Determination Of Sediment Yield By GeoWEPP Erosion Estimation Model

2019 ◽  
Author(s):  
Cengizhan Yıldırım ◽  
Mustafa Tüfekçioğlu
Keyword(s):  
Sediment Yield ◽  
Estimation Model

scholarly journals Torrential Flood Water Management: Rainwater Harvesting through Relation Based Dam Suitability Analysis and Quantification of Erosion Potential

2021 ◽  
Vol 10 (1) ◽  
pp. 27
Author(s):  
Bilal Ahmad Munir ◽  
Sajid Rashid Ahmad ◽  
Raja Rehan
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Rainwater Harvesting ◽  
Suitability Analysis ◽  
Valley Bottom ◽  
The North ◽  
Roughness Index ◽  
Dam Site ◽  
Very High

In this study, a relation-based dam suitability analysis (RDSA) technique is developed to identify the most suitable sites for dams. The methodology focused on a group of the most important parameters/indicators (stream order, terrain roughness index, slope, multiresolution valley bottom flatness index, closed depression, valley depth, and downslope gradient difference) and their relation to the dam wall and reservoir suitability. Quantitative assessment results in an elevation-area-capacity (EAC) curve substantiating the capacity determination of selected sites. The methodology also incorporates the estimation of soil erosion (SE) using the Revised Universal Soil Loss Equation (RUSLE) model and sediment yield at the selected dam sites. The RDSA technique identifies two suitable dam sites (A and B) with a maximum collective capacity of approximately 1202 million m3. The RDSA technique was validated with the existing dam, Gomal-Zam, in the north of Sanghar catchment, where RDSA classified the Gomal-Zam Dam in a very high suitability class. The SE estimates show an average of 75 t-ha−1y−1 of soil loss occurs in the study area. The result shows approximately 298,073 and 318,000 tons of annual average sediment yield (SY) will feed the dam A and B respectively. The SE-based sediment yield substantiates the approximate life of Dam-A and Dam-B to be 87 and 90 years, respectively. The approach is dynamic and can be applied for any other location globally for dam site selection and SE estimation.

Determining central activation failure and peripheral fatigue in the course of sustained maximal voluntary contractions: a model-based approach

2005 ◽  
Vol 98 (6) ◽  
pp. 2292-2297 ◽  
Author(s):  
Maartje L. Schillings ◽  
Dick F. Stegeman ◽  
Machiel J. Zwarts
Keyword(s):  
Electrical Stimulation ◽  
Healthy Subjects ◽  
Linear Interpolation ◽  
Voluntary Contraction ◽  
Peripheral Fatigue ◽  
Estimation Model ◽  
Central Activation ◽  
Model Based ◽  
Voluntary Contractions

In the study of fatigue, several methods have been used to calculate the development of central activation failure (CAF) and peripheral fatigue (PF) in the course of a sustained maximal voluntary contraction (MVC). This paper presents a model that enables simultaneous determination of CAF and PF during sustained MVC by using only force registration and superimposed electrical stimulation. In the model, we explicitly use the assumption, which is virtually always made implicitly in earlier studies, that a constant relative fraction of maximal possible force is activated by the electrical stimulation. That fraction can be determined at the start and at the end of a sustained MVC. The model shows that in the course of a sustained MVC, CAF can be calculated by merely using 1) this fraction, 2) the amplitudes of the superimposed force responses to stimulation, and 3) the course of voluntary force. After CAF quantification, the development of PF during MVC becomes available as well. The present study first examines the model assumption with data of sustained MVCs of variable durations on six healthy subjects. Subsequently, it shows CAF values in a group of 27 healthy subjects determined with both the model and a method of linear interpolation for PF estimation. Model-based CAF values were significantly higher during, but not at the start and at the end of, a 2-min sustained MVC. Next to a well-justified CAF determination, the model has the advantage of simultaneously quantifying PF, which was not possible with the previous methods.

DETERMINATION OF SEDIMENT YIELD BY TRANSFERRING RAINFALL DATA

1977 ◽  
Vol 13 (3) ◽  
pp. 529-541 ◽  
Author(s):  
Jeffrey H. Smith ◽  
Donald R. Davis ◽  
Martin Fogel
Keyword(s):  
Sediment Yield ◽  
Rainfall Data

scholarly journals Determination of best sediment estimation model in semi-arid rangelands by using small reservoirs dams sedimentation(case study: daremorid watershed in kerman province)

2019 ◽  
Vol 9 (18) ◽  
pp. 233-240
Author(s):  
peyman madanchi ◽  
محمود عرب خدری ◽  
Mahmood Habibnejad Roshan ◽  
◽  
◽  
...  
Keyword(s):  
Estimation Model ◽  
Small Reservoirs ◽  
Arid Rangelands ◽  
Semi Arid

scholarly journals A Rapid Recognition of Impassable Terrain for Mobile Robots with Low Cost Range Finder Based on Hypotheses Testing Theory

2017 ◽  
Vol 12 (6) ◽  
pp. 813
Author(s):  
Yang Gao ◽  
Xueyi Wu ◽  
Yu Liu ◽  
Jian Ming Li ◽  
Jia Hao Liu
Keyword(s):  
Low Cost ◽  
Threshold Value ◽  
Vital Role ◽  
Hypotheses Testing ◽  
Estimation Model ◽  
Testing Theory ◽  
Slope Estimation ◽  
Sampling Set ◽  
Sample Set

The recognition of impassable terrain plays a vital role in the motionplanning of a mobile robot, which generally relies on expensive sensors such as stereovision cameras. This paper proposes a rapid impassable terrain recognition algorithmbased on hypotheses testing theory using low-cost range finders with different diffusionangles. In this algorithm, a slope estimation model using two range finders mountedon different heights is first established, where the influence of the diffusion angle ofthe range sensor is considered. To deal with inaccurate measuring from low costrange finders, the hypothesis testing theory is then applied to judge whether there isan impassible terrain approaching, where the historical slope estimation results aretreated as a sample set of the same slope, and the judgement of impassible terrainis then made based on the sampling set rather than the concurrent slope estimation.So the robot is only required to count the number of slope estimation that supportthe determination of a terrain as being impassible, and the judgement is confirmedonly when that number is larger than a precisely designed threshold value. Thenthe stable recognition for impassable terrain would be acquired while the risk ofwrong judgement is limited. The experiments’ results indicate that this algorithmcan provide a reliable recognition of impassable terrain using lower cost range finderswith different diffusion angles with minimal computation.

scholarly journals Fusion of Spectroscopy and Cobalt Electrochemistry Data for Estimating Phosphate Concentration in Hydroponic Solution

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2596 ◽  
Author(s):  
Dae-Hyun Jung ◽  
Hak-Jin Kim ◽  
Hyoung Kim ◽  
Jaeyoung Choi ◽  
Jeong Kim ◽  
...  
Keyword(s):  
Data Fusion ◽  
Spectral Data ◽  
Near Infrared ◽  
Accurate Determination ◽  
Model Performance ◽  
Phosphate Concentration ◽  
Least Squares Regression ◽  
Estimation Model ◽  
Network Estimation

Phosphate is a key element affecting plant growth. Therefore, the accurate determination of phosphate concentration in hydroponic nutrient solutions is essential for providing a balanced set of nutrients to plants within a suitable range. This study aimed to develop a data fusion approach for determining phosphate concentrations in a paprika nutrient solution. As a conventional multivariate analysis approach using spectral data, partial least squares regression (PLSR) and principal components regression (PCR) models were developed using 56 samples for calibration and 24 samples for evaluation. The R2 values of estimation models using PCR and PLSR ranged from 0.44 to 0.64. Furthermore, an estimation model using raw electromotive force (EMF) data from cobalt electrodes gave R2 values of 0.58–0.71. To improve the model performance, a data fusion method was developed to estimate phosphate concentration using near infrared (NIR) spectral and cobalt electrochemical data. Raw EMF data from cobalt electrodes and principle component values from the spectral data were combined. Results of calibration and evaluation tests using an artificial neural network estimation model showed that R2 = 0.90 and 0.89 and root mean square error (RMSE) = 96.70 and 119.50 mg/L, respectively. These values are sufficiently high for application to measuring phosphate concentration in hydroponic solutions.

scholarly journals Pemanfaatan WebGIS untuk Pemetaan Wilayah Rawan Longsor Kabupaten Boyolali dengan Metode Skoring dan Pembobotan

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Muhammad Sholikhan ◽  
Sri Yulianto Joko Prasetyo ◽  
Kristoko Dwi Hartomo
Keyword(s):  
Information System ◽  
Spatial Information ◽  
Rock Type ◽  
Web Design ◽  
Soil Maps ◽  
Estimation Model ◽  
Web Mapping ◽  
Internet Browser ◽  
Weighting Methods

WebGIS is an online-based application of Geographic Information System, this application is a combination of web design and web mapping. WebGIS is mainly used for publishing map-based spatial information. Therefore, the author utilized webGIS, in order to mapping area that prone to landslides by using scoring and weighting methods. Parameters that used in this paper referring to the estimation model by Puslittanak in 2004, the parameters were rainfall, rock type, slope, land use, and type of soil maps. The determination of area prone to landslides was carried out by multiplying score by weight for each parameter, subsequently, the result was added up according to the reference of Puslittanak. The result of this study indicates that there are 4 sub-districts with high disaster-prone level, the sub-districts are Ampel, Cepogo, Musuk, and Selo. The final result of the map processed into a webGIS by applying Google maps service and framework bootstrap; the webGIS can be accessed by internet browser.

Sign in / Sign up

Export Citation Format

Share Document