FY 2017 Performance Metrics

Extend the capabilities of the DOE’s Advanced Climate Model for Energy (ACME) to simulate and evaluate human-natural interdependencies for the carbon and water cycles.



Implement and evaluate the impacts of irrigation on the hydrologic cycle in the ACME model

Product Definition

Globally, around 70% and 90% of freshwater withdrawals and consumptions are used for irrigation purposes, respectively [Döll, 2009]. The large-scale water withdrawals from rivers, lakes, reservoirs, and aquifers have directly and substantially altered the terrestrial water and energy cycles [Haddeland et al., 2006; Kustu et al., 2010; Wada et al., 2010; Famiglietti et al., 2011; Leng et al., 2014; Pohkrel et al., 2015]. Irrigation impacts are expected to increase with growing world population and food demand, while production of bioenergy crops may further exacerbate irrigation water demands. Hence understanding the role of irrigation in human-Earth system interactions is important for adaptive planning of water, land, and energy use. During the last two decades, noteworthy progress has been made to represent irrigation in global hydrological models for assessing water resource availability and use, but there have been limited efforts in modeling irrigation in global land surface models and Earth system models (ESMs). From a modeling perspective, estimation of irrigation amount and choices of irrigation water sources and methods are key aspects in parameterizing irrigation water use and modeling its impacts. The most under-represented aspect of irrigation modeling is the irrigation method that determines how the extracted water is applied to the irrigated areas. Given the various approaches used to model irrigation, considerable discrepancy exists in simulating irrigation effects, especially at local/regional scales. To reduce such uncertainty, an interactive irrigation scheme has been developed and incorporated into the Accelerated Climate Modeling for Energy (ACME) Land Model (ALM) with consideration of the irrigation water sources (i.e., surface water and groundwater) and methods (i.e., drip, sprinkler and flood irrigation). The model has been used to investigate how the simulated irrigation effects are influenced by the water sources and methods for irrigation. By designing different irrigation scenarios, the pathways through which irrigation affects land surface water balance and how differences in irrigation water sources and methods affect irrigation water use efficiency are studied using numerical experiments. A set of numerical experiments with the new irrigation scheme in ALM showed that both different water sources (e.g., groundwater versus surface water) and methods of irrigation (e.g., sprinkler, flood, or drip) could lead to large differences in simulating the hydrological impacts of irrigation, suggesting that modeling of irrigation must consider those two factors to reduce uncertainty.

Product Documentation

The Accelerated Climate Modeling for Energy (ACME) is an ESM developed by the U.S. Department of Energy (DOE). To represent irrigation in the ACME Land Model (ALM), a groundwater pumping module has been added following Leng et al., 2014 so that the estimated irrigation water demand can be met by withdrawing water from surface water storage (i.e., accumulated total runoff) and/or groundwater. The fraction of surface water withdrawal to the total water withdrawal is constrained by a global data set. The water table depth is updated after water is extracted for irrigation. In addition to the direct impacts on groundwater resources, changes in water table depth lead to subsequent changes in the subsurface drainage and recharge from the bottom soil layer to the aquifer, thus indirectly influencing soil water content through soil-aquifer interactions.
After the irrigation water is extracted, it can be applied to the irrigated areas using three distinct irrigation methods, i.e., drip, sprinkler, and flood irrigation. In practice, drip irrigation applies water directly to the root zone to reduce the wetted area, so it features the highest water use efficiency. Sprinkler irrigation is less efficient because a large fraction of the water is sprayed into the air, which can result in wind drift and evaporation losses. In flood irrigation, less water is lost to evaporation than in sprinkler irrigation, but more water can be lost as runoff in the fields. The irrigation methods are parameterized mainly following the guidance of reflecting the distinct water use efficiencies among the three methods. For sprinkler irrigation, water is added directly to the canopy as precipitation. In drip irrigation, water is applied directly and slowly to the soil layers in the root zone to facilitate plant water use. In flood irrigation, water is poured directly and quickly to the ground surface in a period of 30 min. as precipitation falling on the ground surface, bypassing the canopy. The approach implemented in ALM can reflect the distinct irrigation water use efficiencies among the three irrigation methods, which is important for evaluating water use and hydrologic impacts driven by irrigation.

A series of sensitivity experiments were performed with ALM at 1-degree resolution driven by observed atmospheric forcing [Qian et al., 2006]. After cycling the atmospheric forcing for model spin-up, results for 1971-2005 were compared to contrast simulations with different irrigation water sources (surface water only, surface water and groundwater) and different irrigation methods (sprinkler with irrigation water applied to the canopy versus directly to the ground, flood, and drip) with water sources from both surface and groundwater. The impacts of water sources and irrigation methods were evaluated by comparing the effects of irrigation on water fluxes (e.g., evapotranspiration and runoff), soil moisture, groundwater table depth, and irrigation water use efficiency.