Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)techniques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model’s result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.

Estimation and mapping of water erosion and soil loss:Application of Gavrilovic erosion potential model(EPM)using GIS and remote sensing in the Assif el mal Watershed,Western high Atlas

Water erosion is a serious problem that leads to soil degradation,loss,and the destruction of structures.Assessing the risk of erosion and determining the affected areas has become crucial in order to understand the main factors influencing its evolution and to minimize its impacts.This study focuses on evaluating the risk of erosion in the Assif el mal watershed,which is located in the High Atlas Mountains.The Erosion Potential Model(EPM)is used to estimate soil losses depending on various parameters such as lithology,hydrology,topography,and morphometry.Geographic information systems and remote sensing techniques are employed to map areas with high erosive potential and their relationship with the distribution of factors involved.Different digital elevation models are also used in this study to highlight the impact of data quality on the accuracy of the results.The findings reveal that approximately 59%of the total area in the Assif el mal basin has low to very low potential for soil losses,while 22%is moderately affected and 19.9%is at high to very high risk.It is therefore crucial to implement soil conservation measures to mitigate and prevent erosion risks.

Imaging simulation and analysis of attitude jitter effect on topographic mapping for lunar orbiter stereo optical cameras

The geometric accuracy of topographic mapping with high-resolution remote sensing images is inevita-bly affected by the orbiter attitude jitter.Therefore,it is necessary to conduct preliminary research on the stereo mapping camera equipped on lunar orbiter before launching.In this work,an imaging simulation method consid-ering the attitude jitter is presented.The impact analysis of different attitude jitter on terrain undulation is conduct-ed by simulating jitter at three attitude angles,respectively.The proposed simulation method is based on the rigor-ous sensor model,using the lunar digital elevation model(DEM)and orthoimage as reference data.The orbit and attitude of the lunar stereo mapping camera are simulated while considering the attitude jitter.Two-dimensional simulated stereo images are generated according to the position and attitude of the orbiter in a given orbit.Experi-mental analyses were conducted by the DEM with the simulated stereo image.The simulation imaging results demonstrate that the proposed method can ensure imaging efficiency without losing the accuracy of topographic mapping.The effect of attitude jitter on the stereo mapping accuracy of the simulated images was analyzed through a DEM comparison.

Performance validation of High Mountain Asia 8-meter Digital Elevation Model using ICESat-2 geolocated photons

High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of Asia.The science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m DEM.In this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land covers.Inferences were made from statistical quantifiers and elevation profiles.For the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test sites.The second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,respectively.The third test site,situated in the Zanda County of the Qinghai-Tibet,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible bias.Additionally,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological parameters.The results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.

The variation in basal channels and basal melt rates of Pine Island Ice Shelf

In recent years,there has been a significant acceleration in the thinning,calving and retreat of the Pine Island Ice Shelf(PIIS).The basal channels,results of enhanced basal melting,have the potential to significantly impact the stability of the PIIS.In this study,we used a variety of remote sensing data,including Landsat,REMA DEM,ICESat-1 and ICESat-2 satellite altimetry observations,and Ice Bridge airborne measurements,to study the spatiotemporal changes in the basal channels from 2003 to 2020 and basal melt rate from 2010 to 2017 of the PIIS under the Eulerian framework.We found that the basal channels are highly developed in the PIIS,with a total length exceeding 450 km.Most of the basal channels are ocean-sourced or groundingline-sourced basal channels,caused by the rapid melting under the ice shelf or near the groundingline.A raised seabed prevented warm water intrusion into the eastern branch of the PIIS,resulting in a lower basal melt rate in that area.In contrast,a deepsea trough facilitates warm seawater into the mainstream and the western branch of the PIIS,resulting in a higher basal melt rate in the main-stream,and the surface elevation changes above the basal channels of the mainstream and western branch are more significant.The El Ni?o event in 2015–2016 possibly slowed down the basal melting of the PIIS by modulating wind field,surface sea temperature and depth seawater temperature.Ocean and atmospheric changes were driven by El Ni?o,which can further explain and confirm the changes in the basal melting of the PIIS.

Modified method for extraction of watershed boundary with digital elevation modeling

Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.

Using GIS Spatial Distribution to Predict Soil Organic Carbon in Subtropical China

Spatial distribution of organic carbon in soils is difficult to estimatebecause of inherent spatial variability and insufficient data. A soil-landscape model for a region,based on 151 samples for parent material and topographic factors, was established using a GISspatial analysis technique and a digital elevation model (DEM) to reveal spatial distributioncharacteristics of soil organic carbon (SOC). Correlations between organic carbon and topographicfactors were analyzed and a regression model was established to predict SOC content. Results forsurface soils (0-20 cm) showed that the average SOC content was 12.8 g kg^(-1), with the SOC contentbetween 6 and 12 g kg^(-1) occupying the largest area and SOC over 24 g kg^(-1) the smallest. Also,soils derived from phyllite were the highest in the SOC content and area, while soils developed onpurple shale the lowest. Although parent material, elevation, and slope exposure were allsignificant topographic variables (P < 0.01), slope exposure had the highest correlation to SOCcontent (r = 0.66). Using a multiple regression model (R^2 = 0.611) and DEM (with a 30 m X 30 mgrid), spatial distribution of SOC could be forecasted.

Extraction and Analysis of Gully Head of Loess Plateau in China Based on Digital Elevation Model

In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.

Hydrological daily rainfall-runoff simulation with BTOPMC model and comparison with Xin'anjiang model

A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.

Determining Topographic Shielding from Digital Elevation Models for Cosmogenic Nuclide Analysis:a GIS Approach and Field Validation

Topographic shielding of cosmic radiation flux is a key parameter in using cosmogenic nuclides to determine surface exposure ages or erosion rates. Traditionally, this parameter is measured in the field and uncertainty and/or inconsistency may exist among different investigators. This paper provides an ArcGIS python code to determine topographic shielding factors using digital elevation models （DEMs）. This code can be imported into ArcGIS as a geoprocessing tool with a user-friendly graphical interface. The DEM-derived parameters using this method were validated with field measurements in central Tian Shan. Results indicate that DEM-derived shielding factors are consistent with field-measured values. It provides a valuable tool to save fieldwork efforts and has the potential to provide consistent results for different regions in the world to facilitate the comparison of cosmogenie nuclide results.

Prediction of Soil Depth from Digital Terrain Data by Integrating Statistical and Visual Approaches

Information about the spatial distribution of soil attributes is indispensable for many land resource management applications; however, the ability of soil maps to supply such information for modern modeling tools is questionable. The objectives of this study were to investigate the possibility of predicting soil depth using some terrain attributes derived from digital elevation models （DEMs） with geographic information systems （GIS） and to suggest an approach to predict other soil attributes. Soil depth was determined at 652 field observations over the A1-Muwaqqar Watershed （70 km2） in Jordan. Terrain attributes derived from 30-m resolution DEMs were utilized to predict soil depth. The results indicated that the use of multiple linear regression models within small watershed subdivisions enabled the prediction of soil depth with a difference of 50 cm for 77% of the field observations. The spatial distribution of the predicted soil depth was visually coincided and had good correlations with the spatial distribution of the classes amalgamating three terrain attributes, slope steepness, slope shape, and compound topographic index. These suggested that the modeling of soil-landscape relationships within small watershed subdivisions using the three terrain attributes was a promising approach to predict other soil attributes.

Application of Radar-Measured Rain Data in Hydrological Processes Modeling during the Intensified Observation Period of HUBEX

On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km2 of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.

Calculation of watershed flow concentration based on the grid drop concept

The grid drop concept is introduced and used to develop a micromechanism-based methodology for calculating watershed flow concentration. The flow path and distance traveled by a grid drop to the outlet of the watershed are obtained using a digital elevation model （DEM）. Regarding the slope as an uneven carpet through which the grid drop passes, a formula for overland flow velocity differing from Manning＇s formula for stream flow as welt as Darcy＇s formula for pore flow is proposed. Compared with the commonly used unit hydrograph and isochronal methods, this new methodology has outstanding advantages in that it considers the influences of the slope velocity field and the heterogeneity of spatial distribution of rainfall on the flow concentration process, and includes only one parameter that needs to be calibrated. This method can also be effectively applied to the prediction of hydrologic processes in un-gauged basins.

Machine learning and geostatistical approaches for estimating aboveground biomass in Chinese subtropical forests

Background:Aboveground biomass(AGB)is a fundamental indicator of forest ecosystem productivity and health and hence plays an essential role in evaluating forest carbon reserves and supporting the development of targeted forest management plans.Methods:Here,we proposed a random forest/co-kriging framework that integrates the strengths of machine learning and geostatistical approaches to improve the mapping accuracies of AGB in northern Guangdong Province of China.We used Landsat time-series observations,Advanced Land Observing Satellite(ALOS)Phased Array L-band Synthetic Aperture Radar(PALSAR)data,and National Forest Inventory(NFI)plot measurements,to generate the forest AGB maps at three time points(1992,2002 and 2010)showing the spatio-temporal dynamics of AGB in the subtropical forests in Guangdong,China.Results:The proposed model was capable of mapping forest AGB using spectral,textural,topographical variables and the radar backscatter coefficients in an effective and reliable manner.The root mean square error of the plotlevel AGB validation was between 15.62 and 53.78 t∙ha^(−1),the mean absolute error ranged from 6.54 to 32.32 t∙ha^(−1),the bias ranged from−2.14 to 1.07 t∙ha^(−1),and the relative improvement over the random forest algorithm was between 3.8%and 17.7%.The largest coefficient of determination(0.81)and the smallest mean absolute error(6.54 t∙ha^(−1)were observed in the 1992 AGB map.The spectral saturation effect was minimized by adding the PALSAR data to the modeling variable set in 2010.By adding elevation as a covariable,the co-kriging outperformed the ordinary kriging method for the prediction of the AGB residuals,because co-kriging resulted in better interpolation results in the valleys and plains of the study area.Conclusions:Validation of the three AGB maps with an independent dataset indicated that the random forest/cokriging performed best for AGB prediction,followed by random forest coupled with ordinary kriging(random forest/ordinary kriging),and the random forest model.The proposed random forest/co-kriging framework provides an accurate and reliable method for AGB mapping in subtropical forest regions with complex topography.The resulting AGB maps are suitable for the targeted development of forest management actions to promote carbon sequestration and sustainable forest management in the context of climate change.

Characteristics and influencing factors of proximity distance index on the northern Shaanxi Loess Plateau in China

Topographic feature points and lines are the framework of topography,and their spatial distance relationship is an breakthrough in the study of topographical geometry,internal structure and development level.Proximity distance(PD)is an indicator to describe the distance between the gully source point(GSP)and the watershed boundary.In the upstream catchment area,PDs can be expressed by the streamline proximity distance(SPD),as well as by the horizontal proximity distance(HPD)and the vertical proximity distance(VPD)in the horizontal and vertical dimensions,respectively.The series of indicators(e.g.,SPD,HPD and VPD)are important for quantifying the geomorphological development process of a loess basin because of the headward erosion of loess gullies.In this study,the digital elevation model data with 5 m resolution and a digital topographic analysis method are used for the statistical analyses of the SPD,VPD and HPD in 50 sample areas of 6 geomorphic types in the Loess Plateau of northern Shaanxi.The spatial characteristics and the influencing factors are also analysed.Results show that:1)Central tendencies for the HPDs and the VPDs for the whole study area and the six typical loess landforms are evident.2)Spatial patterns of the HPDs and the VPDs exhibit evident trends and zonal distributions over the whole study area.3)The HPDs have a strong positive correlation with gully density(GD)and hypsometric integral.The VPDs also correlates with GD to an extent.Vegetation cover,mean annual precipitation and loess thickness have stronger effects on the VPD than on the HPD.

Simulation of astronomical solar radiation over Yellow River Basin based on DEM

Based on the developed distributed model for calculating astronomical solar radiation (ASR), monthly ASR with a resolution of 1 km×1 km for the rugged terrains of Yellow River Basin was calculated, with DEM data as the general characterization of terrain. This model gives an all-sided consideration on factors that influence the ASR. Results suggest that (1) Annual ASR has a progressive decrease trend from south to north; (2) the magnitude order of seasonal ASR is: summer>spring>autumn>winter; (3) topographical factors have robust effect on the spatial distribution of ASR, particularly in winter when a lower sun elevation angle exists; (4) the ASR of slopes with a sunny exposure is generally 2 or 3 times that of slopes with a shading exposure and the extreme difference of ASR for different terrains is over 10 times in January; (5) the spatial differences of ASR are relatively small in summer when a higher sun elevation angle exists and the extreme difference of ASR for different terrains is only 16% in July; and (6) the sequence of topographical influence strength is: winter>autumn>spring>summer.

Analysis of Runoff in Ungauged Mountain Watersheds in Sichuan,China using Kinematic-wave-based GIUH Model

Floods are one of the most common natural hazards occurring all around the world.However,the knowledge of the origins of a food and its possible magnitude in a given region remains unclear yet.This lack of understanding is particularly acute in mountainous regions with large degrees in Sichuan Province,China,where runoff is seldom measured.The nature of streamflow in a region is related to the time and spatial distribution of rainfall quantity and watershed geomorphology.The geomorphologic characteristics are the channel network and surrounding landscape which transform the rainfall input into an output hydrograph at the outlet of the watershed.With the given geomorphologic properties of the watershed,theoretically the hydrological response function can be determined hydraulically without using any recorded data of past rainfall or runoff events.In this study,a kinematic-wave-based geomorphologic instantaneous unit hydrograph (KW-GIUH) model was adopted and verified to estimate runoff in ungauged areas.Two mountain watersheds,the Yingjing River watershed and Tianquan River watershed in Sichuan were selected as study sites.The geomorphologic factors of the two watersheds were obtained by using a digital elevation model (DEM) based on the topographic database obtained from the Shuttle Radar Topography Mission of US's NASA.The tests of the model on the two watersheds were performed both at gauged and ungauged sites.Comparison between the simulated and observed hydrographs for a number of rainstorms at the gauged sites indicated the potential of the KW-GIUH model as a useful tool for runoff analysis in these regions.Moreover,to simulate possible concentrated rainstorms that could result in serious flooding in these areas,synthetic rainfall hyetographs were adopted as input to the KW-GIUH model to obtain the flow hydrographs at two ungauged sites for different return period conditions.Hydroeconomic analysis can be performed in the future to select the optimum design return period for determining the flood control work.

Effect of digital elevation models on monitoring slope displacements in open-pit mine by differential interferometry synthetic aperture radar

Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the potential to be a cost-effective method for monitoring surface displacements over extensive areas,such as open-pit mines.DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model(DEM).However,since the topography of the ground surface in open-pit mines changes largely due to excavations,measurement errors can occur due to insufficient information on the elevation of mining areas.In this paper,effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry.In addition,validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system(GPS)monitoring conducted for three years at the same limestone quarry.It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters.Comparing the monitoring results of DInSAR and GPS,the root mean square error(RMSE)of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM,considering the excavation processes,is used.It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.

Deriving the slope-mean shielded astronomical solar radiation spectrum and slope-mean possible sunshine duration spectrum over the Loess Plateau

Solar radiation is often shielded by terrain relief, especially in mountainous areas, before reaching the surface of the Earth. The objective of this paper is to study the spatial structures of the shielded astronomical solar radiation(SASR) and the possible sunshine duration(PSD) over the Loess Plateau. To this end, we chose six test areas representing different landforms over the Loess Plateau and the software package of Matlab was used as the main computing platform. In each test area, 5-m-resolution digital elevation model established from 1:10,000 scale topographic maps was used to compute the corresponding slope, SASR and PSD. Then, we defined the concepts of the slope-mean SASR spectrum and the slope-mean PSD spectrum, and proposed a method to extract them from the computed slope, SASR and PSD over rectangular analysis windows. Using this method, we found both spectrums in a year or in a season for each of the four seasons in the six test areas. Each spectrum was found only when the area of the corresponding rectangular analysis window was greater than the corresponding stable area of the spectrum. The values of the two spectrums decreased when the slope increased.Furthermore, the values of the stable areas of the spectrums in a year or in a season were positively correlated with the variable coefficients of the slope or the profile curvature. The values of the stable areas of the two spectrums in a year or in a season may represent the minimum value of test areas for corresponding future research on the spatial structures of the SASR or PSD. All the findings herein suggest that the spatial structures of the PSD and the SASR are caused by the interactions between solar radiation and terrain relief and that the method for extracting either spectrum is effective for detecting their spatial structures. This study may deepen our understanding of the spatial structure of solar radiation and help us further explore the distribution of solar energy in mountainous regions.

A New Treatment of Depression for Drainage Network Extraction Based on DEM

Depressions in landscapes function as buffers for water and sediment. A landscape with depressions has less runoff, less erosion and more sedimentation than that without depressions. Sinks in digital elevation models （DEMs） can be considered the real features that represent depressions in actual landscapes or spurious features that result from errors in DEM creation. In many hydrological and erosion models, all sinks are considered as spurious features and, as a result, these models do not deal with the sinks that represent real depressions. Consequently, the surface runoff and erosion are overestimated due to removing the depressions. Aiming at this problem, this paper presents a new method, which deal with the sinks that represent real depressions. The drainage network is extracted without changing the original DEM. The method includes four steps： detecting pits, detecting depressions, merging depressions, and extracting drainage network. Because the elevations of grid cells are not changed, the method can also avoid producing new fiat areas, which are always produced by the conventional filling methods. The proposed method was applied to the Xihanshui River basin, the upper reach of the Jialingjiang River basin, China, to automatically extract the drainage network based on DEM. The extracted drainage network agrees well with the reality and can be used for further hydrologic analysis and erosion estimation.