森林火灾防治决策专家系统的研究与实现

笔者比较系统地收集、研究了林火专家多年积累的理论、经验和解决问题的方法以及各种预测模型、模型的适应条件和使用规则等 ,利用人工智能和COM组件技术 ,通过模型技术和专家系统技术的有机结合 ,建立了基于网络的森林火灾防治决策专家系统。实现了森林火灾从火灾预测、林火扑救决策、清理火场、看守火场到最后的损失评估全过程的推理辅助决策 ;实现了整个决策过程中预测模型和预测结果随外界条件的突变而进行的实时修正 ,从而真正实现了森林火灾管理各个阶段的实时性、准确性和正确性。     

A Daily Time Series Analysis of StreamWater Phosphorus Concentrations Along an Urban to Forest Gradient

During a 1-year period, we sampled stream water total phosphorus (TP) concentrations daily and soluble reactive phosphorus (SRP) concentrations weekly in four Seattle area streams spanning a gradient of forested to urban-dominated land cover. The objective of this study was to develop time series models describing stream water phosphorus concentration dependence on seasonal variation in stream base flows, short-term flow fluctuations, antecedent flow conditions, and rainfall. Stream water SRP concentrations varied on average by ±18% or ±5.7 μg/L from one week to another, whereas TP varied ±48% or ±32.5 μg/L from one week to another. On average, SRP constituted about 47% of TP. Stream water SRP concentrations followed a simple sine-wave annual cycle with high concentrations during the low-flow summer period and low concentrations during the high-flow winter period in three of the four study sites. These trends are probably due to seasonal variation in the relative contributions of groundwater and subsurface flows to stream flow. In forested Issaquah Creek, SRP concentrations were relatively constant throughout the year except during the fall, when a major salmon spawning run occurred in the stream and SRP concentrations increased markedly. Stream water SRP concentrations were statistically unrelated to short-term flow fluctuations, antecedent flow conditions, or rainfall in each of the study streams. Stream water TP concentrations are highly variable and strongly influenced by short-term flow fluctuations. Each of the processes assessed had statistically significant correlations with TP concentrations, with seasonal base flow being the strongest, followed by antecedent flow conditions, short-term flow fluctuations, and rainfall. Times series models for each individual stream were able to predict ∼70% of the variability in the SRP annual cycle in three of the four streams (r² = 0.57–0.81), whereas individual TP models explained ∼50% of the annual cycle in all streams (r² = 0.39–0.59). Overall, time series models for SRP and TP dynamics explained 82% and 76% of the variability for these variables, respectively. Our results indicate that SRP, the most biologically available and therefore most important phosphorus fraction, has simpler and easier-to-predict seasonal and weekly dynamics.     

Impacts of land use conversion on bankfull discharge and mass wasting

Mass wasting and channel incision are widespread in the Nemadji River watershed of eastern Minnesota and northwestern Wisconsin. While much of this is a natural response to glacial rebound, sediment coring and tree ring data suggest that land use has also influenced these erosional processes. We characterized land use, inventoried mass wasting, surveyed stream channels and collected discharge data along segments of five streams in the Nemadji River watershed. Due to natural relief in this region, wetlands and agricultural lands are concentrated in the flatter terrain of the uplands of the Nemadji watershed, while forestland (coniferous or deciduous) is concentrated in the deeply incised (50-200% slope) stream valleys. Bankfull discharge was higher where forests had been converted from coniferous to deciduous forests and where there were fewer wetlands. Mass wasting increased exponentially with bankfull flows. While mass wasting was not correlated with forest type conversion and agricultural land use, it was negatively dependent upon wetland extent in headwater areas. Interactions between the spatial distribution of land use and terrain obfuscate any clear cause-and-effect relationships between land use, hydrology and fluvial processes.     

峡谷地形中森林地表火蔓延实验研究

在峡谷形的受限结构实验台上进行森林火灾实验，燃料采用与林间可物相似的混合物，观测火蔓延过程在这种地型结构中的特点。改变风速，通过温度时间曲线分析林火蔓延过程以及烟气运动的规律，所得到的结果也将为林火模型进一步的建立提供实验依据。     

Computer-aided classification of forest cover types from small scale aerial photography

The US National Park Service must map forest cover types over extensive areas in order to fulfill its goal of maintaining or reconstructing presettlement vegetation within national parks and monuments. Furthermore, such cover type maps must be updated on a regular basis to document vegetation changes. Computer-aided classification of small scale aerial photography is a promising technique for generating forest cover type maps efficiently and inexpensively. In this study, seven cover types were classified with an overall accuracy of 62 percent from a reproduction of a 1120,000 color infrared transparency of a conifer-hardwood forest. The results were encouraging, given the degraded quality of the photograph and the fact that features were not centered, as well as the lack of information on lens vignetting characteristics to make corrections. Suggestions are made for resolving these problems in future research and applications. In addition, it is hypothesized that the overall accuracy is artificially low because the computer-aided classification more accurately portrayed the intermixing of cover types than the hand-drawn maps to which it was compared.     

FORPLAN: A FORest Planning LANguage and Simulator

A Forest Planning Language and Simulator (FORPLAN) has been developed to facilitate the use of simulation for integrating fire into the land management planning process.FORPLAN incorporates unique characteristics of previous systems, links numerous models and data bases, allows selection of variable resolution levels, and permits discrete time simulation of disturbances on plants, fuels, and animals. No previous computer experience is required of the user, sinceFORPLAN recognizes simple English words and phrases.     

火灾时人员疏散开始时间范围的研究

火灾中人员疏散的开始时间是一个受多方面因素影响的随机量。现行的火灾数值模拟计算中常将它处理成一常量，显然与实际不符。该项研究采用统计理论的正态分布函数，建立了一个随机数学模型，研究火灾中人员疏散开始时间的范围，结合实例数据，似合出一通用公式实现定量研究。     

Carbon forestry economic mitigation potential in India,by land classification

Carbon forestry mitigation potential estimates at the global-level are limited by the absence or simplicity of national-level estimates, and similarly national-level estimates are limited by absence of regional-level estimates. The present study aims to estimate the mitigation potential for a large diverse country such as India, based on the GTAP global land classification system of agro-ecological zones (AEZs), as well the Indian AEZ system. The study also estimates the implications of carbon price incentive (US$50 and $100) on mitigation potential in the short-, medium- and long-term, since afforestation and reforestation (A & R) is constrained by lack of investment and financial incentives. The mitigation potential for short and long rotation plantations and natural regeneration was estimated using the GCOMAP global forest model for two land area scenarios. One scenario included only wastelands (29 Mha), and the second enhanced area scenario, included wastelands plus long fallow and marginal croplands (54 Mha). Under the $100 carbon price case, significant additional area (3.6 Mha under the wasteland scenario and 6.4 Mha under the enhanced area scenario) and carbon mitigation is gained in the short-term (2025) compared to the baseline when using the GTAP land classification system. The area brought under A & R increases by 85–100% for the $100 carbon price compared to $50 carbon price in the short-term, indicating the effectiveness of higher carbon price incentives, especially in the short-term. A comparison of estimates of mitigation potential using GTAP and Indian AEZ land classification systems showed that in the short-term, 35% additional C-stock gain is achieved in the $100 carbon price case in the enhanced area scenario of the Indian AEZ system. This difference highlights the role of the land classification system adopted in estimation of aggregate mitigation potential estimates, particularly in the short-term. Uncertainty involved in the estimates of national-level mitigation potential needs to be reduced, by generating reliable estimates of carbon stock gain and losses, and cost and benefit data, for land use sector mitigation options at a scale disaggregated enough to be relevant for national mitigation planning.     

Bandwidth determination for kernel density analysis of wildfire events at forest sub-district scale

Forest fire is regarded as one of the most significant factors leading to land degradation. While evaluating fire hazard or producing fire risk zone maps, quantitative analyses using historic fire data is often required, and during all these modeling and multi-criteria analysis processes, the fire event itself is taken as the dependent variable. However, there are two main problematic issues in analyzing historic fire data. The first difficulty arises from the fact that it is in point format, whereas a continuous surface is frequently needed for statistically analyzing the relationship of fire events with other factors, such as anthropogenic, topographic and climatic conditions. Another, and probably the most bothersome challenge is to overcome inaccuracy inherent in historic fire data in point format, since the exact coordinates of ignition points are mostly unknown. In this study, kernel density mapping, a widely used method for converting discrete point data into a continuous raster surface, was used to map the historic fire data in Mumcular Forest Sub-district in Mu?la, Turkey. The historic fire data was transferred onto the digital forest stand map of the study area, where the exact locations of ignition points are unknown; however, the exact number of ignition points in each compartment of the forest stand map is known. Different random distributions of ignition points were produced, and for each random distribution, kernel density maps were produced by applying two distinct kernel functions with several smoothing parameter options. The obtained maps were compared through correlation analysis in order to illustrate the effect of randomness, choice of kernel function and smoothing parameter. The proposed method gives a range of values rather than a single bandwidth value; however, it provides a more reliable way than comparing the maps with different bandwidths subjectively by eye.     

Cap and trade policy for managing water competition from potential future carbon plantations

Carbon sequestration from reforestation can play a large role in mitigating global climate change. However, resulting interception of rainfall runoff may impose high irrigation, water supply and/or environmental flow costs. This article presents an assessment of water trade policy to manage fresh water supply, carbon sequestration trade-offs for the Murray-Darling Basin. A linked Australian high spatial resolution land use and global integrated assessment framework evaluated plausible and internally-consistent global scenarios to 2050 involving significant carbon planting incentive. Substantial flow loss from increased interception was estimated absent policy to balance carbon water trade-offs. Absent policy to address the trade-off, irrigation opportunity costs was estimated to substantially exceed carbon sequestration economic value in futures with significant carbon sequestration incentive. The value of integrating interception from new carbon plantings into the existing water trade system was estimated at $3.3 billion and $2.0 billion (2050 annual value) for our strong and moderately strong global climate action outlooks with our reference case assumptions. The conclusion that trade provision in policy to cap interception impacts can produce significant benefits in scenarios with significant carbon sequestration incentive remained robust over a very broad set of sensitivities tested with benefit estimated at over $1 billion annually at 2050 even for very conservative assumptions.