Spatial and Seasonal Variation of O and H Isotopes in the Jiulong River, Southeast China

Han

et al. 2019

Water

Self Cite

River water samples between August 2017 (wet season) and March 2018 (dry season) from the Mun River Basin in northeast Thailand were collected and their dissolved heavy metals concentrations (Al, Mn, Fe, Cu, Zn, and Ba) were measured. Compared with international drinking water guidelines, Mn was the dominant pollutant in the dry season. The correlation analysis (CA) suggested that similar sources were shown in each element pair of Al-Fe, Mn-Zn, and Fe-Ba in both seasons. The principal component analysis (PCA) results showed that the dominant source of dissolved heavy metals was sedimentary inputs or colloid destabilization in the wet season, while anthropogenic inputs were the main sources in the dry season, such as agricultural runoff, industrial effluents, and domestic discharge. On the basis of water quality index (WQI), water at most sites in the wet and dry seasons can be categorized as excellent water, except for a few sites with substandard values. The river water posed no significant health risks according to the health risk assessment, but Mn, Fe, and Ba needed to be paid more attention due to the relatively high values. Al, Fe, and Ba were the main dissolved heavy metals flowing into the Mekong River, and Cu contributed to the background value in the Mekong river.

Section: Sample Collection and Storagementioning

confidence: 99%

Spatial and Temporal Variation of Dissolved Heavy Metals in the Mun River, Northeast Thailand

Han

et al. 2019

Water

Self Cite

“…Unfortunately, systematic isotopic studies concerning large-scale catchments [5,[8][9][10][11][12][13][14] are unevenly distributed around the world. Consequently, the GNIR database (Global Network of Isotopes in Rivers, [4]) lacks information in some specific areas, including Northern Italy, where the main Italian rivers (Po and Adige) are not taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

The Po River Water Isotopes during the Drought Condition of the Year 2017

Marchina

Natali

Bianchini

2019

Water

The year 2017 was anomalously warm and dry across the whole Italian Peninsula, and the paucity of precipitation was emphasized during the extreme summer drought of the main Italian river, i.e., the Po river, which was characterized by a discharge persistently below 600 m 3 /s (in spite of the average discharge of 1500 m 3 /s). During these extreme conditions, the Po river oxygen and hydrogen stable isotopes (δD, δ 18 O) displayed a relation (δD = 6.1*δ 18 O − 6.6) significantly different from that recorded in the previous investigation of the years 2012-2014 (δD = 7.5*δ 18 O + 6.5). The lowering of the slope and the negative intercept clearly reflect the transition toward arid conditions that characterized the investigated period. The difference is expressed by the derivative parameter Line-Conditioned excess (LC-exc), which better describes the compositional difference of Po river water in the year 2017 with respect to that of the period 2012-2014, when the system was less affected by warm or dry conditions and the river discharge was more similar to the historical trends. The isotopic anomaly observed in 2017 throughout the river is even greater in the terminal part of the river, where in the meanders of the deltaic branches, the river flow progressively slows down, suffering significant evaporation. The isotopic signature of the water appears, therefore, an appropriate tool to monitor the watershed response to evolving environmental conditions. These sensitive isotopic parameters could be interpreted as "essential climate variables" (ECV) that are physical, chemical, or biological geo-referenced parameters that critically contribute to the characterization of Earth's climate. Future research needs to find relationships between ECV (including the water stable isotopes) and the evolution of ecosystems, which especially in the Mediterranean area, appear to be fragile and severely affected by natural and anthropogenic processes.

“…Secondary forest land and shrub land: 45%; agricultural land: 50% Note: MAT, mean annual temperature; MAP, mean annual precipitation. Data were cited from [30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

“…Public Health 2020, 17, x 6 of Soil properties, including (a) clay percent, (b) silt percent, (c) sand percent, (d) soil pH, (e) SOC content, and (f) SON content, in the soils of the JRC and CC. The data of the JRC and CC are cited from[30][31][32][33][34][35][36][37]. SOC, soil organic carbon; SON, soil organic nitrogen.…”

mentioning

confidence: 99%

Effects of Soil Properties on K Factor in the Granite and Limestone Regions of China

Zhang

et al. 2020

IJERPH

Self Cite

Soil erosion has become a serious ecological problem in many catchments. Soil erodibility K factor can be estimated based on a series of soil properties, however, the identification of dominant soil properties that affect K factor prediction at different soil types has been little concerned. In this study, 3 soil profiles from the Jiulongjiang River Catchment (JRC) of granite region in Fujian province and 18 soil profiles from the Chenqi Catchment (CC) of karst region in Guizhou province were selected. Soil properties, including soil particle size distribution, soil organic carbon (SOC) and soil organic nitrogen (SON) content, and soil pH, were determined, and the K factors were estimated in the erosion productivity impact calculator (EPIC) model. The soils in the granite region were characteristic for coarse texture, low SOC and SON, and strong acidity compared with limestone soils. Although the K factors in both regions ranged from 0.009 to 0.018, they were overestimated in limestone soils due to frequent soil aggregation, which enhanced soil permeability, hence reduced soil erodibility. The results of principal component analysis (PCA) and structural equation model (SEM) showed that (1) K factor estimation in the soils of the granite region mainly depended on soil texture, of which silt was the most important factor; (2) while K factor in limestone soils was mainly controlled by soil organic matter (SOM) content, other soil properties, including soil pH, clay and silt contents, could indirectly affect prediction of K factor by affecting SOM accumulation.