Flood occurrence hazard forecasting based on geographical information system

The application of Geographical Information system (GIS) in modeling flood and its prediction in catchments offers considerable potential. Several examples illustrate simple GIS techniques to produce flood hazard indices or its zonation using hydrologic-type models. Existing flood models can also be loosely coupled to a GIS, such as the HMS (Hydrological Modeling System) model. Forethermore, models can be fully integrated into a GIS by embedded coupling, such as the SCS (Soil Conservation Service) model. Installation of flood forecasting systems in watersheds with incomplete hydrometric data may reduce the flood-induced damages. In this study Geographical Information system used to up to date the watershed data and estimation of SCS model parameters which is sensible to considered the real time flood forecasting in Kasilian catchment of Mazandaran province. The main aim of this paper is to investigate the possibility of the linkage between GIS with a comprehensive hydrologic model, especially HMS. The use of GIS could produce a suitable agreement between observed results (extracted rainfall and runoff data of 1992, 1995 and 1996 from the related stations) with the calculated results of the hydrological model. The obtained results from rainfall-runoff process simulations of the model in this research showed that submergibility of the main watershed, Kasillian, does not depend on the outlet discharge rate of each one of its watershed independently. But it is related to how those two outlet hydrographs from main river watershed are combined. The model is capable of showing the flood characteristics temporally and spatially in each cross section of the channel network.     

A regional real-time debris-flow warning system for the District of North Vancouver, Canada

Engineered (structural) debris-flow mitigation for all creeks with elements at risk and subject to debris flows is often outside of the financial capability of the regulating government, and heavy task-specific taxation may be politically undesirable. Structural debris-flow mitigation may only be achieved over long (decadal scale) time periods. Where immediate structural mitigation is cost-prohibitive, an interim solution can be identified to manage residual risk. This can be achieved by implementing a debris-flow warning system that enables residents to reduce their personal risk for loss of life through timely evacuation. This paper describes Canada??s first real-time debris-flow warning system which has been operated for 2 years for the District of North Vancouver. The system was developed based on discriminant function analyses of 20 hydrometric input variables consisting of antecedent rainfall and storm rainfall intensities for a total of 63 storms. Of these 27 resulted in shallow landslides and subsequent debris flows, while 36 storms were sampled that did not reportedly result in debris flows. The discriminant function analysis identified as the three most significant variables: the 4-week antecedent rainfall, the 2-day antecedent rainfall, and the 48-h rainfall intensity during the landslide-triggering storm. Discriminant functions were developed and tested for robustness against a nearby rain gauge dataset. The resulting classification functions provide a measure for the likelihood of debris-flow initiation. Several system complexities were added to render the classification functions into a usable and defensible warning system. This involved the addition of various functionality criteria such as not skipping warning levels, providing sufficient warning time before debris flows would occur, and hourly adjustment of actual rainfall vs. predicted rainfall since predicted rainfall is not error-free. After numerous iterations that involved warning threshold and cancelation refinements and further model calibrations, an optimal solution was found that best matches the actual debris-flow data record. Back-calculation of the model??s 21-year record confirmed that 76% of all debris flows would have occurred during warning or severe warning levels. Adding the past 2 years of system operation, this percentage increases marginally to 77%. With respect to the District of North Vancouver boundaries, all debris flows occur during Warning and Severe Warnings emphasizing the validity of the system to the area for which it was intended. To operate the system, real-time rainfall data are obtained from a rain gauge in the District of North Vancouver. Antecedent rainfall is automatically calculated as a sliding time window for the 4-week and 2-day periods every hour. The predicted 48-h storm rainfall data are provided by the Geophysical Disaster Computational Fluid Dynamics Centre at the Earth and Ocean Science Department at the University of British Columbia and is updated every hour as rainfall is recorded during a given storm. The warning system differentiates five different stages: no watch, watch level 1 (the warning level is unlikely to be reached), watch level 2 (the warning level is likely to be reached), warning, and severe warning. The debris-flow warning system has operated from October 1, 2009 to April 30, 2010 and October 1, 2010 and April 30, 2011. Fortunately, we were able to evaluate model performance because the exact times of debris flows during November 2009 and January 2010 were recorded. In both cases, the debris flows did not only occur during the warning level but coincided with peaks in the warning graphs. Furthermore, four debris flows occurred during a warning period in November 2009 in the Metro Vancouver watershed though their exact time of day is unknown. The warning level was reached 13 times, and in four of these cases, debris flows were recorded in the study area. One debris flow was recorded during watch II level. There was no severe warning during the 2 years of operation. The current warning level during the wet season (October to April) is accessible via District of North Vancouver??s homepage (www.dnv.org) and by automated telephone message during the rainy season.     

Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m³ km^?2 year^?1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m³ km^?2 year^?1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.     

An integrated model to assess critical rainfall thresholds for run-out distances of debris flows

A dramatic increase in debris flows occurred in the years after the 2008 Wenchuan earthquake in SW China due to the deposition of loose co-seismic landslide material. This paper proposes a preliminary integrated model, which describes the relationship between rain input and debris flow run-out in order to establish critical rain thresholds for mobilizing enough debris volume to reach the basin outlet. The model integrates in a simple way rainfall, surface runoff, and concentrated erosion of the loose material deposited in channels, propagation, and deposition of flow material. The model could be calibrated on total volumes of debris flow materials deposited at the outlet of the Shuida catchment during two successive rain events which occurred in August 2011. The calibrated model was used to construct critical rainfall intensity-duration graphs defining thresholds for a run-out distance until the outlet of the catchment. Model simulations show that threshold values increase after successive rain events due to a decrease in erodible material. The constructed rainfall intensity-duration threshold graphs for the Shuida catchment based on the current situation appeared to have basically the same exponential value as a threshold graph for debris flow occurrences, constructed for the Wenjia catchment on the basis of 5 observed triggering rain events. This may indicate that the triggering mechanism by intensive run-off erosion in channels in this catchment is the same. The model did not account for a supply of extra loose material by landslips transforming into debris flow or reaching the channels for transportation by run-off. In August 2012, two severe rain events were measured in the Shuida catchment, which did not produce debris flows. This could be confirmed by the threshold diagram constructed by the model.     

基于小流域的地震扰动区降雨型滑坡泥石流危险性评价方法

地震扰动区存在大量震裂松散坡体,在持续或者密集的降雨条件下极易转化为滑坡灾害。同时,滑坡又会给泥石流提供大量松散固体物质,增加泥石流的危险性。因此,在震区,灾害通常以"链"的形式出现,比单一灾种危害性大。为了更有效地对地质灾害危险性进行评价,笔者将滑坡、泥石流作为灾害链,综合地加以分析和研究。选择5·12汶川大地震中受灾严重的都江堰市白沙河流域的17条泥石流沟作为研究区,建立滑坡-泥石流危险性评价耦合模型,研究24 h不同降雨量条件下小流域滑坡泥石流危险性的变化。耦合模型包括了坡体稳定性评价模型,水文模型及以泥石流规模、发生频率、流域面积、主沟长度、流域高差、切割密度、不稳定斜坡比为评价因子的泥石流危险性评价统计模型。研究结果表明:随着降雨量的增大,参与泥石流活动的松散物质方量持续增加,但当24 h降雨量超过200 mm后,泥石流沟的危险度等级不再发生变化;17条泥石流沟中4条为中危险度,12条为高危险度,1条为极高危险度。这说明研究区地质灾害问题相当严峻,在多雨季节存在泥石流群发的可能性,直接威胁到居住在泥石流沟附近的人民群众生命财产安全;因此,对于有直接危害对象的高危险度及其以上的泥石流沟,应该按照高等级设防标准进行工程治理及发布预警报。同时也说明,将滑坡、泥石流作为灾害链研究具必要性和可行性。     

分布式降雨径流物理模型的建立和应用

根据流域降雨径流的主要过程,考虑流域气象及下垫面要素的空间异质性,建立了具有物理基础的分布式降雨径流模型。模型将流域离散为栅格计算单元,并按水流特性分栅格单元为坡面单元和河网单元。在坡面单元上主要计算降雨、下渗、坡面流、壤中流等水文过程,而河网单元则主要计算河道汇流过程。模型利用空间权重插值方法将雨量站点的降雨量插值到各个计算单元,采用运动波方程来计算坡面流,将壤中流概化为垂向流和侧向流,分别用Green-Ampt公式和运动波方程来模拟,河道汇流也采用运动波方程。模型结构简单、参数的物理意义明确,大多数参数可利用DEM、土壤类型图、植被类型图直接获取,少数敏感参数通过率定确定。模型在浙江省甬江上游黄土岭流域和皎口流域进行了应用和检验,其结果令人满意。     

南水北调中线工程水源林生态系统对水质的影响——以秦岭南坡中山地带火地塘林区为例

通过对秦岭南坡中山地带火地塘林区大气降水与支沟溪流水和流域出口径流水质的比较分析,以及溪流水和流域出口径流水质与水量的相关分析,发现7~10月份大气降水呈微酸性,经过森林生态系统的调节,径流pH值升高,且不随流量变化而发生变化;森林生态系统对随降水输入的NO₃-、NH₄+、PO₄3-有很好的净化作用,这种作用对于降低南水北调中线工程取水地丹江口水库水质富营养化的威胁非常有益,对重金属元素Cd、Pb、Mn有固定作用;对K、Na、Ca、Mg、Fe有增加作用,尤其对Ca、Mg含量增幅较大,但这种作用不会对水质产生不良影响,对Fe的调升有利于水质改善;森林生态系统在调减Zn含量方面作用显著;林区径流水质与水量之间并无较大关系,水质不随水量变化而发生较大变化,森林生态系统对水质有很好的稳定作用。     

Erosion risk assessment and sediment yield production of the King Talal Watershed, Jordan

 King Talal Dam (KTD) watershed is the most important one in Jordan. At its outlet lies the KTD (80 MCM capacity) which serves irrigation purposes in the Jordan Valley. However, the dam suffers from accelerated annual sedimentation. Therefore, this study is directed to assess the erosion risk over the watershed, and to simulate actual annual sediment yield at the dam in order to devise the appropriate conservation practices. Generalized assessment was first conducted over the watershed on the basis of drainage texture, rainfall erosion index (R), and the ratio p²/P. As a result, the watershed is divided into zones of severe, high (gullying), high (overland flow) and low erosion risk. Sediment yield at the dam was evaluated by a simulation model. For model validation the simulation results were compared to the measured values over 12 years period, and a good agreement was obtained in some of the years. The simulation results allow us to assess the application of two practical conservation practices: terracing and plantation of trees. Received: 18 November 1997 · Accepted: 18 May 1998     

Adequacy of satellite derived rainfall data for stream flow modeling

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. G. Artan, J. L. Smith and K. Asante – work performed under USGS contract 03CRCN0001.     

Evaluation of rainfall spatial correlation effect on rainfall-runoff modeling uncertainty,considering 2-copula

Lack of accuracy of rainfall-runoff simulation (RRS) remains critical for some applications. Among various sources of uncertainty, precipitation plays a particular role. Rainfall rates as the main input data of RRS are of the first factors controlling the accuracy. In addition to the depth, spatial and temporal distributions of rainfall impact the flood discharge. Most of the previous studies on RRS uncertainty have ignored rainfall spatial distribution, where in large catchments, it is necessary to be modeled explicitly. Karoon III is one most important basin of the Iran because of the Karoon III dam in the outlet. In the present work, effect of spatial correlation of rainfall on HEC-HMS (SMA) continuous RRS uncertainty is evaluated using 2variate copula (2copula). Monte Carlo simulation (MCS) approach was used to consider the rainfall spatial dependence. To reduce the computational expense, sampling efficiency and convergence for MCS, Latin hypercube sampling (LHS) was used. Copula functions consider wide range of marginal probability distribution functions (PDFs), eliminating limits of regular join PDFs. For this aim, two scenarios were investigated. In the first scenario, sub-basin rainfall was considered independent, and in the second scenario, 2copula was adopted to model spatial correlation of rainfall. Dimensionless rainfall depths were calculated for each sub-basin, and the PDFs were determined. The generated random dimensionless rainfalls were reweighted and multiplied by watershed’s mean rainfall value. Stochastic Climate Library was used to generate continuous daily rainfalls. Sampling from dimensionless rainfalls using LHS algorithm, 100 runs of calibrated model-simulated 100 flows for each day following MCS, and 80 % certainty bound was calculated. Results showed that considering dependence decreased 18 % of the maximum uncertainty bound width, so the methodology could be recommended for decreasing predicted runoff error.     

兰州市寺儿沟泥石流物源特征及其危险性分析

寺儿沟流域位于甘肃省兰州市西固区, 历史上曾发生过大规模泥石流, 造成重大人员伤亡和财产损失。文章基于野外调查和遥感解译, 结合已有文献成果和室内测试, 研究寺儿沟泥石流物源特征及影响因素, 采用FLO-2D软件模拟分析泥石流的危险性。研究结果表明: 寺儿沟以黏性泥石流为主, 表现为低频活动, 目前处于衰退期; 寺儿沟流域内物源丰富, 可分为坡面型物源、崩滑型物源、沟道型物源和人为型物源共4种, 其中崩滑型、沟道型物源控制了泥石流的暴发规模; 而一次性冲出量的大小主要取决于泥石流起动时崩滑体的发育程度, 崩滑体越发育, 一次性冲出量越大, 泥石流规模越大; 在临界降雨条件下, 寺儿沟将会暴发泥石流, 中—高危险区集中于流通区, 严重威胁冲沟内构筑物如兰西高铁、环城高速等安全运营。当遭遇极端强降雨时, 寺儿沟将暴发更大规模泥石流。因此, 有必要进一步研究极端天气条件下泥石流的危险性, 为区内泥石流的防灾减灾提供地质依据。      

新疆玛纳斯河流域洪水预报研究

在充分考虑了融雪径流型河流自身特点的基础上,将自回归滑动平均模型ARMA(p,q),概化为ARMA(p,1),并运用最小信息(AIC)准则,确定模型的最佳阶数p,运用修正的可变遗忘因子递推最小二乘法,进行参数的动态修正,达到了最佳参数的跟踪效果.通过在玛纳斯河流域应用,表明该模型具有较高的预报精度,其确定性系数均达到了0.90以上,径流总量相对误差控制在7%以下,洪峰流量相对误差<10%,峰现时差≤2.     

鄱阳湖湖口河段近期演变规律及趋势分析

湖口河段是鄱阳湖流域水量汇入长江的唯一出口,也是江西与外界航运交通的咽喉,其演变情势直接影响流域防洪和航运安全。利用历次实测的水下地形图及湖口水文站实测断面资料,对河道冲淤、纵向及平面变化进行了分析。结果表明:湖口河段左岸滩地以淤积为主,主河槽及深泓线近期冲刷较严重,右岸受地形约束基本保持稳定。在未来一定时期内,河段岸线仍将保持相对稳定,并将维持左岸滩地淤积,主河槽和右岸冲刷的趋势。     

The formation and development of debris flows in large watersheds after the 2008 Wenchuan Earthquake

The Wenchuan earthquake has caused abundance of loose materials supplies for debris flows. Many debris flows have occurred in watersheds in area beyond 20 km², presenting characteristics differing from those in small watersheds. The debris flows yearly frequency decreases exponentially, and the average debris flow magnitude increases linearly with watershed size. The rainfall thresholds for debris flows in large watersheds were expressed as I?=?14.7 D ^?0.79 (2 h?<?D?<?56 h), which is considerably higher than those in small watersheds as I?=?4.4 D ^?0.70 (2 h?<?D?<?37 h). A case study is conducted in Ergou, 39.4 km² in area, to illustrate the formation and development processes of debris flows in large watersheds. A debris flow develops in a large watershed only when the rainfall was high enough to trigger the wide-spread failures and erosions on slope and realize the confluence in the watershed. The debris flow was supplied by the widely distributed failures dominated by rill erosions (14 in 22 sources in this case). The intermittent supplying increased the size and duration of debris flow. While the landslide dam failures provided most amounts for debris flows (57 % of the total amount), and amplified the discharge suddenly. During these processes, the debris flow velocity and density increased as well. The similar processes were observed in other large watersheds, indicating this case is representative.     

袁河流域水环境容量分析的设计水文条件计算

设计水文条件是流域水环境容量分析的重要前提,然而在一些小流域,水文站点相对较少,给设计水文条件计算带来一定难度。本文采用区域化方法,以袁河流域为例,根据其现有的水文站及其毗邻锦江流域水文站的水文资料采用一元线性函数建立了设计流量和集水面积的关系,采用幂指函数Y=aQb分别建立了流量与流速、平均水深及河宽的关系。根据建立的模型对袁河流域各控制断面的设计流量、设计流速、平均水深及河宽进行了计算,从而为水文站较少流域设计水文条件的计算提供了范例。     

Impact of suspended sediment load on the silting of SMBA reservoir (Algeria)

The phenomenon of suspended sediment load is very complex in Mina River basin because of its important soil heterogeneity, vegetation deficiency and rainfall variability in time and space. The methodological approach adopted in this paper consists of finding a regressive power model, which may explain better the suspended sediment discharge as a function of the flow discharge collected at Wadi El-Abtal and Sidi AEK Djilali hydrometric stations by studying this relation at various temporal scales: daily, annual, monthly and seasonal. The obtained monthly power relations, explaining the greatest part of the variance, lead to interpolate, extrapolate and analyse suspended and bed loads deposited on Sidi M’hamed Ben Aouda (SMBA) reservoir since being in service in 1977/1978. These allow authors to find relations between specific erosion and effective rainfall and propose some solutions for river basin managers and policy makers to reduce the silting of SMBA reservoir.     

汶川震区暴雨泥石流危险范围预测研究

汶川地震发生后,灾区暴雨泥石流活动进入一个新的活跃期。根据对北川震区2008年9月24日暴雨泥石流调查,泥石流流域中地震诱发大量滑坡导致松散物源巨大,泥石流过程的洪峰流量比通常的要大数倍,应用以往泥石流危险范围预测模型进行计算的结果与实际的误差较大。因此,需要建立适用于强震区的泥石流危险范围预测方法。本文以9.24北川暴雨泥石流为典型实例,结合野外调查,利用震后高分辨航空图像和9.24暴雨后SPOT5图像分别提取泥石流发生前流域中滑坡物源储量及发生后形成的堆积扇特征数据,应用多元回归方法建立了汶川震区泥石流危险范围预测模型,该方法可用于估算泥石流最大堆积距离和堆积宽度。验证和应用结果表明:该模型适用于强震区泥石流危险范围的预测,模型方法可为震区重建中安全地段选择和未来地震区风险管理提供重要依据。     

Estimating aquifer recharge in Mission River watershed, Texas: model development and calibration using genetic algorithms

Soil moisture balance studies provide a convenient approach to estimate aquifer recharge when only limited site-specific data are available. A monthly mass-balance approach has been utilized in this study to estimate recharge in a small watershed in the coastal bend of South Texas. The developed lumped parameter model employs four adjustable parameters to calibrate model predicted stream runoff to observations at a gaging station. A new procedure was developed to correctly capture the intermittent nature of rainfall. The total monthly rainfall was assigned to a single-equivalent storm whose duration was obtained via calibration. A total of four calibrations were carried out using an evolutionary computing technique called genetic algorithms as well as the conventional gradient descent (GD) technique. Ordinary least squares and the heteroscedastic maximum likelihood error (HMLE) based objective functions were evaluated as part of this study as well. While the genetic algorithm based calibrations were relatively better in capturing the peak runoff events, the GD based calibration did slightly better in capturing the low flow events. Treating the Box-Cox exponent in the HMLE function as a calibration parameter did not yield better estimates and the study corroborates the suggestion made in the literature of fixing this exponent at 0.3. The model outputs were compared against available information and results indicate that the developed modeling approach provides a conservative estimate of recharge.     

Risk degree of debris flow applying neural networks

A number of methods for prediction of debris flows have been studied. However, the successful prediction ratios of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for risk degree predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 171 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 99.12% demonstrates that the presented ANN model with seven significant factors can provide a highly stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

A prediction model for debris flows triggered by a runoff-induced mechanism

Many debris flows were triggered within and also outside the Dayi area of the Guizhou Province, China, during a rainstorm in 2011. High-intensity short-duration rainfall was the main triggering factor for these gully-type debris flows which are probably triggered by a runoff-induced mechanism. A revised prediction model was introduced for this kind of gully-type debris flows with factors related to topography, geology, and hydrology (rainfall) and applied to the Wangmo River catchment. Regarding the geological factor, the “soft lithology” and “loose sediments” in the channel were added to the list of the average firmness coefficient for the lithology. Also, the chemical weathering was taken into account for the revised geological factor. Concerning the hydrological factor, a coefficient of variation of rainfall was introduced for the normalization of the rainfall factor. The prediction model for debris flows proposed in this paper delivered three classes of the probability of debris flow occurrence. The model was successfully validated in debris flow gullies with the same initiation mechanism in other areas of southwest China. The generic character of the model is explained by the fact that its factors are partly based on the initiation mechanisms and not only on the statistical analyses of a unique variety of local factors. The research provides a new way to predict the occurrence of debris flows initiated by a runoff-induced mechanism.