Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture,groundwater, and digital elevation data

Inadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.     

Spatio-temporal evolution and time-stable characteristics of soil moisture within remote sensing footprints with varying soil, slope, and vegetation

Air-borne passive microwave remote sensors measure soil moisture at the footprint scale, a scale of several hundred square meters or kilometers that encompasses different characteristic combinations of soil, topography, vegetation, and climate. Studies of within-footprint variability of soil moisture are needed to determine the factors governing hydrologic processes and their relative importance, as well as to test the efficacy of remote sensors. Gridded ground-based impedance probe water content data and aircraft-mounted Electronically Scanned Thinned Array Radiometer (ESTAR) pixel-average soil moisture data were used to investigate the spatio-temporal evolution and time-stable characteristics of soil moisture in three selected (LW03, LW13, LW21) footprints from the Southern Great Plains 1997 (SGP97) Hydrology Experiment. Better time-stable features were observed within a footprint containing sandy loam soil than within two pixels containing silty loam soil. Additionally, flat topography with split wheat/grass land cover produced the largest spatio-temporal variability and the least time stability in soil moisture patterns. A comparison of ground-based and remote sensing data showed that ESTAR footprint-average soil moisture was well calibrated for the LW03 pixel with sandy loam soil, rolling topography, and pasture land cover, but improved calibration is warranted for the LW13 (silty loam soil, rolling topography, pasture land) and LW21 (silty loam soil, flat topography, split vegetation of wheat and grass land with tillage practice) pixels. Footprint-scale variability and associated nonlinear soil moisture dynamics may prove to be critical in the regional-scale hydroclimatic models.     

Assessment of the Accuracy of SRTM C- and X-Band High Mountain Elevation Data: a Case Study of the Polish Tatra Mountains

Global digital elevation models (DEMs) are an invaluable source of information in large area studies. Of particular interest are shuttle radar topography mission (SRTM) data that are freely available for the scientific community worldwide. Prior to any application, global datasets should be evaluated using reference data of higher accuracy. Therefore, the main objective of this study was to assess the accuracy of the SRTM C-band (version 4) DEM and SRTM X-band DEM of mountainous areas located in Poland and to examine the quality of data in relation to topographic parameters, radar beam geometry, initial voids in data and the presence of forest cover. A DEM from the Central National Geodetic and Cartographic Inventory, Poland, served as a reference. The study consisted of three steps: (i) the computation of vertical errors of the SRTM C- and X-band DEMs, (ii) the examination of any systematic bias in the data, and (iii) the analysis of the relationships between the elevation errors and terrain slope, aspect, local incidence angle, occurrence of voids and land cover. We found that the SRTM C- and X-band DEMs have mean errors equal to 4.31 ± 14.09 and 9.03 ± 37.40 m and root mean square errors equal to 14.74 and 38.47 m, respectively. Only 82 % of the C-band DEM and 74 % of the X-band DEM vertical errors had absolute values below 16 m. We found that the most important factors determining the occurrence of high errors were the distribution of initial voids and high slope angles for the C-band DEM, and local incidence angle, slope, aspect and radar beam geometry for the X-band DEM. In both cases, the presence of forest cover increased the mean error by approximately 10 m.     

Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2

Active microwave remote sensing observations of backscattering, such as C‐band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS‐2) satellite, have the potential to measure moisture content in a near‐surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near‐surface soil moisture with the ERS‐2 satellite is explored by comparing model estimates of backscattering with ERS‐2 SAR observations. This comparison was made for two ERS‐2 overpasses coincident with near‐surface soil moisture measurements in a 6 ha catchment using 15‐cm time domain reflectometry probes on a 20 m grid. In addition, 1‐cm soil moisture data were obtained from a calibrated soil moisture model. Using state‐of‐the‐art theoretical, semi‐empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r² values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r² values. Likewise, using the first day of ERS‐2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r² values. Moreover, RMS differences were as large as 3·7 dB and r² values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS‐2 SAR data may be useful for estimating fields‐scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd.     

The effects of scene heterogeneity on soil moisture retrieval from passive microwave data

The τ–ω model of microwave emission from soil and vegetation layers is widely used to estimate soil moisture content from passive microwave observations. Its application to prospective satellite-based observations aggregating several thousand square kilometres requires understanding of the effects of scene heterogeneity. The effects of heterogeneity in soil surface roughness, soil moisture, water area and vegetation density on the retrieval of soil moisture from simulated single- and multi-angle observing systems were tested. Uncertainty in water area proved the most serious problem for both systems, causing errors of a few percent in soil moisture retrieval. Single-angle retrieval was largely unaffected by the other factors studied here. Multiple-angle retrievals errors around one percent arose from heterogeneity in either soil roughness or soil moisture. Errors of a few percent were caused by vegetation heterogeneity. A simple extension of the model vegetation representation was shown to reduce this error substantially for scenes containing a range of vegetation types.     

THE INFLUENCE OF TOPOGRAPHY ON TIME AND SPACE DISTRIBUTION OF SOIL SURFACE WATER CONTENT

The distribution of water content in time and space at the soil surface has been investigated on a small farmland catchment (1.3 km² ) from four field surveys corresponding to different moisture statuses. For each survey, about 400 samples were collected at the soil surface at a depth of 5 cm along ten axes parallel to the greatest slope. The relationship between the measurements and the topography has been analysed. The structure of the data is well explained by a topographic index referring to the downslope conditions and defined as the elevation difference between the sample point and the stream point corresponding to the outlet of the water pathway derived from the digital elevation model (DEM). This index can be considered as an hydraulic head, at least for saturated conditions. A threshold for this index allows two domains within the catchment to be distinguished; an upper domain where the water content is nearly constant and varies slowly, and a lower domain where moisture status increases and is highly variable. The spatial distribution of these two domains is well correlated to the spatial distribution of the soils. Thus, both topography and the spatial distribution of soil appear to control the spatial distribution of surface water content at the 1-km² scale. © 1997 by John Wiley & Sons Ltd.     

Influence of the topography of the surface of the Earth on vertical sounding of the temperature profile

Atmospheric temperature and humidity fields as well as information on other meteorological parameters are nowadays retrieved from radiance measurements recorded by operational meteorological satellites. Up to now, the inversion procedures used only take into account crude information on the topography of the Earth’s surface. However, the applied radiative transfer codes have to consider the Earth’s surface as the lower boundary of the atmospheric model and, therefore, need a more precise mean elevation and a classification of the roughness of the Earth’s surface. The influence of the topography of the Earth surface on retrieved temperature profiles is studied by using a physico-statistical inversion method. An objective analysis is made of the more precise mean elevation and derivation of roughness parameters using a new high-resolution digital elevation model (DEM) with a resolution of 500 m×500 m. By means of a geomorphological process and a newly developed topography rejection test, areas with a high surface roughness are localized and singled out. The influence of topography on the retrieved temperature profiles is illustrated by case studies. Changes are found predominantly in areas with a high variation of topography. Using the new high-resolution DEM and the topography rejection test, the geographical position of the calculated temperature profiles tends to be shifted towards areas with a small vertical variation of topography. The mean elevation determined by the new elevation model better characterizes the area observed. Hence, the temperature profiles can be calculated down to lower atmospheric levels. Furthermore, a guess profile better describing the atmospheric situation is selected by the more precise elevation. In addition, the temperature profiles obtained near the coast are improved considerably by the more precise determination of the surface property ‘sea’ and ‘land,’ respectively. Integration of an independent physical information such as topography leads, on average, to a slight improvement of the results of the physico-statistical inversion procedure. In some cases, however, significant improvements have been achieved regarding the desired accuracy of temperature profiles of the order of 1 K. In future, the spatial resolution of new high-resolution sounding instrumentation on the next generation of operational meteorological satellites will be increased. To exploit the resolving power of this new instrumentation, the different variation of the topography of the Earth surface, especially in regions with a high variation of topography, can be taken into account more precisely by using a high-resolution DEM.     

Calibration of an integrated land surface process and radiobrightness (LSP/R) model during summertime

In this study, a soil vegetation and atmosphere transfer (SVAT) model was linked with a microwave emission model to simulate microwave signatures for different terrain during summertime, when the energy and moisture fluxes at the land surface are strong. The integrated model, land surface process/radiobrightness (LSP/R), was forced with weather and initial conditions observed during a field experiment. It simulated the fluxes and brightness temperatures for bare soil and brome grass in the Northern Great Plains. The model estimates of soil temperature and moisture profiles and terrain brightness temperatures were compared with the observed values. Overall, the LSP model provides realistic estimates of soil moisture and temperature profiles to be used with a microwave model. The maximum mean differences and standard deviations between the modeled and the observed temperatures (canopy and soil) were 2.6 K and 6.8 K, respectively; those for the volumetric soil moisture were 0.9% and 1.5%, respectively. Brightness temperatures at 19 GHz matched well with the observations for bare soil, when a rough surface model was incorporated indicating reduced dielectric sensitivity to soil moisture by surface roughness. The brightness temperatures of the brome grass matched well with the observations indicating that a simple emission model was sufficient to simulate accurate brightness temperatures for grass typical of that region and surface roughness was not a significant issue for grass-covered soil at 19 GHz. Such integrated SVAT-microwave models allow for direct assimilation of microwave observations and can also be used to understand sensitivity of microwave signatures to changes in weather forcings and soil conditions for different terrain types.     

Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China

The profile characteristics and the temporal dynamics of soil moisture variation were studied at 26 locations in Da Nangou catchment (3.5 km²) in the loess area of China. Soil moisture measurements were performed biweekly at five depths in the soil profile (0–5, 10–15, 20–25, 40–45 and 70–75 cm) from May to October 1998 using Delta-T theta probe. Soil moisture profile type and temporal variation type and their relationship to topography and land use were identified by detrended canonical correspondence analysis (DCCA) and correlation analysis. The profile distribution of time-averaged soil moisture content can be classified into three types i.e. decreasing-type, waving-type and increasing-type. The profile features of soil moisture (e.g. profile gradient and profile variability) are influenced by different environmental factors. The profile type of soil moisture is only attributed to land use while profile gradient and profile variability of soil moisture is mainly related to land use and topography (e.g. landform type and slope). The temporal dynamics of layer-averaged soil moisture content is grouped into three types including three-peak type, synchro-four-peak type and lagged-four-peak type. These types are controlled by topography rather than by land use. The temporal dynamic type of soil moisture shows significant correlation with relative elevation, slope, aspect, while temporal variance displays significant relation with slope shape. The mean soil moisture is related to both the profile and dynamics features of soil moisture and is controlled by both land use and topography (e.g. aspect, position, slope and relative elevation). The spatial variability of soil moisture across landscape varies with both soil depths and temporal evolution.     

Topographic accuracy assessment of bare earth lidar-derived unstructured meshes

This study is focused on the integration of bare earth lidar (Light Detection and Ranging) data into unstructured (triangular) finite element meshes and the implications on simulating storm surge inundation using a shallow water equations model. A methodology is developed to compute root mean square error (RMSE) and the 95th percentile of vertical elevation errors using four different interpolation methods (linear, inverse distance weighted, natural neighbor, and cell averaging) to resample bare earth lidar and lidar-derived digital elevation models (DEMs) onto unstructured meshes at different resolutions. The results are consolidated into a table of optimal interpolation methods that minimize the vertical elevation error of an unstructured mesh for a given mesh node density. The cell area averaging method performed most accurate when DEM grid cells within 0.25 times the ratio of local element size and DEM cell size were averaged. The methodology is applied to simulate inundation extent and maximum water levels in southern Mississippi due to Hurricane Katrina, which illustrates that local changes in topography such as adjusting element size and interpolation method drastically alter simulated storm surge locally and non-locally. The methods and results presented have utility and implications to any modeling application that uses bare earth lidar.     

InSAR相位分解及其在生成DEM和研究地震形变场中的应用

InSAR是极具发展潜力的微波遥感新技术,可应用于数字高程模型的产生、制图和大范围微小地表形变的测量。考虑参考面、地形和地表形变等因素,本文从几何角度分析和讨论了In-SAR的相位分解,并给出了各相位分量的函数表达式,阐述了地表高程和形变信息提取的基本原理。最后以JERS和ENVISAT卫星数据为例,展示了合成孔径雷达干涉测量在生成数字高程模型和提取地震形变场中的应用及其数据处理过程。     

TerraSAR-X/TanDEM-X获取高精度数字高程模型技术研究

以双星系统(TerraSAR-X/TanDEM-X)下的bistatic数据模式为例研究了差分干涉获取高精度DEM产品的融合算法和技术流程.针对不同观测几何条件下(升降轨,不同入射角)观测数据的畸变和缺失,提出一种迭代的顾及垂直基线、阴影和叠影的数据融合新方法重建高分辨率高精度的数字高程模型,并对TanDEM-X融合的DEM在不同地物属性特征下(山区及高楼林立的城区)的精度进行定量分析.本文采用了两对覆盖珠海、澳门区域的升降轨TerraSAR-X/TanDEM-X干涉对进行融合处理,并通过收集的高精度Lidar数据进行精度比较分析.此外,本文还定量分析了TanDEM-X的DEM对常规DInSAR技术的改进,并与SRTM、ASTER的结果进行对比.结果表明:提出的升降轨融合方法较单一轨道平台能够较好地改正或减弱由于几何畸变引起的高程信息缺失或错误,通过与Lidar数据的对比发现TanDEM-X的融合DEM在山区的精度较高,其残差的标准差为3.5 m,较单一轨道(升、降轨)分别降低8%和22%,能够通过迭代的方法获取高分辨率(可达2~5m)、高精度的地形信息;而针对城区密集建筑物的复杂地形来说,融合的DEM的精度稍低,残差的标准差为11.8m,但较单一轨道(升、降轨)来说有较大改进,其残差标准差分别降低了28%和22%;而在分布较为稀疏的居民区,融合的DEM能够较Lidar数据获取更好的建筑物高度及外形信息,此时的残差标准差可达5m.同时,TanDEM-X的融合DEM作为外部DEM能够较SRTM和ASTER来说更好地去除地形信息,尤其在山区及高程建筑密集分布的城区,从而利于后续的相位解缠和形变信息的精确获取和解译,为更高精度的时序InSAR形变监测提供有利条件.     

Flow network derivation from a high resolution DEM in a low relief,agrarian landscape

Digital flow networks derived from digital elevation models (DEMs) sensitively react to errors due to measurement, data processing and data representation. Since high‐resolution DEMs are increasingly used in geomorphological and hydrological research, automated and semi‐automated procedures to reduce the impact of such errors on flow networks are required. One such technique is stream‐carving, a hydrological conditioning technique to ensure drainage connectivity in DEMs towards the DEM edges. Here we test and modify a state‐of‐the‐art carving algorithm for flow network derivation in a low‐relief, agricultural landscape characterized by a large number of spurious, topographic depressions. Our results show that the investigated algorithm reconstructs a benchmark network insufficiently in terms of carving energy, distance and a topological network measure. The modification to the algorithm that performed best, combines the least‐cost auxiliary topography (LCAT) carving with a constrained breaching algorithm that explicitly takes automatically identified channel locations into account. We applied our methods to a low relief landscape, but the results can be transferred to flow network derivation of DEMs in moderate to mountainous relief in situations where the valley bottom is broad and flat and precise derivations of the flow networks are needed. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluation of ASTER GDEM and SRTM and their suitability in hydraulic modelling of a glacial lake outburst flood in southeast Tibet

The resolution and accuracy of digital elevation models (DEMs) can affect the hydraulic simulation results for predicting the effects of glacial lake outburst floods (GLOFs). However, for the Tibetan Plateau, high‐quality DEM data are often not available, leaving researchers with near‐global, freely available DEMs, such as the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) and the Shuttle Radar Topography Mission data (SRTM) for hydraulic modelling. This study explores the suitability of these two freely available DEMs for hydraulic modelling of GLOFs. Our study focused on the flood plain of a potentially dangerous glacial lake in southeastern Tibet, to evaluate the elevation accuracy of ASTER GDEM and SRTM, and their suitability for hydraulic modelling of GLOFs. The elevation accuracies of ASTER GDEM and SRTM were first validated against field global position system (GPS) survey points, and then evaluated with reference to the relatively high precision of 1:50 000 scale DEM (DEM5) constructed from aerial photography. Moreover, the DEM5, ASTER GDEM and SRTM were used as basic topographic data to simulate peak discharge propagation, as well as flood inundation extent and depth in the Hydrologic Engineering Center's River Analysis System one‐dimensional hydraulic model. Results of the three DEM predictions were compared to evaluate the suitability of ASTER GDEM and SRTM for GLOF hydraulic modelling. Comparisons of ASTER GDEM and SRTM each with DEM5 in the flood plain area show root‐mean‐square errors between the former two as ± 15·4 m and between the latter two as ± 13·5 m. Although SRTM overestimates and ASTER GDEM underestimates valley floor elevations, both DEMs can be used to extract the elevations of required geometric data, i.e. stream centre lines, bank lines and cross sections, for flood modelling. However, small errors still exist in the cross sections that may influence the propagation of peak discharge. The flood inundation extent and mean water depths derived from ASTER GDEM predictions are only 2·2% larger and 2·3‐m deeper than that of the DEM5 predictions, whereas the SRTM yields a flood zone extent 6·8% larger than the DEM5 prediction and a mean water depth 2·4‐m shallower than the DEM5 prediction. The modelling shows that, in the absence of high‐precision DEM data, ASTER GDEM or SRTM DEM can be relied on for simulating extreme GLOFs in southeast Tibet. Copyright © 2011 John Wiley & Sons, Ltd.     

RESTORATION OF THE ORIGINAL TOPOGRAPHY OF THE XIAONANHAI LANDSLIDE IN CHONGQING AND CALCULATION OF ITS VOLUME

As documented in history, an M6¼ earthquake occurred between Qianjiang, Chongqing and Xianfeng, Hubei(also named the Daluba event)in 1856. This earthquake caused serious geological hazards, including a lot of landslides at Xiaonanhai, Wangdahai, Zhangshangjie and other places. Among them, the Xiaonanhai landslide is a gigantic one, which buried a village and blocked the river, creating a quake lake that has been preserved to this day. As the Xiaonanhai landslide is a historical earthquake-induced landslide, it is impossible to obtain the remote sensing image and DEM data before the earthquake, which brings certain difficulties to the estimation of landslide volume and the establishment of numerical simulation model. In this paper, the original topography before the earthquake is inferred by the methods of geomorphic analogy in adjacent areas and numerical simulation, and the volume of the Xiaonanhai landslide body is calculated. Firstly, the principle and application of UAV aerial photography are introduced. We employed an unmanned airplane to take pictures of the Xiaonanhai landslide and adjacent areas, yielding high-precision DOM images(digital orthophoto graph)and DEM data which permit generating terrain contours with a 25m interval. We also used the method of intensive manual depth measurement in waters to obtain the DEM data of bottom topography of Xiaonanhai quake lake. Based on field investigations, and combining terrain contours and DOM images, we described the sizes and forms of each slump mass in detail. Secondly, considering that the internal and external dynamic geological processes of shaping landforms in the same place are basically the same, the landforms such as ridges and valleys are also basically similar. Therefore, combining with the surrounding topography and landform of the Xiaonanhai area, we used MATLAB software to reconstruct two possible original landform models before the landslide. The original topography presented by model A is a relatively gentle slope, with a slope of 40°~50°, and the original topography presented by model B is a very high and steep slope, with a slope of 70°~80°. Thirdly, Geostudio software is used to conduct numerical simulation analysis on the slope stability. The safety factor of slope stability and the scale of landslide are analyzed under the conditions of static stability, seismic dynamic response and seismic dynamic response considering topographic amplification effect. The results show that large landslide is more likely to occur in model B, which is more consistent with the reality. In order to verify the credibility of recovered DEM data of valley bottom topography, we visited the government of Qianjiang District, collected the drilling data of 11 boreholes in two survey lines of Xiaonanhai weir dam. It is verified that the recovered valley bottom elevation is basically consistent with that revealed by the borehole data. Finally, according to the two kinds of topographic data before and after the landslide, the volume of the landslide is calculated by using the filling and excavation analysis function of ArcGIS software. There is a gap between the calculation results of filling and excavation, the filling data is 3×10⁶m³ larger than the excavation data. The reasons are mainly as follows: 1)Due to the disorderly accumulation of collapse blocks, the porosity of the accumulation body became larger, causing the volume of the fill to expand; 2)It has been more than 150a since the Xiaonanhai earthquake, and the landslide accumulation has been seriously reconstructed, therefore, there are some errors in the filling data; 3)The accumulation body in Xiaonanhai quake lake might be subject to erosion and siltation, this may affect the accuracy of the filling data. In conclusion, it is considered that the calculated results of the excavation are relatively reliable, with a volume of 4.3×10⁷m³.     

Investigating soil moisture sensitivity to precipitation and evapotranspiration errors using SiB2 model and ensemble Kalman filter

Accurate soil moisture information is useful in agricultural practice, weather forecasting, and various hydrological applications. Although land surface modeling provides a viable approach to simulating soil moisture, many factors such as errors in the precipitation can affect the accuracy of soil moisture simulations. This paper examined how precipitation rate and evapotranspiration rate affect the accuracy of soil moisture simulation using simple biosphere model with and without data assimilation through ensemble Kalman filter (EnKF). For each of the two variables, seven levels of relative errors (?20, ?10, ?5, 0, 5, 10 and 20 %) were introduced independently, thus a total of 49 combined cases were investigated. Observations from Wudaogou Hydrology Experimental site in the Huaihe River basin, China, were used to drive and verify the simulations. Results indicate that when the error of precipitation rate is within 10 % of the observations, the resulting error in soil moisture simulations is less significant and manageable, thus the simulated precipitation can be used to drive hydrological models in poorly gauged catchments when observations are not available. When the error of evapotranspiration rate is within 20 % of the observations, which is partly caused by model structural and parameterization errors, its impact on soil moisture simulation is less significant and can be acceptable. This study also demonstrated that the EnKF can perform consistently well to improve soil moisture simulation with less sensitivity to precipitation errors.     

基于无人机摄影测量技术的地震地表破裂带定量参数提取 ——以1709年中卫南M7½地震为例

本文首先介绍了无人机摄影测量技术获取数字高程模型(digital elevation model,缩写为DEM)和地貌数据(正射影像)的作业流程,对比分析了三种不同质量密集点云生成的DEM在水平位置和高程上的差异;然后以1709年中卫南M7?大地震的主体地表破裂带为例,提取其上地震断层的垂直位错量和水平位移量.研究结果...     

The fractal properties of topography as controlled by the interactions of tectonic,lithological, and geomorphological processes

Landscape topography widely exhibits fractal structure. Because of the complexity of relief geometry this structure is not homogeneous in space, and the study of its spatial characteristics represents a powerful method for investigating the interrelationships between landforms and underlying processes. We explore these interrelationships using the digital elevation model (DEM) of an area located in central Italy, where landscape topography is strongly linked to its geological evolution, being characterized by alternating intermountain basins and mountain ranges trending NW–SE. A modified version of the method based on the standard deviation of relief elevations is used to evaluate the fractal parameters of relief after tiling the DEM in spatial units characterized by homogeneous fractal geometry, and statistical methods in conjunction with spatial analysis techniques are applied to the resulting terrain datasets. Both the lowest and (to a lesser extent) the highest values of fractal dimension are found to follow the ridge‐and‐valley trend. Low fractal dimension is observed in the mountain ranges characterized by massive strata of limestone, and along the fault scarps defining the contact between the intermountain basins and the surrounding slopes, where sediment deposition prevails. High fractal dimension is observed in regions characterized by highly erodible terrigenous lithology, and in areas where tectonic activity favors erosional processes mainly by rivers. The analysis of the (fractal) power law parameters also suggests that each major lithological complex has its own characteristic fractal signature. These results provide new insights into the link between the fractal properties of topography and the tectonic, lithological, and geomorphological features of the area, and show that the analysis approach proposed is useful to depict key aspects about the geomorphological and geological setting of an area, using only a DEM. Copyright © 2017 John Wiley & Sons, Ltd.     

How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks

The quality of digital elevation model (DEM)‐derived river drainage networks (RDNs) is influenced by DEM quality, basin physical characteristics, scale, and algorithms used; these factors should not be neglected. However, few research studies analyse the different evaluation approaches used in the literature with respect to adequacy, meaning of the results, advantages, and limitations. Focusing on coarse‐resolution networks, this paper reviews the use of these techniques and offers new insights on these issues. Additionally, we propose adaptations for selected metrics and discuss distinct interpretations for the evaluation of RDNs derived at different spatial resolutions (1, 5, 10, 20, and 30 km) considering the Uruguay River basin (206,000 km²) as a case study. The results demonstrate that lumped basin/river characteristics and basin delineation analysis should not be used as evaluation criteria for RDN quality; however, some of these metrics offer useful complementary information. Percentage of the DEM‐derived RDN within a uniform buffer placed around a river network considered as reference and mean separation distance between these two networks are more suitable metrics, but the former is insensitive to serious errors. The change in reference from a fine‐scale network to a coarse‐resolution manual tracing network significantly augments the discrepancy of these largest errors when the mean distance metric was applied, and visual comparison analysis is necessary to interpret the results for other metrics. We recommend the use of the mean distance metric in combination with a detailed visual assessment, the importance of which increases as the resolution coarsens. In both cases, the impact of network quality can be further refined by quantifying the basin shape and river length errors.     

基于非结构网格的电阻率三维带地形反演

地表起伏地形在野外矿产资源勘察中不可避免,其对直流电阻率法勘探影响巨大.近年来,电阻率三维正演取得诸多进展,特别是应用非结构网格我们能够进行任意复杂地形和几何模型的电阻率三维数值模拟,但面向实际应用的起伏地形下电阻率三维反演依然困难.本文基于非结构化四面体网格,并考虑到应用GPS/GNSS时,区域地球物理调查中可非规则布设测网的实际特点,实现了任意地形(平坦或起伏)条件下、任意布设的偶极-偶极视电阻率数据的不完全Gauss-Newton三维反演.合成数据的反演结果表明了方法的有效性,可应用于复杂野外环境下的三维电法勘探.