Investigating the uncertainty and transferability of parameters in SWAT model under climate change

ABSTRACT

There is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned     

Status of Macrobenthic Community and Its Relationships to Trace Metals and Natural Sediment Characteristics

Laizhou Bay, located in the northwest of Shandong Peninsula, has complex transitional environments between terrestrial and marine ecosystems. In the present study, a total of 122, 131, and 139 species were collected in spring, summer, and autumn 2011, respectively. Species constitutions of macrobenthos were grouped into four phyla, of which annelida were the most abundant phylum, the average biomass proportion of echinodermata was the lowest, and the proportion of important species for mollusca was the highest. The structure of the macrobenthic community showed significant differences between sites, and greater divergence was observed between the third site (S03) and other stations. The ABC plots showed that the biomass curve lay below the abundance curve, and the W‐statistic value was negative. The result of the BOPA index showed that two stations had moderate ecological status in spring and that there were two heavily polluted sites and one moderately polluted site in summer. The BIO‐ENV analyses indicated that the grain‐size fractions together with trace metals (Hg, Pb, Zn, Cu, and Cr) could be considered as the major environmental variables influencing the macrobenthic patterns. The results together demonstrated that the macrobenthic communities in Laizhou Bay were negatively affected, perhaps by the tremendous impact of heavy metals in the sediments.     

新疆库米什盆地硝酸盐类矿床成矿离子迁移规律及成矿模型

为了深入认识库米什盆地硝酸盐矿床成矿离子的空间分布特征、表层沉积物中硝酸盐含量较高的原因,以盆地硝酸盐矿床为研究对象,开展研究区内各类补给水样和沉积物样可溶性盐类物质化学组成的定量分析研究;结合野外地质踏勘工作,探讨研究区硝酸盐矿床成矿离子的迁移规律,初步建立盆地硝酸盐矿床沉积成矿作用模型.结果表明,K+、Na+、NO...     

Discovering Spatial Interaction Communities from Mobile Phone Data

In the age of Big Data, the widespread use of location‐awareness technologies has made it possible to collect spatio‐temporal interaction data for analyzing flow patterns in both physical space and cyberspace. This research attempts to explore and interpret patterns embedded in the network of phone‐call interaction and the network of phone‐users’ movements, by considering the geographical context of mobile phone cells. We adopt an agglomerative clustering algorithm based on a Newman‐Girvan modularity metric and propose an alternative modularity function incorporating a gravity model to discover the clustering structures of spatial‐interaction communities using a mobile phone dataset from one week in a city in China. The results verify the distance decay effect and spatial continuity that control the process of partitioning phone‐call interaction, which indicates that people tend to communicate within a spatial‐proximity community. Furthermore, we discover that a high correlation exists between phone‐users’ movements in physical space and phone‐call interaction in cyberspace. Our approach presents a combined qualitative‐quantitative framework to identify clusters and interaction patterns, and explains how geographical context influences communities of callers and receivers. The findings of this empirical study are valuable for urban structure studies as well as for the detection of communities in spatial networks.     

Negotiating on location, timing, duration, and participant in agent-mediated joint activity-travel scheduling

Agent-based simulation has become an important modeling approach in activity-travel analysis. Social activities account for a large amount of travel and have an important effect on activity-travel scheduling. Participants in joint activities usually have various options regarding location, participants, and timing and take different approaches to make their decisions. In this context, joint activity participation requires negotiation among agents involved, so that conflicts among the agents can be addressed. Existing mechanisms do not fully provide a solution when utility functions of agents are nonlinear and non-monotonic. Considering activity-travel scheduling in time and space as an application, we propose a novel negotiation approach, which takes into account these properties, such as continuous and discrete issues, and nonlinear and non-monotonic utility functions, by defining a concession strategy and a search mechanism. The results of experiments show that agents having these properties can negotiate efficiently. Furthermore, the negotiation procedure affects individuals’ choices of location, timing, duration, and participants.     

1980－2018年山西省太行山南麓暴雨时空变化特征

基于1980-2018年山西省太行山南麓晋城市5个站点的降水资料,利用小波分析和Mann-Kendall方法,研究了太行山南麓暴雨时空变化特征。结果表明:39年平均年暴雨日数有0.9个,年际变化幅度较小。暴雨量与暴雨日数的空间分布并不一致,1980、1981、1982、1995和1996年暴雨日数较多。分析50-59、60-69、70-79、80-89、90-99、100以上6个暴雨量区间空间分布发现,暴雨的空间分布在不同区间并没有明显的趋同性。年暴雨降水量有不同程度的增加趋势,晋城市下辖5站暴雨量趋势均存在突变,突变时间存在差异,暴雨量在19811983年和19921995年为两个峰值时段,之后有所缓和。39年暴雨时间序列的小波波谱显示,太行山南麓暴雨呈现0~3 a、3~7 a、8~24 a等3类周期准振荡变化规律,各波动周期稳定性和显著性不同。3~7 a出现5个多少准周期振荡,该周期表现较为显著,8~24 a出现2个准振荡周期,且这两个周期非常稳定,具有全域性的特征。晋城市3~7 a的暴雨振荡周期和8~24 a特大暴雨振荡周期与现实非常吻合。     

A multi-model study of atmosphere predictability in coupled ocean–atmosphere systems

Of great importance for guiding numerical weather and climate predictions, understanding predictability of the atmosphere in the ocean − atmosphere coupled system is the first and critical step to understand predictability of the Earth system. However, previous predictability studies based on prefect model assumption usually depend on a certain model. Here we apply the predictability study with the Nonlinear Local Lyapunov Exponent and Attractor Radius to the products of multiple re-analyses and forecast models in several operational centers to realize general predictability of the atmosphere in the Earth system. We first investigated the predictability characteristics of the atmosphere in NCEP, ECMWF and UKMO coupled systems and some of their uncoupled counterparts and other uncoupled systems. Although the ECMWF Integrated Forecast System shows higher skills in geopotential height over the tropics, there is no certain model providing the most precise forecast for all variables on all levels and the multi-model ensemble not always outperforms a single model. Improved low-frequency signals from the air − sea and stratosphere − troposphere interactions that extend predictability of the atmosphere in coupled system suggests the significance of air − sea coupling and stratosphere simulation in practical forecast development, although uncertainties exist in the model representation for physical processes in air − sea interactions and upper troposphere. These inspire further exploration on predictability of ocean and stratosphere as well as sea − ice and land processes to advance our understanding of interactions of Earth system components, thus enhancing weather − climate prediction skills.

     

ANALYSIS OF SETTLEMENT PATTERNS DURING NEOLITHIC AND BRONZE PERIOD AND ITS INFLUENCING FACTORS IN HUALONG COUNTY, QINGHAI PROVINCE,CHINA

依据青海省化隆县考古调查获得的新石器-青铜时代(5.3～2.6kaB.P.)的遗址位置和面积,尝试利用聚落等级和等级规模的方法分析该县新石器-青铜时代的聚落形态演变过程,并结合研究区周边地区的全新世气候记录和考古研究资料分析其可能的影响因素.结果显示:马家窑文化时期(5.4～4.0kaB.P.),化隆县出现具有一定人口规模和整合的聚落系统,可能与适宜气候背景下,农业快速发展导致的人口流动有关;齐家文化时期(4.2～3.8kaB.P.),化隆县人口规模未发生显著变化,没有出现聚落等级,聚落系统结构简单,各聚落之间为平等竞争关系,可能与区域聚落分布梅征改变有关;3.6～2.5kaB.P.,化隆县人口规模增加,三级等级聚落系统明显整合,可能是卡约文化的农业生产水平和生计方式适应气候变化的结果.因此,气候变化、生计模式和人口流动是化隆县新石器-青铜时代聚落形态演变和社会组织结构发展的主要原因.     

STONE KNIFE'S FUNCTION: SIMULATION EXPERIMENT VIA STARCH GRAIN ANALYSIS

淀粉粒分析在国内外环境考古学研究中得到了大量应用,但是目前国内还没有关于淀粉粒分析、石器功能与植物利用关系的现代过程研究.本研究针对石刀这一新石器时代重要的生产和生活工具开展现代过程的模拟实验,尝试利用淀粉粒分析方法验证石刀功能及其加工的植物类型.我们利用打制的简易石片模拟石刀,对未成熟和成熟的小麦(Triticum aestivum L.)进行了共两次割穗操作,提取并观察石片割穗后不同部位表面残留物中的淀粉粒形态及其组合.实验结果表明,石片表面残留物中的淀粉粒主要来源于小麦秸秆;小麦秸秆淀粉粒的A型和B型淀粉粒(未成熟和成熟小麦秸秆淀粉粒——A+B型淀粉粒,含量分别为90.91％和92.59％)分别与其成熟籽粒的A型和B型淀粉粒形态、大小相似,具备形态鉴定的特征;小麦秸秆中还发现了独特的多面体型淀粉粒(未成熟和成熟小麦秸秆多面体型淀粉粒含量分别为9.09％和7.41％),这是小麦种子中缺少的类型.根据本次现代实验模拟的结果,考古遗址出土石刀上提取到的淀粉粒很可能来自于植物收割(或切削)过程的残留物,结合淀粉粒分析、石刀形制和出土状况进行分析,可以获取出土石刀功能与古人类植物利用的信息.