Bert De Bièvre

Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development

The participation of the general public in the research design, data collection and interpretation process together with scientists is often referred to as citizen science. While citizen science itself has existed since the start of scientific practice, developments in sensing technology, data processing and visualisation, and communication of ideas and results, are creating a wide range of new opportunities for public participation in scientific research. This paper reviews the state of citizen science in a hydrological context and explores the potential of citizen science to complement more traditional ways of scientific data collection and knowledge generation for hydrological sciences and water resources management. Although hydrological data collection often involves advanced technology, the advent of robust, cheap and low-maintenance sensing equipment provides unprecedented opportunities for data collection in a citizen science context. These data have a significant potential to create new hydrological knowledge, especially in relation to the characterisation of process heterogeneity, remote regions, and human impacts on the water cycle. However, the nature and quality of data collected in citizen science experiments is potentially very different from those of traditional monitoring networks. This poses challenges in terms of their processing, interpretation, and use, especially with regard to assimilation of traditional knowledge, the quantification of uncertainties, and their role in decision support. It also requires care in designing citizen science projects such that the generated data complement optimally other available knowledge. Lastly, we reflect on the challenges and opportunities in the integration of hydrologically-oriented citizen science in water resources management, the role of scientific knowledge in the decision-making process, and the potential contestation to established community institutions posed by co-generation of new knowledge.

Linking hydrological, infinite slope stability and land-use change models through GIS for assessing the impact of deforestation on slope stability in high Andean watersheds

In the Ecuadorian Andes, episodic slope movements comprising shallow rotational and translational slides and rapid flows of debris and soil material are common. Consequently, not only considerable financial costs are experienced, but also major ecological and environmental problems arise in a larger geographical area. Sediment production by slope movement on hillslopes directly affects sediment transport and deposition in downstream rivers and dams and morphological changes in the stream channels. In developing countries world-wide, slope movement hazards are growing: increasing population pressure and economic development force more people to move to potentially hazardous areas, which are less suitable for agriculture and rangelands. This paper describes the methods used to determine the controlling factors of slope failure and to build upon the results of the statistical analysis a process-based slope stability model, which includes a dynamic soil wetness index using a simple subsurface flow model. The model provides a time-varying estimate of slope movement susceptibility, by linking land-use data with spatially varying hydrologic (soil conductivity, evapotranspiration, soil wetness) and soil strength properties. The slope stability model was applied to a high Andean watershed (Gordeleg Catchment, 250 ha, southern Ecuadorian Andes) and was validated by calculating the association coefficients between the slope movement susceptibility map of 2000 and the spatial pattern of active slope movements, as measured in the field with GPS. The proposed methodology allows assessment of the effects of past and future land-use change on slope stability. A realistic deforestation scenario was presented: past land-use change includes a gradual fragmentation and clear cut of the secondary forests, as observed over the last four decades (1963-2000), future land-use change is simulated based on a binary logistic deforestation model, whereby it was assumed that future land-use change would continue at the same rate and style as over the last 37 years (1963-2000)

User-driven design of decision support systems for polycentric environmental resources management

Open and decentralized technologies such as the Internet provide increasing opportunities to create knowledge and deliver computer-based decision support for multiple types of users across scales. However, environmental decision support systems/tools (henceforth EDSS) are often strongly science-driven and assuming single types of decision makers, and hence poorly suited for more decentralized and polycentric decision making contexts. In such contexts, EDSS need to be tailored to meet diverse user requirements to ensure that it provides useful (relevant), usable (intuitive), and exchangeable (institutionally unobstructed) information for decision support for different types of actors. To address these issues, we present a participatory framework for designing EDSS that emphasizes a more complete understanding of the decision making structures and iterative design of the user interface. We illustrate the application of the framework through a case study within the context of water-stressed upstream/downstream communities in Lima, Peru. Environmental management may involve polycentric governance arrangements.Decision support for such contexts needs to meet diverse user requirements.A user-driven approach is proposed that involves actor and decision making analysis.This is combined with co-design methods from Human-Computer Interaction research.The result is more tailored decision support for users with different experiences.

Regionalization of land‐use impacts on streamflow using a network of paired catchments

Quantifying the impact of land use and cover (LUC) change on catchment hydrological response is essential for land-use planning and management. Yet hydrologists are often not able to present consistent and reliable evidence to support such decision-making. The issue tends to be twofold: a scarcity of relevant observations, and the difficulty of regionalizing any existing observations. This study explores the potential of a paired catchment monitoring network to provide statistically robust, regionalized predictions of LUC change impact in an environment of high hydrological variability. We test the importance of LUC variables to explain hydrological responses and to improve regionalized predictions using 24 catchments distributed along the Tropical Andes. For this, we calculate first 50 physical catchment properties, and then select a subset based on correlation analysis. The reduced set is subsequently used to regionalize a selection of hydrological indices using multiple linear regression. Contrary to earlier studies, we find that incorporating LUC variables in the regional model structures increases significantly regression performance and predictive capacity for 66% of the indices. For the runoff ratio, baseflow index, and slope of the flow duration curve, the mean absolute error reduces by 53% and the variance of the residuals by 79%, on average. We attribute the explanatory capacity of LUC in the regional model to the pairwise monitoring setup, which increases the contrast of the land-use signal in the data set. As such, it may be a useful strategy to optimize data collection to support watershed management practices and improve decision-making in data-scarce regions.

High-resolution hydrometeorological data from a network of headwater catchments in the tropical Andes

This article presents a hydrometeorological dataset from a network of paired instrumented catchments, obtained by participatory monitoring through a partnership of academic and non-governmental institutions. The network consists of 28 headwater catchments (<20 km2) covering three major biomes in 9 locations of the tropical Andes. The data consist of precipitation event records at 0.254 mm resolution or finer, water level and streamflow time series at 5 min intervals, data aggregations at hourly and daily scale, a set of hydrological indices derived from the daily time series, and catchment physiographic descriptors. The catchment network is designed to characterise the impacts of land-use and watershed interventions on the catchment hydrological response, with each catchment representing a typical land use and land cover practice within its location. As such, it aims to support evidence-based decision making on land management, in particular evaluating the effectiveness of catchment interventions, for which hydrometeorological data scarcity is a major bottleneck. The data will also be useful for broader research on Andean ecosystems, and their hydrology and meteorology.