Wouter Buytaert

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.

A Comparative Performance Analysis of TRMM 3B42 (TMPA) Versions 6 and 7 for Hydrological Applications over Andean–Amazon River Basins

AbstractThe Tropical Rainfall Measuring Mission 3B42 precipitation estimates are widely used in tropical regions for hydrometeorological research. Recently, version 7 of the product was released. Major revisions to the algorithm involve the radar reflectivity–rainfall rate relationship, surface clutter detection over high terrain, a new reference database for the passive microwave algorithm, and a higher-quality gauge analysis product for monthly bias correction. To assess the impacts of the improved algorithm, the authors compare the version 7 and the older version 6 products with data from 263 rain gauges in and around the northern Peruvian Andes. The region covers humid tropical rain forest, tropical mountains, and arid-to-humid coastal plains. The authors find that the version 7 product has a significantly lower bias and an improved representation of the rainfall distribution. They further evaluated the performance of the version 6 and 7 products as forcing data for hydrological modeling by comparing ...

Web technologies for environmental Big Data

Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources. We review web service related technologies to manage, transfer and process Big Data.We examine international standards and related implementations.Many existing algorithms can be easily exposed as services and cloud-enabled.The adoption of standards facilitate the implementation of workflows.Use of web technologies to tackle environmental issues is acknowledged worldwide.

Regionalization as a learning process

This paper deals with the uncertainty involved in geographical migration of hydrological model structures, commonly known as regionalization. Regionalization relies on the hypothesis that calibrated parameter sets from a donor catchment can be useful to predict discharge of an ungauged catchment. However, since every catchment is unique, model parameters need to be adapted for differences between a calibration and a prediction catchment, either by transformation or further selection. This process is inherently uncertain. Model parameters, and therefore the required changes, do not exactly represent quantities that we can measure or calculate. This paper outlines an approach to learn about how model parameters should be transformed between a gauged and an ungauged catchment. The approach consists of an iterative process, in which a model structure is applied successively to gauged catchments. After each step, parameter behavior is evaluated as a function of catchment properties and intercatchment similarities. The method is illustrated with an application of a customized version of TOPMODEL to a set of catchments in the Ecuadorian Andes. First, parameter sets are generated for a donor catchment. This model ensemble is then used to predict the discharge of the other catchments, after applying a stochastic parameter transformation to account for the uncertainty in the model migration. The parameter transformation is then evaluated and improved before further application. The case study shows that accurate predictions can be made for predicted basins. At the same time, knowledge is gained about model behavior and potential model limitations.

Web-based environmental simulation: bridging the gap between scientific modeling and decision-making.

Data availability in environmental sciences is growing rapidly. Conventional monitoring systems are collecting data at increasing spatial and temporal resolutions; satellites provide a constant stream of global observations, and citizen scientist generate local data with electronic gadgets and cheap devices. There is a need to process this stream of heterogeneous data into useful information, both for science and for decision-making. Advances in networking and computer technologies increasingly enable accessing, combining, processing, and visualizing these data. This Feature reflects upon the role of environmental models in this process. We consider models as the primary tool for data processing, pattern identification, and scenario analysis. As such, they are an essential element of science-based decision-making. The new technologies analyzed here have the potential to turn the typical top-down flow of information from scientists to users into a much more direct, interactive approach. This may accelerate the dissemination of environmental information to a larger community of users. It may also facilitate harvesting feedback, and evaluating simulations and predictions from different perspectives. However, the evolution poses challenges, not only to model development but also to the communication of model results and their assumptions, shortcomings, and errors.

Diverging Responses of Tropical Andean Biomes under Future Climate Conditions

Observations and projections for mountain regions show a strong tendency towards upslope displacement of their biomes under future climate conditions. Because of their climatic and topographic heterogeneity, a more complex response is expected for biodiversity hotspots such as tropical mountain regions. This study analyzes potential changes in the distribution of biomes in the Tropical Andes and identifies target areas for conservation. Biome distribution models were developed using logistic regressions. These models were then coupled to an ensemble of 8 global climate models to project future distribution of the Andean biomes and their uncertainties. We analysed projected changes in extent and elevational range and identified regions most prone to change. Our results show a heterogeneous response to climate change. Although the wetter biomes exhibit an upslope displacement of both the upper and the lower boundaries as expected, most dry biomes tend to show downslope expansion. Despite important losses being projected for several biomes, projections suggest that between 74.8% and 83.1% of the current total Tropical Andes will remain stable, depending on the emission scenario and time horizon. Between 3.3% and 7.6% of the study area is projected to change, mostly towards an increase in vertical structure. For the remaining area (13.1%–17.4%), there is no agreement between model projections. These results challenge the common believe that climate change will lead to an upslope displacement of biome boundaries in mountain regions. Instead, our models project diverging responses, including downslope expansion and large areas projected to remain stable. Lastly, a significant part of the area expected to change is already affected by land use changes, which has important implications for management. This, and the inclusion of a comprehensive uncertainty analysis, will help to inform conservation strategies in the Tropical Andes, and to guide similar assessments for other tropical mountains.

High‐resolution satellite‐gauge merged precipitation climatologies of the Tropical Andes

Satellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the Tropical Andes. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) was active for 17 years (1998–2014) and has generated one of the longest single-sensor, high-resolution, and high-accuracy rainfall records. In this study, high-resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite-gauge (S-G) merging approaches. The resulting precipitation products are evaluated by cross validation and catchment water balances (runoff ratios) for 50 catchments across the Tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients but underestimates absolute monthly rainfall rates. The S-G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge-only product based on ordinary Kriging. Among the S-G merging methods, performance of inverse distance interpolation of satellite-gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g., Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S-G merged products presented in this study are available in the public domain.

Analysis of the water balance of small paramo catchments in south ecuador

The paramo is a high altitudinal wetland ecosystem in the upper Andes of Venezuela, Colombia, Ecuador and northern Peru. It is a reliable and constant source of high quality water and as such, the major water provider for the Andean highlands and part of the coastal plains. Water is used for consumption as well as electricity production. However, scientific evidence suggests that the quality and quantity of this water source may be at risk, due to increasing human interference in the wetland ecosystem. The current study analyses the water balance of two microcatchments near Cuenca, Ecuador. One is covered by the typical natural grass vegetation, while the other catchment is heavily interfered and intensive cultivation, cattle grazing and drainage are taking place. Three rain gauges and a V-notch were installed in each catchment, and one meteorological station in a nearby location. Analysis of the precipitation data reveals that seasonal variability in the paramo is extremely low. This property is a major reason for the sustained base flow, which characterises the paramo. However, evapotranspiration, represented by the crop coefficient, is more than twice as high in the cultivated areas (0.95), compared to the natural vegetation (0.42). The increased evapotranspiration may seriously affect the water production of interfered paramo catchments. Finally, based on water balance analysis, the variation in water storage in the paramo is very low, with a yearly variation of about 25 mm. In the interfered catchment, the storage in variation is even lower, about 15 mm, suggesting a deterioration of the regulation capacity.

Citizen Science for Water Resources Management: Toward Polycentric Monitoring and Governance?

Novel and more affordable technologies are allowing new actors to engage increasingly in the monitoring of hydrological systems and the assessment of water resources. This trend may shift data collection from a small number of mostly formal institutions (e.g., statutory monitoring authorities, water companies) toward a much more dynamic, decentralized, and diverse network of data collectors (including citizens and other non-specialists). Such a move toward a more diverse and polycentric type of monitoring may have important consequences for the generation of knowledge about water resources and the way that this knowledge is used to govern these resources.

Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

AbstractAn extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000–13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cevennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimatio...