Identification and quantification of the hydrological impacts of imperviousness in urban catchments: a review

Urbanisation produces numerous changes in the natural environments it replaces. The impacts include habitat fragmentation and changes to both the quality and quantity of the stormwater runoff, and result in changes to hydrological systems. This review integrates research in relatively diverse areas to examine how the impacts of urban imperviousness on hydrological systems can be quantified and modelled. It examines the nature of reported impacts of urbanisation on hydrological systems over four decades, including the effects of changes in imperviousness within catchments, and some inconsistencies in studies of the impacts of urbanisation. The distribution of imperviousness within urban areas is important in understanding the impacts of urbanisation and quantification requires detailed characterisation of urban areas. As a result most mapping of urban areas uses remote sensing techniques and this review examines a range of techniques using medium and high resolution imagery, including spectral unmixing. The third section examines the ways in which scientists and hydrological and environmental engineers model and quantify water flows in urban areas, the nature of hydrological models and methods for their calibration. The final section examines additional factors which influence the impact of impervious surfaces and some uncertainties that exist in current knowledge.     

Land-cover change in upper Barataria Basin estuary,Louisiana, 1972-1992: increases in Wetland area

The Barataria Basin, Louisiana, USA, is an extensive wetland and coastal estuary system of great economic and intrinsic value. Although high rates of wetland loss along the coastal margin of the Barataria Basin have been well documented, little information exists on whether freshwater wetlands in the upper basin have changed. Our objectives were to quantify land-cover change in the upper basin over 20 years from 1972–1992 and to determine land-cover transition rates among land-cover types. Using 80-m resolution Landsat MSS data from the North American Landscape Characterization (NALC) data archive, we classified images from three time steps (1972, 1985, 1992) into six land-cover types: agriculture, urban, bottomland hardwood forest, swamp forest, freshwater marsh, and open water. Significant changes in land cover occurred within the upper Barataria Basin over the study period. Urban land increased from 8% to 17% of the total upper basin area, primarily due to conversions from agricultural land, and to a lesser degree, bottomland forest. Swamp forest increased from 30% to 41%, associated with conversions from bottomland hardwood forest and freshwater marsh. Overall, bottomland forest decreased 38% and total wetland area increased 21%. Within the upper Barataria, increases in total wetland area may be due to land subsidence. Based on our results, if present trends in the reduction of bottomland forest land cover were to continue, the upper Barataria Basin may have no bottomland hardwood forests left by the year 2025, as it is subjected to multiple stressors both in the higher elevations (from urbanization) and lower elevations (most likely from land subsidence). These results suggest that changes in the upper freshwater portions of coastal estuaries can be large and quite different from patterns observed in the more saline coastal margins.     

LANDSAT MID-INFRARED DATA AND GIS IN REGIONAL SURFACE SOIL-MOISTURE ASSESSMENT1

ABSTRACT: Landsat satellite Thematic Mapper (TM) data were used to assess regional soil moisture conditions. The mid-infrared (MIR) data of TM band 7 were overlain onto four principal land-use categories (Agricultural/Irrigated, Urban/Clearings, Forest/ Wetlands, Water) using a geographic information system (GIS). M data were used to assess four qualitative surface soil-moisture conditions (water/very wet, wet, moist, and dry) within each land-use category of a 208,354 ha southwestern Florida study area. The MIR response was inversely related to the qualitative surface soil-moisture content. Integration of Landsat TM MIR data with land use through GIS appears to be a useful technique for high-resolution regional soil moisture assessment, and further research to reline this technique is recommended.     

“5·12”地震前后都江堰市地表覆盖状况变化分析

本文以应用遥感技术,对“5·12”地震都江堰区域地表覆盖状况进行分析评价。选取都江堰市基于2007年的LandsatTM影像和2010年HJ-1卫星CCD影像,通过面向对象和目视解译相结合的方法,提取了草地、河流、旱地、水田、建设用地等9类生态类型环境覆盖信息。结果表明：“5·12”汶川地震对地表生态环境的变化较大,北...     

济南市近30年矿产开采遥感监测

利用遥感技术可快速准确地提取矿产开采的分布和面积,为环保部门执法管理提供及时、全面的信息。基于近30年(1985—2015年)来Landsat系列卫星影像,采用决策树分析和面向对象的分类技术,通过人机交互方式,提取出矿产开采的精细图斑。结果表明,从1985到2015年,矿产开采面积由3.35 km2增至35.11 km2,呈持续增大趋势。增速最快的时间集中在2005—2010年,说明这个期间段,济南市矿产开发强度最大。     

Temporal and Spatial Relationships Between Watershed Land Use and Salt Marsh Disturbance in a Pacific Estuary

Historical and recent remote sensing data can be used to address temporal and spatial relationships between upland land cover and downstream vegetation response at the watershed scale. This is demonstrated for sub-watersheds draining into Elkhorn Slough, California, where salt marsh habitat has diminished because of the formation of sediment fans that support woody riparian vegetation. Multiple regression models were used to examine which land cover variables and physical properties of the watershed most influenced sediment fan size within 23 sub-watersheds (1.4 ha to 200 ha). Model explanatory power increased (adjusted R(2) = 0.94 vs. 0.75) among large sub-watersheds (>10 ha) and historical watershed variables, such as average farmland slope, flowpath slope, and flowpath distance between farmland and marsh, were significant. It was also possible to explain the increase in riparian vegetation by historical watershed variables for the larger sub-watersheds. Sub-watershed area is the overriding physical characteristic influencing the extent of sedimentation in a salt marsh, while percent cover of agricultural land use is the most influential land cover variable. The results also reveal that salt marsh recovery depends on relative cover of different land use classes in the watershed, with greater chances of recovery associated with less intensive agriculture. This research reveals a potential delay between watershed impacts and wetland response that can be best revealed when conducting multi-temporal analyses on larger watersheds.     

The use of Landsat multispectral scanner data for the analysis and management of flooding on the river Severn,England

Remote sensing has emerged as one of the major techniques for the analysis and delineation of large floods. This analysis can provide data invaluable for the hydrological management of large river systems. A need for information on the extent of floodplain inundation for the lower reaches of the largest river in the UK was met by a search through Landsat images of floods and the analysis of the best example recorded. Automated classification of the Landsat imagery of this flood on the river Severn in 1977 was used to provide estimates of the extent and spatial distribution of inundation. Flood images were generated using the Plessey IDP 3000 image processor, and the maps derived accorded well with aerial photography and qualitative flood information. Three distinct floodplain environments were delineated and flood images produced by different spectral bands compared. Specific questions prompted by flood hazard management and concerning the processes and extent of flooding were answered by the Landsat data analysis. Management of the flood risk of large rivers is expensive and remote sensing data is a relatively cheap and effective way of monitoring control works and providing data for the prediction of the effects of future hydrological works. Remote sensing is a practical way in which spatial information concerning the behavior of large dynamic systems can be obtained both quickly and relatively cheaply.     

FLOOD HAZARD STUDIES IN THE MISSISSIPPI RIVER BASIN USING REMOTE SENSING1

ABSTRACT. The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicate that ERTS-I is extremely useful as a regional tool for flood management. Quantitative estimates of area flooded were made in St. Charles County, Missouri and Arkansas. Flood hazard mapping was conducted in three study areas along the Mississippi River using pre-flood ERTS-1 imagery enlarged to 1:250,000 and 1:100,000 scale. The flood prone areas delineated on these maps correspond to areas that would be inundated by significant flooding (approximately the 100 year flood). The flood prone area boundaries were generally in agreement with flood hazard maps produced by the U. S. Army Corps of Engineers and U. S. Geological Survey although the latter are somewhat more detailed because of their larger scale. Initial results indicate that ERTS-1 digital mapping of flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.     

ESTIMATION OF SOIL MOISTURE WITH API ALGORITHMS AND MICROWAVE EMISSION1

Large area soil moisture estimations are required to describe input to cloud prediction models, rainfall distribution models, and global crop yield models. Satellite mounted microwave sensor systems that as yet can only detect moisture at the surface have been suggested as a means of acquiring large area estimates. Relations previously discovered between microwave emission at the 1.55 cm wavelength and surface moisture as represented by an antecedent precipitation index were used to provide a pseudo infiltration estimation. Infiltration estimates based on surface wetness on a daily basis were then used to calculate the soil moisture in the surface 0–23 cm of the soil by use of a modified antecedent precipitation index. Reasonably good results were obtained (R²= 0.7162) when predicted soil moisture for the surface 23 cm was compared to measured moisture. Where the technique was modified to use only an estimate of surface moisture each three days an R² value of 0.7116 resulted for the same data set. Correlations between predicted and actual soil moisture fall off rapidly for repeat observations more than three days apart. The algorithms developed in this study may be used over relatively flat agricultural lands to provide improved estimates of soil moisture to a depth greater than the depth of penetration for the sensor.