The impact of soybean expansion on mammal and bird,in the Balsas region,north Brasilian Cerrado

In order to analyse the impact of land use change, it is particularly important to know how organisms use resources distributed across a heterogeneous landscape. The main objective of this study is to analyse the potential impact of land use change on bird and mammal fauna, by using a coupled model approach. The CLUE (Conversion of Land Use and its Effects) model has been applied to obtain the spatial pattern of land use change for a scenario with soybean expansion in the Cerrado of Maranhão State in Brazil. These land use change maps were used as the input for the LEDESS (Landscape Ecological Decision and Evaluation Support System) model to evaluate the impact of habitat fragmentation on mammal and bird species. The scenarios demonstrated that high quality habitat for all studied species will be lost in the future when current trends in agricultural expansion continue, but these changes will have species-specific impacts. The most relevant ecological impact under the explored scenarios was habitat fragmentation expressed by the increase the number of habitat clusters. The coupled model approach of LEDESS and CLUE made it possible to project the spatial impact of soybean expansion on habitat dynamics in the studied region. This model approach can help to design effective ecological infrastructure to facilitate species survival and to implement an effective habitat network in the Balsas region.     

中国土地利用空间格局动态变化模拟——以规划情景为例

土地利用变化研究在环境可持续发展研究领域中具有重要的地位,其空间分布格局的变化影响到生物地球化学循环、气候变化、生物多样性等。采用土地利用动态变化模型Dyna-CLUE模拟了在规划情景下中国土地利用变化未来空间分布格局。将土地利用类型分为六大类,即耕地、草地、林地、建设用地、水域和其它用地。驱动因子包括地形地貌、气候、社会交通等方面,对动态驱动因子如气温、降水、人口交通等,考虑了其在未来情景下的发展趋势。基于土地利用类型与驱动因子之间的定量关系和土地利用类型之间的转换规则等,模拟出至2020年中国土地利用分布格局。结果表明,至2020年,中国东南部、黄淮海平原、四川盆地等地区耕地面积将增加,东北、西北等农牧交错区、农林交错区和沙漠边缘耕地面积将会呈轻度减少趋势;林地面积将增加1417.91万hm2,主要发生在中国东北部以及西南部水热条件好的地区;中国草地在面积上保持稳定,空间上中东部、东南地区草地面积减少,内蒙古中部,青海东部,四川盆地北缘区和青藏高原等地面积增加;建设用地增加531.76万hm2,主要发生在中国的东部地区。     

土地利用变化模拟研究进展

土地利用变化研究经历了近30年的快速发展,学者基于不同建模目标构建出多种土地利用变化模型,实现了从数量模拟到时空格局模拟,从单一模型向多种模型耦合的跨越。当前研究主要在元胞自动机(Cellular Automata,CA)模型和CLUE-S (Conversion of Land Use and its Effects at Small region extent)模型的基础上进行改进,马尔科夫模型、系统动力学(System Dynamics,SD)模型、Logistic回归和随机森林等均可计算CA模型和CLUE-S模型中所需的土地利用需求,多标准评价、地理加权回归、多主体模型以及人工神经网络等方法也多被用于CA模型的扩展,而CLUE-S的改进则存在模型本身系列的升级。这些模型广泛应用于各种区域和尺度土地利用变化预测实例研究并研发软件系统和数据集。驱动力分析主要从自然因素与人文因素两方面进行,人文因素是引发土地利用变化的主要因素。在目前的研究中,由于技术手段的限制,仍然存在时空尺度、数据误差、数据整合的不确定性等问题。未来土地利用变化模拟研究应进一步发挥大数据技术优势,推动土地利用变化模拟研究朝向精细化、多元化方向发展。结合生态环境领域实际问题,深挖土地利用变化与其生态环境效应之间的互馈机制,将研究视角从探究人类活动对土地利用变化的影响逐渐转向二者相互作用,最终促进人地关系协调发展。     

Response of land use/coverage change to hydrological dynamics at watershed scale in the Loess Plateau of China

In this study Qiaozidong and Qiaozixi watersheds in Loess Plateau were selected as the case to investigate the effects of land use/coverage change on hydrological dynamics. The results showed that the runoff coefficient of controlled watershed reduced by about 50%, 85%, 90%, respectively, in wet, normal and dry years in comparison with that of uncontrolled watershed. The average runoff coefficient reduced by 73.6% during the period of 1995–2004 compared with that in the previous period of 1986–1994 for land use in controlled watershed. And the impacts of land use and vegetation changes on runoff were strengthened in response to the increasing rainfall. Additionally, the impacts of land use/coverage change on runoff yield are characterized by seasonal fluctuation. The maximum monthly runoff reduction in the both watersheds occurred in May, which was consistent with the period of the maximum land coverage appeared. Finally, when the rainfall intensity reached a certain threshold, the variance of flood peak in two watersheds reduced, which showed that the effects of forest on flood weakened. The flood peak discharge frequencies indicated that peak discharge would respond to the land use and vegetation change obviously on condition that there were the same frequencies of rainfall intensity in the earlier and later periods.     

土地利用模型时间尺度预测能力分析——以CLUE\|S模型为例

模型模拟是生态学中的重要方法,特别是当实验不可进行时.在不同预案下基于模型的土地利用预测对于土地利用规划和政策制定具有十分重要意义.然而,很多研究没有对模型在研究区的时间尺度预测能力加以分析,从而可能导致模拟结果的不可靠.以岷江上游地区为例,采用Kappa指数系列对CLUE-S模型在研究区的时间尺度预测能力进行研究.结果表明CLUE-S模型在岷江上游地区时间尺度上的最大预测能力为22a,超过时间预测能力的预测结果不可靠.研究为土地利用模型模拟时间尺度确定提供了一种有效的方法.     

Simulation of watershed hydrology and stream water quality under land use and climate change scenarios in Teshio River watershed,northern Japan

Quantitative prediction of environmental impacts of land-use and climate change scenarios in a watershed can serve as a basis for developing sound watershed management schemes. Water quantity and quality are key environmental indicators which are sensitive to various external perturbations. The aim of this study is to evaluate the impacts of land-use and climate changes on water quantity and quality at watershed scale and to understand relationships between hydrologic components and water quality at that scale under different climate and land-use scenarios. We developed an approach for modeling and examining impacts of land-use and climate change scenarios on the water and nutrient cycles. We used an empirical land-use change model (Conversion of Land Use and its Effects, CLUE) and a watershed hydrology and nutrient model (Soil and Water Assessment Tool, SWAT) for the Teshio River watershed in northern Hokkaido, Japan. Predicted future land-use change (from paddy field to farmland) under baseline climate conditions reduced loads of sediment, total nitrogen (N) and total phosphorous (P) from the watershed to the river. This was attributable to higher nutrient uptake by crops and less nutrient mineralization by microbes, reduced nutrient leaching from soil, and lower water yields on farmland. The climate changes (precipitation and temperature) were projected to have greater impact in increasing surface runoff, lateral flow, groundwater discharge and water yield than would land-use change. Surface runoff especially decreased in April and May and increased in March and September with rising temperature. Under the climate change scenarios, the sediment and nutrient loads increased during the snowmelt and rainy seasons, while N and P uptakes by crops increased during the period when fertilizer is normally applied (May through August). The sediment and nutrient loads also increased with increasing winter rainfall because of warming in that season. Organic nutrient mineralization and nutrient leaching increased as well under climate change scenarios. Therefore, we predicted annual water yield, sediment and nutrient loads to increase under climate change scenarios. The sediment and nutrient loads were mainly supplied from agricultural land under land use in each climate change scenario, suggesting that riparian zones and adequate fertilizer management would be a potential mitigation strategy for reducing these negative impacts of land-use and climate changes on water quality. The proposed approach provides a useful source of information for assessing the consequences of hydrology processes and water quality in future land-use and climate change scenarios.     

城市化流域生态系统服务价值时空分异特征及其对土地利用程度的响应

以南京市九乡河流域为研究区域,以2003与2009年2景QuickBird影像数据为基本信息源,应用空间自相关模型,结合GIS空间分析技术,定量探讨了城市化流域生态系统服务价值时空分异特征,以及土地利用程度对生态服务价值空间分异的影响.结果表明:2003-2009年,九乡河流域生态系统服务总价值减少了2.59％,而流域生态系统服务价值的空间聚集性增强;生态服务价值的高-高区域主要集中在流域上游,低-低区域主要集中在流域下游的仙林大学城一带;九乡河流域生态系统服务价值空间分异发生了明显变化,下游仙林大学城一带低-低分布区快速扩张,而高-高分布区仅在九乡河源头及下游的局部区域有所增加;流域生态服务价值空间自相关表现出明显的尺度效应,随着研究尺度增大,生态服务价值的空间自相关性逐渐增强;九乡河流域生态服务价值的空间分异及其变化主要是由土地开发利用引起,流域土地利用程度对生态服务价值存在明显的负效应.     

Impact of land use change during 1989–2009 on eco-capacity in Dongjiang watershed

Aims For sustainable watershed development planning, this study explores how ecological carrying capacity varies with changes in land use type and population.
Methods Based on interpretation and analysis of five Landsat TM remote sensing images for 1989, 1994, 1999, 2004, and 2009, respectively, we examined the spatio-temporal patterns of land use change in the upper, middle, and lower reaches of Dongjiang watershed, using the total rate of change and single and integrated degree of land use dynamics as indicators. We calculated the total and per capita eco-capacity for the watershed in different years based on the population data, equivalence factors, and yield factors, in addition to the data of land use and land cover change, and further analyzed the factors determining the direction of changes in the eco-capacity.
Important findings The results showed that: (1) there were apparent changes in the area for various land use types between 1989 and 2009. Despite the urban development, the coverage of forest vegetation increased, indicating lack of trade-off between urbanization and vegetation coverage. However, there were different patterns of change in land use among the upper, middle, and lower reaches. The land use type mainly varied from garden fields to forests in the upper and middle reaches of the watershed, while in the lower reach a change from arable land to build-up area dominated. (2) With the population growth along the Dongjiang watershed over the past two decades, although the per capita eco-capacity indicated a downward trend, its rate of decline lagged behind thepopulation growth rate, and the total eco-capacity still showed a trend of increase, implying an optimization of land use types during the 20-year period. With respect to the temporal patterns, in the decade (1994–2004) after the end of the “10-year greening of Guangdong Province”, per capita eco-capacity tended to be relatively stable under the pressure of population growth, while it declined quickly in the periods of 1989–1994 and 2004–2009. The former period was probably associated with the development of reform and opening up policy, and the latter seemed to have less possibility on spatial optimization of land use types. The total eco-capacity showed different trends among the three regions; the upper and middle reaches exhibited an unstable trend (i.e., from decreasing to increasing), while the lower reach indicated a pattern of increasing–decreasing–stable trend. In conclusion, the increasing population demand for urbanization did not lead to deterioration of the forest resources in the watershed. To some extent, we could thus achieve the coordinated development in both aspects. In spite of increasing demand on ecological resources with population growth, we could establish a better strategy in land use to improve ecological services, and to reduce the downward trend in the per capita eco-capacity.     

Land cover change or land‐use intensification: simulating land system change with a global‐scale land change model

Land‐use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land‐use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970–2000 period and projections of other global and regional land change models.     

Towards an integrated global framework to assess the impacts of land use and management change on soil carbon: current capability and future vision

Intergovernmental Panel on Climate Change (IPCC) Tier 1 methodologies commonly underpin project‐scale carbon accounting for changes in land use and management and are used in frameworks for Life Cycle Assessment and carbon footprinting of food and energy crops. These methodologies were intended for use at large spatial scales. This can introduce error in predictions at finer spatial scales. There is an urgent need for development and implementation of higher tier methodologies that can be applied at fine spatial scales (e.g. farm/project/plantation) for food and bioenergy crop greenhouse gas (GHG) accounting to facilitate decision making in the land‐based sectors. Higher tier methods have been defined by IPCC and must be well evaluated and operate across a range of domains (e.g. climate region, soil type, crop type, topography), and must account for land use transitions and management changes being implemented. Furthermore, the data required to calibrate and drive the models used at higher tiers need to be available and applicable at fine spatial resolution, covering the meteorological, soil, cropping system and management domains, with quantified uncertainties. Testing the reliability of the models will require data either from sites with repeated measurements or from chronosequences. We review current global capability for estimating changes in soil carbon at fine spatial scales and present a vision for a framework capable of quantifying land use change and management impacts on soil carbon, which could be used for addressing issues such as bioenergy and biofuel sustainability, food security, forest protection, and direct/indirect impacts of land use change. The aim of this framework is to provide a globally accepted standard of carbon measurement and modelling appropriate for GHG accounting that could be applied at project to national scales (allowing outputs to be scaled up to a country level), to address the impacts of land use and land management change on soil carbon.     

Optimal conservation planning of multiple hydrological ecosystem services under land use and climate changes in Teshio river watershed,northernmost of Japan

Most anthropogenic activities impacted on water quality and quantity, and further impacted on ecosystem services (ESs) in watershed are related to land use and climate changes those may cause losses of ecosystem functions. Effective information regarding ESs and their optimal priority conservation planning responded to land use and climate changes provide useful support for diverse stakeholders in ESs planning, management and policies. This study integrated the approach of spatially explicit ESs (water yield, inorganic nutrient, organic nutrient and sediment retentions) by using hydrology and material flow model (Soil and Water Assessment Tools, SWAT model) into systematic conservation of hydrological ESs according to land use and climate changes in Teshio watershed located in the north of Hokkaido, Japan. We investigated the spatial patterns and the hotspots of ESs changes to determine the spatial pattern of changes in systematic conservation optimal area of ES protection in terms of ESs protection targets. Under the land use and climate change scenarios, the forest land use significantly affected on the water yield, sediment, organic-Nitrogen (N) and organic-Phosphorous (P) retentions. The agricultural land (paddy and farmland fields) impacted on the inorganic-N and inorganic-P retentions. We applied the systematic conservation model (MARXAN model) to optimize the area for management of hydrological ESs satisfied the protection targets (30% and 50% of potential maximum ESs values among all scenarios) in all and individual ecosystem services, respectively. The simulated results indicated that the areas of spatial optimal ESs protection for all hydrological ESs were totally different from those for individual ESs. For bundles of ESs, the optimal priority conservation areas concentrated in southwest, north, and southeast of this watershed, which are related to land use, topography and climate driving factors. These places could guarantee ESs sustainability from both environmental protection and agricultural development standpoints. The priority conservation area turned more compact under climate change because the increased precipitation and temperature increased ESs amount. For individual ESs, the optimal priority conservation areas of water yield, sediment retention and organic nutrient retention were traded off against those of inorganic nutrient retention (lower Jaccard's indexes and negative correlations of selection times). Especially, the negative correlation of selection times increased as the conservation target increased from 30% to 50%. The proposed approach provided useful information for assessing the responses of ESs and systematic conservation optimal planning to the land use and climate changes. The systematic conservation optimal areas of hydrological ESs provided an effective trade-off tool between environmental protection (sediment and organic nutrient retentions) and economic development (water yield and inorganic nutrient retention).     

黄土丘陵沟壑区典型流域土地利用/土地覆被变化水文动态响应

以黄土高原第三副区桥子东、西沟流域为例,分析了土地利用／土地覆被变化的水文动态响应。研究结果表明：土地利用／土地覆被对年径流有显著影响,治理流域较未治理流域在丰水年、平水年和枯水年的径流系数分别减少约50％、85％和90％;流域土地利用后期（1995～2004年）较前期（1986～1994年）多年平均径流系数下降73．6％,且随降雨增多,土地利用与植被变化对径流的响应增强。土地利用／土地覆被变化对径流量的影响具有季节性特征,治理与非治理流域多年平均最大月径流系数减少时期与流域最大地表覆盖期具有一致性,即5月份径流系数减少值最大;同一降水条件下流域两期土地利用的产流量仅在生长季具有明显的差异。流域洪水径流量与场降雨量和30min最大雨强有较好的相关关系,场降雨量与30min雨强对治理流域洪水流量的影响要强于非治理流域;暴雨在达到一定强度后,对比流域的洪峰流量差异减小,即森林植被对洪水的影响减弱。经洪水频率分析,认为流域前后两期土地利用若具有相同频率的降雨强度,则一定频率范围内洪峰流量对土地利用与植被变化产生明显响应。     

CLUE-S模型在南京市土地利用变化研究中的应用

土地利用/覆盖变化模型是研究区域景观动态并解释其驱动机制的重要技术手段.应用CLUE-S模型,在Landsat TM影像等相关数据支持下,对南京地区1998-2006年土地利用的时空动态变化进行了研究.结果表明:各土地利用类型变化受地形因素影响最大,人均GDP与城镇用地和农业用地的分布呈显著相关,城乡主干道对土地利用变化的贡献显著大于省级及以上道路;海拔较高区域林地的发生比率较高,而地形低平区域农田、城建用地的发生比率较高.经检验,在300 m空间分辨率水平,对南京地区2003年、2006年土地利用状况模拟的精度分别达到了85.7%和84.1%;而通过将研究区分成若干子区,分别修正模型参数并重新模拟,准确率提高到89.7%和88.3%,分区赋值法有效地提高了模拟精度.研究表明,CLUE-S模型对城市发展的空间结构也有较强的预测能力,对指导城市规划、分析景观动态的驱动机制有重要参考价值.     

黄土高塬沟壑区小流域土地利用变化及其生态效应分析

基于王东沟流域1994和2004年两期土地利用图,通过构建土地利用动态变化模型和区域生态环境指标,定量分析了王东沟流域1994--2004年土地利用时空变化特征,并以生态系统服务功能衡量了土地利用类型和土地利用变化类型的生态效应．结果表明,1994—2004年王东沟流域农地大幅度减少,草地和果园大量增加,林地和非生产地变化不大;变化速度依次为草地〉果园〉非生产地〉农地〉林地;土地利用变化类型多样,农地转出和林地转入是其主要类型;土地利用的空间迁移方向为农地和果园向西北方向迁移（塬区）,林地和草地向东南方向（沟壑区）迁移．1994--2004年土地利用变化带来了良好的生态效益,但不同土地类型和不同土地变化类型的生态效应不同,提高和降低生态系统服务功能的作用并存．农地减少对生态环境产生负面作用,林草和果园的增加改善了生态环境,提高了其生态服务价值;土地利用变化类型中,改善生态环境的主要是转为林地和果园的变化类型,降低生态系统服务功能的主要是林地转出类型和农地转为非生产地类型．     

应用SWAT模型研究潮河流域土地利用和气候变化对径流的影响

为定量分析潮河流域土地利用和气候变化对流域径流变化的影响,应用SWAT模型对流域上游至下游的大阁、戴营和下会3个水文站径流进行模拟,采用情景法分析径流对土地利用和气候变化的响应。在模型校准期和验证期采用两个参数:p因子和r因子来评价模拟的拟合度及不确定性。结果表明,3个水文站在校准期和验证期的p因子值分别为:0.70和0.77,0.87和0.82,0.92和0.78,r因子值分别为0.63和0.90,0.97和0.79,0.88和0.92,评价整个流域模拟有效性的模型目标函数g最佳值为0.66,说明该模型对潮河流域的产水量模拟具有很好的适用性。以1981—1990年为基准期,1991—2000年流域土地利用变化造成年径流量减少了4.10 mm,而气候变化导致年径流增加了29.68 mm;2001—2009年土地利用变化造成年径流量减少2.98mm,气候变化造成年径流量减少了14.30 mm。与1999年土地利用条件模拟径流值相比,几种极端情景法模拟分析结果表明:灌木林地情景下年径流增加了158.2%,草地情景下年径流增加了4.1%,林地和耕地情景下年径流分别减少23.7%和41.7%;不同气候变异情景模拟结果显示,径流对降水的变化敏感性高于对温度变化的敏感性,降水每增加10%,径流平均增加23.9%。温度每增加12%,径流平均减少6%。因此,在气候变化背景下,优化土地利用结构与方式是实现流域水资源科学管理的途径之一。     

Gross changes in reconstructions of historic land cover/use for Europe between 1900 and 2010

Historic land‐cover/use change is important for studies on climate change, soil carbon, and biodiversity assessments. Available reconstructions focus on the net area difference between two time steps (net changes) instead of accounting for all area gains and losses (gross changes). This leads to a serious underestimation of land‐cover/use dynamics with impacts on the biogeochemical and environmental assessments based on these reconstructions. In this study, we quantified to what extent land‐cover/use reconstructions underestimate land‐cover/use changes in Europe for the 1900–2010 period by accounting for net changes only. We empirically analyzed available historic land‐change data, quantified their uncertainty, corrected for spatial‐temporal effects and identified underlying processes causing differences between gross and net changes. Gross changes varied for different land classes (largest for forest and grassland) and led to two to four times the amount of net changes. We applied the empirical results of gross change quantities in a spatially explicit reconstruction of historic land change to reconstruct gross changes for the EU27 plus Switzerland at 1 km spatial resolution between 1950 and 2010. In addition, the reconstruction was extended back to 1900 to explore the effects of accounting for gross changes on longer time scales. We created a land‐change reconstruction that only accounted for net changes for comparison. Our two model outputs were compared with five commonly used global reconstructions for the same period and area. In our reconstruction, gross changes led in total to a 56% area change (ca. 0.5% yr^?1) between 1900 and 2010 and cover twice the area of net changes. All global reconstructions used for comparison estimated fewer changes than our gross change reconstruction. Main land‐change processes were cropland/grassland dynamics and afforestation, and also deforestation and urbanization.     

不同空间尺度的景观格局对流溪河水质的影响

为探究不同空间尺度的景观格局对流溪河水质的影响,于2020年6月和2021年1月在流溪河干流15个采样点进行了水样的采集,测定了水温、溶解氧、pH、氨氮、硝态氮、硫酸盐和氯化物等水质指标。结合遥感解译所得的土地利用数据,提取了不同空间尺度(子流域和河岸带缓冲区)的景观格局指数,采用Bioenv分析、Mantle检验、方差分解和层次分割理论等方法揭示了景观格局对水质变化的影响。研究结果表明：氨氮是流溪河的主要污染物。土地利用结构与空间格局特征对水质的影响存在空间尺度效应。在100 m河岸带缓冲区,水域是影响水质的主要贡献源;而在其他空间尺度建设用地是影响水质的主要贡献源。在子流域尺度,林地和建设用地的斑块密度(PD指数)是影响水质变化的核心特征;而在河岸带缓冲区尺度,水域和建设用地的连通性(CONTAG指数)和林地的多样性(SHDI指数)是影响水质变化的关键特征。在各个空间尺度,土地利用与空间格局的交互作用对驱动水质变化起主导作用,尤其在1000 m河岸带缓冲区对水质的贡献率最高。因此,加强1000 m缓冲区尺度土地利用的管理和减少建设用地成片建设规划等对保护流域水质具有重要意义。     

CLUE-S模型在长白山自然保护区外围规划中的应用

受自然保护区旅游业快速发展影响,长白山自然保护区外围土地利用变化加剧。因此,对区域土地利用布局进行科学规划具有十分重要的意义。以长白山自然保护区外围30 km区域为研究对象,探讨了CLUE-S模型在小尺度土地利用规划中的应用。在分析研究区1991—2007年土地利用变化的驱动力基础上,根据区域规划预案,模拟2020土地利用布局。利用模拟结果划定空间管制区和乡镇布局,并与现有规划进行了对比。结果表明,基于CLUE-S模型的土地规划明显抑制了区域景观破碎化进程,减弱了人为活动对景观的影响,该方法可以为长白山区域土地利用规划提供有力的技术手段和科学支撑。     

流溪河流域景观空间特征与河流水质的关联分析

人类活动影响或改变流域景观空间结构,并有可能对河流水质产生不同程度的影响,以流溪河流域为研究区,分析流域景观空间格局特征与水质指数之间的相关关系。将流域划分为27个子流域,采集水样分析水质状况,所选用的水质指标有氨氮(NH3-N)、硝态氮-亚硝态氮(NO3-N+NO2-N)、总磷(TP)、化学需氧量(CODCr)。结果表明:1)该流域土地利用结构与水质具有显著相关性,其中居住用地对水质的影响作用最强,林地对河流水质具有净化功能,与水质指标之间的关系表现为负相关,园地与水质指标关系具有不确定性;2)流域景观特征从上游到下游之间表现为城市化增强的梯度,水质状况响应这个梯度变化表现为上游优于下游,人类活动及城市化发展引起的土地利用变化及土地管理方式对水质变化有显著影响;(3)景观破碎度与水质呈现显著正相关性,是影响水质的重要指标,景观聚集程度和斑块形状复杂程度与水质有负相关关系;子流域尺度和河岸带尺度景观空间特征对水质的影响差异不明显。     

Comprehensive evaluation of the ecohydrological response of watersheds under changing environments

Human activities and climate change pose a continuous threat to the ecological stability of natural rivers in many ways. Understanding and analyzing changes in flow regimes from a multidimensional perspective is essential for water resources management. In this research, a comprehensive evaluation framework was developed to quantitatively assess the hydrological condition of the basin in four aspects: river flow regime, ecological water demand, multiple time scales, and drivers. The health status of the Yuanjiang River was assessed using a combination of Indicators of Hydrologic Alteration (IHA) and eco-flow metrics, and differences in different drivers at different time scales were quantified based on the Choudhury-Yang equation and the ABCD model. The results show that after the abrupt change of the Yuanjiang River in 2004, the runoff decreased by up to 72.97 mm, three of the five groups of IHA reached moderate alteration or above, and its ecological flow was in a tight state for a long time. In addition, the reduction of runoff by precipitation and potential evapotranspiration is not negligible (contribution 40.56%, 6.91%), and the drastic changes in land use and the construction and operation of cascade reservoirs highlight the human impact (contribution 52.53%). Anthropogenic contributions to runoff changes deepen in the order of spring, summer, fall, and winter (6%, 51%, 83%, 95%), and on a monthly scale, human activities were the dominant factor in runoff variability in nine months (61–98%), with climatic factors driving runoff increases of 0.24–6.07 mm only in March, June, September, November, and December.