Towards a virtual observatory for ecosystem services and poverty alleviation

Lead PI
Dr Wouter Buytaert
Imperial College London, Civil & Environmental Engineering
Start Date
1 January, 2011
End Date
30 September, 2012
Project Code

For the indigenous communities of the Pacaya-Samira National Reserve in the Peruvian Amazon, turtle farming is a successful survival strategy.

The practice keeps the natural animal population numbers up and provides a necessary source of food and income. However, the success of the activity is highly dependent on information about the erratic river level, which may flood nesting beaches at crucial times.

In the Yasuni national park in the Ecuadorian Amazon, bush meat hunting regions are threatened by encroaching deforestation. At the same time in the Andean headwaters of Ecuador, Peru and Bolivia, the availability and quality of irrigation water depends strongly on mountain wetland management, and is potentially threatened by global climate change.

These are striking examples of many situations where the livelihoods of local communities depend on crucial ecosystem services. However, a sustainable management of these services is only possible using an advanced integration of climatic, hydrological, and ecological data. Current approaches to integrate such data have largely failed for a variety of reasons.

In Pacaya Samira, little local data are available resulting in very large uncertainties in the model predictions. In the Andean highlands, local politicians and managers have difficulties interpreting model simulations and design proper land management schemes. Finally, both systems can benefit strongly from the incorporation of local expert knowledge to reduce model uncertainties.

Recently, many methodologies for data integration and user interaction have been developed. They are known under the common umbrella of a "virtual observatory" (VO). The ultimate goal of a VO is a perfect integration of data, models and users. Worldwide, many coordinated activities are ongoing to make this integration a reality. However, far less attention has been paid to the question of how these developments can benefit environmental services management and poverty alleviation.

This project designed and implemented an environmental prediction system for the above mentioned case studies, using existing virtual observatory tools. In the second step, we developed, implemented and evaluated tools to improve the value of these systems in the specific conditions of poverty alleviation, i.e.,

  1. Improved communication of simulations. This action particularly focused on the visualisation of modelling results and their uncertainties;
  2. Assessing the value of collected data. In a data sparse and resources constrained environment, an optimal design of new data collection strategies was essential. Here we developed methods to simulate the value of different data on the model predictions;
  3. Integrating local managers' knowledge and practice in modelling systems. This module dealt with the development of a user interface to evaluate models, identify model failures and reject models.

Heavily relying on public domain software, open standards and existing VO efforts, we developed a platform for interdisciplinary, cost-efficient and highly tailored environmental data analysis and simulation. This platform was available immediately for the selected case studies, thus enabling direct poverty alleviation action benefiting an estimated 15000 local inhabitants.

Close collaboration with local stakeholders and integration in existing initiatives ensured a quick adoption of the platform. For instance, the InfoAndina website of project partner CONDESAN which was integrated, had more than 1600 registered users. At the same time, the project generated novel scientific insights in model simulation, communication and improvement in a developing context. The involvement of the PI in the global Virtual Observatory community ensured that the research results would optimally benefit ongoing research in this area.

Authors Title Year Citations
Ochoa-Tocachi, B.F.;Buytaert, W.;De Bièvre, B.;Celleri, R.;Crespo, P.;Villacis, M.;Llerena, C.A.;Acosta, L.;Villazon, M.;Guallpa, M.;Gil-Rios, J.;Fuentes, P.;Olaya, D.;Vinas, P.;Rojas, G.;Arias, S. Impacts of land use on the hydrological response of tropical Andean catchments 2016 5
Ochoa-Tocachi, B.F.;Buytaert, W.;De Bièvre, B. Regionalization of land-use impacts on streamflow using a network of paired catchments 2016
Vitolo, C.;Elkhatib, Y.;Reusser, D.;Macleod, C.J.A.;Buytaert, W. Web technologies for environmental Big Data 2015 36
Baez, S.;Malizia, A.;Carilla, J.;Blundo, C.;Aguilar, M.;Aguirre, N.;Aquirre, Z.;Alvarez, E.;Cuesta, F.;Duque, A.;Farfan-Rios, W.;Garcia-Cabrera, K.;Grau, R.;Homeier, J.;Linares-Palomino, R.;Malizia, L.R.;Cruz, O.Melo;Osinaga, O.;Phillips, O.L.;Reynel, C.;Silman, M.R.;Feeley, K.J. Large-Scale Patterns of Turnover and Basal Area Change in Andean Forests 2015
Greene, S.;Johnes, P.J.;Bloomfield, J.P.;Reaney, S.M.;Lawley, R.;Elkhatib, Y.;Freer, J.;Odoni, N.;Macleod, C.J.A.;Percy, B. A geospatial framework to support integrated biogeochemical modelling in the United Kingdom 2015 6
Nerini, D.;Zulkafli, Z.;Wang, L.P.;Onof, C.;Buytaert, W.;Lavado-Casimiro, W.;Guyot, J.L. A Comparative Analysis of TRMM-Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall-Runoff Modeling Applications 2015 8
Buytaert, W.;Baez, S.;Bustamante, M.;Dewulf, A. Web-Based Environmental Simulation: Bridging the Gap between Scientific Modeling and Decision-Making 2012 12
Beven, K.;Buytaert, W.;Smith, L.A. On virtual observatories and modelled realities (or why discharge must be treated as a virtual variable) 2012 21
Buytaert, W.;De Bièvre, B. Water for cities: The impact of climate change and demographic growth in the tropical Andes 2012 31
Zulkafli, Z.;Buytaert, W.;Onof, C.;Lavado, W.;Guyot, J.L. A critical assessment of the JULES land surface model hydrology for humid tropical environments 2012 11
Name Role Organisation Country
Dr Wouter Buytaert Ecuador; Peru
Dr Wouter Buytaert Lead Principal Investigator Imperial College London United Kingdom
Dr Vera Baez Jacome Principal Investigator CONDESAN Peru
Dr Art Dewulf Co Investigator Wageningen University Netherlands
Dr Neil McIntyre Co Investigator Imperial College London United Kingdom
Mr Pedro Vasquez-Ruesta Co Investigator La Molina National Agrarian University Peru
Cecilia Sandoval Researcher CONDESAN Peru