Evapotranspiration and Precipitation over Pasture and Soybean Areas in the Xingu River Basin, an Expanding Amazonian Agricultural Frontier

The conversion from primary forest to agriculture drives widespread changes that have the potential to modify the hydroclimatology of the Xingu River Basin. Moreover, climate impacts over eastern Amazonia have been strongly related to pasture and soybean expansion. This study carries out a remote-sensing, spatial-temporal approach to analyze inter- and intra-annual patterns in evapotranspiration (ET) and precipitation (PPT) over pasture and soybean areas in the Xingu River Basin during a 13-year period. We used ET estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) and PPT estimates from the Tropical Rainfall Measurement Mission (TRMM) satellite. Our results showed that the annual average ET in the pasture was ~20% lower than the annual average in soybean areas. We show that PPT is notably higher in the northern part of the Xingu River Basin than the drier southern part. ET, on the other hand, appears to be strongly linked to land-use and land-cover (LULC) patterns in the Xingu River Basin. Lower annual ET averages occur in southern areas where dominant LULC is savanna, pasture, and soybean, while more intense ET is observed over primary forests (northern portion of the basin). The primary finding of our study is related to the fact that the seasonality patterns of ET can be strongly linked to LULC in the Xingu River Basin. Further studies should focus on the relationship between ET, gross primary productivity, and water-use efficiency in order to better understand the coupling between water and carbon cycling over this expanding Amazonian agricultural frontier.

Download Full-text

Padrões temporais da precipitação e variabilidade da vegetação sobre a bacia do rio Iriri em anos de ocorrência do El Niño Oscilação Sul (Temporal patterns of precipitation and vegetation variability over Iriri River basin during El Niño/Southern Oscilation)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v12.3.p789-800 ◽

2019 ◽

Vol 12 (3) ◽

pp. 789

Author(s):

Jefferson Inayan Souto ◽

Ariadne Reinaldo Trindade ◽

Paulo Amador Tavares ◽

Norma Ely Santos Beltrão ◽

Altem Nascimento Pontes

Keyword(s):

High Resolution ◽

River Basin ◽

El Niño ◽

El Nino ◽

Rainy Period ◽

La Nina ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Very High

Este estudo investiga a evolução temporal do regime pluviométrico para a bacia do rio Iriri, e sua relação com o ciclo de crescimento da vegetação. Dados de precipitação baseados na técnica do CPC Morphing (CMORPH) e dados de índice de vegetação por diferença normalizada (NDVI) pelos sensores AVHRR (Advanced Very High Resolution Radiometer) e MODIS (Moderate Resolution Imaging Spectroradiometer) são analisados para o período de junho de 2009 a maio de 2014. Os resultados confirmam que o ciclo anual de precipitação da bacia do rio Iriri é caracterizado por uma variação intra-sazonal, que é ressoada na cobertura vegetal no decorrer dos meses. Durante o ano com ocorrência de La Niña, os excedentes mais extremos de precipitação mensal foram observados no meio da estação chuvosa (novembro a abril). Embora no período menos chuvoso os totais de precipitação possam não ser os mais altos, o NDVI varia de forma senoidal em decorrência da sazonalidade da região. Épocas chuvosas podem ser distinguidas das estações chuvosas que não sofrem influência de mecanismos de precipitação, examinando seus padrões de pico mensais. Além disso, foi identificado através do NDVI, que o período menos chuvoso pouco influência no índice vegetativo durante a ocorrência dos fenômenos do El Niño Oscilação Sul (ENOS). Estes resultados podem ter implicações importantes para compreensão da dinâmica dos recursos hídricos e provisões naturais para uma bacia composta por áreas protegidas. A B S T R A C TThis study investigates the temporal evolution of the precipitation regime for the Iriri river basin, and its relation with the vegetation growth cycle. Precipitation data based on CPC Morphing (CMORPH) and normalized differential vegetation index (NDVI) data by AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) are analyzed for the period June 2009 to May 2014. The results confirm that the annual precipitation cycle of the Iriri River basin is characterized by an intra-seasonal variation, which is resounded in the vegetation cover during the months. During the year with the occurrence of La Niña, the most extreme surpluses of monthly precipitation were observed in the middle of the rainy season (November to April). Although in the less rainy period precipitation totals may not be higher, the NDVI varies in sinusoidal form due to the seasonality of the region. Rainy seasons can be distinguished from rainy seasons that are not influenced by precipitation mechanisms by examining their monthly peak patterns. In addition, it was identified through the NDVI, that the less rainy period had little influence on the vegetative index during the occurrence of El Niño Southern Oscillation (ENSO) phenomena. These results may have important implications for understanding the dynamics of water resources and natural provisions for a basin composed of protected areas.Keywords: Climatology, remote sensing, vegetation.

Download Full-text

Evaluation of monotonic trends for streamflow in austral Amazon, Brazil: a case study for the Xingu and Tapajós rivers

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-371-125-2015 ◽

2015 ◽

Vol 371 ◽

pp. 125-130 ◽

Cited By ~ 2

Author(s):

L. Z. Moura

Keyword(s):

River Basin ◽

Confidence Level ◽

Statistical Tests ◽

River Basins ◽

Annual Average ◽

Southwestern Part ◽

Southeastern Part ◽

Xingu River ◽

Increasing Trends

Abstract. This paper has the goal of evaluating monotonic trends in the Xingu and Tapajós river basins in the Austral Amazon region, Brazil. Non-parametric statistical tests such as Mann–Kendall, Bootstrap Mann–Kendall, Sen and Bootstrap Sen are applied on streamflow gauging stations data, to determine the significance and magnitude of possible trends. Data in these river basins is relatively scarce, with time series ranging from twenty to forty years, having many gaps. Former studies indicate a decreasing trend for both annual average and minimum streamflow values in the Tapajós river basin, with 99% confidence level, and a decrease in maximum values in the Xingu river basin, with 90% confidence level. However, past analyses have only used one station near the basin outlet. This study uses data from 7 gauging stations in the Xingu basin and 14 stations in the Tapajós basin. Results indicate opposite trends at the 95% confidence level for different regions in the basins, and for different flow regimes. For the Xingu river basin, trends in the minimum flow for different sub-basins even out at the Altamira station, near its outlet. For the Tapajós river, the southeastern part of the basin has increasing trends, while the southwestern part decreases. At the Itaituba station, they also balance out.

Download Full-text

Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16081379 ◽

2019 ◽

Vol 16 (8) ◽

pp. 1379 ◽

Cited By ~ 4

Author(s):

Zhenzhen Wang ◽

Jianjun Zhao ◽

Jiawen Xu ◽

Mingrui Jia ◽

Han Li ◽

...

Keyword(s):

Northeast China ◽

Arable Land ◽

Pollution Index ◽

Air Pollutant ◽

Thermal Anomalies ◽

Pollutant Concentrations ◽

Moderate Resolution ◽

Resolution Imaging ◽

Straw Burning ◽

Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

Download Full-text

A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

Remote Sensing ◽

10.3390/rs13152895 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2895

Author(s):

Maria Gavrouzou ◽

Nikolaos Hatzianastassiou ◽

Antonis Gkikas ◽

Christos J. Lolis ◽

Nikolaos Mihalopoulos

Keyword(s):

Mediterranean Basin ◽

Eastern Mediterranean ◽

Mean Value ◽

Early Spring ◽

Dust Aerosol ◽

Ozone Monitoring Instrument ◽

Central Mediterranean ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

Download Full-text

250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

Remote Sensing ◽

10.3390/rs13050920 ◽

2021 ◽

Vol 13 (5) ◽

pp. 920

Author(s):

Zhongting Wang ◽

Ruru Deng ◽

Pengfei Ma ◽

Yuhuan Zhang ◽

Yeheng Liang ◽

...

Keyword(s):

Mixing Model ◽

Blue Band ◽

Aerosol Retrieval ◽

Aerosol Distribution ◽

Medium Resolution ◽

Fine Spatial Resolution ◽

Yearly Average ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

Download Full-text

Trends in climate extreme indices assessed in the Xingu river basin - Brazilian Amazon

Weather and Climate Extremes ◽

10.1016/j.wace.2021.100306 ◽

2021 ◽

Vol 31 ◽

pp. 100306

Author(s):

Edmundo Wallace Monteiro Lucas ◽

Francisco de Assis Salviano de Sousa ◽

Fabrício Daniel dos Santos Silva ◽

Rodrigo Lins da Rocha Júnior ◽

David Duarte Cavalcante Pinto ◽

...

Keyword(s):

River Basin ◽

Brazilian Amazon ◽

Climate Extreme ◽

Xingu River ◽

Extreme Indices

Download Full-text

New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests

Nature Communications ◽

10.1038/s41467-021-20994-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Hirofumi Hashimoto ◽

Weile Wang ◽

Jennifer L. Dungan ◽

Shuang Li ◽

Andrew R. Michaelis ◽

...

Keyword(s):

Cloud Cover ◽

Seasonal Patterns ◽

Optical Remote Sensing ◽

Amazon Forest ◽

Evergreen Forests ◽

Geostationary Satellites ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

New Generation

AbstractAssessing the seasonal patterns of the Amazon rainforests has been difficult because of the paucity of ground observations and persistent cloud cover over these forests obscuring optical remote sensing observations. Here, we use data from a new generation of geostationary satellites that carry the Advanced Baseline Imager (ABI) to study the Amazon canopy. ABI is similar to the widely used polar orbiting sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), but provides observations every 10–15 min. Our analysis of NDVI data collected over the Amazon during 2018–19 shows that ABI provides 21–35 times more cloud-free observations in a month than MODIS. The analyses show statistically significant changes in seasonality over 85% of Amazon forest pixels, an area about three times greater than previously reported using MODIS data. Though additional work is needed in converting the observed changes in seasonality into meaningful changes in canopy dynamics, our results highlight the potential of the new generation geostationary satellites to help us better understand tropical ecosystems, which has been a challenge with only polar orbiting satellites.

Download Full-text

Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites

Remote Sensing ◽

10.3390/rs13091627 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1627

Author(s):

Chermelle B. Engel ◽

Simon D. Jones ◽

Karin J. Reinke

Keyword(s):

Real Time ◽

Infrared Imaging ◽

Night Time ◽

Clear Link ◽

Radiative Power ◽

Biogeographical Region ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Fire Radiative Power

This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.

Download Full-text

Consequences of the 2019 Greenland Ice Sheet Melt Episode on Albedo

Remote Sensing ◽

10.3390/rs13020227 ◽

2021 ◽

Vol 13 (2) ◽

pp. 227

Author(s):

Arthur Elmes ◽

Charlotte Levy ◽

Angela Erb ◽

Dorothy K. Hall ◽

Ted A. Scambos ◽

...

Keyword(s):

Radiative Forcing ◽

Surface Albedo ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Energy Budget ◽

Landsat 8 ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Seasonal Snow Cover

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm−2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.

Download Full-text

Assessing Climate Change Trends and Their Relationships with Alpine Vegetation and Surface Water Dynamics in the Everest Region, Nepal

Atmosphere ◽

10.3390/atmos12080987 ◽

2021 ◽

Vol 12 (8) ◽

pp. 987

Author(s):

Mana Raj Rai ◽

Amnat Chidthaisong ◽

Chaiwat Ekkawatpanit ◽

Pariwate Varnakovida

Keyword(s):

Climate Change ◽

Surface Water ◽

River Basin ◽

Climate Impacts ◽

Glacial Lake ◽

Annual Precipitation ◽

Series Data ◽

Lake Area ◽

Alpine Vegetation ◽

Koshi River Basin

The Himalayas, especially the Everest region, are highly sensitive to climate change. Although there are research works on this region related to cryospheric work, the ecological understandings of the alpine zone and climate impacts are limited. This study aimed to assess the changes in surface water including glacier lake and streamflow and the spatial and temporal changes in alpine vegetation and examine their relationships with climatic factors (temperature and precipitation) during 1995–2019 in the Everest region and the Dudh Koshi river basin. In this study, Landsat time-series data, European Commission’s Joint Research Center (JRC) surface water data, ECMWF Reanalysis 5th Generation (ERA5) reanalysis temperature data, and meteorological station data were used. It was found that the glacial lake area and volume are expanding at the rates of 0.0676 and 0.0198 km3/year, respectively; the average annual streamflow is decreasing at the rate of 2.73 m3/s/year. Similarly, the alpine vegetation greening as indicated by normalized difference vegetation index (NDVI) is increasing at the rate of 0.00352 units/year. On the other hand, the annual mean temperature shows an increasing trend of 0.0329 °C/year, and the annual precipitation also shows a significant negative monotonic trend. It was also found that annual NDVI is significantly correlated with annual temperature. Likewise, the glacial lake area expansion is strongly correlated with annual minimum temperature and annual precipitation. Overall, we found a significant alteration in the alpine ecosystem of the Everest region that could impact on the water–energy–food nexus of the Dudh Koshi river basin.

Download Full-text