Search Results (3)

Soil is one of the principal substrates of human life and can serve as a reservoir of water and nutrients. Humic substances, indicators of soil fertility, are dominant in soil organic matter. However, soil degradation has been occurring all over the world, usually by soil salinization. Sustainable soil productivity has become an urgent problem to be solved. In this study, fluorescence excitation-emission matrices integrated with parallel factor analysis (PARAFAC) and canonical correlation analysis (CCA) were applied to characterize the components of fulvic acid (FA) and humic acid (HA) substances extracted from soils from the Liaohe River Delta, China. Along the saline gradient, soil samples with four disparate depths were gathered from four aboriginal halophyte communities, i.e., the Suaeda salsa Community (SSC), Chenopodium album Community (CAC), Phragmites australis Community (PAC), and Artemisia selengensis Community (ASC). Six components (C1 to C6) were identified in the FA and HA substances. The FA dominant fractions accounted for an average of 45.81% of the samples, whereas the HA dominant fractions accounted for an average of 42.72%. Mature levels of the HA fractions were higher than those of the FA fractions, so was the condensation degree, microbial activity, and humification degree of the FA fractions. C1 was associated with the ultraviolet FA, C2 was referred to as visible FA, C3 and C4 were relative to ultraviolet HA, C5 represented microbial humic-like substances (MH), and C6 referred to visible HA. C1, C2, C5 and C6 were latent factors of the FA fractions, determined using the CCA method and could possibly be used to differentiate among the SSC, CAC, PAC and ASC samples. C3, C4, C6 and C5 were latent factors of the HA fractions, which might be able to distinguish the ASC samples from the SSC, CAC and PAC samples. Fluorescence spectroscopy combined with the PARAFAC and CCA is a practical technique that is applied to assess the humic substance content of salinized soils. Full article

This study aims to investigate the effects of land use/cover change (LUCC) and climate change on wetland evapotranspiration (ET), and to identify the importance of the main effect factors in the spatiotemporal dynamics of ET. In the wetland of Liaohe River Delta, China, the ET of eight growing seasons during 1985–2017 was estimated using the surface energy balance algorithm for land (SEBAL) model with Landsat and meteorological data. Results show that the average relative error of regional ET estimated by the SEBAL model is 9.01%, and the correlation coefficient between measured and estimated values is 0.61, which indicates that the estimated values are reliable. This study observed significant spatial and temporal variations in ET across the region of interest. The distribution of the average and relative change rate of daily ET in the study area showed bimodal characteristics, that is, the lowest trough occurred in 2005, whereas crests occurred in 1989 and 2014. Simultaneously, the daily ET varied with the land use/cover area. Regional daily ET displays highly heterogeneous spatial distribution, that is, the ET of different land uses/cover types in descending order is as follows: water body, wetland vegetation, non-wetland vegetation, and non-vegetation (except water area). Therefore, the spatial pattern of ET is relevant to the land use/cover types to some extent. In addition, the temporal variation of wetland ET is closely related to landscape transformation and meteorological factor change. A strong correlation was found between ET and the weighted values of meteorological factors, with a correlation coefficient of 0.69. Meanwhile, the annual fluctuations of daily ET and the weighted values were relatively similar. Therefore, the findings highlight the importance of using cheap and readily available remote sensing data for estimating and mapping the variations in ET in coastal wetland. Full article

Heavy metal pollution in soils and sediments is becoming a matter of wide concern, this study was carried out in Dawa County of the Liaohe River Delta, with the aim of exploring the impacts of land use levels on heavy metal contamination of soil and sediment. A total of 129 soil samples were collected in different land use intensities (LUI). Soil metals (Fe, Mn, Cd, Cr, Cu, Ni, Pb and Zn) and soil salinity, pH, soil organic carbon (SOC), nitrate nitrogen (NO₃⁻-N), available phosphorus (AP) and grain sizes were analyzed. Correlation analysis indicated that SOC and grain size played important roles in affecting the heavy metal distribution. The factor analysis results indicated that heavy metal contamination was most probably caused by industrial and agricultural wastewater discharges, domestic sewage discharge and atmospheric deposition. Using ANOVA, it found that human activities significantly changed soil physic-chemical properties through soil erosion, leaching and fertilizer application, further affecting the behaviors of heavy metals in the soil and sediments. The anthropogenic factors could lead to potential environmental risk, as indicated by the Geo-accumulation index (I_geo) results of heavy metals. Overall, the heavy metals generally had approached or even exceeded moderately polluted (0 < I_geo < 1, 1 < I_geo < 2), but the Pb and Cu pollution level was low (I_geo < 0), and the Cd pollution level was moderately or strongly polluted (2 < I_geo < 3, 3 < I_geo < 4) in the five land use levels. This study will provide valuable information for appropriately determining how land should be used in future reclamation areas, as well as for the sustainable management of estuarine areas around the world. Full article