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Chromophoric dissolved organic matter (CDOM) in riverine systems can be affected by environmental conditions and land-use, and thus could provide important information regarding human activities in surrounding landscapes. The optical properties of water samples collected at 42 locations across the Liaohe River (LHR, China) watershed were examined using UV-Vis and fluorescence spectroscopy to determine CDOM characteristics, composition and sources. Total nitrogen (TN) and total phosphorus (TP) concentrations at all sampling sites exceeded the GB3838-2002 (national quality standards for surface waters, China) standard for Class V waters of 2.0 mg N/L and 0.4 mg P/L respectively, while trophic state index (TSI M ) indicated that all the sites investigated were mesotrophic, 64% of which were eutrophic at the same time. Redundancy analysis showed that total suspended matter (TSM), dissolved organic carbon (DOC), and turbidity had a strong correlation with CDOM, while the other parameters (Chl a, TN, TP and TSI M ) exhibited weak correlations with CDOM absorption. High spectral slope values and low SUVA254 (the specific UV absorption) values indicated that CDOM in the LHR was primarily comprised of low molecular weight organic substances. Analysis of excitation-emission matrices contour plots showed that CDOM in water samples collected from upstream locations exhibited fulvic-acid-like characteristics whereas protein-like substances were most likely predominant in samples collected in estuarine areas and downstream from large cities. These patterns were interpreted as indicative of water pollution from urban and industrial activities in several downstream sections of the LHR watershed.

Chromophoric dissolved organic matter (CDOM) plays an important role in aquatic systems, but high concentrations of organic materials are considered pollutants. The fluorescent component characteristics of CDOM in urban waters sampled from Northern and Northeastern China were examined by excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC) to investigate the source and compositional changes of CDOM on both space and pollution levels. One humic-like (C1), one tryptophan-like component (C2), and one tyrosine-like component (C3) were identified by PARAFAC. Mean fluorescence intensities of the three CDOM components varied spatially and by pollution level in cities of Northern and Northeastern China during July-August, 2013 and 2014. Principal components analysis (PCA) was conducted to identify the relative distribution of all water samples. Cluster analysis (CA) was also used to categorize the samples into groups of similar pollution levels within a study area. Strong positive linear relationships were revealed between the CDOM absorption coefficients a(254) (R (2) = 0.89, p < 0.01); a(355) (R (2) = 0.94, p < 0.01); and the fluorescence intensity (F max) for the humic-like C1 component. A positive linear relationship (R (2) = 0.77) was also exhibited between dissolved organic carbon (DOC) and the F max for the humic-like C1 component, but a relatively weak correlation (R (2) = 0.56) was detected between DOC and the F max for the tryptophan-like component (C2). A strong positive correlation was observed between the F max for the tryptophan-like component (C2) and total nitrogen (TN) (R (2) = 0.78), but moderate correlations were observed with ammonium-N (NH4-N) (R (2) = 0.68), and chemical oxygen demand (CODMn) (R (2) = 0.52). Therefore, the fluorescence intensities of CDOM components can be applied to monitor water quality in real time compared to that of traditional approaches. These results demonstrate that EEM-PARAFAC is useful to evaluate the dynamics of CDOM fluorescent components in urban waters from Northern and Northeastern China and this method has potential applications for monitoring urban water quality in different regions with various hydrological conditions and pollution levels.

This study investigated human-induced long-term wetland degradation that occurred in the Sanjiang Plain. Results from analyzing land-use/land-cover data sets derived from remotely sensed Landsat Multispectral Scanner/Thematic Mapper imagery for four time points showed that wetlands in the Sanjiang Plain have been severely transformed, and the area of wetlands decreased by 38 % from 1976 to 1986, by 16 % from 1986 to 1995, and by 31 % from 1995 to 2005. This study showed that transition to agricultural cultivation accounted for 91 % of wetland losses, whereas transition to grassland and forest accounted for 7 % of the wetlands losses. Institutional strategies and market policies probably exerted great impacts on agricultural practice that directly or indirectly influenced the decrease in wetlands. This study also indicated that an increased population likely led to wetland conversion to cropland by showing a high correlation between population and cropland (R (2) = 0.92, P < 0.001). Wetland loss occurred during later time intervals at a low rate. This study suggests that the existing wetland-protection measures in the Sanjiang Plain should be reinforced further because of possible environmental consequences of wetland loss, such as enhanced soil carbon emission, changed hydrological cycling, and regional temperature increase.

Nuisance cyanobacterial blooms degrade water resources through accelerated eutrophication, odor generation, and production of toxins that cause adverse effects on human health. Quick and effective methods for detecting cyanobacterial abundance in drinking water supplies are urgently needed to compliment conventional laboratory methods, which are costly and time consuming. Hyperspectral remote sensing can be an effective approach for rapid assessment of cyanobacterial blooms. Samples (n=250) were collected from five drinking water sources in central Indiana (CIN), USA, and South Australia (SA), which experience nuisance cyanobacterial blooms. In situ hyperspectral data were used to develop models by relating spectral signal with handheld fluorescence probe (YSI 6600 XLM-SV) measured phycocyanin (PC in cell/ml), a proxy pigment unique for indicating the presence of cyanobacteria. Three-band model (TBM), which is effective for chlorophyll-a estimates, was tuned to quantify cyanobacteria coupled with the PC probe measured cyanobacteria. As a comparison, two band model proposed by Simis et al. (Limnol Oceanogr, 50(11): 237-245, 2005; denoted as SM05) was paralleled to evaluate TBM model performance. Our observation revealed a high correlation between measured and estimated PC for SA dataset (R (2) =0.96; range: 534-20,200 cell/ml) and CIN dataset (R (2) =0.88; range: 1,300-44,500 cell/ml). The potential of this modeling approach for imagery data were assessed by simulated ESA/Centinel3/OLCI spectra, which also resulted in satisfactory performance with the TBM for both SA dataset (RMSE % =26.12) and CIN dataset (RMSE % =34.49). Close relationship between probe-measured PC and laboratory measured cyanobacteria biovolume was observed (R (2) =0.93, p<0.0001) for the CIN dataset, indicating a stable performance for PC probe. Based on our observation, field spectroscopic measurement coupled with PC probe measurements can provide quantitative cyanobacterial bloom information from both relatively static and flowing inland waters. Hence, it has promising implications for water resource managers to obtain information for early warning detection of cyanobacterial blooms through the close association between probe measured PC values and cyanobacterial biovolume via remote sensing modeling.

In the past five decades, the wetlands in the Muleng-Xingkai Plain, Northeast China, have experienced rapid shrinkage and fragmentation. In this study, wetlands cover change and agricultural cultivation were investigated through a time series of thematic maps from 1954, and Landsat satellite images representing the last five decades (1976, 1986, 1995, 2000, and 2005). Wetlands shrinkage and fragmentation were studied based on landscape metrics and the land use changes transition matrix. Furthermore, the driving forces were explored according to socioeconomic development and major natural environmental factors. The results indicate a significant decrease in the wetlands area in the past five decades, with an average annual decrease rate of 9004 ha/yr. Of the 625,268 ha of native wetlands in 1954, approximately 64% has been converted to other land use types by 2005, of which conversion to cropland accounts for the largest share (83%). The number of patches decreased from 1272 (1954) to 197 (1986) and subsequently increased to 326 (2005). The mean patch size changed from 480 ha (1954) to 1521 ha (1976), and then steadily decreased to 574 ha (2005). The largest patch index (total core area index) indicates wetlands shrinkage with decreased values from 31.73 (177,935 ha) to 3.45 (39,421 ha) respectively. Climatic changes occurred over the study period, providing a potentially favorable environment for agricultural development. At the same time population, groundwater harvesting, and fertilizer application increased significantly, resulting in wetlands degradation. According to the results, the shrinkage and fragmentation of wetlands could be explained by socioeconomic development and secondarily aided by changing climatic conditions., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. Water sampling works were conducted on 15 July 2007 and 13 September 2008 concurrent with the Indian Remote-Sensing Satellite (IRS-P6) overpass of the Shitoukoumen Reservoir. Both empirical regression and back-propagation artificial neural network (ANN) models were established to estimate Chl-a and TSM concentration with both in situ and satellite-received radiances signals. It was found that empirical models performed well on the TSM concentration estimation with better accuracy (R (2) = 0.94, 0.91) than their performance on Chl-a concentration (R (2) = 0.62, 0.75) with IRS-P6 imagery data, and the models accuracy marginally improved with in situ spectra data. Our results indicated that the ANN model performed better for both Chl-a (R (2) = 0.91, 0.82) and TSM (R (2) = 0.98, 0.94) concentration estimation through in situ collected spectra; the same trend followed for IRS-P6 imagery data (R (2) = 0.75 and 0.90 for Chl-a; R (2) = 0.97 and 0.95 for TSM). The relative root mean square errors (RMSEs) from the empirical model for TSM (Chl-a) were less than 15% (respectively 27.2%) with both in situ and IRS-P6 imagery data, while the RMSEs were less than 7.5% (respectively 18.4%) from the ANN model. Future work still needs to be undertaken to derive the dynamic characteristic of Shitoukoumen Reservoir water quality with remotely sensed IRS-P6 or Landsat-TM data. The algorithms developed in this study will also need to be tested and refined with more imagery data acquisitions combined with in situ spectra data.

In the remote sensing of chlorophyll-a (Chla) in inland Case-II waters, the assumption that the optical parameter of Chla specific absorption coefficient a*ph remains constant usually restrains application of many models. In this paper, we presented a newly developed model [Rrs(-1)(lambda1) - Rrs(-1)(lambda2)] x Rrs(lambda3) x a*ph(-1)(lambda1) which was improved on a previous three-band model to isolate interferences from a*ph. In terms of the importance of water optical properties in the model development, spectral and absorption characteristics were analyzed for Shitoukoumen Reservoir and Songhua Lake in Northeast China, as typical examples of inland Case-II waters. Both waters showed overwhelming absorption sum of tripton and chromophoric dissolved organic matter (CDOM) owing to their relatively low Chla contents (1.53 to 19.35 microgl(-1)). According to the optical characteristics of waters studied, optimal positions for lambda (1), lambda (2) and lambda (3) were spectrally tuned to be at 664, 684 and 705 nm, respectively. The model allowed accurate Chla estimation with a determination coefficient (R (2)) close to 0.98 and a root mean square error (RMSE) of 0.87 microgl(-1). Comparison of different models further showed the stability of the improved model, implying its potential use in water color remote sensing. Although the findings underline the rationale behind the improved model, an extensive database containing data in different water conditions and water types is required to generalize its application.

In this study, we present the application of the passive microwave emission models to snow-cover environment monitoring and assessment in Northeast China. The study employs the radiative transfer function and strong fluctuation theory to develop the models. We used the exponential form of a spherical symmetric correlation function to describe random permittivity fluctuations. From strong fluctuation, we then obtained the phase matrix and extinction coefficients of snow-packs for the spherical symmetric correlation function. We also used the vector radiative transfer formula for the layer of a random medium by solving Gaussian quadrature and eigen analysis. By comparing the brightness temperatures at 5, 10.7, 18, and 37 GHz, the modelling results agreed with experimental data of dry-snow physical parameters as measured in the fieldwork.

Due to human impact under climatic variations, western part of Northeast China has suffered substantial land degradation during past decades. This paper presents an integrated study of expansion process of salinized wasteland in Da'an County, a typical salt-affected area in Northeast China, by using Geographic Information Systems (GIS) and remote sensing. The study explores the temporal and spatial characteristics of salinized wasteland expansion from 1954 to 2004, and land use/cover changes during this period. During the past 50 years, the salinized wasteland in study area have increased by 135,995 ha, and in 2004 covers 32.31% of the total area, in the meantime grassland has decreased by 104,697 ha and in 2004 covers only 13.15% of the study area. Grasslands, croplands and swamplands were found the three main land use types converted into salinized wasteland. Land use/cover changes shows that between 1954 and 2004, 48.6% of grasslands, 42.5% of swamplands, and 14.1% of croplands were transformed into salinized wasteland, respectively. Lastly, the major factors influencing salinized wasteland expansion and land use/cover changes were also explored. In general, climatic factors supplied a potential environment for soil salinization. Human-related factors, such as policy, population, overgrazing, and intensified and unreasonable utilization of land and water resources are the main causes of salinized wasteland expansion.

In this study, we present the digital evaluation of Landsat TM data and field spectral measurements for retrieving chlorophyll-a (chl-a) concentration and trophic state index in Lake Chagan of Northeast China. Chl-a concentration of the lake can be estimated from the band ratio (TM4/TM3) and the field spectral data at 670 nm (absorption peak) and at 700 nm (reflectance peak). The results show that the best determination coefficient (R (2)) is 0.67 from the TM data, by which chl-a distribution can be mapped. Based on chl-a determination from laboratory analysis, field spectral and TM data, the modified trophic state index (TSI(M)) was applied to assess the lake's trophic state. With the available data in Lake Chagan, each algorithm demonstrates the similar result for assessing the lake's chl-a and trophic state. Our results indicate that Landsat TM and field spectral data could be used effectively to determine chl-a concentration and evaluate the trophic state of Lake Chagan in the study.

Agricultural activities, especially reclamation, are considered major threats to the wetland ecosystems in Sanjiang Plain, the largest concentrated area of the freshwater wetlands in China. In the past decades, the area of the cultivated land and its grain production have been increased at the cost of wetlands shrinkage. The large-scale land reclamation severely affected the ecosystems in this region. However, such effects at the regional scale are seldom evaluated quantitatively. We used three datasets of LANDSAT MSS and/or TM imagery to estimate the area changes and the transition of land use types from 1980 to 2000. We also valued changes in ecosystem services delivered by each land category using value coefficients published by Costanza et al. Sensitivity analysis suggested that these estimates were relatively robust. Finally, the contribution of various ecosystem functions was ranked to the overall value of the ecosystem services in this study. According to our estimates, the total annual ecosystem service values in Sanjiang Plain have declined by about 40% between 1980 and 2000 (156284-182572.18 million US dollars in total over 20 years). This substantial decline is largely attributed to the 53.4% loss of wetlands. For individual ecosystem functions, waste treatment, water supply and disturbance regulation account for more than 60% to the total ecological values. During those two decades, the contribution of disturbance regulation, cultural and recreation decreased, while the contribution of water regulation, nutrient cycling, food production, raw materials and climate regulation increased during the same period. We also put forward a few proposals concerning the future land use policy formulation and sustainable ecosystems. They are adjusting the 'food first' agricultural policy, establishing more nature reserves for wetlands, creating systems for the rational use of water, harnessing the degraded cultivated land and encouraging eco-tourism.