ALBERT

Description: In April–July 2008, intensive measurements were made of atmospheric composition and chemistry in Sabah, Malaysia, as part of the "Oxidant and particle photochemical processes above a South-East Asian tropical rainforest" (OP3) project. Fluxes and concentrations of trace gases and particles were made from and above the rainforest canopy at the Bukit Atur Global Atmosphere Watch station and at the nearby Sabahmas oil palm plantation, using both ground-based and airborne measurements. Here, the measurement and modelling strategies used, the characteristics of the sites and an overview of data obtained are described. Composition measurements show that the rainforest site was not significantly impacted by anthropogenic pollution, and this is confirmed by satellite retrievals of NO2 and HCHO. The dominant modulators of atmospheric chemistry at the rainforest site were therefore emissions of BVOCs and soil emissions of reactive nitrogen oxides. At the observed BVOC:NOx volume mixing ratio (~100 pptv/pptv), current chemical models suggest that daytime maximum OH concentrations should be ca. 105 radicals cm−3, but observed OH concentrations were an order of magnitude greater than this. We confirm, therefore, previous measurements that suggest that an unexplained source of OH must exist above tropical rainforest and we continue to interrogate the data to find explanations for this.

Description: The sea surface salinity (SSS) measured from space by the Soil Moisture and Ocean Salinity (SMOS) mission has recently been revisited by the European Space Agency first campaign reprocessing. We show that, with respect to the previous version, biases close to land and ice greatly decrease. The accuracy of SMOS SSS averaged over 10 days, 100 × 100 km2 in the open ocean and estimated by comparison to ARGO (Array for Real-Time Geostrophic Oceanography) SSS is on the order of 0.3–0.4 in tropical and subtropical regions and 0.5 in a cold region. The averaged negative SSS bias (−0.1) observed in the tropical Pacific Ocean between 5° N and 15° N, relatively to other regions, is suppressed when SMOS observations concomitant with rain events, as detected from SSM/Is (Special Sensor Microwave Imager) rain rates, are removed from the SMOS–ARGO comparisons. The SMOS freshening is linearly correlated to SSM/Is rain rate with a slope estimated to −0.14 mm−1 h, after correction for rain atmospheric contribution. This tendency is the signature of the temporal SSS variability between the time of SMOS and ARGO measurements linked to rain variability and of the vertical salinity stratification between the first centimeter of the sea surface layer sampled by SMOS and the 5 m depth sampled by ARGO. However, given that the whole set of collocations includes situations with ARGO measurements concomitant with rain events collocated with SMOS measurements under no rain, the mean −0.1 bias and the negative skewness of the statistical distribution of SMOS minus ARGO SSS difference are very likely the mean signature of the vertical salinity stratification. In the future, the analysis of ongoing in situ salinity measurements in the top 50 cm of the sea surface and of Aquarius satellite SSS are expected to provide complementary information about the sea surface salinity stratification.

Description: The sea surface salinity (SSS) measured from space by the Soil Moisture and Ocean Salinity (SMOS) mission has recently been revisited by the European Space Agency first campaign reprocessing. We show that, with respect to the previous version, biases close to land and ice greatly decrease. The accuracy of SMOS SSS averaged over 10 days 100 × 100 km2 in the open ocean and estimated by comparison to ARGO SSS is on the order of 0.3–0.4 in tropical and subtropical regions and 0.5 in a cold region. The mean SSS −0.1 bias observed in the Tropical Pacific Ocean between 5° N and 15° N, relatively to other regions, is suppressed when SMOS rainy events, as detected on SSMIs rain rates, are removed from the SMOS-ARGO comparisons. The SMOS freshening is linearly correlated to SSMIs rain rate with a slope estimated to −0.14 mm−1 h, after correction for rain atmospheric contribution. This tendency is the signature of the temporal SSS variability between the time of SMOS and ARGO measurements linked to rain variability and of the vertical salinity stratification between the first centimeter of the sea surface layer sampled by SMOS and the 5 m depth sampled by ARGO. However, given that the whole set of collocations includes situations with rainy ARGO measurements collocated with non rainy SMOS measurements, the mean −0.1 bias and the negative skewness of the statistical distribution of SMOS minus ARGO SSS difference are very likely the mean signature of the vertical salinity stratification. In the future, the analysis of ongoing in situ salinity measurements in the top 50 cm of the sea surface and of Aquarius satellite SSS are expected to provide complementary information about the sea surface salinity stratification.

Description: Decomposition analysis of water footprint (WF) changes, or assessing the changes in WF and identifying the contributions of factors leading to the changes, is important to water resource management. Instead of focusing on WF from the perspective of administrative regions, we built a framework in which the input-output (IO) model, the structural decomposition analysis (SDA) model and the generating regional IO tables (GRIT) method are combined to implement decomposition analysis for WF in a river basin. This framework is illustrated in the WF in Haihe River basin (HRB) from 2002 to 2007, which is a typical water-limited river basin. It shows that the total WF in the HRB increased from 4.3 × 1010 m3 in 2002 to 5.6 × 1010 m3 in 2007, and the agriculture sector makes the dominant contribution to the increase. Both the WF of domestic products (internal) and the WF of imported products (external) increased, and the proportion of external WF rose from 29.1 to 34.4%. The technological effect was the dominant contributor to offsetting the increase of WF. However, the growth of WF caused by the economic structural effect and the scale effect was greater, so the total WF increased. This study provides insights about water challenges in the HRB and proposes possible strategies for the future, and serves as a reference for WF management and policy-making in other water-limited river basins.

Description: In deregulated electricity markets, hydropower portfolio design has become an essential task for producers. The previous research on hydropower portfolio optimisation focused mainly on the maximisation of profits but did not take into account riverine ecosystem protection. Although profit maximisation is the major objective for producers in deregulated markets, protection of riverine ecosystems must be incorporated into the process of hydropower portfolio optimisation, especially against a background of increasing attention to environmental protection and stronger opposition to hydropower generation. This research seeks mainly to remind hydropower producers of the requirement of river protection when they design portfolios and help shift portfolio optimisation from economically oriented to ecologically friendly. We establish a framework to determine the optimal portfolio for a hydropower reservoir, accounting for both economic benefits and ecological needs. In this framework, the degree of natural flow regime alteration is adopted as a constraint on hydropower generation to protect riverine ecosystems, and the maximisation of mean annual revenue is set as the optimisation objective. The electricity volumes assigned in different electricity submarkets are optimised by the noisy genetic algorithm. The proposed framework is applied to China's Wangkuai Reservoir to test its effectiveness. The results show that the new framework could help to design eco-friendly portfolios that can ensure a planned profit and reduce alteration of the natural flow regime.

Description: Decomposition analysis of water footprint (WF) changes, or assessing the changes in WF and identifying the contributions of factors leading to the changes, is important to water resource management. However, conventional studies focus on WF from the perspective of administrative region rather than river basin. Decomposition analysis of WF changes from the perspective of the river basin is more scientific. To address this perspective, we built a framework in which the input–output (IO) model and the Structural Decomposition Analysis (SDA) model for WF could be implemented in a river basin by computing IO data for the river basin with the Generating Regional IO Tables (GRIT) method. This framework is illustrated in the Haihe River Basin (HRB), which is a typical water-limited river basin. It shows that the total WF in the HRB increased from 4.3 × 1010 m3 in 2002 to 5.6 × 1010 m3 in 2007, and the agriculture sector makes the dominant contribution to the increase. Both the WF of domestic products (internal) and the WF of imported products (external) increased, and the proportion of external WF rose from 29.1% to 34.4%. The technological effect was the dominant contributor to offsetting the increase of WF; however, the growth of WF caused by the economic structural effect and the scale effect was greater, so the total WF increased. This study provides insights about water challenges in the HRB and proposes possible strategies for the future, and serves as a reference for WF management and policy making in other water-limited river basins.

Description: Lake eutrophication is a serious global environmental issue. Phytoremediation is a promising, cost-effective, and environmentally friendly technology for water quality restoration. However, besides nutrient removal, macrophytes also deeply affect the hydrologic cycle of lake system through evapotranspiration. Changes in hydrologic cycle caused by macrophytes have a great influence on lake water quality restoration. As a result of the two opposite effects of macrophytes on water quality restoration (i.e. an increase in macrophytes can increase nutrient removal and improve water quality while also increasing evapotranspiration, reducing water volume and consequently decreasing water quality), rational macrophyte control through planting and harvest is very important. In this study, a new approach is proposed to optimise the initial planting area and monthly harvest scheme of macrophytes for water quality restoration. The month-by-month effects of macrophyte management on lake water quality are considered. Baiyangdian Lake serves as a case study, using the common reed. It was found that water quality was closest to Grade III on the Chinese water quality scale when the reed planting area was 123 km2 (40% of the lake surface area) and most reeds would be harvested at the end of June. The optimisation approach proposed in this study will be a useful reference for lake restoration.

Description: China is a water-stressed country, and agriculture consumes the bulk of its water resources. Assessing the virtual water content (VWC) of crops is one important way to develop efficient water management measures to alleviate water resources conflicts among different sectors. In this research, the VWC of rice, as a major crop in China, was assessed and the spatial characteristics were analyzed. In addition to the calculation of green, blue and grey water – the direct water in VWC – the indirect water use of rice was also calculated, using the Input–Output model. The percentages of direct green, blue, grey and indirect water in the total VWC of rice in China were 43.8, 28.2, 27.6, and 0.4%. The total VWC of rice generally showed a three-tiered distribution, and decreased from southeast to northwest. The higher values of direct green water of rice were mainly concentrated in Southeast and Southwest China, while these values were relatively low in Northwest China and Inner Mongolia. The higher direct blue water values were mainly concentrated in the eastern and southern coastal regions and Northwest China, and low values were mainly concentrated in Southwest China. Grey water values were relatively high in Shanxi and Guangxi provinces and low in Northeast and Northwest China. The regions with high values for indirect water were randomly distributed but the regions with low values were mainly concentrated in Northwest and Southwest China. For the regions with relatively high total VWC the high values of blue water made the largest contribution, although for the country as a whole the direct green water is the most important contributor.

Description: Environmental/ecological models are widely used for lake management as they provide a means to understand physical, chemical and biological processes in highly complex ecosystems. Most research focused on the development of environmental (water quality) and ecological models, separately. Limited studies were developed to couple the two models, and in these limited coupled models a lake was regarded as a whole for analysis (i.e., considering the lake to be one well-mixed box), which was appropriate for small-scale lakes and was not sufficient to capture spatial variations within middle-scale or large-scale lakes. In response to this problem, this paper seeks to establish a zoning-based environmental-ecological-coupled model for a lake. The hierarchical cluster analysis (HCA) was adopted to determine the number of zones for a lake based on the analysis of hydrological, water quality and ecological data. MIKE21 model was used to construct two-dimensional hydrodynamics and water quality simulations. STELLA software was used to create a lake ecological model which can simulate the spatial variations of ecological condition based on flow field distribution results generated by MIKE21. The Baiyangdian Lake, the largest freshwater lake in Northern China, was adopted as the study case. The results showed that the new model was promising to predict the spatial variation trends of ecological condition in response to the changes of water quantity and water quality for lakes, and could provide a great convenience for lake management.

Description: Lake eutrophication is a serious global environmental issue. Phytoremediation is a promising, cost-effective, and environmentally friendly technology for water quality restoration. However, besides nutrient removal, macrophytes also deeply affect the hydrologic cycle of a lake system through evapotranspiration. Changes in hydrologic cycle caused by macrophytes have a great influence on lake water quality restoration. As a result of the two opposite effects of macrophytes on water quality restoration (i.e. an increase in macrophytes can increase nutrient removal and improve water quality while also increasing evapotranspiration, reducing water volume and consequently decreasing water quality), rational macrophyte control through planting and harvest is very important. In this study, a new approach is proposed to optimise the initial planting area and monthly harvest scheme of macrophytes for water quality restoration. The month-by-month effects of macrophyte management on lake water quality are considered. Baiyangdian Lake serves as a case study, using the common reed. It was found that water quality was closest to Grade III on the Chinese water quality scale when the reed planting area was 123 km2 (40% of the lake surface area) and most reeds would be harvested at the end of June. The optimisation approach proposed in this study will be a useful reference for lake restoration.