Final Project: Urban Runoff and Hydrology Analysis for South Bay, LA

Introduction:

                  Storm water runoff pollution is considered a major public health issue for just about any coastal urban area. The south end of the Santa Monica Bay of Los Angeles experiences quantifiable fluctuations of oceanic pollutants. These urban runoff toxins include fecal bacteria, trash, and chemical pollutants that are harmful to the local ecology as well as Los Angeles’ beach goers.   During periods of high runoff, the poor water quality of the bay can cause skin infection, respiratory irritation, and even hospitalizing sickness. Southern California is recognized worldwide for its amazing weather and beautiful beach. It is truly a shame to witness such deteriorating anthropogenic impacts within our coastal zones. Environmentally minded communities, such as the City of Santa Monica, began capturing and treating urban runoff to combat this issue. This effort has improved water quality directly off Santa Monica Pier, but the southern reaching regions of the bay are still experiencing a surplus of harmful runoff. I propose a project to better understand “runoff hotspots” within the South Bay of Los Angeles. Through GIS-based, terrain analysis and a customized reclassification I can quantify the best suited locations for storm water capture. By systematically approaching this issue, coastal communities can implement minimum infrastructural investments while still diverting maximum urban runoff. It is important to note that I am not exploring the best locations to install a storm water treatment center. My project is centered on step 1 of the mitigation of coastal pollution: street level water capture.

Methods:

                  First and foremost, I need to define my study area of interest. The South Bay of Los Angeles is comprised of 6 coastal cities. These include El Segundo, Manhattan Beach, Hermosa Beach, Redondo Beach, Torrance, and Palos Verdes. I will be exploring and manipulating a digital elevation model (DEM) that includes all 6 of these defined regions. This will be acquired for no cost though the USGS Seamless Viewer website. With this DEM, I can efficiently run my complete terrain analysis. It is important to define all of the factors that will be utilized within this specific suitability analysis. A combination of steep slope, western facing aspect (orientation), and large volume of street runoff define the perfect scenario for storm water capture. For the sake of mitigating ocean pollution, I will also define a coastal buffer of 1 mile to insure the catch basin technology will be fully diverting runoff from entering our beaches. Each of these 4 factors is then reclassified accordingly. The slope data frame is broken down into five categories ranging 1 (worst) to 5 (best). The value 1 represents minimal slope while 5 represents the steepest terrain. The watershed data frame is broken into ten categories ranging 1 (worst) to 10 (best). Again a value of 1 is equivalent to very low runoff regions while a 10 indicates high flow rates. The top watershed value is exactly double the top slope value. This is my way of weighting the watershed factor. Street runoff is the most important factor within my analysis. These two data frames will be summed giving a total range of 2 (worst) to 15 (best). My other two factors, aspect and buffer, are categorized in a binary fashion. This serves to provide a quick yes or no threshold. For aspect analysis, any orientation containing a form of west (W, SW, or NW) will receive a 1 (yes) while any other direction will receive a value of 0 (no). For the buffer analysis, any area contained by the buffer will receive a 1 while any area outside the mile threshold will receive a 0. The sum of the slope and watershed factors will be multiplied by these binary factors. This serves to eliminate any region that doesn’t face west or exceeds the defined distance from the coastline.

Map Algebra Expression:

                  Final Analysis = (“slope analysis” + “flow intensity”) * “aspect reclass” * “buffer reclass”

Analysis:

                  The four different factors that contribute to my overall analysis are each represented within individual data frames. These data frames were individually reclassified to best consider the problem of storm water runoff. The slope analysis reveals that the steepest regions are located within Palos Verdes. This area is dominated by high-ranking slope indexes. Torrance and Manhattan Beach both contain steep coastal regions as well. The flow intensity analysis reveals the highest watershed values are within Palos Verdes, but it’s also important to note the strip of orange coloring running along the entire South Bay region. This implies that there is a large volume of water running off during wet periods and high prospect for storm water capture systems. The aspect analysis is very simple and only contains two colors. The purple represents any land facing west, northwest, or southwest while the yellow contains all the remaining orientations. Overall, the strip closest to the coastline offers mostly all favorable aspect indicating a directional flow towards the ocean. Lastly, the buffer analysis serves to define the zone of interest. This zone doesn’t exceed a distance of one mile from the ocean. Through the map algebra expression (defined within the “methods” section) the final analysis reveals ultimate insight into the runoff hot spots within the South Bay. The highest scoring zones occur in Palos Verdes revealing very high potential for runoff diversion. The coastal zone of Torrance also received relatively high values as well. Redondo Beach and Hermosa Beach yielded the lowest scores indicating less storm water running off these beach communities. Moving north into Manhattan Beach and El Segundo, raster pixel values increase in the form of a consistent strip located very close to the coastline.

Conclusion:

                  By overlaying my final analysis calculations with a detailed street map of Los Angeles, I am able to define specific streets containing or adjacent to the top runoff hotspots within the South Bay of Los Angeles. Palos Verdes contained the highest index scores (purple coloring). The best candidate streets within this city are Paseo La Cresta, Via Fernandez, Via Del Monte, Paseo Del Sol, and Paseo Del Mar. These are the urban streets that would be responsible for catching the highest volume of storm water. The city of Torrance also contained solid prospects. Paseo De La Playa, Via Mesa Grande, and Via La Soledad all scored highly within my final analysis and therefore should be considered for catch basin implementation. Overall, Redondo Beach scored relatively low within the final analysis calculations, but most of the cities urban runoff could potentially be captured off Gertruda Avenue. Hermosa Beach yielded the lowest scores within the South Bay and therefore should be skipped when considering storm water capture. Manhattan Beach’s best candidate is located within the El Porto Beach parking lot. This region scored highest for the city. Finally, the city of El Segundo would capture most of their urban runoff by focusing on Vista Del Mar. This street runs parallel to the coast and therefore could serve as a solid diversion for polluting runoff. It is important to note that I did not factor in the toxicity of the individual runoff locations; this could potentially alter the focal points of my analysis. Overall, implementing a system to capture and treat storm water can juristically improve water quality throughout the entire Santa Monica Bay. My analysis yielded these specific streets as the top candidates for the South Bay region.