scholarly journals Characterisation of pH variations along the Ba River in Fiji utilising the GEF R2R framework during the 2019 sugarcane season

2021 ◽  
Vol 193 (12) ◽  
Author(s):  
Nicholas Metherall ◽  
Elisabeth Holland ◽  
Sara Beavis ◽  
Adi Mere Dralolo Vinaka
Keyword(s):  
Water Quality ◽  
Small Island ◽  
Sugar Mill ◽  
Rapid Sampling ◽  
Potential Source ◽  
Data Loggers ◽  
The Mean ◽  
Spatio Temporal ◽  
Measured Water ◽  
Ph Variations

AbstractWithin Pacific Small Island Developing States (Pacific SIDS), the ridge-to-reef (R2R) approach has emerged as a framework for monitoring river connectivity between terrestrial and marine ecosystems. The study measured water quality, including pH, over 88.40 km of the Ba River in Fiji. The sampling design focused on measuring spatio-temporal variability in pH throughout the sugarcane season with three rapid sampling periods (RSP1, 2 & 3) along the Ba River, together with continuous measurement of temperature and pH using stationary data loggers at two locations upstream and downstream of the sugar mill. Spatial variability in pH and water quality was characterised before (RSP1 and RSP2) and during (RSP3) the sugarcane season. Mean pH measured before the sugarcane crushing season for RSP1 and RSP2 were 8.16 (± 0.49) and 8.20 (± 0.61) respectively. During the sugarcane crushing season (RSP3), mean pH declined by 3.06 units to 6.94 within 42 m downstream of the sugar mill (P ≤ 0.001). The 3.06 unit decline in pH for RSP3 exceeded both the mean diurnal variation in pH of 0.39 and mean seasonal variation in pH of 2.01. This decline in pH could be a potential source of acidification to downstream coastal ecosystems with implications for coral reefs, biodiversity and fishery livelihoods.

scholarly journals Spatio-Temporal Analysis of Water Quality Parameters in Machángara River with Nonuniform Interpolation Methods

Water ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 507 ◽  
Author(s):  
Iván Vizcaíno ◽  
Enrique Carrera ◽  
Margarita Sanromán-Junquera ◽  
Sergio Muñoz-Romero ◽  
José Luis Rojo-Álvarez ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Analysis ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Interpolation Methods ◽  
Spatio Temporal

Spatio‐temporal dynamics of water quality and eutrophication in Lake Taihu, China

Ecohydrology ◽  
2021 ◽  
Author(s):  
Qiongfang Li ◽  
Yuting Zhu ◽  
Qihui Chen ◽  
Yu Li ◽  
Jing Chen ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Dynamics ◽  
Lake Taihu ◽  
Spatio Temporal

scholarly journals The implications of lag times between nitrate leaching losses and riverine loads for water quality policy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. W. McDowell ◽  
Z. P. Simpson ◽  
A. G. Ausseil ◽  
Z. Etheridge ◽  
R. Law
Keyword(s):  
Water Quality ◽  
Mean Transit Time ◽  
Lag Time ◽  
Practice Change ◽  
N Leaching ◽  
N Losses ◽  
Leaching Losses ◽  
Nitrate N ◽  
The Mean ◽  
Lag Times

AbstractUnderstanding the lag time between land management and impacts on riverine nitrate–nitrogen (N) loads is critical to understand when action to mitigate nitrate–N leaching losses from the soil profile may start improving water quality. These lags occur due to leaching of nitrate–N through the subsurface (soil and groundwater). Actions to mitigate nitrate–N losses have been mandated in New Zealand policy to start showing improvements in water quality within five years. We estimated annual rates of nitrate–N leaching and annual nitrate–N loads for 77 river catchments from 1990 to 2018. Lag times between these losses and riverine loads were determined for 34 catchments but could not be determined in other catchments because they exhibited little change in nitrate–N leaching losses or loads. Lag times varied from 1 to 12 years according to factors like catchment size (Strahler stream order and altitude) and slope. For eight catchments where additional isotope and modelling data were available, the mean transit time for surface water at baseflow to pass through the catchment was on average 2.1 years less than, and never greater than, the mean lag time for nitrate–N, inferring our lag time estimates were robust. The median lag time for nitrate–N across the 34 catchments was 4.5 years, meaning that nearly half of these catchments wouldn’t exhibit decreases in nitrate–N because of practice change within the five years outlined in policy.

scholarly journals Diurnal Body Temperature and Rate of Passage of Loggers in Lions

Animals ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1388
Author(s):  
Ted Friend ◽  
Giulia Corsini ◽  
Vincent Manero ◽  
Raffaella Cocco
Keyword(s):  
Body Temperature ◽  
Time Frame ◽  
Heat Lamp ◽  
Future Studies ◽  
Ambient Temperatures ◽  
Diurnal Patterns ◽  
Data Loggers ◽  
The Mean ◽  
African Lions ◽  
Circadian Patterns

The documentation of diurnal patterns in body temperature in lions could be important because disruption of circadian patterns can be a useful measure of distress. This study quantified changes in body temperature of seven African lions (Panthera leo) at 5 min intervals during cold conditions from noon until the ingested body temperature loggers were expelled the next day. Thirteen loggers were fed to 11 lions during their daily noon feeding, while ambient temperatures were also recorded using six data loggers. The lions had continuous access to their dens and exercise pens during the day but were restricted to their heavily bedded dens that also contained a heat lamp from 23:00 until 08:00 the next day. Body temperatures averaged 37.95 ± 0.42 °C at 15:50, and 36.81 ± 0.17 °C at 06:50 the next day, 30 min before the first loggers passed from a lion, and were significantly different (t-test, t = 8.09, df = 6, p < 0.0003). The mean duration for the time of passage was 22 ± 2.69 (h ± SD), so future studies using the noninvasive feeding of temperature loggers need to consider that time frame.

scholarly journals Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2699 ◽  
Author(s):  
Jian Li ◽  
Liqiao Tian ◽  
Qingjun Song ◽  
Zhaohua Sun ◽  
Hongjing Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Lake Area ◽  
Short Term ◽  
Chl A ◽  
Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

scholarly journals Tropospheric temperature variation over India and links with the Indian summer monsoon : 1971-2000

MAUSAM ◽  
2022 ◽  
Vol 53 (3) ◽  
pp. 289-308
Author(s):  
D. R. KOTHAWALE ◽  
K. RUPA KUMAR
Keyword(s):  
Summer Monsoon ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Temporal Variations ◽  
Mean Annual Temperature ◽  
Tropospheric Temperature ◽  
Temperature Variations ◽  
Annual Cycles ◽  
The Mean ◽  
Spatio Temporal

In the context of the ever increasing interest in the regional aspects of global warming, understanding the spatio-temporal variations of tropospheric temperature over India is of great importance. The present study, based on the data from 19 well distributed radiosonde stations for the period 1971-2000, examines the seasonal and annual mean temperature variations at the surface and five selected upper levels, viz., 850, 700, 500, 200 and 150 hPa. An attempt has also been made to bring out the association between tropospheric temperature variations over India and the summer monsoon variability, including the role of its major teleconnection parameter, the El Niño/Southern Oscillation (ENSO).   Seasonal and annual mean all-India temperature series are analyzed for surface and five tropospheric levels.  The mean annual cycles of temperature at different tropospheric levels indicate that the pre-monsoon season is slightly warmer than the monsoon season at the surface, 850 hPa and 150 hPa levels, while it is relatively cooler at all intermediate levels.  The mean annual temperature shows a warming of 0.18° C and 0.3° C per 10 years at the surface and 850 hPa, respectively.   Tropospheric temperature anomaly composites of excess (deficient) monsoon rainfall years show pronounced positive (negative) anomalies during the month of May, at all the levels.  The pre-monsoon pressure of Darwin has significant positive correlation with the monsoon temperature at the surface and 850 hPa.

scholarly journals Length-weight relationships and condition factor of Hyperopisus bebe (Lacepede, 1803) (Actinopterygii: Osteoglossiformes) in River Galma, Zaria, Kaduna State, Nigeria

2017 ◽  
Vol 4 (8) ◽  
pp. 301-305
Author(s):  
Matouke M. Moise
Keyword(s):  
Water Quality ◽  
Water Body ◽  
Growth Pattern ◽  
Condition Factor ◽  
Allometric Growth ◽  
Male And Female ◽  
B Values ◽  
The Poor ◽  
Poor Water Quality ◽  
The Mean

The investigation of length-weight relationship and condition factor are very relevant indices to ascertain the health of fish in the water body. Length-weigh relationship and condition factor of Hyperopisus bebe (Lacepede, 1803) (Actinopterygii: Osteoglossiformes: Mormyridae) in River Galma, Zaria, Kaduna State, Nigeria, were assessed. The mean length and mean weigh in male and female were 26.703 cm +/- 0.51 cm and 25.32 cm +/- 0.898 cm; 158.2 g +/- 10.1 g and 95.91 g +/- 9.26 g, respectively. The exponent or growth pattern 'b' values for male and female were 2.009 and 2.176. The condition factor for male and female were 0.59 and 0.83, respectively. The negative allometric growth pattern and poor condition factor might be due to the poor water quality in the fish ecosystem and should be regarded with concern.

scholarly journals Comparison of Land Surface Temperature During and Before the Emergence of Covid-19 using Modis Imagery in Wuhan City, China

2020 ◽  
Vol 34 (1) ◽  
Author(s):  
Hamim Zaky Hadibasyir ◽  
Seftiawan Samsu Rijal ◽  
Dewi Ratna Sari
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Anthropogenic Activities ◽  
Temporal Analysis ◽  
The Past ◽  
Modis Imagery ◽  
Rapid Transmission ◽  
The Mean ◽  
Spatio Temporal

Coronavirus disease (COVID-19) was firstly identified in Wuhan, China. By 23rd January 2020, China’s Government made a decision to execute lockdown policy in Wuhan due to the rapid transmission of COVID-19. It is essential to investigate the land surface temperature (LST) dynamics due to changes in level of anthropogenic activities. Therefore, this study aims (1) to investigate mean LST differences between during, i.e., December 2019 to early March 2020, and before the emergence of COVID-19 in Wuhan; (2) to conduct spatio-temporal analysis of mean LST with regards to lockdown policy; and (3) to examine mean LST differences for each land cover type. MODIS data consist of MOD11A2 and MCD12Q1 were employed. The results showed that during the emergence of COVID-19 with lockdown policy applied, the mean LST was lower than the mean LST of the past three years on the same dates. Whereas, during the emergence of COVID-19 without lockdown policy applied, the mean LST was relatively higher than the mean LST of the past three years. In addition, the mean LST of built-up areas experienced the most significant differences between during the emergence of COVID-19 with lockdown policy applied in comparison to the average of the past three years.

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