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Abstract Background Actual evapotranspiration (ETa) is a crucial aspect of the hydrological cycle. It serves as a vital link between the soil–vegetation–atmosphere continuum. Quantifying the leading factors of regional ETa change and revealing the multi-factor compound driving mechanism of ETa evolution is necessary. Structural equation modeling (SEM) has been widely used to study the structural relationships between variables in large-scale areas. However, there is an urgent need for more in-depth exploration of these complex relationships at the grid scale. Therefore, the Yiluo River Basin, a representative area of soil and water conservation engineering demonstration in the Loess Plateau, was selected as the study area, and the SEM at the basin scale and grid-scale were constructed to carry out the research. Results The data indicate that ETa decreased at 1.97 mm per year at the watershed scale from 1982 to 2020. Climate change had the greatest impact on the change of ETa in the watershed, with a total impact coefficient of over 0.9. The direct impact of climate change on ETa increased by 0.571 from 1982–1992 to 1993–2020. The direct impact coefficients of vegetation cover and soil moisture decreased by 0.402 and 0.102, respectively, while the impact coefficient of the water body factors increased by 0.096. At the scale of individual grid cells, the ETa in the watershed was affected by changes in watershed climate, vegetation, and soil moisture, with contributions ranging from − 0.31 to 0.22, − 1.09 to − 0.08, and 0.61 to 0.90, respectively. Spatially, vegetation and soil moisture had a stronger impact on ETa in the upstream area, while climate change had a negative effect, and the downstream region had the opposite effect. Furthermore, the regulatory impact of large reservoirs mitigated the response of water surface evaporation to climate change in the upstream region. Conclusions The application of SEM at different spatial and temporal scales has effectively quantified the driving mechanisms behind actual evapotranspiration in the Yiluo River Basin, while visually representing the spatial distribution characteristics of various influencing factors on ETa. This research provides a theoretical foundation for studying slope water consumption processes and circulation mechanisms.

Study region: This study was conducted in the Ganjiang River Basin, situated in eastern China. Study focus: Previous studies often quantified the impacts of climate change, land use, and dam construction on flow regime by only focusing on two of these factors at one time. In addition, the previous method used to quantify the deviation in the timing of annual extreme water conditions has a flaw. Therefore, this study improved the formula for calculating the deviation in the timing of annual extreme water conditions. Moreover, we proposed a novel framework for quantifying the impacts of dam construction, climate change, and land-use change on flow regime. New hydrological insights for the region: The study observed significant alterations in the flow regime of the Ganjiang River Basin. These modifications were predominantly influenced by dam construction and climate change. Dam construction led to a notable increase in dry season flow and minimum flow indicators, while decreasing maximum flow indicators. Conversely, climate change resulted in a reduction of minimum flow indicators and an increase in maximum flow indicators. Climate change has also led to an increase in the frequency and duration of flow pulses. Intriguingly, dam construction and climate change played offsetting roles for 77 % of the indicators. Considering the global climate change context, judicious dam operation could to mitigate the impact of climate change on the flow regime.

Evapotranspiration (ET) is a key link between atmospheric processes and land surface hydrological processes. With the impact of global warming and human activities, research on ET has become a hot topic. Supported by a total of 1,222 Chinese and English literatures from China National Knowledge Infrastructure and the Web of Science Core Collection from 2013 to 2022, this paper adopts the bibliometric visualization method to review the current research progress and future trend of ET with respect to the time of publication, countries, institutions, journals, and research hotspots. The results show that the number of related research articles is increasing rapidly and the journals with high citations are Journal of Hydrology, Agricultural and Forest Meteorology and Agricultural Water Management. The research hotspots have been focused on prototype observation, remote sensing inversion, mechanism equation, model simulation, spatial–temporal analysis, and attribution identification. In the future, there is an urgent need to integrate algorithms such as machine learning and artificial intelligence, to develop higher resolution remote sensing products, to improve the mechanism equations based on precise observations, and to clarify the impact of synergistic effects on ET among the driving factors. HIGHLIGHTS This study adopts the bibliometric method to systematically sort out the domestic and international articles on evapotranspiration.; The mechanism equations and remote sensing products of evapotranspiration were systematically summarized.; Spatial–temporal analysis and attribution identification methods of evapotranspiration have been summarized.; This study can be a guideline for future research on evapotranspiration.;

With global climate change, flooding events are becoming more frequent. However, the mechanism of how waterlogging stress affects crop roots needs to be studied in depth. Waterlogging stress can also lead to soil nitrogen and phosphorus loss, resulting in agricultural surface pollution. The aim of this study is to clarify the relationship between soil nitrogen and phosphorus distribution, root growth characteristics, and nitrogen and phosphorus loss in runoff water under waterlogging stress during the winter wheat seedling stage. In this paper, Zhengmai 136 was selected as the experimental material, and two water management methods (waterlogging treatment and non-waterlogging control treatment) were set up. Field experiments were conducted at the Wudaogou Hydrological Experimental Station in 2022 to assess the nitrogen and phosphorus concentrations in runoff water under waterlogging stress. The study also aimed to analyze the nitrogen and phosphorus content and the root distribution characteristics in different soil layers under waterlogging stress. The results showed as the following: 1. Waterlogging stress increased the characteristic parameters of winter wheat roots in both horizontal and vertical directions. Compared with the control treatment, the root length increased by 1.2–29.9% in the waterlogging treatment, while the root surface area and volume increased by an average of 3.1% and 41.9%, respectively. 2. Nitrogen and phosphorus contents in waterlogged soils were enriched in the 0–20 cm soil layer, but both tended to decrease in the 20–60 cm soil layer. Additionally, there was an inverse relationship between the distribution of soil nutrients and the distribution of wheat roots. 3. During the seedling stage of winter wheat, nitrogen loss was the main factor in the runoff water. In addition, nitrate nitrogen concentration averaged 55.2% of the total nitrogen concentration, while soluble phosphorus concentration averaged 79.1% of the total phosphorus concentration. 4. The results of redundancy analysis demonstrated that available phosphorus in the soil was the key environmental factor affecting the water quality of runoff water. Total phosphorus and dissolved phosphorus in the water were identified as the dominant factors influencing root growth.

The Yellow River Source Area (YRSA) functions as an ecological barrier within the Yellow River Basin, playing a significant role in providing indispensable ecosystem services. Analyzing the ecosystem service value (ESV) of YRSA holds great significance in establishing ecological protection awareness and promoting ecological actions. In this study, we reveal the spatial and temporal characteristics of ESV in YRSA from 2000 to 2020 based on the land use change and equivalent factor method, and explore the driving mechanisms behind ESV heterogeneity using geographical detector. The results showed that from 2000 to 2020, ESV in the YRSA increased significantly, with an average increase rate of 9.12 × 1021seJ/5a, showing a spatial distribution pattern of low in the northwest and high in the southeast, and this imbalance is gradually weakening. The average annual contribution of grassland ESV reached 45 %, followed by water bodies (23 %). Ecosystem services in the YRSA are mainly dominated by regulating services, among which hydrological regulating services are dominated, with an average annual contribution rate of more than 40 %. Supply and regulation, support and cultural services both form a strong correlation synergy. Climate factors are the main drivers of spatial heterogeneity in ESV, further illustrating the sensitivity of the YRSA to climate change. Moreover, our results accentuate the integral role of the YRSA in furnishing ESV to the broader Yellow River Basin, which provides a theoretical basis and reference for decision makers to assess the ecological security of the ecological barrier zones.

El ciclo hidrológico natural se ve muy afectado por el cambio climático. En particular, en algunas zonas montañosas, las precipitaciones pueden variar significativamente en el tiempo y el espacio, por lo que es muy importante identificar los procesos hidrológicos de las cuencas hidrográficas con alta resolución. Para analizar estos problemas, la prueba Mann-Kendall, la prueba T móvil, el estimador de pendiente Sen y la prueba de correlación de rango Spearman se combinan con la función de interpolación espacial ArcGIS. Se analiza y discute la evolución de las características de distribución espacial y temporal de las precipitaciones y la escorrentía en las cuencas montañosas típicas. Los resultados muestran que las precipitaciones disminuyen de sur a norte, de alta altitud a baja altitud. Esta diferencia se produce principalmente en el oeste de la cuenca. Las conclusiones son las siguientes: 1) la serie de precipitaciones y escorrentías cambió repentinamente en 1991; 2) el valor extremo de la tendencia de las precipitaciones se mueve del centro al oeste; 3) para la relación entre la escorrentía de la temporada de inundaciones y la escorrentía anual, la serie muestra una tendencia ascendente significativa (nivel de confianza del 95 %), lo que indica que la distribución desigual de la escorrentía ha aumentado de forma notable desde la década de 1960.

This study adopted the method of “exchanging space for time” and set up three experimental groups based on the shape, degree of damage, and degree of humification of the litter, namely the undecomposed layer, the semi-decomposed layer, and the decomposed layer. Using typical slopes of arbor and bamboo forests in the Pi River Basin as the research object, from October 2021 to December 2022, the soil carbon release flux was measured by using a closed static chamber gas chromatography method to reveal the carbon release law at the soil–air interface during the decomposition process of litter and quantitatively characterize the dynamic impact of the litter decomposition process on soil carbon release flux. Results showed that soil methane flux remained negative (sink) while soil carbon dioxide flux was positive (source) in both litter-covered and bare soil conditions. The methane and carbon dioxide release from soil was positively correlated with and significantly influenced by environmental factors such as soil moisture content and temperature. The methane release flux from soil showed a linear fitting relationship with soil moisture content and temperature, while the carbon dioxide release flux from soil was more in line with the exponential fitting relationship with soil moisture content and temperature. However, there were significant differences in the roles of various factors under different types of litter.

Climate change profoundly alters land use in alpine regions, and delving into the evolutionary characteristics of these changes is crucial for the sustainable development of regional land resources and the gradual enhancement of the ecological environment. Taking the source region of the Yangtze and Yellow River (SRYAYE) as a case study, we integrate permafrost and snowfall data into the Future Land Use Simulation model (FLUS). Analyzing historical land use, we predict and simulate the land use scenarios for 2030, 2035, and 2060 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climates, and conduct a detailed analysis of the scale, composition, and pattern of land use in this area. Scale. The results showed that ① the Kappa coefficient of the improved FLUS model was higher than 0.927, and that the overall accuracy of the simulation was increased by 2.64%; ② the area of forest land and the high-coverage grassland will increase in the future and the center of gravity will migrate to the west, and that the area of moderate and low-coverage grassland will slightly decrease but tend to become green to the west; and ③ the fragmentation degree of the SRYAYE is decreasing, and the influence of human activities on the landscape pattern is weaker than in the past.

Floods and droughts on farmland seriously damage agricultural production. Porous fiber materials (PFM) made from mineral rocks have high porosity, permeability, and water retention and are utilized widely in green roofs and agricultural production. Therefore, studying the impact of PFM on the improvement of farmland is of great importance for soil and water conservation. We set 64 extreme rainfalls to analyze the impact of PFM on soil water content (SWC), runoff, nutrient loss, microorganism, and plant growth. The results showed that PFM can effectively reduce runoff and improve soil water distribution, and enhance the soil water holding capacity. Furthermore, PFM reduced the loss of nitrogen and phosphorus by 18.3% to 97% in the runoff, and the soil erosion of summer corn was more strongly influenced by lower vegetation cover, compared with winter wheat. Finally, when PFM was buried in the soil, the wheat yield increased by −6.7%–20.4%, but the corn yield in some PFM groups decreased by 5.1% to 42.5% under short-duration irrigation conditions. Our study emphasizes that the effectiveness of PFM depends mainly on the following: First, PFM with high porosity can increase soil water holding capacity and timely replenish the water lost from the surrounding soil. Second, PFM with high permeability can increase infiltration during rainfall and decrease runoff and nutrient loss, reducing the risk of farmland flooding and pollution. Finally, PFM consists of gold ions and alkali metal oxides, which can stabilize agglomerates and improve soil enzyme activity, thereby increasing the relative abundance of some microbial strains and promoting crop growth. However, when the rainfall amount was low or PFM volume was large, PFM could not store water sufficiently during rainfall, which seriously reduced the maximum saturated moisture content and water absorption performance. Meanwhile, the PFM could not release water in time and replenish the soil water deficit, which increased drought risk. In conclusion, the appropriate volume of PFM and irrigation system may enhance soil water storage capacity, minimize agricultural pollution, and promote crop production.

Under the influence of global warming and human activities, the risk sources of land and water resources system networks are complex and uncertain, which has induced a series of ecological and environmental problems. It is of great significance to systematically identify and evaluate the risks of water and land resources system networks from the perspective of water resource attributes and land resource attributes. Therefore, based on the mutual feedback mechanism of water and land resources, this study constructs the water and land resources system network in the Huang-Huai-Hai Watershed. The cluster analysis-ISODATA algorithm and entropy weight-TOPSIS evaluation method were used to evaluate and predict the risk of the water and land resources system network in the Huang-Huai-Hai Watershed. In addition, a model for the optimal allocation of water and land resources for risk mitigation was constructed, and the optimal allocation scheme of water and land resources in the Huang-Huai-Hai Watershed in 2030, 2035 and 2060 under different scenario modes was obtained. The results show that the risk of the water and land resources system network in the Huang-Huai-Hai Watershed from 1990 to 2020 first increased and then decreased, and the proportion of areas above medium–high risk in 2001–2010 was 53.17%. Compared with 2020, the area above medium–high risk in 2030, 2035 and 2060 increased by 1.4–17.38%, 6.78–15.92% and 2.39–6.82%, respectively. After the optimal allocation of water and land resources for risk mitigation, the targets of optimal allocation of water and land resources in 2030, 2035 and 2060 were improved, among which the water shortage under different scenario modes was reduced by 71.92–79.19%, 65.92–74.46% and 62.23–71.69%, and the area above medium–high risk in the water and land resources system network decreased by 48.4–59.79%, 20.99–59.7% and 29.53–49.06%, respectively. The results of this study can provide technical support for coping with global climate change, solving the problem of water shortage and optimizing the spatial layout of the land in the Huang-Huai-Hai Watershed.

Our study was designed to spatially assess the regulation potential of watershed water-land resources, and determine its regulation objectives for subsequent optimal allocation. We centred around the Yiluo River Basin, being a soil conservation demonstration plot in the middle course of the Yellow River Basin. In accordance with the criteria of the green development, the high efficiency and the safety, the evaluation system of water-land resources regulation potential was established. Then the fuzzy comprehensive evaluation method was applied to assess the watershed water-land resources during 2001–2020 and 2030–2050, and the evaluation results were represented by the eigenvalue T. The research findings pointed out that the assessment grade of watershed water-land resources was mainly moderate and better state, and presented significant spatial agglomeration features in the historical and forecast years. In the context of dual influences of climatic variation and water-land resources exploitation, the assessment eigenvalue T of watershed water-land resources increased by 6% in the historical periods, and decreased by 4.57 ∼ 7.74% in the future periods. Based on the assessment results, it was recommended to restrict the water-land resources exploitation in the upstream, control the soil erosion in the midstream, and coordinate the relationship between the exploitation and protection of water-land resources in the lower reaches. Our study offers scientific evidence for the elaborate regulation of watershed water-land resources.

Colloidal quantum dot gradient homojunction would effectively improve the detectivity of mid-infrared photodetector at high-operating temperatures, motivating interest in low-cost, solution-processed and high-performance mid-infrared photodetection.

Measurement(s) river • stream • drainage basin • watershed Technology Type(s) computational modeling technique Sample Characteristic - Environment freshwater river Sample Characteristic - Location Earth (Planet)

Measurement(s) distributed global population and water withdrawal Technology Type(s) mathematical statistics and analysis

Study region: The Yiluo River Basin between the Sanmenxia Dam and the Huayuankou Station of the Yellow River basin. Study focus: The current research is designed to spatially identify different driving factors' contributions to natural runoff variation. The Water and Energy Transfer Process model was used to simulate the runoff of 2044 sub-basins. Based on this, trends of runoff variation were analyzed, and then, the mutation year of runoff variation in each sub-basin was detected. Moreover, the contribution rate of climatic variation and anthropogenic factors on runoff change in each sub-basin was quantified. New hydrological insights for the region: The annual natural runoff in 90.66% of sub-basins and the flood-season (May to October) natural runoff in 45.99% of sub-basins showed declining trends. And the mutation year of runoff change mostly occurred in the 1970 s and 1980 s. The natural runoff change was primarily affected by climatic variation. The contribution rate of climate to the annual and flood-season natural runoff was 69.32% and 71.51%, respectively. While the contribution of man-made activities to the annual and the flood-season natural runoff was 30.68% and 28.49%, respectively, and the high-impact areas were largely distributed downstream. The research provides scientific support for developing and regulating water and land resources in the Yiluo River Basin.

As a climate-sensitive region of the Tibetan Plateau, the source regions of the Yangtze and Yellow Rivers (SRYYRs) urgently require an analysis of land cover change (LUCCs) over a long period, high temporal resolution, and high spatial resolution. This study utilizes nearly 40 years of land cover, the Normalized Difference Vegetation Index (NDVI), climate, and geomorphological data, applying methods including a land transfer matrix, slope trend analysis, correlation analysis, and landscape pattern indices to analyze the spatial and temporal changes, composition, layout, and quality of the local land cover and the factors. The findings reveal that (1) the land cover area change rate was 8.96% over the past 40 years, the unutilized land area decreased by 24.49%, and the grassland area increased by 6.37%. The changes were obvious at the junction of the two source regions and the southeast side of the source region of the Yellow River. (2) the landscape pattern was more centralized and diversified. The number of low-cover grassland patches increased by 12.92%. (3) The region is still dominated by medium- and low-cover vegetation, with the mean annual NDVI increasing at a rate of 0.006/10a, and the rate of change after 2000 is three times higher than previously. (4) The degree of land cover change is greater in the middle altitudes, semisunny aspects, steepest slopes, and middle-relief mountains. Additionally, 76.8% of the region’s vegetation growth is dominated by mean annual temperatures. This study provides fundamental data and theory for understanding LUCCs and the driving factors in alpine plateau regions.

The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought–vegetation interaction in this area under the influence of climate–permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter–Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the source area and provide reference for ecological protection in permafrost regions.

Exploring the impact of urban land use change (LUC) on ecosystem services is significant for ensuring urban ecological security and realizing regional economic development. This study used land use data from 1985, 2000, 2014, and 2020 of Tongling city and the CA–Markov model to predict the LUC in 2025 and 2030. The spatio-temporal distribution characteristics of LUC during 1985–2030 were analyzed using the land use dynamics model and Sankey diagram. The vegetation-corrected ecological services value (ESV) equivalent was used to quantify the impact of LUC on ESV. Estimating the profit/loss value and spatial autocorrelation revealed ESV’s spatial and temporal dynamics in Tongling city. The results show that: 1) The most obvious LUC in the study area during 1985–2030 is the conversion of cultivated land to built-up land, in which the proportion of cultivated land decreased by 9.6%, and built-up land increased by 12.2%. 2) During 1985–2030, the ESV in Tongling showed an increasing trend at the beginning and then decreased, reaching a maximum value of 274.74 billion yuan in 2000. Regarding individual ecosystem service functions, the hydrological regulation function significantly contributed to ESV changes. The area change in paddy fields and built-up land had the most significant impact on ESV. 3) The total addition of ESV in Tongling during 1985–2030 was 5.98 billion yuan; the total loss was 18.59 billion yuan, and the net loss was 12.6 billion yuan. The proportion of area with ESV gains relative to the whole city is getting smaller, and the proportion of area with ESV losses is growing. The spatial autocorrelation shows the presence of high aggregation in ESV profit and loss areas. Simulating future LUC in Tongling and exploring ESV’s response is beneficial to developing new landscape patterns and ecological protection. It also provides a scientific basis for the extensive promotion of sustainable urban development in the future.

El Niño–Southern Oscillation (ENSO) events influence elements of the terrestrial water cycle such as precipitation and temperature, which in turn have a significant impact on drought. This work assessed the impact of El Niño and La Niña on droughts from 1970 to 2020 in the Weihe River basin (WRB) in China. This study used a standardized precipitation index (SPI) to characterize meteorological drought. The regional drought response to extreme events in El Niño/La Niña was analyzed using principal component analysis (PCA), Wilcoxon and Mann–Whitney tests, and other methods. The results showed that, based on PCA, the WRB is divided into two regions, with the northwest region (67%) comprising more area than the southeast region (33%). El Niño/La Niña significantly impacted drought in the WRB. Droughts mainly occurred in the El Niño year and the year following La Niña. El Niño had the highest number of drought years (44%), followed by the year following La Niña (43%). The number of droughts was lowest in the year following El Niño (22%). At 1-, 3-, and 6-month timescales, significant droughts mainly occurred from July to December in El Niño years and the summer following La Niña. On a 12-month timescale, significant droughts mainly occurred from January to April in El Niño years, while no droughts occurred in La Niña years. The longer the timescale of the SPI, the more months of significant drought in El Niño years; however, the intensity of drought in the basin was reduced. In the year following La Niña, summer droughts intensified on a 6-month timescale compared to a 3-month timescale. El Niño and La Niña had greater impacts on the drought index in the northwest region of the WRB. In the northwest region, 60% of the months showed significant drought, compared to only 2% of the months in the southeast region. The drought intensity was higher in the northwest region. The results of this study provide a reference for drought management and early warning systems in the WRB and support solutions to water shortage.

Infrared-to-visible upconverters have widespread application prospects, including bioimaging, night vision, and defense security. A typical upconverter is generally constructed by integrating an infrared photodetector (PD) detecting low-energy infrared with a visible light-emitting diode (LED) emitting high-energy visible light. However, when photocarriers transport through the interface between PD and LED, lateral current spreading is inevitably present, which leads to optical cross-talking and hinders the realization of high-resolution and large-area infrared imaging. Here, near-infrared (NIR) upconverters are fabricated via the integration of silicon (Si) NIR detectors with organic LED (OLED) by complementary metal–oxide–semiconductor compatible manufacturing processes. The pixelated indium tin oxide electrodes introduced as the interfacial carrier transfer channel effectively suppress the lateral current spreading and ensure that the photogenerated carrier of PD could transport into the OLED with a well-defined spatial resolution. The Si-OLED upconverters possess a wafer-level luminous area and large-scale fabrication capacity and realize high-resolution infrared imaging with a resolution as high as 3629 dpi. By changing the organic luminescent layer of OLED, the Si-OLED upconverters could emit red/green/blue visible light under NIR illumination with a low turn-on voltage of 3 V and an excellent upconversion efficiency of 9.2%. Furthermore, the large-area Si-OLED upconverters exhibit flexibility with an infrared upconversion ability even under bending.

Introduction: Droughts and flooding occur frequently due to climate change and human activities, which have significantly affected the ecological environment of farmland and crop production. Rock wool (RW) has some properties like high porosity and water retention capacity, and it is widely used in green roofing and agricultural production to reduce flood and drought disaster.Methods: We set 24 artificial rainfall experiments to analyze the impact of RW on the farmland runoff, soil water storage capacity (SWSC), nitrogen and phosphorus loss and crop growth. Finally, the Critic-Entropy comprehensive evaluation method was used to select the best solution for RW embedding.Results: The result shows that RW could reduce the runoff by 49.6%–93.3%, and it made the SWSC increase by .2%–11% Vol in the 10–70 cm depth. During the runoff process, the concentration of nitrogen and phosphorus decreased with the increase of the RW volume, while the nitrogen and phosphorus loss reduced by 51.9%–96.6% and 72.4%–96.4% respectively when RW was buried in the farmland, so RW could effectively promote soil and water conservation. Finally, RW increased the plant biomass and yield by a maximum of 12.1% and 20.4% respectively due to the large retention of water and nutrients. Therefore, combined with the above experimental result, this study indicates that RW could obtain the best comprehensive benefit in the embedding volume of 536.73 m3/ha.Discussion: When the volume of RW embedding was too large, RW easily caused insufficient water storage in short-duration rainfall or irrigation, which made the RW unable to release water to alleviate the soil water deficit during the critical growth period, which may result in drought events being aggravated and crop yield reduced. Overall, this study is conducive to clarifying the comprehensive application effect of RW in agricultural production, pollution control, and urban landscape, and it provides an important basis for expanding its application field and promoting the stability of farmland ecosystems.

Climatic factors are the main drivers that change net primary productivity (NPP). We chose the Yiluo River Basin as the study area to investigate the response of NPP to climatic factors in the Yellow River’s middle reaches. The temporal and spatial distribution of net primary productivity and the trend change of slope in the basin from 2000 to 2020 are analyzed. In addition, we analyzed the correlation between the NPP and climatic factors (precipitation and temperature) and the time-lag effect. The results show that 1) the annual average NPP in the basin is 556.4 gC/m2/a, the maximum value that occurred in 2019. Most of the NPP’s mutation points in the basin’s forest appeared in 2004, while the NPP’s mutation points in arable land mostly appeared in 2008 and 2009. 2) The slope trend analysis result of NPP from 2000 to 2020 shows that the NPP in 67.88% of the basin shows a significant increasing trend, 3.8% of the basin shows a significant decrease, and the other area show no significant change. 3) The correlation analysis between NPP and climatic factors shows a positive correlation between precipitation and NPP in 62.3% of the basin and a positive correlation between air temperature and NPP in 62.5%. The response of NPP to precipitation and temperature in the basin has different degrees of a time-lag effect. The NPP has a time-lag effect on precipitation in 44.8% of the basin, and its mean lag time is 8 days. NPP has a time-lag effect on temperature in 55.7% of the basin, and its mean lag time is 1 day. This study is beneficial to understanding the influence of climatic factor change on vegetation activities in the Yiluo River Basin. Our study illustrates the significance of time lag in analyzing the relationship between NPP and climatic factors. Furthermore, it provides support for scientific vegetation regulation and allocation, as well as adaptation to climate change in areas similar to the Loess Plateau, based on the lag time distribution corresponding to different vegetation types in different regions of the Yiluo River Basin. After that, these areas’ water resources will be fully utilized by vegetation, and ecological restoration could be accelerated.

Study region: Upper Blue Nile River Basin, Ethiopia Study focus: This study aims to determine possible trends in monthly, seasonal and annual precipitation and streamflow series. The Discrete Wavelet Transform (DWT) was used to obtain detailed information about the time-frequency conditions of six meteorological and five streamflow stations during 1984–2014. The Mann-Kendall test was also applied to the original and the DWT components to determine which periodicities are dominant in reproducing the observed trends. The combined DWT and Mann-Kendall test has not been explored in the UBNRB context. We used three criteria to determine a suitable wavelet, decomposition level, and signal extension mode. From these criteria, the bias ratio between the wavelet approximation series and the original time series was proposed and explored in this study. New hydrological insights for the region: Results show that almost all the precipitation stations experience an insignificant but increasing trend, whereas the streamflow stations exhibit an increasing trend at a 5% significance level. The combined use of DWT and the Mann-Kendall test show that periodic events up to 4 years are more influential in affecting the observed trends.

Our aim in this research was to detect historical and future water yield coefficient evolution and attribution. Based on the calibrated and validated water yield coefficient model in the Yiluo River Basin, the coefficient for the years 2000–2020 was simulated, along with the future projection for 2030–2050 under four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, and SSP585). The spatio-temporal evolution of historical and future water yield coefficients was then analyzed. Moreover, the geographical detector model was used to detect the impacts of climate, land use, and terrain factors on the water yield coefficient. The results showed that the water yield coefficient increased by 8.53% from 2000 to 2020, with the coefficient of farmland increasing by 10.47% and that of forestland decreasing by 8.93%. The coefficient was highest under the SSP370 scenario and the lowest under the SSP585 scenario in projections for 2030–2050. Compared to 2000–2020, the coefficients of the two scenarios increased by 12.2% and 2.0%, respectively. Consequently, under the SSP370 and SSP585 scenarios, the coefficient of farmland increased by 13.2% and 2.7%, and that of the forestland decreased by 0.9% and 14.6%, respectively. Driving factors detection indicated that land use types had the strongest explanatory power affecting the water yield coefficient; the explanatory value reached 26.5% in 2000–2020 and will exceed 29.5% in 2030–2050. In addition, the interaction between any two factors was stronger than a single factor. This research provides scientific support for the precise management of watershed and water-land resources.

Studying the probability characteristics of meteorological drought transmission to hydrological drought can help alleviate drought and optimize the allocation of water resources. This study takes the Yiluo River as the research object, and Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were used to represent meteorological and hydrological drought, respectively. First, the stability of the precipitation and stream flow sequence is tested by using the heuristic segmentation algorithm. The correlation between meteorological and hydrological watershed was analyzed using cross wavelet transform and lag correlation to study the transmission time of meteorological drought to hydrological drought. Second, the characteristics of drought such as drought duration, drought intensity, and drought intensity are discussed by using the run theory. Finally, the joint distribution of the SPI and SSI sequence is constructed using Copula function. From the perspective of conditional probability, the propagation probability and propagation threshold from different levels of meteorological drought to hydrological drought are calculated. A hydrological drought prediction model based on the SPI—P(SSI|SPI) relation curve is proposed. The model is also validated based on the historical data. The results show that the model is suitable for light and middle hydrological drought prediction.

With the increasing impact of climate change on ecosystems, it is crucial to analyze how changes in precipitation and temperature affect global ecosystems. Therefore, this study aims to investigate the spatiotemporal variation characteristics of the Enhanced Vegetation Index (EVI) in the global forest, grassland, shrubland, and tundra (FGST) from 2000 to 2021. We utilized partial correlation analysis and grey relation analysis to assess the responses of different vegetation types to precipitation, temperature, and extreme water and heat indicators. The result shows that, despite a “warmer and drier” trend in FGST (excluding tundra), global climate change has not adversely affected the ongoing vegetation growth. It presents a favorable implication for global carbon dioxide assimilation. Different vegetation types displayed different sensitivities to changes in precipitation and temperature. Shrubland proved to be the most sensitive, followed by grassland, forest, and tundra. As the impacts of global climate change intensify, it becomes crucial to direct our attention toward dynamics of vegetation types demonstrating heightened sensitivity to fluctuations in precipitation and temperature. Our study indicates that, except for forests, extreme precipitation indicators have a stronger impact on EVI than extreme temperature indicators. Forests and tundra have demonstrated heightened susceptibility to the intensity of extreme climatic events, while grasslands and shrublands have been more sensitive to the duration of such events. Understanding these responses can offer valuable insights for developing targeted strategies for adaptation and preservation. Our study enhances comprehension of the feedback relationship between global climate change and vegetation, offering scientific evidence for global climate change evaluation.

Understanding the spatial and temporal distributions and variations of basin water budget components is essential for effective water resources management. Due to a lack of basic hydro-meteorological information, the Upper Blue Nile River Basin (UBNRB) remains poorly understood in quantifying its hydrologic fluxes and associated dynamics. This study used a physically based distributed hydrologic model, WEP. We used multi-year land use information to better estimate the water budget components (evapotranspiration, runoff and storage) of the UBNRB. WEP simulation was validated at two main sections of the Upper Blue Nile river monthly from 1992 to 2014 (23 years). Results show that the basin stores a significant amount of water during the long rainy season (June to September) due to higher precipitation and limited evapotranspiration. However, it loses this storage through evapotranspiration during the dry season (October to February). The overall basin precipitation is 1,051 mm per year. Evapotranspiration accounts for 58% of the annual water budget, runoff is 25% and storage is 18%. The findings reported in this study can shed some light on understanding the UBNRB water budget dynamics and inform water management practitioners.

The key to dealing with extreme problems at watershed or region scales in the context of climate change is the “de-extremalization” of hydrological processes. The foundation lies in how to optimize the allocation of ecological restoration on slopes to mitigate the extreme impacts of climate change on hydrological processes and improve ecological service functions. Previous studies focused on analyzing the direct effects of slope land use, vegetation distribution, or historical pattern of ecological restoration on runoff processes. This study developed a slope ecological restoration evaluation system to evaluate the naturalness, functional types, and functional coordination of slope ecological restoration at different historical stages and quantitatively identified the mitigation effect on climate change in the future, which was applied to the Huangshui River Basin (above Minhe County) in Qinghai Province, China. Based on the land suitability evaluation methods, a set of layout schemes were constructed. The runoff mutation and ecological function of different schemes under climate change were evaluated, and the highly suitable scheme was selected as the optimal scheme. Compared with the current situation, the coupling coordination degree index of the scheme would increase from 0.32 to 0.59. Meanwhile, the runoff and coefficient of variation would decrease by 30% and 60%, respectively, during the wet season under the high-emission scenario RCP8.5. This study closely links the ecological construction of slopes with the response to extreme climates, which provides technical methods and practical support for the optimization of regional ecological patterns and scientific water governance modes.

Drought and floods frequently occurred in the Huaibei plain, which was the main factor that restricted agricultural development. We conducted rainfall experiments, which aimed to explore the impacts of porous fiber material (PFM) on the farmland water cycle processes and soil water storage capacity. In this study, we designed two types of rainfall intensities, 4 PFM volumes, 4 growth periods of winter wheat, and a total of 8 experimental groups and 32 rainfall events to evaluate the effects. The result showed that PFM had significantly affected the soil water circulation in the grain-filling period, and the peak flow and runoff decreased maximumly compared with other periods. However, the effect of PFM on surface runoff was slighter in the fallow period, and the peak flow or runoff decreased with the PFM volumes increased (R2 = −0.92, −0.99). In the 100 and 50 mm/h rainfall intensities, PFM decreased the average values of runoff by (55.2–59.6%) and (57.2–90.2%), reduced peak flow by (62.2–68%) and (64.2–86%), and increased the stable infiltration rate by (13.4–14.3%) and (26.6–41.3%), respectively. After the rainfall experiments ended for 1 h, the surface soil water rapidly infiltrated into PFM, which made the water-storage capacity of PFM groups higher than the control groups by 0.2–11% Vol. Subsequently, PFM increased the water-holding capacity by 0.3–2.3% Vol in the 10–70 cm depth from the heading period to the fallow period. It had a positive relationship between the PFM volumes and the average values of soil water content (R2 = 0.8, 0.84). In general, PFM could increase infiltration, reduce runoff, and improve the water-storage capacity to alleviate soil water deficit and the risk of farmland drought and floods. It has an excellent application effect in long-duration rainfall.

Landscape composition and configuration determine the source of pollutants. They also determine the interception and pollution-holding potential of the surface landscape. Using the upper reaches of the Si River Basin, a major grain-producing region in Shandong province in east-central China, as a case study, this study analyzed the influence of landscape characteristics on river water quality (RWQ) after superimposing topographic slope factors for 2017, and investigated which spatial scale had the strongest influence on RWQ. The landscape indices of three spatial scales (riparian zone, river reach and sub-catchment) and three slope scales (general land, flat ground and steep slope) were extracted. Correlation analysis and redundancy analysis were used to reveal the effects of landscape characteristics on RWQ at different scales. The results indicate that the landscape types were dominated by arable land and construction land in 2017. Landscape indices at different scales were significantly different. The RWQ generally met Class II or III surface water quality standard. Arable land and construction land had a negative impact on RWQ, both of which were “source” landscapes, while forest was a “sink” landscape that can effectively alleviate the deterioration of RWQ. The eight landscape indices which indicated heterogeneity, fragmentation level, landscape diversity, and shape information had different degrees of correlation with NO3−-N, NH4+-N, CODMn and BOD5. Different scales of landscape features had different correlations with RWQ, with the strongest correlation in the riparian zone, followed by the river reach, and the weakest in the sub-catchment. The influence of steep slope land was higher than that of flat ground land. The study confirmed that landscape structure and configuration had a scale effect on RWQ. It thus has great significance for water resources protection and land use management in the study area.

Climate changes and underlying surface of the watershed have affected the evolution of streamflow to a different degree. It is of great significance to quantitatively evaluate main drivers of streamflow change for development, utilization, and planning management of water resources. In this study, the Huangshui River basin, a typical basin of the Qinghai-Tibetan Plateau, China, was chosen as the research area. Huangshui is the largest first-class tributary in the upstream of the Yellow River. Based on the Budyko hypothesis, streamflow and meteorological datasets from 1958 to 2017 were used to quantitatively assess the relative contributions of changes in climate and watershed characteristics to streamflow change in research area. The results show that the streamflow of Huangshui River basin shows an insignificant decreasing trend; the sensitivity coefficients of streamflow to precipitation, potential evapotranspiration, and watershed characteristic parameter are 0.5502, −0.1055, and −183.2007, respectively. That is, 1 unit increase in precipitation would induce an increase of 0.5502 units in streamflow, and 1 unit increase in potential evapotranspiration would induce a decrease of 0.1055 units in streamflow, and an increase of 1 unit in the watershed characteristic coefficient would induce a decrease of 183.2007 units in streamflow. The streamflow decreased by 20.48 mm (13.59%) during the change period (1994–2017) compared with that during the reference period (1958–1993), which can be attributed to watershed characteristic changes (accounting for 73.64%) and climate change (accounting for 24.48%). Watershed characteristic changes exert a dominant influence upon the reduction of streamflow in the Huangshui River basin.

Water and soil losses from sloping farmlands potentially contribute to water eutrophication and land degradation. However, few studies explored the combined effects of ridge direction and ridge width on surface runoff and soil losses of sloping farmlands. Twenty-seven experimental plots (8 m long and 4 m wide) with nine treatments (three ridge direction: cross ridge, longitudinal ridge, and oblique ridge; and three ridge width: 40, 60, and 80 cm) were adopted under natural rainfall conditions for two years in the Luanhe River Basin of China. Results indicated that ridge direction had significant effects on runoff and sediment yield (p < 0.05). The ridge width had no significant effect on runoff and sediment yield. No significant interaction effect was found between ridge direction and width on runoff and sediment yield of the sloping farmland based on statistical analyses. Compared with cross-ridge (CR) tillage and oblique-ridge (OR) tillage, longitudinal-ridge (LR) tillage significantly decreased runoff by 78.9% and 64.9% and soil losses by 88.2 and 83.5%, respectively (p < 0.05). The effects of ridge directions on runoff and sediment yield were related to rainfall grade. When the rainfall grade reached rainstorm, the runoff yield under CR, LR, and SR had significant differences (p < 0.05). The runoff under LR and OR treatment was 5.16 and 3.3 times, respectively, of that under CR. When the rainfall level was heavy rain or rainstorm, the sediment yield under LR was significantly greater than that under CR. The sediment yield was 13.45 times of that under CR. Cross-ridge tillage with a ridge width of 40 cm is an optimally effective measure of soil and water conservation on sloping farmland in arid and semiarid regions of China.

In order to study the effect of the construction of the sponge cites on the process of urban water circulation in China, we analyzed the precipitation data from 756 stations across China between 1961 and 2011 and national land-use data in 2014. The spatial distribution characteristics of built-up area and amount of annual average runoff interception in sponge cities were explored in five different zonal scale levels. Assuming that the sponge cities have been built at the national-level construction land and the volume capture ratio of annual runoff is taken as 85%, the amount of annual average runoff interception in sponge cities is 988.58 × 108 m3 during 1961 to 2011 in China, where the annual precipitation is greater than or equal to 400 mm. The cities with more amount of annual average runoff interception are mostly distributed in Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta. As to the Haihe River Basin, the annual average amount of surface water resources is 135.69 × 108 m3 between 2005 and 2014, and the amount of annual average runoff interception is 219.58 × 108 m3 from 1961 to 2011. The construction of sponge cities has the greatest impact on the surface water resources in the Haihe River Basin. Taking 80%–85% as the volume capture ratio of annual runoff in sponge cities is not reasonable, which may lead to the irrational exploitation and utilization of regional water and soil resources.

This study analysed the temporal and spatial changes in the water yield coefficient (WYC), which represents the ratio of the gross amount of water resources to precipitation. Factors such as precipitation, rainstorm days, rainless days, vegetation cover change, and land use/cover change were considered to determine the causes of these changes. The results led to the following conclusions: (1) The average annual WYC of the Huang-Huai-Hai River Basin is between 0.03 and 0.58, with an average value of 0.17, which is smaller than the national average WYC of 0.4. (2) Temporally, the WYC varied slightly, with the western part showing a negative trend and the eastern part showing a positive trend. The WYC is positively correlated with precipitation, rainstorm days, and the normalized difference vegetation index (NDVI) and negatively correlated with rainless days. However, a slower change in NDVI produced a faster change in WYC. In areas with land use types exhibiting a large evapotranspiration decrease, the rate of change in the WYC increased. (3) Spatially, the distribution is fairly regular, exhibiting a gradual increase from the northern part of the Yellow River Basin (WYC < 0.1) to the surrounding areas. When the WYC is correlated with precipitation, rainstorm days, rainless days, and NDVI, the R2 values of the linear fitting results are 0.98, 0.91, 0.96, and 0.73, respectively. The WYC is positively correlated with precipitation, rainstorm days, and vegetation coverage and negatively correlated with rainless days, but the correlation coefficient is greatly influenced by the precipitation characteristics and land use types. In areas featuring high proportions of land use types associated with high evapotranspiration, the average WYC is low.

In this study, the major winter wheat planting area of China is selected as the study area, with the time scale of the growth period of winter wheat (a total of 56 growth periods during October 1961 to May 2016). The significance, stability, magnitude of the trend and the average trend of the study area with eight temperature indices and seven precipitation indices of 453 meteorological stations are tested by Mann−Kendall method and Sen’s nonparametric method. The following observation can be made: (1) the cold extreme indices show strong and stable downward trend in most of the stations in the study area, while the hot extreme indices show a strong and stable upward trend, especially in the northern winter wheat planting area and the north of the southern winter wheat planting area. (2) The trends of extreme precipitation indices in most of the sites in the study area are insignificant and unstable. Only in R20mm, a significant and stable decreasing trend is shown in some stations, which is mainly located in the northern winter wheat planting area and part of the central and western regions in the study area. The results in some ways could enrich the references for understanding the climate change in the growth period of winter wheat in the region and help to formulate a better agronomic management practice of winter wheat.

High temporal-spatial precipitation is necessary for hydrological simulation and water resource management, and remotely sensed precipitation products (RSPPs) play a key role in supporting high temporal-spatial precipitation, especially in sparse gauge regions. TRMM 3B42V7 data (TRMM precipitation) is an essential RSPP outperforming other RSPPs. Yet the utilization of TRMM precipitation is still limited by the inaccuracy and low spatial resolution at regional scale. In this paper, linear regression models (LRMs) have been constructed to correct and downscale the TRMM precipitation based on the gauge precipitation at 2257 stations over China from 1998 to 2013. Then, the corrected TRMM precipitation was validated by gauge precipitation at 839 out of 2257 stations in 2014 at station and grid scales. The results show that both monthly and annual LRMs have obviously improved the accuracy of corrected TRMM precipitation with acceptable error, and monthly LRM performs slightly better than annual LRM in Mideastern China. Although the performance of corrected TRMM precipitation from the LRMs has been increased in Northwest China and Tibetan plateau, the error of corrected TRMM precipitation is still significant due to the large deviation between TRMM precipitation and low-density gauge precipitation.

The physical-based drought indices such as the self-calibrated Palmer Drought Severity Index (sc-PDSI) with the fixed time scale is inadequate for the multiscalar drought assessment, and the multiscalar drought indices including Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), and Standardized Precipitation Evapotranspiration Index (SPEI) based on the meteorological factors are lack of physical mechanism and cannot depict the actual water budget. To fill this gap, the Standardized Water Budget Index (SWBI) is constructed based on the difference between areal precipitation and actual evapotranspiration (AET), which can describe the actual water budget but also assess the drought at multiple time scales. Then, sc-PDSI was taken as the reference drought index to compare with multiscalar drought indices at different time scale in Haihe River basin. The result shows that SWBI correlates better with sc-PDSI and the RMSE of SWBI is less than other multiscalar drought indices. In addition, all of drought indices show a decreasing trend in Haihe River Basin, possibly due to the decreasing precipitation from 1961 to 2010. The decreasing trends of SWBI were significant and consistent at all the time scales, while the decreasing trends of other multiscalar drought indices are insignificant at time scale less than 3 months.

This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen’s slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = −0.37) and Adet (Z = −0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980–2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies.