To model land-use impacts on water quality and water quantity, there needs to be a good understanding of the past to calibrate and validate numerical models. The current lack of processes to quantify historical variation in ditch networks was a driver in the development a new study in Finland to quantify the spatial and temporal development of past ditching at a catchment scale.
A new paper in the Journal of Irrigation and Drainage Engineering uses aerial images to provide new insight into temporal and special distribution of catchment-scale peatland drainage. To the authors’ knowledge, this is the first study presenting methods for quantifying drainage history in catchments dominated by peatland forestry. Learn about it in "Development of Aerial Photos and LIDAR Data Approaches to Map Spatial and Temporal Evolution of Ditch Networks in Peat-Dominated Catchments" by Joy Bhattacharjee; Hannu Marttila; Ali Torabi Haghighi; Miia Saarimaa; Anne Tolvanen; Ahti Lepistö; Martyn N. Futter; and Bjørn Kløve. Read the abstract below, then the full paper in the ASCE Library.
Spatiotemporal information on historical peatland drainage is needed to relate past land use to observed changes in catchment hydrology. Comprehensive knowledge of historical development of peatland management is largely unknown at the catchment scale. Aerial photos and light detection and ranging (LIDAR) data enlarge the possibilities for identifying past peatland drainage patterns. Here, our objectives are (1) to develop techniques for semiautomatically mapping the location of ditch networks in peat-dominated catchments using aerial photos and LIDAR data, and (2) to generate time series of drainage networks. Our approaches provide open-access techniques to systematically map ditches in peat-dominated catchments through time. We focused on the algorithm in such a way that we can identify the ditch networks from raw aerial images and LIDAR data based on the modification of multiple filters and number of threshold values. Such data are needed to relate spatiotemporal drainage patterns to observed changes in many northern rivers. We demonstrate our approach using data from the Simojoki River catchment (3,160 km2) in northern Finland. The catchment is dominated by forests and peatlands that were almost all drained after 1960. For two representative locations in cultivated peatland (downstream) and peatland forest (upstream) areas of the catchment; we found total ditch length density (km/km2), estimated from aerial images and LIDAR data based on our proposed algorithm, to have varied from 2% to 50% compared with the monitored ditch length available from the National Land survey of Finland (NLSF) in 2018. A different pattern of source variation in ditch network density was observed for whole-catchment estimates and for the available drained-peatland database from Natural Resources Institute Finland (LUKE). Despite such differences, no significant differences were found using the nonparametric Mann-Whitney U test with a 0.05 significance level based on the samples of pixel-identified ditches between (1) aerial images and NLSF vector files and (2) LIDAR data and NLSF vector files.
Read the full paper in the ASCE Library: https://doi.org/10.1061/(ASCE)IR.1943-4774.0001547