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Objective A prerequisite for managing a catchment is to comprehensively understand the changes in its water quality. Using different methods, this paper comparatively analyzes the spatiotemporal variation in water quality of the Yangtze River, including its main streams and tributaries. Method The study is based on water quality data collected from 2008 to 2018 from 16 monitoring sections within the basin. Various methods, including the comprehensive water quality index (WQI), water pollution index (WPI), and comprehensive water quality identification index (Iwq), were used to assess water quality. Additionally, statistical methods including the Mann- Kendall trend test, cluster analysis, and discriminant analysis were utilized to analyze the spatiotemporal variation in water quality. Result In flooding and non-flooding seasons, the section proximal to the Leshan Minjiang Bridge had minimum dissolved oxygen (DO) concentration, which is 2.86 mg/L and 3.16 mg/L, respectively. Conversely, the Nanchang Chucha section had maximum concentration of chemical oxygen demand (CODMn) and ammonia nitrogen (NH3-N), which was 10.00 mg/L and 6.45 mg/L, and 2.23 mg/L and 4.48 mg/L, respectively. In the nonflooding season, 31.82% of water in the Nanchang Chucha section achieved Class IV grade or higher (evaluated by WPI), whereas this figure reduced to 19.70% (evaluated by WQI) for the Leshan Minjiang Bridge section. The Iwq method yielded the highest water quality, followed by WQI and WPI. All three methods indicated that water quality had improved in the Leshan Minjiang Bridge, Changsha Xingang, and Nanchang Chucha sections. Water quality varied spatially, with poor quality observed in the Leshan Minjiang Bridge, Changsha Xinkang, and Nanchang Chucha sections, and slightly poor quality was found in the Minjiang, Xiangjiang, and Ganjiang sections. Conclusion The evaluation of water quality using different methods within the Yangtze River basin yielded varied results, with the WQI method working best. [ABSTRACT FROM AUTHOR]

Objective The Haihe River plays a pivotal role in supporting various industrial and agricultural sectors in northern China. This paper presents a comprehensive evaluation of its environmental security and coordinated development to identify factors that influence environmental security most. Method The analysis was based on the pressure-state-response model, from which we proposed an improved comprehensive and systematic indicator system, including indicators that have been neglected, such as biodiversity and non-conventional water sources. A fuzzy comprehensive evaluation method was used to assess the water environmental security, and the entropy weight method and principal component analysis method were used to calculate the weights. A dynamic ternary-coupled coordination degree model was used to analyze the dynamic coupling and quantitatively calculate the coordination of the subsystem of pressure, state, and response. The key factors affecting water environmental security were identified through comprehensive consideration of the contribution rate and elasticity of the indicators. Result From 2009 to 2020, water nvironmental security in the basin had gradually improved, experiencing a transition from primary-coupling to advanced coupling. During this period, the coordinated development level decreased first followed by an increase. The deviation from the coordination had increased from 22.8 to 24.0, except in 2020 in which it fell to 17.3. The security of primary indicators had increased in all levels, among which the state indicator improved most significantly, despite still in relatively dangerous status. The secondary indicators had different influences on water environment security, among which the increase in population and urbanization had the most detrimental effect. Ammonia nitrogen and total phosphorus in the basin had been greatly reduced, but water quality in some parts of the basin were still category I-III, with potential to grow further. Increasing the use of non-conventional water sources can improve water environmental security. Conclusion In medium and long term, water environmental security in the basin can be improved by reducing the discharge of pollutants such as COD, BOD-5, and permanganate. Increasing use of desalinated seawater and rainwater collection, as well as storage capacity of green landscape can also improve water environmental security. It is crucial to maintaining and enhancing biodiversity and vegetation coverage to reduce water and nutrient losses to improve water security in the basin. [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.)

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.)

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.)

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.)

(Background and objective) Hydrological process is a complex phenomenon and affected by many biological and physical processes. Its modelling in water resource management and decision-making in watershed or catchment is often based on conceptual models where the complicated processes that directly or indirectly modulate water flow in different components are highly simplified. Such models are mathematically simple and have been widely used in both practical and scientific communities. Different conceptual hydrological models are available, but how they compare with each other for simulating hydrological processes in watersheds is not well studied. The purpose of this paper is to fill this gap.(Method) We compared 45 conceptual hydrological models for their application in the Lijiang River Basin. For each model, we simulated daily runoff in the basin from 2008 to 2016 using the same dataset, and compared and analyzed their performance in terms of model structure, calculated evapotranspiration and runoff, from which we identified main factors which affect model applicability and accuracy most.(Result) MODHYDROLOG was the model that worked best for simulating hydrological flow in the basin, followed by GR4J, IHACRES and Hillslope models. Model which was least accurate for simulating runoff did not work well for modelling real evapotranspiration and other runoff components neither. An accurate evapotranspiration calculation was not decisive for accurate runoff simulation, and dividing the runoff into different components was the key factor in applicability and accuracy of the models. We also found that the generalized semi-distributed model not only simplified the operation process of the model, but also affected the simulation accuracy. (Conclusion) Among the 45 conceptual models we compared, MODHYDROLOG, GR4J, IHACRES and Hillslope models worked best for simulating hydrological processes in the Lijiang River Basin and similar basins. [ABSTRACT FROM AUTHOR]

(Background and objective) Global warming and anthropogenic activities will change ecological functions of lakes, resulting in eutrophication and algal blooms, for example. Monitoring the change in aquatic vegetation and algae is important to improve lake management but difficult, especially at large scale. Remot sensing can plug this gap and in this paper, we study the feasibility of using it to acquire vegetation dynamics in lakes. (Method) The studied site is Ulansuhai lake in the upper reach of the Yellow River basin. Emergent and submerged vegetation as well as floating algae were calculated based on spectral feature analysis of the spectral data acquired from the Landsat8 imageries. A decision tree classification model was constructed to analyze the aquatic vegetation and algal blooms. A MNDSI spectral index was proposed to identify the aquatic vegetation and yellow moss algal blooms; a NDWI spectral water index was used to extract water bodies that were free of vegetation and algae. An improved enhanced vegetation index (AEVI) was used to extract the emergent vegetation; a modified macroalgal index (MFAI) was used to distinguish the submerged vegetation from the yellow moss algal blooms. The accuracy of the method was tested against ground-truth data. (Result) The spectral index combined with the decision tree classification model is effective to distinguish the aquatic vegetation from the yellow moss algal blooms. Using the Landsat8 imageries acquired from 1986 to 2018 revealed that the emergent vegetation taxa grew slowly, and the coverage area of the submerged vegetation showed periodic changes, decreasing 1986 to 2013 and increasing after 2013. The yellow moss algal bloom did not show identifiable trends, with their outbreaks occurring irregularly from 1986 to 2018. [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.)

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.)

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.)

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.)

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.)

(Objective) The China meteorological assimilation driving datasets is a database built up over the past decades specifically for application to the SWAT model (CMADS) in data-poor regions. This paper studies its application in upper reach of the Kaidu river in Northwestern China. (Method) We assessed two aspects. The first one is to assess the performance of the CMADS dataset in terms of estimating precipitation, maximum and minimum temperatures. The second is to compare the simulated results using the CMADS dataset and ground-true meteorological data.(Result) 1 The CMADS dataset is accurate for estimating temperature with its correlation with ground-true data being more than 0.9, but is less accurate for estimating daily precipitation, with its correlation with ground-truth data being 0.59. However, the correlation between calculated and measured monthly precipitations was high, reaching 0.84. 2 The simulated runoff using SWAT combined with CMADS dataset was in general more accurate than the results simulated using SWAT combined with the ground-truth data, indicating that, for regional hydrological modelling, CMADS dataset is more accurate than point-measured data. 3 Using the CMADS overestimated the baseflow and the lowest flow and underestimate the peak flow in model calibration stage, while underestimated the peak flow and overestimated baseflow slightly in model validation stage. In general, the runoff calculated using the CMADS was acceptable, except in a few extreme cases.(Conclusion) Testing the CMADS dataset against the upper reach of Kaidu river basin shows it is accurate and reliable. It can be used to simulate hydrological processes in regions short of measured meteorological data. [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.)