干旱气候因子与森林火灾

森林火灾作为一种自然灾害, 气候变化直接或间接影响森林燃烧的火环境, 进而对火发生和火行为产生影响. 干旱气候条件与森林火灾的发生有密切的关系, 气象条件通过气温、 日照、 蒸发量、 风力、 空气湿度等影响着森林火灾的发生和发展. 一般情况下, 气温高、 降水少、 湿度小、 风力大易发生森林火灾. 在山区, 山谷风和地形影响森林火灾蔓延, 森林火灾的蔓延主要受山谷风所控制, 具有间歇性, 另外地形的变化在很大程度上制约着火势的蔓延. 所以, 要利用不同时段的气象条件、 山风出现的时间及有利地形, 及时组织灭火和控制火势蔓延. 森林火灾的发生有各种类型, 通过对森林火灾中一些特殊火行为及相关元素对火灾发展蔓延影响分析, 找出森林火灾扑救与逃生的方法及注意事项.     

Forest fire risk mapping of Kolli Hills, India, considering subjectivity and inconsistency issues

Forest fires have adverse ecological, economic, and social impacts. In this light, the present research aimed, first, to construct a fire risk model using a GIS-based multi-criteria analysis and second, to derive a forest fire risk modeling strategy that alleviates the problem of inconsistency in the assigning of scores and weights to forest fire categories and layers. Third, the local-orientation effects and causes, which are relevant to the subjectivity problem, were investigated by comparing the risk scoring and weighting outcomes from Indian and Korean expert groups (IEG and KEG). Fourth, forest fire factors that can be considered regional and global also were investigated. Kolli Hills, India, was selected as the study area in this research. In the interests of alleviating the inconsistency problem, a weighting and scoring scheme based on the analytic hierarchy process was applied. The experiences from the existence of prevailing westerly winds, the most common forest types (i.e., in Korea: pine trees), and the different anthropogenic pressures between Korea and India resulted in the different scoring and weighting decisions of the two expert groups. Among the five fire risk factors, slope, road, and settlement can be considered to be global factors. On the other hand, forest cover and aspect are regional factors that can be more influenced by local environmental conditions. When considering the producer’s accuracy, the approach of the IEG together with the natural breaks thresholding method provided the best fire risk mapping result. On the other hand, the model from the IEG with equal interval provided the best result from the viewpoint of user’s accuracy and overall accuracy. Overall, this paper proposes a forest fire risk mapping procedure as basis for developing a global forest fire risk modeling in the future, where a series of standardized modeling steps and variables should be defined.     

Simulation-based optimization of emergency evacuation strategy in ultra-high-rise buildings

Emergency evacuation in high-rise buildings is a crucial problem. The evacuation strategy of using stairs and evacuation elevators should be optimized. In this paper, simulation-based optimization method is used to optimize the evacuation strategy of using stairs and elevators in high-rise buildings. The stair simulation is based on a cellular automata model, and several typical pedestrians’ walk preferences are considered in this model. In the simulation, evacuation elevators can arrive at the refuge floors, and the scheduling of the elevators is optimized based on the GA algorithm. The simulation-based optimization is designed as a two-level problem: The upper level is a strategy level; the lower level is an operation level. In the study case, the evacuation strategy of a 100-floor ultra-high-rise office building is optimized. We find that if evacuees follow the traditional stair evacuation strategy, the evacuation time is 42.6 min. After optimization, the evacuation time of optimal strategy by using both stairs and elevators is 25.1 min. Compared with the traditional stair evacuation strategy, the efficiency of evacuation is improved by 41.1%. It is also found that the merging behavior in stairwells will decrease the velocity of the pedestrian flow. Stairs are still the main egress, and evacuation elevators are an assistant egress during high-rise building evacuation.     

Simulation of seismic-prospecting random noise in the desert by a Brownian-motion-based parametric modeling algorithm

Random noise has a negative impact on seismic-prospecting record processing. An important step to improve the methods aimed at the attenuation of random noise is to scientifically characterize the properties of the noise. Numerical modeling is useful to understand the nature of the random noise. In this study, we present a Brownian-motion-based parametric modeling algorithm for the simulation of seismic-prospecting random noise in the desert. The optimal Hurst exponent required to implement the method can be determined by comparing the spectral properties related to the noise data and the simulated results. The data used to analyze the properties of the noise were acquired in the Tarim Basin (Northwest of China). We verify the performance of the modeling algorithm by comparing the results obtained after the simulation with the real noise data in both the time domain and the spatio-temporal domain. The experimental results thus obtained prove the accuracy and efficiency of the proposed modeling algorithm. This study can be used as a basis to investigate the seismic-prospecting random noise characteristics and thus contribute to its mitigation.     

A new approach for forest fire risk modeling using fuzzy AHP and GIS in Hyrcanian forests of Iran

The presented research was performed in order to model the fire risk in a part of Hyrcanian forests of Iran. The fuzzy sets integrated with analytic hierarchy process (AHP) in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. The used factors included four major criteria (topographic, biologic, climatic, and human factors) and their 17 sub-criteria. Fuzzy AHP method was used for estimating the importance (weight) of the effective factors in forest fire. Based on this modeling method, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas mean was analyzed based on fuzzy extent analysis. Then, the fuzzy weights of criteria and sub-criteria were obtained. The major criteria models and fire risk model were presented based on these fuzzy weights. On the other hand, the spatial data of 17 sub-criteria were provided and organized in GIS to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risk of its classes to fire occurrence. Then, all sub-criteria maps were converted to fuzzy format using fuzzy membership function in GIS. The fuzzy map of each major criterion (topographic, biologic, climatic, and human criteria) was obtained by weighted overlay of its sub-criteria fuzzy maps considering to major criterion model in GIS. Finally, the fuzzy map of fire risk was obtained by weighted overlay of major criteria fuzzy maps considering to fire risk model in GIS. The actual fire map was used for validation of fire risk model and map. The results showed that the fuzzy estimated weights of human, biologic, climatic, and topographic criteria in fire risk were 0.301, 0.2595, 0.2315, and 0.208, respectively. The results obtained from the fire risk map showed that 38.74% of the study area has very high and high risk for fire occurrence. Results of validation of the fire risk map showed that 80% of the actual fires were located in the very high and high risk areas in fire risk map. It can show the acceptable accuracy of the fire risk model and map obtained from fuzzy AHP in this study. The obtained fire risk map can be used as a decision support system for predicting of the future fires in the study area.     

基于CA的小流域分布式降雨径流模拟

构建基于元胞自动机(CA)模型的分布式水文模型,模拟小流域内降雨径流过程。从元胞状态、转换规则与时间步长3个方面扩展普通CA模型,包括5个子状态、5个元胞系数及两条转换规则,并实现模型与GIS的集成。以黄土高原岔巴沟流域的降雨径流观测数据对模型进行了验证分析。试验结果表明,确定性系数、峰现时差与洪峰误差3个评价指数都达到一定精度,实现了流域内径流过程的可视化。结合CA模型与GIS技术可以较为有效地模拟流域次降雨径流过程,模型在该试验区是基本适用的。     

基于MapGIS的森林防火监测预警系统设计与实现

快速、准确的进行林火火源监测及定位可以有效缩短扑救时间,降低林业资源损失和自然环境污染.为了解决这一问题,采用地理信息系统(geographic information system, GIS)和遥感(remote sensing, RS)作为研究手段、运用实例研究的方法,以MapGIS开发平台为基础,设计并开发“森林防火监测预警系统”.“遥感影像定位”和“视频图像定位”作为两种常用的监测定位手段,可以从宏观和微观的不同角度互补;火险等级预报为监测重点提供参考依据;火势推演分析紧密结合气象信息和植被信息模拟火场扩散情况.结果表明,GIS在森林防火监测定位方面不仅有着良好的可视性,其强大的空间分析特性尤为突出,对促进森林防火管理的信息化、科学化起到十分重要的作用.      

Considerations for modeling burn probability across landscapes with steep environmental gradients: an example from the Columbia Mountains, Canada

Fire and land management in fire-prone areas can be greatly enhanced by estimating the likelihood of fire at every point on the landscape. In recent years, powerful fire simulation models, combined with an in-depth understanding of an area’s fire regime and fire environment, have allowed forest managers to estimate spatial burn probabilities. This study describes a methodology for selecting input data and model parameters when creating burn probability maps in difficult-to-model areas and reports the results of a case study for a large area of the Columbia Mountains, British Columbia, Canada. In addition to having particularly mountainous topography, the study area is covered by vegetation types that are poorly represented in fire behavior systems, even though these vegetation types have experienced considerable (if highly irregular) fire activity in premodern times (before 1920). Parameterization of the fire environment for simulation modeling was accomplished by combining various types of fire information (e.g., fire history studies, reconstructed fire climatologies), new technologies (high-resolution remotely sensed data, wind flow modeling), and—a must in data-limited areas—ample expert advice. In this study, we made extensive use of personal accounts from experienced fire behavior officers for the creation of model inputs. Despite difficulties in validating outputs of burn probability models, the multisource model-building approach described here provides a conservative, yet informative, means of estimating the likelihood of fire. Due to the data-intensive nature of the modeling and paucity of input data, an argument is made that modelers must focus on the inputs that are the most influential for their study area.     

水流模拟智能化问题的探讨

对水流模拟的发展历史进行了总结,指出阻碍水流模拟发展的主要问题,提出克服这些瓶颈问题的方法是将智能科学与水利科学交叉融合,实现水流的智能模拟。据此,介绍了水流智能模型理论,结合遗传算法、模糊逻辑、元胞自动机、混沌分析理论、人工神经网络、专家系统、数据挖掘等智能理论和技术,对水流智能模拟的实现途径作了探讨,并指出建造一个优秀的水流模拟智能系统的关键是联合运用各种智能方法,认为智能化是当前水流模拟发展的新方向,水流智能模型将是水利科学的一种新的研究途径,并将在研究水流问题上具有广阔的应用前景。     

Evaluating the persistence of post‐fire residual patches in the eastern Canadian boreal mixedwood forest

In boreal forest ecosystems, wildfire severity (i.e. the extent of fire‐related tree mortality) is affected by environmental conditions and fire intensity. A burned area usually includes tree patches that partially or entirely escaped fire, called ‘residual patches’. Although the occurrence of residual patches has been extensively documented, their persistence through time, and thus their capacity to escape several consecutive fires, has not yet been investigated. Macroscopic charcoal particles embedded in organic soils were used to reconstruct the fire history of 13 residual patches of the eastern Canadian boreal mixedwood forest. Our results display the existence of two types of residual patches: (i) patches that only escaped fire by chance, maybe because of local site or meteorological conditions unsuitable for fire spread (random patches), and (ii) patches with lower fire susceptibility, also called ‘fire refuges’ that escaped at least two consecutive fires, probably because of particular site characteristics. Fire refuges can escape fire for more than 500 years, up to several thousand years, and probably burn only during exceptionally severe fire events. Special conservation efforts could target fire refuges owing to their old age, long ecological continuity and potential specific biological diversity associated to different microhabitats.     

基于变步长加速搜索的微震源定位方法

微震定位方法是微震监测技术的重要组成部分,其关键是定位震源位置。利用空间网格划分并计算网格交点目标函数值,对微震定位目标函数二维及三维空间分布进行了分析,并据此获取了目标函数连续且极小值唯一、单轴收敛范围逐步减小、各轴收敛范围不一的规律。利用以上规律及模式搜索法、网格搜索法的优缺点,探索出了基于连续比较模块、变步长模块、加速模块的变步长加速搜索法。通过模拟算例与工程数据下收敛稳定性、结果精确度、计算速度以及参数初始值影响程度4个指标的效果对比,结果表明：模拟算例下,对比模拟退火算法、遗传算法,变步长加速搜索法的目标函数值标准差、定位误差标准差、波速误差标准差均为0;该算法的定位误差平均值分别为其余二者的0.7%、1.9%;该算法的计算时间平均值分别为其余二者的6.9%、33.2%。该算法单独更改各参数对定位误差的影响在0.005～0.025 m之间;减小搜索步长下限可有效提高结果精确度,并增加相应的计算时间。在规定初至到时与目标函数模型及检波器位置坐标下,搜索算法对定位精度无实质影响。     

Long-term Trends in Vegetation Dynamics and Forest Fires in Brandenburg (Germany) Under a Changing Climate

The human influence on environmental processes has been described for many types of land use. One of the oldest tools to modify people’s environment is fire, which has dominated fire regimes in many regions over long time scales. This paper focuses on a German case study region, where 80–90% of the fires are human-caused. The objectives of this study are the application of the Regional Fire Model (Reg-FIRM), a process-based fire model that is incorporated into the LPJ Dynamic Global Vegetation Model, to temperate forests under historic climate conditions and to explore ranges of potential impacts of future climate change on fire and vegetation dynamics. Simulation experiments are designed to simulate historic fire pattern and to explore influences of vegetation on fire. Simulated fire pattern reproduced the observed average fire conditions reasonably well although with a smaller amplitude. This leads to underestimation of extreme fire years as well as an overestimation of low fire years. Vegetation composition influenced fire spread conditions in the temperate forest and had little impact on fire ignition potentials, except when only broad-leaved deciduous forests were assumed. Fire is likely to change under climate change conditions. Simulated experiments were conducted to explore the effects of climate change and rising CO₂ concentration given the potential natural vegetation as the best-case for Brandenburg. Three GCM scenarios predicting different future climatic changes were applied, and resulted in quantitatively different future fire patterns. Depending on future precipitation pattern and the influence of the CO₂ effect on canopy conductance and thus litter moisture, fire was predicted to either decrease or slightly increase in Brandenburg forests, but the burnt area would not exceed current, extreme fire years. Generally, fire changes had no implication for vegetation composition in Brandenburg, but reduced vegetation carbon gain after 2050. In the HadCM3 application, simulated increase in grass cover due to a large burnt area after 2075 accelerated fire spread conditions, thus still increasing the burnt area, while climatic fire danger and number of fires already began to decline. These interactions underline the importance to consider the full range of fire processes and interactions with vegetation dynamics in a simulation model.     

Calibrating nonparametric cellular automata with a generalized additive model to simulate dynamic urban growth

Understanding factors that drive urban growth is essential to cellular automata (CA) based urban modeling. Multicollinearity among correlated factors may cause negative effects when building CA transition rules, leading to a decrease in simulation accuracy. We use a nonparametric generalized additive model (GAM) to evaluate these relationships through flexible smooth functions to capture the dynamics of urban growth. A GAM-based CA (termed GAM-CA) model was then developed to simulate the rapid urban growth in Shanghai, China from 2000 to 2015. GAM highlights the significance of each candidate factor driving urban growth during the past 15 years. Compared to logistic regression, the GAM-CA transition rules fitted the observed data better and yielded improved overall accuracy and hence more realistic urban growth patterns. The new CA model has great potential for capturing key driving factors to simulate dynamic urban growth, and can predict future scenarios under various spatial constraints and conditions.     

Waterflooding optimization with the INSIM-FT data-driven model

In a recent paper, we developed a physics-based data-driven model referred to as INSIM-FT and showed that it can be used for history matching and future reservoir performance predictions even when no prior geological model is available. The model requires no prior knowledge of petrophysical properties. In this work, we explore the possibility of using INSIM-FT in place of a reservoir simulation model when estimating the well controls that optimize water flooding performance where we use the net present value (NPV) of life-cycle production as our cost (objective) function. The well controls are either the flowing bottom-hole pressure (BHP) or total liquid rates at injectors and producers on the time intervals which represent the prescribed control steps. The optimal well controls that maximize NPV are estimated with an ensemble-based optimization algorithm using the history-matched INSIM-FT model as the forward model. We compare the optimal NPV obtained using INSIM-FT as the forward model with the estimate of the optimal NPV obtained using the correct full-scale reservoir simulation model when performing waterflooding optimization.     

A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China

Forest fire is known as an important natural hazard in many countries which causes financial damages and human losses; thus, it is necessary to investigate different aspects of this phenomenon. In this study, performance of four models of linear and quadratic discriminant analysis (LDA and QDA), frequency ratio (FR), and weights-of-evidence (WofE) was investigated to model forest fire susceptibility in the Yihuang area, China. For this purpose, firstly, a forest fire locations map was prepared implementing MODIS satellite images and field surveys. Then, it was classified into two groups including training (70%) and validation (30%) by a random algorithm. In addition, 13 forest fire effective factors were prepared and used such as slope degree, slope aspect, altitude, Topographic Wetness Index (TWI), plan curvature, land use, Normalized Difference Vegetation Index (NDVI), annual rainfall, distance from roads and rivers, wind effect, annual temperature, and soil texture. Using the training dataset and effective factors, LDA, QDA, FR, and WofE models were applied and forest fire susceptibility maps were prepared. Finally, area under the curve (AUC) of receiver operating characteristics (ROC) was implemented for investigating the performance of the models. The results depicted that WofE had the best performance (AUC = 82.2%), followed by FR (AUC = 80.9%), QDA (AUC = 78.3%), and LDA (AUC = 78%), respectively. The results of this study showed the high contribution of altitude, slope degree, and temperature. On the other hand, it was seen that slope aspect and soil had the lowest importance in forest fire susceptibility mapping. From the AUC results, it can be concluded that FR, WofE, LDA, and QDA had acceptable performance and could be used for forest fire susceptibility mapping at the regional scale.     

A multiple-code simulation study of the long-term EDZ evolution of geological nuclear waste repositories

This simulation study shows how widely different model approaches can be adapted to model the evolution of the excavation disturbed zone (EDZ) around a heated nuclear waste emplacement drift in fractured rock. The study includes modeling of coupled thermal-hydrological-mechanical (THM) processes, with simplified consideration of chemical coupling in terms of time-dependent strength degradation or subcritical crack growth. The different model approaches applied in this study include boundary element, finite element, finite difference, particle mechanics, and elasto-plastic cellular automata methods. The simulation results indicate that thermally induced differential stresses near the top of the emplacement drift may cause progressive failure and permeability changes during the first 100 years (i.e., after emplacement and drift closure). Moreover, the results indicate that time-dependent mechanical changes may play only a small role during the first 100 years of increasing temperature and thermal stress, whereas such time-dependency is insignificant after peak temperature, because of decreasing thermal stress.     

Lava flow simulations using discharge rates from thermal infrared satellite imagery during the 2006 Etna eruption

Techniques capable of measuring lava discharge rates during an eruption are important for hazard prediction, warning, and mitigation. To this end, we developed an automated system that uses thermal infrared satellite MODIS data to estimate time-averaged discharge rate. MODIS-derived time-varying discharge rates were used to drive lava flow simulations calculated using the MAGFLOW cellular automata model, allowing us to simulate the discharge rate-dependent spread of lava as a function of time. During the July 2006 eruption of Mount Etna (Sicily, Italy), discharge rates were estimated at regular intervals (i.e., up to 2 times/day) using the MODIS data. The eruption lasted 10 days and produced a ~3-km-long lava flow field. Time-averaged discharge rates extracted from 13 MODIS images were utilized to produce a detailed chronology of lava flow emplacement, demonstrating how infrared satellite data can be used to drive numerical simulations of lava flow paths during an ongoing eruptive event. The good agreement between simulated and mapped flow areas indicates that model-based inundation predictions, driven by time-varying discharge rate data, provide an excellent means for assessing the hazard posed by ongoing effusive eruptions.     

新安江产流模型与改进的BP汇流模型耦合应用

为提高新安江模型的汇流计算精度并减少经验因素对参数率定的影响,将新安江产流模型与改进的BP汇流模型相耦合,建立XBK(XAJ-BP-KNN)模型。该模型以前期模拟流量和新安江产流模型计算的产流量作为BP网络的输入,出口断面流量作为网络输出,拟合汇流的非线性关系,代替新安江模型的分水源、线性水库及河道马斯京根法的汇流计算;采用相似原理和K-最近邻算法,基于历史样本的模拟误差及相应影响要素对网络输出进行误差修正,实现了无前期实测流量的连续模拟;模型使用SCE-UA算法与遗传早停止LM算法相结合的全局优化方法进行参数优选。在呈村流域的验证表明XBK模型的模拟精度高于新安江模型,全局优化方法能找到最优参数,降低了模型的使用难度。     

基于分数阶傅里叶变换的探地雷达子波提取算法

针对探地雷达子波提取问题,提出了一种基于分数阶傅里叶变换的子波提取算法。假设探地雷达地下介质模型为线性系统并是时变的,并且子波在传播过程中不变,把子波和地层信息描述为一个时间的积分形式。分数阶傅里叶变换是酉变换,具有保范性,把子波的提取问题转化为在分数阶傅里叶变换域上的最优滤波问题。对分数阶傅里叶变换的阶数p在(－2,2]范围以1/300为步长进行了搜索,在分数阶傅里叶变换域上找到最优解,最后经过分数阶傅里叶变换反变换得到子波估计的时域信号。仿真实验首先验证了分数阶傅里叶变换最优滤波算法的正确性,然后利用探地雷达实验数据提取了子波,验证了该算法在提取子波中的有效性。