Irrigation is one of the main users of water worldwide and its overuse may affect the natural regimes of water systems. To avoid this, drainage and irrigation management needs to be improved. This study aims to determine the amount of water lost to drainage in a semi-arid Mediterranean irrigated area. Water use, rainfall and drainage were monitored for 12 months (2019–2020) in a 425 ha sub-basin in the Algerri-Balaguer irrigation district (8000 ha, NE Spain). In addition, irrigation requirements were estimated using the single-crop FAO-56 method and a two-source energy balance model (TSEB) was used to estimate actual evapotranspiration in the sub-basin. Water lost to drainage in the sub-basin was estimated as 18% of the total water that entered the perimeter as irrigation and rainfall, which are almost five time higher than theoretical requirements of leaching. Out of the total drainage water, 57% was estimated to be irrigation water and 43% rainwater. The average amount of irrigation water used was 614 mm and irrigation efficiency in the sub-basin was estimated at 80.2% and averaged actual evapotranspiration at 1144 mm. The available margin of improvement is between 19.3% of the present irrigation drainage ratio and the 3.8% estimated with the leaching requirement model.
<p>Irrigation consumes around 70% of the world&#8217;s freshwater and has a significant impact on the continental water and energy cycles of the basins where it is present. Despite the clear benefits of irrigation, it has a strong impact on the continental water cycle, which must be evaluated to improve water resources management. Land-Surface Models (LSM) and remote sensing data can be used to analyse and quantify how irrigation affects the continental water cycle.</p><p>The Ebro basin is located in the Iberian Peninsula and is a representative Mediterranean basin. It is therefore characterised by a variety of different landscapes, as well as an uneven distribution of precipitation. This leads to the construction of a large network of dams and canals to supply water to agricultural irrigated districts. In fact, irrigated agriculture and farming represent 92% of the basin's total water consumption, according to the Ebro Hydrographic Confederation.</p><p>This work presents studies using datasets developed at the Ebro Observatory to simulate irrigation related processes over the Ebro basin with a LSM. It is provided at 1 km spatial resolution and contains meteorological and physiographical data, namely vegetation classes, actual irrigated areas, irrigation methods per area, and a new version of the SAFRAN meteorological forcing. All of the simulations used in the work presented here are carried out using the SURFEX LSM v9 version, which has an irrigation scheme implemented.</p><p>In the first place, we evaluate how the new physiographic datasets impact irrigation simulation in the area. Then, the datasets are used to perform simulations to analyse the impact of different irrigation scenarios (defined by different model parameters) on irrigation, evaporation, streamflow, and drainage. The scenarios defined are the default configuration of SURFEX&#8217;s irrigation scheme, a realistic simulation based on a survey to farmers from several irrigation districts from the Ebro basin, and further scenarios modifying the irrigation event&#8217;s frequency and amount of water. For this analysis, the simulations are carried out from 2008 to 2019.&#160;</p><p>In the second place, a comparison of our simulation results to remote sensing irrigation estimations from the ESA funded IRRIGATION+ project is performed. For this, the irrigation estimation is added to the precipitation of the SAFRAN forcing, which is then used to force SURFEX simulations. The irrigation products span different periods ranging from 2015 to 2021 and are based on different techniques: data assimilation (Sentinel-1), SM-based DELTA algorithm (Sentinel-1), SM-based inversion algorithm (Sentinel-1, ERA5-Land, GLEAM product), and the Hydrological Similar Pixels (HSP) algorithm.</p><p>This work is a contribution to the LIAISE campaign, through the IDEWA project (PCI2020-112043), as well as to the IRRIGATION+ (4000129870/20/I-NB) project.</p>
Abstract. In semi-arid irrigated environments, the agricultural drainage is at the heart of three agro-environmental issues: it is an indicator of water productivity, it is the main control to prevent soil salinization and waterlogging problems, and it is related to the health of downstream ecosystems. Crop water balance models combined with subsurface models can be used to estimate the drainage quantities and dynamics at various spatial scales. However, the precision (capacity of a model to fit the observed drainage using site-specific calibration) and accuracy (capacity of a model to approximate observed drainage using default input parameters) of such models have not yet been assessed in irrigated areas. To fill the gap, this study evaluates four parsimonious drainage models based on the combination of two surface models (RU and SAMIR) and two subsurface models (Reservoir and SIDRA) with varying complexity levels: RU-Reservoir, RU-SIDRA, SAMIR-Reservoir, and SAMIR-SIDRA. All models were applied over two sub-basins of the Algerri-Balaguer irrigation district, northeastern Spain, that are equipped with surface and subsurface drains driving the drained water to general outlets where the discharge is continuously monitored. Results show that RU-Reservoir is the most precise (average KGE (Q0.5) of 0.87), followed by SAMIR-Reservoir (average KGE (Q0.5) of 0.79). However, SAMIR-Reservoir is the most accurate model for providing rough drainage estimates using the default input parameters provided in the literature.
The modeling of irrigation in land surface models are generally based on two soil moisture parameters SMthreshold and SMtarget at which irrigation automatically starts and stops respectively. Typically, both parameters are usually set to optimal values allowing to fill the soil water reservoir with just the estimated right amount and to avoid crop water excess at all times. The point is that agricultural practices greatly vary according to many factors (climatological, crop, soil, technical, human, etc.). To fill the gap, we propose a new calibration method of SMthreshold and SMtarget to represent the irrigation water use in any (optimal, deficit or even over) irrigation regime. The approach is tested using the dual-crop coefficient FAO-56 model implemented at the field scale over an 8,100 ha irrigation district in northeastern Spain where the irrigation water use is precisely monitored at the district scale. Both irrigation parameters are first retrieved at monthly scale from the irrigation observations of year 2019. The irrigation simulated by the FAO-56 model is then evaluated against observations at district and weekly scale over 5 years (2017-2021) separately. The performance of the newly calibrated irrigation module is also assessed by comparing it against three other modules with varying configurations including default estimates for SMthreshold and SMtarget. The proposed irrigation module obtains systematically the best performance for each of the 5 years with an overall correlation coefficient of 0.95±0.02 and root-mean square error of 0.27±0.07 hm3/week (0.64±0.17 mm/day). Unlike the three irrigation modules used as benchmark, the new irrigation module is able to reproduce the farmers’ practices throughout the year, and especially, to simulate the actual water use in the deficit and excess irrigation regimes occurring in the study area in spring and summer respectively.
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