Research on the potential of the deep learning-based "decomposition-optimization-reconstruction" method in runoff prediction for typical climate- and human-regulated basins in northern China.

River runoff may be affected mainly by the natural climate or human activities, and runoff series present complex characteristics, such as non-stationarity, which makes accurate prediction of runoff challenging. To address the problem that the prediction accuracy of the traditional deep learning methods is affected by the non-stationarity of runoff, which is based on the idea of "decomposition - optimization - reconstruction", this paper constructs a combination model that introduces variational mode decomposition (VMD) and the whale optimization algorithm (WOA) to optimize a bidirectional long short-term memory neural network (BiLSTM) (VMD-WOA-BiLSTM). The combination model is applied to runoff prediction in typical climate- and human-regulated watersheds in northern China, specifically in the semi-arid regions of the Hailar River Basin and the Dahei River Basin.

Hydrogeochemical evolution patterns of diverse water bodies in mining area driven by large-scale open-pit combined underground mining-taking Pingshuo Mining Area as an example.

Large-scale open-pit combined underground mining activities (OUM) not only reshape the original topography, geomorphology, and hydrogeochemical environment of the mining area, but also alter the regional water cycle conditions. However, due to the complexity arising from the coexistence of two coal mining technologies (open-pit and underground mining), the hydrological environmental effects remain unclear. Here, we selected the Pingshuo Mining Area in China, one of the most modernized open-pit combined underground mining regions, as the focus of our research.

Identifying the spatio-seasonal pattern of hydrochemical evolution and surface water-groundwater interaction in a large urban river basin, Northwest China.

There is insufficient understanding of the spatio-temporal evolution of surface water-groundwater quality and hydraulic connection under both natural and human influences in urban river basins. To this end, this paper investigated the spatio-seasonal pattern of hydrochemical evolution and surface water-groundwater interaction in a typical urban river basin (Dahei River basin) based on isotopic and hydrochemical data of 132 water samples collected during three seasons (normal, wet and dry seasons). From the normal season to the wet season, surface water in the Dahei River basin was dominated by the impacts of evaporation and groundwater discharge processes.

A national-scale assessment of land subsidence in China's major cities.

China's massive wave of urbanization may be threatened by land subsidence. Using a spaceborne synthetic aperture radar interferometry technique, we provided a systematic assessment of land subsidence in all of China's major cities from 2015 to 2022. Of the examined urban lands, 45% are subsiding faster than 3 millimeters per year, and 16% are subsiding faster than 10 millimeters per year, affecting 29 and 7% of the urban population, respectively.

Improvement of evapotranspiration simulation study in the Hailar River basin under the influence of vegetation dynamics.

In arid and semi-arid areas with <400 mm of precipitation, evapotranspiration (ET) accounts for about 80% of precipitation and is the main water consumer in the watershed. However, vegetation greening in recent years will increase ET and exacerbate the aridity of the area by affecting soil moisture in the root system. Vegetation changes are regional and spatially heterogeneous, therefore, in order to characterize ET changes under vegetation dynamics, it is necessary to expand the spatial scale of ET simulation.

Identification of pollution source and prediction of water quality based on deep learning techniques.

Semi-arid rivers are particularly vulnerable and responsive to the impacts of industrial contamination. Prompt identification and projection of pollutant dynamics are crucial in the accidental pollution incidents, therefore required the timely informed and effective management strategies. In this study, we collected water quality monitoring data from a typical semi-arid river.

Exploring the spatiotemporal variations in regional rainwater harvesting potential resilience and actual available rainwater using a proposed method framework.

Rainwater harvesting potential provides a basis for alleviating regional drought and water shortages. The resilience of rainwater harvesting potential is directly related to the sustainable level of actual available rainwater. Thus, SWAT model was combined with the proposed rainwater harvesting potential evaluation model to quantify rainwater harvesting potential, its resilience and actual available rainwater in the study area.

Changes in vegetation cover and its influencing factors in the inner Mongolia reach of the yellow river basin from 2001 to 2018.

Vegetation cover is one of the primary indicators of changes in ecosystems. China has implemented a few large-scale afforestation programs in the arid and semi-arid areas, including the Inner Mongolia Reach of the Yellow River Basin to prevent and control soil erosion. Although these programs have alleviated the environment problems in the region to a certain extent, the effects of the increasing vegetation greenness on the environments under climate change remain controversial for the argued large water consumption.

Phytoplankton community variation and ecological health assessment for impounded lakes along the eastern route of China's South-to-North Water Diversion Project.

Interbasin water diversion projects have been proven to effectively alleviate water resource shortages in areas along water diversion lines, but few studies have focused on ecological health in impounded lakes compared with research on water quality and pollutants. Herein, monitoring data were collected during the nonwater diversion period (NWDP) and the water diversion period (WDP) from 2018 to 2019, and the index of biological integrity (IBI) method based on phytoplankton communities was used to evaluate the ecological health of the impounded lakes (Nansi Lake and Dongping Lake) along the eastern route of the South-to-North Water Diversion Project. The results demonstrated that water diversion improved the water quality of the impounded lakes during the WDP, especially total nitrogen and ammonia nitrogen.

Contribution of nonpoint source pollution from baseflow of a typical agriculture-intensive basin in northern China.

Baseflow is an essential component of total surface runoff that is widely considered one of the most influential factors regarding water quality via nonpoint source (NPS) pollution. Previously, many researchers and policy makers have directed their efforts toward surface runoff pollution, largely ignoring nutrient delivery via baseflow. Taking a typical agriculture-intensive basin of northern China as an example, this study explored the spatiotemporal characteristics of baseflow and pollution load in relation to NPS pollution.

Assessing alterations of water level due to environmental water allocation at multiple temporal scales and its impact on water quality in Baiyangdian Lake, China.

Lakes in arid/semiarid regions face problems of insufficient inflow and degradation of water quality, which threaten the health of the lake ecosystem. Baiyangdian Lake (BYDL), the largest lake in the North China Plain, is confronted with such challenges. The objective of this study was to improve understanding of how changes in water level influence water quality in the BYDL at different temporal scales, especially related to implementations of intermittent environmental water allocation activities in the past two decades, by using data on monthly lake water level, climate factors of precipitation and temperature, and lake water quality.

Spatiotemporal variations in evapotranspiration and its influencing factors in the semiarid Hailar river basin, Northern China.

Evapotranspiration (ET) is a critical variable in the world's water cycle, and plays a significant role in estimating the impact of environmental change on the regional hydrothermal cycle. Moreover, as an essential of eco-hydrological processes, changes in ET may exceptionally impact the local climate and provide indicative information on the eco-system's functioning. The Hailar River Basin (HRB), located in northern China, is one of the most sensitive areas to climate warming.

Root-zone soil moisture estimation based on remote sensing data and deep learning.

Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (<5 cm). Researchers have attempted to estimate root-zone soil moisture using multiple regression, data assimilation, and data-driven methods.

Evaluating the influence of different environmental water allocation schemes on the water level of a typical shallow lake in semiarid regions: From the perspective of an integrated modeling approach.

Many lakes in semiarid regions around the world rely on environmental water allocation to maintain the health of the lake ecosystem. However, under changing environments, the competition for water resources between human society and natural ecosystems has intensified. How to manage environmental water allocation more reasonably and precisely has become an important issue.

A novel ecohydrological model by capturing variations in climate change and vegetation coverage in a semi-arid region of China.

Variations in vegetation are influenced by regional climate regimes and, in turn, control the water balance behavior in water-limited regions. Owing to its role in ecohydrological processes, vegetation is an essential link in modeling the relationships among climate conditions, vegetation patterns, and dynamic water balance behavior. However, previous ecohydrological models have been empirical and complex, without physically significant parameters.

Modification and upscaling of S-W model based on vertical distributions of soil moisture and vegetation root biomass.

Soil water is the dominant factor controlling evapotranspiration (ET) in arid and semi-arid regions. However, the widely used ET simulation models, such as the Shuttleworth-Wallace model (S-W model), are insufficient in simulating the direct influence of soil moisture (SM), especially in the root zone. Based on SM and ET field data, we found that the influence of SM on ET increased with soil depth in the grassland.

Evaluating the risks of spatial and temporal changes in nonpoint source pollution in a Chinese river basin.

In watershed management, it is of great importance to evaluate the risks of nonpoint source (NPS) pollution. In this study, the Nonpoint Source Pollution Risk Index (NSPRI), a multi-factor NPS risk assessment model that was based on the source-sink landscape theory, was proposed and applied in Muzhuhe River Basin, Shandong, China to (1) highlight spatial and temporal variations in the risks from nitrogen and phosphorus losses, and (2) identify how the basin characteristics influenced the risk of nutrient loss. According to the analysis on land use change, the study area is featured with high proportions of forest and agricultural land uses; the area of urban and industrial land had increased considerably from 2000 and 2018.

Modeling water quantity and quality for a typical agricultural plain basin of northern China by a coupled model.

Water crisis across the globe has placed high pressure on social development due to the need to balance the water consumption between sustainable economy and functioning ecosystem. Integrated process-based modeling has been reported as an effective tool to better understand the complex mechanisms of water issues on a basin scale. Considering that it is still relatively difficult to simulate the water quantity-quality processes simultaneously, this study proposed an integrated modeling framework by coupling a hydrological model with a water quality model.

Dynamic landscapes and the driving forces in the Yellow River Delta wetland region in the past four decades.

Wetlands provide a broad range of ecosystem services, such as flood control, groundwater replenishment, and water purification. These services are particularly important in the Yellow River Delta, one of four estuarine deltas in China. The aim of this study was to examine the patterns and drivers forces of wetland landscape in the Yellow River Delta.

Unraveling the sensitivity and nonlinear response of water use efficiency to the water-energy balance and underlying surface condition in a semiarid basin.

Ecological water use efficiency (WUE) is a crucial indicator of hydrological and vegetation carbon cycle coupling and can drastically affect water and energy exchanges. However, little is known about the sensitivity of WUE to water-energy exchange in semiarid regions. Moreover, few studies have considered the link between WUE and water-energy exchange models, i.

Integrating satellite observations and human water use data to estimate changes in key components of terrestrial water storage in a semi-arid region of North China.

Sustainable management strategies for water resources rely on accurate knowledge about the dynamics of hydrological processes, especially in drylands, where freshwater is the limiting factor for the development of human society and ecosystems. The populated Loess Plateau (LP) in North China is a typical semi-arid region where competition for water between people and nature is worth noting because of afforestation promoted by the Grain to Green Program. In this study, changes in key components of terrestrial water storage (TWS) in the LP were explored using a multi-satellite approach, including Gravity Recovery and Climate Experiment (GRACE) observations and Earth observations of precipitation, evapotranspiration and soil moisture.

Establishing a time series trend structure model to mine potential hydrological information from hydrometeorological time series data.

This paper addresses the problem of missing latent time series information caused by the differences in the analysis of time series data and non-time series data. A time series trend structure model (TSTM) was established using the analysis of time series patterns and rules, the trends of patterns and rules, and trends in confidence and support. Shandong Province was selected as the study area.

Exploring the application of artificial intelligence technology for identification of water pollution characteristics and tracing the source of water quality pollutants.

Point sources are important routes through which pollutants enter rivers. It is important to identify the characteristics of and trace the origins of water pollutants. In this study, an artificial intelligence system called the integrated long short-term memory network (LSTM), using cross-correlation and association rules (Apriori), was used to identify the characteristics of water pollutants and trace industrial point sources of pollutants.

Vertical variations of soil water and its controlling factors based on the structural equation model in a semi-arid grassland.

Soil water content (SWC) of a vertical profile plays an important role in the soil-plant-atmosphere continuum system through eco-hydrological process, which was controlled by multiple factors. Previous studies ignored soil water from a systematic perspective because of the lack of suitable methods to deal with interrelated factors. We developed a meta-model based on structural equation model (SEM) to identify the factors contributing to soil water, and the interactions among these factors, in a semi-arid grassland system.

Assessment of lake eutrophication using a novel multidimensional similarity cloud model.

Lake eutrophication is characterized by a variety of indicators, including nitrogen and phosphorus concentrations, chemical oxygen demand, chlorophyll levels, and water transparency. In this study, a multidimensional similarity cloud model (MSCM) is combined with a random weighting method to reduce the impacts of random errors in eutrophication monitoring data and the fuzziness of lake eutrophication definitions on the consistency and reliability of lake eutrophication evaluations. Measured samples are assigned to lake eutrophication levels based on the cosine of the angle between the cloud digital characteristics vectors of each sample and those of each eutrophication grade.