A general multi-objective programming model for minimum ecological flow or water level of inland water bodies

Assessment of ecological flow or water level for water bodies is important for the protection of degraded or degrading ecosystems caused by water shortage in arid regions, and it has become a key issue in water resources planning. In the past several decades, many methods have been proposed to assess ecological flow for rivers and ecological water level for lakes or wetlands. To balance water uses by human and ecosystems, we proposed a general multi-objective programming model to determine minimum ecological flow or water level for inland water bodies, where two objectives are water index for human and habitat index for ecosystems, respectively. Using the weighted sum method for multi-objective optimization, minimum ecological flow or water level can be determined from the breakpoint in the water index–habitat index curve, which is similar to the slope method to determine minimum ecological flow from wetted perimeter–discharge curve. However, the general multi-objective programming model is superior to the slope method in its physical meaning and calculation method. This model provides a general analysis method for ecological water uses of different inland water bodies, and can be used to define minimum ecological flow or water level by choosing appropriate water and habitat indices. Several commonly used flow or water level assessment methods were found to be special cases of the general model, including the wetted perimeter method and the multi-objective physical habitat simulation method for ecological river flow, the inundated forest width method for regeneration flow of floodplain forest and the lake surface area method for ecological lake level. These methods were applied to determine minimum ecological flow or water level for two representative rivers and a lake in northern Xinjiang of China, including minimum ecological flow for the Ertix River, minimum regeneration flow for floodplain forest along the midstream of Kaxgar River, and minimum ecological lake level for the Ebinur Lake. The results illustrated the versatility of the general model, and can provide references for water resources planning and ecosystem protection for these rivers and lake.     

民勤湖区表层土壤养分的空间异质性

利用地统计学方法研究了民勤绿洲湖区表层土壤养分碱解氮、速效磷和速效钾的空间异质性.结果表明:绿洲、过渡带和荒漠三种景观下表层土壤中氮磷钾含量都呈现出“丰氮、富钾、贫磷”的特征;碱解氮与速效磷的变异系数在绿洲区最小,荒漠区最大,而速效钾在荒漠区最小,过渡带最大,但都属于中等变异;从绿洲到荒漠,碱解氮、速效磷呈U型分布特征,而速效钾为倒U型分布特征.碱解氮的最佳拟合模型为Exponential,速效磷为PentaspHerical,速效钾为Tetrasherical;氮和磷的富集区位于绿洲区,而速效钾在过渡带上出现富集中心.土壤的养分元素含量除了与成土母质的元素有关外,人类活动的影响也是非常重要的因素.     

1964—2014年柴窝堡湖面积的时序变化及驱动因素

以乌鲁木齐柴窝堡湖为例,根据Corona和Landsat遥感数据,提取近50 a湖泊水面变化的时间序列,利用激光测高卫星ICEsat/GLAS数据,提取2003—2009年水位变化信息,进而分析湖泊在气候变化和人类活动条件下的年、月空间变化特征。结果表明:柴窝堡湖水面变化分3个阶段:1964—2004年、2005—2010年和2011—2014年,其面积变化率分别为0.012 km2·a-1、-0.256 km2·a-1和-4.798 km2·a-1。水面变化由缓到急,并在2014年9月25日首现干涸,湖泊水体生态功能正在逐步丧失。湖泊水面的月变化在2005年以后逐渐明显,春季处于水面峰值,秋季处于低谷,多年的月变化曲线直观地反映了水面面积加速减退的趋势。湖面边界的空间变化与湖面水位的变化过程体现了"陡岸平底"的湖泊形态特征。2005年以前,湖水面积变化较小,而湖水水位变化相对明显;2005年以后,湖水面积显示有规律的加速缩减;2012年湖水边界退缩到湖盆底部后,湖水面积与地下水位变化呈现明显的相关性。驱动因素分析结果表明,1993年以后的地下水开采是湖泊水位与面积变化的主要动因,1999—2004年显著增加的降水减缓了湖泊水面的萎缩速度;而2004年以后,由于持续高强度地开采湖区地下水,湖泊的水量平衡被打破,导致了柴窝堡湖干涸的生态灾难。     

Dynamics of ecosystem carbon stocks during vegetation restoration on the Loess Plateau of China

In the last few decades, the Loess Plateau had experienced an extensive vegetation restoration to reduce soil erosion and to improve the degraded ecosystems. However, the dynamics of ecosystem carbon stocks with vegetation restoration in this region are poorly understood. This study examined the changes of carbon stocks in mineral soil(0–100 cm), plant biomass and the ecosystem(plant and soil) following vegetation restoration with different models and ages. Our results indicated that cultivated land returned to native vegetation(natural restoration) or artificial forest increased ecosystem carbon sequestration. Tree plantation sequestered more carbon than natural vegetation succession over decades scale due to the rapid increase in biomass carbon pool. Restoration ages had different effects on the dynamics of biomass and soil carbon stocks. Biomass carbon stocks increased with vegetation restoration age, while the dynamics of soil carbon stocks were affected by sampling depth. Ecosystem carbon stocks consistently increased after tree plantation regardless of the soil depth; but an initial decrease and then increase trend was observed in natural restoration chronosequences with the soil sampling depth of 0–100 cm. Moreover, there was a time lag of about 15–30 years between biomass production and soil carbon sequestration in 0–100 cm, which indicated a long-term effect of vegetation restoration on deeper soil carbon sequestration.