Alluvial soil with a depth of (1.3mm) weighs (2.9) and its dry weight (2.5N). Knowing that the field capacity of the soil (35 kg), its wilting point (10 kg), bulk density As (14). Find 1- Total available water (mm) 2- The actual depth of water to be added as irrigation water depth (mm).

Repeat Problem 2.11 with the following data. 2.11 The grain-size characteristics of a soil are given in the following table. a. Draw the grain-size distribution curve. b. Determine the percentages of gravel, sand, silt, and clay according to the MIT system. c. Repeat Part b using the USDA system. d. Repeat Part b using the AASHTO system.

Since laboratory or field experiments are generally expensive and time consuming, geotechnical engineers often have to rely on empirical relationships to predict design parameters. Section 6.6 presents such relationships for predicting optimum moisture content and maximum dry unit weight. Let us use some of these equations and compare our results with known experimental data. The following table presents the results from laboratory compaction tests conducted on a wide range of fine-grained soils using various compactive efforts (E). Based on the soil data given in the table, determine the optimum moisture content and maximum dry unit weight using the empirical relationships presented in Section 6.6. a. Use the Osman et al. (2008) method [Eqs. (6.15) through (6.18)]. b. Use the Gurtug and Sridharan (2004) method [Eqs. (6.13) and (6.14)]. c. Use the Matteo et al. (2009) method [Eqs. (6.19) and (6.20)]. d. Plot the calculated wopt against the experimental wopt, and the calculated d(max) with the experimental d(max). Draw a 45 line of equality on each plot. e. Comment on the predictive capabilities of various methods. What can you say about the inherent nature of empirical models?