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Determination of the effective utilization coefficient of irrigation water based on geographically weighted regression

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Frontiers of Earth Science 2022年第2期16卷 401-410页

作者： Rui SHI Gaoxu WANG Xuan ZHANG Yi XU Yongxiang WU Wei WU College of Hydrology and water resource Hohai UniversityNanjing 210098China State Key Laboratory of Hydrology-water resources and hydraulic engineering Nanjing 210029China Hydrology and water resources department Nanjing Hydraulic Research InstituteNanjing 210029China

This study uses geographically weighted regression to determine the spatial distribution of the effective utilization coefficient of irrigation water in Zhejiang Province,China,owing to the influences of spatial attributes on the irrigation efficiency.The sample set of this study comprised 165 agricultural test sites.A multivariate linear regression model and a geographically weighted regression model were established using the effective utilization coefficient of agricultural irrigation water as the dependent variable in addition to a suite of independent variables,including the actual irrigation area,the percentage of farmland using water-saving irrigation,the type of irrigation area,the net water consumption per mu,the water intake method,the terrain slope,and the soil field capacity.Results revealed a positive spatial correlation and noticeable agglomeration features in the effective utilization coefficient of irrigation water in Zhejiang Province.The geographically weighted regression model performed better in terms of fit and prediction accuracy than the multivariate linear regression model.The obtained findings confirm the suitability of the geographically weighted regression model for determining the spatial distribution of the effective utilization coefficient of irrigation water in Zhejiang,and offer a new approach on a regional scale.

关键词： effective utilization coefficient of irrigation water spatial autocorrelation multivariate linear regression geographically weighted regression

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A comparative study of three different learning algorithms applied to ANFIS for predicting daily suspended sediment concentration

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International Journal of Sediment Research 2017年第3期32卷 340-350页

作者： Keivan Kaveh Minh Duc Bui Peter Rutschmann Department of Hydraulic and Water Resource Engineering/School of civil engineering Technische Universitt Mnchen (TUM)

The modeling and prediction of suspended sediment in a river are key elements in global water recourses and environment policy and management. In the present study, an Adaptive Neuro-Fuzzy Inference System model trained with the Levenberg-Marquardt learning algorithm is considered for time series modeling of suspended sediment concentration in a river. The model is trained and validated using daily river discharge and suspended sediment concentration data from the Schuylkill River in the United States. The results of the proposed method are evaluated and compared with similar networks trained with the common Hybrid and Back-Propagation algorithms, which are widely used in the literature for prediction of suspended sediment concentration. Obtained results demonstrate that models trained with the Hybrid and Levenberg-Marquardt algorithms are comparable in terms of prediction accuracy.However, the networks trained with the Levenberg-Marquardt algorithm perform better than those trained with the Hybrid approach.

关键词： Fuzzy Inference System Hybrid learning rule Levenberg-Marquardt algorithm Schuylkill river Suspended sediments

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Transferability and Scalability of Soil Total Carbon Prediction Models in Florida, USA

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Pedosphere 2018年第6期28卷 856-872页

作者： Sabine GRUNWALD Congrong YU Xiong XIONG department of Soil and water Sciences University of Florida State Key Laboratory of Hydrology-water resources and hydraulic engineering Hohai University College of Hydrology and water resource Hohai University Agricultural and Biological engineering department University of Florida

The applicability, transferability, and scalability of visible/near-infrared(VNIR)-derived soil total carbon(TC) models are still poorly understood. The objectives of this study were to: i) compare models of three multivariate statistical methods, partial least squares regression(PLSR), support vector machine(SVM), and random forest methods, to predict soil logarithm-transformed TC(logTC) using five fields(local scale) and a pooled(regional-scale) VNIR spectral dataset(a total of 560 TC spectral datasets), ii)assess the model transferability among fields, and iii) evaluate their up-and downscaling behaviors in Florida, USA. The transferability and up-and downscaling of the models were limited by the following factors: i) the spectral data domain, ii) soil attribute domain,iii) methods that describe the internal model structure of VNIR-TC relationships, and iv) environmental domain space of attributes that control soil carbon dynamics. All soil logTC models showed excellent performance based on all three methods with R^2> 0.86,bias 2.70%, and ratio of prediction error to interquartile range(RPIQ) > 4.54. The PLSR method performed substantially better than the SVM method to scale and transfer the TC models. This could be attributed to the tendency of SVM to overfit models, while the asset of the PLSR method was its robustness when the models were validated with independent datasets, transferred, and/or scaled. The upscaled soil TC models performed somewhat better in terms of model fit(R2), RPD, and RPIQ, whereas the downscaled models showed less bias and smaller RMSE based on PLSR. We found no universal trend indicating which of the four limiting factors mentioned above had the most impact that constrained the transferability and scalability of the models. Given that several factors can impinge on the empirically derived soil spectral prediction models, as demonstrated by this study, more focus on their applicability and scalabili

关键词： attribute domain multivariate statistical methods partial least squares regression random forest support vector machine soil carbon dynamics visible-near infrared spectroscopy

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Impact of temperature and precipitation lapse rate on hydrological modelling over Himalayan Gandak River Basin

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Journal of Mountain Science 2022年第12期19卷 3487-3502页

作者： Brijesh KUMAR Dipankar ROY Venkataraman LAKSHMI Department of Hydraulic and Water Resource Engineering Bule Hora UniversityBule Hora 144Ethiopia department of Civil engineering Madanapalle Institute of Technology&ScienceMadanapalle 517325India engineering Systemsand Environment Universityof VirginiaCharlottesvilleVA22904USA

The hydrology of Himalayan region is influenced by temperature lapse rate(TLAPS)and precipitation lapse rate(PLAPS).Therefore,hydrological modeling considering TLAPS and PLAPS is crucial to manage the water resources in these terrains.In this research,Himalayan Gandak River basin is considered as the study area where TLAPS and PLAPS vary significantly due to high altitude of Himalayas.To assess the impact of TLAPS and PLAPS on water balance components,Soil water Assessment Tool(SWAT)model was calibrated(2000-2007)and validated(2008-2014)on daily time step for three projects i.e.,Reference Project(RP),Snowmelt Project(SP)and distributed elevation band snowmelt project(SWAT-ETISM).The analysis discloses that SWAT-ETISM model(which has TLAPS and PLAPS parameters)outperforms the RP and the SP models in predicting streamflow with improved statistical indicators R2=0.88,NSE=0.84 and PBIAS=11.9.Furthermore,it was observed that SWAT-ETISM model comprehensively improved the streamflow statistics by improving the snow water equivalent and water balance components through the consideration of TLAPS and PLAPS values for the region.Hence,the proposed SWAT-ETISM model can be used for estimation of the water budget at the high-altitude and data scarce alpine Himalayan regions and worldwide,where PLAPS and TLAPS are substantial due to altitudinal variation.

关键词： Streamflow SWAT-ETISM Himalayan Regions water balance Temperature lapse rate Precipitation lapse rate

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Discrete element modeling of the effect of particle size distribution on the small strain stiffness of granular soils

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Particuology 2017年第3期15卷 21-29页

作者： Xiaoqiang Gu Lutong Lu Jiangu Qian department o.fGeotechnical engineering & Key Laboratory of Geotechnical and engineering of the Ministry of Education Tongji University Shanghai 200092 China State Key Laboratory of Hydrology-water resource and hydraulic engineering Nanjing Hydraulic Research Institute Nanjing 210098 China

Discrete element modeling was used to investigate the effect of particle size distribution on the small strain shear stiffness of granular soils and explore the fundamental mechanism controlling this small strain shear stiffness at the particle level. The results indicate that the mean particle size has a negligible effect on the small strain shear modulus. The observed increase of the shear modulus with increasing particle size is caused by a scale effect. It is suggested that the ratio of sample size to the mean particle size should be larger than 11.5 to avoid this possible scale effect. At the same confining pressure and void ratio, the small strain shear modulus decreases as the coefficient of uniformity of the soil increases. The Poisson＇s ratio decreases with decreasing void ratio and increasing confining pressure instead of being constant as is commonly assumed. Microscopic analyses indicate that the small strain shear stiffness and Poisson＇s ratio depend uniquely on the soil＇s coordination number.

关键词： Discrete element method Particle size distribution Small strain stiffness Poisson＇s ratio Coordination number

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Space-time evolution rules of acoustic emission location of unloaded coal sample at different loading rates

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International Journal of Mining Science and Technology 2012年第6期22卷 847-854页

作者： Ai Ting Zhang Ru Liu Jianfeng Ren Li State Key Laboratory of hydraulic and Mountain River engineering School of Water Resource and HydropowerSichuan University department of Mechanics and engineering Science Sichuan University

By using MTS815 rock mechanics test system,a series of acoustic emission(AE) location experiments were performed under unloading confining pressure,increasing the axial stress.The AE space-time evolution regularities and energy releasing characteristics during deformation and failure process of coal of different loading rates are compared,the influence mechanism of loading rates on the microscopic crack evolution were studied,combining the AE characteristics and the macroscopic failure modes of the specimens,and the precursory characteristics of coal failure were also analyzed quantitatively.The results indicate that as the loading rate is higher,the AE activity and the main fracture will begin earlier.The destruction of coal body is mainly the function of shear strain at lower loading rate and tension strain at higher rate,and will transform from brittleness to ductility at critical velocities.When the deformation of the coal is mainly plasticity,the amplitude of the AE ringing counting rate increases largely and the AE energy curves appear an obvious ''step'',which can be defined as the first failure precursor point.Statics of AE information shows that the strongest AE activity begins when the axial stress level was 92-98%,which can be defined as the other failure precursor point.As the loading rate is smaller,the coal more easily reaches the latter precursor point after the first one,so attention should be aroused to prevent dynamic disaster in coal mining when the AE activity reaches the first precursor point.

关键词： Coal Unloaded test Acoustic emission Space-time evolution Loading rate Precursory characteristics

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Effects of water,fertilizer,dissolved oxygen and temperature coupling on the photosynthesis,quality and yield of lettuce

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International Journal of Agricultural and Biological engineering 2023年第5期16卷 132-141页

作者： Zan Ouyang Juncang Tian College of water resources and Civil engineering Hunan Agricultural UniversityChangsha 410128China School of Civil and hydraulic engineering Ningxia UniversityYinchuan 750021China engineering and Technology Research Center of water-Saving Irrigation and water resource Regulation in Ningxia Ningxia UniversityYinchuan 750021China engineering Research Center for Efficient Utilization of water resources in Modern Agricultural in Arid Regions Ministry of EducationYinchuan 750021China

With the increased demand for vegetables of nutritional value,enhancing vegetable quality while pursuing high yield has become a goal of many investigators.In the present study,the effects of irrigation quota(A),fertilizer amount(B),dissolved oxygen(DO,C),and temperature in the climate chamber(D)applied in combination with the quality and yield of lettuce were investigated.Four-factor and three-level orthogonal designs were used to determine the single-factor trend,the sequence of primary and secondary influencing factors,and optimal regulatory measures concerning the lettuce.The order of the primary and secondary effects on the plant height,net photosynthesis rate(P_(n)),transpiration rate(E),vitamin C content(V_(c)),soluble protein content(S_(p)),dry matter accumulation(Dm),yield,irrigation water use efficiency(IWUE)of the lettuce plants followed the order A>B>D>C.In addition,the order of the primary and secondary effects on the intercellular carbon dioxide concentration(C_(i)),chlorophyll content,and nitrate content followed the order A>D>B>C.The optimum scheme for lettuce was A3B2C1D3(irrigation quota of 69 mm;fertilizer amount of 1.30 g/pot;DO of 6.5 mg/L;and temperature in the climate chamber of 20℃).Under the coordinated regulation of water,fertilizer,air,and temperature,the quality and yield of lettuce have been significantly improved.This study had important reference significance for the comprehensive regulation of water,fertilizer,air,and temperature facilities for vegetables.

关键词： Aerated irrigation Increased-temperature irrigation Growth Photosynthesis Dry matter accumulation Principal component analysis

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Evaluation and attribution of trends in compound dry-hot events for major river basins in China

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Science China Earth Sciences 2024年第1期67卷 79-91页

作者： Shaotang XIONG Tongtiegang ZHAO Chengchao GUO Yu TIAN Fang YANG Wenlong CHEN Xiaohong CHEN Key Laboratory of water Security Guarantee in Guangdong-Hong Kong-Marco Greater Bay Area of Ministry of water resources&Sun Yatsen University/Southern Marine Science and engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China China Institute of water resource and Hydropower Research Beijing 100038China Pearl River hydraulic Research Institute Guangzhou 510611China

Concurrent compound dry and hot events(CDHEs)amplified more damange on the ecosystems and human society than individual extremes.Under climate change,compound dry and hot events become more frequent on a global scale.This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation,change in temperature and change in the dependence between precipitation and temperature.The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model.A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins.It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China,except for the upper and middle reaches of the Yangtze River.In West China,precipitation changes drove the increase in CDHEs in 18 river basins(23%),particularly in parts of North Xinjiang,Qinghai and Gansu.On the other hand,dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins(16%)of China with other factors,including parts of South China,East China and Northwestern China.Furthermore,changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs.

关键词： Climate extreme Compound dry and hot extreme Precipitation Temperature Return period

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Evaluation of the parameters affecting the roughness coefficient of sewer pipes with rigid and loose boundary conditions via kernel based approaches

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International Journal of Sediment Research 2020年第2期35卷 171-179页

作者： Kiyoumars Roushangar Roghayeh Ghasempour Sanam Biukaghazadeh department of water resource engineering Faculty of Civil EngineeringUniversity of Tabriz Center of Excellence in Hydroinformatics University of Tabriz

One of the important issues in water transport and sewer systems is determining the flow resistance and roughness coefficient.An accurate estimation of the roughness coefficient is a substantial issue in the design and operation of hydraulic structures such as sewer pipes,the calculation of water depth and flow velocity,and the accurate characterization of energy losses.The current study,applies two kernel based approaches [Support Vector Machine(SVM) and Gaussian Process Regression(GPR)] to develop roughness coefficient models for sewer pipes.In the modeling process,two types of sewer bed conditions were considered:loose bed and rigid bed.In order to develop the models,different input combinations were considered under three scenarios(Scenario 1:based on hydraulic characteristics,Scenarios2 and 3:based on hydraulic and sediment characteristics with and without considering sediment concentration as input).The results proved the capability of the kernel based approaches in prediction of the roughness coefficient and it was found that for prediction of this parameter in sewer pipes Scenario 3 performed better than Scenarios 1 and 2.Also,the sensitivity analysis results showed that Dgr(Dimensionless particle number) for a rigid bed and wb/y(ratio of deposited bed width,wb,to flow depth,y) for a loose bed had the most significant impact on the modeling process.

关键词： Gaussian process regression Loose bed Rigid bed Roughness coefficient Sewer pipes Support vector machine

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Estimating the annual runoff frequency distribution based on climatic conditions and catchment characteristics:A case study across China

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International Soil and water Conservation Research 2023年第3期11卷 470-481页

作者： Ziwei Liu Hanbo Yang Taihua Wang Dawen Yang State Key Laboratory of Hydro-Science and engineering Department of Hydraulic EngineeringTsinghua UniversityBeijing100084China

Estimation of the annual runoff frequency distribution is an essential basis for water resource management.This study proposes a framework for estimating the annual runoff frequency distribution across252 catchments in China based on climatic conditions and catchment characteristics from 1956 to 2000.The Budyko land-specific parameter n,which intergrates influences other than the mean climate conditions,is firstly estimated based on easily ascertainable catchment characteristics without the requirementsof having long-term runoff observations.Second,the annual runoff statistical parameters,namely,the mean value and standard deviation(STD),are derived based on the Budyko rainfall-runoffmodel with the central moment method.Finally,the annual runoff on any recurrence interval is obtainedby the Pearson-Ill frequency function.Results show that the parameter n can be estimated fromthe catchment average slope,longitude,and climatic seasonality index.The estimated statistical parametersof annual runoff have acceptable agreement with observed values(mean value:R^(2)-0.94,STD:R^(2)-0.91,and both relative errors<10%).In addition,estimated annual runoff at each catchment fortypical wet and dry years(25%and 75%ranked percentiles)coincides well with observed values,with R^(2) of 0.92-0.93 and relative erors less than 10%.This result indicates the robustness of this framework forestimating the annual runoff frequency distribution,which provides a simple and effective tool forungauged orpoorlygauged catchments.

关键词： runoff distribution climatic

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