Study region: The Baihe River Basin located in the upper Han River, central China. Study focus: Potential evapotranspiration (PET) is commonly utilized as the forcing data for hydrological simulation. The lack of observations for estimating PET usually limits the calculation of evapotranspiration in hydrological models. Fortunately, gridded PET products with high data availability provide a great opportunity for hydrological simulation. This study assessed the accuracy of five gridded PET products against the gauge-based data. The Distributed Time Variant Gain Model (DTVGM) was modified to evaluate the performance of these five PET products in streamflow simulation. Additionally, the effect of different PET inputs on simulated runoff components, evapotranspiration, and soil moisture were investigated. New hydrological insights for the region: The results indicate that there are large discrepancies in spatial-temporal distribution of five PET products. Among selected products, GLEAM-b is most consistent with the gauge-based PET in the study region. For the streamflow simulation, five gridded PET products can achieve good performance with the Nash-Sutcliffe efficiency (NSE) values exceeding 0.75 in the validation period. This finding demonstrates the feasibility of using gridded PET products for streamflow simulation. Moreover, GLEAM-b performs better than other products in streamflow simulation according to the evaluation indicators. For simulated runoff components and water balance components, baseflow and evapotranspiration are more sensitive to different PET inputs.

Classification is beneficial for understanding flood variabilities and their formation mechanisms from massive flood event samples for both flood scientific research and management purposes. Our study investigates comprehensive manageable flood event classes from 1446 unregulated flood events in 68 headstream catchments of China using hierarchical and partitional clustering methods. Control mechanisms of meteorological and physio-geographical factors (e.g., meteorology or land cover and catchment attributes) on spatial and temporal variabilities of individual flood event classes are explored using constrained rank analysis and a Monte Carlo permutation test. We identify five robust flood event classes, i.e., moderately, highly, and slightly fast floods as well as moderately and highly slow floods, which account for 24.0 %, 21.2 %, 25.9 %, 13.5 %, and 15.4 %, respectively, of the total number of events. All of the classes are evenly distributed in the entire period, but the spatial distributions are quite distinct. The fast flood classes are mainly in southern China, and the slow flood classes are mainly in northern China and the transition region between southern and northern China. The meteorological category plays a dominant role in flood event variabilities, followed by catchment attributes and land covers. Precipitation factors, such as volume and intensity, and the aridity index during the events are the significant control factors. Our study provides insights into flood event variabilities and aids in flood prediction and control.

The rapid development of urbanization has significant impacts on regional climate, and thereby affects the hydrological characteristics of urban areas. Urban hydrological models have been mainly focused on the changes in hydrological response caused by complex urban underlying surfaces and urban pipe network construction in previous studies, while there is a need to strengthen research on the climate change patterns caused by urbanization. Vapor pressure deficit (VPD) is a key indicator for studying water cycle in climate system, and it has a close relationship with hydrological processes such as precipitation, evapotranspiration, and surface water transport. However, as a meteorological indicator affected by multiple factors, a deep understanding of the quantitative analysis method for the contribution of different factors to VPD changes is still lacking. This study uses a urban-rural station pairing method to analyze the impact of urbanization and proposes a method based on partial differential equations to quantitatively explore the contribution of different factors to urban-rural VPD difference. Taking daily-scale data of urban-rural paired stations in mainland China as an example, the study finds that urbanization significantly increases VPD in the core urban areas, and the urban-rural VPD difference gradually expands over time, showing significant seasonal and geographical variations. The method based on partial differential equations can effectively capture the trend of the urban-rural VPD difference, thereby confirming the validity of the derived method for evaluating the contributions. Relative humidity is the main factor contributing to the urban-rural differences in VPD in most regions, but shows a different pattern in some plateau continental climate regions. This study establishes a framework for analyzing the impact of urbanization on specific meteorological indicators, especially providing a way to quantify the contribution of factors causing urban climate change, which is of reference value for further considering the uniqueness of urban climate in the construction of urban hydrological models.

The river basin is a fundamental natural unit interlinked with water, soil, air, ecology, and society, serving as a water management system for local communities. The River Basin Simulator (RBS) operates as a simulation system driven by datasets and hydrological knowledge, utilizing the technology of a digital twin basin. This paper addresses the initiative of WG1.14, specifically the Development & Application of River Basin Simulators, under Theme 1 of the HELPING program for IAHS, encompassing the goals and work plan of WG1.14. The development and applications of RBS in China, including the Yangtze River Simulator and its practical applications, are presented. Through RBS development, it can play a pivotal role in supporting the integration of natural hydrology with socio-hydrology, thereby fostering sustainable development. The initiative of WG1.14 has the potential to promote the development of tools for the digital twin basin, building a bridge from Change (Panta Rhei) to Solution (HELPING). This includes understanding hydrological processes, utilizing advanced hydrological models, and the practical application of socio-hydrology insights, supporting Theme 1 of HELPING with global and local interaction.

The nonstationary impacts of climate change and multi-reservoirs on extreme floods cannot be ignored due to the potential risk to flood control and river security. Nonstationary regional flood frequency analysis (NS-RFFA) provides an effective way to consider these influences. But there is currently no standard framework of NS-RFFA and insufficient consideration of uncertainty in quantile estimates. In the study, we proposed an improved framework of NS-RFFA considering the influence of multi-reservoirs as well as climate change and involving uncertainty estimation. The framework was applied to analyze the frequency of extreme floods in the Huai River Basin (HRB) where multi-reservoirs have been constructed and to reveal the extreme flood variation under the impact of climate change and reservoir group. Results show that precipitation during flood season and reservoir index played a dominant role in the variations of annual maximum streamflow in the HRB. The impact of reservoirs was more significant in the upstream tributaries than in the mainstream. The nonstationary models with location parameters varying with time and/or main influencing factors perform better on fitting extreme streamflow in the HRB compared with stationary and at-site analysis. The quantile estimates and their uncertainty based on NS-RFFA are dynamic, which gives an expression of the changing environment effects on annual maximum streamflow. Thus, our work contributes an improved framework of NS-RFFA considering the influence of climate change and reservoirs, providing more accurate and reliable estimates for river flood risk management.

River damming is believed to largely intercept nutrients, particularly retain more phosphorus (P) than nitrogen (N), and thus harm primary productivity, fishery catches, and food security downstream, which seriously constrain global hydropower development and poverty relief in undeveloped regions and can drive geo-political disputes between nations along trans-boundary rivers. In this study, we investigated whether reservoirs can instead improve nutrient regimes downstream. We measured different species of N and P as well as microbial functions in water and sediment of cascade reservoirs in the upper Mekong River over 5 years and modelled the influx and outflux of N and P species in each reservoir. Despite partially retaining total N and total P, reservoirs increased the downstream flux of ammonium and soluble reactive phosphorus (SRP). The increase in ammonium and SRP between outflux and influx showed positive linear relationships with the hydraulic residence time of the cascade reservoirs; and the ratio of SRP to dissolved inorganic nitrogen increased along the reservoir cascade. The lentic environment of reservoirs stimulated algae-mediated conversion of nitrate into ammonium in surface water; the hypoxic condition and the priming effect of algae-induced organic matter enhanced release of ammonium from sediment; the synergy of microbial phosphorylation, reductive condition and sediment geochemical properties increased release of SRP. This study is the first to provide solid evidence that hydropower reservoirs improve downstream nutrient bioavailability and N-P balance through a process of retention-transformation-transport, which may benefit primary productivity. These findings could advance our understanding of the eco-environmental impacts of river damming.

This paper examines the ethical issues of water environment in the context of river management in practical engineering and technological applications. In particular, three important issues are discussed in this paper referring to two actual engineering cases in ancient and modern China, that is, the construction of ancient Dujiangyan irrigation project in Sichuan, China, and the modern practice of integrated operation of flood control and pollution prevention in Huai River Basin. The three issues include how to consider the trade-offs between flood control and irrigation, how to balance flood control and contamination prevention related to sudden water pollution incident, and how to ensure the protection of water environments and ecology in rivers under the grand challenges of natural environmental changes and high-intensity human activities. Finally, this paper concludes by emphasizing the future development of water environmental ethics and its interdisciplinary integration with modern science & technology in smart river management in China.

The Yangtze River, the third largest river around the globe, has been heavily engineered with a series of hydroelectric dams. Meanwhile, it receives elevated organic matter and nutrient loads from its densely populated catchment, subsequently altering dissolved greenhouse gas (GHG) concentrations along the river. However, the large-scale longitudinal patterns and drivers of GHG concentrations in the Yangtze River remain poorly understood. Using longitudinal sampling design in a 2400 km section, we report dissolved carbon dioxide, methane, and nitrous oxide concentrations along the Yangtze River at 145 sites. We observe significant spatial clustering with higher carbon dioxide and nitrous oxide concentrations in the middle reach of the Yangtze River. The results of nonlinear regression reveal that riverine GHGs are high when wetland coverage is high and dissolved oxygen is low. Wetlands and oxygen, not the Three Gorges Dam and tributaries, are the primary correlates of spatial variations of CO2 and CH4 concentrations, respectively. N2O is surprisingly well predicted by CO2, implying their common drivers or sources. We strongly recommend that wetland contribution to GHG budgets and its sensitivity to environmental change be considered when estimating riverine GHGs in the Yangtze River. In light of our study, future control of GHG emissions from large rivers may largely depend on how external inputs and internal metabolism are regulated by decreasing nutrient loading.

城市下垫面对径流过程的调控特征及其空间差异是城市化水文效应关注的热点.现有研究受基础资料和模型发展等制约,城市复杂下垫面影响下降雨-径流过程模拟和径流过程特征指标变化机制辨识仍需加强.本文采用时变增益水文非线性产流模型耦合排水管网水动力模型,实现了对城市多种下垫面类型和汇流方式下降雨-径流过程的耦合模拟.在此基础上,以不同下垫面和排水管网等条件的四座城市（北京、深圳、武汉和重庆）典型小区为例,通过相似性检验和秩次分析等探索了下垫面对径流过程特征指标（径流系数、年径流总量控制率、洪水时间尺度及峰现时间延迟等）的影响、空间差异及关键影响因子,并量化其贡献.结果表明:耦合模型对各小区场次径流过程的模拟效果明显优于国内外使用广泛的暴雨洪水管理模型（SWMM）. 60%场次（12/20）的综合模拟精度提高了4～86%;特别是对模型偏差的改善效果最好,其次为效率系数.除径流系数外,各地块年径流总量控制率、标准化洪水时间尺度和峰现时间延迟占比存在显著的空间差异,其差异性指数分别为0.43、0.22和0.16（p＜0.05）.显著性影响因子包括排水管网系统的管道长度（r=0.51）和下垫面类型中林地（r=0.56）、海绵措施（r=0.52）、草地（r=0.48）和不透水地表（r=0.46）面积占比;其中排水管网和下垫面类型的贡献率分别为4.27%和37.83%.下垫面类型对径流过程的调控占主导,其中北京以草地调蓄为主,表现为延迟和削减洪峰,对径流总量有一定削减作用;深圳调控并不显著,表现为以不透水地表产生的尖瘦型径流过程;武汉以林地调蓄为主,表现为削减径流总量和延迟洪峰;重庆以水域调蓄为主,表现为削减径流总量和洪峰流量.本文可为拓展城市化径流效应研究、海绵城市建设效果评估等提供理论和技术支持,也为中国城市水文模型的发展提供参考借鉴.

The first-stage of middle route of South-to-North Water Transfer Project (MRSNWTP) will transport water to Beijing in 2014, a great deal of scientific and technological work has already been done in the planning and designing of MRSNWTP, After implementation of this project both water-exporting and importing areas will face new problems and challenges in regard to MRSNWTP management and operation. This paper discusses impact by MRSNWTP on regional economic and social sustainable development, including impact of water resource protection measures on social and economic development, role and impact of agriculture production, urban water-saving, groundwater management, and ecological restoration in water-importing areas, and integrated adjustment and control methods of natural resources, economic and environmental factors in water-exporting and importing areas. The paper will hopefully stimulate further debate and arouse more valuable ideas, in regard to basic issues in the management of the South-to-North Water Transfer Project.

This paper attempts to set up multivariate linear regression analysis (MLRA) model and 3-layers BP artificial neural network (ANN) mode on river networks and do some comparative researches about them. The applications to the watershed of Tarim indicate that the river flow processes which are simulated separately by two models are satisfactory. They can be the foundation for water resource allocation and scheduling. Above all, through analyzing the structures and forecast precisions of these models, artificial neural network model is better as compared with multivariate linear regression analysis model. In the end, this article puts forward some proposals about how to strengthen the predict abilities of river flow forecasting methods of river networks.

The hydrologic system is an open and complicated system, and also is a dynamic non-linear multiplexed systems, the space-time change of hydrologic factors has high non-linear characteristics. On the one hand, it is an important process which is with the natural factors such as weather, climate and topography interactions and inter-dependent in hydrologic cycle. On the other hand, it is affected differently by human product activities such as the basin development degree, local cultural level and so on, thus has formed complicated evolution rule of hydrologic system. f problems of non-linear hydrologic changes on essence are studied form the linear angle or approximately, there must be its inevitably limitation. To forecast the future evolution behavior of hydrologic dynamic system, we must know the topological structure or change rule of trace of system attractor. And phase space is the most ideal and the most direct-viewing space to describe the topological structure of system attractor. To construct the dynamical forecast model of time series, we must reconstruct the phase space of hydrologic dynamical system. The method of reconstructing the phase space can use the time series to reconstruct a low-dimension space whose dynamical system attractor does not change. According to theory of chaotic phase space, we established the single-point model, multi-point model, lineal model, three-parameter D(m,τ, k) model of local similarity model. The philosophy and algorithm of four kinds of model of chaotic phase space are also introduced, then its applicable for hydrology is discussed. This paper makes a prediction study about the month series of the Baishan reservoir of the second Songhua River using the above four kinds of models. It is reasonable and superior to use this model in medium-and-long-term hydrologic prediction. The application of the model in the long term runoff prediction of Baishan reservoir is shown, the result of calculation shows that the models are highly effective and is worthy of popularization and application. The research in this paper shows that applying the theory of chaotic phase space in the medium-and-long-term prediction of runoff system uses much more information of the time series than traditional methods. It is effective to reveal the non-linear structure of the hydrologic dynamical system, and it is a new method different from traditional definite method and random method. We should point out that it is significant for raising flood prediction precision to further explore the prediction method of phase space as well as easy methods.

The general situation of West Route of South - to - North water transfer project is briefly introduced, and the advance of study on ecological water requirements is simply reviewed. Based on the particular condition of Yalong River Basin, on the principle of analyzing ecological flow, several methods are chosen and used to calculate the ecological flow at the damsite Reba, and then the available quantity of transferable water is estimated. The results show that the ecological flow is 36. 3 similar to 46. 8 m(3)/s, and 3 the available quantity of transferable water is 42. 30 x 10(8) similar to 45. 62 x 10(8) m(3) accounting for 69. 6% similar to 75. 1 % of normal annual runoff.

In the past decades, runoff in the Yellow River has decreased sharply, with the mainstream drying up at times in recent years. At the Loess Plateau locating at the middle reaches of Yellow River Basin, people have constructed widespread silt arresters and terraces to conserve soil and water resources. However, for lack of systematic observation on water cycle, how does climate change and human activities as silt arresters and terraces affect local water cycle mechanism, what extent do they affect, and origin of local groundwater, is still under dispute. These call for a detailed study of interactions between precipitation, surface water and groundwater in Loess Plateau, which needs systematical observation on water cycle. In the study area Chabgou Catchment, typical Loess Plateau Ravine Region with great human activities, Chabagou Catchment and Caoping Xigou Experimental Watershed have been chosen to perform systematic hydrological and climatic observation, and to collect water samples periodically and instantaneously for isotopic and hydrochemical analysis. At Caoping Xigou Experimental Watershed, artificial rain also has been carried out to study the processes of runoff yield and precipitation infiltration. In combination with isotopic compositions and hydrochemistry of different waters, the hydrological study will provide reliable data foundation, and then to give some suggestions to reconstruction of local environment and ecology.

Since the 1950s the hydrological regimes have been significantly influenced by anthropogenic factors such as large scale soil - water conservation measures in the Loess Plateau. While these measures have reduced soil erosion, they also result in noticeable changes in the stream flow regime. In this paper the changes of stream flow regime were evaluated in the Chabagou catchment. The results indicated that a noticeable inflexion of stream flow occurred in 1978 due to conservation measures, Average annual stream reduces by 30% compared with the period before 1978. Reductions in annual stream flow were associated with interannual and intraannual variability in stream flow. Stream flow in wet season appears to be the main factor responsible for the decrease in intraannual variability. In addition, the hydrological regime of the catchment was changed consistently with the tip and down progress of sediment - trapping dams.