Simulating the effects of spatial configurations of agricultural ditch drainage networks on surface runoff from agricultural catchments

The study of runoff is a crucial issue because it is closely related to flooding, water quality and erosion. In cultivated catchments, agricultural ditch drainage networks are known to influence runoff. As anthropogenic elements, agricultural ditch drainage networks can therefore be altered to better manage surface runoff in cultivated catchments. However, the relationship between the spatial configuration, i.e., the density and the topology, of agricultural ditch drainage networks and surface runoff in cultivated catchments is not understood. We studied this relationship by using a random network simulator that was coupled to a distributed hydrological model. The simulations explored a large variety of spatial configurations corresponding to a thousand stochastic agricultural ditch drainage networks on a 6.4 km2 Mediterranean cultivated catchment. Next, several distributed hydrological functions were used to compute water flow-paths and runoff for each simulation. The results showed that (i) denser networks increased the drained volume and the peak discharge and decreased hillslopes runoff, (ii) greater network density did not affect the surface runoff any further above a given network density, (iii) the correlation between network density and runoff was weaker for small subcatchments (< 2 km2) where the variability in the drained area that resulted from changes in agricultural ditch drainage networks increased the variability of runoff and (iv) the actual agricultural ditch drainage network appeared to be well optimized for managing runoff as compared with the simulated networks. Finally, our results highlighted the role of agricultural ditch drainage networks in intercepting and decreasing overland flow on hillslopes and increasing runoff in drainage networks

The accuracy of drainage network delineation as a function of environmental factors: A case study in Central and Northern Sweden

Drainage networks delineated from Digital Elevation Models (DEMs), are the basis for the modelling of geomorphological and hydrological processes, biogeochemical cycling, and water resources management. Besides providing effective models of water flows, automatically extracted drainage networks based on topography can diverge from reality to varying degrees. The variability of such disagreement within catchments has rarely been examined as a function of the heterogeneity of land cover, soil type, and slope in the catchment of interest. This research gap might not only substantially limit our knowledge of the uncertainty of hydrological prediction, but can also cause problems for users attempting to use the data at a local scale. Using 1:100000 scale land cover maps, Quaternary deposits maps, and 2 m resolution DEMs, it is found that the accuracy of delineated drainage networks tends to be lower in areas with denser vegetation, lower hydraulic conductivity, and higher erodibility. The findings of this study could serve as a guide for the more thoughtful usage of delineated drainage networks in environmental planning, and in the uncertainty analysis of hydrological and biochemical predictions. Therefore, this study makes a first attempt at filling the knowledge gap described above

A minimalist model for coevolving supply and drainage networks

Numerous complex systems, both natural and artificial, are characterized by the presence of intertwined supply and/or drainage networks. Here, we present a minimalist model of such coevolving networks in a spatially continuous domain, where the obtained networks can be interpreted as a part of either the counter-flowing drainage or co-flowing supply and drainage mechanisms. The model consists of three coupled, nonlinear partial differential equations that describe spatial density patterns of input and output materials by modifying a mediating scalar field, on which supply and drainage networks are carved. In the two-dimensional case, the scalar field can be viewed as the elevation of a hypothetical landscape, of which supply and drainage networks are ridges and valleys, respectively. In the three-dimensional case, the scalar field serves the role of a chemical signal, according to which vascularization of the supply and drainage networks occurs above a critical ‘erosion’ strength. The steady-state solutions are presented as a function of non-dimensional channelization indices for both materials. The spatial patterns of the emerging networks are classified within the branched and congested extreme regimes, within which the resulting networks are characterized based on the absolute as well as the relative values of two non-dimensional indices.publishedVersio

Methods for photointerpretation of drainage networks in geosar radar remote sensing system

Metodología para fotointerpretar redes de drenajes en imágenes de radarMethodology for photo interpretation of drainage networks in radar image

High-resolution DEM generated from LiDAR data for water resource management

Terrain patterns play an important role in determining the nature of water resources and related hydrological modelling. Digital Elevation Models (DEMs), offering an efficient way to represent ground surface, allow automated direct extraction of hydrological features (Garbrecht and Martz, 1999), thus bringing advantages in terms of processing efficiency, cost effectiveness, and accuracy assessment, compared with traditional methods based on topographic maps, field surveys, or photographic interpretations. However, researchers have found that DEM quality and resolution affect the accuracy of any extracted hydrological features (Kenward et al., 2000). Therefore, DEM quality and resolution must be specified according to the nature and application of the hydrological features. The most commonly used DEM in Victoria, Australia is Vicmap Elevation delivered by the Land Victoria, Department of Sustainability and Environment. It was produced by using elevation data mainly derived from existing contour map at a scale of 1:25,000 and digital stereo capture, providing a state-wide terrain surface representation with a horizontal resolution of 20 metres. The claimed standard deviations, vertical and horizontal, are 5 metres and 10 metres respectively (Land- Victoria, 2002). In worst case, horizontal errors could be up to ±30m. Although high resolution stereo aerial photos provide a potential way to generate high resolution DEMs, under the limitations of currently used technologies by prevalent commercial photogrammetry software, only DSMs (Digital Surface Models) other than DEMs can be directly generated. Manual removal of the nonground data so that the DSM is transformed into a DEM is time consuming. Therefore, using stereo aerial photos to produce DEM with currently available techniques is not an accurate and costeffective method. Light Detection and Ranging (LiDAR) data covering 6900 km² of the Corangamite Catchment area of Victoria were collected over the period 19 July 2003 to 10 August 2003. It will be used to support a series of salinity and water management projects for the Corangamite Catchment Management Authority (CCMA). The DEM derived from the LiDAR data has a vertical accuracy of 0.5m and a horizontal accuracy of 1.5m. The high quality DEM leads to derive much detailed terrain and hydrological attributes with high accuracy. Available data sources of DEMs in a catchment management area were evaluated in this study, including the Vicmap DEM, a DEM generated from stereo aerial photos, and LiDAR-derived DEM. LiDAR technology and LiDAR derived DEM were described. In order to assess the capability of LiDAR-derived DEM for improving the quality of extracted hydrological features, sub-catchment boundaries and drainage networks were generated from the Vicmap DEM and the LiDAR-derived DEM. Results were compared and analysed in terms of accuracy and resolution of DEMs. Elevation differences between Vicmap and LiDAR-derived DEMs are significant, up to 65m in some areas. Subcatchment boundaries derived from these two DEMs are also quite different. In spite of using same resolution for the Vicmap DEM and the LiDARderived DEM, high accuracy LiDAR-derived DEM gave a detailed delineation of sub-catchment. Compared with results derived from LiDAR DEM, the drainage networks derived from Vicmap DEM do not give a detailed description, and even lead to discrepancies in some areas. It is demonstrated that a LiDAR-derived DEM with high accuracy and high resolution offers the capability of improving the quality of hydrological features extracted from DEMs

Monitoring planning for urban drainage networks

Urban drainage network (UDN) monitoring is an important task whose planning can be related to various purposes, as for example contaminant detection and epidemiological studies. This paper proposes two different strategies for the identification of a monitoring system for UDNs. The optimal solution, in terms of location and number of sensors, is firstly addressed using a deterministic approach. A new mathematical model is developed and a global optimization solver is employed to perform the optimization procedure. Secondly, the position of devices is also investigated using a new strategy based on the complex network theory (CNT) tools. The comparison between the results achieved by both the strategies is finally presented with reference to a benchmark network

Characteristic analysis of a flash flood-affected creek catchment using LiDAR-derived DEM

Flooding occurred across a large area of southern and central Queensland in December 2010 and January 2011. Intense rainfall over the Gowrie Creek catchment caused severe flash flooding through the Toowoomba CBD (Central Business District) on the afternoon of Monday, 10 January 2011, taking lives and damaging the community. Flash floods are sudden and unexpected floods that arise from intense rainfall, generally over a small, steep catchment area. Smaller and steeper catchments have shorter critical storm duration, and they respond more quickly to rainfall events. The resulting flood wave is characterized by very high water flows and velocities and abrupt water level rises, leading to extremely hazardous conditions. Effective flash flood forecasting for specific locations is a big challenge because of the behaviour of intense thunderstorms. A flash flood forecasting and warning system calls for accurate spatial information on catchment characteristics. A high-resolution DEM is a key spatial dataset for the characterization of a catchment to design possible flood mitigation measures. The characteristics of a catchment have a strong influence on its hydrological response. The nature of floods is dependent on both the intensity and duration of the rainfall and the catchment characteristics such as catchment area, drainage patterns and waterway steepness. Therefore, analysis of catchment characteristics is critical for hydrologic modelling and planning for flood risk mitigation. The analysis of catchment characteristics can support hydrological modelling and planning for flood risk mitigation. For example, the shape indices of sub-catchments can be used to compare the hydrological behaviour of different subcatchments. The longitudinal profiles of the creeks illustrate the slope gradients of the waterways. A hypsometric curve for each sub-catchment provides an overall view of the slope of a catchment and is closely related to ground slope characteristics of a catchment. Airborne light detection and ranging (LiDAR), also referred to as airborne laser scanning (ALS), is one of the most effective means of terrain data collection. Using LiDAR data for generation of DEMs is becoming a standard practice in the spatial science community. This study used airborne LiDAR data to generate a high-resolution DEM for characteristic analysis of Gowrie Creek catchment in Toowoomba, Queensland, Australia, which was affected by a flash flood in January 2011. Drainage networks and sub-catchment boundaries were extracted from LiDAR-derived DEM. Catchment characteristics including sub-catchment areas and shape indices, longitudinal profiles of creeks and hypsometric curves of sub-catchments were calculated and analysed

Mass movement susceptibility mapping using satellite optical imagery compared with InSAR monitoring: Zigui County, Three Gorges region, China

Mass movements on steep slopes are a major hazard to communities and infrastructure in the Three Gorges region, China. Developing susceptibility maps of mass movements is therefore very important in both current and future land use planning. This study employed satellite optical imagery and an ASTER GDEM (15 m) to derive various parameters (namely geology; slope gradient; proximity to drainage networks and proximity to lineaments) in order to create a GIS-based map of mass movement susceptibility. This map was then evaluated using highly accurate deformation signals processed using the Persistent Scatterer (PS) InSAR technique. Areas of high susceptibility correspond well to points of high subsidence, which provides a strong support of our susceptibility map

Conceptual quality modelling and integrated control of combined urban drainage system

This paper presents the first results of conceptual quality modelling approach oriented to the integrated real-time control (RTC) strategy for urban drainage networks (UDN) and wastewater treatment plants (WWTP) developed in the European project LIFE EFFIDRAIN (Efficient Integrated Real-time Control in Urban Drainage and Wastewater Treatment Plants for Environmental Protection). Model predictive control (MPC) has been selected as a proper RTC to minimize the polluting discharge in case of raining events. The simulator SWMM5 was modified to integrate a lumped conceptual model for total suspended solids (TSS) called SWMM-TSS, which has been used as virtual reality for calibration and validation of the proposed modelling approaches in Perinot network, a real case study in Bordeaux.Peer ReviewedPostprint (author's final draft

Limit theorems for random spatial drainage networks

Suppose that, under the action of gravity, liquid drains through the unit d-cube via a minimal-length network of channels constrained to pass through random sites and to flow with nonnegative component in one of the canonical orthogonal basis directions of Rd, d ≥ 2. The resulting network is a version of the so-called minimal directed spanning tree. We give laws of large numbers and convergence in distribution results on the large-sample asymptotic behaviour of the total power-weighted edge length of the network on uniform random points in (0, 1)d. The distributional results exhibit a weight-dependent phase transition between Gaussian and boundary-effect-derived distributions. These boundary contributions are characterized in terms of limits of the so-called on-line nearest-neighbour graph, a natural model of spatial network evolution, for which we also present some new results. Also, we give a convergence in distribution result for the length of the longest edge in the drainage network; when d = 2, the limit is expressed in terms of Dickman-type variables