Paul McCall
Ex 4
Q1.
Correct.
Overall, the linear regression line fits the observed data well, but the coefficients of the regression line are determined dominantly by high flow data. As a result, this graph shows a systematic bias for low flow less than 50 mm/month. The bias can introduce serious errors in calculating monthly stream discharge of undisturbed WS17 during dry season.
2.5/3
Q2.
Yes, I think it is acceptable. The regression fit is nearly perfect for ’37-’39, which is reassuring. A problem comes from possible succession of species in the watersheds, especially over the number of years we are analyzing for. We are not taking into account how WS18 has changed, or how WS17 would have possibly changed if it really had been left undisturbed. Climate changemight also come into play as temperature and precipitation change may have changed a bit. Three years of data might not be long enough to see some sort of major events (wet or dry) that cause big changes in the difference of flow between the watersheds.
If natural disturbance such as hurricanes or insect infection influences the hydrologic response of one of the two watersheds after the clear-cutting, the derived regression relationship is no longer valid. In fact, the hemlock trees of WS18 were seriously infected by the introduction of hemlock woolly adelgid (Adelges tsugae), an exotic invasive insect, in 2002 (
1.5/2
Q3.
What a nice zero line! 3/3
Q4.
The clear cutting in 1940 causes a sharp increase of stream flow from the watershed.
-200 mm per year in 1941-1954 because the clear-cutting eliminated the evaporation from intercepted rainfall, and reduced transpiration rate from vegetation. In addition, well-developed macropore structure of forested watershed, which increases infiltration rate, if not significantly.
It took about twenty years for the stream flow numbers to stabilize after the pine planting in 1955. During the twenty years, Q dropped consistently nearly every year. The stabilization point of the pine forest has about 200-300 less Q(mm) per year coming out of the watershed. The change in Q during the transition period is due to the maturation of the newly planted pine forest – as they grew they caused increased rates of evapotranspiration.
3/4
Q5.
The evapotranspiration of a mature pine forest is higher than a mature oak forest. This is clearly shown by the graph above – WS17est is with oak cover, and WS17Q is the actual plot of Q – the mature pine forest (1975 and on) has about 250 less Q(mm) per year, which is a substantial amount considering yearly Q numbers are in the 1000 Q(mm) range.
Coniferous forests have higher evapotranspiration rates than deciduous forests. Their needle structure allows more surface area to allow greater transpiration (more stoma?), and higher interception/evaporation. Also, coniferous trees keep their needles all year, while deciduous trees drop their leaves for about half of the year, so coniferous forests have a lot more transpiration in the winter than deciduous forests.
3/3
Q6.
Correct.
There is a pronounced decrease of actual Q from December though June. This is the period where deciduous trees have no leaves, so very little transpiration is occurring in hardwood stands, while coniferous stands still have high transpiration because they do not drop their needles.
In April and May, the deciduous are just leafing out. At this time, stronger solar radiation increases ET, which makes the difference larger.
3.5/4
Total:
16.5/19= / 8.7Late: -2
Final: 6.7