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Changes in land use and increased intensity of rainfall are factors of greater influence that accelerate the soil erosion process. The application of basin scale sedimentological models integrated to Geographic Information Systems GISis a what are the different five agents of erosion that allows the definition of critical zones, and of this the establishment of measures of control of processes of production and transport of sediments.
This study evaluates the water erosion using the Universal Soil Loss Equation USLEfive scenarios were studied: corresponding to the start of operations of the El Portillo II dam, and the before and after the two extreme events in the basin September and October The transport of sediments what are the different five agents of erosion evaluated by regression, using full annually records eight years of flows of two gauging stations in the basin. Los cambios de uso de suelo y el aumento en la intensidad de las lluvias, son factores de mayor influencia que aceleran el proceso de erosión hídrica.
El transporte de sedimentos se evaluó mediante regresión, empleando registros anuales completos ocho años de caudales sólidos y líquidos de dos estaciones de medición. The spatial and temporal variation of changes in land use brings with it, not only environmental problems, it also has a social and economic impact. Changes in land use in Mexico have grew up, particularly during the second half of the last century; in this way, by the country only had half of relationship building in the workplace tips original plant cover Challenger and Dirzo, According to Cuevas, et al.
The vulnerability of unprotected soil to the impact of extreme rainfalls events on watersheds is significant. From this, runoff becomes greater, which implies what are the different five agents of erosion increase in the drag of soil particles; that is, it contributes to the sediment production-transport-deposition process where sediment sources are generally the upper parts of the basins Pereyra, et al. The extreme events that have plagued the country in recent decades have strongly contributed to a significant increase in water erosion, where intense rainfall plays an important role in production of sediments.
The model of the Universal Soil Loss Equation USLEfor the estimation of the erosion of water in little gullies and between them, considers the effect of the rainfall erosivity R ; likewise, it considers that the main agents that contribute to the control of water erosion are the vegetal cover C and the soil management Psince the susceptibility of the soil to erosion or erodability Kit depends not only on the characteristics of the soil, but also on how unprotected it is; on the other hand, the LS factor represents the combined effect of the slope S and the length L of the land exposed to erosion Arellano, ; ; CORTOLIMA, However, the information generated using the USLE model represents only an indicator of the critical zones and does not have an accurate intrinsic valuation.
In the other sense, the current what are the different five agents of erosion up tendency in the magnitude of surface runoff, makes clear the need to have records of liquid flows and its solid fraction, with trust data in the planning, design and operation of water management projects. Although sometimes the measurement of flows by gauging stations has been replaced by the gauging in waterworks like spillways of dams, this does not provide solid flow information.
In addition to the above, the short record periods available represent a barrier to visualizing the temporal variability of runoff, as the quantity and quality of data are very important factors in the water erosion and sediments dynamic analysis. Therefore, the emphasis of this studio is the analysis of the influence of the plant cover changes on the variation of erosion rates and the sediment transportation, associated with extreme rainfall events.
The upper basin of Cuxtepeques river, object of this study, is the one corresponding to the delimitation given by the watershed of the El Portillo II storage irrigation dam. Figure 1 Location of the Study Basin. The micro-climate conditions in the basin vary according to the location, as in highest areas of the Sierra Madre there is temperate local climate with summer rain-fall, the middle zone presents a semi-warm humid and in the lowest sub-humid warm zone Arellano, The rainfall data with years with complete record, were taken from the station called Finca Cuxtepeques, because to its proximity with the Sierra Madre of Chiapas.
In the period from to an average annual rainfall of 2, The basin's topography is characterized by mild slopes in the valley to very steep slopes in some points of the Sierra Madre. Regarding the USLE developed by Wischmeier and Smithits parameters are shown in Equation 1 and each of these variables are described below:. For the present study, the almost inexistence of management practices for soil conservation was taken into consideration, so that the P factor has unit value, in each analysis scenario.
The other parameters were obtained in some cases with modifications to the original methodology; they were made by different authors for the regional conditions of study site. Factor of erosivity R was obtained through the equation given by Bauman and Arellano :. Where: R is in MJ-mm- ha-h-year -1 and Pp is the annual mean rainfall in mm.
This annual mean rainfall was calculated for the period between each study scenario, considering only continuous records of Finca Cuxtepeques gauging station. The erodability soil factor K in What is the difference between elements minerals and rocks - MJ-mm-ha -1 was obtained by consider the main soil group in each case.
In the other hand, the slope length-gradient factor LS was calculated with the product of L and S. The L factor was evaluated with the Equation 3 Desmet and Govers, :. Where: A ij is the contributing unitary area to the entrance of a pixel, D is the pixel what does left associative mean and X is a correcting form factor. The exponent m in Equation 3 was obtained with:. The correction of the imagines was made using Erdas Imagine version 8.
The soil lost rates were defined according to the criteria of Arellano ; however, for this study it was decided to include a class adapted from the categories proposed by Pérezaccording to shown in Table 1. The weighted mean rates were obtained like the harmonic mean of values by grid in the erosion maps, and the annual means with to multiply this with the basin area to estimate the sediment rate Gottschalk, Table 1 Classification of water erosion rates.
The behavior of the runoff volumes was analyzed with Flow-mass curve method or accumulated volumes for each gauging station of the basin. For is it worth paying for dating apps reddit analysis of the temporal variability of the flows, data of runoff volume and its solid fraction were used.
To determine the existence of regional homogeneity and the possibility of adjusting the data to a curve using the statistical regression procedure. Five more stations were selected, and two homogeneity tests were applied: Test of Discordance and Test S of Wiltshire Campos ; Applying the Equation 2 what is the butterfly effect urban dictionary obtained the R value for each study scenario Table 2.
The high R values are consistent because it is an area with high rainfalls and are analogous to those reported by Arellano Table 2 Results got for the R factor. The soil erodability factor map K is showed in Figure 2 ; it shows that the soils in the middle-high zone are more susceptible to erosion, with a K value of 0. While soils in valley have values less than 0.
Figure 2 Spatial Variability of K Factor. As according to Arellano the LS factor Figure 3 represents the spatial variability from what are the different five agents of erosion process and has effect both in the runoff volume and the surface velocity of the flow. The map generated for LS factor Figure 3 shows the spatial variability from basin relief. The values indicate a variation in low basin areas ofwhile in middle-high and high zones there are values from 5 to Highest values are not common; however, these are numerically high, this mean that flow velocity is greater and thus also higher erosive capacity.
For the C factor, the data are showed in Figure 4. The first study casepoint highest frequency in values less 0. In the other hand, the second scenario indicates a reduction of values; whose changes toward the third scenario are not of great relevance. In opposite side is the equivalence class example scenerythis shows a high increase of the factor, this tendency continues in the last scenariowith important rises in some points, remain values of 0.
With the Map Algebra technical, Equation 1 and ArcMap version 10, raster maps were made for each study scenario as shown in Figure 5 for Figure 5 Erosion Map for the First Scenario In the first case, the less percent of affected surface corresponds to very low Ton-ha -1 -year -1 with 0. Table 3 Erosion rate by affected area in five scenarios. Figure 6 Erosion Rates in the Basin.
It is observed a decrease in erosion rates from the first to the second scenarios ; in this period, the incipient erosion rate has the less percent with 1. The variation in some values in the third scenery is subtle, with changes almost imperceptible. The variation in very low and very severe rates showed increase of 0. Also, the changes in last two scenarios to with respect to the three previous ones, are intensive and drastic, a lot of percent of the areas basin were affected by very severe and extraordinary erosion rates.
The fourth scenario shows that The foregoing shows the impact of the extreme rainfall of the hydro-meteorological events of September and October on the basin water erosion. The annual mean and weighted water erosion rates estimated for each period, showed a constant increase in the areas affected with water erosion severe, progressive in some cases and drastic in other ones Table 3 and Figure 6. The mass curves calculated for the what are the different five agents of erosion gauging stations Figure 7 showed similar behaviors; even these have changes in their tendency in near dates.
The most pronounced changes occurred between June and November In general, the turning points of the curve for the San Francisco II gauging station are two or three months behind La Concordia gauging station. Nevertheless, both curves have statistical homogeneity each other. The regional homogeneity tests were applied to seven gauging stations, between them San Francisco II and La Concordia.
The Discordance Test showed that none gauging station processed in this test has anomalous records. The results in both tests and the gauging stations used are shown in Table 4. Table 4 Results got of homogeneity tests. The homogeneity in the sub-region formed by the seven gauging stations is a good indicator to use these gaging data. Because what are the different five agents of erosion the dam basin, there are only two gauging stations, it was made by regression: an adjustment from data set for several models.
The best polynomial model was with grade six. To compare with models shown by Krysanova et al. Where Vs is the solid volume in millions of m3 and V is liquid volume in millions of m3. The curves are shown in Figure 8. Figure 8 Adjustment by Regression. The generation of raster maps with Map Algebra technical has been key for this objective. It is accepted that is essential the calibration of the USLE parameters in field, as this will contribute to obtain more sense results.
The changes in the vegetation cover in the basin and the rainfall intensity show a great relationship with variations in erosion rates in each study period. The basin susceptibility versus the water erosion has increased significantly, which is radically reflected in the scenarios from to that show how do the nitrogenous bases pair up in a dna molecule impact of rainfalls in Sept-ember what are the different five agents of erosion accelerated the severe water erosion in several areas.
The results show the need to establish support practices to improve the management conditions and vegetation, thus, to reduce its vulnerability to the impacts induced by extreme rainfalls and generated by the global climate change. The homogeneity tests showed congruence with each other, giving favorable results. Both tests represent a significant reference for the flood regional analyst that can be applied to study the sedimentation in the basin.
Although the regression curve obtained shows a good fit to the data, it becomes clear that there is a need to have longer recording periods, since it will allow to know in detail the changes that the dynamics of the sediment production and the load have undergone suspension in the recent past. Arellano-Monterrosas, J. Bauman, J. In: 25 years of assessment of erosion-proceedings. Gheat, Belgium.
Gabriels and W. Cornelis eds. Campos-Aranda, D.
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