corrijo referencias

Author: vhgauto

biblio/bibliografia.bib

@@ -199,7 +199,7 @@ @article{Abrial2021
    volume = {603},
    year = {2021},
 }
-@article{Lovino2018,
+@article{Lovino2018X,
    abstract = {This study examines the joint variability of precipitation, river streamflow and temperature over northeastern Argentina; advances the understanding of their links with global SST forcing; and discusses their impacts on water resources, agriculture and human settlements. The leading patterns of variability, and their nonlinear trends and cycles are identified by means of a principal component analysis (PCA) complemented with a singular spectrum analysis (SSA). Interannual hydroclimatic variability centers on two broad frequency bands: one of 2.5-6.5 years corresponding to El Niño Southern Oscillation (ENSO) periodicities and the second of about 9 years. The higher frequencies of the precipitation variability (2.5-4 years) favored extreme events after 2000, even during moderate extreme phases of the ENSO. Minimum temperature is correlated with ENSO with a main frequency close to 3 years. Maximum temperature time series correlate well with SST variability over the South Atlantic, Indian and Pacific oceans with a 9-year frequency. Interdecadal variability is characterized by low-frequency trends and multidecadal oscillations that have induced a transition from dryer and cooler climate to wetter and warmer decades starting in the mid-twentieth century. The Paraná River streamflow is influenced by North and South Atlantic SSTs with bidecadal periodicities. The hydroclimate variability at all timescales had significant sectoral impacts. Frequent wet events between 1970 and 2005 favored floods that affected agricultural and livestock productivity and forced population displacements. On the other hand, agricultural droughts resulted in soil moisture deficits that affected crops at critical growth stages. Hydrological droughts affected surface water resources, causing water and food scarcity and stressing the capacity for hydropower generation. Lastly, increases in minimum temperature reduced wheat and barley yields.},
    author = {Miguel A. Lovino and Omar V. Müller and Gabriela V. Müller and Leandro C. Sgroi and Walter E. Baethgen},
    doi = {10.5194/hess-22-3155-2018},
@@ -483,7 +483,7 @@ @article{Sagan2020a
   file = {C:\Users\victo\Zotero\storage\Q4RI43NM\1-s2.0-S0012825220302336-main.pdf}
 }
 
-@incollection{Chen2017,
+@incollection{Chen2017X,
   title = {Remote {{Sensing}} of {{Lakes}}' {{Water Environment}}},
   booktitle = {Comprehensive {{Remote Sensing}}},
   author = {Chen, X. and Feng, L.},
@@ -698,21 +698,7 @@ @article{Bonansea2019
    volume = {95},
    year = {2019},
 }
-@article{Delegido2019,
-   abstract = {Transparency or turbidity is one of the main indicators in studies of water quality using remote sensing. Transparency can be measured in situ through the Secchi disc depth (SD), and turbidity using a turbidimeter. In recent decades, different relationships between bands from different remote sensing sensors have been used for the estimation of these variables. In this paper, several indices and spectral bands have been calibrated in order to estimate transparency from Sentinel-2 (S2) images from field data, obtained throughout 2017 and 2018 in Júcar basin reservoirs with a great variety of trophic states. Three atmospheric correction methods developed for waters have been applied to the S2 level L1C images taken at the same day as the field data: Polymer, C2RCC and C2X. From the spectra obtained from S2 and the SD field data, it has been found that the smallest error is obtained with the images atmospherically corrected with Polymer and a potential adjustment of the reflectivities’ ratio of the blue and green bands (R490/R560), which allow the estimation of SD with a relative error of 13%. Also the C2X method presents good adjustment with the same bands ratio, although with a greater error, while the correction C2RCC shows the worst correlation. The relationship between SD (in m) and turbidity (in NTU) has also been obtained, which provides an operational method for estimating turbidity with S2. The relationship for the different reservoirs between SD and chlorophyll-a concentration, suspended solids and dissolved organic matter, is also shown.},
-   author = {J. Delegido and P. Urrego and E. Vicente and X. Sòria-Perpinyà and J. M. Soria and M. Pereira-Sandoval and A. Ruiz-Verdú and R. Peña and J. Moreno},
-   doi = {10.4995/raet.2019.12603},
-   issn = {19888740},
-   issue = {54},
-   journal = {Revista de Teledeteccion},
-   keywords = {Eutrophication,Júcar basin reservoirs,Secchi disk,Sentinel-2,Turbidity},
-   note = {Analiza el uso de distintos algoritmos de corrección atmosférica y determina cual resulta en un mejor R2 al realizar un ajuste potencial entre las diferentes bandas. Compara la ecuación propuesta con la de Pereira-Sandoval y concuye que esta también se reduce a un ajuste potencial. Propone una relación usando las bandas R(490)/R(560), el cual en otro paper (Alikas) resulto el de menor correlación y donde se señala que se usa en realidad para aguas oceanicas.},
-   pages = {15-24},
-   publisher = {Universitat Politecnica de Valencia},
-   title = {Turbidity and secchi disc depth with sentinel-2 in different trophic status reservoirs at the comunidad valenciana},
-   volume = {2019},
-   year = {2019},
-}
+
 @article{Pereira-Sandoval2019,
    abstract = {Chlorophyll-a concentration and Secchi disk depth are two of the most important biophysical parameters used to assess water quality and determine the ecological state of inland waters. The Ocean Color 2 and Dall'Olmo three-band algorithms were used to estimate chlorophyll-a concentration and the calibration of the ratio 490/705 nm was used to produce an algorithm for estimating Secchi disk depth. These algorithms have been calibrated for the Sentinel 2-Multispectral Instrument (S2-MSI) and validated using in situ measurements of chlorophyll-a, Secchi disk depth and radiometry. This data was taken in the Valencia region reservoirs as part of the project Ecological Status of Aquatic Systems with Sentinel Satellites (ESAQS). The results show that for estimating chlorophyll-a concentration, it is better to apply a prior classification based on their trophic status. For eutrophic and hypertrophic waters, the TBDO algorithm had an error of 23 mg/m3 over a chlorophyll-a concentration range of between 10 to 169 mg/m3. For ultraoligotrophic to mesotrophic waters, the better algorithm was OC2_490, which resulted in an error equal to 0.9 mg/m3 over a chlorophyll-a concentration range of between 0.54 to 5.8 mg/m3. For the estimation of water transparency by Secchi disk depth, we have obtained good results with the ratio 490/705 nm, with an error equal to 0.88 m over a Secchi disk depth range of between 0.26 to 8.1 m. These algorithms have been applied to S2-MSI images and satisfactory results have been obtained for different reservoirs in the Valencia region (Spain).},
    author = {Marcela Pereira-Sandoval and Esther Patricia Urrego and Antonio Ruiz-Verdú and Carolina Tenjo and Jesús Delegido and Xavier Soria-Perpinyà and Eduardo Vicente and Juan Soria and José Moreno},