GEOG 2043 ENVIRONMENTAL FIELD TECHNIQUES LAB 9 SOIL MOISTURE 2: USING A t-TEST TO COMPARE MEANS

OBJECTIVES:

• To compare soil moisture at different positions on a hillslope
• To compare the soil moisture on north- and south-facing slopes, and to look at relative effects of solar radiation and tree cover on soil moisture.

BACKGROUND:  Soil moisture varies with time, depending on the seasonal patterns of precipitation, temperature and evapotranspiration.  Soil moisture also varies from place to place, depending on soil type, topographic position, aspect, and tree cover.  Understanding these variations is critical for estimating the volume of excess runoff during storm events, and for determining changes in plant-available water.  Movement of water through soils also governs important biogeochemical processes, such as nutrient cycling, and in certain situations, plays a role in hazard mitigation, as soil moisture content will control the speed at which a contaminant will seep into the ground.

Water that infiltrates into a soil is held there by capillary tension and molecular forces.  Capillary water is held loosely in the pore spaces between soil particles, and it is readily available to plants in the first few days after a precipitation event.  As time goes on, however, this water is removed, leaving only thin films of water around individual grains.  This water is held so tightly to the grains that plants cannot extract it, thus we say that the soil is at the wilting point.

There are numerous ways to measure soil moisture, and the technique you choose will depend on the question you are asking, and on the equipment available.  Some techniques, like time-domain reflectometry (TDR), allow for in situ soil-moisture measurements and are relatively fast, while others, like gravimetric techniques, are more time consuming and destructive, requiring the removal of soil samples for analysis.  In this lab you will use a gravimetric technique to determine spatial variations in soil moisture along a transect from the ridge crest to the bottom of the hillslope.  Since soil and vegetation characteristics affect soil moisture, it is important that you note these differences in the field.
 

ASSIGNMENT:  We will provide you with a spreadsheet listing the wet and dry weights of each sample, plus the depth of each sample.

1.  The first task is to plot a profile of each hillslope. To do this you must first calculate the horizontal distance between each sampling location.  This distance can be determined with the pythagorean theorem, knowing the vertical difference measured with the hand level (eye height) and the slope distance measured with the tape(8 or 10 meters, depending on which group was taking the measurements).  Plotting the cumulative values of horizontal distance and vertical difference give a plot of each hillslope.  Make sure to label each axis and put the correct units on the graph (meters). The title for each graph should be entitled by the aspect of the slope (north/south). Determine from these graphs the average slope, S, for each hillslope. Recall that SLOPE = RISE / RUN, multiplied by 100%.

2. The second task is to determine the soil moisture content for each sampling location.  The moisture content, in percent, is

where Wm is the moist weight of the soil, and Wd is the dry weight.  The dry bulk density of the soil, rs, is the the dry weight divided by the volume.  The volume of soil extracted from each location is determined knowing the depth of the sample, h, and the radius of the corer (r =1 cm).  The formula for volume is thus: V = rho*r^2*h.
 

TASKS

1. Calculate the coordinates (horizontal and vertical change) for each sampling point and graph a transect for each slope. Calculate the average slope for each hillslope.
 
2. Calculate the gravimetric soil moisture content, and the bulk density for each sampling location.

3. Evaluate the hypothesis that there is no significant difference in soil moisture on north- and east-facing hillslopes, Ho: u1 = u2.  Use a t-test with a significance level a = 0.05.  The test statistic is given by the following equation

where X1 and X2 are the means of the two samples, n1 and n2 are the sample sizes, and sp is the square root of the pooled variance; this parameter is defined as:

where s^2 is the estimated variance of each set of measurements.  Note there are n1 + n2 - 2 degrees of freedom.

The steps involved in evaluating the null hypothesis are as follows:

• Calculate the pooled variance using equation (2);

• Calculate the value of the test statistic using equation (1);

• Consult a table of t-values for the appropriate degrees of freedom, and the chosen significance level, a (for a two-tailed test with a = 0.05, we use the column corresponding to a/2 = 0.025).  If the absolute value of the calculated value of t is less than the tabulated value, then we cannot reject the null hypothesis.  In other words, we conclude that there is no significant difference in the mean values of soil moisture on the two hillslopes.  If the calculated value of t is more than the tabulated value, then we reject the null hypothesis, and conclude that the mean values of soil moisture on the two hillslopes are different (at the 5% level of significance).

4. Provide a table summarizing the data a t-test results, and then discuss your findings in several paragraphs.  Explain why the two slopes are the same or different.