Statistical emulators of irrigated crop yields and irrigation water requirements

2020 ◽  
Vol 284 ◽  
pp. 107828
Author(s):  
Élodie Blanc
2021 ◽  
Author(s):  
Romeu G. Jorge ◽  
Isabel P. de Lima ◽  
João L.M.P. de Lima

<p>In irrigated agricultural areas, where the availability of water for irrigation does not rely on any water storage, water management requires special attention, in particular under large annual and inter-annual variability in the hydrological regime and the uncertainty of climate change. The inherent increased vulnerability of the agro-ecosystem, makes the monitoring of crop conditions and water requirements a valuable tool for improving water use efficiency and, therefore, crop yields.</p><p>This presentation focus on one such agricultural area, located in the Lis Valley (Centre of Portugal), which is a rather vulnerable area also facing drainage and salinity problems. The study aims at contributing to better characterizing the temporal and spatial distribution of rice water requirements during the growing season. Irrigation water sources are the Lis River and its tributaries, which discharges depend directly from precipitation. The most important problems of water distribution in the Lis Valley irrigation district are water shortage and poor water quality in the dry summer period, aggravated by limitations of the irrigation and drainage systems that date back to the end of the 1950’s.</p><p>We report preliminary results on using remote sensing data to better understand rice cropping local conditions, obtained within project GO Lis (PDR2020-101-030913) and project MEDWATERICE (PRIMA/0006/2018). Rice irrigation is traditionally conducted applying continuous flooding, which requires much more irrigation water than non-ponded crops, and therefore needs special attention. In particular, data obtained from satellite Sentinel-2A land surface imagery are compared with data obtained using an unmanned aerial vehicle (UAV). Data for rice cultivated areas during the 2020 cultivation season, together with weather and crop parameters, are used to calculate biophysical indicators and indices of water stress in the vegetation. Actual crop evapotranspiration was appraised with remote sensing based estimates of the crop coefficient (Kc) and used to assess rice water requirements. Procedures and methodologies to estimate Kc were tested, namely those based on vegetation indices such as the Normalized Difference Vegetation Index (NDVI). Results are discussed bearing in mind the usefulness of the diverse tools, based on different resolution data (Sentinel-2A and UAV), for improving the understanding of the impacts of irrigation practices on crop yield and main challenges of rice production and water management in the Lis Valley irrigation district.</p>


2015 ◽  
Vol 7 (1) ◽  
pp. 39-51 ◽  
Author(s):  
Ali Fares ◽  
Ripendra Awal ◽  
Samira Fares ◽  
Alton B. Johnson ◽  
Hector Valenzuela

The impact of potential future climate change scenarios on the irrigation water requirements (IRRs) of two major agricultural crops (coffee and seed corn) in Hawai'i was studied using the Irrigation Management System (IManSys) model. In addition to IRRs calculations, IManSys calculates runoff, deep percolation, canopy interception, and effective rainfall based on plant growth parameters, site specific soil hydrological properties, irrigation system efficiency, and long-term daily weather data. Irrigation water requirements of two crops were simulated using historical climate data and different levels of atmospheric CO2 (330, 550, 710 and 970 ppm), temperature (+1.1 and +6.4 °C) and precipitation (±5, ±10 and ±20%) chosen based on the Intergovernmental Panel on Climate Change (IPCC) AR4 projections under reference, B1, A1B1 and A1F1 emission scenarios. IRRs decreased as CO2 emission increased. The average percentage decrease in IRRs for seed corn is higher than that of coffee. However, runoff, rain canopy interception, and deep percolation below the root zone increased as precipitation increased. Canopy interception and drainage increased with increased CO2 emission. Evapotranspiration responded positively to air temperature rise, and as a result, IRRs increased as well. Further studies using crop models will predict crop yield responses to these different irrigation scenarios.


2014 ◽  
Vol 11 (1) ◽  
pp. 91-107 ◽  
Author(s):  
F. Cui ◽  
X. Zheng ◽  
C. Liu ◽  
K. Wang ◽  
Z. Zhou ◽  
...  

Abstract. Contemporary agriculture is shifting from a single-goal to a multi-goal strategy, which in turn requires choosing best management practice (BMP) based on an assessment of the biogeochemical effects of management alternatives. The bottleneck is the capacity of predicting the simultaneous effects of different management practice scenarios on multiple goals and choosing BMP among scenarios. The denitrification–decomposition (DNDC) model may provide an opportunity to solve this problem. We validated the DNDC model (version 95) using the observations of soil moisture and temperature, crop yields, aboveground biomass and fluxes of net ecosystem exchange of carbon dioxide, methane, nitrous oxide (N2O), nitric oxide (NO) and ammonia (NH3) from a wheat–maize cropping site in northern China. The model performed well for these variables. Then we used this model to simulate the effects of management practices on the goal variables of crop yields, NO emission, nitrate leaching, NH3 volatilization and net emission of greenhouse gases in the ecosystem (NEGE). Results showed that no-till and straw-incorporated practices had beneficial effects on crop yields and NEGE. Use of nitrification inhibitors decreased nitrate leaching and N2O and NO emissions, but they significantly increased NH3 volatilization. Irrigation based on crop demand significantly increased crop yield and decreased nitrate leaching and NH3 volatilization. Crop yields were hardly decreased if nitrogen dose was reduced by 15% or irrigation water amount was reduced by 25%. Two methods were used to identify BMP and resulted in the same BMP, which adopted the current crop cultivar, field operation schedules and full straw incorporation and applied nitrogen and irrigation water at 15 and 25% lower rates, respectively, than the current use. Our study indicates that the DNDC model can be used as a tool to assess biogeochemical effects of management alternatives and identify BMP.


2015 ◽  
Vol 19 (7) ◽  
pp. 3073-3091 ◽  
Author(s):  
J. Jägermeyr ◽  
D. Gerten ◽  
J. Heinke ◽  
S. Schaphoff ◽  
M. Kummu ◽  
...  

Abstract. Global agricultural production is heavily sustained by irrigation, but irrigation system efficiencies are often surprisingly low. However, our knowledge of irrigation efficiencies is mostly confined to rough indicative estimates for countries or regions that do not account for spatiotemporal heterogeneity due to climate and other biophysical dependencies. To allow for refined estimates of global agricultural water use, and of water saving and water productivity potentials constrained by biophysical processes and also non-trivial downstream effects, we incorporated a process-based representation of the three major irrigation systems (surface, sprinkler, and drip) into a bio- and agrosphere model, LPJmL. Based on this enhanced model we provide a gridded world map of irrigation efficiencies that are calculated in direct linkage to differences in system types, crop types, climatic and hydrologic conditions, and overall crop management. We find pronounced regional patterns in beneficial irrigation efficiency (a refined irrigation efficiency indicator accounting for crop-productive water consumption only), due to differences in these features, with the lowest values (< 30 %) in south Asia and sub-Saharan Africa and the highest values (> 60 %) in Europe and North America. We arrive at an estimate of global irrigation water withdrawal of 2469 km3 (2004–2009 average); irrigation water consumption is calculated to be 1257 km3, of which 608 km3 are non-beneficially consumed, i.e., lost through evaporation, interception, and conveyance. Replacing surface systems by sprinkler or drip systems could, on average across the world's river basins, reduce the non-beneficial consumption at river basin level by 54 and 76 %, respectively, while maintaining the current level of crop yields. Accordingly, crop water productivity would increase by 9 and 15 %, respectively, and by much more in specific regions such as in the Indus basin. This study significantly advances the global quantification of irrigation systems while providing a framework for assessing potential future transitions in these systems. In this paper, presented opportunities associated with irrigation improvements are significant and suggest that they should be considered an important means on the way to sustainable food security.


2007 ◽  
Vol 7 (3) ◽  
pp. 149-159 ◽  
Author(s):  
J. A. Rodríguez Díaz ◽  
E. K. Weatherhead ◽  
J. W. Knox ◽  
E. Camacho

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