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.

Fractal Measures of Drainage Network to Investigate Surface Deformation from Remote Sensing Data: A Paradigm from Hindukush (NE-Afghanistan)

This approach represents the relative susceptibility of the topography of the earth to active deformation by means of geometrical distinctiveness of the river networks. This investigation employs the fractal analysis of drainage system extracted from ASTER Global Digital Elevation Model (GDEM-30m resolution). The objective is to mark active structures and to pinpoint the areas robustly influenced by neotectonics. This approach was examined in the Hindukush, NE-Afghanistan. This region is frequently affected by deadly earthquakes and the modern fault activities and deformation are driven by the collision between the northward-moving Indian subcontinent and Eurasia. This attempt is based on the fact that drainage system is strained to linearize due to neotectonic deformation. Hence, the low fractal dimensions of the Kabul, Panjsher, Laghman, Andarab, Alingar and Kocha Rivers are credited to active tectonics. A comprehensive textural examination is conducted to probe the linearization, heterogeneity and connectivity of the drainage patterns. The aspects for these natural textures are computed by using the fractal dimension (FD), lacunarity (LA) and succolarity (SA) approach. All these methods are naturally interrelated, i.e. objects with similar FD can be further differentiated with LA and/or SA analysis. The maps of FD, LA and SA values are generated by using a sliding window of 50 arc seconds by 50 arc seconds (50" × 50"). Afterwards, the maps are interpreted in terms of regional susceptibility to neotectonics. This method is useful to pinpoint numerous zones where the drainage system is highly controlled by Hindukush active structures. In the North-Northeast of the Kabul block, we recognized active tectonic blocks. The region comprising, Kabul, Panjsher, Andrab, Alingar and Badakhshan is more susceptible to damaging events. This investigation concludes that the fractal analysis of the river networks is a bonus tool to localize areas vulnerable to deadly incidents influencing the Earth’s topography and consequently intimidate human lives.

Drainage Network and Lineament Analysis:An Approach for Potwar Plateau(Northern Pakistan)

Drainage responds rapidly to tectonic changes and thus it is a potential parameter for teetonogeomorphological analysis. Drainage network of Potwar is a good geological record of movement, displacements, regional uplifts and erosion of the tectonic units. This study focuses on utilizing drainage network extracted from Shuttle Radar Digital Elevation Data （SRTM-DEM） in order to constrain the structure of the Potwar Plateau. SWAN syncline divides Potwar into northern Potwar deformed zone （NPDZ） and southern Potwar platform zone （SPPZ）. We extracted the drainage network from DEM and analyzed 112 streams using stream power law. Spatial distribution of concavity and steepness indices were used to prepare uplift rate map for the area. DEM was further utilized to extract lineaments to study the mutual relationship between lineaments and drainage patterns. We compared the local correlation between the extracted lineaments and drainage network of the area that gives us quantitative information and shows promising prospects. The streams in the NPDZ indicate high steepness values as compared to the streams in the SPPZ. The spatial distribution of geomorphic parameters distinctive deformation and uplift rates suggest the among eastern, central and western parts. The local correlation between drainage network and lineaments from DEM is strongly positive in the area within I km of radius.

Application of digital elevation model in delineating drainage networks

A practical method to extract drainage network from DEM (digital elevation model) is introduced. DEM pretreatment includes depression and flat areas treatment. The flow direction of each grid cell in DEM is calculated according to the 8-direction pour point model, and then the flow accumulation grid from the flow direction grid. With the flow accumulation grid, streams are defined according to the given threshold value of flow accumulation. Taking Gufo River watershed as an example, the extraction of drainage network was done from DEM. The results are basically consistent with the digitized drainage network from the relief maps.

Urban Drainage Network Scheduling Strategy Based on Dynamic Regulation: Optimization Model and Theoretical Research

With the acceleration of urbanization in China,the discharge of domestic sewage and industrial wastewater is increasing,and accidents of sewage spilling out and polluting the environment occur from time to time.Problems such as imperfect facilities and backward control methods are com-mon in the urban drainage network systems in China.Efficient drainage not only strengthens infrastructure such as rain and sewage diversion,pollution source monitoring,transportation,drainage and storage but also urgently needs technical means to monitor and optimize production and operation.Aiming at the optimal control of single-stage pumping stations and the coordinated control between two-stage pumping stations,this paper studies the modelling and optimal control of drainage network systems.Based on the Long Short Term Memory(LSTM)water level prediction model of the sewage pumping stations,and then based on the mechanism analysis of drainage pipe network,the factors that may cause the water level change of pumping station are obtained.Grey correlation analysis is carried out on these influencing factors,and the prediction model is established by taking the factors with a high correlation degree as input.The research results show that compared with the traditional prediction model,the LSTM model not only has higher prediction accuracy but also has better inflection point tracking ability.

A RIVER FLOW ROUTING MODEL BASED ON DIGITAL DRAINAGE NETWORK

On the basis of Digital Elevation Model （DEM） data, watershed delineation and spatial topological relationship were proposed by the Digital Elevation Drainage Network Model （DEDNM） for the area upstream of the Hanzhong Hydrological Station in the Hanjiang River in China. Then, the Muskingum-Cunge method considering lateral flow into the river was applied to flood routing on the platform of digital basin derived from DEDNM. Because of considering lateral flow into the river, the Muskingum-Cunge method performs better than the Muskingum method in terms of the Nash-Sutcliffe model efficiency coefficient and the relative error of flood discharge peak value. With a routing-after-superposition algorithm, the Muskingum-Cunge method performs better than the Muskingum method in terms of the Nash-Sutcliffe model efficiency coefficient and the relative error of flood discharge peak value. As a result, the digital basin coupled with the Muskingum-Cunge method provides a better platform for water resources management and flood control.

A New Algorithm to Automatically Extract the Drainage Networks and Catchments Based on Triangulation Irregular Network Digital Elevation Model

A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined by computing the spatial gradient of triangle and triangle edges. Outflow edge was defined by comparing the contribution area that is separated by the steepest descent of the triangle. Local channels were then tracked to build drainage networks. Both triangle edges and facets were considered to construct flow path. The algorithm has been tested in the site for Hawaiian Island of Kaho'olawe, and the results were compared with those calculated by ARCGIS as well as terrain map. The reported algorithm has been proved to be a reliable approach with high efficiency to generate well-connected and coherent drainage networks.

A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation

Similarity measurement has been a prevailing research topic geographic information science.Geometric similarity measurement inin scaling transformation(GSM_ST)is critical to ensure spatial data quality while balancing detailed information with distinctive features.However,GSM_ST is an uncertain problem due to subjective spatial cognition,global and local concerns,and geometric complexity.Traditional rule-based methods considering multiple consistent conditions require subjective adjustments to characteristics and weights,leading to poor robustness in addressing GSM_ST.This study proposes an unsupervised representation learning framework for automated GSM_ST,using a Graph Autoencoder Network(GAE)and drainage networks as an example.The framework involves constructing a drainage graph,designing the GAE architecture for GSM_ST,and using Cosine similarity to measure similarity based on the GAE-derived drainage embeddings in different scales.We perform extensive experiments and compare methods across 71 drainage networks duringfive scaling transformations.The results show that the proposed GAE method outperforms other methods with a satisfaction ratio of around 88%and has strong robustness.Moreover,our proposed method also can be applied to other scenarios,such as measuring similarity between geographical entities at different times and data from different datasets.

RS-SVM Machine Learning Approach Driven by Case Data for Selecting Urban Drainage Network Restoration Scheme

Urban drainage pipe network is the backbone of urban drainage,flood control and water pollution prevention,and is also an essential symbol to measure the level of urban modernization.A large number of underground drainage pipe networks in aged urban areas have been laid for a long time and have reached or practically reached the service age.The repair of drainage pipe networks has attracted extensive attention from all walks of life.Since the Ministry of ecological environment and the national development and Reform Commission jointly issued the action plan for the Yangtze River Protection and restoration in 2019,various provinces in the Yangtze River Basin,such as Anhui,Jiangxi and Hunan,have extensively carried out PPp projects for urban pipeline restoration,in order to improve the quality and efficiency of sewage treatment.Based on the management practice of urban pipe network restoration project in Wuhu City,Anhui Province,this paper analyzes the problems of lengthy construction period and repeated operation caused by the mismatch between the design schedule of the restoration scheme and the construction schedule of the pipe network restoration in the existing project management mode,and proposes a model of urban drainage pipe network restoration scheme selection based on the improved support vector machine.The validity and feasibility of the model are analyzed and verified by collecting the data in the project practice.The research results show that the model has a favorable effect on the selection of urban drainage pipeline restoration schemes,and its accuracy can reach 90%.The research results can provide method guidance and technical support for the rapid decision-making of urban drainage pipeline restoration projects.

Effectiveness of urban distributed runoff model for discharge and water depth calculation in urban drainage pipe networks

Effective urban land-use re-planning and the strategic arrangement of drainage pipe networks can significantly enhance urban flood defense capacity.Aimed at reducing the potential risks of urban flooding,this paper presents a straightforward and efficient approach to an urban distributed runoff model(UDRM).The model is developed to quantify the discharge and water depth within urban drainage pipe networks under varying rainfall intensities and land-use scenarios.The Nash efficiency coefficient of UDRM exceeds 0.9,which indicates its high computational efficiency and potential benefit in predicting urban flooding.The prediction of drainage conditions under both current and re-planned land-use types is achieved by adopting different flood recurrence intervals.The findings reveal that the re-planned land-use strategies could effectively diminish flood risk upstream of the drainage pipe network across 20-year and 50-year flood recurrence intervals.However,in the case of extreme rainfall events(a 100-year flood recurrence),the re-planned land-use approach fell short of fulfilling the requirements necessary for flood disaster mitigation.In these instances,the adoption of larger-diameter drainage pipes becomes an essential requisite to satisfy drainage needs.Accordingly,the proposed UDRM effectively combines land-use information with pipeline data to give practical suggestions for pipeline modification and land-use optimization to combat urban floods.Therefore,this methodology warrants further promotion in the field of urban re-planning.

Geomorphic indices and relative tectonic uplift in the Guerrero sector of the Mexican forearc

Tectonically active areas,such as forearc regions,commonly show contrasting relief,differential tectonic uplift,variations in erosion rates,in river incision,and in channel gradient produced by ongoing tectonic deformation.Thus,information on the tectonic activity of a defined area could be derived via landscape analysis.This study uses topography and geomorphic indices to extract signals of ongoing tectonic deformation along the Mexican subduction forearc within the Guerrero sector.For this purpose,we use field data,topographical data,knickpoints,the ratio of volume to area（Rva）.the stream-length gradient index（St）,and the normalized channel steepness index（k_（sn））.The results of the applied landscape analysis reveal considerable variations in relief,topography and geomorphic indices values along the Guerrero sector of the Mexican subduction zone.We argue that the reported differences are indicative of tectonic deformation and of variations in relative tectonic uplift along the studied forearc.A significant drop from central and eastern parts of the study area towards the west in values of R_（VA）（from ~500 to^300）,St（from ~500 to ca.400）,maximum St（from ~1500-2500 to ~ 1000） and k_（sn）（from ~150 to ~100） denotes a decrease in relative tectonic uplift in the same direction.We suggest that applied geomorphic indices values and forearc topography are independent of climate and lithology.Actual mechanisms responsible for the observed variations and inferred changes in relative forearc tectonic uplift call for further studies that explain the physical processes that control the forearc along strike uplift variations and that determine the rates of uplift.The proposed methodology and results obtained through this study could prove useful to scientists who study the geomorphology of forearc regions and active subduction zones.

Study on Planning an Ecological Stormwater Regulation System Based on Low Impact Development Mode： A Case Study in China

This paper sets Chaihu Town, Zhongxiang City of Hubei Province as an example, analyzing the ecological and hydrological conditions of Chaihu Town, applying LID （low impact development） mode and putting forward the ecological stormwater regulation system planning strategy which adapts to the development of small towns. The main conclusions are as follows： （1） The ＂three-low＂ development mode is put forward, which means low impact, low cost and low carbon, using this construction mode to minimize the ecological impact, relying on natural green space and water to achieve the function of rainstorm regulation; （2） Through the analysis and calculation of the local amount of precipitation, this paper scientifically calculates the required area of storage water and green space, taking the roads as trunks, green spaces as stems, water as veins, and building the green infrastructure system; （3） The author has been repairing and integrating the original drainage ditches of the planning area, replacing traditional rain drainage pipes, establishing ＂two-loop＂ water network system which aims at the detention and purification of rainwater, maximizing ecological benefit, economic benefit and landscape benefit.

Drainage evolution in intermontane basins at the Qinling-Daba Mountains

River capture is of great significance to landform evolution and hominine migration.In the Qinling-Daba Mountains,there is a viewpoint that Jialing River captured Hanjiang River,but this is still controversial.In this paper,we discuss the drainage evolution processes in intermountain basins at the Qinling-Daba Mountains based on a combination of detrital zircon UPb geochronology and geomorphic indexes.We suggest that the Hanjiang River gradually captured the Jialing River from east to west,accompanied by the evolution of the ancient Yangtze River.In terms of geomorphic evidences,wide valleys did not match with discharge,and a series of wind gaps developed in the Shiquan-Ankang basin.In addition,the valley shapes and width-toheight ratios(Vf)indicate two possible rapid incisions.The hypsometric integrals(HI)reflect that the landform gradually changes from the old stage to the youth stage from west to east.Theχvalues show that the drainage divide is moving to the side of the Yuehe River,and the Yuehe River is gradually shrinking.According to the sedimentary records,the zircon U-Pb age distributions indicate the provenance change.The high-altitude terraces show three age peaks(200–250,400–505,and 700–900 Ma),with the dominant Indosinian age peak(200–250 Ma),while the modern fluvial sediments only show a single peak of Jinning(700–900 Ma).These data show that there are two major river captures:(1)The ancient Hanjiang River cut through the regional compression ridge,and then captured the Hanzhong Basin river system(a part of the ancient Jialing river system)from east to west,and(2)The southern tributary captured the trunk with the uplift of the divide in the Shiquan-Ankang Basin,forming the modern drainage pattern in the upper Hanjiang River.The activities of the regional strike-slip fault,and the associated compression uplift played a key role in the river captures,the drainage evolution,and related landforms in the Shiquan-Ankang basin.In addition,it is shown that the evolution of the upper tributary basins lagged behind the response of the trunk channel to the tectonic activities and river captures.The interconnected wide valleys caused by river capture may have provided convenient geomorphological conditions for human migration into the Qinling-Daba Mountains along those river valleys.

Efficient Priority-Flood depression filling in raster digital elevation models

Depressions in raster digital elevation models(DEM)present a challenge for extracting hydrological networks.They are commonly filled before subsequent algorithms are further applied.Among existing algorithms for filling depressions,the Priority-Flood algorithm runs the fastest.In this study,we propose an improved variant over the fastest existing sequential variant of the Priority-Flood algorithm for filling depressions in floating-point DEMs.The proposed variant introduces a series of improvements and greatly reduces the number of cells that need to be processed by the priority queue(PQ),the key data structure used in the algorithm.The proposed variant is evaluated based on statistics from 30 experiments.On average,our proposed variant reduces the number of cells processed by the PQ by around 70%.The speed-up ratios of our proposed variant over the existing fastest variant of the Priority-Flood algorithm range from 31%to 52%,with an average of 45%.The proposed variant can be used to fill depressions in large DEMs in much less time and in the parallel implementation of the Priority-Flood algorithm to further reduce the running time for processing huge DEMs that cannot be dealt with easily on single computers.