Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM

Abstract

Water is the major factor limiting crop production in western Kansas due to declining groundwater levels in the Ogallala aquifer resulting from withdrawals for irrigation exceeding recharge rates coupled with erratic semi-arid rainfall. Study objectives were to assess yield and water productivity of water limited cropping systems in western Kansas using DSSAT-CSM (Decision Support System for Agrotechnology Transfer Cropping Systems Model). The cropping systems evaluated included continuous (corn, wheat, and grain sorghum) and rotation (cornwheat, corn-wheat-grain sorghum, and corn-wheat-grain sorghum-corn). Results showed that the model adequately reproduced measured days to flowering and maturity as well as yield and aboveground biomass of all three crops. Crop rotation improved water productivity of corn. Under deficit irrigation, corn in rotation produced higher yields, crop water productivity, and irrigation water use efficiency compared to continuous corn, implying that crop rotation is a better option under limited well capacities. Under full irrigation, yield and water productivity of continuous wheat were lower than wheat in rotation. In contrast, continuous wheat yields under deficit irrigation were better than under crop rotation. Deficit irrigation substantially improved irrigation water use efficiency of grain sorghum under both continuous and crop rotations. Long-term average grain sorghum yields under rotation were higher than those of continuous grain sorghum. Indicating grain sorghum should be grown in rotation under deficit irrigation. This research did not simulate the impacts of pests, weeds and diseases, hail and freeze damage on crop yield. However, the study identifies cropping systems that are more likely to produce highest water productivity under semi-arid climate similar to that in western Kansas.

Impact of cover crop on corn–soybean productivity and soil water dynamics under different seasonal rainfall patterns

“…To meet needs of a growing world population in the face of increasing climate variability, agricultural systems will be required to be more efficient in water use (Dietzel et al., 2016; Jin et al., 2017; Kang et al., 2017). There is a need to promote efficient use of water for ensuring food security in the 21st century under increased climate variability (Araya, Kisekka, Gowda, & Prasad, 2017; Kunkel et al., 2013; Wallace, 2000). The southeastern United States is one of the nation's leading commodity crop planting regions due to its intensive crop production systems (Feng, Ouyang, Adeli, Read, & Jenkins, 2018; Yang et al., 2019a).…”

Yield and Water Productivity of Winter Wheat under Various Irrigation Capacities

“…Other studies also indicated that winter wheat is relatively less sensitive to water stress and less water consumptive when compared to corn (Colaizzi et al 2006;Araya et al 2017a). For example, there was on an average 40% and 35% increase in grain and BM yield, respectively, by applying 190 mm irrigation under IC 5 mm/day strategy when compared to the dryland wheat.…”

“…Increased nitrogen fertilizer increased yield and BM of winter wheat when grown with irrigation. Other studies also indicated that winter wheat is relatively less sensitive to water stress and less water consumptive when compared to corn (Colaizzi et al 2006;Araya et al 2017a). For this reason, in some waterlimited areas, growing wheat and grain sorghum may contribute to water saving (Araya et al 2017a).…”

“…Other studies also indicated that winter wheat is relatively less sensitive to water stress and less water consumptive when compared to corn (Colaizzi et al 2006;Araya et al 2017a). For this reason, in some waterlimited areas, growing wheat and grain sorghum may contribute to water saving (Araya et al 2017a). For example, Zhang and Oweis (1999) reported savings of >60% of irrigation water for a yield loss of <35% by…”

Coupling Hyperspectral Remote Sensing Data with a Crop Model to Study Winter Wheat Water Demand

“…Crop model simulation is a widely used method to indirectly obtain crop growth status variables (e.g., leaf area index, biomass, and evapotranspiration (ET)) [5]. Many crop models, such as DSSAT-CSM, EPIC, APSIM, WOFOST and STICS etc., have been developed and refined to successfully simulate wheat growth and production under different soil moisture, fertility and salinity conditions [6][7][8][9][10]. Determination of model parameters, initial conditions and driving variables (meteorological data, soil properties, field management etc.)…”