scholarly journals Application of the Regression-Augmented Regionalization Approach for BTOP Model in Ungauged Basins

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2294
Author(s):  
Ying Zhu ◽  
Lingxue Liu ◽  
Fangling Qin ◽  
Li Zhou ◽  
Xing Zhang ◽  
...  
Keyword(s):  
River Discharge ◽  
Regression Equation ◽  
Spatial Distance ◽  
Spatial Proximity ◽  
Future Research ◽  
Model Parameters ◽  
Regression Equations ◽  
Ungauged Basins ◽  
Discharge Simulation ◽  
Watershed Characteristic

Ten years after the Predictions in Ungauged Basins (PUB) initiative was put forward, known as the post-PUB era (2013 onwards), reducing uncertainty in hydrological prediction in ungauged basins still receives considerable attention. This integration or optimization of the traditional regionalization approaches is an effective way to improve the river discharge simulation in the ungauged basins. In the Jialing River, southwest of China, the regression equations of hydrological model parameters and watershed characteristic factors were firstly established, based on the block-wise use of TOPMODEL (BTOP). This paper explored the application of twelve regionalization approaches that were combined with the spatial proximity, physical similarity, integration similarity, and regression-augmented approach in five ungauged target basins. The results showed that the spatial proximity approach performs best in the river discharge simulation of the studied basins, while the regression-augmented regionalization approach is satisfactory as well, indicating a good potential for the application in ungauged basins. However, for the regression-augmented approach, the number of watershed characteristic factors considered in the regression equation impacts the simulated effect, implying that the determination of optimal watershed characteristic factors set by the model parameter regression equation is a crux for the regression-augmented approach, and the regression strength may also be an influencing factor. These findings provide meaningful information to establish a parametric transfer equation, as well as references for the application in data-sparse regions for the BTOP model. Future research should address the classification of the donor basins under the spatial distance between the reference basin and the target basin, and build regression equations of model parameters adopted to regression-augmented regionalization in each classification group, to further explore this approach’s potential.

scholarly journals Estimation of Monthly River Discharge from Danish Catchments

2003 ◽  
Vol 34 (4) ◽  
pp. 295-320 ◽  
Author(s):  
Dirk-I. Müller-Wohlfeil ◽  
Chong-Yu Xu ◽  
Hans Legard Iversen
Keyword(s):  
Water Balance ◽  
River Discharge ◽  
Nutrient Loading ◽  
Potential Evapotranspiration ◽  
Balance Model ◽  
Model Parameters ◽  
Calibration Data ◽  
Regression Equations ◽  
Explanatory Variables ◽  
Data Subset

To simulate the nutrient loading of Danish coastal waters, river discharge from unmonitored areas must be assessed. In an attempt to identify the most suitable method, for this purpose eight different versions of the three-parameter monthly water balance model “MWB-3” were tested on data from various Danish catchments for the period 1989-97. The model with the highest R2 and the lowest correlation between the model parameters was chosen for subsequent establishment of regression equations between the model parameters and catchment and climate characteristics. The most important explanatory variables of the regressions are soil properties, potential evapotranspiration, groundwater table depth, percentage of wetland area and catchment slope. Mean R2 was 0.82 for the calibration data subset (62 catchments) and 0.79 for the test data subset (22 catchments). Sensitivity tests indicate that the selected model version is more robust for application in catchments dominated by loamy soils than in catchments dominated by sandy soils. Though the MWB-3 model provides a good basis for determining the water balance of Danish catchments at the regional and national levels, modifications and extensions need to be considered for future studies.

scholarly journals Regionalisation of the parameters of the rainfall–runoff model PQRUT

2016 ◽  
Vol 47 (4) ◽  
pp. 748-766 ◽  
Author(s):  
Valeriya Filipova ◽  
Deborah Lawrence ◽  
Harald Klempe
Keyword(s):  
Weighted Regression ◽  
Spatial Proximity ◽  
Model Parameters ◽  
Regression Equations ◽  
Design Flood ◽  
Discharge Data ◽  
Peak Flows ◽  
Parsimonious Model ◽  
Rainfall Runoff Model ◽  
Event Based

This paper presents the regionalisation of the three parameter event-based PQRUT model, which is used for design flood analyses. The PQRUT model is used for the analysis of peak flows for which a sub-daily temporal resolution is required. The availability of high-resolution discharge data and disaggregated precipitation data have made it possible to re-evaluate the regional regression equations currently in use. We also assess whether the model parameters show spatial dependency. Event-based calibration was performed for the 45 highest flood events for each of 55 selected catchments across Norway, representing peak flows generated predominantly by rainfall. Due to the geographical heterogeneity of most areas in Norway, a statistically significant homogeneous region was only identified for catchments in southeastern Norway. Multiple linear regression and weighted regression were, therefore, used to develop a single set of equations, applicable to the entire country. The results for the weighted regression indicate a decrease in the median Kling–Gupta efficiency from 0.64 to 0.51 for calibration and regionalisation, respectively. The results also suggest that regression methods may perform better than methods based on spatial proximity in regions with varying topography when a parsimonious model is used.

scholarly journals Using machine learning methods for supporting GR2M model in runoff estimation in an ungauged basin

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pakorn Ditthakit ◽  
Sirimon Pinthong ◽  
Nureehan Salaeh ◽  
Fadilah Binnui ◽  
Laksanara Khwanchum ◽  
...  
Keyword(s):  
Machine Learning ◽  
Resource Planning ◽  
Performance Criteria ◽  
Spatial Proximity ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Hydrological Data ◽  
Taylor Diagram ◽  
Physical Attributes ◽  
Monthly Runoff

AbstractEstimating monthly runoff variation, especially in ungauged basins, is inevitable for water resource planning and management. The present study aimed to evaluate the regionalization methods for determining regional parameters of the rainfall-runoff model (i.e., GR2M model). Two regionalization methods (i.e., regression-based methods and distance-based methods) were investigated in this study. Three regression-based methods were selected including Multiple Linear Regression (MLR), Random Forest (RF), and M5 Model Tree (M5), and two distance-based methods included Spatial Proximity Approach and Physical Similarity Approach (PSA). Hydrological data and the basin's physical attributes were analyzed from 37 runoff stations in Thailand's southern basin. The results showed that using hydrological data for estimating the GR2M model parameters is better than using the basin's physical attributes. RF had the most accuracy in estimating regional GR2M model’s parameters by giving the lowest error, followed by M5, MLR, SPA, and PSA. Such regional parameters were then applied in estimating monthly runoff using the GR2M model. Then, their performance was evaluated using three performance criteria, i.e., Nash–Sutcliffe Efficiency (NSE), Correlation Coefficient (r), and Overall Index (OI). The regionalized monthly runoff with RF performed the best, followed by SPA, M5, MLR, and PSA. The Taylor diagram was also used to graphically evaluate the obtained results, which indicated that RF provided the products closest to GR2M's results, followed by SPA, M5, PSA, and MLR. Our finding revealed the applicability of machine learning for estimating monthly runoff in the ungauged basins. However, the SPA would be recommended in areas where lacking the basin's physical attributes and hydrological information.

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

scholarly journals Estimation of baseflow parameters of variable infiltration capacity model with soil and topography properties for predictions in ungauged basins

2011 ◽  
Vol 8 (4) ◽  
pp. 7017-7053 ◽  
Author(s):  
Z. Bao ◽  
J. Liu ◽  
J. Zhang ◽  
G. Fu ◽  
G. Wang ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Simulation ◽  
Parameters Estimation ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Ungauged Catchments ◽  
Vic Model ◽  
Predictions In Ungauged Basins

Abstract. Equifinality is unavoidable when transferring model parameters from gauged catchments to ungauged catchments for predictions in ungauged basins (PUB). A framework for estimating the three baseflow parameters of variable infiltration capacity (VIC) model, directly with soil and topography properties is presented. When the new parameters setting methodology is used, the number of parameters needing to be calibrated is reduced from six to three, that leads to a decrease of equifinality and uncertainty. This is validated by Monte Carlo simulations in 24 hydro-climatic catchments in China. Using the new parameters estimation approach, model parameters become more sensitive and the extent of parameters space will be smaller when a threshold of goodness-of-fit is given. That means the parameters uncertainty is reduced with the new parameters setting methodology. In addition, the uncertainty of model simulation is estimated by the generalised likelihood uncertainty estimation (GLUE) methodology. The results indicate that the uncertainty of streamflow simulations, i.e., confidence interval, is lower with the new parameters estimation methodology compared to that used by original calibration methodology. The new baseflow parameters estimation framework could be applied in VIC model and other appropriate models for PUB.

scholarly journals Effects of Land Use Planning in PERPRES 54/2008 on River Discharges

2018 ◽  
Author(s):  
Miga Magenika Julian ◽  
Fumihiko Nishio ◽  
Poerbandono ◽  
Philip J. Ward
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
River Discharge ◽  
Balance Model ◽  
Climate Data ◽  
Spatial Simulation ◽  
Flood Prevention ◽  
Simulation Scenario ◽  
Discharge Simulation ◽  
Effects Of Land Use

In 2008, a presidential regulation number 54 (Peraturan Presiden Nomor 54 Tahun 2008 - Perpres 54/2008) that regulates uses of land for various degrees of utilization and conservation across Jakarta, Bogor, Depok, Tangerang, Bekasi, Puncak and Cianjur (Jabodetabekpuncur) was issued. Perpres 54/2008 is a reference for the implementation of development related to water and soil conservation, the availability of ground water and surface water, flood prevention, and economic development for the welfare of the community. This study was intended to investigate the effects of land use planning in Perpres 54/2008 on river discharges based on spatial simulation of the Ciliwung and Cisadane watersheds. Three evaluation points for each watershed were investigated: downstream, middle and upper watersheds. Here, we simulated the river discharge at 100m×100m resolution with land use data in year 2007. A calibrated spatial water balance model named Spatial Tools for River Basins and Environment and Analysis of Management Option (STREAM) was used for river discharge simulation. The inputs of this model were climate data (precipitation and temperature), land use and topography. Two scenarios of land use were used, the actual land use condition (i.e. year 2007) and planned land use according to Perpres 54/2008. Based on Perpres 54/2008 simulation scenario, if land use planned in Perpres 54/2008 have successfully implemented, it can reduces river discharge by 0.1% to 5.6%.

scholarly journals Mean-field model of interacting quasilocalized excitations in glasses

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Corrado Rainone ◽  
Pierfrancesco Urbani ◽  
Francesco Zamponi ◽  
Edan Lerner ◽  
Eran Bouchbinder
Keyword(s):  
Elastic Medium ◽  
Density Of States ◽  
Field Model ◽  
Mean Field ◽  
Mean Square Displacement ◽  
Decisive Role ◽  
Future Research ◽  
Model Parameters ◽  
Mean Field Model ◽  
Structural Glasses

Structural glasses feature quasilocalized excitations whose frequencies \omegaω follow a universal density of states {D}(\omega)\!\sim\!\omega^4D(ω)∼ω4. Yet, the underlying physics behind this universality is not fully understood. Here we study a mean-field model of quasilocalized excitations in glasses, viewed as groups of particles embedded inside an elastic medium and described collectively as anharmonic oscillators. The oscillators, whose harmonic stiffness is taken from a rather featureless probability distribution (of upper cutoff \kappa_0κ0) in the absence of interactions, interact among themselves through random couplings (characterized by a strength JJ) and with the surrounding elastic medium (an interaction characterized by a constant force hh). We first show that the model gives rise to a gapless density of states {D}(\omega)\!=\!A_{g}\,\omega^4D(ω)=Agω4 for a broad range of model parameters, expressed in terms of the strength of the oscillators’ stabilizing anharmonicity, which plays a decisive role in the model. Then — using scaling theory and numerical simulations — we provide a complete understanding of the non-universal prefactor A_{g}(h,J,\kappa_0)Ag(h,J,κ0), of the oscillators’ interaction-induced mean square displacement and of an emerging characteristic frequency, all in terms of properly identified dimensionless quantities. In particular, we show that A_{g}(h,J,\kappa_0)Ag(h,J,κ0) is a non-monotonic function of JJ for a fixed hh, varying predominantly exponentially with -(\kappa_0 h^{2/3}\!/J^2)−(κ0h2/3/J2) in the weak interactions (small JJ) regime — reminiscent of recent observations in computer glasses — and predominantly decays as a power-law for larger JJ, in a regime where hh plays no role. We discuss the physical interpretation of the model and its possible relations to available observations in structural glasses, along with delineating some future research directions.

scholarly journals On the selection of precipitation products for the regionalisation of hydrological model parameters

2021 ◽  
Vol 25 (11) ◽  
pp. 5805-5837
Author(s):  
Oscar M. Baez-Villanueva ◽  
Mauricio Zambrano-Bigiarini ◽  
Pablo A. Mendoza ◽  
Ian McNamara ◽  
Hylke E. Beck ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Temporal Distribution ◽  
Hydrological Regime ◽  
Hydrologic Model ◽  
Spatial Proximity ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Water Balance Components ◽  
Feature Similarity

Abstract. Over the past decades, novel parameter regionalisation techniques have been developed to predict streamflow in data-scarce regions. In this paper, we examined how the choice of gridded daily precipitation (P) products affects the relative performance of three well-known parameter regionalisation techniques (spatial proximity, feature similarity, and parameter regression) over 100 near-natural catchments with diverse hydrological regimes across Chile. We set up and calibrated a conceptual semi-distributed HBV-like hydrological model (TUWmodel) for each catchment, using four P products (CR2MET, RF-MEP, ERA5, and MSWEPv2.8). We assessed the ability of these regionalisation techniques to transfer the parameters of a rainfall-runoff model, implementing a leave-one-out cross-validation procedure for each P product. Despite differences in the spatio-temporal distribution of P, all products provided good performance during calibration (median Kling–Gupta efficiencies (KGE′s) > 0.77), two independent verification periods (median KGE′s >0.70 and 0.61, for near-normal and dry conditions, respectively), and regionalisation (median KGE′s for the best method ranging from 0.56 to 0.63). We show how model calibration is able to compensate, to some extent, differences between P forcings by adjusting model parameters and thus the water balance components. Overall, feature similarity provided the best results, followed by spatial proximity, while parameter regression resulted in the worst performance, reinforcing the importance of transferring complete model parameter sets to ungauged catchments. Our results suggest that (i) merging P products and ground-based measurements does not necessarily translate into an improved hydrologic model performance; (ii) the spatial resolution of P products does not substantially affect the regionalisation performance; (iii) a P product that provides the best individual model performance during calibration and verification does not necessarily yield the best performance in terms of parameter regionalisation; and (iv) the model parameters and the performance of regionalisation methods are affected by the hydrological regime, with the best results for spatial proximity and feature similarity obtained for rain-dominated catchments with a minor snowmelt component.

scholarly journals Prediksi Tinggi Badan Ditentukan dari Panjang Rentang Lengan dan Panjang Telapak Kaki Pada Mongoloid Feminina Khususnya Etnis Jawa

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Nur Mujaddidah Mochtar
Keyword(s):  
Clinical Medicine ◽  
Pearson Correlation ◽  
Body Height ◽  
Regression Equation ◽  
The Body ◽  
Regression Equations ◽  
Foot Length ◽  
Arm Span ◽  
Knee Height ◽  
The Mean

Background: There are various circumstances where measurements are not actually possible, replacement parameters can be used to estimate body height. Many characteristics of body height measurement and how to measure it. These include anthropometric measurements that can be used for the identification of medicolegal-forensic processes. Body height in clinical medicine and in the field of scientific research can be easily estimated using various anthropometric parameters such as arm span, knee height, foot length and foot breadth, and others. The arm span and foot length has proved to be one of the most reliable predictors. This study was conducted to estimate of body height from arm span and foot length using the regression equation and to determine the correlation between the body height and arm span and foot length.Methods: This study was conducted at Universitas Muhammadiyah Surabaya with 182 Javanese female students. Stature, arm span and foot length measured directly using anthropometric technique and measuring tape. The data obtained were then analyzed with SPSS version 16. The regression equation was derived for the estimate of body height and the relationship between stature, arm span and foot length determined by the Pearson correlation.               Results: We found that the mean body height of Javanese women was 1534,45 ± 47,623  mm, mean of arm span 1543,25 ± 60,468 mm and the mean of foot length 226,14 ± 9,586 mm. The correlation between stature and arm span was positive and significant (r = 0,715  , p <0,05). The correlation between stature and foot length was positive and significant (r = 0,726 , p <0,05). The correlation between stature and arm span and foot length was positive and significant (r = 0,798, p <0,05).               Conclusion: Body height correlates well with the arm span and foot length so that it can be used as a reliable marker for high estimates using regression equations.

scholarly journals PROBLEMS FOR ANTI-CRISIS ANALYTICAL PROCEDURES OF FINANCIAL STABILITY OF TRADE ENTERPRISES

2020 ◽  
Author(s):  
Ludmila Anipko ◽  
◽  
Irina Klimovych ◽  
Keyword(s):  
Financial Stability ◽  
Regression Equation ◽  
Regression Coefficients ◽  
Regression Equations ◽  
Financial Condition ◽  
Financial Audit ◽  
Analytical Procedures ◽  
Financial Monitoring ◽  
Complex Indicators

Anti-crisis analytical procedures the financial stability of trade enterprises (hereinafter – AP FS) are part of the internal financial audit of economic activity. The system of financial monitoring is practically acceptable for the implementation of AP FS. The developed classification allows to determine the ability of the enterprise to implement AP FS. An analytical method has been developed that allows, based on the analysis of the financial condition and multivariate forecast, to develop measures to ensure the financial stability of the trade enterprise continuously. By interpolation, the study of the current financial situation, and extrapolation – a multivariate forecast, the numerical value of the integrated (complex) indicator that characterizes financial stability is determined by the regression equation, including factors listed in the classification, the significance of which is determined by regression equations. Based on the analysis of the numerical values of the regression coefficients, it is possible to determine the most important factors that affect the financial stability of trade enterprises, and those that have almost no effect on it. Components with significantly small numerical values of the regression coefficients can be generally discarded. This will reduce the number of indicators that affect financial stability and thus, you can reduce the number of components in the regression equation to the two three most important, which allows you to solve the problem of optimization. The expediency of using integrated and complex indicators is shown. The obtained results are only an information basis for the economic administration of the trade enterprise in making management decisions, the formation of long-term plans. The developed approaches to assessing the financial stability of enterprises are universal and can be used for enterprises in other sectors of the economy.

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