Quantifying Landscape Pattern Research Articles

Quantifying Landscape Pattern–Hydrological Process Linkage in Northwest Iran

The enormous heterogeneity and complexity of landscape patterns and their linkage with the hydrological responses have rarely been quantified and cataloged, especially in ungauged regions. This research therefore linked the landscape characteristics to hydrological processes using a newly developed runoff landscape index (RLI) at the watershed scale in Ardabil Province, northwest Iran. First, 11 common landscape metrics were calculated using Fragstats 4.2.1 software. Then, a runoff landscape index (RLI) was developed based on land cover (λC), soil (λK), and topography (λS) factors in 28 watersheds. Correlation and regression analyses were also conducted to determine the relationship between RLI, commonly used landscape metrics, and mean base flow. The spatial variations of all meaningful landscape metrics and RLI were considerable throughout the study watersheds. The mean values of λC, λK, and λS were found to be 2.78 ± 1.08, 0.50 ± 0.10, and 1.22 ± 0.30, respectively. The mean RLI varied from 0.00009 in the Lay Watershed with an area of 19.09 km2 to 0.28 in the Boran Watershed with 10,268.95 km2. The correlation coefficient (r > 0.42; p-value < 0.05) was obtained significantly between RLI and only five landscape metrics, including the largest patch index (LPI), landscape shape index (LSI), landscape division index (DIVISION), splitting index (SPLIT), and Shannon’s diversity index (SHDI). In addition, a regression model with R2 of 0.97 and 0.67, respectively, in calibration and validation steps was established between river base flow as the dependent variable and main waterway length, LPI, LSI, SPLIT, modified Simpson’s diversity index (MSIDI), and λS as independent variables. The result confirms the significant interdependence of RLI and landscape characteristics, which can be used to interpret the landscape’s dynamic and its effects on hydrological processes.

Landscape Pattern Changes and Climate Response in Nagqu Hangcuo National Wetland Park in the Tibetan Plateau

Wetlands are vital ecosystems in the Tibetan Plateau that play a crucial role in water conservation, flood storage, and biodiversity maintenance. They are sensitive to climate change and typically have high ecological and environmental quality levels due to minimal human disturbance. This study aimed to quantify landscape pattern changes within the Nagqu Hangcuo National Wetland Park (NNWP) and identify the impact of climate on wetland change. Using remote sensing data from six periods (1990, 1995, 2000, 2005, 2010, and 2015), dynamic change analysis, landscape pattern analysis, and correlation analysis were employed to determine the evolutionary features of the wetland landscape and explore their relationship with climatic factors. The results showed that the total wetland area increased from 15.11 km2 in 1990 to 15.23 km2 in 2015. The meadow area increased the most among landscape types, primarily converted from swamps. Over 25 years, the fragmentation of the NNWP’s landscape increased while diversity decreased and its shape became more complex. Meadows were more sensitive to climatic factors than other landscape types, with correlation coefficients between wetland separation and sunshine duration being more significant than other climatic factors. Therefore, it is imperative to monitor landscape pattern changes and the effects of climate change to better protect wetland parks through long-term planning, suitable mechanisms, and advanced technology.

Quantifying cross-scale patch contributions to spatial connectivity

ContextConnectivity between habitat patches is vital for ecological processes at multiple scales. Traditional metrics do not measure the scales at which individual habitat patches contribute to the overall ecological connectivity of the landscape. Connectivity has previously been evaluated at several different scales based on the dispersal capabilities of particular organisms, but these approaches are data-heavy and conditioned on just a few species.ObjectivesOur objective was to improve cross-scale measurement of connectivity by developing and testing a new landscape metric, cross-scale centrality.MethodsCross-scale centrality (CSC) integrates over measurements of patch centrality at different scales (hypothetical dispersal distances) to quantify the cross-scale contribution of each individual habitat patch to overall landscape or seascape connectivity. We tested CSC against an independent metapopulation simulation model and demonstrated its potential application in conservation planning by comparison to an alternative approach that used individual dispersal data.ResultsCSC correlated significantly with total patch occupancy across the entire landscape in our metapopulation simulation, while being much faster and easier to calculate. Standard conservation planning software (Marxan) using dispersal data was weaker than CSC at capturing locations with high cross-scale connectivity.ConclusionsMetrics that measure pattern across multiple scales are much faster and more efficient than full simulation models and more rigorous and interpretable than ad hoc incorporation of connectivity into conservation plans. In reality, connectivity matters for many different organisms across many different scales. Metrics like CSC that quantify landscape pattern across multiple different scales can make a valuable contribution to multi-scale landscape measurement, planning, and management.

Effects of nitrogen removal from wastewater on phytoplankton in eutrophic prairie streams

AbstractBiological nutrient removal (BNR) may be an effective strategy to reduce eutrophication; however, concerns remain about effects on receiving waters of removing both nitrogen (N) and phosphorus (P), rather than P alone.Phytoplankton abundance (as µg chlorophyll a/L) and community composition (as nmol biomarker pigment/L) were quantified over 6 years in two connected eutrophic streams to determine how algae and cyanobacteria varied in response to a shift from tertiary (P removal) to BNR (N and P removal) wastewater treatment.Phytoplankton were sampled biweekly at nine stations May to September and were analysed using generalised additive models (GAMs) to quantify landscape patterns of phototrophs and identify potential causal relationships both before (2010–2012) and after (2017–2019) BNR installation in 2016.Analysis with GAMs showed that 69%–79% of deviance in phytoplankton abundance and composition could be explained by date‐ and site‐specific variance in stream flow, temperature, and solute concentrations (mainly nutrients), whereas similar GAMs using only effluent N content (δ15Nwater) as a predictor explainedc. 60% of phototroph deviance. Prior to BNR, phytoplankton levels (mainly chlorophytes) increased with‐rich effluent, whereas their abundance declined with δ15N after BNR (diatoms, chlorophytes).Overall, declines in total effluent release of N (67%–97%) but not P (c. 0%) due to BNR resulted in a 52 ± 7% decline in phytoplankton abundance relative to upstream values, despite high inter‐annual variation in discharge and baseline chlorophyll a concentration.Nitrogen removal by BNR improved water quality in N‐limited ecosystems.

Linking landscape pattern, ecosystem service value, and human well-being in Xishuangbanna, southwest China: Insights from a coupling coordination model

Landscape pattern, ecosystem service value (ESV), and human well-being are closely related. Determining the link between the three is significant to the realization of regional sustainable development. However, the relationship is complex and vulnerable to multiple factors, many of which remain unknown. This study used remote sensing imagery of Xishuangbanna to map land-use in 1996, 2003, 2010, and 2016 and used landscape metrics to quantify landscape pattern changes. This research evaluated changes to ESV using the benefit transfer method and evaluated changes in human well-being using the evaluation index system and the entropy weight method. A coupling coordination model was used to analyze the coupling coordination state of the three, and the grey correlation method was used to determine key factors involved in the coupling mechanism. The results show that: (1) Forest, rubber, and tea are the main land-use types, with the area of forest decreasing, the area of rubber presenting an inverted V-shape change trend, the area of tea presenting an N-shape change trend, and the transformation of a large quantity of forest land into rubber and tea plantations. (2) The landscape pattern has become more fragmented, and connectivity and stability are in decline. (3) Climate regulation, water regulation, and erosion prevention are the main ecosystem services and, from 1996 to 2016, total ESV decreased by 3.53 billion yuan, mainly due to the decrease in forest ESV. Meanwhile, across the region, the area of high value decreased, and the area of median value increased, with a distribution trend of high value in the north and low value in the south. (4) The level of human well-being continues to rise. (5) The link between landscape pattern, ESV, and human well-being was relatively strong, and the coupling coordination degree first increased and then decreased, changing from grudging coordination to primary coordination and then dropping to a state of near maladjustment. Patch density and food production are the key coupling effect factors of landscape pattern and ESV on human well-being, respectively. The study results provide a reference for regional land-use policy and economic decision-making.

Quantifying landscape pattern and ecosystem service value changes: A case study at the county level in the Chinese Loess Plateau

Implementation of ecological restoration projects in the Chinese Loess Plateau has improved the ecological environment significantly, and altered the structure of rural land use dramatically. Therefore, it is critical to characterize and quantify the changes in landscape patterns and ecosystem service value (ESV), especially at the county level, to provide sustainable land-use plans to local policymakers. This study mapped land use for 1985, 1995, 2005 and 2015 by using remote sensing imagery of Yongshou County, a typical hilly-gully region in Loess Plateau, and quantified the changes in landscape patterns by using spatial metrics. It employed the benefit transfer method to estimate changes in ESV. The results showed the following: (1) Grassland, forestland and cropland were the main land-use types, with the most increased area in forestland and grassland. (2) The landscape pattern was becoming more fragmented, and connectivity and accessibility decreased. (3) The total ESV increased by 3.5 million RMB, mainly because of increased ESV in grassland; meanwhile, synergies existed among regulation and support services, and trade-offs existed among supply services and regulation. (4) The changes in land-use types and landscape patterns had significant positive effects on the ESV. These results on ESV change with land-use support scientific decision-making services for the formulation of land-use planning and landscape structure adjustment plans at the county level to ensure sustainable management of ecosystems.

PyLandStats: An open-source Pythonic library to compute landscape metrics.

Quantifying the spatial pattern of landscapes has become a common task of many studies in landscape ecology. Most of the existing software to compute landscape metrics is not well suited to be used in interactive environments such as Jupyter notebooks nor to be included as part of automated computational workflows. This article presents PyLandStats, an open-source Pythonic library to compute landscape metrics within the scientific Python stack. The PyLandStats package provides a set of methods to quantify landscape patterns, such as the analysis of the spatiotemporal patterns of land use/land cover change or zonal analysis. The implementation is based on the prevailing Python libraries for geospatial data analysis in a way that they can be forthwith integrated into complex computational workflows. Notably, the provided methods offer a large variety of options so that users can employ PyLandStats in the way that best supports their needs. The source code is publicly available, and is organized in a modular object-oriented structure that enhances its maintainability and extensibility.

Spatio-temporal analysis and prediction of landscape patterns and change processes in the Central Zagros region, Iran

Unfortunately in recent decades Central Zagros region has been changed adversely due to human activities. To analyze changes land cover maps produced using multi-temporal classification of Landsat satellite images of TM, ETM+ and OLI sensors, respectively for 1989, 2000 and 2013 years. Then derived maps used as input data in Land Change Modeler (LCM) to predict land cover changes on 2020, 2030, 2040 and 2050 based on a historical scenario. Results of classification and prediction were used to analyze landscape patterns and change processes. Five landscape pattern metrics as Normalized Entropy, Edge Density, Patch Area, Patch Compactness and Relative Richness were used to quantify landscape pattern and occurrence of ten landscape change processes as Attrition, Aggregation, Dissection, Creation, Shrinkage, Perforation, Shift, Deformation, Enlargement and Fragmentation were studied. Land cover maps showed great changes in central Zagros region in Lorestan province (Iran) whereas residential areas have destroyed about 5166.7 km2 of Zagros forests from 1989 to 2013. In this period residential areas are increased about 47.71 km2. Based on a “historical” scenario between 2013 up to 2050 about 4304.66 km2 of Zagros forests will lose and residential areas will increase about 244.51 km2 from. Results of landscape pattern analysis show increase of all studied landscape pattern metrics values; Normalized entropy from 0.001895 to 0.45236, Relative richness 11.12 to 22.89 percent, Edge density 0.002–0.44 m/ha, Patch area 92.04–193171.7 ha and Patch compactness 0.006 to 0.568 patches/100ha from 1989 to 2050. More over occurred change processes in different periods include: Shift, Enlargement, Attrition, Aggregation, Creation and Dissection. Results of this study present a clear perspective of future for managers and planners and can be used in natural resources management and environmental policy making, as well as creating mitigation measures in vulnerable areas.

Landscape pattern change in Marakan protected area, Iran

The importance of protected areas (PAs) is mainly to protect biodiversity that is affected by the interactions between climate changes, landscape connectivity, and land use. The objectives are (1) identifying land use/cover classes and their changes occurred in the studied period, (2) quantifying landscape pattern to analyze the diversity, complexity, and fragmentation characteristics at class and landscape levels. Land use/cover (LU/LC) changes of the Marakan protected area (MPA), as a biodiversity hotspot in the northwest of Iran, were investigated with post-classification method, and also landscape pattern changes were analyzed using landscape metrics at the class and landscape levels in a time span of 31 years. The most obvious observations were as follows: (1) incremental changes occurred in the area of human-dominated LU/LC types and a tendency for development of merging patches and emerging new patches was detected. (2) Rangelands as the dominant LU/LC types in MPA depicted mainly a trend for conversion into low-quality rangelands, (3) MPA at the landscape level witnessed a decrease in the fragmentation due to decreasing of the patches number specifically in high and low-density rangeland and merging process of patches in human-dominated LU/LC types. The main net changes are considered as negative from the ecological point of view, mainly in high-density rangeland that undoubtedly affects ecosystem process and function. Therefore, the decision makers and planners may consider and manage these undesirable changes on the landscape scale, which can be easily understood by local people.

Multi-Criteria Assessment of Land Cover Dynamic Changes in Halgurd Sakran National Park (HSNP), Kurdistan Region of Iraq, Using Remote Sensing and GIS

Halgurd Sakran National Park (HSNP) is Iraq’s first designated national park, located in the Kurdistan Region, which has suffered multiple armed conflicts over the past decades. This study assesses how vegetation dynamics have affected the landscape structure and composition of the core zone of the park over the last 31 years. Spatio-temporal changes in land cover were mapped for three points in time using remote sensing, geographic information systems (GIS), and landscape metrics. Land cover changes were mapped using random forest classifications of satellite images from Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 LDCM acquired in 1984, 1998, and 2015. Five landscape pattern metrics were analysed at class and landscape levels in order to quantify landscape patterns arising from land use and land cover (LULC) change in HSNP using FRAGSTATS 4.2. These landscape pattern metrics were patch metrics, area metrics, shape metrics interspersion/juxtaposition and contagion metrics and diversity metrics. Significant changes in cultivated areas after 1991 were observed, which indicate the role of anthropogenic activities in land cover change. Areas of bare surface and forest lands declined and became more fragmented in 1984 and 1998 while, at the same time, cultivated areas increased, with a continuing fragmentation of pasture land. Internal migration of people was one of the major drivers of LULC change. The results reveal that significant LULC changes in terms of composition and spatial structure over the 31-year period have occurred in the designated protected area. Landscape metrics were able to assess the trend of spatial patchiness over the studied period. A discussion of the significance of changes in land use systems for understanding the causes and consequences of change is provided.

Effects of Urbanization on Landscape Patterns in a Mountainous Area: A Case Study in the Mentougou District, Beijing, China

We explored the process of urbanization in a mountainous area to seek a sustainable urbanization strategy. Previous urbanization research has mainly focused on flat terrain and coastal areas, and urbanization in mountainous areas remains poorly understood. This study integrated geographic information systems, remote sensing, and statistical analysis to quantify landscape patterns dynamics in response to urbanization, with a case study of Mentougou District in Beijing, China from 1985 to 2014. We found that the total built-up area increased along with the population and economic indicators. The built-up area increased by one-third over the study period, with 73.38% of the increase from converted cropland and 12.22% from converted orchard. The urban expansion area was concentrated in the plain sub-region (<200 m elevation, comprising 68.85% of the expansion area). The landscape patterns varied over this period. For the whole region, the low mountain sub-region and the high mountain sub-region, landscape patterns gradually became more heterogeneous and fragmented, but they showed the opposite trend in the plain sub-region. None of the urbanization indicators (population, economic and built-up land area) were significantly correlated with landscape metrics for the whole region, but they were significantly correlated in the plain sub-region. The impacts of urbanization on landscape patterns were mainly focused on the plain sub-region, and the effects in the low mountain and high mountain sub-regions were weak. Future urban development in mountainous areas should focus on the protection of cropland and local industries as part of a sustainable development strategy for the whole region.

Quantifying landscape pattern and ecosystem service value changes in four rapidly urbanizing hill stations of Southeast Asia

Hill stations are known for their favorable cool climate and natural environments which generate valuable ecosystem services that benefit the local population, tourists and visitors. However, rapid urbanization threatens the sustainability of these highly valued fragile landscapes. We aim to characterize and quantify the changes in the landscape patterns and ecosystem service values (ESVs) of Baguio (Philippines), Bogor (Indonesia), Dalat (Vietnam), and Pyin Oo Lwin (Myanmar), and discuss their implications to landscape sustainability. We used remote sensing imagery to map land-use/cover (2001 and 2014), and spatial metrics and gradient analysis to characterize the changes in landscape pattern. We employed a benefit transfer method to estimate the changes in ESV and human-to-ESV ratio. A land-change model was used to simulate different scenarios of future built-up expansions (2014–2030). The landscapes of Dalat and Pyin Oo Lwin are becoming more fragmented, while those of Baguio and Bogor are getting more aggregated. Dalat had the highest decrease (absolute change) in ESV and H-ESV ratio, while Bogor had the highest percentage decrease (2001–2014). Rapid urbanization has been a major factor in the landscape transformation of Baguio, Bogor, Dalat and Pyin Oo Lwin. If the current built-up expansion rate will speed up, the decline in future ESV and H-ESV ratio (2014–2030) will be higher than if the rate will continue or slow down. Unless the concept of landscape sustainability is taken seriously in landscape and urban planning, the respective ‘values’ of these precious hill stations will become less and less.

Locally optimized separability enhancement indices for urban land cover mapping: Exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia

Abstract Landsat data were used to assess urbanization-induced dynamics in Land use/cover (LULC), surface thermal intensity, and its relationships with urban biophysical composition. The study was undertaken in Addis Ababa city, Ethiopia. Ground-based data and high resolution images were used as reference data in LULC classification. To more accurately quantify landscape patterns and their changes, we applied new locally optimized separability enhancement indices and decision rules (SEI–DR approach) to address commonly observed classification accuracy problems in urban environments. We tested the SEI–DR approach using eight Landsat images acquired between 1985 and 2010. Two approaches were applied to quantify surface heat intensity (SHIn) and to examine its spatial patterns over 25 years: thermal gradient analysis and hot spot analysis. A Simultaneous Autoregressive Spatial error model (SARerr) was used to explore relationships between surface temperature and biophysical variables describing urban surfaces. Compared to Maximum Likelihood (ML) and Support Vector Machine (SVM) classification, accuracy improvement achieved through use of the SEI–DR procedure was, respectively, 6% and 5% and the differences were statistically significant (P

Quantifying landscape pattern and assessing the land cover changes in Piatra Craiului National Park and Bucegi Natural Park, Romania, using satellite imagery and landscape metrics

Protected areas of Romania have enjoyed particular importance after 1989, but, at the same time, they were subject to different anthropogenic and natural pressures which resulted in the occurrence of land cover changes. These changes have generally led to landscape degradation inside and at the borders of the protected areas. In this article, 12 landscape metrics were used in order to quantify landscape pattern and assess land cover changes in two protected areas, Piatra Craiului National Park (PCNP) and Bucegi Natural Park (BNP). The landscape metrics were obtained from land cover maps derived from Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) images from 1987, 1993, 2000, 2009 and 2010. Three land cover classes were analysed in PCNP and five land cover map classes in BNP. The results show a landscape fragmentation trend for both parks, affecting different types of land covers. Between 1987 and 2010, in PCNP fragmentation was, in principle, the result not only of anthropogenic activities such as forest cuttings and illegal logging but also of natural causes. In BNP, between 1987 and 2009, the fragmentation affected the pasture which resulted in the occurrence of bare land and rocky areas because of the erosion on the Bucegi Plateau.

A method for delineating a hierarchically networked structure of urban landscape

We developed a new approach combining statistical and graphical methods to build a hierarchically networked structure for understanding spatial characteristics of urban landscapes at multiple scales. Natural breaks optimization algorithm is applied to determine the optimal number of urban land hierarchies and assign discrete patches into ordered sub-groups according to a selected geometric or functional attribute. Patches contained in a sub-group are linked to the patches in the next sub-group according to the spatial relationships between the patch centroids and Voronoi cells. The conceptual foundations and technical details of this approach are elaborated in the case study of building a hierarchically networked structure of urban built-up patches in Beijing. This approach can be applied to quantify landscape patterns of other land uses to facilitate assessments of interconnection between various types of land uses at varied hierarchical levels (spatial scales) and to evaluate ecological service functions of urban built infrastructures.

Monitoring landscape changes in Caucasian black grouse (Tetrao mlokosiewiczi) habitat in Iran during the last two decades.

Caucasian black grouse (Tetrao mlokosiewiczi) is on the 'red' list of species of high conservation concern as nearest threatened (NT) and also in level (I) of Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The black grouse distribution range in Iran is restricted to the Arasbaran region, Northwest of Iran, and the populations and range of this specialist bird species have been declining over the last decades. Management of forest and grassland structures is important for black grouse population survival. The main goals of this study were to monitor and quantify the landscape pattern changes in Caucasian black grouse habitat in the Arasbaran biosphere reserve in two periods of 14 years (1987-2001) and 10 years (2001-2011). For quantifying landscape pattern changes, various landscape metrics were derived by spatial analysis software FRAGSTATS 3.3, including NP (number of habitat patches), LPI (largest patch index) and TE (total edge). The results indicated that the proportion of forest decreased from 39.95 to 31.95% and the proportion of grassland decreased from 44.45 to 38.44% in the 24-year span. NP of forests increased in the first period and decreased in the second period of study. TE of dense forest at altitude above 1800 m decreased. Reduction of forest edge is an indicator of reduction in habitat availability for Caucasian black grouse which use the forest edge for living, lekking and hatching in upland. Our results provided quantitative data on habitat loss and fragmentation in the Arasbaran biosphere reserve and indicated negative impacts of the landscape structure changes on Black grouse habitat.

Gradient of Land Cover and Ecosystem Service Supply Capacities- A Comparison of Suburban and Rural Fringes of Towns Dresden (Germany) and Poznan (Poland)

Quantifying landscape pattern and its change is essential for the monitoring of changes in ecosystem services caused by urbanization and other processes. Landscape indicators can be very useful for such assessments. The authors used landscape metrics for a gradient analysis of land cover between cities and protected areas. The two cities Dresden (Germany) and Poznan (Poland) were chosen, because they are comparable due to inhabitants, area and location in former socialistic regimes. The biggest difference affects legal and socio-economic conditions. Overall, the study shows decrease of ecosystem services and diversity indices with increasing distance from the protected area, but the lines of trend near Dresden and Poznan have a different course. In comparison to Poznan, around Dresden are more protected areas and much more settlement areas are located near or even inside them. Protected areas around Poznan are more aggregated and more distant from the town center, have character that is more natural and are more diversified in terms of land cover configuration. On the other hand, in Dresden, thanks the more compact character of built-up areas and accompanied green urban areas, the landscape of suburban zone is more diversified and the benefits of ecosystem services are closer to the people. The reason are more restrictive legal aspects of spatial planning in Germany.

Decline of traditional landscape in a protected area of the southwestern Alps: The fate of enclosed pasture patches in the land mosaic shift

Traditional landscape elements such as pasture patches enclosed in a forest matrix are progressively disappearing throughout the European Alps. We assessed the land mosaic shift of a protected area located in the western Italian Alps. In particular, the dynamics of pasture patches were studied at both landscape and stand level. Land-cover mapping through object-oriented analysis of historical aerial photographs was used to assess land-cover changes between 1954 and 2000. Spatial statistics were used to quantify landscape patterns, and field samplings within pasture patches were used to explore tree regeneration structure and composition. Our results showed a significant increase in the number of pasture patches caused by their fragmentation following forest expansion. The total surface area of pasture patches decreased by 43% and their core area decreased by 94%. The encroachment of trees on less accessible areas of the pasture patches caused a reduction of patch shape at landscape scale. The gap filling process started 40-50 years ago and began with an early invasion of light demanding species like sycamore maple (Acer pseudoplatanus L.) and common ash (Fraxinus excelsior L.), followed by European beech (Fagus sylvatica L.) and secondarily silver fir (Abies alba Mill.). Traditional land-use and population decline in the Pesio Valley led to a reduction in ecotone areas. A transition to a more homogeneous landscape is expected in the next decades. Given the cultural and productive nature of these mountain meadow-pasture communities, extensive livestock grazing systems could be used to manage their future conservation.

SWAT模型对景观格局变化的敏感性分析——以丹江口库区老灌河流域为例

PDF HTML阅读 XML下载 导出引用 引用提醒 SWAT模型对景观格局变化的敏感性分析——以丹江口库区老灌河流域为例 DOI: 10.5846/stxb201303070366 作者: 作者单位: 郑州大学水利与环境学院,郑州大学水利与环境学院,郑州大学水利与环境学院 作者简介: 通讯作者: 中图分类号: P333 基金项目: 国家自然科学基金资助项目（40971128）；水体污染控制与治理专项课题资助项目（2011ZX07213-001） Sensitivity analysis of swat model on changes of landscape pattern：a case study from Lao Guanhe Watershed in Danjiangkou Reservoir Area Author: Affiliation: School of Environment and Water conservancy, Zhengzhou University,,School of Environment and Water conservancy, Zhengzhou University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:景观的空间配置与类型组成能够对流域的产流、产沙及非点源污染产生影响。在以往SWAT模型研究中，往往默认水文模型考虑了该影响。为分析SWAT模型对不同景观格局变化的敏感性，根据老灌河流域2000年土地利用在各子流域的组成，模拟研究区更为破碎、复杂的景观空间配置，通过设置多套试验参数，利用SWAT模型生成基于不同景观格局的模拟结果。结果表明，SWAT模型不能反映除坡度和面积变化之外的景观水平下各斑块之间因景观空间格局改变对流域产流、产沙以及非点源污染的影响；模型通过其他参数的调整，弥补了模型分析数据的不足，使实测数据与模型部分结果高度吻合。这表明，一个能够反映流域部分水文特征的SWAT模型，未必是对研究区真实情形的模拟，而是各个参数间平衡的结果。因此，在利用SWAT模型分析模拟景观变化时，不应默认模型能够模拟景观空间格局改变对流域水文过程的影响，同时研究者可以通过划分坡度带，提高模型对不同坡度土地利用的敏感性。 Abstract:A number of studies have demonstrated effects of the landscape composition and spatial configuration on the runoff, sediment yield and non-point pollution in a watershed. The SWAT model(Soil and Water Assessment Tool) was widely employed to explore the significance of land management practices on water, sediment, and agricultural chemical yields, which subdivides a watershed into sub-basins connected by a stream network and contain many Hydrologic Response Units (HRUs) characterized by unique combinations of land cover, soil and slope attributes. In a variety of the previous studies, the interaction between hydrographic features and landscape characteristics was taken for granted in the SWAT model, and calibrated model was frequently used to predict the eco-hydrological variation induced by possible land use changes without investigating sensitivity of model on changes of landscape pattern, and the results of model would be used to provide scientific foundation for decision-making in land use management. For a better understanding of SWAT model response to different landscape patterns, this study obtained a series of SWAT model outputs in Lao Guanhe watershed which is one of the head source of Danjiangkou Reservoir Area, by setting two land use scenarios with different landscape metrics, which are characterized by landscape composition and configurations, and proposed to quantify landscape pattern. By comparing the results of SWAT model using the real land-use data in 2000 to that using the simulated land use data, which have exactly same mean slope and area of each land use type in each sub-basin as the real land use map. It was found that, the SWAT model could display a substantial correlation between the runoff, sediment yields, non-point source pollutants and with slope and area of land use type, but failed to demonstrate the sensitivity of the results of SWAT model to the difference in landscape metrics. Perhaps because the model calculated each HRU separately, then summarized them for the output of the watershed. That is to say, if the SWAT model was applied to evaluate the effects of planting trees in the riparian strips on water quality of a stream, only the increase of forest land area and the descent of forest land slope would be taken in account. However, the interaction between forest land and other land use types, which might be more significant in eco-hydrological dynamics, could not play a part in water quality evaluation by using SWAT model. With further analysis, it is found that the runoff outputs of SWAT model, by using land-use data with different landscape characteristics, could not only match the measured data, but perfectly match each other, just by adjusting model parameters. Therefore, an outwardly reasonable output of SWAT model could be a perfect simulation of real situations, or come from shrewd calibration of model parameters. As a result, the SWAT model is not the default one to simulate the hydrologic process changed by the change of landscape spatial configuration, the sensitivity of SWAT model on changes of landscape pattern can be enhanced by defining slopes with different gradients. 参考文献 相似文献 引证文献

Detecting hot and cold spots in a seagrass landscape using local indicators of spatial association

Eelgrass (Zostera marina) is an important feature of coastal ecosystems in Atlantic Canada, providing a suite of valuable ecosystem services. These services, and its sensitivity to stressors, have prompted efforts to characterize the spatial and temporal dynamics of eelgrass landscapes in order to facilitate management and monitoring of coastal ecosystem health. Current methods for broad-scale mapping of eelgrass rely on aerial remote sensing and may not be appropriate in certain types of landscapes, particularly in turbid waters and areas lacking distinct boundaries. This study takes a novel approach to the quantification and analysis of seagrass landscape structure at multiple spatial scales using acoustic data and local spatial statistics. Data from a single-beam acoustic survey in Richibucto, New Brunswick, Canada were analyzed with geostatistical techniques and the Getis-Ord Gi* local spatial statistic in order to detect statistically significant zones of high and low cover in an estuarine seagrass bed. Results showed distinct and significant patterns in seagrass cover at multiple spatial scales within a region of apparently continuous spatial cover. Boundaries between areas of high and low cover were also detected. This study demonstrates how acoustic data and local spatial statistics can be used to quantify landscape pattern and to further the application of landscape techniques in the marine environment.