气候变化对开都河流域径流的影响研究

利用SWAT模型模拟开都河流域的径流变化,并采用1990—2009年的水文站点径流数据进行精度验证,然后设定气候变化情景,模拟不同气候条件下径流的响应特征。结果表明:模拟结果与实测径流较吻合,剔除异常年份（1994年、1995年）后,校准期（1990—2000年）效率系数为0.58,平均相对误差为-5.7%,线性拟合度为0.8;验证期（2000—2009年）的结果与校准期接近,均达到了模型的评价标准,说明SWAT模型在开都河流域的适用性较好。基于此,采用任意情景设置方法,设置了25种气候变化（气温和降水）组合情景,研究了该流域对气候变化的响应,结果表明,气候变化对径流量的影响较为显著,降水增加或气温降低均会导致径流量增加,流域未来年均径流变化的主要影响因素是降水,温度的影响相对较弱。     

不同气候变化情景模式对大凌河流域径流的影响研究

为定量研究不同气候变化情景对大凌河径流的影响,探索气候变化下大凌河径流响应规律,基于分布式水文模型SWAT模型,通过设定不同气候变化情景(假定气温±2℃,降水量变化±10%),定量分析不同气候变化情景对大凌河径流的影响。研究成果表明:模型适合于大凌河径流模拟,模型参数率定期和验证期年径流模拟相对误差均在10%以内,确定性系数均达到0.8以上;气温升高2℃,流域径流增加5.8%,降雨量减少10%,流域径流量减少4.7%;降雨量增加10%,流域径流量增加4.3%。研究成果对于大凌河应对气候变化下水资源保护以及利用可提供参考。     

未来气候情境下渭河流域陕西段非点源污染负荷响应

[目的]在全球气候变暖的背景下,探讨气候条件变化对渭河流域陕西段非点源污染负荷的影响,旨在为流域综合治理措施提供依据,从而缓解气候变化对水环境的不利影响。[方法]基于非点源污染分布式模拟模型(SWAT模型),分别对2020,2030和2050年气温和降雨等气候因子变化下渭河流域陕西段径流及非点源污染负荷进行模拟,探讨了气候变化对该流域径流及水体中氮、磷年均负荷的影响。[结果](1)气候变化对流域径流量影响较大。随着未来气温升高降雨增加的共同作用下,径流量增加;到2050年,在平均气温增加2.2℃,降雨量增加7%的情况下,渭河陕西段径流量将增加11.9%。(2)在未来气候变化的影响下,流域年均总氮负荷增加20.9%;总磷负荷增加13.3%。[结论]未来气温升高和降雨增多的气候变化共同作用下,河道径流量增加,总氮、总磷负荷增多,农业非点源污染问题越来越突出。     

岷江上游流域不同土地利用与气候变化的径流响应研究

土地利用和气候变化对流域水循环和水资源的影响已经引起社会的广泛关注。以岷江上游流域为研究对象,以分布式水文模型SWAT（Soil and Water Assessment Tool）为研究工具,建立不同土地利用和气候变化情景,通过模型的校准与验证,模拟不同土地利用和气候变化的径流响应。模拟结果表明随着森林植被面积的减小径流量增大,且裸地增加对径流影响最显著。模拟径流量随着降水的增加而增大,且增加量主要产生于雨季。     

滦河流域气候变化的水文响应研究

以滦河流域为研究区,基于未来气候变化研究成果建立了16种气候变化情景,结合SWAT分布式水文模型模拟了不同气候变化情景下的水文过程,对滦河流域气候变化的水文响应进行了分析。结果表明:SWAT模型可以较好地模拟滦河流域的月流量过程,在研究区具有较好的适用性;流域气温升高将会导致蒸发量增加、径流减少。在以升温为主、降水变化存在很大不确定性的情况下,滦河流域径流量可能进一步衰减。在未来降水增加的情况下,流域年均地表径流增加趋势的空间差异显著,尤其是流域下游的迁西县等地增加幅度超过12mm,研究结果将为变化环境下滦河流域的水资源管理提供参考。     

基于SWAT模型的南渡江上游流域径流对气候变化的响应

为了评估未来气候变化对热带岛屿性森林流域径流的影响,以海南岛南渡江上游流域为例,构建本地化SWAT模型,基于CMIP6全球气候模式数据提取的气候变化信号,定量辨析了流域径流量对气候变化的响应。结果表明:(1)南渡江上游流域年平均径流量16.1 m³/s,旱季和雨季径流量分别占年径流量的17%,83%;(2)1961—2020年南渡江上游流域年平均径流减少趋势不显著,其中旱季径流增加4.6%,而雨季径流减少9.9%;(3)流域旱季径流增加量远低于雨季径流减少量致使年平均径流量减少,旱季径流增加由降水增多所致,雨季气温升高引起蒸发加剧是造成径流减少的关键;(4)在CMIP6计划的SSP119,SSP126,SSP434,SSP245,SSP460,SSP370和SSP585路径下,21世纪不同时期研究区径流变化主要受降水变化的影响,而21世纪后期气候变化加剧会引起研究区径流变化幅度加大。研究区径流对降水变化的敏感性高于气温,降水变化主导未来时期南渡江上游流域的径流量变化。     

SWAT模型在汤河西支流域水土流失模拟中的应用研究

以汤河西支流域为研究区域,引入SWAT模型,模拟汤河西支流域水土流失时空分布,并设定2种气候变化情景模式(气温升高2℃和气温降低2℃),以SWAT模型为模拟平台,定量分析不同气候变化情景模式对流域水土流失的影响.研究结果表明:SWAT模型模拟的汤河西支流域2000-2010年输沙量和实测输沙量之间的相对误差小于15％,模拟的月含沙量和实测月含沙量之间的拟合系数达到0.7以上,满足流域水土流失预测精度要求,适用于汤河西支流域水土流失模拟;流域年输沙量分布主要受降雨空间分布的影响,年输沙量为0.6 ×108 ～3.5 ×108 t的区域主要在流域东北部;气温升高2℃,流域产沙量减少8.7％,气温降低2℃,流域产沙量增加10.2％,研究成果对于汤河西支流域内水土流失保护和治理规划提供一定的参考价值.     

土地覆被和气候变化对锡林河流域径流量的影响

土地覆被和气候变化是影响流域水资源宏观调控以及合理规划的两个主要因素,以锡林河流域为研究区,借助锡林浩特及周边4个国家气象站点,通过设定情景模式与SWAT模型相结合的方法分别对其进行了分析研究。通过极端土地利用法对研究区内土地利用/覆被设定不同情景模式,研究了土地利用/覆被变化对径流量的影响,另外采用最新的气候模式CMIP5的两种RCP排放情景RCP4.5和RCP8.5,预测了未来气温、降水、径流的变化情形。结果表明:土地变化对径流量的年际变化影响较弱,但对于汛期径流量影响显著;研究区径流量对气候表现敏感程度非常显著,未来最低、最高气温均表现出增温趋势且未来降水、径流变化趋势基本保持一致,呈增长趋势。     

土地利用和气候变化对嘉陵江流域水文特征的影响

以嘉陵江流域为研究区,通过模型校准与验证得到适宜于该流域的SWAT模型,在综合考虑土地利用和气候变化特征的基础上构建多种情景模式,模拟了不同情景下的主要水文要素。结果表明:(1)1985—2005年,流域林地减少,城镇和农村居民用地增加;草地和工业用地在上游减少,中下游地区增加;耕地在上游增加,中下游地区减少。流域总体呈暖干化趋势,上游地区水热条件的变化较中下游地区大。(2)与1976—1995年相比,土地利用和气候变化共同作用使地表径流增加,地下径流、土壤含水量、壤中流、实际蒸散发和产水量减少。其中,气候变化对流域水文过程的影响大于土地利用变化。林草地具有明显的水土保持作用,耕地在水土保持和水源涵养方面呈负贡献。RCP8.5情景下年平均产水量较RCP 4.5情景高,但长期来看,RCP 4.5情景对降低地表径流和实际蒸散发,增加地下径流、壤中流和产水量的作用优于RCP 8.5。(3)土地利用和气候变化对流域地表径流的影响较大,对中下游的影响大于对上游的影响。     

嫩江流域春季解冻期土壤侵蚀对气候变化的响应

利用嫩江流域控制站大赉水文站的春季解冻期径流量和输沙量资料和同期嫩江流域16个气象站的气象资料,分析了1963-1988年嫩江流域春季解冻期土壤侵蚀对气候变化的响应。结果表明:随着春季解冻期平均气温的升高,温差呈明显减少趋势,降水呈增加趋势;平均气温和降水量均对径流量的增加有正向作用,但降水较气温对径流的影响更为显著;通过对平均气温、降水量、径流量（包括融雪径流）和输沙量进行偏相关分析,春季解冻期的降水量和径流量对输沙量的影响显著,且为正相关,与平均气温成负相关,但影响不显著。     

不同气候模式对密云水库流域非点源污染负荷的影响

以密云水库流域内4个气象站1961-2000年40 a的气象特征分析结果为基础,采用统计分析和线性回归的方法,预测流域气候变化趋势,采用任意情景设置法设定25种气候情景(5种温度变化和5种降雨变化的组合情景)和3个水文情景年(丰、平、枯水年)。利用HSPF(hydrologic simulation program-fortran)模型模拟密云水库流域不同气候变化情景下径流量和非点源污染物负荷量的变化情况。结果表明:1)增加20%降雨,能增加73.4%的径流量,而减少20%降雨会减少56.3%的径流,而气温变化对径流和水质负荷影响不是很明显;2)总氮和总磷负荷随径流增加而增大,总磷负荷对径流变化更加敏感,降雨增加20%,总氮和总磷负荷分别增加约70.8%和78.3%;而减少20%降雨,会使得总氮和总磷负荷分别减少约55.3%和57.2%;3)从水文年对比来看,潮河流域丰水年径流量是枯水年的3.1倍,总氮、总磷负荷则分别是枯水年的2.9倍、3.5倍,白河流域丰水年径流量是枯水年的4.6倍,总氮、总磷负荷则分别是枯水年的5.6倍、8.5倍,且年内非点源污染负荷主要集中在汛期,高风险区主要分布在怀柔区、延庆县、滦平县以及密云县,需要对其采取对应的措施来控制非点源污染的影响。     

龙川江上游径流量变化及其对气候变化的响应

基于1970—2012年龙川江上游小河口水文站的径流资料和楚雄的气象资料,运用M-K法、相关系数法、累积距平法等方法,分析了龙川江上游径流量、降水量和气温的年内、年际和年代际的变化以及径流量对气候变化的响应。结果表明:龙川江上游径流量年内分配极不均,在1994年后渐趋均匀,年径流量呈不显著的波动下降趋势,而且径流量在70,80年代和2010—2012年偏枯,90和00年代偏丰;年平均气温和年降水量都呈上升趋势,但后者的趋势不明显;年降水量对年径流量的影响很明显,而年平均气温对径流量的影响较小,四个季节中春季和秋季的径流量受降雨量变化的影响较大,降水量和气温的变化对夏季径流的影响都较为明显,而冬季相反。总之,不同季节的径流量对不同气候因素的响应是不同的。     

Landscape sensitivity to rapid environmental change—a Quaternary perspective with examples from tropical areas

A millennial scale of ‘rapid’ change during the Quaternary is recorded in GRIP and GISP2 ice-core records, and is also found in tropical oceans. Rapid warming episodes followed by gradual cooling, associated with sub-Milankovich cycles implies an asymmetry in the behaviour of climate that is likely to be reflected in landscape responses. Slope failures, floods, colluvial/alluvial sedimentation may reflect short-term changes in the record, but reorganisation of slope and fluvial systems involves significant time lags or delays, often on a millennial scale, and requiring changes to the vegetation cover. While some records of sedimentation indicate major landscape instability during last 20 ky, or in the early Holocene, others indicate pulses of activity throughout the Last Glacial Cycle (LGC). These differences may reflect regional patterns of climate change, but also illustrate the importance of landscape sensitivity to our understanding of the impacts of rapid environmental change. Methodological problems arise in attempting correlations between site-specific records of sedimentation and integrated signals of hydrologic change found in deltaic and off-shore fans.     

水稻灌溉需水量对气候变化响应的模拟

气候变化会导致作物耗水过程改变,从而影响灌溉需水。研究水稻灌溉需水对气候变化的响应规律,有助于合理制定应对气候变化的灌溉策略,保障水资源可持续利用和粮食安全。该文基于1961-2010年气象数据和HadCM3大气环流模式A2和B2两种情景下的统计降尺度模拟结果,利用经田间试验资料验证后的水稻模型ORYZA2000,模拟淹水灌溉和间歇灌溉两种灌溉处理下、历史和未来情景下水稻灌溉需水对气候变化的响应规律。结果表明:过去50年,间歇灌溉和淹水灌溉模式下水稻耗水量呈现显著上升趋势,而水稻灌溉需水量和产量都呈现下降趋势,分别由降水增加和气温升高、辐射下降导致的生育期缩短引起;未来气候情景下,间歇灌溉和淹水灌溉模式下水稻耗水量在未来3个时期(2020s,2050s和2080s)均呈现不同程度的增加;耗水量的显著增加和降水的减少导致了未来3个时期水稻灌溉需水量的明显增加;受持续增温的减产效应影响,水稻产量在未来3个时期呈现减少趋势,且降幅逐渐变大。     

The impacts of potential climate change and climate variability on simulated maize production in China

This study assessed the impacts of potential climate change on maize yields in China, using the CERES-Maize model under rainfed and irrigated conditions, based on 35 maize modeling sites in eastern China that characterize the main maize regions. The Chinese Weather Generator was developed to generate a long time series of daily climate data as baseline climate for 51 sites in China. Climate change scenarios were created from three equilibrium general circulation models: the Geophysical Fluid Dynamics Laboratory model, the high-resolution United Kingdom Meteorological Office model, and the Max Planck Institute model. At most sites, simulated yields of both rainfed and irrigated maize decreased under climate change scenarios, primarily because of increases in temperature, which shorten maize growth duration, particularly the grain-filling period. Decreases of simulated yields varied across the general circulation model scenarios. Simulated yields increased at only a few northern sites, probably because maize growth is currently temperature-limited at these relatively high latitudes. To analyze the possible impacts of climate variability on maize yield, we specified incremental changes to variabilities of temperature and precipitation and applied these changes to the general circulation model scenarios to create sensitivity scenarios. Arbitrary climate variability sensitivity tests were conducted at three sites in the North China Plain to test maize model responses to a range of changes (0%, +10%, and +20%) inthe monthly standard deviations of temperature and monthly variation coefficients of precipitation. The results from the three sites showed that incremental climate variability caused simulated yield decreases, and the decreases in rainfed yield were greater than those of irrigated yield.     

Development and application of a simple hydrologic model simulation for a Brazilian headwater basin

Physically based hydrologic models for watersheds are important tools to support water resources management and predict hydrologic impacts produced by land-use change. Grande River Basin is located in southern Minas Gerais State, and the Grande River is the main tributary of Basin which has 2080 km² draining into the Camargos Hydropower Plant Reservoir (CEMIG — “Minas Gerais State Energy Company”). The objectives of this work were: 1) to create a semi-physically based hydrologic model in semi-distributed to sub-basins approach and based on GIS and Remote Sensing tools and, 2) to simulate the hydrologic responses of the Grande River Basin, thus creating an important tool for management and planning of water resources for region. The hydrologic model is based on the SCS Curve Number (SCS-CN) and MGB/IPH models, and structured into three hydrologic components: estimation of the flow components (quick runoff, hortonian and base flows), propagation into the respective soil reservoirs (surface, sub-surface and shallow saturated zone) and propagation into the channels. Precipitation and discharge data sets were obtained from the Brazilian National Water Agency (ANA). Reference evapotranspiration (ETo) data were obtained from the Brazilian National Meteorological Institute (INMET). In order to estimate actual evapotranspiration, crop coefficient, soil moisture and satellite image interpretation of actual land-use were applied. The long-term hydrologic data series were structured for period between 1990 and 2003. The calibration and validation process was carried out by evaluating the behavior of the Nash–Sutcliffe Coefficient (C_NS), obtained from three different combinations of calibration and validation years. This allowed us to evaluate the model performance to simulate years in which El Niño (EN) and La Niña (LN) events were registered (1997–1998 and 1999–2000, respectively). The combinations of calibration and validation years were: the first 7 years to calibrate and remaining 6 years to validate; the first 9 years to calibrate and remaining 4 years to validate; and first 11 years to calibrate and the last 2 years to validate. The statistical precision showed that the model was able to simulate the hydrologic impacts, including years of EN and LN events, with C_NS scores greater than 0.70 in both situations. The evaluation of the C_NS scores showed small variation in the coefficient as the years of validation decreased. In addition, the model was also able to simulate the hydrologic impacts of land-use change in the Grande River Basin, based on the C_NS scores of 0.80 for different combinations of validation periods. The hydrologic impacts in Grande River Basin produced from grassland area converted to eucalyptus under three specific scenarios were evaluated, which predicted annual runoff mean reductions of up to 17.8%, due to an increase in evapotranspiration rate for the eucalyptus plantation.     

Development and application of a simple hydrologic model simulation for a Brazilian headwater basin

Physically based hydrologic models for watersheds are important tools to support water resources management and predict hydrologic impacts produced by land-use change. Grande River Basin is located in southern Minas Gerais State, and the Grande River is the main tributary of Basin which has 2080 km² draining into the Camargos Hydropower Plant Reservoir (CEMIG — “Minas Gerais State Energy Company”). The objectives of this work were: 1) to create a semi-physically based hydrologic model in semi-distributed to sub-basins approach and based on GIS and Remote Sensing tools and, 2) to simulate the hydrologic responses of the Grande River Basin, thus creating an important tool for management and planning of water resources for region. The hydrologic model is based on the SCS Curve Number (SCS-CN) and MGB/IPH models, and structured into three hydrologic components: estimation of the flow components (quick runoff, hortonian and base flows), propagation into the respective soil reservoirs (surface, sub-surface and shallow saturated zone) and propagation into the channels. Precipitation and discharge data sets were obtained from the Brazilian National Water Agency (ANA). Reference evapotranspiration (ETo) data were obtained from the Brazilian National Meteorological Institute (INMET). In order to estimate actual evapotranspiration, crop coefficient, soil moisture and satellite image interpretation of actual land-use were applied. The long-term hydrologic data series were structured for period between 1990 and 2003. The calibration and validation process was carried out by evaluating the behavior of the Nash–Sutcliffe Coefficient (C_NS), obtained from three different combinations of calibration and validation years. This allowed us to evaluate the model performance to simulate years in which El Niño (EN) and La Niña (LN) events were registered (1997–1998 and 1999–2000, respectively). The combinations of calibration and validation years were: the first 7 years to calibrate and remaining 6 years to validate; the first 9 years to calibrate and remaining 4 years to validate; and first 11 years to calibrate and the last 2 years to validate. The statistical precision showed that the model was able to simulate the hydrologic impacts, including years of EN and LN events, with C_NS scores greater than 0.70 in both situations. The evaluation of the C_NS scores showed small variation in the coefficient as the years of validation decreased. In addition, the model was also able to simulate the hydrologic impacts of land-use change in the Grande River Basin, based on the C_NS scores of 0.80 for different combinations of validation periods. The hydrologic impacts in Grande River Basin produced from grassland area converted to eucalyptus under three specific scenarios were evaluated, which predicted annual runoff mean reductions of up to 17.8%, due to an increase in evapotranspiration rate for the eucalyptus plantation.     

The Impact of Climate Change on Metal Transport in a Lowland Catchment

This study investigates the impact of future climate change on heavy metal (i.e., Cd and Zn) transport from soils to surface waters in a contaminated lowland catchment. The WALRUS hydrological model is employed in a semi-distributed manner to simulate current and future hydrological fluxes in the Dommel catchment in the Netherlands. The model is forced with climate change projections and the simulated fluxes are used as input to a metal transport model that simulates heavy metal concentrations and loads in quickflow and baseflow pathways. Metal transport is simulated under baseline climate (“2000–2010”) and future climate (“2090–2099”) conditions including scenarios for no climate change and climate change. The outcomes show an increase in Cd and Zn loads and the mean flux-weighted Cd and Zn concentrations in the discharged runoff, which is attributed to breakthrough of heavy metals from the soil system. Due to climate change, runoff enhances and leaching is accelerated, resulting in enhanced Cd and Zn loads. Mean flux-weighted concentrations in the discharged runoff increase during early summer and decrease during late summer and early autumn under the most extreme scenario of climate change. The results of this study provide improved understanding on the processes responsible for future changes in heavy metal contamination in lowland catchments.     

吉林省西部主要水体面积动态变化遥感监测

[目的]分析吉林省西部主要水体的动态变化,了解西部水资源现状,为水资源保护、利用和可持续发展提供有力支持。[方法]利用2000年以来的MODIS数据,采用目视解译的方法提取吉林省西部主要水体分布及面积数据,对年际、年内变化规律及影响因素进行分析。[结果]2000年以来,月亮泡水库、向海水库和查干湖均表现出向北部推进和水域面积增加的趋势;水体面积表现出明显的年周期变化规律,雨季期间及后期一般会出现较大的水域面积,形成了与季节性气候相适应的年周期变化状态;气候变化趋势,特别是降水对水体面积的影响较为显著,人类活动也起到了明显的推动作用。[结论]2000年以来,受气候变化及人类活动的影响,西部主要水体的水域面积有增加的趋势。