Irrigation Patterns Resemble ERA‐Interim Reanalysis Soil Moisture Additions

Abstract

Irrigation modulates the water cycle by making water available for plants, increasing transpiration and atmospheric humidity, while decreasing temperatures due to the energy that is needed for evaporation. Irrigation is usually not included in atmospheric reanalysis systems, but moisture can be added to the soil due to data assimilation. This paper compares these soil moisture additions to the irrigation patterns. In the ERA‐interim atmospheric reanalysis, 2 m temperature observations are assimilated. A mismatch between modeled and observed temperatures is corrected by adding or removing moisture from the soil. These corrections show a clear pattern of mean soil moisture additions in many areas. To determine the cause of these increments, the spatial and temporal patterns of these soil moisture increments are compared to irrigation water demand and precipitation bias. In irrigated areas, the annual means and cycles of soil moisture increments correlate well with irrigation, and less with precipitation bias. Therefore, in irrigated areas, the soil moisture increments are more likely caused by irrigation than by the precipitation bias. In nonirrigated areas, a weak statistical relation between soil moisture increments and precipitation bias is present. Irrigation is currently not included in reanalysis systems. However, as irrigation indirectly influences the water balance in atmospheric reanalysis systems, we recommend to include this process in reanalysis models. Moreover, the influence of irrigation on the local and regional atmosphere should be taken into account when interpreting atmospheric data over strongly irrigated areas.

Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data

“…As outlined in Ozdogan et al (2006), ET and in turn irrigation water requirements can decrease within agricultural microclimates. However, nonlinear repercussions on temperature extremes can be expected when the required water supply cannot be met (Thiery et al, 2017) and (semi-)arid regions are generally expected to be adversely affected by water scarcity (Kueppers et al, 2007). As a consequence, especially in water-scarce regions, government agencies and water managers are challenged to increase water use efficiency, optimize the distribution of water among farms and detect illegal groundwater pumping activities (Siebert et al, 2010;Taylor et al, 2012).…”

“…To date, irrigation practices are typically not explicitly included in land surface, climate or weather models. On the other hand, irrigation directly impacts land surface temperature, humidity and soil moisture observations, and through them irrigation indirectly impacts model simulations when they are being assimilated (Tuinenburg and Vries, 2017). A range of climate modeling studies employed irrigation modules on a global scale.…”

Potential Added Value of Incorporating Human Water Use on the Simulation of Evapotranspiration and Precipitation in a Continental‐Scale Bedrock‐to‐Atmosphere Modeling System: A Validation Study Considering Observational Uncertainty

“…These include only diagnostic data sets, which are either interpolated in situ observations, merged observational data sets, and in case of ET, are based on the Penman‐Monteith equation or empirically derived formulations, such as the Priestley‐Taylor equation. We refrain from using modeled estimates, in which ET and P are estimated with the help of a land surface model and/or a reanalysis, because these do not consider HWU explicitly (e.g., irrigation; Tuinenburg & de Vries, ). The gridded observations comprise five P and three ET data sets, which have been used in previous studies (Greve et al, ; Martens et al, ; Müller et al, ).…”

“…Here the incorporation of uncertainties in land surface models also leads to an improved predictability of P (Orth et al, ) and extremes, such as the heat wave over Europe in 2003 (MacLeod et al, ). This in turn might indicate the lack of information and realism that current land surface models comprise (Davin et al, ; Miralles et al, ; Tuinenburg & de Vries, ). Here even observation‐based estimates of terrestrial ET exhibit relatively large uncertainties (Müller et al, , ; Sörensson & Ruscica, ; Trambauer et al, ).…”

Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data

“…To date, irrigation practices are typically not explicitly included in land surface, climate, or weather models. On the other hand, irrigation directly impacts land surface temperature, humidity, and soil moisture observations, and through them indirectly impact model simulations when they are being assimilated (Tuinenburg and Vries, 2017). In recent years, a range of climate modelling studies employed irrigation modules, which were mainly based on a combination of static) spatial maps of 2 Hydrol.…”