Dynamic Diurnal Changes in Green Algae Biomass in the Southern Yellow Sea Based on GOCI Images

Macroalgae blooms of Ulva prolifera have occurred every summer in the southern Yellow Sea since 2007,inducing severe ecological problems and huge economic losses.Genesis and secular movement of green algae blooms have been well monitored by using remote sensing and other methods.In this study,green algae were detected and traced by using Geostationary Ocean Color Imager(GOCI),and a novel biomass estimation model was developed from the relationship between biomass measurements and previously published satellite-derived biomass indexes.The results show that the green algae biomass can be determined most accurately with the biomass index of green algae for GOCI(BIGAG),which is calculated from the Rsurf data that had been atmospherically corrected by ENVI/QUAC method.For the first time,dynamic changes in green algae biomass were studied over an hourly scale.Short-term biomass changes were highly influenced by Photosynthetically Available Radiation(PAR)and tidal phases,but less by sea surface temperature variations on a daily timescale.A new parameter of biomass changes(PBC),calculated by the ratio of the biomass growth rate to movement velocity,could provide an effective way to assess and forecast green tide in the southern Yellow Sea and similar areas.

Long-term Changes in the Saline Lake Qarun(Egypt)

1 Introduction There is now ample evidence of the impacts of the recent climate change and anthropogenic activities on different saline lake ecosystems.All over the world salt lakes are threatened by climate change,water diversions upstream for agricultural purposes,watershed changes,introduction of aliens,etc.that result in catastrophic

The Influence of Weather and Climate Variability on Groundwater Quality in Zanzibar

Climate change and variability have been inducing a broad spectrum of impacts on the environment and natural resources including groundwater resources. The study aimed at assessing the influence of weather, climate variability, and changes on the quality of groundwater resources in Zanzibar. The study used the climate datasets including rainfall (RF), Maximum and Minimum Temperature (Tmax and Tmin), the records acquired from Tanzania Meteorological Authority (TMA) Zanzibar office for 30 (1989-2019) and 10 (2010-2019) years periods. Also, the Zanzibar Water Authority (ZAWA) monthly records of Total Dissolved Solids (TDS), Electrical Conductivity (EC), and Ground Water Temperature (GWT) were used. Interpolation techniques were used for controlling outliers and missing datasets. Indeed, correlation, trend, and time series analyses were used to show the relationship between climate and water quality parameters. However, simple statistical analyses including mean, percentage changes, and contributions to the annual and seasonal mean were calculated. Moreover, t and paired t-tests were used to show the significant changes in the mean of the variables for two defined periods of 2011-2015 and 2016-2020 at p ≤ 0.05. Results revealed that seasonal variability of groundwater quality from March to May (MAM) has shown a significant change in trends ranging from 0.1 to 2.8 mm/L/yr, 0.1 to 2.8 μS/cm/yr, and 0.1 to 2.0℃/yr for TDS, EC, and GWT, respectively. The changes in climate parameters were 0.1 to 2.4 mm/yr, 0.2 to 1.3℃/yr and 0.1 to 2.5℃/yr in RF, Tmax, and Tmin, respectively. From October to December (OND) changes in groundwater parameters ranged from 0.2 to 2.5 mm/L/yr 0.1 to 2.9 μS/cm/yr, and 0.1 to 2.1℃/yr for TDS, EC, and GWT, whereas RF, Tmax, and Tmin changed from 0.3 to 1.8 mm/yr, 0.2 to 1.9℃/yr and 0.2 to 2.0℃/yr, respectively. Moreover, the study has shown strong correlations between climate and water quality parameters in MAM and OND. Besides, the paired correlation has shown significant changes in all parameters except the rainfall. Conclusively, the study has shown a strong influence of climate variability on the quality of groundwater in Zanzibar, and calls for more studies to extrapolate these results throughout Tanzania.

Change of parameters of BCC/RCG-WG for daily non-precipitation variables in China： 1951-1978 and 1979-2007

Parameters of weather generator BCC/RCG-WG for daily non-precipitation variables including maximum temperature, minimum temperature and sunshine hours at 669 stations in China are estimated using history daily records from 1951 to 1978 and from 1979 to 2007 respectively. The changes in the parameters for the two periods are revealed to explore the impact of climate change on these parameters. The results show that the parameters of the non-precipitation variables have experienced different changes. While the annual means and the amplitudes of the seasonal cycle show a clear change, the interannual variability, the timings of the seasonal cycles, and the temporal correlations for each variable remain practically unchanged. This indicates that climate changes in China over the last 57 years are mainly reflected in variations in the means and in the strength of the seasonal cycles. The changed parameters have implications for the stationary assumption implied in the parameter estimation and use of the weather generator for climate change studies.