A decision-oriented model to evaluate the effect of land use and agricultural management on herbicide contamination in stream water

Modelling stream water pollution by herbicides in agricultural areas is a critical issue since numerous and incompletely known processes are involved. A decision-oriented model, SACADEAU-Transf, which represents water and pesticide transfer in medium-sized catchments (10–50 km²) is presented. This model aims at evaluating the effect of land use, agricultural practice and landscape on the contamination of stream water in rural catchments. The processes are represented in an easily understandable way with a moderate amount of information, producing semi-quantitative and spatialized outputs. Modelling focuses on the first few months after herbicide application when high levels of contamination are generally observed, by considering transfer through the catchment area via surface and subsurface flow. The surface flow, based on a tree plot network representation of the catchment, is controlled by soil-surface properties and saturated conditions. The subsurface flow based on Topmodel concepts is controlled by the topography. Herbicide transfer is coupled to water transfer by taking into account the main characteristics of the chemicals. The model simulates the daily water and herbicide outflow at the outlets of the farmers' fields as well as from the catchment. Preliminary results on maize herbicide transfer are presented for an agricultural catchment with an area of 17 km² located in north-western France. The relevance of SACADEAU-Transf model is discussed in view of the qualities required for the decision-oriented models developed for improving agro-environmental management.     

Use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis NPP measures across the eastern USA

Moderate Resolution Imaging Spectroradiometer (MODIS) estimates of gross primary production (GPP) were validated using field-based estimates of net primary production from the Forest Inventory and Analysis (FIA) Program across the eastern USA. A total of 54 969 MODIS pixels and co-located FIA plots were analysed to validate MODIS GPP estimates. We used a data resolution of individual MODIS pixels and co-located FIA plots, and used detailed pixel- and plot-specific attributes by applying screening variables (SVs) to assess conditions under which MODIS GPP was most strongly validated. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. The six hypotheses addressed were (1) MODIS pixel quality checks, (2) FIA plot quality checks, (3) land-cover classification comparability of co-located MODIS pixels and FIA plots, (4) FIA plot homogeneity, (5) FIA plot tree density and (6) MODIS seasonal variation. SVs were assessed in terms of trade-off between improved relations and reduced number of samples. MODIS seasonal variation and FIA plot tree density were the two most efficient SVs, followed by basic quality checks for each data set. Sequential application of SVs indicated that combined usage of five of the eight SVs provided an efficient data set of 17 090 co-located MODIS pixels and FIA plots, which raised the Pearson correlation coefficient from 0.01 for the Complete data set of 54 969 plots to 0.48 for this screened subset of 17 090 plots. The screened subset of plots exhibited good representation of the Complete data set in terms of species abundance, plot distribution and mean productivity. We conclude that the application of SVs provides a useful approach to ensure compatibility of two data sets for broad-scale forest carbon budget analysis and monitoring.     

A new algorithm for grid-based hydrologic analysis by incorporating stormwater infrastructure

We developed a new algorithm, the Adaptive Stormwater Infrastructure (ASI) algorithm, to incorporate ancillary data sets related to stormwater infrastructure into the grid-based hydrologic analysis. The algorithm simultaneously considers the effects of the surface stormwater collector network (e.g., diversions, roadside ditches, and canals) and underground stormwater conveyance systems (e.g., waterway tunnels, collector pipes, and culverts). The surface drainage flows controlled by the surface runoff collector network are superimposed onto the flow directions derived from a DEM. After examining the connections between inlets and outfalls in the underground stormwater conveyance system, the flow accumulation and delineation of watersheds are calculated based on recursive computations. Application of the algorithm to the Sangdong tailings dam in Korea revealed superior performance to that of a conventional D8 single-flow algorithm in terms of providing reasonable hydrologic information on watersheds with stormwater infrastructure.     

Using Linked Micromap Plots to Characterize Omernik Ecoregions

The paper introduces linked micromap (LM) plots for presenting environmental summaries. The LM template includes parallel sequences of micromap, label, and statistical summary graphics panels with attention paid to perceptual grouping, sorting and linking of the summary components. The applications show LM plots for Omernik Level II Ecoregions. The summarized United States continental data includes USGS digital elevation, 30-year normal precipitation and temperature, and 8 million AVHRR pixels classified into 159 types of land cover. One LM plot uses a line-height glyph to represent all 159 land cover percentages per ecoregion. LM plots represent new visualization methodology that is useful in the data and knowledge based pattern representation and knowledge discovery process. The LM plots focus on providing an orienting overview. The overview provides a starting place for subsequent drilling down to what could otherwise be viewed as an overwhelming mass of data. The overview also provides a starting place to learn about the intellectual structure that lies behind the notion of ecoregions and begins to connect this abstract structure to quantitative methods.     

Assessment of Digital Elevation Model (DEM) aggregation methods for hydrological modeling: Lake Chad basin,Africa

Digital Elevation Models (DEMs) are used to compute the hydro-geomorphological variables required by distributed hydrological models. However, the resolution of the most precise DEMs is too fine to run these models over regional watersheds. DEMs therefore need to be aggregated to coarser resolutions, affecting both the representation of the land surface and the hydrological simulations. In the present paper, six algorithms (mean, median, mode, nearest neighbour, maximum and minimum) are used to aggregate the Shuttle Radar Topography Mission (SRTM) DEM from 3″ (90 m) to 5′ (10 km) in order to simulate the water balance of the Lake Chad basin (2.5 Mkm²). Each of these methods is assessed with respect to selected hydro-geomorphological properties that influence Terrestrial Hydrology Model with Biogeochemistry (THMB) simulations, namely the drainage network, the Lake Chad bottom topography and the floodplain extent.The results show that mean and median methods produce a smoother representation of the topography. This smoothing involves the removing of the depressions governing the floodplain dynamics (floodplain area<5000 km²) but it eliminates the spikes and wells responsible for deviations regarding the drainage network. By contrast, using other aggregation methods, a rougher relief representation enables the simulation of a higher floodplain area (>14,000 km² with the maximum or nearest neighbour) but results in anomalies concerning the drainage network. An aggregation procedure based on a variographic analysis of the SRTM data is therefore suggested. This consists of preliminary filtering of the 3″ DEM in order to smooth spikes and wells, then resampling to 5′ via the nearest neighbour method so as to preserve the representation of depressions. With the resulting DEM, the drainage network, the Lake Chad bathymetric curves and the simulated floodplain hydrology are consistent with the observations (3% underestimation for simulated evaporation volumes).     

Representing effects of micro-topography on runoff generation and sub-surface flow patterns by using superficial rill/depression storage height variations

An adequate representation of micro-topography in spatially explicit, physically based models can be crucial in modeling runoff generation, surface/subsurface flow interactions or subsurface flow patterns in hydrological systems with pronounced micro-topography. However, representation of micro-topography in numerical models usually requires high grid resolutions to capture relevant small scale variations in topography at the range of centimeters to meters. High grid resolutions usually result in longer simulation times, especially if fully integrated model approaches are used where the governing partial differential equations for surface and subsurface flow are solved simultaneously. This often restricts the implementation of micro-topography to plot scale models where the overall model domain is small to minimize computational cost resulting from a high grid resolution. In this study an approach is presented where a highly resolved digital elevation model (DEM) for a hummocky topography in a plot scale wetland model (10 m × 21 m × 2 m), is represented by spatially distributed rill/depression storage zones in a numerical model with a planar surface. By replacing the explicit micro-topography with spatially distributed rill/depression storage zones, important effects of micro-topography on surface flow generation and subsurface transport characteristics (e.g. residence time distributions) are being preserved, while at the same time the number of computational nodes is reduced significantly. We demonstrate that the rill/depression storage concept, which has been used for some time to represent time delays in the generation of surface runoff, can also be used to mimic subsurface flow patterns caused by micro-topography. Results further indicate that the rill/depression storage concept is an efficient tool to represent micro-topography in plot scale models because model computation times drop significantly. As important aspects of surface and subsurface flows induced by micro-topography can be mimicked adequately by applying the rill/depression storage concept on a coarser grid, it may also be a useful tool to represent micro-topography in numerical flow models beyond the plot scale.     

Optimising drainage from sugar cane fields using a one-dimensional flow routing model: a case study from Ripple Creek,North Queensland

Inundation of sugar cane fields in the Ripple Creek catchment is perceived by some cane farmers to be a major contributor to loss of production. To alleviate this inundation, drainage systems have been designed which are capable of removing surface water very rapidly. However, when the Herbert River is in flood this water may have nowhere to go. This combination of an efficient drainage system, the lack of an outlet for the water, and the growing of cane on land which may be unsuitable, has led to some farms facing extended periods of inundation. For this reason, proposals have been made to the Ripple Creek Drainage Board to modify the drainage system to produce a more equitable distribution of inundation. In this paper, we examined the application of the Mike-11 modelling system to the Ripple Creek catchment. We found that the modelled predictions of depth, discharge and velocity matched observational data collected as part of an intensive CSIRO monitoring program. The model developed was then used to examine the hydrologic impact of opening a new channel to divert flow into the Seymour River. We found that opening this channel had some impact on indundation in parts of the catchment, but that the impact depended on whether or not the Herbert River was in flood at the time.     

基于DEM的数字流域河网编码方法研究

数字流域模型中基于二叉树理论的河网编码方法能够实现任意河段的直接定位和高效的拓扑运算.论文首先讨论了利用DEM提取河网的基本原理,然后根据二叉树二元编码规则完成数字流域的河网编码.     

Estimation of catchment-scale water-balance with a soil-vegetation-atmosphere transfer model

Catchments with a small elevation range and relatively long dry periods in high radiation conditions may be described as an array of vertical one-dimensional pathways for water and energy. Such a representation enhances the ability of SVAT modeling to simulate mass exchanges across the catchment. This note reports on a comparison of a Soil-Vegetation-Atmosphere Transfer (SVAT) model (Braud et al., 1995), a deterministic hydrological model (Dawes and Hatton, 1993) and a stochastic hydrological model (Sivapalan and Woods, 1995; Kalma et al., 1995). The original version of the SVAT model only considers vertical transport and this one-dimensional representation must be aggregated to describe the entire catchment. Therefore, two new versions have been developed: a deterministic SVAT model which sub-divides the catchment into 40 sub-regions linked by surface flow, and a stochastic model which provides a distribution of the output fluxes as related to the spatial distribution of initial water content and/or soil properties. All simulations have been made for a 60-day period.     

Hierarchical GTM: constructing localized nonlinear projectionmanifolds in a principled way

It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets and, therefore, a hierarchical visualization system is desirable. In this paper, we extend an existing locally linear hierarchical visualization system PhiVis in several directions: 1) We allow for nonlinear projection manifolds. The basic building block is the Generative Topographic Mapping (GTM). 2) We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. 3) Using tools from differential geometry, we derive expressions for local directional curvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the ancestor visualization plots which are captured by a child model. We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set and apply our system to two more complex 12- and 18-dimensional data sets     

Impact of DEM accuracy and resolution on topographic indices

Topography is an important land-surface characteristic that affects most aspects of the water balance in a catchment, including the generation of surface and sub-surface runoff; the flow paths followed by water as it moves down and through hillslopes and the rate of water movement. All of the spatially explicit fully distributed hydraulic and hydrological models use topography (represented by the DEM of the area modelled) to derive bathymetry. DEM is also used to derive some other key information critical in fully distributed hydraulic and hydrological models.With high-resolution DEMs such as LiDAR (Light Detection and Ranging) becoming more readily available and also with the advancements in computing facilities which can handle these large data sets, there is a need to quantify the impact of using different resolution DEMs (e.g. 1 m against 10 m or 25 m) on hydrologically important variables and the loss of accuracy and reliability of the results as we move from high resolution to coarser resolution.The results from statistical analysis carried out to compare field survey elevations with the LiDAR DEM-derived elevations, show that there are small differences between the two data sets but LiDAR DEM is a reasonably good representation of the actual ground surface compared to other commonly used DEMs derived from contour maps.The results from the analysis clearly show that the accuracy and resolution of the input DEM have serious implications on the values of the hydrologically important spatial indices derived from the DEM. The result also indicates that the loss of details by re-sampling the higher resolution DEM to coarser resolution are much less compared to the details captured in the commonly available coarse resolution DEM derived from contour maps. Topographic indices based on contour derived DEMs should be used with caution and where available, the higher resolution DEM should be used instead of the coarse resolution one.     

Extraction of bajadas from digital elevation models and satellite imagery

A methodology was designed for the extraction of bajadas from the 15 min US Geological Survey digital elevation models and Landsat Thematic Mapper imagery. The method was demonstrated for the Death Valley-California where progressive eastward tilting has enabled the west-side fans to coalesce and form bajadas. First, the drainage that crossed the uplands and the bajadas was extracted from the DEM. The drainage pixels were successively grown by checking the surrounding pixels on the basis of their gradient. It was concluded that for gradient in the interval [2°,11°] the upslope bajadas border was segmented. In order to eliminate the drainage pixels that belonged to the uplands, the drainage pixels were subtracted. Then, the isolated small 8-connected foreground pixels were identified and subtracted too. Finally, region growing was performed again to the remaining pixels with the same growing criterion. Isolated 8-connected background pixels, representing almost flat regions inside bajadas, were identified and merged to the segmented pixels. At the end, by taking into account the spectral response in the satellite image, the downslope border of bajadas was segmented. The extracted polygon was in agreement with the information depicted on (a) the US Geological Survey topographic map of scale 1:100,000 and (b) the satellite image and (c) the polygon classified manually by a photo-interpreter.     

基于几何流多级树Bandelet分割编码的医学图像压缩方法

本文提出了一种新的医学图像压缩方法,利用稀疏表示方法结合图像结构的几何规律,构建图像的灰度级有规则变化的方向的几何流表示方法,获得二元方形图像四叉树表示形式。针对几何正则化数据的小波分解结果存在较少的显着系数问题,使用二维向量场表示正则性的方向,并用样条表示法得到了这些方向的逼近。最后,在几何流图像的方向分解的基础上,利用M-band离散小波变换构建多级树Bandelet分割编码方式,实现了Bandelet系数计算改进。实验结果表明,该方法可有效提高医学图像压缩方法的计算效率。     

Errors in river lengths derived from raster digital elevation models

Length of river reaches is one of the most important characteristics of stream networks when applying hydrological or environmental simulation models. A common method of obtaining estimates of river lengths is based on deriving flow directions, accumulated area and drainage lines from raster digital elevation models (DEM). This method leads to length estimates with variable accuracy, which depends on DEM horizontal resolution, flatness of terrain, DEM vertical accuracy, the algorithm used to obtain flow directions and the way by which distances are calculated over raster structures. We applied an automatic river length extraction method for eight river reaches in the River Uruguay Basin (206 000 km²), in Southern Brazil, and compared its results to the lengths obtained from drainage vector lines digitalized over satellite images. Our results show that relative errors can be higher than 30% in flat regions with relatively low DEM resolution. Preprocessing of DEM by the method known as stream burning greatly improves results, reducing errors to the range 1.9–7.4%. Further improved estimates were obtained by applying optimized values for the length of orthogonal and diagonal steps called distance transforms, reducing the errors to the range ?2.0–3.3%.     

DEM generation using ASAR (ENVISAT) for addressing the lack of freshwater ecosystems management,Santa Cruz Island,Galapagos

Low relief oceanic islands often suffer from scarcity of freshwater resources. Remote sensing has proved to be an effective tool to generate valuable data for hydrological analysis and has improved the management of ecosystems and water. However, remotely sensed data are often tested over areas with existing validation databases and not always where the need is greatest. In this paper we address the need for topographical data to understand the hydrological system of Santa Cruz Island (Galapagos archipelago) so that management of freshwater ecosystems and resources can take place. No high resolution, high accuracy topographical data exist for Santa Cruz Island, and its growing population has created an urgent need for water resource management and protection of unique and pristine ecosystems.Inaccessible National Park land covers more than 97% of Galapagos territory, which makes the use of remote sensing methods indispensable. SRTM data was insufficient in terms of grid size (90 m) to carry out the needed data analysis. We used ASAR data (ENVISAT) in VV polarization image mode for Digital Elevation Model (DEM) generation, in order to extract drainage network, watersheds, and flow characteristics from a morpho-structural analysis.Results show the high potential of these data for both interferometric and radargrammetric generation methods. Although interferometry suffered from low coherence over highly vegetated areas, it showed high precision over the rest of the island. Radargrammetry gave consistent results over the entire island, and details were enhanced by integrating the 90 m SRTM data as an external DEM. Accuracy of the SRTM and the combined radargrammetric/SRTM DEM was similar, with the radargrammetric having a finer pixel-based resolution (20 m).Validation of the extracted drainage networks and watersheds was carried out using ground-based field observations and comparison to mapped river networks visually extracted from aerial photographs and high resolution (1 m) satellite imagery available on GoogleEarth^©. For the first time, watershed characteristics and flow paths were made available for an island of the Galapagos archipelago. Furthermore, the drainage network is shown to be strongly influenced by observed and extracted structural discontinuities. Having characterized freshwater flow, water balance calculations were carried out for Pelican Bay watershed, where urban areas, agricultural land and Galapagos National Park land are concomitant.     

Maintaining the confidentiality of plot locations by exploiting the low sensitivity of forest structure models to different spectral extraction kernels

The United States Forest Service Forest Inventory and Analysis (FIA) unit maintains a large national network of inventory plots. While the consistency and extent of this network make FIA data attractive for ecological modelling, the FIA is charged by statute not to publicly reveal inventory plot locations. However, use of FIA plot data by the remote sensing community often requires that plot measurements be matched with spatially correspondent values from spectral or geographic data layers. Extracting spatial data in a known way and associating it with plot information leaves open the possibility that a user might use extracted spatial characteristics and a moving window filter to directly infer the plot's location. Direct inference of plot location in this way would be impossible, however, if the original method of sampling the geographic data was unknown. Tests using five Landsat scenes covering a wide range of ecological types showed that varying the weights of pixels within approximately 50 m of the plot centre has little effect on the quality of subsequent models predicting basal area. This finding may support the development of automated extraction routines that vary (perhaps randomly) the geographic data extraction process and therefore increase the security of FIA plot locations.     

Extraction of drainage networks by using the consistent labeling technique

Automatic deduction of the drainage network direction from Landsat imagery is a problem in remote sensing. The problem can be formulated in the abstract as a consistent labeling problem which is given a set of units (stream segments), possible labels (flow directions), and constraints on the way adjacent stream segments must be labeled. The goal is to find a mapping from their units to the labels that satisfies the constraints. Consistent labeling problems can be solved by tree search algorithms. In this paper, the stream labeling problem is formulated as a consistent labeling problem. The extraction of stream and valley segments from the Landsat images is discussed, and constraints on segments which meet at junctions are given. The tree search algorithm, employing a method called forward checking, is given and is used to determine the flow direction of all the stream segments in a way that is globally consistent with the junction constraints.     

GIS-based modeling of secondary hydrocarbon migration pathways and its application in the northern Songliao Basin, northeast China

Hydrocarbon migration pathways are the linkage between hydrocarbon source areas and accumulation sites. Modeling accurately the pathways of hydrocarbon migration is of important significance in determining the location of favorable petroleum exploration targets. In this paper, GIS-based modeling algorithms are presented for searching the pathways of secondary hydrocarbon migration by considering the geologic mechanisms. These algorithms are constructed on a raster digital elevation model (DEM) of the top boundary of a carrier bed, in which secondary migration occurred. On the DEM, a 3×3 pixel sized window is used for searching. The center of the search window is initially assumed at a point on the boundary of a hydrocarbon source area, from which the secondary hydrocarbon migration starts. The altitude values in the eight adjoining pixels enclosing the central pixel of the search window are compared, and the pixel with an altitude value not only larger than the central pixel but also the largest of the eight surrounding pixels is the next target pixel where the search window will move to. Each searched path will terminate at either a convex point, which indicates the existence of a trap for hydrocarbon accumulation, or a point on the boundary of the DEM, which suggests that the pathway of hydrocarbon migration extends outside the DEM. In addition, a concourse point of two paths is also considered as a termination point of either path. The algorithms were successfully applied in the modeling of the secondary migration pathways in the northern Songliao Basin, northeast China. The modeled results matched well with drilling data, suggesting the robustness of the algorithms.     

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing ground plots whose coordinates are obtained from Global Positioning System (GPS) receivers that are calibrated to the same geographic coordinate system, and then matching ground plots to image pixels containing the centers of the ground plots. Errors in rectification and GPS coordinates cause observations of ground attributes to be associated with spectral values of incorrect pixels which, in turn, introduces classification errors into the resulting maps. The most important finding of the study is that for common magnitudes of rectification and GPS errors, as many as half the ground plots may be assigned to incorrect pixels. The effects on areal estimates obtained by aggregating class predictions for individual pixels are deviation of the estimates from their true values, erroneous confidence intervals, and incorrect inferences. Results are reported in detail for both probability-based (design-based) and model-based approaches to inference for proportion forest area using maps constructed from Landsat imagery, forest inventory plot observations and a logistic regression model.