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Based on daily temperature observation dataset with high quality and spatial resolution, this paper revealed the dominant invading paths of the extreme cold surges (ECSs) within China by using the fifth percentile of temperature drops instead of the traditional unified threshold in the operation. The maximal probabilities of the ECSs from the upstream regions to the down‐stream regions along the invading paths are also provided. Results indicate the distribution of the fifth percentile is quite different in various regions, with the highest value centers of more than 8°C in northern China, and a secondary center of 6–7°C in southern China. While in the areas between the Yellow River basin and the Yangtze River basin, the two longest rivers in China, the values are below 5°C. This result explains the unreasonable frequency gap between the two rivers in previous unified threshold. Based on the distribution, the whole country is roughly divided into 18 regions at an approximate box of 5°N × 10°E to acquire clear and objective invading paths by the lead–lag correlation analysis and an objective identification of the paths. Results show the ECS invading path in northern China has a dominant west or northwest track. But in southern China, the invading paths are more complex, generally from north to south. In China, about 30–40% ECS cases in the upstream regions can lead to the ECSs in the down‐stream regions along the dominant paths. By the identification and the lead–lag correlation, northwestern China could be regarded as the source of ECSs invading other regions. [ABSTRACT FROM AUTHOR]

This study investigates shared benefits through the cooperation between North Korea and China over transboundary water management in the Yalu River Basin. Primary attention has been placed on joint hydropower development since the 1950s, which has brought in developmental benefits for North Korea and security benefits for China. Data on the study have been collected from relevant papers, government publications, and media reports of China and South Korea. The information on North Korea, particularly about hydropower dams, is only accessible through secondary sources collected from South Korean government thinktanks due to the lack of publicly available data. The case study method is deployed for exploring specific issues and context and addressing problems. The significance of the study lies in the fact that this study is one of the first studies to examine transboundary river cooperation for development and security benefits between the countries. An array of bilateral agreements over the river basin has culminated in co‐building and jointly operating the four dams along the river. The construction of two additional dams, which is nearing completion, symbolizes shared benefits for both countries, hydroelectricity for North Korea, and regional security for China. Research Impact Statement: The study provides an in‐depth and unique analysis of joint hydropower development between North Korea and China in the Yalu River Basin. [ABSTRACT FROM AUTHOR]

Acquiring freshwater resources is a necessary component of sustainable human settlement subject to increasing pressure from population and climate changes. This sometimes scarce resource primarily comes from rivers, and international river basins ( IRBs), where watersheds and watercourses cross political boundaries, are often spaces of great political tension and conflict worldwide. Such conflict potential has garnered interest from a wide range of research communities, and each emphasises public access to hydrologic data as integral to successful international management of IRBs. However; these hydrologic data, especially measurements of river flow rate, are often closely guarded state secrets. Satellites have been cited as a key technology set to challenge this data monopoly that have yet been unable to calculate river flow rate without some form of guarded ancillary data. Now, at-many-stations hydraulic geometry ( AMHG) offers a means of circumventing data limitations without any a priori information, and the forthcoming NASA/ CNES Surface Water and Ocean Topography ( SWOT) satellite also promises to estimate flow rates solely from its novel measurements following launch. In this paper, we explore how these newly available estimates of river flow rate could reconfigure water-management and interstate relations in IRBs, and demonstrate AMHG, for two cases: the Ganges- Brahmaputra and Mekong. For these basins we find that satellite flow rate retrievals will likely reinforce and favour state-level negotiations of water resource governance. Also, satellite flow retrievals can have the direct, concrete effect of improving hydrologic understanding of the upstream Ganges- Brahmaputra, a sorely needed advance that will positively benefit millions of Bangladeshis and affect state-level interactions between India, China, and Bangladesh. Finally, we avoid offering prescriptive water management solutions for each case, as local stakeholders will ultimately determine if and how such satellite retrievals will be used. [ABSTRACT FROM AUTHOR]

The spatial variability of the soil C:N ratio (C:N) influences C and N leaching and basic fertility in the field. This paper aims to identify the spatial heterogeneity of C:N in a Mollisol watershed of Northeast China and determine the main mechanisms that drive these differences. A random sampling method was used, with both geostatistical and traditional analysis being used to describe the spatial distribution of the C:N at various depths. C:N was also compared between slope position, previous vegetation and tillage methods in the watershed. The horizontal distribution of the C:N was mainly influenced by structural factors (88·4-99·9%) and often gradually deceased along the hydrographic flow direction, becoming lowest at the watershed outlet. The C:N increased as soil depth increased at all slope positions, and was higher on the back slope than on summit slope, followed by bottom slope in all soil depths. C:N was negatively (significant at p < 0·01) correlated to TN, and positively (significant at p < 0·05) correlated to elevation at all soil depths. Compared to the reforested area, C:N was typically greater in the agricultural area in the 20-60 cm depth. The planting of soybean ( Glycine max L) can significantly increase the C:N at the 40-50 cm depth. C:N was higher in cross-slope tillage than in down-slope tillage, especially at soil depths of 40-50 cm. Generally, topographical factors, land use, crop planting and tillage methods can effectively influence the spatial heterogeneity of C:N in this watershed. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The assessment of flood risk is now widely recognised to need research and data on both the probability and the consequences of flooding; the research reported here concentrates on the latter data input. Building on the UK Foresight Future Flooding project, this paper describes the development of future scenarios through which to assess possible future flood risk in the Taihu Basin area of China. In addition, we describe the flood damage assessment model that was developed there to build on these scenarios so as to calculate anticipated risk. Acknowledged methodological limitations remain, but some important developments have resulted. First, the pre-existing flood loss data that were available from Shanghai meant that this aspect of the risk model's input was more regionally appropriate than would otherwise have been the case. Second, the damage assessment has been related both to constructed scenarios and to an agreed National Plan, so that the two can be compared. Third, the scenario construction was linked in Taihu to the statistical base contained in the 2006 Yearbook and the Fifth National Socio-economic Survey data, giving a sounder 'base case' of current flood vulnerability than used in the UK Foresight Future Flooding project. Finally, much more attention was given here to agricultural production and flood risk, given the importance of agriculture in the Chinese economy and its focus on food production for a growing population. [ABSTRACT FROM AUTHOR]

Planning for the long-term management of flooding should be underpinned by credible evidence of current and future flood risk. Simulation of flood extents and depths is a key component of the evidence base of flood risk analysis, but flood modelling can be a time-consuming activity. For scenario analysis studies, such as that undertaken on the Taihu Basin in China, the potentially extensive computational and staff time demands of standard flood modelling are compounded by the need for simulations of multiple futures over large areas. In this paper, we describe how a credible flood simulation method was selected and implemented for the Taihu Basin within the challenging data, resource and programme constraints. The lessons learned from the study are described and generalised to help inform modelling components of other studies, particularly broad scale analysis for flood risk management planning. [ABSTRACT FROM AUTHOR]

The relationship between forests and streamflows has long been an important research interest in China. The purpose of this paper is to summarize progress and lessons learned from the forest-streamflow studies over the past four decades in China. To better measure the research gaps between China and other parts of the world, a brief global review on the findings from paired watershed studies over the past 100 years was also provided. In China, forest management shifted in the later 1990s from timber harvesting to forest restoration. Forest-streamflow research was accordingly changed from assessing harvesting impacts to evaluating both harvesting and forestation effects. Over the past four decades, Chinese forest hydrology research has grown substantially. Significant progress has been made on measuring individual processes, but little solid, long-term data were available to assess the relationship between forest changes and streamflows because of an absence of standard paired watersheds. In addition, misuse of statistical analyses was often found in the literature. A unique opportunity exists in China to study the forestation effects on streamflow as several large-scale forestation programs are being implemented. Such an opportunity should include a robust paired watershed design under an integrated watershed ecosystem framework to avoid repeating the lessons already learned. Recommendations on future forest-streamflow research directions in China are provided. [ABSTRACT FROM AUTHOR]

This study presents an analysis of the changes in extreme temperatures over major river basins in China under different shared socioeconomic pathway (SSP) scenarios based on a set of dynamical downscaling over CORDEX East Asia, performed with the regional climate model RegCM4 at a resolution of 25 km, driven by the global climate model FGOALS‐g3. The results indicated that the dynamical downscaling tended to reduce the warm (cold) biases of the present‐day daily maximum (TXx) and minimum temperatures (TNn) simulated by FGOALS‐g3. Under the SSP scenarios, substantial increases in TXx and TNn and the number of warm days and warm nights throughout China were projected by both models. The average increase in TXx in most of the river basins ranged from 1 to 2°C under the SSP1‐2.6 scenario, from 2 to 3°C under the SSP2‐4.5 scenario, and from 3 to 5°C under the SSP5‐8.5 scenario. Reductions in the number of cold days and cold nights were projected across China, but these reductions were smaller than the increases in the number of warm days and warm nights. The interregional variability in the increases in TXx and TNn was more pronounced in the SSP5‐8.5 scenario and the RegCM4 model than in the other SSP scenarios and the FGOALS‐g3 model, respectively. Larger percentages of the land area and population of China would be affected by greater increases in extreme high temperatures and TNn. Under the SSP2‐4.5 (SSP1‐2.6) scenario, 20–65% (50–95%) of the impacts of extreme temperatures under the SSP5‐8.5 scenario could be avoided across most regions in China. The avoided impacts of warm days and warm nights were greater than those of the other extreme temperature indices. More of the impacts of extreme temperatures could be avoided in the Huai River basin, Yellow River basin, Hai River basin, and Northwest Interior River basin than in the other river basins in China. [ABSTRACT FROM AUTHOR]

Scholars and policymakers debate whether centralized environmental governance improves protection. In China, in response to its environmental crisis, the government designed a centralized payment for ecosystems services (PES) policy to alter the costs and benefits for local stakeholders to protect the environment. This study analyses the impact of the 2014 centralization of environmental governance, focusing on the oldest eco‐compensation for watershed services (EWS) model in Zhejiang province. We find that the centralization of EWS led to increased ecosystem protection due to administrative and fiscal incentives; however, the policy faces challenges such as over‐centralization of EWS program development, transboundary negotiation processes, and inadequate monitoring systems that ultimately hinder effective implementation and future innovation. Based on our analysis, we recommend developing a hybrid model with enhanced monitoring by citizens and increasing local autonomy to tailor eco‐system payment programs to local needs. These reforms would improve the design of PES to achieve its promise to incentivize environmental protection. [ABSTRACT FROM AUTHOR]

A comprehensive and reliable assessment of the water resources in China's transboundary river basins is vital for water resources management and peaceful development. In this study, we built machine learning (random forest, gradient boosting, and stacking) and traditional linear models to identify the relation between the runoff coefficient and its influencing factors, including topography, climate, land cover, and soil. The cross‐validation results show that the machine learning models greatly outperform the traditional linear model in predicting runoff coefficient. High‐resolution (0.1°) runoff coefficient and runoff maps for the China's transboundary river basins riparian countries were produced and compared with other estimates at the country level. The best water resources estimates achieved from the machine learning model are consistent with the Food and Agriculture Organization of the United Nations AQUASTAT database (root‐mean‐square error  = 76.97 km3/year, normalized root‐mean‐square error = 12%) at the country level. This outperformed two currently available runoff products: the UNH/GRDC Global Composite Runoff Fields and the Global Streamflow Characteristics Dataset. The study also demonstrated that accurate precipitation data can improve runoff and water resources estimation accuracy and that climate and topographic factors have a controlling role in prediction, whereas the influences of land cover and soils are weak. Finally, China's transboundary water resources were calculated and thoroughly assessed at basin and country levels. Key Points: High‐resolution (0.1 degrees) runoff coefficient and runoff maps of all the CTRB riparian countries were producedMachine learning models were more accurate than a traditional linear model and two popular runoff data productsThe water resources of China's transboundary river basins were comprehensively assessed at basin and country level for the first time [ABSTRACT FROM AUTHOR]

The article focuses on the study which examines the temporal trends of reference evapotranspiration (ETref) in the Yellow River Basin (YRB), China. Sensitivity coefficients of ETref to meteorological variables were identified with contributions of key meteorological variables to the temporal trend of ET ref being detected. The sensitive regions for ET ref response to the changes of the four meteorological variables are not similar in the YRB.

The establishment of water-saving crop planning is an inevitable choice of the water-saving agriculture for the water-deficiency region in the arid and semiarid Loess Plateau of China and the world. The water-saving crop planning refers to the planting structure that centres the adjustment of the crop’s adaptation to water, the optimization of temporal and spatial layout for crops, the local natural resources, marketing resources, human resources and financial input to enable region or basin with limited water resources to achieve the maximum economic, social and ecological benefits of planting industry under certain technology and economy. After the analysis on the research progress of optimization theory, optimization goals, optimization methods of water-saving cultivation structure and macro-control measures, it is pointed out that the main deficiencies of the current research of water-saving cultivation pattern optimization are lacking of a strong theoretical basis, and the immaturity of optimization technologies. The future crucial research direction will focus on five aspects such as the special optimization theory system, the division methods by studying the watershed unit and using 3S technology, optimization model based on multi-objective evolutionary algorithm, evaluation of rationality and macro-control measures on the basis of the public participation. [ABSTRACT FROM AUTHOR]

Model parameter calibration is a fundamentally important stage that must be completed before applying a model to address practical problems. In this study, we describe an automatic calibration framework that combines sensitivity analysis (SA) and an adaptive surrogate modeling‐based optimization (ASMO) algorithm. We use this framework to calibrate catchment‐specific sensitive parameters for streamflow simulation in the variable infiltration capacity (VIC) model with a 0.25° spatial resolution over 10 major river basins of China from 1960 to 1979. We found that three parameters—the infiltration parameter (B) and two of the soil depth parameters (D1, D2)—are highly sensitive in most basins, while other parameter sensitivities are strongly related to the dynamic environment of the basin. Compared with directly calibrating the seven parameters recommended for the default calibration procedure, our framework not only reduced the computing time by two thirds through opting out of insensitive parameters (type I error) but also improved the Nash‐Sutcliffe model efficiency coefficient (NSE) for optimized results when it identified a missing sensitive parameter (type II error) in the case study river basins. Results show that the SA‐based ASMO framework is an effective and efficient model‐optimization technique for matching simulated streamflow with observations across China. The NSE for monthly streamflow ranged from 0.75 to 0.97 and from 0.71 to 0.97 during the validation and calibration periods, respectively. The calibrated parameters can be applied directly in streamflow simulations across China, and the proposed calibration framework holds important implications for relevant simulation studies in other regions. Key Points: We proposed a calibration framework that combines sensitivity analysis (SA) and an adaptive surrogate modeling‐based optimization (ASMO)Calibrating unnecessary parameters (Type I error) and missing sensitive parameters (Type II error) were detected in default VIC calibrationThis SA‐based ASMO framework is an effective and efficient model‐optimization technique for streamflow simulations across China [ABSTRACT FROM AUTHOR]