Climate change and agricultural vulnerability: a case study of rain-fed wheat in Kairouan, Central Tunisia

In the Maghreb and North African regions, the interannual climate variability causes severe impacts on agriculture through long drought episodes. Impacts are expected to increase due to projected climate change. Decreasing water availability will have a direct impact on the agriculture sector and could endanger the socioeconomic development and social stability in Tunisia where rain-fed agriculture represents the main occupancy and means of subsistence for the large rural populatio

Documenting evapotranspiration and surface energy fluxes over rainfed annual crops within a Mediterranean hilly agrosystem

International audiencehe current study aims to document evapotranspiration and associated surface energy fluxes for rainfed annual crops within a Mediterranean hilly agrosystem, in order to provide information on crop water use under such little-studied conditions. For this, an experimental study is conducted within the Tunisian study site of the OMERE observatory (French acronym for the Mediterranean Observatory of Water and the Rural Environment), located in the north-eastern Cap Bon peninsula. It relies on eddy covariance (EC) measurements at the plot scale. We report that (1) observations are consistent with previous studies under Mediterranean or semi-arid contexts, with time series of energy fluxes that depict classical seasonal dynamics, (2) common flux ratios (i.e., Bowen Ratio, ratio of actual to reference evapotranspiration) may change according to upwinds and downwinds, which requires further investigations about possible changes in aerodynamic conditions, and (3) a reference evapotranspiration value of 4 mm day−1 seems to be a threshold beyond which actual evapotranspiration decreases systematically and rapidly. In terms of agricultural water management, the current study suggests to look for early sowing species/varieties, in order to reduce the evaporation-based water loss in autumn. Overall, EC measurements seem promising over rainfed annual crops within semiarid hilly agrosystems, for long term observations, environmental modelling and operational purposes. Since the current study is conducted over few small fields within a specific hilly topography, the original results we report here need to be strengthened with complementary studies

Observing Actual Evapotranspiration from Flux Tower Eddy Covariance Measurements within a Hilly Watershed: Case Study of the Kamech Site, Cap Bon Peninsula, Tunisia

There is a strong need for long term observations of land surface fluxes such as actual evapotranspiration (ETa). Eddy covariance (EC) method is widely used to provide ETa measurements, and several gap-filling methods have been proposed to complete inherent missing data. However, implementing gap-filling methods is questionable for EC time series collected within hilly agricultural areas at the watershed extent. Indeed, changes in wind direction induce changes in airflow inclination and footprint, and therefore possibly induce changes in the relationships on which rely gap-filling methods. This study aimed to obtain continuous ETa time series by adapting gap-filling methods to the particular conditions abovementioned. The experiment took place within an agricultural watershed in north-eastern Tunisia. A 9.6-m-high EC flux tower has been operating close to the watershed center since 2010. The sensible and latent heat fluxes data collected from 2010 to 2013 were quality controlled, and the REddyProc software was used to fill gaps at the hourly timescale. Adapting REddyProc method consisted of splitting the dataset according to wind direction, which improved the flux data at the hourly timescale, but not at the daily and monthly timescales. Finally, complete time series permitted to analyze seasonal and inter-annual variability of ETa

Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed Mediterranean agrosystem

International audienceExploring crop spatial organizations within landscapes is a promising solution for agroecological transitions and climate change adaptation in Mediterranean rainfed hilly agrosystems. A prerequisite is to ensure that crop models can simulate a range of agrohydrological processes in such agrosystems. The current study deepened the evaluation of the AquaCrop model by conducting a multicriteria evaluation (canopy cover CC, dry aboveground biomass AGB, actual evapotranspiration ETa, runoff R, soil water content SWC) for a range of crop and soil combinations, and for contrasted hydroclimatic years in northeastern Tunisia. The data were collected in the Kamech catchment (OMERE Observatory) during nine measurement campaigns on predominant soils and crops. AquaCrop simulations were based on field observations and parameters from the literature. AquaCrop could simulate plant dynamics and water fluxes for contrasted hydroclimatic years, with a slight dependence on soil class and a significant dependence on crop type. Model simulations were of moderate quality for CC (R2 of 0.45, RMSE of 0.24 on average) and of acceptable quality for AGB (R2 of 0.81, RMSE of 0.85 ton ha− 1 on average). AquaCrop acceptably simulated water transfer across the soil–plant continuum (R2 of 0.62, RMSE of 0.77 mm day− 1 on average for ETa; R2 of 0.68, RMSE of 0.75 mm day− 1 on average for R; R2 of 0.86, RMSE of 27.4 mm on average for SWC). The model performances were satisfactory for most cases, with p values larger than 5 % for the Student’s t test on linear regressions of validation. Our results were similar to those reported in previous studies over flat terrain, including delayed senescence by model simulations with subsequent overestimation of CC and AGB observations. Additionally, soil cracks likely altered the AquaCrop ability to simulate runoff. Despite these limitations, our results support the application of AquaCrop to evaluate water productivity in hilly agrosystems

Sub-chapter 3.2.2. Long term agro-ecosystem observatories in the Mediterranean

Introduction Alleviating the impacts of climate change is a major challenge facing agriculture in the near future. It is however not the sole challenge, since agriculture is experiencing many other pressures, including a 30 percent increase in global world population, changing dietary patterns and intensifying competition for increasingly scarce land, water and energy resources. In the Mediterranean area, all these challenges are at a very high level since this region already faces a shortage..

Observing actual evapotranspiration within a hilly watershed: case study of the Kamech site, Cap Bon peninsula, Tunisia

Surface-atmosphere flux data acquired by the Kamech flux tower (Environmental Research Observatory OMERE) between March 2010 and August 2013 A single data file (csv format) containing : quality controlled surface-atmosphere fluxes (friction velocity, sensible heat flux, latent heat flux) meteorological data required to gap fill them with REddyProc (incoming solar radiation, air temperature, air humidity) wind direction (sectors NW or S) More details (names of the variables, units) are given in the readme.first.txt fil

Analysis of rainfed cereal-legume mixture cropping water productivity in Lebna catchment, Cap-Bon, Tunisia

International audienceUnder climate change conditions, optimizing water resources management in rainfed agricultural production systems requires the reasonable choice of crops. In this context, the adoption of crops diversification is promoted to increase the agricultural production and the added value per cubic meter of rain water (green water) used by crops. Contributing, therefore, to increase agricultural production and to preserve soil and water resources. The objective of this study is: (i) to identify mixed crops within agricultural fields and, (ii) to evaluate the biomass production and the water productivity in the Lebna watershed (Cap-Bon, Tunisia) using remote sensing and field measurements. The study area, covering 210 km 2 , is characterized by the predominant of cereals, legumes and fodder cropping systems. The experiments allowed the quantification of crop evapotranspiration and the observed biomass production at the agricultural field plots. The use of the sentinel images and the observations at different agricultural fields allowed to produce NDVI maps. The results first confirmed a good correlation between biomass production and NDVI values. The exponential relationships showed a values of R 2 greater than 0.7. The use of sentinel images and GIS allowed to compute water productivity from field to watershed scale. The results revealed a considerable spatial variation in water productivity values for different crops. Compared to a single crop, the cereal-legume mixture cropping improved the water productivity. The maximum value with 9.07 kg m −3 is observed for the mixture crops. The lowest value (0.12 to 2.40 kg m −3) was obtained for the cereal crop. These results help to recommend adaptation measures in agricultural production systems to climate change

Optimized Software Tools to Generate Large Spatio-Temporal Data Using the Datacubes Concept: Application to Crop Classification in Cap Bon, Tunisia

In the context of a changing climate, monitoring agricultural systems is becoming increasingly important. Remote sensing products provide essential information for the crop classification application, which is used to produce thematic maps. High-resolution and regional-scale maps of agricultural land are required to develop better adapted future strategies. Nevertheless, the performance of crop classification using large spatio-temporal data remains challenging due to the difficulties in handling huge amounts of input data (different spatial and temporal resolutions). This paper proposes an innovative approach of remote sensing data management that was used to prepare the input data for the crop classification application. This classification was carried out in the Cap Bon region, Tunisia, to classify citrus groves among two other crop classes (olive groves and open field) using multi-temporal remote sensing data from Sentinel- 1 and Sentinel-2 satellite platforms. Thus, we described the new QGIS plugin “Model Management Tool (MMT)”. This plugin was designed to manage large Earth observation (EO) data. This tool is based on the combination of two concepts: (i) the local nested grid (LNG) called Tuplekeys and (ii) Datacubes. Tuplekeys or special spatial regions were created within a LNG to allow a proper integration between the data of both sensors. The Datacubes concept allows to provide an arranged array of time-series multi-dimensional stacks (space, time and data) of gridded data. Two different classification processes were performed based on the selection of the input feature (the obtained time-series as input data: NDVI and NDVI + VV + VH) and on the most accurate algorithm for each scenario (22 tested classifiers). The obtained results revealed that the best classification performance and highest accuracy were obtained with the scenario using only optical-based information (NDVI), with an overall accuracy OA = 0.76. This result was obtained by support vector machine (SVM). As for the scenario relying on the combination of optical and SAR data (NDVI + VV + VH), it presented an OA = 0.58. Our results demonstrate the usefulness of the new data management tool in organizing the input classification data. Additionally, our results highlight the importance of optical data to provide acceptable classification performance especially for a complex landscape such as that of the Cap Bon. The information obtained from this work will allow the estimation of the water requirements of citrus orchards and the improvement of irrigation scheduling methodologies. Likewise, many future methodologies will certainly rely on the combination of Tuplekeys and Datacubes concepts which have been tested within the MMT tool

Use of SWAT for hydrological modeling and evaluation of water flows in a semi-arid rainfed watershed in Tunisia

International audienceRainfed agriculture provides several benefits such as food and water resource production. However, it is becoming increasingly exposed to climate and anthropogenic changes. Which can increase the threats on crop and water resource production. To investigate the future anthropogenic and climate change impacts on crops production and water resources' preservation it is essential to ensure that models can appropriately simulate complex agro-hydrological processes in rainfed watershed. The objective of this study was to perform a multi-criteria evaluation of the SWAT model to understand and simulate agro-hydrological processes of the rainfed semi-arid watershed in Tunisia. In this study, 20 years (1995-2015) of hydro-meteorological and vegetation data from the Mediterranean Observatory for Rural Environment and Water (OMERE) have been used. Monitoring includes daily hydrometric data, soil moisture on multiple profiles, actual evapotranspiration, and aboveground biomass. The study focuses on the Lebna watershed (210 km 2) northeast of Tunisia marked by the predominance of rainfed wheat, legumes and fodder crops. The SWAT model is implemented by adopting a three-step calibration procedure. A first step was devoted to sensitivity analysis using the SWAT_CUP tool for model parameters. The calibration of the discharge at the level of the watershed, followed by a simultaneous calibration of the discharge and the evapotranspiration in order to test the effect on the model performances. The third step is to specify the management operations in the model and to assess the impacts on the results. The simulation was performed for the years 1995 to 2015, of which the first four years were considered for warming up the model. The analysis of the results of the model is carried out based on the discretization of the watershed according to a parcel division into more than 600 distinct units. According to the results, the model performance was improved by the multiparameter and multivariable calibration in terms of NSE. The ongoing analysis will concentrate on implementing reservoirs to have a better understanding of the possible impacts on the simulation

Regional sub-daily stochastic weather generator based on reanalyses for surface water stress estimation in central Tunisia

International audienc