Precipitation Single strongest variable driving hydrologic processes Formed water vapor in the atmosphere As air cools its ability to ‘hold’ water decreases and some turns to liquid or ice

Hydrologic Cycle http://www.ec.gc.ca/Water/en/nature/prop/e_cycle.htm

Causes of Precipitation

U.S. Annual Precipitation Figure 2.6 Have students explain differences in precip due to air masses Rainfall type

U.S. Annual Precipitation Figure 2.6 Have students explain differences in precip due to air masses Rainfall type

Illinois. Annual Precipitation Average annual precipitation pattern for Illinois with average monthly amounts (inches) for selected weather stations, 1901-1980 http://www.sws.uiuc.edu/wsp/climate/ClimateToday_precipmap1.asp

Forms of Precipitation Rain - Rain is liquid precipitation that reaches the surface in the form of drops that are greater than 0.5 millimeters in diameter Drizzle - Drizzle is liquid precipitation that reaches the surface in the form of drops that are less than 0.5 millimeters in diameter. Snow - Snow is an aggregate of ice crystals that form into flakes.

Forms of Precipitation Hail - Hail is dense precipitation ice that is that least 5 millimeters in diameter. Graupel - Graupel forms in the same way as hail except the diameter is less than 5 millimeters. Freezing Fog - Freezing fog is a fog composed of supercooled water drops that freeze just after they wet the earth's surface

Illinois Annual Snowfall Average annual snowfall pattern for Illinois with average monthly amounts (inches) for selected weather stations. http://www.sws.uiuc.edu/wsp/climate/ClimateToday_precipmap2.asp

Snow Measurement Determine the water equivalent 5%-60% of snow depth may be water equivalent-- “density” Snow pillows use antifreeze solution and pressure measurement to measure water equivalent

Location of Gages Gauges measure point rainfall True precipitation unaffected by surroundings-winds, trees, buildings Clearance distance 2 times height of object For large areas multiple gauges are needed for more accurate estimates

Placement of Rain Gauges Gauges are affected by wind pattern, eddies, trees and the gauge itself, therefore it is important to have the gauge located and positioned properly. 1m above ground level is standard - all gauges in a catchment should be the same height 2 to 4 times the distance away from an isolated object (such as a tree or building) or in a forest a clearing with the radius at least the tree height or place the gauge at canopy level

Placement of Rain Gauges shielded to protect gauge in windy sites or if obstructions are numerous they will reduce the wind-speed, turbulence and eddies.

Placement of Rain Gauges For sloping ground the gauge should be placed with the opening parallel to the ground The rainfall catch volume is then divided by the opening area that the rain can enter

Number of Gauges Depends on Storm type Frontal storms (large areas, low intensities) -small number of gauges may be O.K. Convective storms (local, intense, uneven distribution) -denser network needed. Convective storms may have seasonal dominance -need to consider this as well. Orographic rainfall due to mountains (not fronts) -may need denser network than flatter area.

Methods of Measuring Rainfall: Manual Often have a funnel opening into a cylinder gauge. Come in a variety of shapes and sizes Calculate the rainfall ( inches) by dividing the volume of water collected by the area of the opening of the cup. (The gauge marking often accounts for this).

Methods of Measuring Rainfall: Remote Tipping bucket rain gauge -The bucket tips when precipitation of 0.2 mm, 0.5 mm, 1.0 mm has been collected. Each tip is recorded by a data logger. Weather Station - Records rainfall, but also evaporation, air pressure, air temperature, wind speed and wind direction (so can be used to estimate evapo-transpiration) Radar - Ground-based radar equipment can be used to determine how much rain is falling and where it is the heaviest.

Weather Station

Methods of averaging rainfall data Arithmetic average Theissen polygons Isohyetal method Although, most of these calculations are done with computer mapping programs, it is still useful to understand these methods.

Isoheyetal method for Mapping Rainfall The most basic method of representing the spatial distribution. This is generally the most accurate method but is also the most laborious. Locate all rainfall stations on a base map and record the rainfall amount. Draw isohyets (lines of equal rainfall) by proportioning the distances between adjacent gauges according to differences in catch.

Thiessen Method for Average Rain Step 1 Figure 2.15

Thiessen Method for Average Rain Step 2 Figure 2.15

Thiessen Method for Average Rain Figure 2.15 Step 3

Thiessen Method for Average Rain Step 4 Figure 2.15 After summing areas and rainfall Thiessen predicts 2.08 inches, and the mean is 1.97 inches. This is because the heavier rainfall amounts in center of study area get more carry more area and weight in the calculation.

Interpolating Rainfall Data Nearest neighbor Inverse distance weighted method Kriging

INTERPOLATION Procedure to predict values of attributes at unsampled points within the region sampled Why? Examples: Can not measure all locations: - temperature Time - acid rain deposition Money - soil characteristics Impossible (physically, legally) - mining: gold deposits - Changing cell size - Missing/unsuitable data - Past date (e.g. temperature) http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Many different methods All methods use location and value at sampling locations to estimate the variable of interest at unmeasured locations Methods differ in weighting and number of observations used Each method produces different results (even with same data) No method best for every application Accuracy is often judged by withheld sample points (difference between the measured and interpolated values) http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Thiessen Polygon Assigns interpolated value equal to the value found at the nearest sample location Conceptually simplest method Only one point used (nearest) Often called nearest sample or nearest neighbor http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

Thiessen Polygon Start: 1) 2) 3) Draw lines connecting the points to their nearest neighbors. Find the bisectors of each line. Connect the bisectors of the lines and assign the resulting polygon the value of the center point 1 2 3 5 4 http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

Sampled locations and values Thiessen polygons http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Thiessen Polygon Advantage: - Ease of application - Appropriate for discrete (i.e., categorical) variables Disadvantages: - Accuracy depends largely on sampling density - Boundaries often odd shaped at transitions - Continuous variables often not well represented http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Inverse Distance Weighted (IDW) Estimates the values at unknown points using the distance and values to nearby know points (IDW reduces the contribution of a known point to the interpolated value) Weight of each sample point is an inverse proportion to the distance. The further away the point, the less the weight in helping define the unsampled location http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Inverse Distance Weighted (IDW) Zi is value of known point Dij is distance to known point Zj is the unknown point n is a user selected exponent (often 1,2 or 3) Any number of points may be used up to all points in the sample; typically 3 or more http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Inverse Distance Weighted (IDW) http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Inverse Distance Weighted (IDW) Factors affecting interpolated surface: Size of exponent, n affects the shape of the surface (larger n means the closer points are more influential) A larger number of sample points results in a smoother surface http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Inverse Distance Weighted (IDW) http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt

INTERPOLATION Inverse Distance Weighted (IDW) http://gisci.isu.edu/classes/504/Lectures/bolstad_interpolation.ppt