Search

With the expansion of China's automobile market and the increase in the proportion of electric vehicles, the influence of the automobile industry on water resources has been increasingly, and as a result, water resources will become an important factor restricting the development of the electric vehicle industry in China. Until now, there are still no in-depth studies on the influences of the water footprint of electric vehicles. The paper establishes a life cycle assessment model by which to analyze the reduction potential of the water footprint of various types of passenger vehicles in their operation. The paper also compares the water footprint of passenger vehicles under different power structures, revealing the potential influence of developing electric vehicles on the demand of water resources. The results show that at the base year (2019), the plug-in hybrid electric vehicles and battery electric vehicles consume more water than the gasoline-based internal combustion engine vehicles do, while water consumption of the hybrid electric vehicles and fuel cell vehicles is lower than that of the gasoline-based internal combustion engine vehicles; as for the year 2035, even after the proportion of renewable energy generation increases, the water withdrawal and consumption of the battery electric vehicles and plug-in hybrid electric vehicles will still be larger than those of the gasoline-based internal combustion engine vehicles. [ABSTRACT FROM AUTHOR]

Stable isotopes in natural water bodies serve as hydrologic tracers, with a history of extensive application in karst groundwater research. The present paper is a systematic review of previous research results, with the objective of sorting out and summarizing the stable isotopic characteristics of karst groundwater in southwest China, which is the most typical karst region worldwide. Comprehensive analysis reveals that the deuterium and oxygen isotope values of most karst groundwater are characterized temporally as 'enriched in the rainy season and depleted in the dry season', which is the opposite of the pattern of precipitation. While the spatial distribution feature is basically consistent with the spatial variation pattern of precipitation, which is characterized as 'depleted from the coast to the interior'. Additionally, the main applications of stable isotopes to karst groundwater are discussed, including karst groundwater recharge source and recharge elevation identification, research on karst groundwater in the hydrological cycle, the hydrological process of karst groundwater, and karst groundwater contamination tracking. Finally, we looked forward to future research on karst groundwater based on deuterium and oxygen isotopes. It is our hope that this review may provide insight into the study of karst groundwater. [ABSTRACT FROM AUTHOR]

Precipitation is the basic component of the Earth's water cycle. Obtaining high-resolution and high-precision precipitation data is of great significance. This paper establishes a precipitation retrieval model based on a random forest classification and regression model during the day and at night with FY-4B/AGRI Level1 data on China from July to August 2022. To evaluate the retrieval effect of the model, the GPM IMERG product is used as a reference, and the retrieval results are compared against those of the FY-4B/AGRI operational precipitation product. In addition, the retrieval results are analyzed according to different underlying surfaces. The results showed that compared with the FY-4B/AGRI operational precipitation product, the retrieval model can better identify precipitation and capture precipitation areas of light rain, moderate rain, heavy rain and torrential rain. Among them, the probability of detection (POD) of the day model increased from 0.328 to 0.680, and the equitable threat score (ETS) increased from 0.252 to 0.432. The POD of the night model increased from 0.337 to 0.639, and the ETS score increased from 0.239 to 0.369. Meanwhile, the precipitation estimation accuracy of the day model increased by 38.98% and that of the night model increased by 40.85%. Our results also showed that due to the surface uniformity of the ocean, the model can identify precipitation better on the ocean than on the land. Our findings also indicated that for the different underlying surfaces of the land, there is no significant difference in each evaluation index of the model. This is a strong argument for the universal applicability of the model. Notably, the results showed that, especially for more vegetated areas and areas covered by water, the model is capable of estimating precipitation. In conclusion, the precipitation retrieval model that is proposed herein can better determine precipitation regions and estimate precipitation intensities compared with the FY-4B/AGRI operational precipitation product. It can provide some reference value for future precipitation retrieval research on FY-4B/AGRI. [ABSTRACT FROM AUTHOR]

• A decision-making system of sponge facility allocation optimization is established; • The runoff coefficient grading of each sub-catchment area is analyzed; • The regression relationships between LID facilities and the control effects are built; • The layout of LID facilities is optimized and gray facilities are connected reasonably. In order to effectively cope with the destruction of natural hydrological cycle mechanism, frequent urban flood, serious water pollution and other problems, which are caused by the rapid urbanization process, the 'sponge city' concept has been widely used in China. This paper mainly focuses on how to rationally arrange the sponge grey and green facilities in built-up urban areas. With background analysis as the premise, model construction as the platform and swarm intelligence optimization as the method, the optimal proportion of sponge green facilities is determined. Furthermore, gray facilities are strengthened for the problem area, and the optimal allocation scenario of sponge facilities with the combination of gray and green is obtained through continuous circulation. The final results show that the optimal layout proportion of rain garden, sunken green space, permeable pavement and green roof are 3.88%, 7.95%, 2.01% and 0.99% respectively, which can meet the 80% runoff control rate and 40% pollution load control rate in the standard. Based on the simulation results of 50a rainfall, regulation and storage facilities are arranged near the severely overloaded node and the diameter of the overloaded pipes are increased. It can be proved that runoff and pollution can be effectively controlled and urban flood can be alleviated with grey facilities by model. The research results of this paper are expected to provide the overall idea and method of layout optimization of grey-green facilities for sponge city construction in built-up urban areas. [ABSTRACT FROM AUTHOR]

Climate change refers to a statistically significant change in the average state of the climate or a climate alteration that lasts for a long period of time. Runoff (R) is as a measure of the interaction between climate change and human activities and plays an important role in the hydrological cycle, as it is directly related to the development of agricultural water management. Therefore, it is a requirement to correctly simulate R and have the ability to separate the impacts due to climate change and human activities. In this paper, five single-type simulation models (Back Propagation Neural Network (BP), Non-Autoregressive (NAR), Radial Basis Function (RBF), Support Vector Machine (SVM) and TOPMODEL Hydrological Model (TOPMODEL)) were adopted to simulate the R to analyze the simulating quality by comparing the evaluation indexes like relative error (RE), relative mean squared error (RMSE) and Nash–Sutcliff Efficiency (NSE) with the combined hierarchical structure hydrological (CHSH) simulation model. In traditional studies, only the relative contribution of the impacts of human activities and climate change on R are considered; however, in this study, the relative contribution of each meteorological factor affecting R is included. To quantitatively analyze the impact of human activities and climate change on R, we used a CHSH simulation model to calculate runoff values for the Lancang River of China for a period of nine years (2005–2013). Our objective was to use this type of model to improve both the accuracy and stability of calculated values of R. For example, the RE, RMSE and NSE of simulated monthly R calculated with the CHSH model were 6.41%, 6.67 × 108 m3 and 0.94, respectively. These values substantiate the improved accuracy and stability of calculated values of R obtained with single-type simulation models (the SVM model, for instance, widely used in runoff simulations, and the RE, RMSE and NSE were 14.1%, 12.19 × 108 m3 and 0.87, respectively). The total contribution of human activities and climate change to R, respectively, accounted for 34% and 66% for the nine-year period based on the CHSH model. Furthermore, we adopted a vector autoregressive (VAR) model to analyze the impacts of the meteorological factors on R. The results from this analysis showed that R has a strong fluctuation response to the changes in precipitation (P) and potential water evaporation (Ep). The contribution rates of Ep, P and air temperature (Ta) to R were 15%, 14% and 2%, respectively. Based on the total climate change contribution, the corresponding contribution rates of Ep, Ta and P in the Lancang River of China were 32%, 30% and 5%, respectively. The values of R calculated with the CHSH model are more accurate and stable compared to values obtained with single-type simulation model. Further, they have the advantage of avoiding drawbacks associated when using a single-type simulation model. Moreover, moving away from the traditional method of separating the impact of meteorological factors on R, the vector autoregressive model proposed in this paper can describe the contribution of different meteorological factors on R in more detail and with precision. [ABSTRACT FROM AUTHOR]

Root-zone soil moisture (RZSM) plays a key role in the hydrologic cycle and regulates water–heat exchange. Although site observations can provide soil profile moisture measurements, they have a restricted representation. Satellites can determine soil moisture on a large scale, yet the depth of detection is limited. RZSM can be estimated on a large scale using the soil moisture analytical relationship (SMAR) and surface soil moisture (SSM). However, the applicability of the SMAR to different deep-root zones and covariate sources is unclear. This paper investigates the applicability of the SMAR in the Shandian River Basin, upstream of the Luan River in China, by combining site and regional soil moisture, soil properties, and meteorological data. In particular, we first compared the estimation results of the SMAR at different depths (10–20 cm; 10–50 cm) and using covariates from different sources (dataset, SMAR-P1; literature, SMAR-P2) at the site in order to generate SMAR calibration parameters. The parameters were then regionalized based on multiple linear regression by combining the SMAR-P1, SMAR-P2, and SMAR calibration parameters in the 10–50 cm root zone. Finally, the Shandian River RZSM was estimated using regional surface soil moisture and the aforementioned regionalized parameters. At the site scale, diffusion coefficient b obtained in the 10–20 cm root zone at the same depth as the surface layer exceeded the upper limit of the SMAR by one. This is not fit an environment within the site context, and thus the SMAR is not applicable at this particular depth. The opposite is observed for the 10–50 cm root zone. In addition, SMAR-P1 (RMSE = 0.02) outperformed SMAR-P2 (RMSE = 0.04) in the estimation of the RZSM at 10–50 cm. Parameter regionalization analysis revealed the failure of SMAR-P2 to pass the significance test (p > 0.05) for building a multivariate linear model, while SMAR-P1 successfully passed the significance test (p < 0.05) and finished the parameter regionalization process. The median RMSE and median R2adj of the regional RZSM results were determined as 0.12 and 0.3, respectively. The regional RZSM agrees with the spatial trend of the Shandian River. This study examines the suitability of the SMAR model in varying deep-root zones and with diverse covariate sources. The results provide a crucial basis for future utilization of the SMAR. [ABSTRACT FROM AUTHOR]

Precipitation is one of the crucial variables in the hydrological and ecological cycles. High-quality precipitation data are of great importance for climate change, water resource management, and agricultural research over complex terrains. Recently, satellite precipitation products have been produced based on different retrieval algorithms, mainly the top–down and bottom–up approaches. Fusing satellite precipitation products based on these two different approaches may combine their advantages and achieve a better data quality for describing precipitation. In this paper, an improved double instrumental variable (IMDIV) method is proposed for data quality enhancement by merging IMERG (integrated multi-satellite retrievals for global precipitation measurement), which is based on the top–down approach, and SM2RAIN (soil moisture to rain), which is based on the bottom–up approach. In detail, IMERG-Early (IMERG early run) and IMERG-Final (IMERG final run) are merging with SM2RAIN at a daily scale, respectively. Rain gauge station records from GHCNd (Global Historical Climatology Network Daily) are used to evaluate the original and fused precipitation products for the Chuanyu region, China, from 2007 to 2019. The results show that the proposed IMDIV method outperforms the original DIV method on precipitation fusion tasks. Moreover, the proposed IMDIV-EAS (fusing IMERG-Early and SM2RAIN) and IMDIV-FIS (fusing IMERG-Final and SM2RAIN) products both outperform the original precipitation products IMERG and SM2RAIN, with higher correlation coefficients (R) of 0.603 and 0.634; better RMSEs of 5.136 and 5.088 mm/day; and better biases of 0.514 and 0.509 mm/day. The results demonstrate the effectiveness of the proposed method and the high quality of the fused products, which could be useful for hydrology and climate studies. [ABSTRACT FROM AUTHOR]

Landslides are one of the most destructive geological disasters and have been caused many casualties and economic losses every year in the world. The reservoir area formed by the world's largest hydropower project, Three Gorges Hydropower project of China, has become a natural testing ground for landslide prediction in the hope of reducing losses. In this paper, a new algorithm with strong optimization ability, the water cycle algorithm (WCA), is combined with the extreme learning machine (ELM) to improve the prediction accuracy of step-wise landslide. The gray relational grade analysis method was adopted to determine the main influencing factors of the landslide's periodic displacement. Then, the determined factors were used as the input items of the proposed WCA-ELM model, and the corresponding periodic displacement was used as the model output item. Taking the Liujiabao landslide in the Three Gorges Reservoir area as a case history, the proposed model was verified through a comparison with the measurements. The results showed that the model has a faster convergence rate and higher prediction accuracy than the traditional back-propagation neural network model and ELM-model. The water cycle algorithm is suitable for optimizing the accuracy of the extreme learning machine model in landslide prediction. [ABSTRACT FROM AUTHOR]

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR. [ABSTRACT FROM AUTHOR]

Featured Application: The application provides a new tool for reducing the error in the simulated runoff of a hydro-logical model by integrating time series models with hydrological models. Improving the accuracy of runoff simulations is a significant focus of hydrological science for multiple purposes such as water resources management, flood and drought prediction, and water environment protection. However, the simulated runoff has limitations that cannot be eliminated. This paper proposes a method that integrates the hydrological and time series models to improve the reliability and accuracy of simulated runoffs. Specifically, the block-wise use of TOPMODEL (BTOP) is integrated with three time series models to improve the simulated runoff from a hydrological model of the Zhou River Basin, China. Unlike most previous research that has not addressed the influence of runoff patterns while correcting the runoff, this study manually adds the hydrologic cycle to the machine learning-based time series model. This also incorporates scenario-specific knowledge from the researcher's area of expertise into the prediction model. The results show that the improved Prophet model proposed in this study, that is, by adjusting its holiday function to a flow function, significantly improved the Nash–Sutcliffe efficiency (NSE) of the simulated runoff by 53.47% (highest) and 23.93% (average). The autoregressive integrated moving average (ARIMA) model and long short-term memory (LSTM) improved the runoff but performed less well than the improved Prophet model. This paper presents an effective method to improve the runoff simulation by integrating the hydrological and time series models. [ABSTRACT FROM AUTHOR]

The activities of coal mining often lead to the formation of underlying runoff areas and have great impacts on both the basin hydrological cycle and water resource management. In order to investigate the changes in the hydrological processes of the coal goaf catchment, this paper analyzes and explores the coal mining influences on the hydrological processes in a small watershed in the Yangquan Basin of China. To disentangle the mining process, a distributed hydrological model, which highlighted the integration of sub-hydrological processes, was developed and implemented in the study area. The calibration and validation results indicated that the developed model simulated streamflow well. This was indicated by the Nash–Sutcliffe model efficiency (NS) and the Coefficient of Correlation (r2) for monthly runoff. The model was first calibrated in the period of 1990–2004 and then validated in the period of 2005–2018. Different scenarios were simulated and cross-compared in order to study the mining effects; the rainfall and runoff of each hydrological station are positively correlated in 2009–2018, and the scenario of change in mining area is negatively correlated with runoff in 2009–2018. The contribution of the changing input variables (rainfall and coal mining area) to the runoff of the Yangquan Basin was analyzed qualitatively and quantitatively; the impact contribution rates of mining activities are 85.96% and 39.34% during the mining and recovery periods in Yangquan station, respectively. The hydrological simulations provided a better understanding of runoff changes in the Yangquan Basin. The analysis results indicate that the hydrologic response to the mining process in Yangquan Basin is changing, and it thus draws attention to other mining places over the world. Methods used in this study can be applied in other regions to orientate the policy-making process. [ABSTRACT FROM AUTHOR]

Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific. [ABSTRACT FROM AUTHOR]

Water is known to play a crucial role in the generation of many large igneous provinces (LIP) worldwide, but the amount and origin of the water in their sources is still under debate. To address this question, this paper presents in situ major-, trace-element, and Sr isotope data coupled with bulk-mineral O-HHe isotope analyses of amphibole in a suite of aillikites from the Tarim LIP (NW China). The cores of zoned macrocrysts and microcrysts display partially overlapping compositions ranging between edenite and pargasite (75-83 versus 75-80 Mg#), which suggest a common origin from an evolving magma. The rims (Mg# = 75-80) of both macrocrysts and microcrysts are very similar to their cores for many elements, except for higher Sr and Ba contents. All the amphibole zones show similar primitive mantle-normalized trace element patterns, suggesting that they crystallized at different stages during magmatic evolution. This interpretation is confirmed by the homogenous Sr isotope compositions (87Sr/86Sr(i) = 0.70298-0.70394) of these amphiboles, which overlap with those of magmatic apatites and perovskites in these aillikites. The hydrogen isotope compositions (-D = -120‰ to -140‰) of the amphiboles are significantly lower than average mantle values. Given the low water contents (<0.66 wt%) of these minerals, the low H iso signatures of the amphiboles might be caused by variable H2O loss during magma ascent. However, open-system Rayleigh fractionation modeling suggests that the hydrogen isotope compositions of these amphibole phenocrysts cannot be fully reproduced by crystallization following magmatic degassing. These low Î'D values require incorporation of recycled altered oceanic crust containing hydrous components in the plume source of these aillikites, which is consistent with the previously published moderately radiogenic He isotope ratios of olivine separates and bulk-rock Os and Pb isotope data for these same samples. We conclude that water in these magmas was derived from a plume source containing recycled water-bearing oceanic crust. [ABSTRACT FROM AUTHOR]

Arid and semiarid areas generally face problems of natural resource degradation. In this paper, two indicators are proposed to characterize the utilization of rainwater: rainwater resource utilization quantity (RRU, mm) and rainwater resource utilization rate (RRUR, dimensionless ratio). A spatiotemporal assessment model (rainwater utilization assessment [RUA] model) for the RRUR and its influencing factors is constructed. The RUA model is based on Soil and Water Assessment Tool and Geographically Temporal Weighted Regression. The Zuli River Basin, located on the Loess Plateau in China, was selected as the study basin. The results show that the annual averages of the RRU and RRUR are 164 mm and 0.44, respectively, in the study basin. The RRU ranged from 71.4 to 243.2 mm, and the RRUR ranged from 0.32 to 0.53 during the evaluation period. Eight explanatory variables were selected, of which the leaf area index (LAI) and rainfall had a significant positive effect on RRUR, but there was spatial and temporal variability in the effects. The forest rehabilitation and crop rotations that can increase the LAI can effectively increase the RRUR, which increased by 0.10 and 0.11, respectively, and the increase in RRU was at least 36.42 mm, with a water volume of 3.85 × 108 m3. The impact of grassland rehabilitation and parallel terracing on the RRUR was small. We found that there is an interval effect and a threshold effect on rainfall utilization in the basin. The interval effect causes the RRUR to fluctuate within a certain range for rainfall intervals of 300–400 or 400–500 mm (Zuli River Basin). Threshold effects can guide the determination of the potential for rainwater utilization in different areas to ensure that the RRUR can be effectively enhanced with management measures. Recommendations for Resource ManagersWe have constructed an assessment model of rainwater resource utilization (RRU) and influencing factors.We have proposed two evaluation indices based on water balance, namely, the RRU quantity and rainwater resource utilization rate (RRUR).The leaf area index of vegetation is the most important influence on rainwater utilization, and the more severe the drought is, the more effective the regulation of water cycle processes by vegetation.The interval effect causes uncertainty in the RRUR for a certain interval of rainfall, with the RRUR fluctuating within a defined range.The threshold effect can guide us in determining the potential for rainwater utilization, and areas where the current RRUR is below the threshold can take management measures to ensure that the RRUR can be effectively increased. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower 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 Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology 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.)

Studies on human activities and the natural water cycle as a coupled system are essential for effective water resource management in river basins. However, existing calculation methods based solely on the natural water cycle do not meet the accuracy requirements of natural society dualistic water cycle simulations. Therefore, it is necessary to establish a more scientific and reasonable calculation unit division method and river confluence relationship determination method. This paper presents a socio-hydrological unit with natural society dual characteristics based on both the hydrological characteristics and the social administrative characteristics of the river basin. According to the elevation of the river buffer zone, river confluence relationships among socio-hydrological units are determined, and upstream and downstream confluence of the human–water system is obtained. Finally, a case study of the Jing-Jin-Ji region in China, an area of intensive human activities, was performed. A reliability of 94.3% was reached using the proposed socio-hydrological unit division and river confluence calculation method, suggesting that the approach is highly applicable. Thus, the proposed method for generating socio-hydrological units and determining river confluence relationships can be applied to study the mutual influence and spatial distribution characteristics of natural society dualistic water cycles. The data requirement is minimal, and the approach can provide benefits in research on human water systems. [ABSTRACT FROM AUTHOR]

An accurate understanding of the relationship between reservoir construction and the dynamic change of groundwater level in downstream areas is of great significance for rational development and utilization of water resources. At present, the research on the interaction between surface water (SW) and groundwater (GW) mainly focuses on the interaction between river and GW. There are few studies on the impact of the reservoir construction on GW level in downstream loess irrigation area. Rainfall, evaporation and climate temperature have a great impact on W level, but the impact of reservoir construction on the GW level should not be ignored in the utilization of water resources. In this paper, a GW flow model under a natural boundary was established by numerical simulation. Taking Heihe Jinpen Reservoir in Heihe River watershed as the research object, the influence of the construction of a mountain reservoir on the dynamic change of GW level in the downstream loess region is studied. By comparing the GW level under the natural state without reservoir construction and the measured GW level after the reservoir was built, the variation of the GW depth in the loess area of the lower reaches in the Heihe River watershed is obtained. The results show that simulation accuracy of the interaction between SW and GW was reasonable; after the Heihe Jinpen Reservoir construction, the mean GW level decrease was about 6.05 m in the downstream loess irrigation area in Guanzhong Basin. It provides a method for the simulation and prediction of SW–GW conversion laws. This study is also of great significance to explore the change law of the water cycle and improve the utilization rate of water resources. [ABSTRACT FROM AUTHOR]

High spatial resolution (1 km or finer) precipitation data fields are crucial for understanding the Earth's water and energy cycles at the regional scale for applications. The spatial resolution of the Global Precipitation Measurement (GPM) mission (IMERG) satellite precipitation products is 0.1° (latitude) × 0.1° (longitude), which is too coarse for regional-scale analysis. This study combined the Geographically Weighted Regression (GWR) and the Multifractal Random Cascade (MFRC) model to downscale monthly GPM/IMERG precipitation products from 0.1° × 0.1° (approximately 11 km × 11 km) to 1 km in Hubei Province, China. This work's results indicate the following: (1) The original GPM product can accurately express the precipitation in the study area, which highly correlates with the site data from 2015 to 2017 (R2 = 0.79) and overall presents the phenomenon of overestimation. (2) The GWR model maintains the precipitation field's overall accuracy and smoothness, with even improvements in accuracy for specific months. In contrast, the MFRC model causes a slight decrease in the overall accuracy of the precipitation field but performs better in reducing the bias. (3) The GWR-MF combined with the GWR and MFRC model improves the observation accuracy of the downscaling results and reduces the bias value by introducing the MFRC to correct the deviation of GWR. The conclusion and analysis of this paper can provide a meaningful experience for 1 km high-resolution data to support related applications. [ABSTRACT FROM AUTHOR]

The transport of atmospheric moisture presents a crucial role in the global hydrological cycle. In this paper, we performed an empirical orthogonal function (EOF) investigation of integrated moisture transport (IVT) which was observed to be connected with the renowned regional climate phenomenon named El Nino–Southern Oscillation (ENSO) in China. Results explained that in the Eastern and Southern China Sea, and Southeastern China, IVT variances were high, and could change significantly yearly. However, in Northern China, variances were quite low, meaning that monthly IVT was more predictable. The spatial distribution of IVT anomalies was different with the seasons. Summer, in particular, exhibited significantly higher IVT values across the equatorial western Pacific, and there was also a transfer of moisture from the tropical Indian Ocean to the Northwestern and Southeastern China. The primary six modes of the EOFs together explained about 52.3%, which accounted for greater than half of the variation in the IVT anomalies. The main mode was related to ENSO and it explained approximately 16.4% variance in the Southern China Sea and central equatorial Pacific, while the second mode illustrated about 10.8% variance and was strongest in the East China Sea and entire Southeastern China. The cross-wavelet coherence indicated that the IVT and ENSO time-series were coherent, having a duration of about 2–8 years. This thus implied that increased IVT was linked with enhanced ENSO activities. This study could contribute to a better perception of how atmospheric circulation patterns could modify the general flow of the atmosphere to affect normal weather conditions in China. [ABSTRACT FROM AUTHOR]

Changing pathways of soil moisture loss, either directly from soil (evaporation) or indirectly through vegetation (transpiration), are an indicator of ecosystem and land hydrological cycle responses to the changing climate. Based on the ratio of transpiration to evaporation, this paper investigates soil moisture loss pathway changes across China using five reanalysis-type datasets for the past and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections for the future. The results show that across China, the ratio of vegetation transpiration to soil evaporation has generally increased across vegetated land areas, except in grasslands and croplands in north China. During 1981–2014, there was an increase by 51.4 percentage points (pps, p < 0.01) on average according to the reanalyses and by 42.7 pps according to 13 CMIP6 models. The CMIP6 projections suggest that the holistic increasing trend will continue into the twenty-first century at a rate of 40.8 pps for SSP585, 30.6 pps for SSP245, and −1.0 pps for SSP126 shared socioeconomic pathway scenarios for the period 2015–2100 relative to 1981–2014. Major contributions come from the increases in vegetation transpiration over the semiarid and subhumid grasslands, croplands, and forestlands under the influence of increasing temperatures and prolonged growing seasons (with twin peaks in May and October). The future increasing vegetation transpiration ratio in soil moisture loss implies the potential of regional greening across China under global warming and the risks of intensifying land surface dryness and altering the coupling between soil moisture and climate in regions with water-limited ecosystems. [ABSTRACT FROM AUTHOR]

Land use change greatly affects the runoff characteristics of the basin, which in turn affects the distribution of surface water and groundwater in the region. Quantitative analyses of the hydrological response of watershed runoff to land use change are conducive to the formulation of sustainable water resource strategies. In this paper, the impact of land use change on runoff characteristics in the Jing River Basin was evaluated using the SWAT model, the land use pattern of the Jing River Basin in 2040 was predicted using CA-Markov model, and five land use change scenarios were set up in combination with the trend of land use transfer, and the response relationship between land use change and runoff hydrological characteristics in the basin was studied. The results show that the land use changes reduce runoff and change the hydrological cycle process of the basin. The hydrological response of different land use types varies significantly, but only has a less impact on annual runoff. Farmland has a promoting effect on production flow; woodland and grassland are not conducive to the formation of surface runoff and will increase underground runoff and evapotranspiration in the basin. The increase in vegetation coverage after returning farmland to woodlands and grasslands has reduced surface runoff, increased the recharge of groundwater, and played a positive role in ecological restoration in the river basin. The research results are of great significance for understanding the hydrological consequences of land use change and the rational planning of land use patterns in river basins. [ABSTRACT FROM AUTHOR]

Hydrological models are a conceptual representation of a simplified hydrological cycle. The hydrological cycle is the water cycle that circulates water from the land surface to the atmosphere and back again to the land. With the use of Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS), an event-based model and a continous hydrological model were established in Zijinguan watershed of Daqinghe River basin. To study the loss methods provided by HEC-HMS and its appropriateness for model fitting, is the main objective of this paper. The watershed was delineated with HEC-GeoHMS in ArcGIS, and its properties were extracted from a Digital Elevation Model (DEM) of 30 m × 30 m. The HEC-HMS includes a soil conservation service curve number (SCS-CN) method and a soil moisture calculation (SMA) loss method, simulating the event and continuous runoff, respectively. SCS Unit hydrograph and Muskingum were used for flow routing. Specifically, eight rainfall events were selected for calibrating (6 events) and verifying (2 events) the event-based model. Similarly, for the continuous model the wet seasons of eight different years were used for calibration and verification. The calibrated parameters of the events model were used in the continuous model. The soil moisture and evapotranspiration data were decoded from the satellite data to set in the continuous model. The performance of SCS-CN and SMA models was compared. During the calibration period, the values of NSE, PEV and PEPF range from 0.605 to 0.744, 3.1 to 13.58%, and 11.104 to 27.72%, and during validation they are 0.527 to 0.634, 4.35% to 5.01%, and 13.66% to 27.88%, for SCS-CN model. For the SMA model, the values of NSE, PEV and PEPF during calibration range from 0.434 to 0.604, 2.879 to 34.326%, −4.831 to 57.48%, and during validation they are 0.094 to 0.624, −19.52% to −12.55%, and 40.213% to 50.15%. Overall, the performance of SCS-CN model is found more satisfactory than that of SMA model. [ABSTRACT FROM AUTHOR]

The landslide caused a huge disaster to the living environment and seriously threatened the lives and property safety of nearby residents. Assess or predict landslide-susceptible the landslide displacement through monitoring are great beneficial to guide landslide control and mitigate these hazards by taking appropriate preparatory measures. In this paper, a new water cycle algorithm optimization BP neural network (BPNN) dynamic prediction model (WCA-BPNN) was established to make up for the shortcoming of BPNN convergence speed. A typical step-wise landslide——Langshuwan Landslide happened in the Three Gorges Reservoir area of China is taken as a case, and the displacement monitoring data of 4 years was used for time series analysis and modeling. The long-term creep effect of the landslide and the short-term acceleration effect of the climate are considered in the model, and the accumulative displacement is divided into two kinds of trend displacement and periodic displacement. The key influencing factors of landslide periodic displacement were screened by gray relational grade analysis method, and then used as learning data. In addition to comparing the predicted value of the model with the measured value, it also compares the accuracy of the three models of BPNN, support vector machine, extreme learning machine under the training conditions of the same learning data set. The results show that the WAC-BPNN model has faster convergence speed and higher prediction accuracy than the traditional BPNN model, and it is also the most accurate of the four models. [ABSTRACT FROM AUTHOR]

This paper investigates the probability of integrating the Xinanjiang model, the most widely used watershed hydrological model in China, with the fully distributed groundwater model MODFLOW for processing a coupled flow simulation. Based on the flow simulation of the Xinanjiang and the SWAT model in the case study area, the correlation between the groundwater recharge and the total flow runoff is analyzed, which is then applied to compute the groundwater recharge in subbasins in the Xinanjiang model. By applying a loosely coupled modeling approach, the spatially distributed groundwater recharge is introduced into MODFLOW with the RCH package via the interface of the subbasins in the Xinanjiang model and the cells in MODFLOW; thus the integration of the two models is successfully realized. The application of the integrated model simulation in Zhangji, a groundwater-dominated area in the Huai River basin, China, demonstrates that the coupled Xinanjiang-MODFLOW simulation produces reasonable groundwater levels comparing to the observations. However the study also shows the need for further research in regarding to the improvement on Xinanjiang model in order to enable its direct integration with MODFLOW. Furthermore, the approach presented in this paper is limited to a unidirectional coupling of Xinanjiang and MODFLOW, which only accounts for groundwater level simulations, while the possible feedbacks from the surface water is neglected. More efforts are required to further facilitate the applicability and capability of the models integration. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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.)

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

Global warming has caused severe regional water security risks, and from the theory of the hydrological cycle, the daily extreme temperature could also bring an impact on the streamflow volume, which could be even more important than the average temperature. Therefore, based on the level of the maximum or minimum temperature warming scenarios, a variety of meteorological datasets were selected to assess the asymmetric effect of increased daily extreme temperature on the streamflow from a multi-scale perspective by using the Variable Infiltration Capacity (VIC) model. Model simulations indicate that the streamflow experiences more significant changes in response to the maximum temperature than in response to the minimum temperature, and the relationships of streamflow with both the maximum and minimum temperatures show an upwards parabolic response function, but the response function varies with the type of warming. Additionally, the seasonal and monthly duration curves results show that the increases in both the maximum and minimum temperatures demonstrate a similar response that leads the proportion of the flood period streamflow to be increased (Tmin : 0.16–0.53%/°C; Tmax : 0.11–0.51%/°C). When the minimum temperature increases, the higher the original temperature in the region, the greater the proportion of the flood period streamflow increases. However, when the maximum temperature increases, the opposite effect occurs. • This paper included a numerical analysis of the sensitivity of streamflow to daily extreme temperature increases. • This paper discusses in detail the regional asymmetric effect of daily extreme temperature increase to streamflow. • A relatively complete picture of the hydrological processes caused by daily extreme temperature rise is presented. [ABSTRACT FROM AUTHOR]

Any skillful prediction is of great benefit to North China, a region that is densely populated and greatly impacted by droughts. This paper reports potential predictability of North China summer drought 1 month ahead based on hindcasts for 1961–2005 from the "ENSEMBLES" project. Correlation scores of the standardized precipitation–evapotranspiration index and standardized precipitation index reach 0.49 and 0.39, respectively. The lower-level northwestern Pacific cyclonic circulation anomaly (NWPCCA) and East Asian upper-tropospheric temperature (UTT) cooling are the crucial circulations with regard to summer drought. Two sources of predictability are identified: 1) Pacific–Japan and Silk Road teleconnections forced by well-established eastern Pacific Ocean El Niño sea surface temperature anomalies (SSTA) in summer, when the two key circulations are both well predicted because of a good prediction of enhanced equatorial central Pacific (CP) rainfall and Indian rainfall deficit, and 2) the subtropical atmosphere–ocean coupling associated with CP El Niño developing, when the skill mainly arises from the reasonable prediction of NWPCCA. In observations, the NWPCCA persists from the preceding spring to summer through a wind–evaporation–SST feedback related to the Pacific meridional mode (PMM). In predictions, the persistence of the NWPCCA is mainly forced by the enhanced convection over the subtropical central North Pacific due to the persistence of the PMM-related meridional SSTA gradient over the CP. This predicted SSTA suppresses the equatorial Pacific rainfall, contributing to low prediction skill for the East Asian UTT cooling. This study demonstrates the importance of extratropical signals from the preceding season in North China summer drought prediction. [ABSTRACT FROM AUTHOR]

In karst terrains, fractures and conduits often occur in clusters, forming groundwater quick flow belts, which are the major passages of groundwater and solute transport. We propose a cost-effective method that utilizes precipitation and spring discharge data to identify groundwater quick flow belts by the multitaper method (MTM). In this paper, hydrological processes were regarded as the transformation of precipitation signals to spring discharge signals in a karst spring catchment. During the processes, karst aquifers played the role of signal filters. Only those signals with high energy could penetrate through aquifers and reflect in the spring discharge, while other weak signals were filtered out or altered by aquifers. Hence, MTM was applied to detect and reconstruct the signals that penetrate through aquifers. Subsequently, by analyzing the reconstructed signals of precipitation with those of spring discharge, we acquired the hydraulic response time and identified the quick flow belts. Finally, the methods were applied to the Niangziguan Spring (NS) catchment, China. Results showed that the hydraulic response time of the spring discharge to precipitation was 3 months at Pingding County; 4 months at Yuxian County, Yangquan City, Xiyang County, and Heshun County; and 27 months at Shouyang County and Zouquan County. These results suggested that Pingding County is located at a groundwater quick flow belt, which is a major passage of groundwater and contaminants, in the NS catchment. This is important since Pingding County is not only the key development area of karst groundwater but also the key conservation area for sustainable development of karst groundwater resources in NS catchment. [ABSTRACT FROM AUTHOR]

The rapid growth of coal production is supporting China's economic development. This paper discusses significant developments of coal preparation industry in China. The development direction of low-quality coal resources is also described, including the comprehensive utilization of resources and green coal preparation. Coal preparation may shift from the simple separation and production of highquality products to a comprehensive utilization of associated resources and lowquality coal. Green coal preparation is a new concept and involves a highly efficient coal preparation method based on the water cycle and comprehensive utilization of resources. This paper also describes a technology that transforms coal (mineral) resources (including natural, secondary, and artificial resources) into useful products (including raw materials and fuel) by separation, extraction, and processing for an eco-friendly approach to using secondary resources. [ABSTRACT FROM AUTHOR]

A lasting decrease in the near-surface wind speed (SWS) in China has been revealed, but a following short-term strengthening in the SWS was rarely noted. In this paper, the daily mean SWS observed datasets from 328 measurement stations in Eastern China during the period 1981–2011 were used to investigate the facts and causes of the observed short-term strengthening in winter SWS in recent decades. The major results are summarized as follows: the SWS showed a significant decrease in the last 30 years, but a short-term strengthening in SWS was observed during the winter since 2000 in Eastern China. The SWS in Eastern China showed a significant decrease of − 0.11 m s−1 decade−1 from 1981 to 1999, followed by a weak increase of 0.0008 m s−1 decade−1 from 2000 to 2011. The short-term strengthening in the SWS since 2000 was mainly induced by the changes of the pressure-gradient force (PGF), which could be attributed to the changes of the sea-level pressure (SLP) in the region (51°–69.75° N, 51.75°–111.75° E). Furthermore, the changes of the PGF during the two periods of 1981–1999 and 2000–2011 were consistent with those of the SLP in the region (51°–69.75° N, 51.75°–111.75° E). The correlation coefficient between PGF and SLP was 0.32 and 0.66 during the period 1981–1999 and 2000–2011, respectively. Therefore, the effects of the changes in SLP over the region (51°–69.75° N, 51.75°–111.75° E) on changes of SWS in the Eastern China should be significant. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Resources / Ziran Ziyuan Xuebao is the property of Journal of Natural Resources 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.)

Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM) resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin. [ABSTRACT FROM AUTHOR]

Forests play an important role in the global carbon cycle and have a potential impact on global climatic change. Monitoring forest biomass is of considerable importance in understanding the hydrological cycle. Because of the problem of dense forest cover, no reliable method with which to retrieve soil moisture in forest areas from the microwave emission signature has been established. All of these issues relate to the microwave emissivity and transmissivity characteristics of a forest. The microwave emission contribution received by a sensor above a forest canopy comes from both the soil surface and the vegetation layer. To analyze the relationship of forest biomass and forest emission and transmissivity, a high-order emission model, the matrix-doubling model, which consists of both soil and vegetation models, was developed and then validated for a young deciduous forest stand in a field experiment. To simulate the emissivity and transmissivity of a deciduous forest in the L and X bands using the matrix-doubling model, the parameters of components of deciduous trees when the leaf area index varies from 1 to 10 were generated by an L-system and a forest growth model. The emissivity and transmissivity of a forest and the relationships of these parameters to forest biomass are presented and analyzed in this paper. Emissivity in the L band when the leaf area index is less than 6 and at viewing angles less than 40°, and transmissivity in the L band are the most sensitive parameters in deciduous forest biomass estimation. [ABSTRACT FROM AUTHOR]

Accurate and reliable long-term forecasting plays an important role in water resources management and utilization. In this paper, a hybrid model called SVR-HUP is presented to predict long-term runoff and quantify the prediction uncertainty. The model is created based on three steps. First, appropriate predictors are selected according to the correlations between meteorological factors and runoff. Second, a support vector regression (SVR) model is structured and optimized based on the LibSVM toolbox and a genetic algorithm. Finally, using forecasted and observed runoff, a hydrologic uncertainty processor (HUP) based on a Bayesian framework is used to estimate the posterior probability distribution of the simulated values, and the associated uncertainty of prediction was quantitatively analyzed. Six precision evaluation indexes, including the correlation coefficient (CC), relative root mean square error (RRMSE), relative error (RE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE), and qualification rate (QR), are used to measure the prediction accuracy. As a case study, the proposed approach is applied in the Han River basin, South Central China. Three types of SVR models are established to forecast the monthly, flood season and annual runoff volumes. The results indicate that SVR yields satisfactory accuracy and reliability at all three scales. In addition, the results suggest that the HUP cannot only quantify the uncertainty of prediction based on a confidence interval but also provide a more accurate single value prediction than the initial SVR forecasting result. Thus, the SVR-HUP model provides an alternative method for long-term runoff forecasting. [ABSTRACT FROM AUTHOR]

Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced. [ABSTRACT FROM AUTHOR]

• Actual evapotranspiration and water stress during the dry seasons were studied. • The SSEBop model's performance can be improved by readjusting aerodynamic resistance. • All land-cover classes, especially farmland areas experienced severe water stress. Due to the simultaneous impacts of economic development and climate change, the Lijiang River Basin in China—the largest karst tourist attraction in the world—has experienced dramatic water shortages during the dry season. As actual evapotranspiration (ET a) plays a critical role in the water cycle, accurate estimation of ET a and water stress are important for sustainable water resources management. In this paper, we mapped the distribution of daily ET a using a modified Operational Simplified Surface Energy Balance (SSEBop) model in combination with Landsat 8 images and assessed water stress using the Crop Water Stress Index (CWSI) during the dry season in the Lijiang River Basin. In general, the daily ET a simulated by the SSEBop model with aerodynamic resistance value of 110 s m−1 was higher than that of satellite-based actual evapotranspiration products (i.e., MOD16A2 and Penman-Monteith-Leuning (PML)_V2 actual evapotranspiration products in this study). Aerodynamic resistance plays a critical role in the estimation of energy fluxes in the SSEBop model and should be readjusted and calibrated with available datasets to improve the model's performance in estimating actual evapotranspiration for particular regions. Readjusted values between 20 and 35 s m−1 of aerodynamic resistance produced reasonable agreement with satellite-based actual evapotranspiration products in the Lijiang River Basin. In addition, insufficient ground-level measurements of actual evapotranspiration might have increased the uncertainty of the SSEBop model's performance. The achievement of higher accuracy in the estimation of actual evapotranspiration and water availability will require establishing local flux towers, particularly in forested areas, to collect evapotranspiration, temperature and other in situ data. For different land-cover classes, forest areas exhibited the highest actual evapotranspiration, whereas farmland and built-up areas had the lowest actual evapotranspiration values compared to the other land-cover classes. All land-cover classes, especially farmland areas, experienced severe water stress. Inadequate precipitation as a result of climate change, combined with high actual evapotranspiration will result in less water being available for the Lijiang River Basin. Additional water is required to compensate for evapotranspiration and support plant growth in the Lijiang River Basin during the growing season. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage 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.)

Global climate change is considered one of the greatest environmental threats in the world. It is expected to significantly change the global hydrological cycle. The two main water cycle components, potential evapotranspiration (PET) and precipitation (P), are closely related to vegetation dynamics. In this study, the partial correlation analysis method was used to analyzed the relationship between Normalized Difference Vegetation Index (NDVI) and climate factors (PET and P) based on grid cells. PET was calculated by FAO-56 Penman-Monteith method. Moreover, we also investigated the NDVI and climate factors in different vegetation cover types. The results showed that grassland, forest and cropland in China were positively correlated with PET and P. The time scales of the maximum partial correlation coefficients between NDVI and PET of grassland vegetation were mostly longer than 5-6 months. These time scales were longer than the time scales related to P. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China, whereas the spatial distribution of related time scales was the opposite. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China. However, the spatial distribution of related time scales was the opposite. The correlations between NDVI and PET, P of cropland vegetation and the time scales related to PET had clear spatial heterogeneity. The time scale of the correlation between NDVI and P for cropland in the northern China was about 2 months. P had a strong influence on the growth of various types of vegetation in the study area, and grassland vegetation was affected by P over the shortest time scale. We compare and analyze the results of this study with other related studies. These results provide a reference for exploring the dynamic changes in different vegetation types and factors impacting them. [ABSTRACT FROM AUTHOR]

Soil infiltration and evaporation are the main factors affecting the water cycle in arid and semi-arid areas, and the sealing measures determine the soil water storage capacity by affecting the evaporation and infiltration process of grassland soil water, which is the key to the ecological environment restoration of arid and semi-arid grassland. This study taking the enclosure time of Hulunbuir grassland for 3 years, 7 years, 10 years and the grazing control grassland as the research objects by using small evaporation instrument and double-ring infiltration instrument.To study the effects of enclosure measures on soil water distribution, soil infiltration and evaporation, and to evaluate the applicability of the main soil evaporation and infiltration models in enclosed grassland. The results show that (1) the enclosure measures can effectively improve the soil water content. In the vertical direction, the soil water content shows a trend of increasing first and then decreasing. (2) The initial infiltration rate and stable infiltration rate of grassland at different enclosure time are significantly different (P<0.05), and the soil infiltration rate and evaporation rate were in the order of EN10 >EN7 >EN3 >CK. (3) Using three infiltration process models to simulate the grassland infiltration process at different enclosure times, the Horton model is able to better model the inflection points of the infiltration process, and the fit accuracy is higher than that of the Philip and Kostiakov models. (4) The cumulative evaporation process of grassland at different closure times was simulated by using Black, Ross, and Power function models.The simulation values calculated by the Rose model are the closest to the measured value, and the simulation accuracy is the highest.The comprehensive analysis shows that the hydrological characteristics of grassland soil change significantly in the early stage of enclosure phase, and the soil properties have reached a good state for 3 to 7 years.With the continuous increase of enclosure time, the change of soil hydrological characteristics is not obvious. The results are helpful for soil and water conservation and ecological environment management in arid and semiarid grassland. [ABSTRACT FROM AUTHOR]

Knowledge of the quantitative importance of the moisture transport pathways and mutual moisture exchange of the source regions of the Yangtze (SYZR) and Yellow (SYR) rivers' basins, the adjacent origins of China's two longest rivers, can provide insights into the regional atmospheric branch of the hydrological cycle over the source regions. The method with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and a Lagrangian moisture source diagnostic to identify the major moisture transport pathways quantifies their importance to two types of daily precipitation events—daily precipitation more than 10 mm (PM) events and daily precipitation less than 10 mm (PL) events—for the two rivers' regions during the summer (June–August, 1986–2015) and finds the characteristics of mutual moisture exchange. The results indicated that both the Bay of Bengal group pathway and the northwest China group pathway play significant roles in PM and PL events over the SYZR, contributing 41.87% and 39.12% to PM events and 41.33% and 33.16% to PL events, respectively. The SYR has five main moisture path groups; the Bay of Bengal group pathway, the northwest China group pathway, and the southeast China group pathway play significant roles in PM and PL events over the SYR, contributing 32.34%, 23.28%, and 34.36% to PM events and 34.84%, 36.18%, and 19.83% to PL events, respectively. The volume of moisture passing from the SYZR to the SYR is approximately 60 times that of the reverse, constituting about 6.9% of the total moisture released in SYR precipitation. It is worth noting that the moisture release was concentrated in the nearer west group pathway, and the main moisture uptake locations were beyond the source region of the two rivers (remote sources) in the PM events. The aggregate moisture release high-frequency moisture transport path groups are found in the southeastern parts of Zhiduo County and the southeast of Zaduo County. [ABSTRACT FROM AUTHOR]

In this paper a geomorphic-centered system was proposed for classifying the wetlands on the Qinghai-Tibet Plateau in western China, where the flora comprises primarily grasses. Although the geomorphic properties (e.g., elevation and morphology) of wetlands form the primary criteria of classification, this system also takes hydrological processes into implicit consideration. It represents an improvement over the hydrogeomorphic perspective as the relative importance of the two components (wetness and landform) of wetlands is clearly differentiated. This geomorphic-centered perspective yields insights into the hydrogeomorphic dynamics of plateau wetlands while indicates their vulnerability to change and degradation indirectly. According to this geomorphic-centered perspective, all plateau wetlands fall into one of the seven types of alpine, piedmont, valley, terrace, floodplain, lacustrine, and riverine in three elevational categories of upland, midland, and lowland. Upland (alpine and piedmont) wetlands with the steepest topography are the most sensitive to change whereas midland (floodplain, terrace and valley) wetlands are less vulnerable to degradation owing to a high water reserve except terrace wetlands. They have a dry surface caused by infrequent hydrological replenishment owing to their higher elevation than the channel. Low lying (lacustrine and riverine) wetlands are the most resilient. The geomorphic-centered perspective developed in this paper provides a framework for improving recognition and management of wetlands on the Plateau. Resilient wetlands can be grazed more intensively without the risk of degradation. Fragile and vulnerable wetlands require careful management to avoid degradation. [ABSTRACT FROM AUTHOR]

In this paper, we analyzed the high/low water levels of eight stations along the Pearl River estuary and the high/low tidal levels of Sanzao station, and streamflow series of Sanshui and Makou stations using wavelet transform technique and correlation analysis method. The behaviors of high/low water levels of the Pearl River estuary, possible impacts of hydrological processes of the upper Pearl River Delta and astronomical tidal fluctuations were investigated. The results indicate that: (1) the streamflow variability of Sanshui and Makou stations is characterized by 1-year period; 1-, 0.5- and 0.25-year periods can be detected in the high tidal level series of Sanzao station, which reflect the fluctuations of astronomical tidal levels. The low tidal level series of Sanzao station has two periodicity elements, i.e. 0.5- and 0.25-year periods; (2) different periodicity properties have been revealed: the periods of high water levels of the Pearl River estuary are characterized by 1-, 0.5- and 0.25-year periods; and 1-year period is the major period in the low water levels of the Pearl River estuary; (3) periodicity properties indicate that behaviors of low water levels are mainly influenced by hydrological processes of the upper Pearl River Delta. High water levels of the Pearl River estuary seem to be affected by both hydrological processes and fluctuations of astronomical tidal levels represented by tidal level changes of Sanzao station. Correlation analysis results further corroborate this conclusion; (4) slight differences can be observed in wavelet transform patterns and properties of relationships between high/low water levels and streamflow changes. This can be formulated by altered hydrodynamic and morphodynamic processes due to intensifying human activities such as construction of engineering infrastructures and land reclamation. [ABSTRACT FROM AUTHOR]

This paper presents an application of the TOPKAPI model, a physically based, fully distributed hydrologic model, to flood simulation at three unique and flood prone sites in China. The TOPKAPI model was applied with a grid size of 1 km×1 km and a time step varying from 1 to 24 h based on the basin conditions and data availability. Model calibration was chiefly based upon moderate variations of parameter values from the ones estimated on physical grounds. The three case studies demonstrated that the model performed well for flood simulation. The TOPKAPI model represents a comprehensive process-based model, which offers a wide range of capability for flood forecasting application, and has potential in prediction of ungauged basins. [ABSTRACT FROM AUTHOR]

The efficient control of water usage is one of the core goals of the strictest water resources management system in China. Therefore, the objective and reasonable evaluation of the effects of implementing this system is crucial. Based on the natural and social water cycle theories and the mechanism of the influence of agricultural, industrial, domestic and ecological water utilization, this paper proposes an evaluation index system through the qualitative and quantitative analysis of external and internal factors affecting the efficiency of water usage. Then, a matter-element model is developed on the basis of game theory weight to evaluate the effects of the implementation of efficiency control measures for regional water usage. By calculating the comprehensive correlation, this model can directly indicate the level of regional water use efficiency control. The model is applied to water usage in Jiangxi Province for the period 2011–2014. The results indicate a gradual improvement in the efficiency of water usage in this province. The matter-element extension evaluation model is simple and practical, and the evaluation results are in agreement with the facts. In summary, this method can provide a new theoretical basis for controlling the efficiency of regional water usage. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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.)

• Introduce an evaluation approach for the Ecological Service Value of Water (ESV-W). • Improve the assessment of Ecosystem Services Value (ESV) by introducing the Agricultural Price Index (API) into the Equivalence Factor (EF). • Improve the Water Allocation and Simulation Model (WAS) to simulate and quantify the 'natural-artificial' soil water cycle. • Analysis of the ESV and ESV-W in the Yangtze River Basin from 2005 to 2020. This paper introduces an evaluation approach for the Ecological Service Value of Water (ESV-W) by coupling the assessment of Ecosystem Services Value (ESV) with the Water Allocation and Simulation Model (WAS). The proposed method is applied to evaluate ESV and ESV-W in the Yangtze River Basin from 2005 to 2020. Firstly, an improved Equivalence Factor (EF) method is employed to estimate ESV by considering different land use types and service categories. Then, the enhanced WAS model is used to quantify and identify the role of the 'natural-artificial' soil water cycle in supporting the ecological service functions. Finally, by integrating the ESV evaluation system with the WAS model, the evaluation method for ESV-W is established. The results indicated that from 2005 to 2020, the total ESV increased from 4.0 to 5.6 trillion US Dollars, with forests being the primary contributor among land use types (about 52%), and regulating services are dominating among service categories (about 70%). The spatial distribution of the ESV showed a decreasing trend from southeast to northwest in the Yangtze River Basin, while the ESV-W exhibited high values concentrated along the main stream of the upper reaches of the Yangtze River and lower in the middle. The ESV-W of the 'natural' soil water cycle still dominates (over 96%), but the ESV-W of the 'artificial' soil water cycle has been rapidly increasing in recent years. In 2020, the ESV-W per unit water of precipitation, irrigation, and ecological water were 4.0 Dollars/ m 3 , 0.7 Dollars/ m 3 , and 32.4 Dollars/ m 3 , respectively. This study aims to provide references for the protection of water ecosystems and the sustainable utilization of water resources. It also serves as a reference for improving the evaluation system of ESV. [ABSTRACT FROM AUTHOR]

Snow plays a crucial role in the global water cycle, providing water to over 20% of the world's population and serving as a vital component for flora, fauna, and climate regulation. Changes in snow patterns due to global warming have far-reaching impacts on water management, agriculture, and other economic sectors such as winter tourism. Additionally, they have implications for environmental stability, prompting migration and cultural shifts in snow-dependent communities. Accurate information on snow and its variables is, thus, essential for both scientific understanding and societal planning. This review explores the potential of remote sensing in monitoring snow water equivalent (SWE) on a large scale, analyzing 164 selected publications from 2000 to 2023. Categorized by methodology and content, the analysis reveals a growing interest in the topic, with a concentration of research in North America and China. Methodologically, there is a shift from passive microwave (PMW) inversion algorithms to artificial intelligence (AI), particularly the Random Forest (RF) and neural network (NN) approaches. A majority of studies integrate PMW data with auxiliary information, focusing thematically on remote sensing and snow research, with limited incorporation into broader environmental contexts. Long-term studies (>30 years) suggest a general decrease in SWE in the Northern Hemisphere, though regional and seasonal variations exist. Finally, the review suggests potential future SWE research directions such as addressing PMW data issues, downsampling for detailed analyses, conducting interdisciplinary studies, and incorporating forecasting to enable more widespread applications. [ABSTRACT FROM AUTHOR]