Results: A Strategy For Modeling Salton Sea Basin Future Climate Scenarios Based On Relationships Between Evapotranspiration And Precipitation
A comparison of the averaged weather station datasets versus the historic individual weather station datasets was made for both precipitation and Eto. The averaged monthly dataset preserved seasonality for both precipitation and Eto as illustrated in the figures. Notably, for the months of February, March, and April, the average monthly precipitation volume was lower than the actual weather station historic data. This occurred for two reasons: 1) the disparity in the number of observations between the two weather station datasets and the average resulting in the largest number of observations
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The results of the two test statistics differed at times, i.e., listing two different curves as providing the “best” fit. In the fore-mentioned situation, a final decision pertaining to the “best” fit was made based on a visual assessment of the figures.
Precipitation Events and Eto Levels
The importance of using monthly data instead of annual data for the Salton Sea Basin. Further, the two models: (1) (Logit Y1,……….12) Month = Constant + X1 Prcp, and (2) (Logit Y1,……….12) Month = Constant + X1 Eto, established that some months were significantly different than others concerning the amounts of precipitation and Eto, respectively. The relationships between the duration of precipitation events (‘CatEvent’) on the volume of precipitation (‘PrcpAmt’ and ‘CatVol’), and also on Eto volumes. A plot of the precipitation and Eto observations, percentage or percentage of observations of a given magnitude, respectively, by month was also made.
The negative relationship between precipitation and Eto was tested statistically using two multinomial logistic regression models and one binomial logistic regression model, respectively: (3) (Logit Y0,...4) PrcpAmt = Constant + X1 Eto, (4) (Logit Y0,….5) CatEvent = Constant + X1 Eto, and (5) (Logit Y0,1) RainEvent = Constant + X1 Eto. The
(Salton Sea Symposium, 1998) However , the condition of the Sea has drastically changed and so has the amount of healthy living organisms in the Sea. By the 1980�s the water level rose greatly and gave way to abandoned businesses, deteriorating structures and empty beaches. The above was due to the fact that evaporation is the only outlet to the Salton Sea , in fact 1.35 million acre feet of water is lost each year , thus increasing its salinity even more. The salinity of the Salton Sea has increased to 45,000 parts per thousand or 45 PPT; the Pacific Ocean is currently 35 PPT.
Iterations of analysis eliminated data points that were listed as “unusual observations,” or any data point with a large standardized residual. After 5 iterations, the analysis showed improved residual plots. Randomness in the versus fits and versus order plots means that the linear regression model is appropriate for the data; a straight line in the normal probability plot illustrates the linearity of the data, and a bell shaped curve in the histogram illustrates the normality of the data.
6. Why is the black line so much more variable than the red line? What 's the difference between the data they show?
The USGS MODFLOW–NWT program was used to develop the model. The model consists of seven model layers representing, from top to bottom, the surficial aquifer system, the Intermediate Confining Unit, the Upper Floridan aquifer, the middle semi-confining unit (where present), the Lower Floridan aquifer, including the lower semi-confining unit, and the Fernandina permeable zone of the Lower Floridan aquifer, where present. The model is discretized into a uniform grid size of 2,500 feet by 2,500 feet. Fully calibrated Hydrologic Simulation Program Fortran (HSPF) surface water models were used to provide estimates of recharge and maximum saturated evapotranspiration as input to the groundwater model. In the first phase of model development, steady-state calibration of the model was performed for the years 2001 and 2009. A transient version of the model is planned to be developed beginning next
The data in the charts provides information to support the theory that less rainfall will
Mean precipitation is another factor
Quito is the capital city from Ecuador where is considering a high elevation area with approximately 2800 meters above sea level in its elevation. Also, the city is located in the center of Andean Region and it is influenced by the equatorial line with latitudes nearest to 0 grades and being in a Tropical Region without seasons (Figure 1). Moreover, Quito doesn’t present stations, only the city shows two times considered like a dry and a wet season. The mean temperature during the year has a mean in minimum about 9.0°C and a maximum 25.4 °C20, also presented a high precipitation near to 1126 mm on 2015 that let to have a high density cloud every year.
Where AET is actual evapotranspiration, P is the precipitation depth, and Q is runoff depth. Combined evaporation and transpiration from plants (evapotranspiration) is balanced by inflows as precipitation and outflows as runoff. Based on a research conducted by McGuiness (1963) for a period of seventeen years (1933-1949), the Rock Creek basin received an average precipitation of 43.5 inches, in which 12 inches was surface runoff. Therefore, if the precipitation and runoff values are substituted into the equation above, actual evapotranspiration rate of the basin equals 31.5 inches. However,
This next graphic displays the typical precipitation during the different El Niño years listed up at the top. This is shown through anomalies/averages. As you can see, California and the Gulf states have large amounts of precipitation up to 5 inches above normal, due to the storms that cut across those areas. The northern parts of the U.S. have close to nearly normal rainfall, while the Ohio Valley and areas of Washington are below the normal amount of precipitation shown by the negative anomalies.
The highest population which aligned with locality and climate requirements was Buenos Aries, with an urban agglomeration population of nearly 14 million. Situated along the east coast of Argentina, the city shares its boundaries with 24 other districts, forming the Greater Buenos Aries (Figure 6). This region spans over 3880 km2 with a population density of over 3500 persons/km2 (Table 3). However, within the city centre, i.e. in Buenos Aries alone, the population density increases to 14000 persons/km2. The two urban stations are located in Buenos Aries and in the surrounding district of El Parlomar. These stations are situated in central metropolitan areas with population densities of 15296 persons/km2 and 2926 persons/km2 (Table 2). These densities are in contrast with those found in the neighbouring regions of the rural weather stations. In Ministro Pistarini and on the outskirts of La Plata, the population density of the rural stations was estimated from the population density of the total internal province, with density of 20 persons/km2 (Table 2). Similarly, the elevation of the stations had a minimal difference of 7 m (Table
The first major problem is the Salton Sea is a salt lake with salinity levels 25% higher than our oceans according to a study conducted by the California Department of fish and Game (Cohen). The salinity levels are gradually rising due to the fact the sea has no outlet and water is only lost through evaporation, leaving dissolved salts behind. In addition, sitting at an elevation of 220
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