Qualitative characteristics of water resulting from the introduction of Eucalyptus silviculture in Pampa biome, RS

Cruz, Jussara Cabral; Valente, Mirian Lago; Baggiotto, Carine; Baumhardt, Edner

doi:10.1590/2318-0331.011616015

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…It is important to emphasize that the native grassland area of this study has an adequate livestock management controlled by the Federal University of Santa Maria. Studies conducted in field areas with high exploitation management have obtained greater differences in water balance results when compared with forested areas [54].…”

Section: Heterogeneity Of the Study Areamentioning

confidence: 99%

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The Influence of Land Surface Temperature in Evapotranspiration Estimated by the S-SEBI Model

et al. 2020

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Evapotranspiration (ET) is one of the least understood components of the hydrological cycle. Its applications are varied, from agricultural, ecological and hydrological monitoring, to control of the evolution of climate change. The goal of this work was to analyze the influence that uncertainties in the estimate of land surface temperature (Ts) can cause on ET estimates by S-SEBI model in the Pampa biome area. Also, the specificities of native grassland of Pampa biome related to energy balance were analyzed. The results indicate that the daily evapotranspiration is higher when the pixel Ts is lower, which also shows the influence of land use on the variability of ET. The results demonstrated that the S-SEBI is less dependent on Ts estimation than other models reported in the literature, such as the SEBS, which not exceed 0.5 mm/day in grasslands. The evapotranspiration variability between forest and grassland were lower than expected, demonstrating that the Pampa biome have in Rio Grande do Sul the same importance that forests regarding to the processes of the hydrological cycle, since it covers 63% of the State.

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Section: Heterogeneity Of the Study Areamentioning

confidence: 99%

“…with high exploitation management have obtained greater differences in water balance results when compared with forested areas [54].…”

Section: Heterogeneity Of the Study Areamentioning

confidence: 99%

The Influence of Land Surface Temperature in Evapotranspiration Estimated by the S-SEBI Model

et al. 2020

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“…The PTN biome is a sedimentary basin dominated by a combination of mesic and xeric vegetation growing side by side due to seasonal flooding [52]. The PMP biome consists of large areas of natural grasslands with a floristic matrix composed of forest formations interspersed along the watercourses [53]. Table 1 summarizes other characteristics of the Brazilian biomes, whereas the rainfall regime for each is shown in Figure 2.…”

Section: Study Areamentioning

confidence: 99%

Evaluation of the Performance of SM2RAIN-Derived Rainfall Products over Brazil

2019

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Microwave-based satellite soil moisture products enable an innovative way of estimating rainfall using soil moisture observations with a bottom-up approach based on the inversion of the soil water balance Equation (SM2RAIN). In this work, the SM2RAIN-CCI (SM2RAIN-ASCAT) rainfall data obtained from the inversion of the microwave-based satellite soil moisture (SM) observations derived from the European Space Agency (ESA) Climate Change Initiative (CCI) (from the Advanced SCATterometer (ASCAT) soil moisture data) were evaluated against in situ rainfall observations under different bioclimatic conditions in Brazil. The research V7 version of the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TRMM TMPA) was also used as a state-of-the-art rainfall product with an up-bottom approach. Comparisons were made at daily and 0.25° scales, during the time-span of 2007–2015. The SM2RAIN-CCI, SM2RAIN-ASCAT, and TRMM TMPA products showed relatively good Pearson correlation values (R) with the gauge-based observations, mainly in the Caatinga (CAAT) and Cerrado (CER) biomes (R median > 0.55). SM2RAIN-ASCAT largely underestimated rainfall across the country, particularly over the CAAT and CER biomes (bias median < −16.05%), while SM2RAIN-CCI is characterized by providing rainfall estimates with only a slight bias (bias median: −0.20%), and TRMM TMPA tended to overestimate the amount of rainfall (bias median: 7.82%). All products exhibited the highest values of unbiased root mean square error (ubRMSE) in winter (DJF) when heavy rainfall events tend to occur more frequently, whereas the lowest values are observed in summer (JJA) with light rainfall events. The SM2RAIN-based products showed larger contribution of systematic error components than random error components, while the opposite was observed for TRMM TMPA. In general, both SM2RAIN-based rainfall products can be effectively used for some operational purposes on a daily scale, such as water resources management and agriculture, whether the bias is previously adjusted.

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“…The ALK showed the highest values in this season, focusing on points 1 and 2. It had a tendency towards a positive correlation with TDS, TSS, TP, Cl -, Ca and Mg (Table 10) due to increased precipitation and ion availability originating from the dissolution of rock and soils (Lima and Zakia, 2006;Cruz et al, 2016).…”

Section: Monitoring Of Surface Water Quality In the Summer Of 2020mentioning

confidence: 99%

Seasonal analysis of aquatic water quality in a forestry area, MS, Brazil

Oliveira

Pinto

Lima

et al. 2023

Preprint

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Water quality is one of the world's greatest concerns as it is a fundamental resource for life, and it must constantly be monitored. This study aimed to carry out seasonal monitoring of water quality in the hydrographic basin of the Urutu-MS stream, which is occupied by more than 50% of eucalyptus silviculture forests. Water samples were collected from five points seasonally between autumn 2019 and summer 2020. In total, twenty-three parameters were included, including temperature (Cº), pH, Dissolved Oxygen (DO, mg/L), Conductivity (EC ), Total Alkalinity (ALK), Organic Matter (OM), Chloride (Cl), Sulfate (SO42), Total Iron (Fe Total), Color, Turbidity (NTU), Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Total Phosphorus (PT), Hardness, Aluminum (Al), Manganese (Mn), Magnesium (Mg), Sodium (Na), Calcium (Ca), Copper (Cu) and Dissolved Iron (Fe). The results showed that there is a difference in water quality between the seasons of the year depending on the different concentrations of physical-chemical parameters. Among the seasons, spring was classified in class II, while the others were classified in class I, showing the influence of the onset of rains after the dry winter. Interactions between parameters also followed conventional associations such as ALK and EC, TDS and EC, Color and Turbidity, TSS and Turbidity, EC and Ca, EC and Mg. The ALK and TDS were the main parameters that showed an influence of seasonality.

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Qualitative characteristics of water resulting from the introduction of Eucalyptus silviculture in Pampa biome, RS

Cited by 3 publications

References 15 publications

The Influence of Land Surface Temperature in Evapotranspiration Estimated by the S-SEBI Model

The Influence of Land Surface Temperature in Evapotranspiration Estimated by the S-SEBI Model

Evaluation of the Performance of SM2RAIN-Derived Rainfall Products over Brazil

Seasonal analysis of aquatic water quality in a forestry area, MS, Brazil

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