Impacts of conservation buffers and grasslands on total phosphorus loads using hydrological modeling and remote sensing techniques

CATENA ◽  
2011 ◽  
Vol 86 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Myriam Larose ◽  
Gary C. Heathman ◽  
Darrell Norton ◽  
Douglas Smith
Author(s):  
Vladimir J. Alarcon ◽  
William H. McAnally

This paper presents a methodology for estimating nutrient concentrations of total phosphorus (TP) and total nitrogen (TN) through the use of hydrological modeling, remote sensing datasets, and nutrient export coefficients. The strategy is applied to the Upper Tombigbee watershed, located in the northern region of the states of Mississippi and Alabama, USA. USGS GIRAS (1986), NASA MODIS MOD12Q1 (2001-2004) land use datasets, and USGS-DEM topographical datasets were used to characterize the physiography of the watershed. TN and TP concentration values estimated using the methodology were compared to values reported in the literature.


Author(s):  
Pedro Perez Cutillas ◽  
Gonzalo G. Barberá ◽  
Carmelo Conesa García

El objetivo principal de este trabajo se centra en la determinación y análisis de las variables ambientales que influyen en las divergencias de las estimaciones de erosionabilidad a partir de dos métodos, aplicando tres algoritmos de estimación del Factor K. La exploración de esta información permite conocer el peso que ejerce el origen de los datos de entrada a los modelos en el cómputo de erosionabilidad y qué importancia tiene en función del algoritmo elegido para la estimación del Factor K. Los resultados muestran que las pendientes, así como los índices de vegetación (NDVI) y de composición mineralógico (IOI) obtenidos mediantes técnicas de teledetección han   mostrado los valores de asociación más elevados entre ambos métodos.The main goal of this work is to determine and analyze the influence of environmental variables on the changes of two erodibility methods, through the application of three estimation algorithms of K Factor. The analysis of this information allows knowing the significance of the input data to the models in the erodibility estimation, and likewise the consequence of the algorithm selected for the estimation of K Factor. The results show that the slopes, as well as the vegetation index (NDVI) and the mineralogical composition index (IOI), generated both by remote sensing techniques, have shown the highest values of association between methods.


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