Till Francke

Modelling spatio-temporal patterns of sediment yield and connectivity in a semi-arid catchment with the WASA-SED model

Abstract Rainfall–runoff induced soil erosion causes important environmental degradation by reducing soil fertility and impacting on water availability as a consequence of sediment deposition in surface reservoirs used for water supply, particularly in semi-arid areas. However, erosion models developed on experimental plots cannot be directly applied to estimate sediment yield at the catchment scale, since sediment redistribution is also controlled by the transport conditions along the landscape. In particular, representation of landscape connectivity relating to sediment transfer from upslope areas to the river network is required. In this study, the WASA-SED model is used to assess the spatial and temporal patterns of water and sediment connectivity for a semi-arid meso-scale catchment (933 km2) in Brazil. It is shown how spatial and temporal patterns of sediment connectivity within the catchment change as a function of landscape and event characteristics. This explains the nonlinear catchment response in terms of sediment yield at the outlet. Citation Medeiros, P. H. A., Güntner, A., Francke, T., Mamede, G. L. & de Araújo, J. C. (2010) Modelling spatio-temporal patterns of sediment yield and connectivity in a semi-arid catchment with the WASA-SED model. Hydrol. Sci. J. 55(4), 636–648.

Automated catena-based discretization of landscapes for the derivation of hydrological modelling units

In hydrological and soil erosion modelling at large spatial scales, semi‐distributed approaches may use representative hillslope profiles to reproduce landscape variability. Until now, the process of delineating landscape units as homogeneous parts of the landscape with regard to their terrain, vegetation, and soil properties required expert knowledge and familiarity with the study area. In addition, the delineation procedure was often highly time‐consuming and included a high degree of subjectivity. This paper presents a novel, semi‐automated approach for the delineation of landscape units, the derivation of representative toposequences, and their partitioning into terrain components. It incorporates an algorithm to retrieve representative catenas and their attributes for elementary hillslope areas based on elevation and other key spatial data frequently required as environmental model input, e.g. vegetation and soil data. An example application for the Ésera catchment in Spain illustrates that with the presented approach, upscaling of hillslope properties becomes feasible for environmental modelling at large scales while ensuring reproducible results.

Connectivity of overland flow by drainage network expansion in a rain forest catchment

Soils in various places of the Panama Canal Watershed feature a low saturated hydraulic conductivity (Ks) at shallow depth, which promotes overland-flow generation and associated flashy catchment responses. In undisturbed forests of these areas, overland flow is concentrated in flow lines that extend the channel network and provide hydrological connectivity between hillslopes and streams. To understand the dynamics of overland-flow connectivity, as well as the impact of connectivity on catchment response, we studied an undisturbed headwater catchment by monitoring overland-flow occurrence in all flow lines and discharge, suspended sediment, and total phosphorus at the catchment outlet. We find that connectivity is strongly influenced by seasonal variation in antecedent wetness and can develop even under light rainfall conditions. Connectivity increased rapidly as rainfall frequency increased, eventually leading to full connectivity and surficial drainage of entire hillslopes. Connectivity was nonlinearly related to catchment response. However, additional information on factors such as overland-flow volume would be required to constrain relationships between connectivity, stormflow, and the export of suspended sediment and phosphorus. The effort to monitor those factors would be substantial, so we advocate applying the established links between rain event characteristics, drainage network expansion by flow lines, and catchment response for predictive modeling and catchment classification in forests of the Panama Canal Watershed and in similar regions elsewhere.

Monitoring Seasonal Changes in the Water Surface Areas of Reservoirs Using TerraSAR-X Time Series Data in Semiarid Northeastern Brazil

The 933 km2 Benguê catchment in northeastern Brazil is characterized by distinct rainy and dry seasons. Precipitation is stored in variously sized reservoirs, which is essential for the local population. In this study, we used TerraSAR-X SM (HH) data for an one-year monitoring of seasonal changes in the reservoir areas from July 2011 to July 2012. The monitoring was based on acquisitions in the ascending pass direction, complemented by occasional descending-pass images. To detect water surface areas, a histogram analysis followed by a global threshold classification was performed, and the results were validated using in situ GPS data. Distinguishing between small reservoirs and similar looking dark areas was difficult. Therefore, we tested several approaches for identifying misclassified areas. An analysis of the surface area dynamics of the reservoirs indicated high spatial and temporal heterogeneities and a large decrease in the total water surface area of the reservoirs in the catchment by approximately 30% within one year.

Increasing life expectancy of water resources literature

In a study from 2008, Lariviere and colleagues showed, for the field of natural sciences and engineering, that the median age of cited references is increasing over time. This result was considered counterintuitive: with the advent of electronic search engines, online journal issues and open access publications, one could have expected that cited literature is becoming younger. That study has motivated us to take a closer look at the changes in the age distribution of references that have been cited in water resources journals since 1965. Not only could we confirm the findings of Lariviere and colleagues. We were also able to show that the aging is mainly happening in the oldest 10–25% of an average reference list. This is consistent with our analysis of top-cited papers in the field of water resources. Rankings based on total citations since 1965 consistently show the dominance of old literature, including text books and research papers in equal shares. For most top-cited old-timers, citations are still growing exponentially. There is strong evidence that most citations are attracted by publications that introduced methods which meanwhile belong to the standard toolset of researchers and practitioners in the field of water resources. Although we think that this trend should not be overinterpreted as a sign of stagnancy, there might be cause for concern regarding how authors select their references. We question the increasing citation of textbook knowledge as it holds the risk that reference lists become overcrowded, and that the readability of papers deteriorates.

lumpR: An R package facilitating landscape discretisation for hillslope-based hydrological models

The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial or depend on commercial back-end software, and allow only a limited or no workflow automation at all. 5 Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multiscale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option 10 to include expert knowledge. Conversely, completely automatic operation also allows extensive analysis of aspects related to landscape discretisation. In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hill15 slopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes.

Comparison of approaches for water surface area segmentation using high resolution TerraSAR-X data for reservoir monitoring in a large semi-arid catchment in northeastern Brazil

The semi-arid Northeast of Brazil is characterized by distinct rainy and dry seasons. The water supply for the local population is based on surface reservoirs in which precipitation is collected. There are more than 150 reservoirs in the 933 km2 Benguê catchment, however, little is known about the temporal dynamics of the water storage in the reservoirs. In this study, we use TerraSAR-X imagery for a year-long monitoring of reservoir surface areas and their seasonal changes. The precise extraction of the reservoir surface areas forms the basis of the monitoring. Therefore, we evaluated the results of a pixel-based threshold classification and a feature-based segmentation (mean shift). The evaluation was based on in-situ GPS measurements and manual digitization. The results of the manual digitization and threshold classification were similar as both tended to underestimate the water surface area in comparison to GPS in-situ data. The mean shift segmentation, however, tended to spread over the shorelines into the surrounding areas. We used the threshold classification for the analysis of 47 TerraSAR-X images. The viewing direction of the TerraSAR-X sensor was also important for the distinction of the entire area of the reservoirs, since geometric effects at the shorelines shaded parts of the water surface area. For the monitoring of the reservoir area with only one viewing direction we derived an empirical geometry correction factor.