明本研究成果是非常可靠的。此外,本研究还表明,HEC-RAS一维水力模型可用于高山峡谷地区古滑坡堰塞湖溃决洪水重建研究,可为青藏高原东南缘岷江上游古环境重建和地貌演化提供参考。