Alan D. Leung & Tyler A. Patel ENGR 180 - Spatial Analysis Final Report December 12, 2011
Table of Contents I. Abstract………………………………………………………………………… …...............2-3 II. Introduction……………………………………………………………………........................4 III. ExperimentalProcedure………………………………………...........................................5 IV. Results……………………………………………………………………………… ……….6-8 V. Spatial Analysis……………………………………………………………………………...8-9 VI. Conclusion……………………………………………………………………………………10 VII. Acknowledgements………………………………………………………………………… 11 VIII. References…………………………………………………………………………… 11
Leung and Patel 2
I. Abstract A summary of the purpose, general methods and significant conclusions. On November 5th and December 3rd, 2011 we conducted field sampling of Bear Creek, Merced, at originally four specific locations. Only three locations were revisited on the second sampling day due to certain conditions. The goal of this experiment is to analyze how dissolved oxygen, also known as oxygen saturation, varies down the creek. The two methods we used to accomplish this are statistical analysis and more importantly spatial analysis techniques with Google Maps and Earth and ArcGIS’s mapping tool.The field sampling method consisted of using a dissolved oxygen meter that was part of a field testing kit provided by Professor Mike Dunlap from the department of Science and Engineering at UC Merced. At the different sampling sites we expected to see varying levels of dissolved oxygen. Specifically, we expected higher levels of oxygen saturation in areas prior to agricultural areas. Around areas of agriculture where fertilizers are heavily used we expect the oxygen to decrease. In urban areas we expect the DO levels to decrease even more because of synthetic pollutants from residential, business, and industrial sectors run off into the creek. In our experiment, we found in our datapoint location that the area before agriculture started the level of oxygen in the water was about one DO level higher than our end point near the Merced Automall. During our first trial on November 5th, 2011, we observed the following values: At site (1) the reported DO level, the site before agriculture, to be 9.62 with a mean temperature of 13.33, site (3), middle of suburb area, reported 9.92 mean with a temperature of 12.10, and site (4), the automall, reported 8.01 mean with a temperature of 13. During our second trial on December 3rd, 2011, we observed the following values:
Leung and Patel 3 At site (1) the reported DO level, the site before agriculture, to be 9.70 with a mean temperature of 12.27, site (3), middle of suburb area, reported 9.95 mean with a temperature of 12.09, and site (4), the automall, reported 8.00 mean with a temperature of 12.89. Although this may not seem be a significant drop, the decrease of DO in water, despite it being one unit, seems to be consistent with our hypothesis that the DO in water would decrease as it makes its way from the initial point to the end location. There are many environmental factors that could influence the observed pattern such as possible run-off from the urban sewers and agricultural areas, temperature, vegetation, and weather identified with our spatial analysis tools.
Google Map 1: A simple map plotting the directions we took to get to our four sampling sites.
Leung and Patel 4
II: Introduction A brief background of principals and theories used and explanation of hypothesis. The measurement of dissolved oxygen in water is the single most important water quality factors that helps scientist and engineers determine the quality of the water body. Dissolved oxygen in water comes from two sources. The majority of the dissolved oxygen in the natural habitat comes from plants through the process of photosynthesis. The second major source of dissolved oxygen comes from atmosphere as oxygen gas diffuses easily into water. This sorption of oxygen is also encouraged waves, water falls, rapids and other water turbulent areas that mix the water and the atmospheric oxygen together . The presence of saturated oxygen in bodies of water is important to the sustainability of it’s given ecosystem. Like humans, marine activity requires a certain amount of dissolved oxygen in order to survive. Generally speaking, high values of dissolved oxygen is a good sign of a healthy water body (although too high could be problematic), but low levels of dissolved oxygen are signs of severe pollution. From the Scioto Soil and Water conservation District website, the water quality is categorized into three scales where less than 4mg/L is considered to be bad, 4-10 mg/L is considered to be good and 10mg/L+ is excellent. The decreased amounts of oxygen put a strain on the organisms that need it to survive and result decrease in the amount of life present in the water. The goal of this paper is to analyze the variability of dissolved oxygen in Bear Creek where Tyler Patel and I, Alan Leung will start from a location several miles away from the city limits of the city of Merced where we believe to be the beginning of the agricultural area and make our way to the end of Merced while measuring the temperature and dissolved oxygen of the water. We hypothesized that the dissolved oxygen in Bear Creak would be greater at areas before agriculture and gradually decrease as it makes its way from the agricultural area to the end of the city limits.
Leung and Patel 5
III: Experimental Procedure An overiew of methods implemented and measurements taken during the experiment. Part A: Field Sampling of Bear Creek The dissolved oxygen meter requires some preparation before sampling, which can be accompilished by following the instructions listed in the manual that came with the meter. After this the meter is ready for field sampling and one can just drop the probe into the water one wants to sample. Note that dissolved oxygen can vary due to many factors even at different locations within the same sampling site. For example areas with large aquatic plants will experience higher concentrations of dissolved oxygen due to photosynthesis. In addition, The data set obtained from the dissolved oxygen field kit may be unreliable because it is diffult to estimate the sampling error the devise my contain. We estimate our level of confidence will be in the tenth decimal place for each parameter measured. This assumption should suffice for our school project. We attempted to measure Nitrate levels for indications of fertilizer but our equipment was malfunctioning. Using a portable GPS (Global Positioning System) we obtained the latitude and longitude coordinates of each site we sampled. Part B: Spatial Analysis After our basic data set was obtained from field sampling we plotted the coordinates of each sampling site into ArcMap, a specific program of the ArcGIS suite created by the Economic and Social Research Institute (Esri) that specializes in Geographic Information System (GIS) software. Using different mapping techniques and program features we looked at different aspects of the environment around our sampling sites that may influence our data.
Leung and Patel 6
IV: Results Presentation and explanation of results obtained from field sampling.
Bear Creak Measurements on November 5th, 2011
Sample
Lattitude Longitude (Degrees, (Degrees, Decimal Decimal Brief Minutes N) Minutes W) Description Next to S Bear Creak Rd. before Farming begins
1 37.324269
-120.332225 Irrigation Canal on Kibby Road, Near major farming areas
2 37.312684
-120.41514 Bear Creek Park, In the middle of suburban area
3 37.310692
-120.471687
4 37.30705
-120.506182
Near the Merced Auto Mall, next to railroad track crossing
Dissolved Oxygen Temperature Concentration (C) Measurement 1 Measurement 2 Measurement 3 Mean Std Dev Measurement 1 Measurement 2 Measurement 3 Mean Std Dev Measurement 1 Measurement 2 Measurement 3 Mean Std Dev Measurement 1 Measurement 2
9.66 9.66 9.54 9.62 0.06 11.70 11.64 11.00 11.45 0.32 10.07 9.80 9.89 9.92 0.11 8.03 7.80
14.20 13.20 12.60 13.33 0.66 13.60 13.40 13.20 13.40 0.16 12.50 12.00 11.80 12.10 0.29 13.20 13.00
Measurement 3 Mean Std Dev
8.20 8.01 0.16
12.80 13.00 0.16
Time 3:00 PM
1:00 PM
4:30 PM
5:30 PM
Bear Creak Measurements on December, 3, 2011
Sample
Lattitude Longitude (Degrees, (Degrees, Decimal Decimal Brief Minutes N) Minutes W) Description Next to S Bear Creak Rd. before Farming begins
1 37.324269
-120.332225 Bear Creek Park, In the middle of suburban area
3 37.310692
-120.471687
4 37.30705
-120.506182
Near the Merced Auto Mall, next to railroad track crossing
Dissolved Oxygen Temperature Concentration (C) Measurement 1 Measurement 2 Measurement 3 Mean Std Dev Measurement 1 Measurement 2 Measurement 3 Mean Std Dev Measurement 1 Measurement 2 Measurement 3 Mean Std Dev
9.64 9.69 9.77 9.70 0.05 10.11 9.79 9.95 9.95 0.13 8.00 7.80 8.20 8.00 0.16
13.23 12.80 13.00 13.01 0.18 12.42 12.11 11.75 12.09 0.27 12.88 12.99 12.80 12.89 0.08
Time 1:00 PM
3:00 PM
5:02 PM
Leung and Patel 7
IV: Results (cont.) Sampling Site 1 Sampling site 1 was chosen because it is upstream from agriculture and isolated from a large amount of human activity. On both days of sampling we saw high levels of relative dissolved oxygen. We believe this is due to it's isolation such as the introduction of nitrate, phosphate and other synthetic pollutants. Sampling Site 2 Our second sampling site was a irrigation canal therefore we believe it is an outlier in our data set. This is why we did not included it in the second day of sampling. We wanted to test this area because of its location in agriculture and see how dissolved oxygen would change around areas that use lots of fertilizer such as nitrate and phosphate (ingredients for fertilzer). Our hypothesis for this situation is that we expected the dissolved oxygen to decrease because overfertilization which leads to overconsumption of dissolved oxygen due to higher concentrations of bacteria as algae decomposes.
Sampling Site 3
The third sampling site was located in the surburban area of the city of Merced and was located in a very green area filled with lots of diverse species of trees and plant life. The canopy created by the trees may decrease the amount of sunlight this particular area gets and effect our saturated oxygen content. This location was chosen to see how the dissolved oxygen changed from our agricultural site as it passed through more urban areas of the city.
Leung and Patel 8 Sampling Site 4
The fourth sampling site was located near the Merced Automall next to where the train tracks cross the creek. This area was chosen because we thought it would be representative of the quality of the Bear Creek water that leaves Merced. There were many obvious visual indications that the water was polluted including lots of trash and discoloration.
Water quality variable, dissolved oxygen, was measured twice at the same sites; we wrote down the GPS locations so that we could revist these locations. On November 5th, 2011, there was a decrease in dissolved oxygen of 1.61unit from the initial point to the endpoint. While December 3, 2011, there was a decrease in dissolved oxygen of 1.7 unit. We define the initial point as “Before Farming Begins” while the end point as “AutoMall” location.
V: Spatial Analysis
Arc Map 1
City County
Agriculture
Bear Creek Urban
Leung and Patel 9
V: Spatial Analysis Implementing other GIS research of Merced, CA
we find that the perimeter, provided depth
contours and estimated the total water volume in each lake near Bear Creek. The deepest section of Silver Lake, at approximately four meters, is in the southwestern section. For Lake Casey, the highest depth, at about 6.5 meters, is in the easternmost section. The spatial analysis revealed that the highest dissolved phosphorus levels in Silver Lake on 7/8/99 occurred in the southwestern section while the lowest were in the northeastern part. For Lake Casey, the highest observed levels of phosphorus varied greatly on the three dates when the most sites were sampled. From the results of the spatio-temporal analysis of the 71 space-time locations in Silver Lake with complete records, there is a strong positive relationship between surface temperature and dissolved phosphorus. Also, there is a significant negative relationship between dissolved oxygen and dissolved phosphorus.
The spatio-temporal analysis of the residuals from the regression using time varying
covariates indicated that any temporal correlation that is present in the raw data can be adequately explained by the aforementioned covariates. However, these independent variables from Table 1 do not completely account for the spatial correlation. Thus, examining individual maps of phosphorus at fixed time points appears to be entirely justified. ArcMap 1 above shows our four data values as red dots mapped on spatially arranged, according to the GPS, on a GIS map file of Merced. We have divided the map based on land usage. The green area on the map contains primarily agricultural lands filled with various types of farms and cropland while the yellow area represents the city county of Merced. The brown area is dense urban areas, and the lighter blue lines represent all types of canals and creeks that are in the area and the dark blue blotches signify large bodies of water like lakes. We have highlighted Bear Creek in purple allowing us to see our point of interest more clearly. This map allows us to see what types of factors might influence each data point.
Leung and Patel 10
VI. Conclusions Overall the dissolved oxygen decreased as we sampled down Bear Creek. Although this may not seem be a significant drop, the decrease of DO in water, despite it being one unit, seems to be consistent with our hypothesis that the DO in water would decrease as it makes its way from the initial point to the end location. There are many factors that could influence the observed pattern such as possible run-off from the urban sewers and agricultural areas, temperature, vegetation, and weather. We just saw in our spatial analysis lots of parameters that could possibly affect the dissolved oxygen content and influence the decrease in DO we observed. This experiment demonstrated the importance of the developing field of spatial analysis. These mapping techonologies such as Google Maps and Earth, and ArcGIS added a whole different level of dynamics to our data set. We were able to see how data is effected by the surrounding environment by creating and studying digital maps. This project can be continue by future ENGR 180 students and the dissolved oxygen and other environmental parameters of Bear Creek can be tested and mapped spatially as exemplified in ArcMap 2. Also looking at other connecting bodies of water vary in dissolved oxygen may indicate sources of potential pollutants. In this way Spatial Analysis can be used to solve real world environmental problems and help create a more sustainable society. ArcMap 2
Leung and Patel 11
VII. Acknowledgements (1) Google Maps and Earth for providing free resources to locate data points. (3) Jacob Flanagan and Otto Alvarez, our ENGR 180 TAs for helping us with the spatial analysis. (2) Mike Dunlap from UC Merced Science and Engineering allowing us to borrow the DO meter. (3) Ryan Lucas from UC Merced's Environmental Systems Graduate Group for providing us with insightful advice about how to conduct and interpret our field sampling. (4) The work of both authors was supported, in part, by the Roy J. Carver Trust, the University of Northern Iowa and NASA’s Space Grant
VI. References (1)
Cressie, N. (1985). Fitting Variogram Models by Weighted Least Squares. Math Geology. 17(5), pp 563-586.
(2)
Cressie, N. (1993). Statistics for Spatial Data. John Wiley and Sons, New York.
(3)
Ecker, M.D. and Janssen, A. (1999). Water Quality in Lake Casey and Silver Lake, Iowa; Spatial Modeling and Prediction. Proceedings to the Ninth Annual Iowa Space Grant Conference. pp 1-10.