Geo-spatial analysis of the temporal trends of kharif crop phenology metrics over India and its relationships with rainfall parameters

The Global Inventory Modeling and Mapping Studies bimonthly Normalized Difference Vegetation Index (NDVI) data of 8?×?8 km spatial resolution for the period of 1982–2006 were analyzed to detect the trends of crop phenology metrics (start of the growing season (SGS), seasonal NDVI amplitude (AMP), seasonally integrated NDVI (SiNDVI)) during kharif season (June to October) and their relationships with the amount of rainfall and the number of rainy days over Indian subcontinent. Direction and magnitude of trends were analyzed at pixel level using the Mann–Kendall test and further assessed at meteorological subdivision level using field significance test (α?=?0.1). Significant pre-occurrence of the SGS was observed over northern (Punjab, Haryana) and central (Marathwada, Vidarbha and Madhya Maharashtra) parts, whereas delay was found over southern (Rayalaseema, Coastal Andhra Pradesh) and eastern (Bihar, Gangetic West Bengal and Sub-Himalayan West Bengal) parts of India. North, west, and central India showed significant increasing trends of SiNDVI, corroborating the kharif food grain production performance during the time frame. Significant temporal correlation (α?=?0.1) between the rainfall/number of rainy days and crop phenology metrics was observed over the rainfed region of India. About 35–40 % of the study area showed significant correlation between the SGS and the rainfall/number of rainy days during June to August. June month rainfall/number of rainy days was found to be the most sensitive to the SGS. The amount of rainfall and the number of rainy days during monsoon were found to have significant influence over the SiNDVI in 24–30 % of the study area. The crop phenology metrics had significant correlation with the number of rainy days over the larger areas than that of the rainfall amount.     

Phytoplankton variation and its relationship with the environment in Xiangxi Bay in spring after damming of the Three-Gorges, China

Following the completion of the Three-Gorges Dam, there was a strong spring phytoplankton bloom in Xiangxi Bay of Three-Gorges Reservoir. However, our knowledge of relationship between spring phytoplankton bloom and environmental factors was still limited. In this study, phytoplankton species composition, biomass, chlorophyll a concentration and environmental factors at two sampling sites in Xiangxi Bay were investigated during 25 March to 18 May 2007. The Xiangxi Bay was eutrophic with the lowest values of total nitrogen and total phosphorus being 0.80 and 0.07?mg/L, respectively. A total of 66 algal taxa belonging to seven phyla and 45 genera were identified. Peridiniopsis niei Liu was the most abundant species which preferred standing water. Canonical correspondence analysis and correlation analysis revealed that nitrate was significantly associated with phytoplankton growth. The phytoplankton chlorophyll a concentration was correlated significantly negatively with nitrate concentration, and nitrate concentration was very low during bloom periods. Heavy rainfall was the main reason of phytoplankton chlorophyll a concentration and biomass decreasing and blooms disappearing. In addition, heavy rainfall also brought more nitrate into the Bay which provided sufficient nitrogen source for blooms occurring again.     

Impacts of climate-induced changes on the distribution of pesticides residues in water and sediment of Lake Naivasha, Kenya

This study reports evidence of increased chlorpyrifos contamination in sediment and water in Lake Naivasha following its intensive application in the horticultural farms in the catchment area. Analytical results show that levels of chlorpyrifos residues were influenced by climate-induced rainfall pattern with higher levels reported during period of heavy precipitation with significant decrease during low rainfall. On average, the levels ranged between 14.8 and 32.8 ng g^?1 in sediment during rainy season compared to a range of 8.5–16.6 ng g^?1 in the dry season. Additionally, the mean concentration of chlorpyrifos in water ranged between 8.61 and 22.4 μg L^?1 during rainy season and below detection limit (bdl) ?13.6 μg L^?1 in dry season as quantified by enzyme-linked immunosorbent assay. Meanwhile, independent t test analysis indicated that there was significant difference in concentration at p?≤?0.05 between the seasons with respect to sediment and water samples. This demonstrated that climate-induced variations had considerable influence on contamination. While diazinon and carbofuran were equally applied intensively, their levels were below the detection limit in the all the samples analyzed. ELISA results were validated by the capillary-HPLC photodiode-array detector instrument analysis, and statistical comparison showed no significant difference between them. It was evident that chlorpyrifos residues determination in water and sediment by ELISA can be a useful strategy in environmental management and monitoring program, and a complimentary analytical tool to high performance liquid chromatography. Levels of chlorpyrifos detected in sediment and water were found to exceed recommended criteria for protection of aquatic life and preservation of water quality and may be hazardous if not regularly monitored.     

钦州湾近岸海域水质状况及富营养化分析

2012年5月钦州湾近岸海域水质监测结果表明,钦州湾近岸水温、盐度、pH、溶解氧等基本环境参数均有利于亚热带海洋生物的生长繁殖;溶解无机氮(DIN)和活性硅酸盐(SiO2-3-Si)均显示过剩,但溶解无机磷(DIP)具有低磷特征,高的氮磷比值使PO3-4-P可能成为浮游植物生长的潜在限制因子,且COD部分站位出现超标现象。污染指数(A)和单因子污染指数(Pi)结果显示,近期整个钦州湾近岸水域污染程度达到2级,属于开始受到污染,水质受到化学耗氧有机物不同程度的污染,超标率达到30%。富营养状态指数结果表明,钦州湾近岸海域总体尚未达到富营养化,但局部区域已出现富营养化状况。COD对富营养化的贡献率平均值及范围为72.46%(67.36%~83.96%),COD已成为影响钦州湾近岸海域富营养化的重要因素。     

Intra-monsoonal variation of zooplankton population in the Sundarbans Estuarine System,India

The present study was conducted during July 2013 (early phase of monsoon or EM) and September 2013 (later phase of monsoon or LM) to ascertain the intra-monsoonal variation on zooplankton, by selecting 15 study stations in the river Saptamukhi, one of the main estuaries in the Sundarbans Estuarine System (SES). In 2013, SES experienced an unusually high monsoonal rainfall also exacerbated by cloud burst event at Himalayan region (upper stretches of SES) which tremendously increased the river runoff. The present work was aimed to decipher the effect of this unusual precipitation during the monsoon season on zooplankton assemblages along with different hydrological parameters. The abundance of zooplankton was recorded as lower during EM compared to LM. Altogether, 56 zooplankton taxa were identified with copepods forming the predominant population. Thirty-three copepod species were reported with 25 calanoid species forming the bulk of the biomass followed by 5 and 3 species of cyclopoids and harpacticoid, respectively. A combination of multivariate cluster analysis, biotic indices, and canonical correspondence analysis revealed noticeable alterations in the zooplankton community structure across the spatio-temporal scale. Furthermore, significant intra-monsoonal changes in zooplankton population correlated with several hydrological parameters were clearly noticed. Paracalanus parvus, Bestiolina similis and Oithona similis were observed to be the most dominant copepod species in both sampling periods. The result of the present study provides new insight on estuarine zooplankton community after unusual rainfall during monsoon season, and provides further evidence to support the conservation and management of the SES ecosystem.     

Study on phosphorus loadings in ten natural and agricultural watersheds in subtropical region of China

Water eutrophication in subtropical regions of southern China threatens watershed health and is of major concern. However, annual phosphorus (P) loading and its dominant causes are still unclear, especially at the watershed scale. In this study, we investigated dynamic P loadings and associated factors (e.g., land use, livestock production, and runoff depth) in ten watersheds that varied in area from 9 to 5,212 ha in a hilly area of Hunan Province, China. A flowmeter was installed at the outlet of each watershed, and total P (TP) and soluble P (SP) concentrations were monitored periodically from June 2010 to October 2012. The results showed that annual P loadings (APLs) in the ten watersheds ranged from 22.8 to 247.8 kg P/km² and that P loss primarily occurred from April to June of each year during the main rainfall season in the study area. In addition, the average eutrophication (>0.05 mg P/L) ratio for stream waters was 86.7 % during the study period, which was indicative of a potentially serious condition for the local water environments. Annual P loadings were linearly related to livestock density (LD; R?=?0.92, p?<?0.01), whereas the eutrophication ratio of stream water was significantly (p?<?0.05) correlated with LD (R?=?0.61), percentage cropland (R?=?0.71), and percentage forest cover (R?=??0.68). Thus, it is concluded that the control of livestock production has the greatest potential for reducing P loadings in watersheds in this subtropical area. This will be beneficial to the amelioration and protection of local environment.     

Assessment of the labile fractions of copper and zinc in marinas and port areas in Southern Brazil

The dissolved labile and labile particulate fractions (LPF) of Cu and Zn were analyzed during different seasons and salinity conditions in estuarine waters of marina, port, and shipyard areas in the southern region of the Patos Lagoon (RS, Brazil). The dissolved labile concentration was determined using the diffusive gradients in thin films technique (DGT). DGT devices were deployed in seven locations of the estuary for 72 h and the physicochemical parameters were also measured. The LPF of Cu and Zn was determined by daily filtering of water samples. Seasonal variation of DGT–Cu concentrations was only significant (p?<?0.05) at one shipyard area, while DGT–Zn was significant (p?<?0.05) in every locations. The LPF of Cu and Zn concentrations demonstrated seasonal and spatial variability in all locations, mainly at shipyard areas during high salinity conditions. In general, except the control location, the sampling locations showed mean variations of 0.11–0.45 μg?L^?1 for DGT–Cu, 0.89–9.96 μg?L^?1 for DGT–Zn, 0.65–3.69 μg?g^?1 for LPF–Cu, and 1.35–10.87 μg?g^?1 for LPF–Zn. Shipyard areas demonstrated the most expressive values of labile Cu and Zn in both fractions. Strong relationship between DGT–Zn and LPF–Zn was found suggesting that the DGT–Zn fraction originates from the suspended particulate matter. Water salinity and suspended particulate matter content indicated their importance for the control of the labile concentrations of Cu and Zn in the water column. These parameters must be taken into consideration for comparison among labile metals in estuaries.     

Seasonal variation of nonylphenol concentrations and fluxes with influence of flooding in the Daliao River Estuary, China

Nonylphenol is an endocrine disruptor with harmful effects including feminization and carcinogenesis on various organisms. This study aims to investigate the distribution and ecological risks of nonylphenol in the Daliao River Estuary, China. Nonylphenol, together with other phenolic endocrine disruptors (bisphenol A, 4-t-butylphenol, 4-t-octylphenol, and 2,4-dichlorophenol), was detected in surface water and sediment on three cruises in May 2009, June 2010, and August 2010, respectively. A large flooding occurred during our sampling campaign in August and its effect on nonylphenol concentrations and fluxes in the estuary was therefore evaluated. The results showed that nonylphenol with a concentration range between 83.6–777 ng l^?1 and 1.5–456 ng?g^?1 dw in surface water and sediment was the most abundant among the phenolic compounds, accounting for 59.1–81.0 and 79.9–92.1 % of the total phenolic concentration in surface water and sediment, respectively. The concentrations recorded in May and June were comparable, whereas those in August were considerably higher, mainly due to the flush of flooding. The flooding also caused a 50 times increase in nonylphenol flux from the estuary into the adjacent Bohai Sea. Nonylphenol concentrations in the estuary have exceeded the threshold level of undesirable effects with a potential risk of harm to local species, especially benthic organisms.     

Study of harmful algal blooms in a eutrophic pond, Bangladesh

The purpose of this research was to analyze the underlying mechanisms and contributing factors related to the seasonal dynamic of harmful algal blooms in a shallow eutrophic pond, Bangladesh during September 2005–July 2006. Two conspicuous events were noted simultaneously throughout the study period: high concentration of phosphate–phosphorus (>3.03; SD 1.29 mg l^???1) and permanent cyanobacterial blooms {>3,981.88 × 10³ cells l^???1 (SD 508.73)}. Cyanobacterial blooms were characterized by three abundance phases, each of which was associated with different ecological processes. High nitrate–nitrogen (>2.35; SD 0.83 mg l^???1), for example, was associated with high cyanobacterial abundance, while low nitrate–nitrogen (0.36; SD 0.2 mg l^???1) was recorded during moderate abundance phase. Extremely low NO₃–N/PO₄–P ratio (>3.55, SD 2.31) was recorded, and all blooming taxa were negatively correlated with this ratio. Cyanobacterial blooms were positively correlated with temperature (r?=?0.345) and pH (0.833; p?=?0.05) and negatively correlated with transparency (r?=???0.956; p?=?0.01). Although Anabaena showed similar relationship with water quality parameters as cyanobacteria, the co-dominant Microcystis exhibited negative relationship with temperature (r?=???0.386) and nitrate–nitrogen (r?=???0.172). This was attributed to excessive growth of Anabaena that suppressed Microcystis’s growth. Planktothrix was the third most dominant taxa, while Euglena was regarded as opportunistic.     

Assessing spatio-temporal trend of vector breeding and dengue fever incidence in association with meteorological conditions

Th aim of this study is to investigate spatio-temporal trends of dengue vector breeding and epidemic (disease incidence) influenced by climatic factors. The spatio-temporal (low-, medium-, and high-intensity periods) evaluation of entomological and epidemiological investigations along with climatic factors like rainfall (RF), temperature (T_max), relative humidity (RH), and larval indexing was conducted to develop correlations in the area of Lahore, Pakistan. The vector abundance and disease transmission trend was geo-tagged for spatial insight. The sufficient rainfall events and optimum temperature and relative humidity supported dengue vector breeding with high larval indices for water-related containers (27–37%). Among temporal analysis, the high-intensity period exponentially projected disease incidence followed by post-rainfall impacts. The high larval incidence that was observed in early high-intensity periods effected the dengue incidence. The disease incidence had a strong association with RF (r = 0.940, α = 0.01). The vector larva occurrence (r = 0.017, α = 0.05) influenced the disease incidence. Similarly, RH (r = 0.674, α = 0.05) and average T_max (r = 0.307, α = 0.05) also induced impact on the disease incidence. In this study, the vulnerability to dengue fever highly correlates with meteorological factors during high-intensity period. It provides area-specific understanding of vector behavior, key containers, and seasonal patterns of dengue vector breeding and disease transmission which is essential for preparing an effective prevention plan against the vector.     

Annual and Seasonal Rainfall Trends in an Equatorial Tropical River Basin in Malaysian Borneo

Annual and seasonal rainfall trends in the Limbang River Basin (LRB), located in the equatorial tropics of Malaysian Borneo, have been characterised through Mann-Kendall and Spearman’s Rho non-parametric tests. Rainfall from 13 rain gauge stations in the LRB for the period 1948–2016 was examined in the present study. Basic statistical analysis of rainfall in the region indicates normal distribution, low missing percentage and homogenous characteristics of precipitation. Annual and seasonal rainfall in the LRB shows spatial variation while considering different rain gauge stations. In annual rainfall, eight stations showed a decreasing trend and five stations showed an increasing trend. Rain gauge stations which showed a statistically significant increase in annual rainfall were Limbang DID (2.77 and 2.85 mm/year) and Long Napir (3.65 and 3.77 mm/year). In recognising the two annual monsoon seasons in this area, a significant increase in rainfall was noticed in Long Napir (2.79 and 2.88 mm/year) during the Southwest monsoon (SWM) period. During the Northeast monsoon (NEM), along with Long Napir (3.90 and 3.95 mm/year), Limbang DID (2.86 and 3.02 mm/year), Pandaruan (1.82 and 1.87 mm/year) and Medamit Nanga (1.93 and 2.00 mm/year) also showed a significant increase in rainfall. At the same time, a distinct trend was noticed in rainfall amounts during the inter-monsoon (IM) periods. During the first inter-monsoon month (April), seven rain gauge stations showed an increasing trend in rainfall, whereas in the second inter-monsoon month (October), nine stations showed a decreasing rainfall trend. In April, Long Napir (1.86 and 1.95 mm/year) indicated a significant increasing trend, whereas in the month of October, the rain gauge station at Ukong showed a significant decreasing trend (− 2.45 and − 2.37 mm/year). Though minor spatial changes in trend characteristics were observed among the rain gauge stations, the LRB as a whole showed a consistent increasing (significant and non-significant) trend in annual and seasonal rainfall.

     

Forest biomonitoring of the largest Slovene thermal power plant with respect to reduction of air pollution

The condition of the forest ecosystem in the vicinity of the largest Slovene power plant [the ?o?tanj Thermal Power Plant (?TPP)] was monitored during the period 1991–2008 by determining the total concentration of sulphur, ascorbic acid and chlorophyll in Norway spruce needles. After 1995, the introduction of cleaning devices at the ?TPP dramatically reduced the former extremely high SO₂ and dust emissions. The most significant findings of this comprehensive, long-duration survey are as follows: (1) the chosen parameters are suitable bioindicators of stress caused by air pollution in Norway spruce needles; they reflect both spatial and temporal variations in air pollution as well as the degree of efficiency of the cleaning devices; (2) observations show that the physiological condition of Norway spruce in northern Slovenia has significantly improved since 1995, when the first desulphurization device at ?TPP was built, together with a reduction in the area influenced by pollution from ?TPP; (3) metabolic processes in spruce needles react to air pollution according to the severity of the pollution and the length of exposure; exposure to high SO₂ ambient levels and/or spread over a long duration can damage the antioxidant defence mechanisms of spruce trees as well as diminishing the concentration of ascorbic acid; (4) a reduction in the exposure to air pollution improves the vitality of the trees (e.g. higher concentrations of total (a?+?b) chlorophyll), as well as restoring their defence capabilities as shown by higher concentrations of ascorbic acid; and (5) forest monitoring should be continued and focused on integrating the effects of multiple stressors, which can additionally affect a forest ecosystem.     

The influence of estuarine water quality on cover of barnacles and Enteromorpha spp.

The influence of ambient water quality on the settlement of barnacles and the green alga Enteromorpha spp. to an artificial substratum in the estuaries of Sydney, Australia, was investigated to test the efficacy of both groups of organisms as indicators of changes in water quality due to urban stormwater runoff and/or sewage overflows. Wooden settlement panels were immersed for 4 months on 17 occasions between 1996 and 2005 at 11 locations known to vary in water-quality parameters (conductivity, total uncombined ammonia, oxidised nitrogen, total nitrogen, filterable phosphorus, total phosphorus, faecal coliforms and chlorophyll-a) and ambient meteorological conditions (total rainfall, maximum rainfall). Water-quality data were collected during the time that the settlement panels were deployed. Cover of barnacles was highly variable among locations (range 1.2?C55.2%). Hierarchical partitioning found that chlorophyll-a, total phosphorus and total nitrogen had significant independent positive effects on barnacle cover. Together, these variables explained 26% of the variation in barnacle cover. Mean cover of Enteromorpha spp., however, did not vary significantly among locations suggesting that other potentially more important factors are influencing its settlement and growth. The results of this study suggest that barnacle cover is likely to be a useful indicator of some components of water quality.     

Seasonal variation in the acute effects of ozone on premature mortality among elderly Japanese

We conducted a multicity time-series study using monitoring data to assess seasonal patterns of short-term ozone–mortality association among elderly aged 65 years and over in Japan. Daily exposure to ambient ozone was computed using hourly measurements of photochemical oxidants available at multiple monitoring stations in each city. Effects of ozone on daily all-cause non-accidental, cardiovascular, and respiratory mortality were estimated using distributed lag linear models, controlling for confounding by temporal, day of the week, temperature, and flu epidemics. City-level effect estimates were combined using inverse variance meta-analysis. In spring and autumn, a 10-ppbv increase of daily maximum 8-h average ozone concentration in the previous 3 days was associated with 0.69 % (95 % confidence interval (CI): 0.27–1.10), 1.07 % (0.34–1.82), and 1.77 % (0.78–2.77) increases in daily all-cause, cardiovascular, and respiratory mortality, respectively. Forward displacement of respiratory mortality was large during the cold season despite lower ozone concentration. Results were generally independent of fine particulate matter and nitrogen dioxide. Findings suggest significant mortality effects of short-term ozone exposure among the elderly during the moderate season. Those with underlying respiratory diseases were susceptible, even during winter.     

Lead (Pb) quantification in potable water samples: implications for regulatory compliance and assessment of human exposure

Assessing the health risk from lead (Pb) in potable water requires accurate quantification of the Pb concentration. Under worst-case scenarios of highly contaminated water samples, representative of public health concerns, up to 71–98 % of the total Pb was not quantified if water samples were not mixed thoroughly after standard preservation (i.e., addition of 0.15 % (v/v) HNO₃). Thorough mixing after standard preservation improved recovery in all samples, but 35–81 % of the total Pb was still un-quantified in some samples. Transfer of samples from one bottle to another also created high errors (40–100 % of the total Pb was un-quantified in transferred samples). Although the United States Environmental Protection Agency’s standard protocol avoids most of these errors, certain methods considered EPA-equivalent allow these errors for regulatory compliance sampling. Moreover, routine monitoring for assessment of human Pb exposure in the USA has no standardized protocols for water sample handling and pre-treatment. Overall, while there is no reason to believe that sample handling and pre-treatment dramatically skew regulatory compliance with the US Pb action level, slight variations from one approved protocol to another may cause Pb-in-water health risks to be significantly underestimated, especially for unusual situations of “worst case” individual exposure to highly contaminated water.     

ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya

The present study explores for the first time the possibility of modelling sediment concentration with artificial neural networks (ANNs) at Gangotri, the source of Bhagirathi River in the Himalaya. Discharge, rainfall and temperature have been considered as the main controlling factors of variations in sediment concentration in the dynamic glacial environment of Gangotri. Fourteen feed forward neural networks with error back propagation algorithm have been created, trained and tested for prediction of sediment concentration. Seven models (T1-T7) have been trained and tested in the non-updating mode whereas remaining seven models (T1a-T7a) have been trained in the updating mode. The non-updating mode refers to the scenario where antecedent time (previous time step) values are not used as input to the model. In case of the updating mode, antecedent time values are used as network inputs. The inputs applied in the models are either the variables mentioned above as individual factors (single input networks) or a combination of them (multi-input networks). The suitability of employing antecedent time-step values as network inputs has hence been checked by comparative analysis of model performance in the two modes. The simple feed forward network has been improvised with a series parallel non-linear autoregressive with exogenous input (NARX) architecture wherein true values of sediment concentration have been fed as input during training. In the glacial scenario of Gangotri, maximum sediment movement takes place during the melt period (May–October). Hence, daily data of discharge, rainfall, temperature and sediment concentration for five consecutive melt periods (May–October, 2000–2004) have been used for modelling. High Coefficient of determination values [0.77–0.88] have been obtained between observed and ANN-predicted values of sediment concentration. The study has brought out relationships between variables that are not reflected in normal statistical analysis. A strong rainfall: sediment concentration and temperature: sediment concentration relationship is shown by the models which are not reflected in statistical correlation. It has also been observed that usage of antecedent time-step values as network inputs does not necessarily lead to improvement in model performance.     

Changes in the soft-bottom macrobenthic diversity and community structure from the ports of Mumbai, India

Soft-bottom macrobenthic diversity and community structure were assessed at Mumbai and Jawaharlal Nehru ports during three different periods between 2001 and 2002 (November 2001 post-monsoon 1, April/May 2002 pre-monsoon, and October 2002 post-monsoon 2). A total of 43 macrobenthic invertebrate species belonging to five phyla were recorded. Macrofaunal abundance (PM1 186, PreM 106, and PM2 31 ind m^?2) and species diversity index (PM1 0.87, PreM 0.73, and PM2 0.30) were very low in all the seasons. Polychaetes were the most dominant macrobenthic group (72.09%) followed by decapoda, amphipoda, and bivalves (4.56%). Canonical correspondence analysis showed that sediment texture, temperature, and suspended particulate matter were the most important environmental variables influencing polychaete species composition. Significant seasonal variations were observed, influenced by dissimilar monsoonal patterns. Macrobenthic population density during November 2001 was higher than that of October 2002 post-monsoon season. Pre-monsoon season recorded more carnivorous polychaete species than post-monsoon seasons. The present study showed lower values of polychaete diversity index in all the seasons compared to earlier studies. Out of 31 polychaete species, 19 have been reported for the first time from this area. Polychaete species and Glycera longipinnis, Paraprionospio pinnata, and Cossura coasta recorded from 1985 to 1986 were also observed in the present study. Species like Sigambra constricta, Perinereis cavifrons, Prionospio polybranchiata, and Parheteromastus tenuis were not recorded in the present study, although they were observed during earlier studies in this area.     

Comprehensive inter-comparison of INSAT multispectral rainfall algorithm estimates and TMPA 3B42-RT V7 estimates across different climate regions of India during southwest monsoon period

The main objective of this study is to validate and inter-compare two Near-Real-Time Satellite Rainfall Estimates (NRT-SREs): INSAT Multispectral Rainfall Algorithm (IMSRA, simple blended product) and TMPA 3B42-RT V7 (3B42-RT, multisatellite product) across India. This study aims to provide some insight into the error characteristics of both the NRT-SREs to the algorithm developers and end users by inter-comparing the daily rainfall estimates during the southwest monsoon period of 2010–2013. This study utilizes various volumetric statistics and categorical statistics to understand and evaluate the performance of NRT-SREs in terms of both spatial and volumetric error characteristics (hit, miss, and false error) at different rainfall thresholds across different Köppen–Geiger climate regions of India using the gridded gauge data provided by Indian Meteorological Department as reference dataset. A detailed statistical evaluation shows that the 3B42-RT performs comparatively better than the IMSRA across India. The results indicate that both IMSRA and 3B42-RT have a general tendency of overestimating the low rainfall rates (0–2.5 mm/day) and underestimating the high rainfall rates (>?35.5 mm/day). At lower threshold values (0 and 2.5 mm/day), it is found that the miss error is dominant in IMSRA, whereas the false error is dominant in 3B42-RT. As the threshold increases (7.5 and 35.5 mm/day), both the miss and false errors increase in both SREs. Additionally, the spatial analysis of the results clearly indicate that the performance of the tested NRT-SREs is not uniform across different climatic regions, an important aspect to be considered for development/improvement of the tested NRT-SRE algorithms.     

Analysis of spatial and seasonal distributions of MODIS aerosol optical properties and ground-based measurements of mass concentrations in the Yellow Sea region in 2009

Satellite-retrieved data on aerosol optical depth (AOD) and Ångström exponent (AE) using a moderate resolution imaging spectrometer (MODIS) were used to analyze large-scale distributions of atmospheric aerosols in East Asia. AOD was relatively high in March (0.44?±?0.25) and low in September (0.24?±?0.21) in the East Asian region in 2009. Sandstorms originating from the deserts and dry areas in northern China and Mongolia were transported on a massive scale during the springtime, thus contributing to the high AOD in East Asia. However, whereas PM10 with diameters ≤10 μm was the highest in February at Anmyon, Cheongwon, and Ulleung, located leeward about halfway through the Korean Peninsula, AOD rose to its highest in May. The growth of hygroscopic aerosols attendant on increases in relative humidity prior to the Asian monsoon season contributed to a high AOD level in May. AE typically appears at high levels (1.30?±?0.37) in August due to anthropogenic aerosols originating from the industrial areas in eastern China, while AOD stays low in summer due to the removal process caused by rainfall. The linear correlation coefficients of the MODIS AOD and ground-based mass concentrations of PM10 at Anmyon, Cheongwon, and Ulleung were measured at 0.4~0.6. Four cases (6 days) of mineral dustfall from sandstorms and six cases (12 days) of anthropogenically polluted particles were observed in the central area of the Korean Peninsula in 2009. PM10 mass concentrations increased at both Anmyon and Cheongwon in the cases of mineral dustfall and anthropogenically polluted particles. Cases of dustfall from sandstorms and anthropogenic polluted particles, with increasing PM10 mass concentrations, showed higher AOD values in the Yellow Sea region.     

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.