Water quality safety is the key factor to maintain the ecosystem service functions of lakes. Field investigations and statistical analyses were carried out to study the water quality of a large, agriculture-stressed lakes (e.g., Chagan Lake) in Northeast China. The hydro-chemical properties of the Chagan Lake are HCO₃·CO₃-Na. Nutrient (N and P) and non-nutrient (pH and F⁻) were found to be the major factors that threaten water quality safety of the lake. The concentration of total nitrogen (TN) and total phosphorus (TP) was found to vary seasonally and at different locations. The overall lake water had mean TN and TP values of 2.19 mg/L and 0.49 mg/L, respectively, in summer. TN was the major factor for water quality deterioration in the western region of the lake, while TP was the principal factor in the other regions, as determined by a principal component analysis (PCA). Fluoride (F⁻) concentration in the lake water were related to the values of total dissolved solid (TDS), pH, and electrical conductivity (EC). In addition, eutrophication is a fundamental index that has been affecting the ecological evaluation of water quality. The results showed that trophic level index (TLI), trophic state index (TSI), and eutrophication index (EI) were evaluated to quantify the risk of eutrophication. However, TLI and TSI can better describe the purification effect of the wetland. These indices showed that the lake water was hyper-eutrophic in summer, with TLI, TSI, and EI values of 60.1, 63.0, and 66.6, respectively. Disparities in water quality were observed among whole areas of the lake. Overall, this study revealed that controlling agriculture drainage is crucial for lake water quality management. The study generated critical data for making water quality management plans to control the risk.

The salinization of freshwater lakes by agricultural activities poses a threat to many lake ecosystems around the world. Quantitative, medium- to long-term studies are needed to understand how some common agricultural practices, such as the discharge of crop irrigation in the vicinities of large lakes, may affect lake salinization. In this study, hydrological, hydrodynamics, water quality and meteorological datasets were used to analyze the long-term spatial-temporal variations of water salinities of a major lake, the Chagan Lake, in Northeast China. An integrated hydrodynamics-salinity model was used to simulate lake water salinity changes taking place at different times and locations, including (i) salt accumulations during a non-frozen period, and (ii) the time when water salinity may reach a significant threshold (1 psu) that jeopardizes a major environmental and economic value of this lake (i.e., the cultivation of local fish species). The results confirmed that Chagan Lake was indeed undergoing salinization in the ten year period between 2008 and 2018. The spatial-temporal patterns of the salinization processes were identified. For instance, (i) the mean salinity of the lake water was found to be 0.55 psu in the summer season of the region and 0.53 psu in the winter, and (ii) between May to October the salinity was up to 0.62 psu in the western region of the lake. The rate of salt accumulation was found to be 97 ton per annum during the non-frozen period. The simulation predicted that by 2024 the lake water will become sub-saline (salinity > 1.07 psu) which is toxic to fish species, if the current practice of irrigation discharge into the lake continues. In the scenario that the amount of irrigation discharges into the lake doubles, the western region of the lake will become sub-saline within one year, and then the whole lake within three years. Overall, this study has produced results that are useful to authorities around the world, for balancing the risks and benefits of developing crop irrigation fields in areas surrounding large freshwater lakes.

Background: Interferometric Synthetic Aperture Radar (InSAR) has become a promising technique for monitoring wetland water levels. However, its capability in monitoring wetland water level changes with Sentine-1 data has not yet been thoroughly investigated. Methods: In this study, we produced a multitemporal Sentinel-1 C-band VV-polarized SAR backscatter images and generated a total of 28 interferometric coherence maps for marsh wetlands of China’s Momoge National Nature Reserve to investigate the interferometric coherence level of Sentinel-1 C-VV data as a function of perpendicular and temporal baseline, water depth, and SAR backscattering intensity. We also selected six interferogram pairs acquired within 24 days for quantitative analysis of the accuracy of water level changes monitored by Sentinel-1 InSAR. The accuracy of water level changes determined through the Sentinel-1 InSAR technique was calibrated by the values of six field water level loggers. Results: Our study showed that (1) the coherence was mainly dependent on the temporal baseline and was little affected by the perpendicular baseline for Sentinel-1 C-VV data in marsh wetlands; (2) in the early stage of a growing season, a clear negative correlation was found between Sentinel-1 coherence and water depth; (3) there was an almost linear negative correlation between Sentinel-1 C-VV coherence and backscatter for the marsh wetlands; (4) once the coherence exceeds a threshold of 0.3, the stage during the growing season, rather than the coherence, appeared to be the primary factor determining the quality of the interferogram for the marsh wetlands, even though the quality of the interferogram largely depends on the coherence; (5) the results of water level changes from InSAR processing show no agreement with in-situ measurements during most growth stages. Based on the findings, we can conclude that although the interferometric coherence of the Sentinel-1 C-VV data is high enough, the data is generally unsuitable for monitoring water level changes in marsh wetlands of China’s Momoge National Nature Reserve.

Irrigation practice for rice culture can be especially challenging in areas with limited water supply and soil salinization. In this study, we carried out a field experiment to assess the effects of different water discharge frequencies on soil salt content, rice yield and water use efficiency on a saline-sodic soil in a semi-arid region of Northeast China. The experiment comprised of three frequency levels of discharge [9-time (I-9-30), 6-time (I-6-30) and 3-time (I-3-30) discharge, all followed with a 30-mm irrigation] in comparison with the traditional irrigation practice of 2-time discharge followed with an 80-mm irrigation (I-2-80). Our initial hypothesis was that increasing discharge frequency would increase both salt reduction and rice yield. Daily precipitation was recorded by a nearby weather station, and evapotranspiration and soil water percolation rates were measured at experimental sites using soil pits. The measurements were used to establish a water balance for each treatment. Our results showed that soil salt reduction increased with the increasing discharge frequency at a 30-mm irrigation water depth. The 9-time discharge reduced a large amount of soil salt (995.0 kg ha⁻¹) after five months of the study. Rice yield also increased with the increasing discharge frequency with a 30-mm irrigation water depth; however, when compared to the traditional 2-time discharge followed with an 80-mm irrigation, rice yield at the sites with more frequent discharge (i.e., I-9-30, I-6-30 and I-3-30) was 11%–18% lower. Because of this, rice yield and irrigation water use efficiency were significantly higher under the traditional practice of high-irrigation with low-frequency discharge (I-2-80) than under I-9-30, I-6-30 and I-3-30. These results indicate a need for a trade-off amongst salt reduction, rice yield and water use when considering selection of irrigation and discharge schedules.

Determining the dynamics of surface hydrological connectivity in a landscape of multiple lakes with different sizes and depths is challenging. This is especially the case for ungagged, large areas of multi-lake systems. Integrated use of remote sensing and geostatistical analysis can be a useful approach for developing metrics that can be used to identify the hydrological connectivity and their changes. In this study, we conducted a geostatistical analysis of 18 wet and dry binary state rasters derived from Landsat images over a large ungauged multi-lake system, the Momoge National Nature Reserve in Northeast China. Our goal was to investigate applicability and dynamics of three surface hydrological connectivity metrics, namely, geostatistical connectivity function (GCF), maximum distance of connection (MDC), and surface water extent (SWE) of the top 10 largest connectomes (i.e., seasonally connected water bodies). We found that, during a dry year, the reduction rate of the GCF curve was slower along the west–east (W–E) direction than along the north–south (N–S) direction, which was contrary to the patterns exhibited in a normal or wet year. The minimum values of the MDC in W–E and N–S directions in the dry year were 22.4 km and 6.3 km, respectively, while the maximum values of the MDC along the above two directions in the wet year were 50.7 km and 65.1 km, respectively. The components and spatial distribution of the top 10 largest connectomes changed dramatically in different months of each hydrological year, resulting in a huge change in the monthly SWE of the top 10 largest connectomes. Overall, this study validated the usefulness of combining remote sensing image analysis with geostatistical methods to quantify the surface hydrological connectivity from different perspectives in an ungauged area. The approach may be applicable to studies in other geographical regions, to guide water resources and wetland management practices.

Connectivity metrics for surface water are important for predicting floods and droughts, and improving water management for human use and ecological integrity at the landscape scale. The integrated use of synthetic aperture radar (SAR) observations and geostatistics approach can be useful for developing and quantifying these metrics and their changes, including geostatistical connectivity function (GCF), maximum distance of connection (MDC), surface water extent (SWE), and connection frequency. In this study, we conducted a geostatistical analysis based on 52 wet and dry binary state (i.e., water and non-water) rasters derived from Sentinel-1 A/B GRD products acquired from 2015 to 2019 for China’s Momoge National Nature Reserve to investigate applicability and dynamics of the hydrologic connectivity metrics in an ungauged (i.e., data such as flow and water level are scarce) multi-lake system. We found: (1) generally, the change of GCF in North–South and Northeast–Southwest directions was greater than that in the West–East and Northwest–Southeast directions; (2) MDC had a threshold effect, generally at most 25 km along the W–E, NW–SE and NE–SW directions, and at most 45 km along the N–S direction; (3) the flow paths between lakes are diverse, including channelized flow, diffusive overbank flow, over-road flow and “fill-and-merge”; (4) generally, the values of the three surface hydrological connectivity indicators (i.e., the MDC, the SWE, and the conneciton frequency) all increased from May to August, and decreased from August to October; (5) generally, the closer the distance between the lakes, the greater the connection frequency, but it is also affected by the dam and road barrier. The study demonstrates the usefulness of the geostatistical method combining Sentinel-1 SAR image analysis in quantifying surface hydrological connectivity in an ungagged area. This approach should be applicable for other geographical regions, in order help resource managers and policymakers identify changes in surface hydrological connectivity, as well as address potential impacts of these changes on water resources for human use and/or ecological integrity at the landscape level.