Water use efficiency and yield of winter wheat under different irrigation regimes in a semi-arid region

In irrigation schemes under rotational water supply in semi-arid region, the water allocation and irrigation scheduling are often based on a fixed-area proportionate water depth with every irrigation cycle irrespective of crops and their growth stages, for an equitable water supply. An experiment was conducted during the 2004- 2005 season in Haouz irrigated area in Morocco, which objective was 1) to evaluate the effects of the surface irrigation scheduling method (ex-isting rule) adopted by the irrigation agency on winter wheat production compared to a full ir-rigation method and 2) to evaluate drip irrigation versus surface irrigation impacts on water sav-ing and yield of winter wheat. The methodology was based on the FAO-56 dual approach for the surface irrigation scheduling. Ground measure- ments of the Normalized Difference Vegetation Index (NDVI) were used to derive the basal crop coefficient and the vegetation fraction cover. The simple FAO-56 approach was used for drip irrigation scheduling. For surface irrigation, the existing rule approach resulted in yield and WUE reductions of 22% and 15%, respectively, compared with the optimized irrigation sched-uling proposed by the FAO-56 for full irrigation treatment. This revealed the negative effects of the irrigation schedules adopted in irrigation schemes under rotational water supply on crops productivity. It was also demonstrated that drip irrigation applied to wheat was more efficient with 20% of water saving in comparison with surface irrigation (full irrigation treatment). Drip irrigation gives also higher wheat yield com-pared to surface irrigation (+28% and +52% for full irrigation and existing rule treatments re-spectively). The same improvement was ob-served for water use efficiency (+24% and +59% respectively)

Potential for early forecast of Moroccan wheat yields based on climatic drivers

Wheat production plays an important role in Morocco. Current wheat forecast systems use weather and vegetation data during the crop growing phase, thus limiting the earliest possible release date to early spring. However, Morocco' s wheat production is mostly rainfed and thus strongly tied to fluctuations in rainfall, which in turn depend on slowly evolving climate dynamics. This offers a source of predictability at longer time scales. Using physically guided causal discovery algorithms, we extract climate precursors for wheat yield variability from gridded fields of geopotential height and sea surface temperatures which show potential for accurate yield forecasts already in December, with around 50% explained variance in an out‐of‐sample cross validation. The detected interactions are physically meaningful and consistent with documented ocean‐atmosphere feedbacks. Reliable yield forecasts at such long lead times could provide farmers and policy makers with necessary information for early action and strategic adaptation measurements to support food security

The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat

Evapotranspiration is an important component of the water cycle, especially in semi-arid lands. A way to quantify the spatial distribution of evapotranspiration and water stress from remote-sensing data is to exploit the available surface temperature as a signature of the surface energy balance. Remotely sensed energy balance models enable one to estimate stress levels and, in turn, the water status of continental surfaces. Dual-source models are particularly useful since they allow derivation of a rough estimate of the water stress of the vegetation instead of that of a soil–vegetation composite. They either assume that the soil and the vegetation interact almost independently with the atmosphere (patch approach corresponding to a parallel resistance scheme) or are tightly coupled (layer approach corresponding to a series resistance scheme). The water status of both sources is solved simultaneously from a single surface temperature observation based on a realistic underlying assumption which states that, in most cases, the vegetation is unstressed, and that if the vegetation is stressed, evaporation is negligible. In the latter case, if the vegetation stress is not properly accounted for, the resulting evaporation will decrease to unrealistic levels (negative fluxes) in order to maintain the same total surface temperature. This work assesses the retrieval performances of total and component evapotranspiration as well as surface and plant water stress levels by (1) proposing a new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) in two versions (parallel and series resistance networks) based on the TSEB (Two-Source Energy Balance model, Norman et al., 1995) model rationale as well as state-of-the-art formulations of turbulent and radiative exchange, (2) challenging the limits of the underlying hypothesis for those two versions through a synthetic retrieval test and (3) testing the water stress retrievals (vegetation water stress and moisture-limited soil evaporation) against in situ data over contrasted test sites (irrigated and rainfed wheat). We demonstrated with those two data sets that the SPARSE series model is more robust to component stress retrieval for this cover type, that its performance increases by using bounding relationships based on potential conditions (root mean square error lowered by up to 11 W m−2 from values of the order of 50–80 W m−2), and that soil evaporation retrieval is generally consistent with an independent estimate from observed soil moisture evolution

Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

International audienceA CO2-responsive land surface model (the ISBAA- gs model of M´et´eo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale

Linkages between snow cover, temperature and rainfall and the North Atlantic Oscillation over Morocco

Snowpack significantly contributes to water resources in North Africa. The objective of this work was to analyze the impact of the North Atlantic Oscillation (NAO) on rainfall and temperature in Morocco at a sub-seasonal scale and to evaluate, for the first time, linkages between the NAO and snow cover area (SCA) derived from remote sensing observations. For this purpose, we analyzed daily SCA products (2000-2013) from the MODIS sensor, meteorological data from 37 stations (1993-2011), NCEP re-analysis of surface air temperature and rainfall rate, and a monthly NAO index. The linear linkages sought using simple correlation analysis demonstrated that negative (positive) NAO (1) is associated with enhanced (reduced) rainfall in December and February for the northern part of the country; (2) occurs with above-normal (below-normal) temperature and, in contrast with rainfall, the correlation persists far inland and late in the season. These results highlight a possible competing influence of NAO on the snowpack dynamic through rainfall and temperature. Indeed, negative (positive) NAO tends to favor earlier (later) melting and lesser (greater) SCA in spring (April-May) through milder temperatures. Results have direct implications for seasonal forecast of SCA in Morocco

Projected changes on the surface water resources of the Rherhaya basin (High Atlas, Morocco) by a set of Med-CORDEX models.

International audienceTo anticipate the potential changes in water quantity available within the Rherhaya mountainous watershed (near to Marrakech), it’s important to know the evolution of this resource in relation with climate changes. In this study we use the GR4J model with a snow module with time series of precipitations and discharge (1989 - 2009). The model was calibrated and validated successfully over various periods. Then we used an ensemble of 5 regional climate models (RCM) provided by the Med-CORDEX program with a method of perturbation by quantiles to simulate future scenarios of flow predictions.The evaluation of the precipitations simulated by the RCMs models (RCM) shows a strong underestimation of ~50% but a good reproduction of the cycle for the temperatures. The future changes according to two scenarios RCP4.5 and RCP8.5 show a rise of the temperatures (+1.4°, +2.6° respectively) in conjunction with a decrease in total precipitation (-19%,- 31%). Concerning the hydrological modeling with GR4J, stable results are obtained for calibration and validation whatever the chosen period, with maximum bias of 15% in validation on the monthly flows. Flow forecasts (2049-2065) present a strong projected decrease in surface runoff (-30%, -60%) and significant drops of the snow-covered reservoir levels, related to the precipitation decrease and the temperature increase