Artificial Drainage Networks Research Articles

The Impact of Peatland Restoration on the Site Hydrology of an Abandoned Block-Cut Bog

Artificial drainage networks established throughout peatlands during the peat extraction process often remain active following abandonment, maintaining a water table relatively far from the surface of the peat, and hindering the survival and reestablishment of Sphagnum mosses. As an initial restoration effort, the primary drainage network of an abandoned cutover peat- land was blocked with a series of peat dams, consequently reducing the runoff efficiency and causing the site-average water table to rise by 32 cm. Higher water tables and a blocked drainage network resulted in increased runoff variability, dependent upon antecedent conditions (capacity to retain additional water on-site), and event-based precipitation dynamics. Evapotranspiration (ET) rates were 25% higher following rewetting (3.6 mm day �1 ) compared to pre- restoration ET rates of 2.7 mm day �1 . Total storage changes were restricted following rewetting, as a factor of the reduced runoff losses limiting water table drawdown, thereby con- straining peat compression and preventing undue drying of the unsaturated zone. An average surface level rebound of 3 cm was observed, increasing the mean hydraulic conduc- tivity by an order of magnitude. Changes to the system hydrology following restoration efforts produced hydro- logical conditions more favourable for the recolonization of Sphagnum mosses.

A spatial stochastic algorithm to reconstruct artificial drainage networks from incomplete network delineations

AbstractA spatial stochastic algorithm that aims to reconstruct an entire artificial drainage network of a cultivated landscape from disconnected reaches of the network is proposed here. This algorithm uses random network initialisation and a simulated annealing algorithm, both of which are based on random pruning or branching processes, to converge the multi-objective properties of the networks; the reconstructed networks are directed tree graphs, conform to a given cumulative length and maximise the proportion of reconnected reaches. This algorithm runs within a directed plot boundaries lattice, with the direction governed by elevation. The proposed algorithm was applied to a 2.6-km2 catchment of a Languedocian vineyard in the south of France. The 24-km-long reconstructed networks maximised the reconnection of the reaches obtained either from a hydrographic database or remote sensing data processing. The distribution of the reconstructed networks compared to the actual networks was determined using specific topographical and topological metrics on the networks. The results show that adding data on disconnected reaches to constrain reconstruction, while increasing the accuracy of the reconstructed network topology, also adds biases to the geometry and topography of the reconstructed network. This network reconstruction method allows the mapping of uncertainties in the representation while integrating most of the available knowledge about the networks, including local data and global characteristics. It also permits the assessment of the benefits of the remote sensing partial detection process in drainage network mapping.

Applications of network analysis for adaptive management of artificial drainage systems in landscapes vulnerable to sea level rise

The vulnerability of coastal landscapes to sea level rise is compounded by the existence of extensive artificial drainage networks initially built to lower water tables for agriculture, forestry, and human settlements. These drainage networks are found in landscapes with little topographic relief where channel flow is characterized by bi-directional movement across multiple time-scales and related to precipitation, wind, and tidal patterns. The current configuration of many artificial drainage networks exacerbates impacts associated with sea level rise such as salt-intrusion and increased flooding. This suggests that in the short-term, drainage networks might be managed to mitigate sea level rise related impacts. The challenge, however, is that hydrologic processes in regions where channel flow direction is weakly related to slope and topography require extensive parameterization for numerical models which is limited where network size is on the order of a hundred or more kilometers in total length. Here we present an application of graph theoretic algorithms to efficiently investigate network properties relevant to the management of a large artificial drainage system in coastal North Carolina, USA. We created a digital network model representing the observation network topology and four types of drainage features (canal, collector and field ditches, and streams). We applied betweenness-centrality concepts (using Dijkstra’s shortest path algorithm) to determine major hydrologic flowpaths based off of hydraulic resistance. Following this, we identified sub-networks that could be managed independently using a community structure and modularity approach. Lastly, a betweenness-centrality algorithm was applied to identify major shoreline entry points to the network that disproportionately control water movement in and out of the network. We demonstrate that graph theory can be applied to solving management and monitoring problems associated with sea level rise for poorly understood drainage networks in advance of numerical methods.

Agrarian landscapes linear features detection from LiDAR: application to artificial drainage networks

Linear features of agrarian landscapes are the anthropogenic elements such as hedgerows, ditches, and bench terraces that strongly impact agrarian areas' environmental behaviour, especially the ecological and hydrological areas. The need to map these linear elements for environmental impact assessments of agrarian areas is thus increasing since these maps limit the developments of spatial indicators and spatially distributed modelling. Until now, no generic remote sensing methodology has been proposed for such mapping purposes. This research was designed to assess the use of airborne LiDAR data for agrarian landscape linear features mapping. We proposed a methodology that uses LiDAR data in three steps. We first estimated elevation profiles from LiDAR points on a set of pre‐located sites. We secondly performed profile shape description with wavelet transform or a watershed algorithm. Finally, we classified the profiles using classification trees with predictors coming from shape analysis. Methodology accuracies were calculated for a ditch network detection problem in a Mediterranean vineyard landscape. LiDAR Toposys data and field survey data for ditch location were collected in June 2002. As ditches are always located on field boundary lattices, elevation profiles were only computed on field boundary sites. Methodologies, using wavelets or the watershed algorithm, gave similar accuracies. Overall accuracy is about 70% with a high ditch omission rate (50%) but low commission rate (15%). The omissions conform to those obtained when performing visual classification of profiles. This high omission rate in ditch detection is therefore due to LiDAR data, not methods. Dense vegetation over ditches during the summertime and the specific LiDAR points spatial sampling design explain these omissions. However, the proposed methodology, especially using wavelets transform, looks transposable for the automatic detection or characterization of other agrarian linear features.

Modelling Spatial Variability Along Drainage Networks with Geostatistics

Local characteristics of drainage networks such as cross-section geometry and hydraulic roughness coefficient, influence surface water transfers and must be taken into account when assessing the impact of human activities on hydrological risks. However, as these characteristics have not been available till now through remote sensing or hydrological modelling, the only available methods are interpolation or simulation based on scarce data. In this paper we propose a statistical model based on geostatistics that allows us to take account of both the spatial distribution and spatial uncertainties. To do this, we modify the geostatistical framework to suit directed tree supports corresponding to drainage network structures. The stationarity concept is specified assuming conditional independence between parts of the network; variogram fitting and modelling are then modified accordingly. A sequential multi Gaussian simulation procedure going upstream along the network is proposed. We illustrate this approach by studying the width of an 11-km long artificial drainage network in the south of France.

Do gravel bed river size distributions record channel network structure?

Bed load sediment particles supplied to channels by hillslopes are reduced in size by abrasion during downstream transport. The branching structure of the channel network creates a distribution of downstream travel distances to a given reach of river and thus may strongly influence the grain size distribution of the long‐term bed load flux through that reach. Here we investigate this hypothesis, using mass conservation and the Sternberg exponential decay equation for particle abrasion, to predict bed material variability at multiple scales for both natural and artificial drainage networks. We assume that over a sufficiently long timescale, no net deposition occurs and that grains less than 2 mm are swept away in suspension. We find that abrasion during fluvial transport has a surprisingly small effect on the bed load sediment grain size distribution, for the simple case of spatially uniform supply of poorly sorted hillslope sediments. This occurs because at any point in the channel network, local resupply offsets the size reduction of material transported from upstream. Thus river bed material may essentially mirror the coarse component of the size distribution of hillslope sediment supply. Furthermore, there is a predictable distance downstream at which the bed load grain size distribution reaches a steady state. In the absence of net deposition due to selective transport, large‐scale variability in bed material, such as downstream fining, must then be due primarily to spatial gradients in hillslope sediment production and transport characteristics. A second key finding is that average bed load flux will tend to stabilize at a constant value, independent of upstream drainage area, once the rate of silt production by bed load abrasion per unit travel distance is equal to the rate of coarse sediment supply per unit channel length (q). Bed load flux equilibrates over a distance that scales with the inverse of the fining coefficient in the abrasion rate law (α) and can be approximated simply as q/3α. Thus the efficiency of particle abrasion sets a fundamental length scale, shorter for weaker rocks and longer for harder rocks, which controls the expression in the river bed of variability in sediment supply. We explore the role of the abrasion length scale in modulating the influence of sediment supply variability in a number of channel network contexts, including individual tributary junctions, a sequence of tributary inputs along a main stem channel, and variable basin shapes and network architecture as expressed by the width function. These findings highlight the need for both data and theory that can be used to predict the grain size distributions supplied to channels by hillslopes.

Simulation of an Agricultural Drainage Network Using a GIS Network Model

At present, application of GIS network analysis for agricultural drainage management is limited, although the nature of water flow within a drainage network is by and large in a similar way to that of, for example, the traffic flow over a road network. This is due to the limitation of the current GIS network model, which has difficulties in handling the complexity and event-based dynamic nature of the drainage network. This research therefore focuses on drainage management problems in a floodplain where drainage is controlled by the natural and artificial drainage networks. GIS network capabilities were employed, with enhancements of specific needs for the drainage simulation. A specialized three-dimensional network model was developed to allow computation of important parameters for network analysis, making dynamic simulation of drainage corresponding to individual rainfall events possible. Test simulation results indicate that the simulation tends to overestimate the discharge volume and pollutant, but ...

Transport of Mercury in Three Contrasting River Basins

Total mercury (THg) concentrations and loadings in the Minnesota, Mississippi, and St. Croix Rivers were determined over a 2-year period. These rivers drain watersheds with greatly contrasting land use, soil, and hydrological characteristics. The Minnesota River basin is characterized by a vast artificial drainage network and fertile prairie soils that support the intensive cultivation of row crops. Mercury levels in this river are strongly correlated with total suspended solids concentrations, varying widely in response to precipitation and snowmelt runoff events. The St. Croix River and the headwater Mississippi River (above its confluence with the Minnesota River) drain watersheds characterized by more acidic and sandy soils, more forest and wetland areas, less artificial drainage, and less cultivation as compared to the Minnesota River watershed. Mercury concentrations and loadings in these rivers are much lower than those observed in the Minnesota River, vary over a much narrower range, and reflect a...

Studying the role of old agricultural terraces on runoff generation in a small Mediterranean mountainous basin

The small drainage basin of Cal Parisa was instrumented in early 1989 to study the hydrological and sediment routing behaviour of Mediterranean mountain areas formerly used for agriculture but now abandoned. Environmental changes produced by agricultural land use included the construction of terraces on the major part of the basin and subsequent artificial channelling of surface waters. Field observations and hydrological data suggest that storm runoff is generated by the contributing role of saturated areas, most of them originating from the terrace system. Modelling of the natural conditions before terracing, with the help of TOPMODEL, supports the hypothesis that terracing promotes the premature formation of saturated areas, increasing saturation overland flow at the expense of lower baseflow and actual evapotranspiration. Now, after land abandonment, the more relevant environmental hazard is linked to the spontaneous reorganization of the unmaintained artificial drainage network.