Simple Spatial Modeling Tool for Prioritizing Prescribed Burning Activities at the Landscape Scale

Abstract:   Resources for prescribed fire are frequently insufficient to manage public lands for all conservation and resource management objectives, necessitating prioritization of the application of fire across the landscape within any given year. Defining tradeoffs when applying prescribed fire to large landscapes is problematic not only because of the complexity of weighing competing management objectives at the landscape scale, but also because of the difficult nature of independently applying need-to-burn criteria to large areas. We present a case study of a simple modeling process implemented at Eglin Air Force Base in the Florida Panhandle (U.S.A.) to prioritize the application of prescribed fire. In a workshop setting, managers and biologists identified key conservation criteria and landscape management objectives that drive the application of prescribed fire. Remote sensing and other spatial data were developed to directly or indirectly represent all these criteria. Using geographic information system software, managers and biologists weighted each criterion according to its relative contribution to overall burn prioritization, and individual values for the criterion were scored according to how they influence the need to burn. Subsequently, this process has been validated and modified through ecological monitoring. This modeling process has also been applied to the 77,400-ha Blackwater River State Forest, public land adjacent to Eglin Air Force Base, demonstrating its applicability to lands with varying management priorities. The advantages of this model-based approach for prioritizing prescribed fire include the reliance on accessible, inexpensive software, the development of spatially explicit management objectives, the ease of transferability, and clearly stated assumptions about management that may be tested and reviewed through monitoring and public comment.     

BUILDUP,WASHOFF, AND EVENT MEAN CONCENTRATIONS1

ABSTRACT: Most watershed water quality simulation models require the user to specify pollutant buildup and washoff rate parameters for pollutants, by land use. Buildup and washoff rates are difficult to measure directly, and only limited guidance and few observed data are available from the literature. Many studies, however, report storm event mean concentrations (EMCs). These EMCs must arise as a result of the buildup and washoff processes, but typically represent the net contribution from a variety of pervious and impervious surfaces. This paper explores the relationship between EMCs and buildup/washoff parameters. An assumption of the mathematical form of the buildup/washoff relationship gives an algebraic expression for the EMC consistent with model assumptions. This yields techniques to separate observed EMCs into contributions from different land uses and from pervious and impervious surfaces. Given this relationship, numerical optimization may be used to estimate site specific values of buildup and washoff parameters from observed storm EMCs for use in modeling. Use of this approach helps ensure that model parameters are consistent with observed data, providing a rational starting point for final model calibration. Several site examples demonstrate use of the method.     

Spatial modeling and prediction under stationary non-geometric range anisotropy

For modeling spatial processes, we propose a rich parametric class of stationary range anisotropic covariance structures that, when applied in R², greatly increases the scope of variogram contors. Geometric anisotropy, which provides the most common generalization of isotropy within stationarity, is a special case. Our class is built from monotonic isotropic correlation functions and special cases include the Matérn and the general exponential functions. As a result, our range anisotropic correlation specification can be attached to a second order stationary spatial process model, unlike ad hoc approaches to range anisotropy in the literature. We adopt a Bayesian perspective to obtain full inference and demonstrate how to fit the resulting model using sampling-based methods. In the presence of measurement error/microscale effect, we can obtain both the usual predictive as well as the noiseless predictive distribution. We analyze a data set of scallop catches under the general exponential range anisotropic model, withholding ten sites to compare the accuracy and precision of the standard and noiseless predictive distributions.     

Rough Set Rule Induction for Suitability Assessment

The data that characterize an environmental system are a fundamental part of an environmental decision-support system. However, obtaining complete and consistent data sets for regional studies can be difficult. Data sets are often available only for small study areas within the region, whereas the data themselves contain uncertainty because of system complexity, differences in methodology, or data collection errors. This paper presents rough-set rule induction as one way to deal with data uncertainty while creating predictive if–then rules that generalize data values to the entire region. The approach is illustrated by determining the crop suitability of 14 crops for the agricultural soils of the Willamette River Basin, Oregon, USA. To implement this method, environmental and crop yield data were spatially related to individual soil units, forming the examples needed for the rule induction process. Next, four learning algorithms were defined by using different subsets of environmental attributes. ROSETTA, a software system for rough set analysis, was then used to generate rules using each algorithm. Cross-validation analysis showed that all crops had at least one algorithm with an accuracy rate greater than 68%. After selecting a preferred algorithm, the induced classifier was used to predict the crop suitability of each crop for the unclassified soils. The results suggest that rough set rule induction is a useful method for data generalization and suitability analysis.     

INTEGRATED RIVER BASIN OPTIMIZATION: MODELING ECONOMIC AND HYDROLOGIC INTERDEPENDENCE1

ABSTRACT: This paper presents an integrated optimal control model that optimizes economic performance of reservoir management in watersheds in which there are significant economic and hydrologic interdependencies. The model is solved using the General Algebraic Modeling System (GAMS). Results show that application of this model to New Mexico's Rio Chama basin can increase total system benefits over historical benefits by exploiting complementarities between hydroelectricity production, instream recreation, and downstream lake recreation.     

EVALUATION OF AN INDUCED INFILTRATION MODEL AS APPLIED TO GLACIAL AQUIFER SYSTEMS1

ABSTRACT: Numerical models were used to examine the limitations of the assumptions used in an analytical induced infiltration model. The assumptions tested included negligible streambed effects, negligible areal recharge, two-dimensional ground water flow, fully penetrating rivers and wells, and constant surface water stage. For situations that deviate from the underlying assumptions, the analytical model becomes a less reliable predictor of induced infiltration. The numerical experiments show that streambed effects cannot be neglected if the streambed conductivity is more than one order of magnitude lower than the aquifer hydraulic conductivity. Areal recharge cannot be neglected if the ground water basin receives more than 5 in/yr of areal recharge. Three-dimensional flow effects due to well partial penetration cannot be neglected if the ratio of horizontal hydraulic conductivity to vertical hydraulic conductivity (K_h/K_u) is greater than 10. Surface water elevation fluctuations can significantly influence the induced infiltration rate, depending on the degree of fluctuations and the ground water hydraulic gradient.     

THE APPLICATION OF HYDROLOGIC MODELS TO SMALL WATERSHEDS HAVING MILD TOPOGRAPHY1

ABSTRACT: The application of hydrologic models to small watersheds of mild topography is not well documented. This study evaluates the applicability of hydrologic models described by Huggins and the Soil Conservation Service to small watersheds by comparing the simulated and actual hydrograph for both gaged and ungaged situations. The annual maximum rainfall events plus storms exceeding 2.5 inches from 25 years of rainfall and runoff data for two small watersheds were selected for the model evaluations. These storms had a variety of patterns and occurred on many different watershed conditions. Simulated and actual hydrographs were compared using a parameter which contained volume, peak, and shape factors. One-half of the selected storms were used to calibrate the models. For both models, there were no significant differences between the simulated and actual runoff volumes and peak runoff rates. Parameters obtained during the calibration process and relationships developed to estimate antecedent moisture and to modify tabulated runoff curve numbers were used to simulate the runoff hydrograph from the remaining storms. These remaining storms or test storms were simulated only once in order to imitate an ungaged situation. In general, both the Huggins and SCS model performed similarly on the test storms, but the level of model performance was lower than that for the calibration storms. For both models, the two-day antecedent rainfall was more important than the five-day in determining antecedent moisture and modifying tabulated curve numbers. The time of concentration which resulted in good hydrograph simulations was about three times larger than that estimated using published empirical relationships.     

基于灰建模的瓦斯含量多变量预测模型研究

研究了GM(1,N)、GM(0,N)瓦斯含量预测模型的数学原理,收集郑煤集团告成矿地质勘探期间及生产期间的瓦斯含量实测资料,获得16个可靠点,选取基岩厚度、新生界厚度、煤层厚度、煤层水分、煤层灰分、50m顶板含砂率6个因素作灰色建模预测的指标,分别建立了GM(1,6)和GM(0,6)瓦斯含量多变量预测模型。根据计算和评价结果,GM(1,6)和GM(0,6)瓦斯含量预测模型精度均能够满足工程精度的要求,说明利用灰色模型来预测瓦斯含量是可行的。由于前者精度略高于后者,故建议告成矿采用GM(1,6)模型来进行未知地区煤层瓦斯含量的预测。需要注意,由于模型没有考虑构造的影响,在实际预测时,还应根据构造对待预测区的影响关系和影响程度对模型的预测结果进行修正。     

长株潭城市群生态宜居水平综合评价

随着长株潭城市群工业化进程加快,其经济发展水平和城镇化水平得到飞速的提升,但是生态环境和宜居环境受到较大影响.基于层次分析法,从生态环境、资源节约、公共配套、社会民生4个维度构建生态宜居综合评价指标体系,综合测度2010～2018年长株潭城市群的生态宜居水平.结果显示2010～2018年间,长株潭城市群生态宜居综合水平...     

汶川县生态保护红线人类活动本底调查评估

生态保护红线是国家和区域生态安全的底线,以阿坝州汶川县划定的生态保护红线区为研究区域,利用GIS软件对研究区域内人类活动遥感影像进行遥感解译,并对研究区生态保护红线内的人类活动进行本底实地调查,结合遥感解译和实地调查结果,对红线内人类活动强度进行了评价.结果 表明:红线内人类活动面积共计142.04hm2,人类活动斑块...