PI: Zoubeida Kebaili Bargaoui (Ecole Nationale d’Ingénieurs de Tunis)
U.S. Partner: Kelly Caylor (Princeton University)
Project Dates: August 2013 to July 2015
Tunisia is a primarily agricultural country with sub-humid, sub-arid, and arid climate zones. As a result, the country's economy is very sensitive to the impact of droughts, so research on drought alert systems to facilitate drought monitoring, mitigation, and adaptation programs could be very useful. The project aims to contribute to drought identification and alert in Tunisia using water budget modeling, which incorporates satellite information. It will leverage the experimental African Drought Monitor (ADM) system developed by Princeton University researchers in collaboration with UNESCO and installed in Niamey and Nairobi. North Africa is not currently well covered by ADM, so this PEER Science project intends to enhance drought monitoring in the region by using local observations that are currently unavailable to ADM. Actual prediction of the water balance terms is one point of departure in ADM. The Princeton researchers are using a variable infiltration capacity (VIC) land surface model as the computational basis for the water balance representation in ADM and for land surface temperature modeling. Climate and soil data including from remote sensing sources are used as model inputs to compute soil moisture content and resulting water stress indicators.
The Tunisian research team, on the other hand, has developed a water balance model in recent years using ground-based local precipitation, air temperature, and soil data for runoff and evapotranspiration prediction. In the first phase of the project, the Tunisian model will be compared with ADM/VIC results to reconstitute a historic period of observation using runoff data (1960- 2010). The next element of the project is to assess the quality of satellite estimates and reanalysis data (rainfall in particular) that feed the VIC model by comparing them with ground estimations (historic reconstitution). In addition, the ENIT team has developed an application using ground observations and water balance modeling to assess drought indices, some of which have already been implemented in ADM. However, the drought index based on soil moisture percentiles adopted by ADM is not included in the Tunisian applications so far. An assessment of the drought indices and evaluation of their quality and ability to identify well-known past drought periods will also be carried out as part of the PEER project. Data will be shared through a web-based interface that will be developed as part of the existing ADM web interface in order to display the results of the North Tunisia Drought Monitor. Users will be able to access maps of model outputs (mainly precipitation, evapotranspiration, surface runoff, and soil moisture) and to spatially averaged drought indicators. Overall, the project should help to facilitate drought mitigation and adaptation efforts.
Summary of Recent Activities
During the first quarter of 2015, Dr. Bargaoui and his team collected data for modelling the Douimis and Beja watersheds. Utilizing GIS information, soil texture, soil occupation, geology, average basin hydraulic conductivity at saturation, average porosity, and field capacity were measured as they are required by the water balance BBH model. Aymen Ben Jaafar (PhD student) performed the calibration at Douimis watershed which, along with the Beja basin, was added to the six originally proposed areas of study.
The modelling of Oussafa basin (a Wadi Siliana sub-basin) using BBH was completed by team member Manoubia Zamouri, who finalized and presented her Master thesis during this period. Another PhD student, Nesrine Abid, finalized the BBH model calibration for the Joumine and Sejnane basins and this work, along with her modeling, has been accepted as an oral presentation at IUGG 2015
. The research team also acquired climatic and soil monitoring sensors to implement an intelligent system composed of wireless sensors that measure environmental data linked to drought indicators. PhD student Fantazi Walid from the Telecom Laboratory at ENIT will use this equipment to set up a spatio temporal database that interfaces with a web mapping application to constantly monitor and display the data.
The team now has 25 years of model predictions of evapotranspiration and soil moisture content to compute drought indices. This work was presented as a Poster at the IRTG 2015
conference. Additionally, team member Saoussen Dhib, along with an ITC team from the Netherlands, performed two correction procedures to TRMM-3B42 images using 78 heavy rainy events observed in northern Tunisia from January 2007 to August 2009. This work will enable the African Drought Monitor team to evaluate and test the satellite data method they adopt.
In the coming months, the team will estimate the actual amount of evapotranspiration using the calibrated BBH models for the Joumine and Sejnane basins. The team will also calibrate the BBH models for the Abid and Barbara basins and write a tutorial about drought indicators based on Evapotranspiration and soil moisture content using the BBH model. Dr. Bargaoui also plans exchange visits with Princeton University and organizing a local workshop on their work.
Website of Princeton University’s African Drought Monitor
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