Actual Variance Research Articles

Research on Cost Control of Railway Engineering Based on Grounded Theory

An analysis of cost management within railway construction projects has been conducted using the Analytic Hierarchy Process (AHP) and a regression analysis to evaluate and rank key financial and operational factors affecting project costs. This research assesses the impact of various metrics, such as Safety Inspections, Emergency Preparedness, and Equipment Maintenance, along with financial indicators such as Actual Cost and Variance, on cost control strategies by building a hierarchical model and implementing AHP. The results indicate a clear preference for Financial Metrics, with a priority vector of 0.667, over Operational Metrics, which have a priority vector of 0.334. Among the Financial Metrics, Actual Cost, with a priority vector of 0.565, is identified as the most influential, underscoring the importance of direct cost management. Among the Operational Metrics, Emergency Preparedness is the most important, with a priority vector of 0.540, emphasizing the importance of effective risk management. A regression analysis confirms these priorities, with significant correlations presented between these metrics and variances in costs. According to this study, changes in Emergency Preparedness and Equipment Maintenance can predict cost fluctuations, aligning with the findings of the AHP study. The AHP evaluations are demonstrated to be reliable, with consistency ratios significantly below the 0.1 benchmark (0.043 for Financial Metrics and 0.008 for Operational Metrics), indicating a high degree of consistency in judgment. The statistical validation enhances the framework’s effectiveness in steering strategic decisions regarding cost management. This paper discusses the implications of these results to reduce financial risks and improve project outcomes.

Financial Reporting, Tracking, and Analysis Practices Effect on Financial Performance of Commercial State Corporations in Kenya

In Kenya, legislative acts by parliament establish state corporations to promote social and economic progress. The state corporations advisory committee has identified eight distinct categories of these entities, which include financial, commercial, industrial, regulatory, public universities, training and research, service, regional development authorities, as well as tertiary education corporations. Out of the 33 state corporations in commercial and manufacturing category, 18 fall under manufacturing while 15 are commercial-oriented and therefore by their operational nature expected to make profits or operating surplus. The study focused on the fifteen (15) profit-making state corporations. Most commercial state corporations are in a state of perennial loss-making. Their financial performance trend between 2016-2020, shows that out of the 15 corporations in the commercial sector, only four (26.67%) are sustainable from their operations. This leaves over 73.33% of them struggling to survive and have to depend on government funding to address their liquidity challenges. This study sought to assess the impact of financial reporting and analysis on the financial performance of commercial state corporations in Kenya. The study assumed a descriptive study design. The study used a census procedure since all fifteen State Corporations under the commercial category were studied. Data was analysed using descriptive and inferential statistics. The inferential statistics results indicate that financial reporting and analysis have a positive and statistically significant effect on financial performance of commercial SOEs. The study found that improved financial performance was observed upon conducting periodical operational budget estimations, capital project estimations, periodical cash flow projections, and comparison of actual costs and budget variance analysis. The management and finance department to ensure that financial reporting processes are strengthened to enhance accuracy, openness, and compliance with governing requirements.

Robust sequential fusion Kalman estimators with asymptotic equivalence and stability for networked uncertain sensor systems

For networked uncertain sensor systems (NUSSs) with an improved unified sensor model with “hard” and “soft” sensors including five uncertainties plus two-step random measurement delays and colored measurement noises, applying the block matrix inversion formula, a new sequential inverse covariance fusion (SICF) approach is presented. It can sequentially compute the global inverse covariance according to the time order of the received data, but need not wait until all data are received. The corresponding minimax robust time-varying and steady-state sequential fusion (SF) Kalman estimators (predictor, filter, and smoother) are presented in the sense that their actual error variances are guaranteed to have the corresponding minimal upper bounds for all admissible uncertainties. They have lower computation complexities and higher accuracies equivalent to ones of the robust optimal batch-fusion (BF) Kalman estimators, and are suitable for real-time applications. Their asymptotic equivalence, absolute asymptotic stability, and accuracy relations are proved. Their strict complexity analysis is given. They constitute a novel universal robust SF estimation, convergence and stability theory for NUSSs. One simulation example applied to the uncertain ARMA signal processing verifies the effectiveness of the proposed approach and theory.

A 219‐year reconstruction of April–June mean minimum temperature from the tree‐ring earlywood density on the Changbai Mountains, China

AbstractUsing mean earlywood density data from Pinus koraiensis cores, we reconstructed the April–June mean minimum temperature from 1797 to 2015 for the Changbai Mountains. The reconstruction explained 52.6% of the actual mean minimum temperature variance during 1901–2015. After smoothing with an 11‐year moving average, we identified three major cold periods (1797–1875, 1881–1899, and 1903–1946) and three major warm periods (1876–1880, 1900–1902, and 1947–2015) in the reconstructed series. Spatial correlation showed that the reconstruction contained climatic signals for a large area including most of northeast China, especially the Bohai Rim region and the eastern side of the Mongolian Plateau. A comparison between the newly reconstructed temperature series for the surrounding areas reveals similar variations, particularly in the warming trend during the second half of the 20th century. The driving factors of the mean minimum temperature were influenced mainly by the interaction of solar activity and large‐scale atmospheric‐oceanic variability. The reconstructed series provides a basis for understanding past climate change in the Changbai Mountains and for predicting future climate change trends in Northeast China.

Distributed fusion robust filter for multisensor networked singular control system with uncertain variances and missing measurement

AbstractA distributed fusion time‐varying robust filtering algorithm for multisensor networked singular control system is studied in this paper, mainly aiming at the system with missing measurement and uncertain variances in practical application. First, the singular value decomposition (SVD) method and de‐randomization method are used to transform the singular control system into a standard system only with uncertain variances. Based on the new standard system, a minimax robust local Kalman filter is proposed by using the minimax robust estimation principle, which ensures that the actual filtering error variance has the corresponding minimum upper bound for all allowable uncertainties. Further, the robust local and distributed fusion filters for original singular control systems are proposed, and the actual and conservative filtering error variances are obtained. Their robustness is proved by Lyapunov equation method and nonnegative definite matrix decomposition method. A simulation example of two‐loop system verifies the effectiveness of the proposed results.

Robust weighted fusion Kalman estimators for systems with uncertain noise variances, multiplicative noises, missing measurements, packets dropouts and two‐step random measurement delays

AbstractFor multisensor networked systems with uncertain noise variances, multiplicative noises and multiple networked‐induced uncertainties including missing measurements, packets dropouts and two‐step random measurement delays, the robust weighted fusion estimation problem is addressed in this article. More precisely, the system noise variances are assumed to be uncertain but bounded, the other four uncertainties are compensated into fictitious white noise by the proposed model transformation method, which includes the augmented method and extended fictitious noise technique. Then local multi‐model system is obtained, for which robust local Kalman estimator is obtained based on the minimax robust estimation principle and unified estimation method. Based on this, the six robust weighted fusion time‐varying Kalman estimators are presented in a unified form, which include robust weighted fusers weighted by matrices, diagonal, scalars, and a robust covariance intersection (CI) fuser and two fast CI (FCI) fusers. The robustness proving method, including the extended Lyapunov equation approach with two kinds of generalized Lyapunov equations, non‐negative matrix factorization and elementary transformation of matrix, is presented to prove that the actual estimation error variances are guaranteed to have minimal upper bounds for all admissible uncertainties. The accuracy relations are proved. Further, the robust local and fused steady‐state Kalman estimators are presented. Finally, a simulation example applied to Internet‐based three tank water system is given to demonstrate effectiveness of the proposed results.

Recurring Errors in Studies of Gender Differences in Variability

The past quarter century has seen a resurgence of research on the controversial topic of gender differences in variability, in part because of its potential implications for the issue of under- and over-representation of various subpopulations of our society, with respect to different traits. Unfortunately, several basic statistical, inferential, and logical errors are being propagated in studies on this highly publicized topic. These errors include conflicting interpretations of the numerical significance of actual variance ratio values; a mistaken claim about variance ratios in mixtures of distributions; incorrect inferences from variance ratio values regarding the relative roles of sociocultural and biological factors; and faulty experimental designs. Most importantly, without knowledge of the underlying distributions, the standard variance ratio test statistic is shown to have no implications for tail ratios. The main aim of this note is to correct the scientific record and to illuminate several of these key errors in order to reduce their further propagation. For concreteness, the arguments will focus on one highly influential paper.

Enhanced Variability and Declining Trend of Soil Moisture Since the 1880s on the Southeastern Tibetan Plateau

AbstractHistorical soil moisture (SM) variations, trends, and their driving factors remain scarce for the area of Tibetan Plateau (TP), which hinders putting a sensible assessment of the current and future ecological drought risk into perspective. Here, we report the first three century‐long regional summer (July–August) SM reconstruction for the southeastern TP during 1691–2007 CE using a paleoclimate proxy, that is, tree‐ring δ18O. The SM reconstruction, which explained 60.9% of the actual variance, revealed that an abrupt wet‐to‐dry change occurred in 1884. After 1884, SM exhibited a decreasing trend and enhanced variability, and dry summers occurred more frequently. In particular, the variability in SM reached an unprecedented level after the 1950s relative to that during the past three centuries. A structural equation model and running correlation analysis revealed that SM variation was mainly controlled by precipitation rather than temperature. This indicates that the anthropogenic‐related weakening of the Indian summer monsoon played a more dominant role in SM changes after 1884 than the increase in temperature. If the SM variability is to be further increased in the future, it may undermine ecosystem stability and forest health. The results of this study are significant for predicting ecological drought in ecologically vulnerable regions such as the High Asia.

Streamflow reconstruction in the Kafirnigan River, Tajikistan since 1568 CE reveals a linkage between southern Central Asian hydrological variation and ENSO

AbstractLong‐term hydroclimate change can provide reliable reference for water resources management in Central Asia. However, only a few palaeohydrological records exist in Tajikistan. To obtain a long‐term perspective on hydrological changes in Tajikistan, we developed, for the first time, a streamflow reconstruction from September of the previous year to June of the current one in the Kafirnigan River basin, based on Juniperus semiglobosa tree‐ring width indices from the Iskanderkul area in northern Tajikistan. The streamflow reconstruction explains 40% of the actual streamflow variance during the period 1939–1993. Spatial correlation analyses with gridded precipitation data indicate that our streamflow reconstruction contains a strong regional hydroclimatic signal for southern Central Asia. The high and low intervals of our streamflow reconstruction are closely related to the interdecadal variations of El Niño‐Southern Oscillation (ENSO). Our reconstructed streamflow is significantly correlated with sea surface temperatures in the eastern equatorial Pacific Ocean and northern Indian Ocean, indicate the existence of remarkable 11‐, 5.6–5.7‐, 4.3‐, 2.6‐, 2.3‐ and 2.0‐year cycles, and suggest a relationship between southern Central Asian streamflow variations and ENSO activity.

Fast and accurate joint inference of coancestry parameters for populations and/or individuals.

We introduce a fast, new algorithm for inferring from allele count data the FST parameters describing genetic distances among a set of populations and/or unrelated diploid individuals, and a tree with branch lengths corresponding to FST values. The tree can reflect historical processes of splitting and divergence, but seeks to represent the actual genetic variance as accurately as possible with a tree structure. We generalise two major approaches to defining FST, via correlations and mismatch probabilities of sampled allele pairs, which measure shared and non-shared components of genetic variance. A diploid individual can be treated as a population of two gametes, which allows inference of coancestry coefficients for individuals as well as for populations, or a combination of the two. A simulation study illustrates that our fast method-of-moments estimation of FST values, simultaneously for multiple populations/individuals, gains statistical efficiency over pairwise approaches when the population structure is close to tree-like. We apply our approach to genome-wide genotypes from the 26 worldwide human populations of the 1000 Genomes Project. We first analyse at the population level, then a subset of individuals and in a final analysis we pool individuals from the more homogeneous populations. This flexible analysis approach gives advantages over traditional approaches to population structure/coancestry, including visual and quantitative assessments of long-standing questions about the relative magnitudes of within- and between-population genetic differences.

Inter-annual and intra-annual tree-ring oxygen isotope signals in response to monsoon rainfall in northwestern Thailand

We present a new teak ( Tectona grandis L.f.) tree-ring stable oxygen isotope (δ18OTR) chronology from Mae Tuen (MT) site, Tak province, northwestern Thailand at inter-annual (167-year, A.D.1850–2016) and intra-annual (A.D.2006–2016) timescales. The inter-annual δ18OTR chronology showed a significant negative correlation ( r = −0.678, p < 0.01) with the May–October amount of regional rainfall obtained from CRU TS4.03. We established a linear regression model that explained 46.0% of the actual rainfall variance and reconstructed monsoon season rainfall back to A.D.1850. The seasonal variations in moisture conditions were reflected in inter-annual δ18OTR variability. The rainfall amount and δ18O in precipitation (δ18Op) mainly controlled intra-annual variations in teak δ18OTR. These results show that the variation in Thai teak δ18OTR is dominated by rainfall, highlighting the strength of δ18OTR as a monsoon rainfall proxy.

Robust integrated sequential covariance intersection fusion Kalman filters and their convergence and stability for networked sensor systems with five uncertainties

AbstractFor networked sensor systems (NSSs) with hard and soft sensors including five uncertainties, two universal approaches of solving the robust fusion estimation problems are presented. It includes an integrated sequential covariance intersection (SCI) fusion minimax robust Kalman filtering approach with cross‐covariance information and a generalized Lyapunov equation approach with four pairs of Lyapunov equations. Applying them, the robust local and SCI fused time‐varying and steady‐state Kalman filters are presented in the sense that their actual estimation error variances are guaranteed to have the corresponding minimal upper bounds. The equivalent batch SCI fusers are also presented. Their robustness and accuracy relations are proved, and the sensitivity of the SCI fuser with respect to the fused orders of sensors is analyzed. Applying the dynamic error system analysis method and the dynamic variance error system analysis method, a new convergence and absolute asymptotic stability theory of robust fusion Kalman filtering is presented. The classical Kalman filtering convergence and stability theory is developed. Compared with the original covariance intersection fuser, they significantly reduced the computational complexity and burden. Compared with the optimal and conservative SCI fusers, they significantly improved the robust accuracies. They are suitable to deal with asynchronous or random delayed data and are suitable for real‐time applications. A simulation applied to the two‐mass spring damper mechanical system shows their effectiveness.

Locally weighted total least-squares variance component estimation for modeling urban air pollution.

Land use regression (LUR) models are one of the standard methods for estimating air pollution concentration in urban areas. These models are usually low accurate due to inappropriate stochastic models (weight matrix). Furthermore, the measurement or modeling of dependent and independent variables used in LUR models is affected by various errors, which indicates the need to use an efficient stochastic and functional model to achieve the best estimation. This study proposes a locally weighted total least-squares variance component estimation (LW-TLS-VCE) for modeling urban air pollution. In the proposed method, in the first step, a locally weighted total least-squares (LW-TLS) regression is developed to simultaneously considers the non-stationary effects and errors of dependent and independent variables. In the second step, the variance components of the stochastic model are estimated to achieve the best linear unbiased estimation of unknowns. The efficiency of the proposed method is evaluated by modeling PM2.5 concentrations via meteorological, land use, and traffic variables in Isfahan, Iran. The benefits provided by the proposed method, including considering non-stationary effects and random errors of all variables, besides estimating the actual variance of observations, are evaluated by comparing four consecutive methods. The obtained results demonstrate that using a suitable stochastic and functional model will significantly increase the proposed method's efficiency in PM2.5 modeling.

Sequential Covariance Intersection Fusion Robust Time-Varying Kalman Filters with Uncertainties of Noise Variances for Advanced Manufacturing.

This paper addresses the robust Kalman filtering problem for multisensor time-varying systems with uncertainties of noise variances. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, the robust local time-varying Kalman filters are presented. Further, the batch covariance intersection (BCI) fusion and a fast sequential covariance intersection (SCI) fusion robust time-varying Kalman filters are presented. They have the robustness that the actual filtering error variances or their traces are guaranteed to have a minimal upper bound for all admissible uncertainties of noise variances. Their robustness is proved based on the proposed Lyapunov equations approach. The concepts of the robust and actual accuracies are presented, and the robust accuracy relations are proved. It is also proved that the robust accuracies of the BCI and SCI fusers are higher than that of each local Kalman filter, the robust accuracy of the BCI fuser is higher than that of the SCI fuser, and the actual accuracies of each robust Kalman filter are higher than its robust accuracy for all admissible uncertainties of noise variances. The corresponding steady-state robust local and fused Kalman filters are also presented for multisensor time-invariant systems, and the convergence in a realization between the local and fused time-varying and steady-state Kalman filters is proved by the dynamic error system analysis (DESA) method and dynamic variance error system analysis (DVESA) method. A simulation example is given to verify the robustness and the correctness of the robust accuracy relations.

Increased extreme drought events in south–central China since the last century：Evidence from oxygen isotope signatures preserved in tree ring cellulose

Tree-ring cellulose oxygen isotope ratios (δ18O) is a well-established proxy for hydroclimatic conditions in monsoon Asia. We reconstructed June–October relative humidity (RHJ–O) variations from 1808 to 2017, based on tree-ring cellulose δ18O data, which explain 46.2% of the actual RH variance in the Nanyue region, south–central China. Extreme wet events occurred frequently prior to the 1900s, but there have been more extreme dry events since the 1900s, apart from the late 1930s and early 1950s. Periodicity analysis revealed that the reconstructed RHJ–O records show obvious 15–30 years cycles from the 1830–1970s. The multi-decadal signals may reflect the effect of the Pacific Decadal Oscillation (PDO) on hydroclimate. In the positive PDO phase, there is drying in south–central China, which is related to a weaker East Asian summer monsoon (EASM) via the Pacific–Japan teleconnection. The decadal signal has weakened since the 1970s. In addition, the reconstructed RHJ–O record shows strong interannual variations, which may be related to the Central Pacific El Niño–Southern Oscillation (CP ENSO). During extreme CP El Niño events, there is a weaker EASM due to the Pacific–Japan teleconnection, and the study site experienced drought. Our reconstructed moisture record is characterized by a decreasing influence from the PDO and increasing influence from the CP ENSO in recent decades. Moreover, the frequency of CP ENSO events is projected to increase under anthropogenic warming. Consequently, more extreme droughts which are related to CP ENSO events may increase in the south–central China in near future.

Is tree ring chronology of blue pine (Pinus wallichiana A. B. Jackson) prospective for summer drought reconstruction in the Western Himalaya?

• Tree ring chronology of blue pine is potential for long term SPEI (drought index) reconstruction. • Provides a reliable drought records (322-year’s) during monsoon season of the western Himalaya. • The spectral peaks (2–4 years) indicate drought fluctuations are linked mostly to ENSO events. • The reconstructed monsoon SPEI showed notable drying towards 1990 to 2017AD. A long record of drought beyond observable data is scarce in the Himalayan region, making it difficult to understand the region's long-term variability. Here we reconstructed the Standardized Precipitation Evapotranspiration Index (SPEI) a drought index using the tree-ring chronology of blue pine ( Pinus wallichiana ), to retrieve the past drought variations. The chronology is prepared from tree ring width series of well replicated samples of blue pine covering time span of 1660–2017 CE, from Darma Valley, Indian Western Himalaya. We observed that the combined expression of precipitation and temperature, conveyed as SPEI, is more effective in limiting tree growth during the monsoon season than either precipitation or temperature alone. The SPEI of June-September (monsoon season) exhibited a significant strong positive correlation (r = + 0.69, p < 0.001) with the tree ring chronology. Based on this relationship, we reconstructed monsoon SPEI covering 1696–2017 CE. The variance explained for the calibration period 47% of the actual SPEI variance of 1903–2017 CE. The extended SPEI time series indicates several high and low intensity droughts, which are consistent with the historical drought records of the Himalayan region. Furthermore, analyses of the spatial correlations reveal that the variation in the reconstructed monsoon SPEI is strongly associated with the regional summer drought variability in the Himalayan region. We recorded a strong teleconnection of SPEI data and sea surface temperature changes in the Indian and Pacific Oceans, indicating that Indian summer monsoon variability is prevalent for this region's summer monsoon SPEI. Furthermore, in the spectral analysis peaks between 2.0 and 4.0 years indicates that the summer drought fluctuation is linked to El Niño-Southern Oscillation (ENSO).

Timely completion of spinal fusion: A multidisciplinary quality improvement initiative to improve operating room efficiency.

Failure to complete surgery within the scheduled timeframe impairs operating room efficiency leading to patient dissatisfaction and unplanned labor costs. We sought to improve timely completion (within 30 min of scheduled time) of first-case spine fusion surgery (for idiopathic scoliosis) from a baseline of 25%-80% over 12 months. We also targeted timely completion of perioperative stages within predetermined target completion times. The project was conducted in three overlapping phases over 16 months. A simplified process map outlining five sequential perioperative stages, preintervention baselines (N=24) and time targets were defined. A multidisciplinary team conducted a series of tests of change addressing the aims. The key drivers included effective scheduling, team communications, family engagement, data collection veracity, standardized pathways, and situational awareness. Data collected by an independent data collector and from electronic medical records were analyzed using control charts and statistical process control methods. Post-intervention, timely case completion increased from 25% to 68% (N=49) (95% CI 15.1-62.7), (p=0.003) and was sustained (N=14). Implementation of prediction model for case-scheduling decreased difference between scheduled and actual case end-time (33 vs. 53 min [baseline]) and variance [lower/upper control limits ([-26, 51] vs. [-109, 216]min [baseline]). Average start time delay decreased from 6 to 2min and on-time surgical starts improved from 50% to 70% (95% CI 3.2-41.6%). Timely completion increased for anesthesia induction (60% to 85%), surgical procedure (26% to 48%) and emergence from anesthesia (44% to 80%) but not for intraoperative patient preparation (30% to 25%) perioperative stages. Families reported satisfaction with preoperative processes (N=14), and no untoward intraoperative safety events occurred. Application of QI methodology reduced time variation of several tasks and improved timely completion of spine surgery. Beyond the study period, sustained team behavior, adaptive changes, and vigilant monitoring are imperative for continued success.

Robust fusion filter for multisensor descriptor system with uncertain‐variance noises and packet dropout

AbstractFor the multisensor linear stochastic descriptor system with uncertain‐variance noises and packet dropout, the standard state space model of the new reduced‐order augmented state is obtained based on the singular value decomposition (SVD) approach and augmented state approach. By applying the min‐max robust estimation principle and Kalman filtering theory, the local robust time‐varying Kalman filters of the reduced‐order augmented state and fictitious process noise are proposed. Then, the local robust time‐varying filters of the original descriptor system are presented according to the relation of the reduced‐order augmented state and the original state. And the distributed and covariance intersection (CI) fusion robust time‐varying filters are presented, and the actual and conservative filtering error variances are obtained. Further, the robustness of the local and fused robust filters are proved by applying Lyapunov equation approach, and the accuracy relation between them is analyzed. A simulation example applied to a circuit system shows its effectiveness and applicability.

Template switching and duplications in SARS-CoV-2 genomes give rise to insertion variants that merit monitoring

The appearance of multiple new SARS-CoV-2 variants during the COVID-19 pandemic is a matter of grave concern. Some of these variants, such as B.1.617.2, B.1.1.7, and B.1.351, manifest higher infectivity and virulence than the earlier SARS-CoV-2 variants, with potential dramatic effects on the course of the pandemic. So far, analysis of new SARS-CoV-2 variants focused primarily on nucleotide substitutions and short deletions that are readily identifiable by comparison to consensus genome sequences. In contrast, insertions have largely escaped the attention of researchers although the furin site insert in the Spike (S) protein is thought to be a determinant of SARS-CoV-2 virulence. Here, we identify 346 unique inserts of different lengths in SARS-CoV-2 genomes and present evidence that these inserts reflect actual virus variance rather than sequencing artifacts. Two principal mechanisms appear to account for the inserts in the SARS-CoV-2 genomes, polymerase slippage and template switch that might be associated with the synthesis of subgenomic RNAs. At least three inserts in the N-terminal domain of the S protein are predicted to lead to escape from neutralizing antibodies, whereas other inserts might result in escape from T-cell immunity. Thus, inserts in the S protein can affect its antigenic properties and merit monitoring.

Runoff reconstruction for the Bailong River from tree rings back to AD 1601, reveals changing hydrological signals of China north–south transition zone

AbstractWe present a runoff reconstruction for the Bailong River based on the composite chronology developed from four sampling sites of Pinus tabulaeformis in the China north–south transition zone. The runoff reconstruction, spanning 1601–2013 CE, was developed by calibrating tree‐ring data with the instrumental runoff record. Runoff reconstruction accounted for 44.3% of the actual runoff variance during the common period 1958–2010 and provided a long‐term perspective on hydrological change in the China north–south transition zone. In the past 413 years, high‐ and low‐runoff years accounted for 15.50% and 15.98%, respectively. Of all the 17 extreme hydrological events, 14 of them are extremely high‐flow years, and 17th century was the wettest period during the past 413 years. The preliminary analysis results show that there is a relationship between our runoff reconstruction and the Atlantic multidecadal oscillation at multidecadal scale. Since the 1990s, runoff in the China north–south transition zone has also seen a significant decrease as a result of dry trends of the source region.