鄱阳湖水位变化的复合驱动机制

基于对鄱阳湖开放水文系统特点和影响因素的深入分析,通过构建一组联合的神经网络模型,定量辨识了包括湖盆地形变化、三峡工程作用、长江流域气候变化等因素对湖泊水位变化的影响分量、时空差异及其发展趋势,并对其作用机制进行了探讨。结果表明：相对于1980—1999年,2003—2014年鄱阳湖湖盆地形变化、三峡工程运行、长江流域气候变化和其他人类活动对湖泊水位降低的平均贡献率分别为50%、18%和32%。由于影响机制的不同,湖泊水位对这3个驱动因子的响应表现出明显的时空差异。冬、春季节湖泊水位降低主要由湖盆地形变化引起,而夏、秋季节的水位降低则主要归因于长江流域气候变化及其他人类活动的综合影响。湖盆地形变化对湖泊水位的影响在湖区都昌站附近最为突出,并且该影响仍呈长期增加趋势。三峡工程引起的湖泊水位变化在湖口处最大,向南部湖区逐渐减弱,其长期变化趋势日渐稳定。长江流域气候变化及其他人类活动的作用值得特别注意,该影响年际间波动较大,在某些年份里（如2006年、2011年）可成为湖泊水位降低的主导因素,但年际变化趋势不明显。     

近50年来长江与鄱阳湖水文相互作用的变化

通过分析1957-2008 年长江与鄱阳湖相互作用的基本特征及其与长江中游、鄱阳湖流域的径流量和气候变化的关系,并用2004-2006 年三峡水库蓄水、放水量的数据,定量地计算和比较了三峡水库运行和区域气候变化对长江与鄱阳湖相互作用的影响程度,得出如下主要结论：1)从年际、年代际尺度上来看,鄱阳湖流域的气候变化和五河入湖流量是鄱阳湖水位和水量变化的主要因素,同时也在很大程度上决定了长江与鄱阳湖相互作用关系及其强弱变化。2) 长江与鄱阳湖的相互作用强度是此消彼长的关系。从季节来看,鄱阳湖对长江的较强作用主要在4-6月,而长江对鄱阳湖的较强作用主要发生在7-9 月。3) 三峡水库运行并没有改变长江与鄱阳湖作用的基本特征,在多数季节三峡水库的影响不足以解释长江径流量变化的10%,但是水库在不同季节的蓄水或放水在一定程度上影响了江湖作用的季节变化和鄱阳湖流域的旱涝机率。4-6月的放水加强了长江作用,由于此时正值鄱阳湖流域的雨季,增强的长江作用在湿润气候的环境下可能增加初夏鄱阳湖流域发生洪涝的概率;7-9 月的少量蓄水则减弱长江对鄱阳湖的作用,降低了湖区洪涝的概率;而10 月份三峡水库的大量蓄水可能增加鄱阳湖流域的旱季干旱发生率。     

对筑坝调控鄱阳湖水的思考

对鄱阳湖目前存在的问题、控湖后可产生的效益和解决控湖工程难题的途径作了一些思考，建议尽快筑坝控湖以提高湖泊效益。     

鄱阳湖水文特征动态变化遥感监测

鄱阳湖是中国第一大淡水湖,对鄱阳湖的水文变化进行持续监测可以为流域内生态环境变化提供基础数据,有利于研究其与长江和流域内河流的交互关系,更好地服务于陆面过程模式和水资源管理。本文利用卫星测高数据反演的鄱阳湖水位数据与MODIS数据结合,对鄱阳湖2000—2015年的水位、水域面积和水量变化进行研究,并通过水量平衡模型,推导出了同期长江—鄱阳湖的水量交互。研究发现,2000—2015年鄱阳湖面积呈现波动性变化,最大水域面积为3600 km ²,是最小水域面积482 km ²的7.5倍。2004年、2007年、2009年和2011年水域面积比较低,2012年后形势好转。每年1月、2月、12月份是鄱阳湖干季,水域面积低至500 km ²,湖口处水位可低至4.71 m,湖面从南往北倾斜,南北水位差异达2.59 m。相对于2000—2015年最低水量,干季时湖泊水量平均增加量为3 km ³。每年6—9月份是鄱阳湖的湿季,水域面积一般大于2670 km ²,水位高于15 m,南北水位差异不大,相对于2000—2015年最低水量,湿季时湖泊水量平均增加量为12 km ³。2000—2015年鄱阳湖流入长江的水量范围为-7~40.66 km ³,每年有93.33%的时间水流从鄱阳湖流入长江。流入长江的水量多少具有明显的季节性,通常5月、6月流入长江的水量高于7月、8月,主要因为7月、8月长江中上游降水增加,长江干流来水增多,对鄱阳湖湖水倒灌有一定的顶托作用。     

鄱阳湖典型湿地植物现状与保护策略

鄱阳湖是我国最大的吞吐型、季节性浅水通江湖,呈现丰水期和枯水期周期性交替的独特水文节律。近年来鄱阳湖水位波动加剧,在各种因素及2020年特大洪水的影响下,鄱阳湖沉水植物呈退化趋势。综述了鄱阳湖湿地植物种类、典型湿地植物及其适应策略等,探讨鄱阳湖水文水质变化、10年禁渔、采砂等对沉水植物群落等分布的影响,为鄱阳湖湿地植物的保护及恢复提供参考。     

Growing impacts of low-flow events on vegetation dynamics in hydrologically connected wetlands downstream Yangtze River Basin after the operation of the Three Gorges Dam

Wetland vegetation is intimately related to floodplain inundations, which can be seriously affected by dam operation. Poyang Lake is the largest floodplain wetland in China and naturally connected with the Yangtze River and the Three Gorges Dam(TGD) upstream. To understand the potential impacts of TGD on Poyang Lake wetlands, we collected remote sensing imagery acquired during dry season from 1987 to 2020 and extracted vegetation coverage data in the Ganjiang Northern-branch Delta(GND) and the G...     

Landscape Changes and Increasing Flood Frequency in China's Poyang Lake Region*

Jiangxi Province in southeastern China contains Poyang Lake, the largest freshwater lake in China. Poyang Lake and the lower sections of the major Jiangxi rivers flowing into the lake often flood during the early summer months. Floodwater can be several meters above the surrounding lowlands during the most severe flood events. Levees at the margins of Poyang Lake and along the Jiangxi rivers provide flood protection for about 10 million people. The number of severe floods in this region has increased rapidly during the past few decades, resulting in catastrophic levee failures. The three factors likely responsible for the increasing frequency of severe floods are (1) land reclamation and levee construction and (2) lake sedimentation, both of which reduce lake volume, and (3) increasing Changjiang water level, which slows Poyang Lake drainage.     

鄱阳湖水利枢纽工程水位调控方案的探讨

利用历史水文资料、越冬候鸟分布调查资料及基础地理数据等, 从鄱阳湖形态的历史演变和鄱阳湖越冬候鸟生境保护的角度, 探讨鄱阳湖水利枢纽工程的水位调控方案。研究得到以下结论和建议:(1) 在维持鄱阳湖形态不变的情况下, 为有效保护越冬候鸟生境不受水利枢纽工程水位调控的影响, 工程调控水位不宜超过12 m, 但由于低水位运行不利于水利枢纽工程工程效益的发挥, 而高水位运行不利于越冬候鸟栖息地的保护, 为调和工程效益和候鸟保护之间的矛盾, 建议实施适当退田还湖, 以促进鄱阳湖水利枢纽工程的规划实施;(2) 根据地形、越冬候鸟分布范围、圩堤内居民点分布以及圩堤内土地利用现状, 提出了约640 km²实施退田还湖范围;(3) 以退田还湖为前提, 按照“调枯不调洪”原则, 提出鄱阳湖水利枢纽工程的水位调控方案, 为工程的推进和实施提供参考。     

Landscape Changes and Increasing Flood Frequency in China's Poyang Lake Region*

Abstract

Jiangxi Province in southeastern China contains Poyang Lake, the largest freshwater lake in China. Poyang Lake and the lower sections of the major Jiangxi rivers flowing into the lake often flood during the early summer months. Floodwater can be several meters above the surrounding lowlands during the most severe flood events. Levees at the margins of Poyang Lake and along the Jiangxi rivers provide flood protection for about 10 million people. The number of severe floods in this region has increased rapidly during the past few decades, resulting in catastrophic levee failures. The three factors likely responsible for the increasing frequency of severe floods are (1) land reclamation and levee construction and (2) lake sedimentation, both of which reduce lake volume, and (3) increasing Changjiang water level, which slows Poyang Lake drainage.     

鄱阳湖湿地水位与洲滩淹露模型构建

水是控制湿地生态过程的一个重要因子,为了研究洲滩变化和湿地草洲生长发育规律,以便更好地监测和保护湿地生态系统,有必要研究鄱阳湖水体变化特征,分析湿地洲滩水位的时空动态变化和洲滩淹露规律。本文以鄱阳湖国家级自然保护区为例,在对鄱阳湖多年水位进行分析的基础上,利用多时相遥感影像和DEM提取湿地洲滩特征;并在GIS支持下综合考虑地形、鄱阳湖水位、湖泊缓冲区等因素,建立了湿地水位及洲滩淹露模型。时空验证结果表明,该模型具有较好的模拟效果,精度在85%以上。同时,本文根据研究区特点及水体在TM2、7波段的特征差异,构建了一个新的水体指数FDWI,提取水体精度达到98%,特别是对潮湿的沙地、植被和云有很好的区分能力。     

人类活动对鄱阳湖泥沙收支平衡的影响

以鄱阳湖流域内的赣江、抚河、信江、饶河和修水（五河）和鄱阳湖为研究对象,利用水文控制站的水文资料,分析了各流域内主要河流的入湖泥沙和鄱阳湖出湖泥沙特征,对鄱阳湖泥沙收支平衡进行了分析。结果表明：① 1955~2010年五河总入湖泥沙811.69 Mt,其中赣江（占59.7%）>信江（占13.7%）>修河（占10.2%）>抚河（占9.7%）>饶河（占6.7%）;② 径流量是影响入湖输沙量的最主要因素,入湖泥沙与入湖径流的季节特征一致;③ 水库的蓄水拦沙作用是五河入湖泥沙下降的主要原因,但水库对入湖泥沙的影响强度与水库库容和集水区的植被覆盖状况有关;植被覆盖变化对赣江、抚河、饶河和修河的入湖输沙量的影响明显;④ 1955~2010年,鄱阳湖总出湖泥沙560.10 Mt,其中1955~2000年出湖泥沙量呈降低趋势,但受鄱阳湖采砂影响,2001年以来出湖泥沙显著增加;丰水季长江水对鄱阳湖的顶托和倒灌,使出湖泥沙与出湖径流在时间上不同步;三峡工程的运行改变了（长）江（鄱阳）湖之间的水动力关系,长江倒灌泥沙显著减少;⑤ 受鄱阳湖采砂的影响,鄱阳湖泥沙平衡系统由净沉积转变为净侵蚀,1955~2000年入湖泥沙大于出湖泥沙,年均泥沙沉积约为1.41 mm;2001~2010年出湖泥沙大于入湖泥沙,加上采砂输出沙量,2001~2010年鄱阳湖泥沙净减少2 213.65 Mt。     

鄱阳湖自然保护区网络体系建设的探索与尝试

鄱阳湖是国际重要湿地,是中国最大的淡水湖,也是亚洲最大的水禽越冬地,是白鹤、东方白鹳、鸿雁和小天鹅等珍稀水禽全球最主要的越冬地之一。为保护好鄱阳湖湿地生态系统,保护好鄱阳湖珍稀水禽及其栖息地,江西省人民政府先后在鄱阳湖建立了15个自然保护区(国家级2个、省级2个,其余为县级),这15个自然保护区构成了原有的自然保护区网络体系。由于县级保护区保护管理功能的缺失,使得原有的自然保护区体系发挥的作用十分有限,因此需要尝试建立新的自然保护区网络体系。新的鄱阳湖自然保护区网络体系由鄱阳湖国家级自然保护区的11个保护管理(监测)站和南矶湿地国家级自然保护区的保护管理站共同组成,同时还包括鄱阳湖区越冬候鸟和湿地联合保护委员会、护鸟员和信息员队伍以及奖励机制。目前,新的网络体系存在新建保护监测站职能不明确和人员不足等问题,一定程度上制约了保护管理功能的发挥。为更好地发挥鄱阳湖自然保护区网络体系的作用,加强鄱阳湖自然保护区网络体系的建设十分必要,建议国家和地方政府给予更多的政策和资金支持。     

青海湖碳酸盐氧同位素环境记录再认识

青海湖是我国内陆最大的闭流型水体,地处东亚季风和西风的交汇影响区,对区域降水的改变等气候变化反应敏感,其水位变化历史是研究区域季风环境演变极其宝贵和重要的环境档案。青海湖Q14B孔岩芯介壳δ18Oc变化曲线自1991年发表以来,受到国内外同行的广泛关注和继续探讨。依据近年来青海湖气候与环境演变研究的最新研究结果和个人对闭流型湖泊同位素地球化学的认识,对介壳δ18Oc变化曲线进行了重新判读并得出以下结论:14.5~10.5 ka B.P.,青海湖区气候已逐渐从干冷向温湿过渡,季风降水逐渐增加;10.8~10.5 ka B.P.,青海湖处于碳酸盐滩湖环境,湖水深度从几米演变到接近干涸;10.5~9.5 kaB.P.,季风降水增加;9.5~8 ka B.P,湖水位从此前的接近干涸演变到此间的2~8 m,δ18Oc值跌落到一个较低的位置;8~3.5ka B.P,气候条件相对稳定,湖水不断蒸发引起重同位素的富集;3.5~0ka B.P,湖水处于同位素稳定阶段。研究结果还显示,δ18Oc值的短期波动与湖泊水位短期变化关系密切且明显,即水位高低分别对应δ18Oc的低值与高值。δ18Oc值的长期变化与湖泊水位长期变化关系不明显,水位较浅时,二者几乎无关联;水位较深时,水位的长期缓慢下降自然会导致δ18Oc逐渐攀升,而水位的长期缓慢上升也可以伴随δ18Oc逐渐攀升。     

基于能量的鄱阳湖—长江相互作用表征指标研究

鄱阳湖与长江之间存在着复杂的相互作用关系,决定着江湖水沙交换,对整个区域的水资源、防洪、航运、生态环境等均具有重要影响。本文基于能量的观点,在从新的角度解释鄱阳湖和长江相互作用原理的基础上,构建了江湖相互作用的表征指标—能差F_e,对20世纪50年代以来江湖作用关系变化进行了研究。结果表明,自20世纪50年代以来,F_e值整体呈现增加趋势,说明长江作用减弱,鄱阳湖作用不断增强。三峡水库蓄水运用对江湖关系产生了重要影响,进一步削弱了长江作用。从年内变化来看,由于三峡水库的调节,枯水期长江作用略有增强,汛末长江作用减弱较大。江湖作用一定程度上影响着湖区旱涝灾害的产生,当五河来流较大且长江顶托作用明显时,易发生洪涝;当五河来流较小但又对长江有明显的补水作用时,易发生旱情,三峡水库蓄水使湖区9-10月更易发生干旱。     

鄱阳湖流域水文变化特征成因及旱涝规律

本研究分析了1960-2008年鄱阳湖流域的气候和水文变化特征,用水量和能量平衡关系解释和印证了这些特征,并由此揭示了鄱阳湖流域水文变化特征的成因及干旱和洪涝发生的规律.得到以下主要结论:1)正常或偏湿年份鄱阳湖流域6月份容纳水量能力已达到饱和,若6-7月降水量超出正常年份,则流域超饱和,洪涝发生.长江中上游降水量7月份的异常偏多会对鄱阳湖流域的洪涝起触发和强化作用.2)鄱阳湖流域7-10月蒸发量大于降水量,特别是7-8月蒸发量大于降水量的一倍以上,所以若4-6月流域降水量少于平均年同期量的20％以上,则累积效应使秋旱发生.当初冬(11月)降水偏少时,秋旱可持续到来年的初春,形成严重的春旱.长江中上游降水量对鄱阳湖流域的春旱没有直接影响,但7-8月降水量偏少时则对秋旱起重要的强化作用.3)长江对鄱阳湖流域的水文过程和旱涝的发生、发展的影响主要在7-8月的“长江与鄱阳湖耦合作用”时期和9-10月的“弱长江作用”期.     

Research on Forest Phenology Prediction based on LSTM and GRU Model

Research on forest phenology is an important parameter related to climate and environmental changes. An optical camera was used as a near-earth remote sensing satellite device to obtain forest images, and the data of Green excess index (GEI) in the images were calculated, which was fitted with the seasonal variation curve of GEI data by double Logistic method and normalization method. LSTM and GRU deep learning models were introduced to train and test the GEI data. Moreover, the rationality and performance evaluation of the deep learning model were verified, and finally the model predicted the trend of GEI data in the next 60 days. Results showed: In the aspects of forest phenology training and prediction, GRU and LSTM models were verified by histograms and autocorrelation graphs, indicating that the distribution of predicted data was consistent with the trend of real data, LSTM and GRU model data were feasible and the model was stable. The differences of MSE, RMSE, MAE and MAPE between LSTM model and GRU model were 0.0014, 0.013, 0.008 and 5.26%, respectively. GRU had higher performance than LSTM. The prediction of LSTM and GRU models about GEI data for the next 60 days both showed a trend chart consistent with the change trend of GEI data in the first half of the year. GRU and LSTM were used to predict GEI data by deep learning model, and the response of LSTM and GRU deep learning models in forest phenology prediction was realized, and the performance of GRU was better than that of LSTM model. It could further reveal the growth and climate change of forest phenology in the future, and provide a theoretical basis for the application of forest phenology prediction.     

气候变化和人类活动对鄱阳湖流域入湖输沙量影响的定量估算

采用HydroTrend水文模型,以鄱阳湖流域的赣江、抚河、信江、饶河和修水为研究对象,基于1956-2010年鄱阳湖流域气候数据、水沙数据及其他相关资料,分别模拟了5个子流域的入湖水沙通量变化。在此基础上,探讨了气候变化、植被覆盖变化和水库修建活动对输沙量变化的影响,并定量估算了上述因子对流域输沙量变化的贡献。结果表明：① 1956-2010年,气候、植被和水库三种因子影响下的流域年均输沙量分别为15.5 Mt、20.8 Mt、8.5 Mt,而三种因子共同影响下的流域年均输沙量达到12.6 Mt。② 1956-2010年,植被覆盖变化使流域年均输沙量增加4.2 Mt,而水库拦截造成流域年均输沙量减少8.2 Mt,两者分别占实际年均输沙量的32.4%和63.2%。③ 1956-1989年,植被覆盖变化导致的输沙增加量和水库修建拦截导致的输沙减少量均为5.1 Mt/a,两者对流域输沙量贡献持平;1990-2010年,水土流失加重导致的输沙增加量和水库拦截导致的输沙减少量分别为2.7 Mt/a和13.3 Mt/a,水库对入湖输沙量的影响效应是植被覆盖变化的5倍左右。     

Water level changes in Lake Van,Turkey, during the past ca. 600 ka: climatic,volcanic and tectonic controls

Sediments of Lake Van, Turkey, preserve one of the most complete records of continental climate change in the Near East since the Middle Pleistocene. We used seismic reflection profiles to infer past changes in lake level and discuss potential causes related to changes in climate, volcanism, and regional tectonics since the formation of the lake ca. 600 ka ago. Lake Van’s water level ranged by as much as 600 m during the past ~600 ka. Five major lowstands occurred, at ~600, ~365–340, ~290–230, ~150–130 and ~30–14 ka. During Stage A, between about 600 and 230 ka, lake level changed dramatically, by hundreds of meters, but phases of low and high stands were separated by long time intervals. Changes in the lake level were more frequent during the past ~230 ka, but less dramatic, on the order of a few tens of meters. We identified period B1 as a time of stepwise transgressions between ~230 and 150 ka, followed by a short regression between ca. 150 and 130 ka. Lake level rose stepwise during period B2, until ~30 ka. During the past ~30 ka, a regression and a final transgression occurred, each lasting about 15 ka. The major lowstand periods in Lake Van occurred during glacial periods, suggesting climatic control on water level changes (i.e. greatly reduced precipitation led to lower lake levels). Although climate forcing was the dominant cause for dramatic water level changes in Lake Van, volcanic and tectonic forcing factors may have contributed as well. For instance, the number of distinct tephra layers, some several meters thick, increases dramatically in the uppermost ~100 m of the sediment record (i.e. the past ~230 ka), an interval that coincides largely with low-magnitude lake level fluctuations. Tectonic activity, highlighted by extensional and/or compressional faults across the basin margins, probably also affected the lake level of Lake Van in the past.     

Recent lake level variations in Lake Haubi, central Tanzania, interpreted from pollen and sediment studies

Variations in pollen assemblages and in physical and chemical composition of a dated sediment record from the small Lake Haubi in north central Tanzania, reveal lake level fluctuations since the late 19th century. Lake Haubi changed from a seasonally inundated swamp to a lake in the beginning of the 20th century. With the exception of 1942-44, when it dried out completely, it remained water filled until 1994 when it again turned into a swamp. The lake level fluctuations in Lake Haubi are largely in phase with fluctuations of the larger East African lakes levels during the 20th century, and are therefore interpreted as being mainly controlled by regional climatic fluctuations. However, the initial formation of Lake Haubi at the turn of the century was likely due to local catchment specific causes, e.g. changes in land use, as the rapid increase in the water level at this time does not correspond to other lake level records from the region.     

基于SWAT-X模型的抚河流域径流量模拟研究

建立抚河流域的SWAT-X模型,利用其敏感性分析模块分析参数灵敏度,得出4个敏感参数CN2、Gwqmn、rchrg_dp、ESCO;采用沙子岭、南城、廖家湾、娄家村4个水文站1998—2005年月数据进行水文参数率定并评价模型的适应性,结果表明径流模拟值均达到拟合精度(相对误差、相关系数、效率系数),SWAT-X模型适宜于抚河流域的径流量模拟。