https://pc-progress.com/documents/jirka/kandelous_simunek_awm_2010.pdf

Numerical simulations of water movement in a subsurface drip irrigation system under field and laboratory conditions using HYDRUS-2D

Due to increasing competition for water resources by urban, industrial, and agricultural users, the proportion of agricultural water use is gradually decreasing. To maintain or increase agricultural production, new irrigation systems, such as surface or subsurface drip irrigation systems, will need to provide higher water use efficiency than those traditionally used. Several models have been developed to predict the dimensions of wetting patterns, which are important to design optimal drip irrigation system, using variables such as the emitter discharge, the volume of applied water, and the soil hydraulic properties. In this work, we evaluated the accuracy of several approaches used to estimate wetting zone dimensions by comparing their predictions with field and laboratory data, including the numerical HYDRUS-2D model, the analytical WetUp software, and selected empirical models. The soil hydraulic parameters for the HYDRUS-2D simulations were estimated using either Rosetta for the laboratory experiments and inverse analysis for the field experiments. The mean absolute error (MAE) was used to compare the model predictions and observations of wetting zone dimensions. MAE for different experiments and directions varied from 0.87 to 10.43 cm for HYDRUS-2D, from 1 to 58.1 cm for WetUp, and from 1.34 to 12.24 cm for other empirical models.

https://link.springer.com/content/pdf/10.1007%2Fs00271-009-0205-9.pdf

Comparison of numerical, analytical, and empirical models to estimate wetting patterns for surface and subsurface drip irrigation.

Measured and simulated soil wetting patterns under porous clay pipe sub-surface irrigation.

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.

/pdf/soil-water-content-distributions-between-two-emitters-of-a-4vwugypk3i.pdf

Soil Water Content Distributions between Two Emitters of a Subsurface Drip Irrigation System

Dynamics and modeling of soil water under subsurface drip irrigated onion

Simulation of soil wetting pattern with subsurface drip irrigation from line source

Subsurface drip irrigation (SDI) is application of water below soil surface through the emitters, with discharge rates generally in the same range as surface drip irrigation. Performance of SDI with respect to uniformity of water and chemical application in a crop is an essential component for efficient management of SDI. A study was conducted to evaluate performance of SDI used for irrigating okra crop during 2003 and 2004. The parameters evaluated were pressure -discharge relationship of emitters, and uniformity of water application including discharge variation, coefficient of variation, uniformity coefficient, statistical uniformity, and distribution uniformity. The emitter discharge exponent was found to be 0.56 for inbuilt labyrinth type emitters used in SDI The maximum values of standard deviation, variation and coefficient of variation of emitter flow rates were found to be 0.057, 0.08 and 0.025, respectively. Analysis revealed that statistical uniformity, distribution uniformity and uniformity coefficient were more than 90% during two years of study. Based on these parameters, performance of SDI was found excellent during study period.

Performance of Subsurface Drip Irrigation System with Line Source of Water Application in Okra Field

A method and apparatus for reconditioning waste solutions of the nuclear industry which contain ammonium nitrate. The waste solution is continuously sprayed from above into a 300 DEG to 600 DEG C. hot zone, from the lower end of which the decomposition products are withdrawn and are separated into condensate and exhaust gas. The NO content is reduced by adding oxygen, especially at the exit of the decomposition zone. By the presence of reducing agents, such as CO(NH2)2 or preferably NH3, in the solution to be sprayed, the NO2 content of the decomposition products and the NH4NO3 residue in the condensate can be practically eliminated and an additional precipitation in the condensate which can be filtered off can be obtained. Optimal contents are 0.25-0.4 Mol NH3 and 0.15-0.25 Mol CO(NH2)2 per Mol NH4NO3. Prior to the thermal decomposition, the waste solution is preferably concentrated, cooled off, and filtered to about 60% or (if a solution containing reducing agents is to be sprayed) about 48% NH4NO3 at about 60 DEG C. in a thin layer evaporator, and is temporarily stored at room temperature. The addition of ammonia to the concentrate offers a precipitation which can be filtered off.

H. S. Sikarwar

Papers

Simulation of soil wetting pattern with subsurface drip irrigation from line source

Performance of Subsurface Drip Irrigation System with Line Source of Water Application in Okra Field

Knowledge Engineering for an Expert System on Wheat Crop Management.