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Temporal and spatial changes in non-point source pollution, driven by significant alterations in land use due to increased human activity, have considerably affected the quality of groundwater, surface water, and soil environments in the region. This study examines the Weihe River basin in greater detail, an area heavily impacted by human activity. The study developed the River Section Potential Pollution Index (R-PPI) model using the Potential Non-Point Source Pollution Index (PNPI) model in order to investigate the dynamic changes in River Section Potential Pollution (R-PP) over a 31-year period and its associated risks, especially those related to land use and land cover change (LUCC). The predominant land uses in the Weihe River Basin are cropland, grassland, and forest, making up around 97% of the basin's total area. The Weihe River Basin underwent a number of soil and water conservation initiatives between 1990 and 2020, which significantly decreased the potential pollution risk in the river segment. The research separated the R-PP risk values in the area into five different categories using a quantile classification technique. According to the data, there is a polarization of R-PP risk in the area, with downstream parts especially having an increased risk of pollution in river segments impacted by human activity. On the other hand, river segments in the middle and upper reaches of the basin showed a discernible decline in possible pollution risk throughout the study period. The Weihe River Basin's rapid urbanization and land degradation are to blame for the current increase in R-PP risk. The substantial influence of LUCC on the dynamic variations in R-PP risk in the Weihe River Basin is highlighted by this study. Additionally, it offers crucial information for upcoming conservation initiatives and urban planning guidelines meant to enhance the area's ecological well-being and environmental standards. [ABSTRACT FROM AUTHOR]

Automated water body (WB) extraction is one of the hot research topics in the field of remote sensing image processing. To address the challenges of over-extraction and incomplete extraction in complex water scenes, we propose an encoder–decoder architecture semantic segmentation network for high-precision extraction of WBs called EDWNet. We integrate the Cross-layer Feature Fusion (CFF) module to solve difficulties in segmentation of WB edges, utilizing the Global Attention Mechanism (GAM) module to reduce information diffusion, and combining with the Deep Attention Module (DAM) module to enhance the model's global perception ability and refine WB features. Additionally, an auxiliary head is incorporated to optimize the model's learning process. In addition, we analyze the feature importance of bands 2 to 7 in Landsat 8 OLI images, constructing a band combination (RGB 763) suitable for algorithm's WB extraction. When we compare EDWNet with various other semantic segmentation networks, the results on the test dataset show that EDWNet has the highest accuracy. EDWNet is applied to accurately extract WBs in the Weihe River basin from 2013 to 2021, and we quantitatively analyzed the area changes of the WBs during this period and their causes. The results show that EDWNet is suitable for WB extraction in complex scenes and demonstrates great potential in long time-series and large-scale WB extraction. [ABSTRACT FROM AUTHOR]

Droughts in the Weihe River Basin are occurring more frequently and are becoming more intense. These events negatively affect industrial production, economic development, and ecosystems. Studying how vegetation changes in response to them is of practical significance. We report temporal and spatial trends in vegetation cover, use a copula function to analyze relationships between drought and vegetation cover, and assess the probability of vegetation loss in different drought scenarios. A vegetation index trends upwards from north to south in this basin; from 2001 to 2017, vegetation cover also trends upward in most areas, although it decreases in areas with high vegetation cover. An escalated susceptibility to drought has been observed in the southern and eastern sectors, where proximity to the riverbank correlates with heightened drought sensitivity, particularly in zones of intensified vegetation density. The probability of vegetation loss at the same vegetation loss preset point gradually increases with increased drought severity. These results will facilitate the formulation of countermeasures to prevent and combat the effects of drought on vegetation and land management. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the temporal and spatial variation characteristics of soil moisture in the Weihe River Basin, to clarify the main factors affecting soil moisture changes, so as to provide scientific basis for effective monitoring of agricultural drought in the Weihe River Basin. [Methods] Based on the MODIS NDVI, LST data and climatic data of Weihe River Basin from 2000 to 2020, integrated trend analysis and geographic detector, the NDVI-Ts characteristic space was constructed, and the spatiotemporal variation of soil moisture and its driving factors were analyzed. [Results] In the past 20 years, the soil moisture in Weihe River Basin showed a significant downward trend at the rate of 0.004 9/a, and there was an obvious drying phenomenon. In different land use types, the soil moisture contents in the past 20 years followed the order: woodland > grassland > cultivated land > urban and construction land. The overall dry and wet grade was mainly normal (0.4≤TVDI < 0.6). The low value areas of soil moisture mainly distributed in the west and north of Weihe River Basin, and the high value area primarily concentrated in the southeast and northwest edge areas. In the sub-basins, the proportion of drought area in the main basin of Weihe River showed an upward trend, in which the decreasing trend of soil moisture in Guanzhong Plain located in the south of the main basin of Weihe River was the most significant. According to the influence analysis of detection factors, it was found that elevation, the average temperature and the potential evapotranspiration were the main factors affecting soil moisture distribution in Weihe River Basin, and their explanatory power was significantly higher than that of other factors. Factor interaction analysis showed that the combination of the average temperature and the cumulative precipitation had a significant effect on the spatial distribution of soil moisture in Weihe River Basin. [Conclusion] Soil moisture in Weihe River Basin had decreased significantly in the past 20 years, and there was an obvious drying trend. The change of soil moisture in Weihe River Basin was mainly affected by topography, geomorphology and meteorological factors. [ABSTRACT FROM AUTHOR]

[Objective] The aim of this study is to quantitatively assess the evapotranspiration trends and analyze its response to environmental changes in the Weihe River Basin, so as to be conducive to the study of water resources change in this region. [Methods] Based on the Budyko framework and combined with NDVI, land use type. GLEAM evapotranspiration remote sensing data, meteorological and hydrological data and social and economic data, the trend of each driving factor was analyzed, an empirical model of time-varying Budyko parameter was constructed, and the elastic coefficient method was adopted to quantitatively evaluate the influence of each factor change on evapotranspiration. [Results] (1) From 1990 to 2020. the actual evtranspiration in the Weihe River Basin showed a significant growth trend, with the overall growth rate of 1.98 mm/a, and the spatial trend was gradually decreasing from southeast to northwest. (2) The hydrothermal parameter of the underlying surface of the Weihe River Basin showed an increasing trend. and parameter had a high correlation with the NDVI, population, cultivated land area. grassland and GDP of the region. In the simulation of evapotranspiration, the results of the empirical model with time-varying parameter n are better than those with constant parameter n. (3) Evapotranspiration in Weihe River Basin was the most sensitive to precipitation, but not to underlying surface parameter n, which was most sensitive to NDVI. (4) Precipitation contributed the most to evapotranspiration, followed by underlying surface factors, and potential evapotranspiration contributed the least. [Conclusion] Evapotranspiration in the Weihe River Basin showed a significant increase trend during the study period, and climate change played a leading role in the change of evapotranspiration in this region, but the influence of human activities on evapotranspiration became more and more obvious. [ABSTRACT FROM AUTHOR]

Reducing river flows significantly affects livelihoods, ecology and industrial production. Therefore, allowing for ecological flow requirements has been applied to limiting human water consumption and is incorporated into water allocation planning. However, the unavailability of ecological data greatly limits e‐flow studies and this lack of sufficient ecosystem data is mostly addressed by using hydrological metrics as surrogates of the river ecosystem. This study employed the nine indicators of the 'Flow Health' model to assess river hydrological health and explore optimal ecological flow regimes. The modelling estimated the required flow and the extra flood flows of ecosystem conservation under default and custom thresholds. Ecological flows were calculated for five stations of the Weihe River through coupling with three hydrological methodologies. The index of flow deviation indicated that the flow regimes in Weihe River have partially changed from the reference period. Fish and other aquatic habitats have changed by reduced flows, but the health of the floodplain ecosystem has not been seriously affected. The ecological flow modelling results showed that the extra flow required for the ecology restoration in five stations is concentrated from July to September. The optimal ecological flows in dry seasons by coupling three hydrological methods were less than the average current flow, which is reasonable. This coupling provides ideas on how environmental flow assessments are undertaken in similar regions. [ABSTRACT FROM AUTHOR]

Vegetation cover is crucial for ecosystem stability, responding sensitively to climate change and human activities, and is prone to irreversible degradation. However, the mechanisms driving vegetation variations due to natural and anthropogenic factors still need to be fully understood. This study focused on the Weihe River Basin to elucidate the response mechanism of vegetation cover change to climate change and human activities from 2001 to 2020. Long time‐series multi‐source data were combined with a pixel dichotomy model, Theil–Sen median trend analysis, and Mann‐Kendall test to examine the trends and delineate five gradients in vegetation cover change. Additionally, Extreme Gradient Boosting, the Shapley value, and a structural equation model were employed to investigate the multidimensional response of vegetation cover in the basin as a whole and different vegetation cover gradients. The results revealed a general upward trend in vegetation coverage in the Weihe River Basin from 2001 to 2020. Topographic conditions and human activities were identified as primary influencers. Notably, accounting for climate change, particularly about changes in maximum climatic variables, was found to be essential, with temperature changes exerting a greater impact on vegetation cover variations compared to precipitation changes. The interaction between human activities, climate change, and topographic conditions can alter the intensity of each factor's effect. The direction of indicators mentioned above varied across the vegetation cover gradients, emphasizing the need for localized strategies to improve vegetation. These findings offer valuable insights into ecological protection and vegetation restoration in the Weihe River Basin. Plain Language Summary: Understanding how vegetation cover responds to climate change and human influence is vital for maintaining ecosystem health. This study focused on the Weihe River Basin, a region prone to ecological fragility, to explore how vegetation cover responds to human activity and climate change factors, considering basic topographical factors. Models that can identify trends, rank contributions, explore interactions between variables, and quantify the direct and indirect effects of variables were utilized. By analyzing various data and using different models, we found that vegetation coverage generally increased over this period. Factors such as topography and human activities greatly influenced vegetation cover change. Surprisingly, temperature fluctuations had a more substantial impact on vegetation cover than changes in precipitation. Moreover, the interaction between human activities, climate change, and topography can change the intensity and direction of the factor's effect on vegetation cover change. The effects varied across areas with different vegetation cover change conditions of the basin. These findings provide valuable insights for guiding ecological protection and vegetation restoration efforts in the Weihe River Basin. Key Points: Single factor's effect intensity and direction on vegetation cover change changed under the interaction with othersThe impact of extreme climatic conditions on the dynamics of vegetation coverage should not be overlookedThe intensity and direction of the impact of factors varied in diverse vegetation gradients [ABSTRACT FROM AUTHOR]

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Understanding the propagation characteristics and driving factors from meteorological drought to hydrological drought is essential for alleviating drought and for early warning systems regarding drought. This study focused on the Weihe River basin (WRB) and its two subregions (the Jinghe River (JRB) and the middle reaches of the Weihe River (MWRB)), utilizing the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) to characterize meteorological and hydrological drought, respectively. Based on Copula theory and conditional probability, a quantification model for the propagation time (PT) of meteorological–hydrological drought was constructed. The dynamic characteristics of PT on annual and seasonal scales were explored. Additionally, the influences of different seasonal meteorological factors and underlying surface factors on the dynamic changes in PT were analyzed. The main conclusions were as follows: (1) The PT of meteorological–hydrological drought was characterized by faster propagation during the hot months (June–September) and slower propagation during the cold months (December to March of the following year); (2) Under the same level of hydrological drought, as the level of meteorological drought increases, the PT of the drought shortens. The propagation thresholds of meteorological to hydrological drought in the WRB, the JRB, and the MWRB are −0.69, −0.81, and −0.78, respectively. (3) In the dynamic changes in PT, the WRB showed a non-significant decrease; however, both the JRB and the MWRB exhibited a significant increase in PT across different drought levels. (4) The influence of the water and heat status during spring, summer, and winter on PT was more pronounced, while in autumn, the impact of the basin's water storage and discharge status was more significant in the JRB and the MWRB. [ABSTRACT FROM AUTHOR]

The Weihe River Basin has a significant number of tributaries and a delicate ecological environment. Understanding the spatial and temporal evolution and determinants of landscape ecological risk in the Weihe River Basin (WRB) can improve the scientific protection and development of its watershed ecosystems. This study is based on land use statistics from the WRB for a 30-year period represented by 1990, 2000, 2010, and 2020. An initial model for the assessment of landscaping ecological hazards was created using the software that was also used to generate the landscape ecological risk index, such as ArcGIS 10.4 and Fragstats 4.2-64. Next, the spatial and temporal evolution of landscape ecological risk in the vicinity of the study area was characterized by the trajectory of the center of gravity migration and the spatial autocorrelation of GeoDa. Finally, Geodetector was used to analyze ecological risk drivers in the landscapes. According to the findings, the high-risk and relatively high-risk regions are steadily expanding, while the low-risk and relatively low-risk areas dominate the ecological risk landscape in the WRB. Within the Weihe River Basin, Xianyang and Xi'an are the areas to which the high-risk centers of gravity are migrating. Positive spatial correlations were found between the landscape ecological hazards in the study area, most prominently in the form of high-high and low-low aggregations. The primary drivers are the interplay between the GDP component, temperature, and elevation as a single factor. [ABSTRACT FROM AUTHOR]

[Objective] With the intensified influence of climate change and human activities, the climate and underlying surface conditions of the basins have changed. Accurately simulating the process of soil moisture change and analyzing its influencing factors are of great significance for regional water resource management and vegetation construction. [Methods] The Weihe River Basin in the Loess Plateau was taken as the research object. Based on the ABCD hydrological model, the EFAST method was used to analyze the parameter sensitivity of the model, and the constant parameter and time-varying parameter models were constructed. The runoff depth and soil water storage simulation accuracy of different parameter models were compared. The effects of climate change and vegetation restoration on soil water storage changes in the Weihe River Basin were discussed, and the dominant factors of soil water storage changes were clarified. [Results] The proportional parameter of soil water layer recharge groundwater c was the most sensitive, followed by the groundwater storage coefficient d, the upper limit parameter b of the sum of actual evapotranspiration and soil water storage, and the tendency parameter a of runoff that before the soil is completely saturated was the least sensitive. Compared with the ABCD constant parameter model, the time-varying parameter model increased the values of NSE, KGE, and R2 of the runoff depth simulation results by 19%, 10%, and 19%, respectively, and the NSE, KGE, and R2 of the verification period increased by 7%, 7%, and 9%, respectively. The time-varying parameter model significantly improved the runoff depth simulation results. The srtongest correlation between soil water storage in the Weihe river basin and ERA 5-Land 0-100 cm soil layer based on time-varying parameter model simulation, and the change process of the two agreed well. The degree of different influencing factors on the change of soil water storage in the Weihe River Basin from strong to weak was potential evapotranspiration>precipitation>NDVI. [Conclusion] The research results provide a scientific basis for water resources planning and management and vegetation construction in this area and they also provide references for soil water storage research in other similar areas.

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Fenghe River is one of the "Eight Waters of Chang'an", and in-depth research on the status quo of its water environment, influencing factors, and the relationship between surface water and groundwater transformation is the key to the ecological restoration of the river. Based on 62 groundwater samples and 17 surface water samples collected in Fenghe River Basin in July2022, the chemical characteristics and influencing factors of groundwater and surface water were analyzed by mathematical statistics, Piper diagram, Gibbs diagram, ion ratio method and hydrogen and oxygen isotopes, and the transformation relationship between groundwater and surface water was explored. The results show that (1) the groundwater in the study area is weakly alkaline, about 50%is extremely hard water, 25%is hard water, and the total dissolved solids (TDS) is large, the maximum value is as high as 1 916mg·L-1, and NO3- concentration is high; surface water is weakly alkaline, soft or slightly hard water, with less TDS and more organic matter; the cations of surface water and groundwater are mainly Ca2+, the anions are mainly HCO3-, and the surface water is basically HCO3-Ca water; the main chemical types of groundwater are HCO3-Ca, HCO3·SO4-Ca, HCO3-Ca·Mg and HCO3·SO4-Ca·Mg types accounted for 24.19%, 24.19%, 16.13%and 9.68%, respectively, and the spatial variation of water chemistry type is large. (2) The water chemical characteristics of the study area are mainly controlled by rock weathering, and evaporation concentration and atmospheric precipitation are also affected; in addition to the dissolution of rock salt, Na+ in water should also be affected by silicate weathering, and Ca2+, Mg2+ and HCO3-mainly come from the weathering and dissolution of carbonates such as calcite and dolomite; the alternating adsorption of cations in groundwater is common, which has a great impact on Ca2+and Na+concentrations; human activities have increased the concentrations of SO42-, NO3-and Cl-in some groundwaters, while surface water is less affected by human activities. (3) The surface water is mainly used to recharge groundwater in the alluvial fan top-middle in the study area, and the recharge ratio is 46.62%; the leading edge of the alluvial fan is mainly recharged by groundwater for surface water, and the recharge ratio is13.62%; the lower plain is mainly recharged by surface water to groundwater, with a recharge ratio of 38.39%. [ABSTRACT FROM AUTHOR]

Accurate assessment of runoff abundance and depletion encounter characteristics in the basin under runoff non-consistency conditions in multiple temporal dimensions (year-round, flood season and non-flood season) and multiple spatial dimensions (different hydrological stations) is of great significance to the regional flood and drought resistance, and the integrated development and utilization of water resources. We propose a method to analyze the runoff abundance and depletion encounters in a watershed considering the runoff non-consistency. Taking the mainstem of Weihe River as an example, we analyze the runoff evolution of the mainstem of Weihe River at Linjiacun, Xianyang and Huaxian stations from 1960 to 2020 through the sliding average method and Mann-Kendall method, and construct the Copula joint distribution function among different stations from the watershed scale in different time periods, and the abundance and depletion encounter characteristics of the Weihe River mainstem under runoff non-consistency conditions are analyzed. The results show that: (1) The runoff of the main stream of the Weihe River has obvious characteristics of wet and dry evolution, and there was a sudden change around 1978, and the runoff sequence after the sudden change showed a significant downward trend. (2) The synchronism of the run-off in the main stream of the Weihe River decreases with the increase of the distance between the stations. The synchronism of the run-off in the main stream of the Weihe River is the highest at Linjia Village - Xianyang Station, and the synchronism of the run-off in the main stream of the Weihe River is the lowest at Linjia Village - Huaxian Station; Among the different wet and dry encounter combinations, the most likely occurrence of two sites is the flat-flat combination, and the least likely occurrence is the wet and dry combination. (3) After the runoff variation, the synchronization of wet and dry encounters between different stations has changed significantly. The synchronization of wet and dry encounters between Linjiacun Station and Xianyang Station has decreased significantly, and the synchronization of wet and dry encounters between Xianyang Station and Huaxian Station has increased significantly. Before the variation, the synchronization between the stations in the non-flood season is the strongest, and the synchronization between the stations in the whole year is the weakest. After the variation, the synchronization between the stations in the non-flood season is the weakest, and the synchronization between the stations in the flood season is the strongest. The research results can provide a reference for the characterization of runoff abundance and depletion encounters in the main stream of the Weihe River. [ABSTRACT FROM AUTHOR]

Temporal and spatial changes in non-point source pollution, driven by significant alterations in land use due to increased human activity, have considerably affected the quality of groundwater, surface water, and soil environments in the region. This study examines the Weihe River basin in greater detail, an area heavily impacted by human activity. The study developed the River Section Potential Pollution Index (R-PPI) model using the Potential Non-Point Source Pollution Index (PNPI) model in order to investigate the dynamic changes in River Section Potential Pollution (R-PP) over a 31-year period and its associated risks, especially those related to land use and land cover change (LUCC). The predominant land uses in the Weihe River Basin are cropland, grassland, and forest, making up around 97% of the basin’s total area. The Weihe River Basin underwent a number of soil and water conservation initiatives between 1990 and 2020, which significantly decreased the potential pollution risk in the river segment. The research separated the R-PP risk values in the area into five different categories using a quantile classification technique. According to the data, there is a polarization of R-PP risk in the area, with downstream parts especially having an increased risk of pollution in river segments impacted by human activity. On the other hand, river segments in the middle and upper reaches of the basin showed a discernible decline in possible pollution risk throughout the study period. The Weihe River Basin’s rapid urbanization and land degradation are to blame for the current increase in R-PP risk. The substantial influence of LUCC on the dynamic variations in R-PP risk in the Weihe River Basin is highlighted by this study. Additionally, it offers crucial information for upcoming conservation initiatives and urban planning guidelines meant to enhance the area’s ecological well-being and environmental standards.

Automated water body (WB) extraction is one of the hot research topics in the field of remote sensing image processing. To address the challenges of over-extraction and incomplete extraction in complex water scenes, we propose an encoder–decoder architecture semantic segmentation network for high-precision extraction of WBs called EDWNet. We integrate the Cross-layer Feature Fusion (CFF) module to solve difficulties in segmentation of WB edges, utilizing the Global Attention Mechanism (GAM) module to reduce information diffusion, and combining with the Deep Attention Module (DAM) module to enhance the model’s global perception ability and refine WB features. Additionally, an auxiliary head is incorporated to optimize the model’s learning process. In addition, we analyze the feature importance of bands 2 to 7 in Landsat 8 OLI images, constructing a band combination (RGB 763) suitable for algorithm’s WB extraction. When we compare EDWNet with various other semantic segmentation networks, the results on the test dataset show that EDWNet has the highest accuracy. EDWNet is applied to accurately extract WBs in the Weihe River basin from 2013 to 2021, and we quantitatively analyzed the area changes of the WBs during this period and their causes. The results show that EDWNet is suitable for WB extraction in complex scenes and demonstrates great potential in long time-series and large-scale WB extraction.

Droughts in the Weihe River Basin are occurring more frequently and are becoming more intense. These events negatively affect industrial production, economic development, and ecosystems. Studying how vegetation changes in response to them is of practical significance. We report temporal and spatial trends in vegetation cover, use a copula function to analyze relationships between drought and vegetation cover, and assess the probability of vegetation loss in different drought scenarios. A vegetation index trends upwards from north to south in this basin; from 2001 to 2017, vegetation cover also trends upward in most areas, although it decreases in areas with high vegetation cover. An escalated susceptibility to drought has been observed in the southern and eastern sectors, where proximity to the riverbank correlates with heightened drought sensitivity, particularly in zones of intensified vegetation density. The probability of vegetation loss at the same vegetation loss preset point gradually increases with increased drought severity. These results will facilitate the formulation of countermeasures to prevent and combat the effects of drought on vegetation and land management.

In order to have a clearer understanding of the water supply and demand situation in the flood storage and detention area of the Weihe River Basin in Henan Province, this article used a combination model of least squares method and grey prediction model to predict the water demand and supply in the study area in 2025 and 2035, and conducted a supply-demand balance analysis. The results show that under the 50% and 75% guarantee rates in 2025, the proportion of agricultural water demand in the study area is 68% and 73%, respectively. In 2035, under the 50% and 75% guarantee rates, the proportion of agricultural water demand in the study area is 61% and 67%, respectively. The proportion of agricultural water demand in the total water demand is relatively larger. In 2025 and 2035, the flood storage and detention areas in the Weihe River Basin of Henan Province are in a water shortage state. It is recommended that the research area implements the strictest water resources management system, reasonably utilizes the water of South-to-North Water Diversion Project, strengthen the utilization of rainwater and flood resources, and gradually improves the imbalance between water supply and demand. [ABSTRACT FROM AUTHOR]

In order to reduce the influence of nonlinearity and nonstationarity of runoff series to the runoff prediction accuracy, a VMD-TCN model coupled with variational mode decomposition (VMD) and time convolution network (TCN) was proposed and applied to the monthly runoff prediction of Xianyang and Huaxian hydrological stations in the Weihe River Basin. The prediction results of VMD-TCN were compared with those of other models (TCN, EEMD-TCN, ARIMA) by using a variety of model performance evaluation indexes, and the prediction performance of VMD-TCN under different leading times was analyzed. The results show that VMD-TCN has smaller prediction error, higher prediction accuracy and better peak-valley fitting than other models. With the increase of leading time, the prediction performance of the model will gradually decrease but the prediction effect remains good. [ABSTRACT FROM AUTHOR]

In the era of big data, making full use of remote sensing images to automatically extract surface water bodies (WBs) in complex environments is extremely challenging. Due to the weak capability of existing algorithms in extracting small WBs and WB edge information from remote sensing images, we proposed a new method—Multiscale Fusion SegFormer (MF-SegFormer)—for WB extraction in the Weihe River Basin of China using Landsat 8 OLI images. The MF-SegFormer method adopts a cascading approach to fuse features output by the SegFormer encoder at multiple scales. A feature fusion (FF) module is proposed to enhance the extraction of WB edge information, while an Atrous Spatial Pyramid Pooling (ASPP) module is employed to enhance the extraction of small WBs. Furthermore, we analyzed the impact of four kinds of band combinations on WB extraction by the MF-SegFormer model, including true color composite images, false color images, true color images, and false color images enhanced by Gaussian stretch. We also compared our proposed method with several different approaches. The results suggested that false color composite images enhanced by Gaussian stretching are beneficial for extracting WBs, and the MF-SegFormer model achieves the highest accuracy across the study area with a precision of 77.6%, recall of 84.4%, F1-score of 80.9%, and mean intersection over union (mIoU) of 83.9%. In addition, we used the determination coefficient (R2) and root-mean-square error (RMSE) to evaluate the performance of river width extraction. Our extraction results in an overall R2 of 0.946 and an RMSE of 28.21 m for the mainstream width in the "Xi'an-Xianyang" section of the Weihe River. The proposed MF-SegFormer method used in this study outperformed other methods and was found to be more robust for WB extraction. [ABSTRACT FROM AUTHOR]

[Objective] The spatial distribution characteristics and coordination relationship between population and economy in Weihe River Basin were explored to provide theoretical basis for reducing regional gap and promoting regional coordinated development. [Methods] Based on population and GDP data of 88 counties and districts in the Weihe River Basin from 2000 to 2019, the imbalance index, geographical concentration, inconsistency index and other methods were comprehensively used to analyze the dynamic evolution characteristics of the relationship between population and economic spatial distribution in the Weihe River Basin from the overall and local levels. Based on the panel data, the influencing factors of population and economic space differentiation were analyzed. [Results] (1) The imbalance between population and economy in the Weihe River Basin had undergone a process of first decreasing and then expanding. The imbalance index had increased from 0.105 in 2000 to 0.107 in 2019, and regional development differences had always existed. (2) The spatial distribution of population and economy was characterized by dense in the southeast and sparse in the northwest, but the population factors mainly concentrated in the counties and districts along the main stream of the Weihe River, and the economic factors mainly concentrated in the municipal districts. (3) According to the inconsistency index, the relationship between population and economic spatial distribution in the Weihe River Basin could be divided into five types: economic polarization, economic advance, balanced development, population advance, and population polarization. (4) The spatial imbalance of population and economic distribution was not only affected by the market mechanism and the role of the government, but also obviously related to the level of urban development and regional development strategy of counties and districts, and the influence of explanatory variables in different periods was also different. [Conclusion] The situation of uncoordinated regional development in the Weihe River Basin is severe. It is still one of the problems to be solved in the future to promote the development of counties in the northwest of this basin, narrow the inter-provincial development gap, and promote the spatial balance of population and economy. [ABSTRACT FROM AUTHOR]

The complexity of precipitation sequence is a critical indicator to measure the complex nonlinear characteristics of the climate system, effectively presenting the dynamic characteristics time series which are of great significance to the adaptive management of basin water resources responding to global climate change. In this study, the precipitation data of 22 meteorological stations in and around the Weihe River basin was selected, covering the period of 1960-2016, and the nonlinear dynamic parameter sample entropy, the Mann-Kendall trend test and the cumulative anomaly method were employed to analyze the spatial distribution and evolutionary characteristics of monthly precipitation sequence complexity in the basin. In addition, the cross-sample entropy method was introduced to explore the asynchrony of the precipitation sequence in various sub-regions of the Weihe River basin in climate-change-impacted period. The results show that the complexity of monthly precipitation sequence has obvious spatial differences in the whole basin, specially reflecting on the complexity in the east greater than that in the west, the south superior to the north. Also, it is seen that precipitation complexity is gradually increasing along the main river, and that the upstream area is distinctly different from other sub-regions; the precipitation in the basin has a significant downward trend in recent years, while the changes of its sample entropy value is large, showing an obvious increasing on the whole which implies that the systemic dynamic structure of the precipitation is becoming more complex. It may bring great challenges to the regional watershed water resources management; the statistical results in different sub-regions demonstrate negative correlations between the sliding average value of precipitation and the corresponding sample entropy value, i.e. precipitation decreasing along with complexity increasing, and a good correspondence is found between the peak-to-valley values of precipitation and the sample entropy; the spatial asynchrony has been increased in the whole basin during the impact period of climate change, but the change is not significant. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change and anthropogenic interventions have obviously altered the eco-hydrological regimes. A quantitative evaluation and attribution of the eco-hydrological alterations are urgently required. In this study, we evaluated the various attributions of eco-hydrological regimes in the Weihe River Basin (WRB). Firstly, the trends and change-point analysis of hydrological elements were examined, and the natural streamflow was reproduced based on the variable infiltration capacity model. Then, the most ecologically relevant hydrological indicators (ERHIs) were selected and combined with the eco-deficit and eco-surplus indicators to assess the degree of eco-hydrological regime alterations. Finally, the relative contributions to eco-hydrological alterations were quantified using the ‘simulated–observed comparison’ method. The results showed that (1) the streamflow of the WRB exhibited significant decreasing trends (p < 0.01), and a significant change point (p < 0.01) of the streamflow series was identified in 1990. (2) Seven representative indicators of hydrological alteration were selected as ERHIs. (3) During the human-induced period (1991–2017), human activities were the dominant factors in the eco-hydrological alterations as well as the variations of the ERHI indexes and the eco-deficit and eco-surplus metrics. Overall, the proposed framework may improve the understanding of the driving forces of eco-hydrological regime alterations under a changing environment. HIGHLIGHTS The principal component analysis was used to remove redundancy and correlation among the indicators of hydrological alterations and determine the ecologically relevant hydrological indicators.; A combination of ERHIs and eco-metrics to assess the eco-hydrological regime alterations at different time scales is used.; The effects of climate change and anthropogenic activities on the eco-hydrological regime alterations were quantitatively distinguished.;

Frequent droughts may have negative influences on the ecosystem (i.e., terrestrial vegetation) under a warming climate condition. In this study, the linear regression method was first used to analyze trends in vegetation change (normalized difference vegetation index (NDVI)) and drought indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). The Pearson Correlation analysis was then used to quantify drought impacts on terrestrial vegetation in the Weihe River Basin (WRB); in particular, the response time of vegetation to multiple time scales of drought (RTVD) in the WRB was also investigated. The trend analysis results indicated that 89.77% of the area of the basin showed a significant increasing trend in NDVI from 2000 to 2019. There were also significant variations in NDVI during the year, with the highest rate in June (0.01) and the lowest rate in January (0.002). From 2000 to 2019, SPI and SPEI at different time scales in the WRB showed an overall increasing trend, which indicated that the drought was alleviated. The results of correlation analysis showed that the response time of vegetation to drought in the WRB from 2000 to 2019 was significantly spatially heterogeneous. For NDVI to SPEI, the response time of 12 months was widely distributed in the north; however, the response time of 24 months was mainly distributed in the middle basin. The response time of NDVI to SPI was short and was mainly concentrated at 3 and 6 months; in detail, the response time of 3 months was mainly distributed in the east, while a response time of 6 months was widely distributed in the west. In autumn and winter, the response time of NDVI to SPEI was longer (12 and 24 months), while the response time of NDVI to SPI was shorter (3 months). From the maximum correlation coefficient, the response of grassland to drought (SPEI and SPI) at different time scales (i.e., 6, 12, and 24 months) was higher than that of cultivated land, forestland, and artificial surface. The results may help improve our understanding of the impacts of climatic changes on vegetation cover. [ABSTRACT FROM AUTHOR]

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Study region: Weihe River Basin of China Study focus: In recent decades, changing environments destroyed the natural structure of streamflow, making accurate streamflow prediction challenging. This study develops a multi-regime Markov-switching Generalized Autoregressive Conditional Heteroskedasticity (MS-GARCH) model to predict daily streamflow time series with structural breaks (SB), named ARIMA (Autoregressive Integrated Moving Average)-MS-GARCH model. Consequently, the multi-regime ARIMA-MS-GARCH model is compared with other classical single-regime ARIMA-GARCH models to evaluate whether and to what extent it improves streamflow prediction accuracy. New hydrology insights for the region: There exist structural breaks in the daily streamflow time series, and the number of breakpoints at each station varies. The GARCH model ignores the description of volatility aggregation in the daily streamflow time series (α

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change is a significant force influencing catchment hydrological processes, such as baseflow, i.e., the contribution of delayed pathways to streamflow in drought periods and is associated with catchment drought propagation. The Weihe River Basin is a typical arid and semi-arid catchment on the Loess Plateau in northwest China. Baseflow plays a fundamental role in the provision of water and environmental functions at the catchment scale. However, the baseflow variability in the projected climate change is not well understood. In this study, forcing meteorological data were derived from two climate scenarios (RCP4.5 and RCP8.5) of three representative general circulation models (CSIRO-Mk3-6-0, MIROC5, and FGOALSg2) in CMIP5 and then were used as inputs in the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future streamflow. Finally, a well-revised baseflow separation method was implemented to estimate the baseflow to investigate long-term (historical (1960–2012) and future (2010–2054) periods) baseflow variability patterns. We found (1) that baseflow showed a decreasing trend in some simulations of future climatic conditions but not in all scenarios (p < 0.05), (2) that the contribution of baseflow to streamflow (i.e., baseflow index) amounted to approximately 45%, with a slightly increasing trend (p ≤ 0.001), and (3) an increased frequency of severe hydrological drought events in the future (2041–2053) due to baseflows much lower than current annual averages. This study benefits the scientific management of water resources in regional development and provides references for the semi-arid or water-limited catchments. [ABSTRACT FROM AUTHOR]

Current climate change has led to frequent drought events in the Weihe River Basin, and the risks and impacts of drought are becoming increasingly severe. In order to study meteorological drought and hydrological drought at different scales and the propagation of drought between them, in this study, meteorological and hydrological drought conditions were calculated for 3-, 6-, 9-, and 12-month timescales based on 56 years of monthly precipitation and monthly runoff data of the Weihe River Basin using the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI), respectively. We explore analyzing the differences between them and their relationship and establishing regression equations based on the relationship and the dynamic propagation time of meteorological and hydrological droughts at different timescales. The results demonstrate that 1) the frequencies of both meteorological and hydrological droughts have shown an increasing trend in the last 56 years; 2) the relationship between meteorological drought and hydrological drought varied over time; 3) according to dynamic change analysis, propagation time tends to be shorter on the 3-month timescale and longer on the 6-month, 9-month, and 12-month timescales; and 4) the accelerated propagation time between meteorological drought and hydrological drought may be related to the increase in precipitation and temperature. The findings not only provide scientific support for the formulation of drought prevention and disaster reduction strategies in this basin but also have important scientific and practical application value.

In the era of big data, making full use of remote sensing images to automatically extract surface water bodies (WBs) in complex environments is extremely challenging. Due to the weak capability of existing algorithms in extracting small WBs and WB edge information from remote sensing images, we proposed a new method—Multiscale Fusion SegFormer (MF-SegFormer)—for WB extraction in the Weihe River Basin of China using Landsat 8 OLI images. The MF-SegFormer method adopts a cascading approach to fuse features output by the SegFormer encoder at multiple scales. A feature fusion (FF) module is proposed to enhance the extraction of WB edge information, while an Atrous Spatial Pyramid Pooling (ASPP) module is employed to enhance the extraction of small WBs. Furthermore, we analyzed the impact of four kinds of band combinations on WB extraction by the MF-SegFormer model, including true color composite images, false color images, true color images, and false color images enhanced by Gaussian stretch. We also compared our proposed method with several different approaches. The results suggested that false color composite images enhanced by Gaussian stretching are beneficial for extracting WBs, and the MF-SegFormer model achieves the highest accuracy across the study area with a precision of 77.6%, recall of 84.4%, F1-score of 80.9%, and mean intersection over union (mIoU) of 83.9%. In addition, we used the determination coefficient (R2) and root-mean-square error (RMSE) to evaluate the performance of river width extraction. Our extraction results in an overall R2 of 0.946 and an RMSE of 28.21 m for the mainstream width in the “Xi’an-Xianyang” section of the Weihe River. The proposed MF-SegFormer method used in this study outperformed other methods and was found to be more robust for WB extraction.

The ecological watershed is a new concept and one of the critical means of evaluating ecological protection and high—quality development. Therefore, the study of ecological watershed assessment has practical significance. In this study, taking the Shaanxi section of Weihe River as the research area, from eight dimensions of water security, water resources, water environment, water ecology, water landscape, water culture, water management and water economy, the evaluation index system of ecological watershed in Shaanxi section of Weihe River Basin was preliminarily constructed, the current development level of ecological watershed in Weihe River Basin was assessed, and suggestions for the construction of ecological watershed in Weihe River Basin were put forward. The results show that the total ecological watershed score in the Shaanxi section of the Weihe River Basin is 75.6 points, which is at the middle level. Among them, the three dimensions of water security, water environment and water management are acceptable, the three dimensions of water ecology, water culture and water landscape are medium, the water economy dimension is qualified, and the water resources dimension is unqualified. Consequently, the Weihe River Basin needs to take the two dimensions of water resources and water economy as a breakthrough to facilitate the construction of ecological civilization and support the ecological protection and high—quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The Weihe River Basin (WRB), the largest tributary of the Yellow River Basin (YRB), is located in the northwest of China. As the "mother river" of the Guanzhong Plain, it plays an important role in the development of Guanzhong City Group. Based on pH, electric conductivity (EC), total dissolved solids (TDS), and major ionic concentrations of 227 samples collected from the main stream (MS), northern tributaries (NT), and southern tributaries (ST) of the WRB, we explored spatial differential characteristics of hydrochemistry and their controlling factors, solute sources, and water quality of surface water. The results revealed mildly alkaline pH and much higher TDS values than the global average with mean values of 7.9 and 1037.7 mg L−1, respectively. Except NO3−, the concentrations of major ions in the MS and NT were higher than those of the ST, with similar spatial distribution patterns of Ca2+, Na+, Mg2+, SO42−, and Cl−. Na+ and SO42− were the most dominant cation and anion in the MS and NT controlled by both rock weathering and evaporation-crystallization processes. Ca2+ and HCO3− were the most dominant cation and anion in the ST mainly controlled by rock weathering process. Evaporite dissolution contributed the most to dissolved solutes in the MS and NT, while carbonate weathering dominated dissolved solutes in the ST. These findings were confirmed by the results of correlation matrix, principal component analysis (PCA), stoichiometric plots, and different water types identified as Na-SO4·Cl in the MS and NT, and Ca-HCO3 in the ST. Atmospheric and anthropogenic inputs had a minor effect on the surface water chemistry. However, human activities could not be ignored in the ST accounting for 10.9% of the total dissolved solutes, mainly because of the fertilizer application. And the surface water of the ST was more suitable for irrigation and drinking purposes than that of the MS and NT. Knowledge of our findings could contribute new insights to the solute geochemistry and sustainable management of water resources in the lithologically distinct segments of the WRB and other similar areas. [ABSTRACT FROM AUTHOR]

[Objective] The frequency, intensity and spatio-temporal variation of drought events in the Weihe River Basin under climate change were analyzed and the occurrence and development of future regional droughts were predicted to provide references for drought prevention and water security in future. [Method] This study selected the historical recorded data and modeled data from CanESM2 global climate model provided by the CMIP5 statistical downscaling dataset NEX-GDDP. The quadrant transformation method was employed to calibrate these data, and SPEI and the run theory were used to analyze the spatio-temporal evolution characteristics of drought in historical period (1966-2005) and under two emission scenarios (RCP4.5 and RCP8.5) in future (2021-2060). Finally, the spatial and continuous variations of drought frequencies were discussed. [Result] SPEI in both periods showed a decreasing trend at annual scale. Spring droughts were significantly aggravated in the Weihe River Basin under RCP8.5 scenario. The occurrence frequencies of future droughts showed a trend of decreasing at ends and increasing in middle with reduction in light and extreme droughts and increase in medium and severe droughts. The frequencies of short-duration drought events would decrease in future, while the frequencies of medium-and long-duration drought events would increase at watershed scale. The frequencies of long duration drought events in the northern part and the headwater region of the basin would decrease significantly. Drought events would remain the intervals of 1-6 months in future, with certain differences in some areas. [Conclusion] Spring and winter would be the critical periods for preventing drought risks in the Weihe River Basin and the western part would be the key areas for drought risk prevention in future. Light and medium droughts would still be the most important types of droughts, and attention should be paid to the potential disaster risks caused by medium and severe droughts. In addition, measures for reducing adverse effects of long-lasting drought events are suggested. [ABSTRACT FROM AUTHOR]

A reliable system simulation combining socio-economic development with water environment and comprehensively reflect a watershed's dynamic features is crucial. In this study, a complex system dynamics model is constructed to evaluate dynamic changes of socio-economic development and ecological environment of Weihe River Basin (WHR). Development trends of the population, economy, land resources, water demand and supply, water environment and water pollution and management are obtained from 2005 to 2030 through scenarios analysis representing different regional development orientations, namely, population growth (S1), economic leading (S2), resources saving (S3), environment leading (S4), collaborative development (S5). Compared with other scenarios, the total population and GDP will, respectively, reach 3,716.55 × 104 person and 40,077.30 × 108 yuan, and the gap between demand and supply and the amount of water pollution will, respectively, narrow to 0.56 × 108 and 12.26 × 108 cubic meters in collaborative development scenario (S5). The results reveal the collaborative development scenario (S5) can achieve not only steady population and economy growth, as well as narrow down the gap between water supply and demand, but also optimize watershed environment management of the WHR. Thus, the system dynamics model used in our research provides a powerful tool for assisting decision-making on issues of coordinative socio-economic development, environmental health protection, water resources conservation, etc., in a river basin area. Highlights Discussing interrelations among socio-economy, resources and environment in watershed.; Evaluating the joint effects of socio-economic development and watershed environment management.; Water resource demand causes the water resource imbalance in the Weihe River Basin.; Strengthening environmental protection requires coordinative development.; Identifying optimal and practical strategy for coordinative development mode.;

Frequent droughts may have negative influences on the ecosystem (i.e., terrestrial vegetation) under a warming climate condition. In this study, the linear regression method was first used to analyze trends in vegetation change (normalized difference vegetation index (NDVI)) and drought indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). The Pearson Correlation analysis was then used to quantify drought impacts on terrestrial vegetation in the Weihe River Basin (WRB); in particular, the response time of vegetation to multiple time scales of drought (RTVD) in the WRB was also investigated. The trend analysis results indicated that 89.77% of the area of the basin showed a significant increasing trend in NDVI from 2000 to 2019. There were also significant variations in NDVI during the year, with the highest rate in June (0.01) and the lowest rate in January (0.002). From 2000 to 2019, SPI and SPEI at different time scales in the WRB showed an overall increasing trend, which indicated that the drought was alleviated. The results of correlation analysis showed that the response time of vegetation to drought in the WRB from 2000 to 2019 was significantly spatially heterogeneous. For NDVI to SPEI, the response time of 12 months was widely distributed in the north; however, the response time of 24 months was mainly distributed in the middle basin. The response time of NDVI to SPI was short and was mainly concentrated at 3 and 6 months; in detail, the response time of 3 months was mainly distributed in the east, while a response time of 6 months was widely distributed in the west. In autumn and winter, the response time of NDVI to SPEI was longer (12 and 24 months), while the response time of NDVI to SPI was shorter (3 months). From the maximum correlation coefficient, the response of grassland to drought (SPEI and SPI) at different time scales (i.e., 6, 12, and 24 months) was higher than that of cultivated land, forestland, and artificial surface. The results may help improve our understanding of the impacts of climatic changes on vegetation cover.

For many years, the Weihe River Basin (WRB) has struggled to achieve a balance between ecological protection and economic growth. Constructing an Ecological Security Pattern (ESP) is extremely important for ensuring ecological security (ES). This study employed a coupling of multi-objective programming (MOP) and the patch-generating land use simulation (PLUS) model to project land use change (LUCC) in 2040 across three scenarios. Leveraging circuit theory, we generated ecological corridors and identified key ecological nodes, enabling a comparative analysis of ESPs within the WRB. The main results showed that: (1) The Ecological Protection (EP) scenario showed the highest proportions of forestland, grassland, and water, indicating an optimal ecological environment. Conversely, the Economic Development (ED) scenario features the greatest proportion of construction land, particularly evident in the rapid urban expansion. The Natural Development (ND) scenario exhibits a more balanced change, aligning closely with historical trends. (2) The ecological source areas in the EP scenario is 13,856.70 km2, with the largest and most intact patch area. The ecological source patches that have been identified in the ED scenario exhibit fragmentation and dispersion, encompassing a total area of 8018.82 km2. The ecological source areas in the ND scenario is most similar to the actual situation in 2020, encompassing 8474.99 km2. (3) The EP scenario demonstrates minimal landscape fragmentation. The ED scenario presents a more intricate corridor pattern, hindering species and energy flow efficiency. The ND scenario is more similar to the actual distribution in 2020. Protecting and restoring key ecological nodes, and ensuring the integrity and connectivity of ecological sources are crucial for ESP optimization in various scenarios. Combining all results, we categorize the WRB's spatial pattern into "three zones, three belts, and one center" and offer strategic suggestions for ecological preservation, promoting sustainable local ecological and socioeconomic development. [Display omitted] • Simulated and predicted land use in the Weihe River Basin using a coupled MOP and PLUS model. • The proportion structure of land use types differs significantly under different scenarios. • The EP scenario identified new ecological sources in the northern Weihe River Basin. • The EP scenario showed a more concise ESP. • Based on the research results, the plan of "three zones, three belts, and one center" for the Weihe River Basin is proposed. [ABSTRACT FROM AUTHOR]

• Proposed a nonuniform phase space reconstruction method for runoff prediction. • Revealed which predictors are crucial for improving the accuracy of daily runoff. • Constructed new chaos models to improve the accuracy of daily runoff predictions. Phase space reconstruction is crucial for predicting chaotic hydrological time series. However, traditional multivariate phase space reconstruction methods, such as high-dimensional and low-dimensional phase space reconstruction (HDPSR and LDPSR) neglect variable interdependence, resulting in redundant information in the reconstructed phase space and affecting the model prediction accuracy. To address this limitation, this study proposes a new nonuniform phase space reconstruction (NUPSR) method that combines the minimum redundancy maximum relevance criterion and conditional entropy. Then, using HDPSR, LDPSR, NUPSR, particle swarm optimization (PSO), support vector regression (SVR), and bidirectional long- and short-term memory neural networks (BiLSTM), the models HDPSR-PSO-SVR, LDPSR-PSO-SVR, NUPSR-PSO-SVR, HDPSR-PSO-BiLSTM, LDPSR-PSO-BiLSTM, and NUPSR-PSO-BiLSTM are built to evaluate the performance of the NUPSR method. To demonstrate the effectiveness of the NUPSR method in multistep daily runoff prediction, the models PSO-NUPSR-BiLSTM, LDPSR-PSO-BiLSTM, and HDPSR-PSO-BiLSTM are also built. The multifactor daily runoff data from five hydrological stations in the Weihe River Basin are used to evaluate the prediction performance of all models. The results show that the state variables obtained by NUPSR are more independent and less redundant than those obtained by HDPSR and LDPSR, as evidenced by the embedded state variables and lower embedding dimension of NUPSR and the performance of the model based on NUPSR outperforms based on HDPSR and LDPSR. Particularly, the PSO-NUPSR-BiLSTM model exhibits a slower decrease in prediction accuracy compared to the other two models as the number of prediction steps increases. In summary, the NUPSR method effectively selects and reconstructs predictors, significantly improves the prediction accuracy of the coupled models, and has broad application prospects in multivariate prediction in fields such as hydrology. [ABSTRACT FROM AUTHOR]

In order to solve the problem of flood disasters in the flood storage and detention area of the Weihe River Basin in Henan Province, the theoretical and practical potentials of rainwater resource utilization in the study area were first calculated using the analysis method of different underlying surface types, and then the analytic hierarchy process was combined with the fuzzy comprehensive evaluation method. Based on the basic conditions of water resources, implementation feasibility, social economy and water consumption, an evaluation index system for the utilization potential of rainwater resources in the study area was constructed and evaluated. The results show that the theoretical and actual potentials of rainwater resources utilization in the study area are 3.963 billion and 3.880 billion m3 respectively; the utilization potential of rainwater resources is Class I (excellent), the rainwater resources are abundant and easy to use, but the implementation conditions And water efficiency still needs to be improved and improved [ABSTRACT FROM AUTHOR]

Promoting sustainable development of the river basin ecosystem is important for improving human ecological environment. Thus, prior knowledge of natural and social sciences on the integration of natural, economic, and social factors related to rivers should be assimilated to improve river basin governance. This study uses a social-ecological systems (SES) framework to diagnose key factors affecting the governance of the Weihe River Basin, ranging from the social, economic, and political context to related ecosystems, watershed resource systems, watershed management system, and watershed governance actors' five subsystems. Further, corresponding countermeasures are proposed for the problems found during our diagnosis. The results of this study show that applying an SES framework to the diagnosis and analysis of river basin governance integrates the research results of different disciplines and fields. Thus, this study is helpful in identifying and proposing the key impact variables related to river basin management to establish a comprehensive management counterplan. [ABSTRACT FROM AUTHOR]

Periphytic algae is a useful indicator of aquatic ecological conditions. We investigated the periphytic algae on natural substrate and the environmental variables at 44 sites on three river systems in the Weihe River Basin (WRB). A total of 84 species are identified, representing 37 genera. The most common genera were Navicula, Oscillatoria, Nitzschia, Scenedesmus, Cymbell, and Fragilaria. One-way analysis of variance (ANOVA) indicated significant differences among the three river systems in environmental variables (p < 0.05). Non-metric multidimensional scaling (NMDS) analyses also showed differences in periphytic algae communities in the three river systems (p < 0.05) and identified different dominant species in each river system. Canonical correspondence analysis (CCA) and Monte Carlo permutation tests revealed that nutrient concentration, WT, and altitude were the most important variables affecting the structure and distribution of periphytic algae communities. Chemical variables were the most accounted for environmental variables (12.5%), while physical variable and geographical factors (5.8% in total) play a relevant minor role. Our results demonstrate that Navicula pupula, Navicula radiosq, Nitzschia palea, and Nitzschia denticula, exhibiting wide ecological amplitude, are tolerant of high concentrations of nutrient pollution. Variation of periphytic algae communities in WRB is due to the combination of anthropogenic and natural factors including agricultural and domestic wastes water inputting, land use patterns, geology, climatic changes, and river hydrology. HIGHLIGHTS Structure and distribution of periphytic algae communities were investigated in the Weihe River Basin.; The gradient of organic pollution detected in environmental variables was the main gradient, and the periphytic algae responded to this gradient.; The types of substrates in river impact periphytic algae abundance, causing higher periphytic algae abundance in cobbles substrate.; The variation of periphytic algae communities is attributed to the combination of anthropogenic factors and natural factors.; The results support the periphytic algae as ecological indicators in the Weihe River Basin.;

Land use changes are always patchy and widespread within a region, making it a challenge to identify the point-scale pressure of reducing carbon emissions from land use/cover change （LUCC）. The carbon emission observation index （CEOI） was thus proposed to conduct the point-scale comparability analysis, which was based on the unique net C flux effects of conversions between two different land use types. Then, the spatial-temporal characteristics of land use changes and the resulting pressure of reducing carbon emissions were studied in the Weihe River Basin of China, which adopted the LUCC data from 2000 to 2020 and models of the Markov transition matrix （MTM）, compound carbon emission coefficients （CEC） of various types of land use changes, and the CEOI-based classification method on point-scale pressure of reducing carbon emissions. The results showed that： ① The net C flux was from 3.551 Tg C （2000-2010） to 7.031 Tg C （2010-2020）, and the pressure of reducing carbon emissions from LUCC had been continuously increasing, which was mainly driven by the significant increase in change-spots with the super-strong ability to reduce carbon emissions. ② Due to contributions from change spots with carbon uptake ability, the amount of carbon released to the atmosphere was eliminated by approximately 19.21% over the period 2000-2020 and approximately 37.4% during 2000-2010. ③ Change spots on various pressure levels for reducing carbon emissions were distributed unevenly in the basin, with their gravity points in the previous 10 years （2010-2020） far away from those during 2000-2010. Additionally, the gravity points of change-spots with a strong ability to reduce carbon emissions from conversions of grassland into forestland moved northeastward from Tianshui City to Pingliang City, whereas the gravity points of other change-spots with different abilities to reduce carbon emissions were mostly northwestward to the north-central region with higher elevations from the Middle and Lower Reaches of the Weihe River Basin with low elevations.

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The selection of suitable indicators is the key to the development of multi-metric bioassessment. Here, we examined how taxonomic and functional structures of macroinvertebrate communities responded to the environmental gradients in ten mountainous streams in the Weihe River and Hanjiang River basins, two subtropical biodiversity hotspots in central China. Our main objectives were: 1) to examine whether trait-based metrics performed better than taxonomic compositions in differentiating environmental gradients; 2) to test whether indicators (species and traits) were more efficient than entire communities in discriminating three site groups subjected to different levels of human disturbances. Our results showed that both taxonomic and functional trait compositions, including species- and trait-based indicators, were all sensitive to environmental disturbance. Particularly, the trait-based variables responded more sensitive to human disturbances. Indicator assemblages can be effective surrogates of entire communities in response to environmental changes. Traits- and indicators-based metrics should be considered as useful supplements in the existent bio-monitoring schemes in China. We argued that the combination of taxonomic and functional indicators should be implemented in bioassessment, as they reflect different aspects of environmental changes and anthropogenic disturbances.

Climate change is a significant force influencing catchment hydrological processes, such as baseflow, i.e., the contribution of delayed pathways to streamflow in drought periods and is associated with catchment drought propagation. The Weihe River Basin is a typical arid and semi-arid catchment on the Loess Plateau in northwest China. Baseflow plays a fundamental role in the provision of water and environmental functions at the catchment scale. However, the baseflow variability in the projected climate change is not well understood. In this study, forcing meteorological data were derived from two climate scenarios (RCP4.5 and RCP8.5) of three representative general circulation models (CSIRO-Mk3-6-0, MIROC5, and FGOALSg2) in CMIP5 and then were used as inputs in the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future streamflow. Finally, a well-revised baseflow separation method was implemented to estimate the baseflow to investigate long-term (historical (1960–2012) and future (2010–2054) periods) baseflow variability patterns. We found (1) that baseflow showed a decreasing trend in some simulations of future climatic conditions but not in all scenarios (p < 0.05), (2) that the contribution of baseflow to streamflow (i.e., baseflow index) amounted to approximately 45%, with a slightly increasing trend (p ≤ 0.001), and (3) an increased frequency of severe hydrological drought events in the future (2041–2053) due to baseflows much lower than current annual averages. This study benefits the scientific management of water resources in regional development and provides references for the semi-arid or water-limited catchments.

• The LSTM for water use forecasting was improved by considering water availability. • A hydrological model and the LSTM model are integrated based on water use activities. • The coupled model outperforms the original model in the runoff forecasting. • The coupled model allows for rolling forecasts of water use and runoff. Long short-term memory (LSTM) networks have demonstrated excellent capabilities in identifying nonlinear relationships between variables and have proven to be effective in water use forecast modeling. However, current LSTM water use forecasting models do not consider the influence of regional water resources, which limits their ability to make full use of hydrological data. To address this issue, a distributed hydrological model (WetSpa-WW) was integrated in this study with a deep learning model (LSTM) based on water use activities. The water resources results simulated by WetSpa-WW were considered as an additional training input in the LSTM for water use forecasting. The coupled WetSpa-LSTM model was tested on the upper-middle of the Weihe River Basin, and the simulations were compared with those obtained from an experiment that did not consider water resources factors. The results indicated that the WetSpa-LSTM model performed better than the original model in simulating the streamflow. During calibration, logarithmic form of Nash-Sutcliffe efficiency (NSE ln) increased from 0.33 to 0.54 and the relative error (RE) decreased from 28 % to 13 %. Moreover, we observed that water resources factors can improve the accuracy of agricultural water use forecasting (NSE increases by 0.10) more than that of non-agricultural water use forecasting (NSE increases by 0.04). Overall, this study demonstrates the value of considering regional water resources in water use forecasting, and provides a perspective for integrating a distributed hydrological model (WetSpa-WW) and a deep learning model (LSTM) based on water use activities. [ABSTRACT FROM AUTHOR]

Land use change is one of the key factors that directly dominate the hydrological process of the watershed. Human activities have changed land-use patterns, thereby indirectly posing an impact on surface infiltration, evapotranspiration, and soil water in the water cycle process. The water resources were also evolved for the water balance in the basin. This study aims to further explore the impact of land-use evolution on the spatiotemporal changes of blue and green water in the Weihe River Basin. A Cellular Automata-Markov (CA-Markov) model was selected to predict the land-use pattern in 2035 using land-use data in 1995 and 2015. Firstly, a standardized preprocessing was performed on the constraint data using a FUZZY module, including elevation, slope, highway, and railway. Secondly, the Markov module was superimposed onto the land use data to obtain the land transfer probability matrix from 1995 to 2015. Thirdly, the multi-criteria evaluation (MCE) module was used to make land-use maps suitability. The CA-Markov model was used to predict land-use structure in 2035. A variety of land-use change scenarios were set to quantitatively analyze the temporal and spatial responses of land-use change and blue-green water using the soil and water assessment tool (SWAT). The results showed that: 1) The CA-Markov model was effective in simulating the land-use pattern in 2015, where the Kappa coefficient was 0.89, suitable for the prediction. 2) During 1995-2035, the cropland was mainly transferred to building land and grassland, while the grassland was mainly transferred to woodland and cropland. Meanwhile, the cropland showed a decreasing trend, with the single attitude of -0.27%, and the building land had the largest growth rate, with the dynamic attitude of 3.75%.3) The model calibration showed that the evaluation indicators of five hydrological stations all met the standards of R²>0.6 and ENS>0.5, indicating that the SWAT model presented good applicability in each basin of the Weihe River Basin. 4) The blue water increased by 2.38mm/a, and green water decreased by 18.74mm/a from 1995 to 2035. By contrast, the blue water increased by 14.82mm/a, and the green water decreased by 15.23mm/a from 2015 to 2035. As such, the evapotranspiration was reduced in the basin, but the runoff was increased. 5) Returning cropland to woodlands and grasslands contributed to reducing the blue and green water, where the blue water volume decreased by 9.27mm/a, 11.37mm/a, while the green water volume decreased by 32.94, 21.13 mm/a, respectively, under the extreme land-use scenarios. The main reason was that the cropland increased the runoff and evapotranspiration in the basin. The amount of blue and green water decreased, after a large area of cropland was converted into woodland and grassland. Therefore, it is necessary to reasonably plan the cropland, woodland, and grassland for the control of soil erosion, thereby promoting the improvement of the ecological environment in the study area. These findings can be expected to provide a sound scientific reference for land-use planning and water resources management in the Weihe River Basin. [ABSTRACT FROM AUTHOR]