多时间尺度HSPF模型参数不确定性研究

模型参数的不确定性是水文模型应用研究领域的重点与难点.本研究以密云水库东北部的潮河流域为例,构建了潮河流域HSPF水文模型,并采用1998~2010年逐月地表径流量数据对模型参数进行校准与验证,并结合GLUE算法分析了模型参数的敏感性和不确定性.结果表明:(1)经过参数调整,HSPF模型径流模拟取得了较好的效果,率定期和验证期的纳什系数分别为0.84和0.55;(2)可将影响HSPF模型的参数分为3类,即全局敏感性参数(LZSN、INFILT、IRC和AGWRC)、局部敏感性参数(UZSN)和不敏感参数(DEEPFR、BASETP、AGWEPT、INTFW和CEPSC);(3)不同敏感性参数间存在复杂的相关关系,参数组合(LZSN与INFILT)、(INFILT与UZSN)和(UZSN与AGWRC)间均呈极显著负相关关系;(LZSN与UZSN)和(UZSN与AGWRC)呈极显著正相关;(4)HSPF模型参数存在大量复杂的"异参同效"现象,证实影响模拟结果优劣的是参数组合而非某一参数值;(5)模型不确定性发现,模型预测的不确定性范围与降雨量密切相关,即降雨量越大,模型预报的不确定性就越大,反之亦然;(6)不同时间尺度下HSPF模型的模拟效果总体较好,但是也存在一定差异性,年尺度、季节尺度和月尺度下不确定性范围分别包含了81.80%、78.70%和80.56%的观测值,即年尺度效果略优于月尺度和季节尺度;该研究结果可为HSPF模型在相似区域应用与参数本土化提供科学参考和借鉴.     

Relationship Between Bird Abundances and Landscape Characteristics: The Influence of Scale

Scale is important to consider when investigating effects of the environment on a species. Breeding Bird Survey (BBS) data and landscape metrics derived from aerial photographs were evaluated to determine how relationships of bird abundances with landscape variables changed over a continuous range of 16 spatial scales. We analyzed the average number of birds per stop (1985–1994) for five songbird species (family Cardinalidae) for each of 50 stops on 198 BBS transects throughout six states in the Central Plains, USA. Land along each transect was categorized into six cover types, and landscape metrics of fractal dimension (a measure of shape complexity of habitat patches), edge density, patch density, and percent area were calculated, with principal components used to construct composite environmental variables. Associations of bird abundances and landscape variables changed in accordance with small scale changes. Abundances of three species were correlated with edge density and one with component I, which subsumes initial variables of patch density for urban, closed forest, open forest, and open country. Fractal dimension and component II (summarizing amount of closed forest versus open country) were associated with the most species. Correlation patterns of fractal dimension with northern cardinal (Cardinalis cardinalis) and painted bunting (Passerina ciris) abundances were similar, with highest correlations at intermediate to small scales, suggesting indirectly that these species thrive in areas where local habitat conditions are most important. Multiscale analysis can provide insight into the spatial scale(s) at which species respond, a topic of intrinsic scientific interest with applied implications for researchers establishing protocols to assess and monitor avian populations.     

Spatial scales and probability based sampling in determining levels of benthic community degradation in the Chesapeake Bay

The extent of degradation of benthic communities of the Chesapeake Bay was determined by applying a previously developed benthic index of biotic integrity at three spatial scales. Allocation of sampling was probability-based allowing areal estimates of degradation with known confidence intervals. The three spatial scales were: (1) the tidal Chesapeake Bay; (2) the Elizabeth River watershed; and (3) two small tidal creeks within the Southern Branch of the Elizabeth River that are part of a sediment contaminant remediation effort. The areas covered varied from 10^–1 to 10⁴ km² and all were sampled in 1999. The Chesapeake Bay was divided into ten strata, the Elizabeth River into five strata and each of the two tidal creeks was a single stratum. The determination of the number and size of strata was based upon consideration of both managerially useful units for restoration and limitations of funding. Within each stratum 25 random locations were sampled for benthic community condition. In 1999 the percent of the benthos with poor benthic community condition for the entire Chesapeake Bay was 47% and varied from 20% at the mouth of the Bay to 72% in the Potomac River. The estimated area of benthos with poor benthic community condition for the Elizabeth River was 64% and varied from 52–92%. Both small tidal creeks had estimates of 76% of poor benthic community condition. These kinds of estimates allow environmental managers to better direct restoration efforts and evaluate progress towards restoration. Patterns of benthic community condition at smaller spatial scales may not be correctly inferred from larger spatial scales. Comparisons of patterns in benthic community condition across spatial scales, and between combinations of strata, must be cautiously interpreted.     

An adaptive plan for prioritizing road sections for fencing to reduce animal mortality

Mortality of animals on roads is a critical threat to many wildlife populations and is poised to increase strongly because of ongoing and planned road construction. If these new roads cannot be avoided, effective mitigation measures will be necessary to stop biodiversity decline. Fencing along roads effectively reduces roadkill and is often used in combination with wildlife passages. Because fencing the entire road is not always possible due to financial constraints, high-frequency roadkill areas are often identified to inform the placement of fencing. We devised an adaptive fence-implementation plan to prioritize road sections for fencing. In this framework, areas along roads of high, moderate, and low levels of animal mortality (respectively, roadkill hotspots, warmspots, and coldspots) are identified at multiple scales (i.e., in circles of different diameters [200–2000 m] in which mortality frequency is measured). Fence deployment is based on the relationship between the amount of fencing being added to the road, starting with the strongest roadkill hotspots, and potential reduction in road mortality (displayed in mortality-reduction graphs). We applied our approach to empirical and simulated spatial patterns of wildlife–vehicle collisions. The scale used for analysis affected the number and spatial extent of roadkill hot-, warm-, and coldspots. At fine scales (e.g., 200 m), more hotspots were identified than at coarse scales (e.g., 2000 m), but combined the fine-scale hotspots covered less road and less fencing was needed to reduce road mortality. However, many short fences may be less effective in practice due to a fence-end effect (i.e., animals moving around the fence more easily), resulting in a trade-off between few long and many short fences, which we call the FLOMS (few-long-or-many-short) fences trade-off. Thresholds in the mortality-reduction graphs occurred for some roadkill patterns, but not for others. Thresholds may be useful to consider when determining road-mitigation targets. The existence of thresholds at multiple scales and the FLOMS trade-off have important implications for biodiversity conservation.     

农业气候资源多时间尺度分析——以郑州市小麦玉米为例

小波分析的时域局部变化特征可展现气候序列的精细结构,能够揭示不同时间尺度气候序列所隐含的不同变化规律,是进行时域分析的有力工具。论文以郑州市小麦、玉米生育期间的光热水农业气候资源分析为例,用Morlet小波变换法对其进行多时间尺度变化特征及演变规律分析。结果表明:郑州小麦、玉米生育期间的光热水气候要素具有不同的年际及年代际时间尺度周期变化规律和转换特征;小波变换能很好地揭示农业气候资源变化所包含的周期分量;其气候变化特征与全球气候变化趋势相比,有其一致性,也有其局地特殊性。     

Development and Application of an Agricultural Intensity Index to Invertebrate and Algal Metrics from Streams at Two Scales

Research was conducted at 28‐30 sites within eight study areas across the United States along a gradient of nutrient enrichment/agricultural land use between 2003 and 2007. Objectives were to test the application of an agricultural intensity index (AG‐Index) and compare among various invertebrate and algal metrics to determine indicators of nutrient enrichment nationally and within three regions. The agricultural index was based on total nitrogen and phosphorus input to the watershed, percent watershed agriculture, and percent riparian agriculture. Among data sources, agriculture within riparian zone showed significant differences among values generated from remote sensing or from higher resolution orthophotography; median values dropped significantly when estimated by orthophotography. Percent agriculture in the watershed consistently had lower correlations to invertebrate and algal metrics than the developed AG‐Index across all regions. Percent agriculture showed fewer pairwise comparisons that were significant than the same comparisons using the AG‐Index. Highest correlations to the AG‐Index regionally were ?0.75 for Ephemeroptera, Plecoptera, and Trichoptera richness (EPTR) and ?0.70 for algae Observed/Expected (O/E), nationally the highest was ?0.43 for EPTR vs. total nitrogen and ?0.62 for algae O/E vs. AG‐Index. Results suggest that analysis of metrics at national scale can often detect large differences in disturbance, but more detail and specificity is obtained by analyzing data at regional scales.     

多空间尺度景观格局与地表水质响应关系研究

截至2020年底,北京市已建成466条生态清洁小流域,其中,密云水库上游(北京境内)179条小流域,将于2022年底全部达到生态清洁小流域标准.本研究对密云水库流域进行子流域划分并创建缓冲区,通过汛期水质监测,结合统计分析和景观格局指数计算,量化不同空间尺度景观格局和水质的响应关系.结果表明:①密云水库主要河流水质除总...     

Multi-scales Analysis of Driving Forces on Land Use/Cover Change in China： Taking Farmland Returning to Forest or Grassland as a Case

Increasing populations are causing an increase in food demands, and the area of cultivated land expands every year. Inappropriate land transition from ecology to production results in the constant decline of the ecological security level and influences the regional sustainable development. Adjusting unreasonable land use mode and reconstructing natural land cover are important ways to maintain and improve the ecological environment. Also reclaiming farmland as areas for forests and grasslands （FRFG） is another way. Successful implementation of FRFG in China is the result of comprehensive effect of the multi-scales driving forces. This paper analyses the driving forces of FRFG in China on a national （country） -regional （province） - local （county） - household （farmer） level scale, and the results are： driving forces at the national scale include ecological and food security and the western development of China; at the regional scale, ecological and economic benefits become the main factors to influence the dimension of FRFG under the same policy. The driving forces can be divided into 6 types： industrial structure adjustment, water source protection, flood prevention, the Three-Gorge Project protection, reduction of the amount of sediment flowing into the Yellow River and wind erosion desertification prevention. The driving forces at the local scale can be divided into 12 types with developing leading industries, increasing farmers＇ income and improving agricultural production conditions as the main types; at the household scale, the national policy meeting farmers＇ demands and the optimization of individual interests are all driving forces.     

不同空间尺度的江苏省区域经济差异研究

运用基尼系数、空间自相关等方法分析改革开放以来县域和地级市空间尺度下的江苏省区域经济差异变化及其空间机制。研究表明:改革开放以来江苏省县域和地级市尺度的区域经济差异在2008年前均呈扩大趋势,以后差距缩小,且县域尺度大于地级市尺度。在县域和地级市尺度上江苏省区域经济差异均存在明显的空间正相关关系,且不断增强,在县域尺度空间集聚更强。在地级市水平上,苏北的低水平集聚是其产生区域差异的主要原因,而在县域尺度上则苏南的高水平集聚是江苏区域差异主要原因。针对江苏省区域经济差异重点关注县域尺度的区域差异,在地级市尺度上侧重提升落后地区发展水平,而在县域空间尺度上以促进高水平地区的空间扩散为主。     

Simulating spatiotemporal dynamics of urbanization with multi-agent systems—A case study of the Phoenix metropolitan region, USA

Urbanization is a human-dominated process and has greatly impacted biodiversity, ecosystem processes, and regional climate. To understand the socioeconomic drivers of urbanization and project future urban landscape changes, multi-agent systems provide a powerful tool. We develop an agent-based model of urban growth for the Phoenix metropolitan region of the United States, which simulates the behavior of regional authorities, real estate developers, residents, and environmentalists. The BDI (Beliefs-Desires-Intentions) structure is employed to simulate the agents behavior and decision models. The heterogeneity of agents is reflected by adjusting parameters according to the agents’ beliefs, desires and preferences. Three scenarios, baseline, economic development priority and environmental protection, are developed and analyzed. The combination of multi-agent system and spatial regression model is employed to predict the future urban development of the Phoenix metropolitan region. Landscape metrics are used to compare the spatial patterns of the urban landscape resulting from different scenarios in different times. In general, with the rapid urban expansion, the shape of urban patches will become more regular as many of them become coalesced. The spatial analysis of urban development through modeling individual and group decisions and human-environment interactions with a multi-agent systems approach can enhance our understanding of the socioeconomic driving forces and mechanisms of urban development.