Salinization of lakes in arid areas is a common phenomenon with harmful consequences and must be controlled for the better use of lake freshwater and for the conservation of the environment around lakes. Bosten Lake, located in Xinjiang (western China) and the largest inland freshwater lake in China, now experiences salinization. The salinization of Bosten Lake is studied herein by using a physically-based model. After qualitative analysis of lake salinization, the quantitative model is presented that describes the systems of water quantity-water quality-ecology (WQQE) in an integrated way and that simulates the changing processes of lake salinization in the past. On the basis of the WQQE model, an optimal model was also developed to investigate the best strategy for controlling salinization of the lake in the future. The results demonstrated that the developed models can be used to depict the physical process of salinization of Bosten Lake and to provide meaningful information on how to control this salinization. Un modèle à bases physiques pour l'étude de la salinisation du Lac Bosten en ChineRésumé La salinisation des lacs en régions arides est un phénomène courant aux conséquences nuisibles, qui doit être contrôlé dans l'optique d'une meilleure utilisation de l'eau douce des lacs et de la conservation des environnements lacustres. Le Lac Bosten, situé dans le Xinjiang (à l'ouest de la Chine) et constituant le plus grand lac d'eau douce de Chine, subit désormais la salinisation. La salinisation du Lac Bosten est étudiée à l'aide d'un modèle à bases physiques. Après une analyse qualitative de la salinisation lacustre, présentation est faite du modèle quantitatif qui décrit les systèmes quantité d'eauqualité d'eau-écologie (WQQE) d'une manière intégrée et qui simule les processus évolutifs de salinisation lacustre au cours du passé. Grâce au modèle WQQE, un modèle optimal a également été développé afin d'identifier la meilleure stratégie de contrôle de la salinisation du lac pour le futur. Les résultats montrent que les modèles développés peuvent être utilisés pour représenter les processus physiques de salinisation du Lac Bosten et pour produire une information pertinente en vue du contrôle de cette salinisation.

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As demands on limited water resources intensify, concerns are being raised about water resources carrying capacity (WRCC), which is defined as the maximum sustainable socioeconomic scale that can be supported by available water resources and while maintaining defined environmental conditions. This paper proposes a distributed quantitative model for WRCC, based on the principles of optimization, and considering hydro-economic interaction, water supply, water quality, and socioeconomic development constraints. With the model, the WRCCs of 60 subregions in Henan Province were determined for different development periods. The results showed that the water resources carrying level of Henan Province was suitably loaded in 2010, but that the province would be mildly overloaded in 2030 with respect to the socioeconomic development planning goals. The restricting factors for WRCC included the available water resources, the increasing rate of GDP, the urbanization ratio, the irrigation water utilization coefficient, the industrial water recycling rate, and the wastewater reuse rate, of which the available water resources was the most crucial factor. Because these factors varied temporally and spatially, the trends in predicted WRCC were inconsistent across different subregions and periods.

Based on the monitoring data of 78 monitoring stations from 2003 to 2012, five key water quality indexes (biochemical oxygen demand: BOD5, permanganate index: CODMn, dissolved oxygen: DO, ammonium nitrogen: NH3-N, and total phosphorus: TP) were selected to analyze their temporal and spatial characteristics in the highly disturbed Huaihe River Basin via Mann-Kendall trend analysis and boxplot analysis. The temporal and spatial variations of water pollutant concentrations in the Huaihe River Basin were investigated and analyzed to provide a scientific basis for water pollution control, water environment protection, and ecological restoration. The results indicated that the Yinghe River, Quanhe River, Honghe River, Guohe River, and Baohe River were the most seriously polluted rivers, followed by Hongze Lake, Luoma Lake, Yishuhe River, and Nansi Lake. BOD5, CODMn, and NH3-N were the major pollution indexes, for which the monitoring stations reported that more than 40 % of the water quality concentrations exceeded the class IV level. There were 21, 50, 36, and 21 monitoring stations that recorded significantly decreasing trends for BOD5, CODMn, NH3-N, and TP, respectively, and 39 monitoring stations showed a significantly increasing trend for DO. Moreover, the water quality concentrations had a certain concentricity and volatility according to boxplot analysis for the 20 monitoring stations. The majority of monitoring stations recorded a large fluctuation for the monitoring indexes in 2003 and 2004, which indicated that the water quality concentrations were unstable. According to the seasonal variations of the water quality concentrations in the mainstream of Huaihe River, the monthly variation trends of the BOD5, CODMn, DO, NH3-N, and TP concentrations were basically consistent among the seven monitoring stations. The BOD5, CODMn, NH3-N, and TP concentrations were affected by the change of the stream discharge; changes in DO and NH3-N concentrations were influenced by the regional environmental temperature, and the DO and NH3-N concentrations decreased when the water temperature increased.