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Food supply is affected by a complex nexus of land, atmosphere, and human processes, including short- and long-term stressors (e.g., drought and climate change, respectively). A simulation platform that captures these complex elements can be used to inform policy and best management practices to promote sustainable agriculture. We have developed a tightly-coupled framework using the macroscale Variable Infiltration Capacity (VIC) hydrologic model and the CropSyst agricultural model. A mechanistic irrigation module has been developed for inclusion in this framework. The performance of VIC-CropSyst was evaluated using two flux tower sites located in agricultural fields in the U.S. (Nebraska and Illinois). The agreement between recorded and simulated evapotranspiration (ET), applied irrigation water, soil moisture, leaf area index (LAI), and yield indicated that, although the model is intended to work at regional scales, it also captures field scale processes in agricultural areas. We also evaluated the regional simulations of VIC-CropSyst's ET over the Washington, Idaho and Oregon in the U.S. VIC-CropSyst is being used in conjunction with socio-economic models, river system models and atmospheric models to simulate the feedback processes between regional water availability, agricultural water management decisions and land-atmospheric interactions. [ABSTRACT FROM AUTHOR]

Reliable information about the wetted dimensions of soil under drip irrigation helps designers to determine optimal emitter flow rates and spacings to reduce system equipment costs and provide better soil water conditions for the most efficient and effective use of water. This study presents a new empirical formula that predicts soil wetted dimensions around a drip emitter. The coefficients were obtained by using regression analysis on the results of field experiments done on the Pardis Agricultural Farm of Tehran University in Karaj, Iran. These data were also used to evaluate the semiempirical model of Zur and Schwartzman, the empirical model of Amin and Ekhmaj, and the analytical model WetUp. Statistical comparisons (mean error, root mean square error, and model efficiency) are made of the simulated data with the observed data. To evaluate the models, published experimental data by Risse et al. and Li et al. were also used. The results demonstrate that the suggested equations can be used for a wide range of discharge rates and soil types. The best result was obtained from the new empirical model proposed in this investigation. The lowest mean error for the wetted radius and wetted depth was 8.21 and 8.62 cm, respectively. [ABSTRACT FROM AUTHOR]

Soil thermal conductivity is an important property of soil that has various applications in simulation of land-surface water and energy processes, and geothermal energy calculations. In this study we conduct laboratory experiments to evaluate the impacts of various soil properties on soil thermal conductivity. The experiments included three soil types (i.e., sand, sandy loam, silt loam), four soil salinity levels, and a wide range of soil water content. To find the most effective factors we utilized different statistical methods (i.e., linear regression, information theoretic sensitivity index, Pearson's correlation coefficient, and random forest). Moreover, we developed and tested three soil thermal conductivity models (i.e., linear regression, random forest and quadratic equations). The results show that soil water content has the highest level of influence on thermal conductivity. Also, the quadratic relationship between thermal conductivity and independent variables provide the most accurate predictions among the models evaluated in this study. [ABSTRACT FROM AUTHOR]

Subsurface drip irrigation (SDI) systems are increasingly being used in agriculture in attempts to use the available water more efficiently. The proper design and management of SDI systems requires knowledge of precise distribution of water around emitters. We conducted both field and numerical experiments to evaluate the soil water content distributions between two neighboring emitters when their wetting patterns started to overlap. The experiments involved SDI systems with emitters installed at different depths and with different spacings along the drip lateral. The HYDRUS software package was used to analyze the field data, assuming modeling approaches in which emitters were represented as (i) a point source in an axisymmetrical two-dimensional domain, (ii) a line source in a planar two-dimensional domain, or (iii) a point source in a fully three-dimensional domain. Results indicated that SDI systems can be accurately described using an axisymmetrical two-dimensional model only before wetting patterns start to overlap, and a planar two-dimensional model only after full merging of the wetting fronts from neighboring emitters. A fully three-dimensional model appears to be required for describing subsurface drip irrigation processes in their entirety. [ABSTRACT FROM AUTHOR]