Experiment on morphological and hydraulic adjustments of step-pool unit to flow increase

Exceptional flood events with a return period of about 50 years can be destructive to step-pool channel segments. However, field investigations and flume experiments have not examined the hydraulic and morphological feedbacks of step-pool morphology during unsteady hydrographs of exceptional flood events. We performed a series of flume experiments with a manually constructed step model, perturbed with three hydrographs that varied in the rate of water supply change. The bed texture, topography, flow regimes, surface flow field and water depth were characterized and measured as the flow rate was increased during the experiments. A distinct pool feature emerged downstream of the manually constructed step when the flow rate exceeded the threshold scaled to the peaks of ordinary flood events in well-graded mountain streams. The pool feature was modified in several different ways with flow rate increase. The bed surface steadily coarsened, micro-bedforms developed and became more pronounced, the bed topography became more spatially complex based on analysis using the Hurst exponent, and last, pool depth steadily increased. Pool modification was also linked to the flow regime: the impinging jet regime led to grain size segmentation in the pool while the jump regime contributed to decelerating flow velocity. The steeper rising limb of hydrograph led to a less developed pool feature, with smaller sized micro-bedforms in the pool bottom to outlet, and higher discharge threshold for distinct coarsening and scouring in the pool. The estimated energy dissipation within the step-pool unit decreased as a power function from low to high flow, quantified as the ratio h_c/H_S, where h_c is the critical water depth and H_S is scour depth. Our results highlight the interaction between morphology, hydraulics, and energy dissipation of step-pool unit and the crucial role of hydrograph shape on the interaction during flow increase © 2019 John Wiley & Sons, Ltd.     

Assessing the significance of wet-canopy evaporation from forests during extreme rainfall events for flood mitigation in mountainous regions of the United Kingdom

There is increased interest in the potential of tree planting to help mitigate flooding using nature-based solutions or natural flood management. However, many publications based upon catchment studies conclude that, as flood magnitude increases, benefit from forest cover declines and is insignificant for extreme flood events. These conclusions conflict with estimates of evaporation loss from forest plot observations of gross rainfall, through fall and stem flow. This study explores data from existing studies to assess the magnitudes of evaporation and attempts to identify the meteorological conditions under which they would be supported. This is achieved using rainfall event data collated from publications and data archives from studies undertaken in temperate environments around the world. The meteorological conditions required to drive the observed evaporation losses are explored theoretically using the Penman–Monteith equation. The results of this theoretical analysis are compared with the prevailing meteorological conditions during large and extreme rainfall events in mountainous regions of the United Kingdom to assess the likely significance of wet canopy evaporation loss. The collated dataset showed that event Ewc losses between approximately 2 and 38% of gross rainfall (1.5 to 39.4 mm day⁻¹) have been observed during large rainfall events (up to 118 mm day⁻¹) and that there are few data for extreme events (>150 mm day⁻¹). Event data greater than 150 mm (reported separately) included similarly high percentage evaporation losses. Theoretical estimates of wet-canopy evaporation indicated that, to reproduce the losses towards the high end of these observations, relative humidity and the aerodynamic resistance for vapour transport needed to be lower than approximately 97.5% and 0.5 to 2 s m⁻¹ respectively. Surface meteorological data during large and extreme rainfall events in the United Kingdom suggest that conditions favourable for high wet-canopy evaporation are not uncommon and indicate that significant evaporation losses during large and extreme events are possible but not for all events and not at all locations. Thus the disparity with the results from catchment studies remains.     

Modelling Chorabari Lake outburst flood,Kedarnath, India

In this study, the Glacier Lake Outburst Flood(GLOF) that occurred over Kedarnath in June 2013 was modeled using integrated observations from the field and Remote Sensing(RS). The lake breach parameters such as area, depth, breach, and height have been estimated from the field observations and Remote Sensing(RS) data. A number of modelling approaches, including Snow Melt Runoff Model(SRM), Modified Single Flow model(MSF), Watershed Management System(WMS), Simplified Dam Breach Model(SMPDBK) and BREACH were used to model the GLOF. Estimations from SRM produced a runoff of about 22.7 m3 during 16–17, June 2013 over Chorabari Lake. Bathymetry data reported that the lake got filled to its maximum capacity(3822.7 m3) due to excess discharge. Hydrograph obtained from the BREACH model revealed a peak discharge of about 1699 m3/s during an intense water flow episode that lasted for 10–15 minutes on 17 th June 2013. Excess discharge from heavy rainfall and snowmelt into the lake increased its hydrostatic pressure and the lake breached cataclysmically.     

基于GIS/AHP集成的浙江省洪涝灾害风险评估

将GIS技术引入洪涝灾害风险评估,可以弥补传统方法评估结果空间化显示不足的缺点。本文针对浙江省洪涝灾害的发生特点,从危险性和易损性两方面选择了浙江省洪涝灾害的影响因素,包括降雨量、地形、河网密度、人口密度和耕地百分比等因子。运用GIS空间分析技术对各因子进行空间化,结合层次分析法（AHP）确定各影响因素的权重,进行浙江省洪涝灾害风险评估和制图,并基于SuperMap iObjects平台设计与开发了浙江省洪涝灾害风险评估系统。研究结果表明：浙江省发生洪涝灾害的风险普遍偏高,高风险区域位于浙北和浙东南的沿海地带,较高风险区域位于浙东、浙南和浙北地区及金衢盆地中间地区,中等风险区位于浙南的西面、浙北及浙西地区。本文分析结果可为浙江省洪涝灾害预防和管理提供决策依据。     

基于面向对象方法的Sentinel-1A SAR在洪水监测 中的应用

开展Sentinel-1A SAR数据在洪水淹没范围提取和水体变化监测方面的应用研究,对科学有效地管理洪涝灾害有重要意义。合成孔径雷达以其不受天气影响、能穿透云层、覆盖面积广等特点成为灾害监测的重要数据来源。面向对象的方法能有效解决影像的椒盐现象被广泛运用于信息提取研究。本文基于Sentinel-1A SAR数据,利用面向对象的方法构建洪水淹没范围提取流程,绘制灾前、灾中、灾后水体变化监测图,对比分析基于传统像元的提取方法,实现对广西临桂会仙岩溶湿地区域不同时期洪水动态监测。研究表明,Sentinel-1A SAR数据在洪水监测领域有巨大的应用潜力,相较于传统基于像元的方法,面向对象的方法能有效抑制杂斑生成,提高空间信息的利用效率,具有更好的提取精度。     

Flood hydrograph simulation in ungaged basins: modeling linear–nonlinear storage-discharge relationships in a semiarid mountain region

For the purpose of flood mitigation in a mountain region, this study aims to evaluate the degree of nonlinearity in the hydrologic storage-discharge relationship. The study area includes a mesoscale catchment, its headwater subcatchment, and its large-scale parent basin in the Zagros mountain region of southwestern Iran. Rainfall events are divided into two variable classes, Low Temporal (LT) and High Temporal (HT), based on their heterogeneity across time. For Low Temporal rainfall events, the mesoscale catchment and its headwater subcatchment show strong nonlinear behavior, but their responses tend to be less nonlinear for High Temporal rainfall events. Meanwhile, for High Temporal events, soil moisture has a dominant role in catchment response. On the other hand, a different perspective is drawn for the larger basin because a strong nonlinear response is obtained for all events regardless of temporal heterogeneities and soil moisture conditions, emphasizing the filtering effect of catchment extent on the rainfall–runoff process.     

南海休渔期调整的探讨

为更好地保护南海幼鱼资源,文章从渔港抽样调查、模型分析和时令谚语3个方面分析了调整南海休渔期的必要性。2017年的南海渔港抽样调查显示,当年的休渔期延长取得的渔业资源保护效果并不理想,但模型分析支持2017年的休渔新政应是3个半月休渔方案中保持产卵群体存量最好的方案。渔民谚语揭示南海幼鱼集中出现在4月。而目前的南海休渔期仍未能覆盖到幼鱼生长的旺发期。因此,建议现行的南海休渔时间再提前半个月或从4月1日开始休渔,甚至未来尝试在春季休渔,这样既可保护成长中的幼鱼,又可保护产卵中的亲鱼。     

Use of genetic algorithm in new approach to modeling of flood routing

The hydrological models and simpli?ed methods of Saint-venant equations are used extensively in hydrological modeling, in particular for the simulation of the ?ood routing. These models require speci?c and extensive data that usually makes the study of ?ood propagation an arduous practice. We present in this work a new model, based on a transfer function, this function is a function of parametric probability density, having a physical meaning with respect to the propagation of a hydrological signal. The inversion of the model is carried out by an optimization technique called Genetic Algorithm. It consists of evolving a population of parameters based primarily on genetic recombination operators and natural selection to?nd the minimum of an objective function that measures the distance between observed and simulated data. The precision of the simulations of the proposed model is compared with the response of the Hayami model and the applicability of the model is tested on a real case, the N'Fis basin river, located in the High Atlas Occidental, which presents elements that appear favorable to the study of the propagation. The results obtained are very satisfactory and the simulation of the proposed model is very close to the response of the Hayami model.     

山东省平邑县归来庄金矿床充水因素分析及水害治理方向

归来庄金矿床为鲁西南地区唯一特大型金矿床,矿山已经转为地下开采,目前矿山正常涌水量为98491m3/d,矿坑共发生中大型突水56次,其中最大突水点水量高达2000m^3/h,矿山涌水量大,突水频繁,矿坑涌(突)水对矿山深部开采生产安全构成了严重的威胁。该文通过收集以往矿床勘查、核实水文地质资料、地下水连同试验成果、矿山水文地质监测资料并经现场调查,认为该矿山充水来源主要有三个方面:大气降水,地表水(浚河水)和碳酸盐岩裂隙岩溶水,其中碳酸盐岩裂隙岩溶水对矿床直接充水,大气降水和浚河水通过碳酸盐岩含水岩组的导水通道间接补给矿坑。矿山水害治理重点在奥陶系碳酸盐岩类含水岩组的岩溶、构造导水通道,提出了对浚河河床漏水点进行注浆封堵和地下水帷幕注浆截流治水方案。     

Application of tank,NAM, ARMA and neural network models to flood forecasting

Two lumped conceptual hydrological models, namely tank and NAM and a neural network model are applied to flood forecasting in two river basins in Thailand, the Wichianburi on the Pasak River and the Tha Wang Pha on the Nan River using the flood forecasting procedure developed in this study. The tank and NAM models were calibrated and verified and found to give similar results. The results were found to improve significantly by coupling stochastic and deterministic models (tank and NAM) for updating forecast output. The neural network (NN) model was compared with the tank and NAM models. The NN model does not require knowledge of catchment characteristics and internal hydrological processes. The training process or calibration is relatively simple and less time consuming compared with the extensive calibration effort required by the tank and NAM models. The NN model gives good forecasts based on available rainfall, evaporation and runoff data. The black‐box nature of the NN model and the need for selecting parameters based on trial and error or rule‐of‐thumb, however, characterizes its inherent weakness. The performance of the three models was evaluated statistically. Copyright © 2000 John Wiley & Sons, Ltd.