The prediction of water yield from a 5 ha experimental catchment, Krawarree, NSW

Soil Research ◽  
1980 ◽  
Vol 18 (2) ◽  
pp. 149 ◽  
Author(s):  
AR Aston ◽  
FX Dunin
Keyword(s):  
Computer Model ◽  
Input Data ◽  
Water Yield ◽  
Monthly Variation ◽  
Modes Of Operation ◽  
Hydrologic Processes ◽  
Recorded Data ◽  
Data Requirements

A computer model called WATSIM was developed and used to predict the water yield of a 5 ha experimental catchment. The model is deterministic in describing the major hydrologic processes, has realistic input data requirements, and can treat the catchment as a series of cascaded hydrologic areas or as a single lumped entity. In both the cascaded and lumped modes of operation, the predicted monthly and annual yields agreed well with recorded data over a six year period, and accounted for approximately 98% of the monthly variation in yield.

scholarly journals Regionalizing rainfall–runoff model parameters to predict the daily streamflow of ungauged catchments in the dry tropics

2009 ◽  
Vol 40 (5) ◽  
pp. 433-444 ◽  
Author(s):  
David A. Post
Keyword(s):  
Input Data ◽  
Water Yield ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Wet Season ◽  
Daily Streamflow ◽  
Total Length ◽  
Dry Tropics ◽  
Rainfall Runoff Model ◽  
Runoff Model

A methodology has been derived which allows an estimate to be made of the daily streamflow at any point within the Burdekin catchment in the dry tropics of Australia. The input data requirements are daily rainfall (to drive the rainfall–runoff model) and mean average wet season rainfall, total length of streams, percent cropping and percent forest in the catchment (to regionalize the parameters of the rainfall–runoff model). The method is based on the use of a simple, lumped parameter rainfall–runoff model, IHACRES (Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data). Of the five parameters in the model, three have been set to constants to reflect regional conditions while the other two have been related to physio-climatic attributes of the catchment under consideration. The parameter defining total catchment water yield (c) has been estimated based on the mean average wet season rainfall, while the streamflow recession time constant (τ) has been estimated based on the total length of streams, percent cropping and percent forest in the catchment. These relationships have been shown to be applicable over a range of scales from 68–130,146 km2. However, three separate relationships were required to define c in the three major physiographic regions of the Burdekin: the upper Burdekin, Bowen and Suttor/lower Burdekin. The invariance of the relationships with scale indicates that the dominant processes may be similar across a range of scales. The fact that different relationships were required for each of the three major regions indicates the geographic limitations of this regionalization approach. For most of the 24 gauged catchments within the Burdekin the regionalized rainfall–runoff models were nearly as good as or better than the rainfall–runoff models calibrated to the observed streamflow. In addition, models often performed better over the simulation period than the calibration period. This indicates that future improvements in regionalization should focus on improving the quality of input data and rainfall–runoff model conceptualization rather than on the regionalization procedure per se.

scholarly journals SIMULATION TESTS OF EXTINGUISHING PROCESS USING MIST NOZZLES WITH APPLICATION OF HYBRID FIRE MODEL

2016 ◽  
Vol 22 (4) ◽  
pp. 573-583 ◽  
Author(s):  
Jerzy GAŁAJ ◽  
Marek KONECKI ◽  
Ritoldas ŠUKYS
Keyword(s):  
Heat Flux ◽  
Computer Model ◽  
Input Data ◽  
Elementary Cell ◽  
Characteristic Parameters ◽  
Computational Cell ◽  
Fire Model ◽  
Fire Extinguishing ◽  
Unique Approach

The article presents a computer model of the fire extinguishing process using mist nozzles. A previously developed hybrid fire model was used for this purpose. Assumptions and relationships were given to represent a math­ematical model of extinguishing process, which comprises a unique approach to the determination of sprinkling area in an elementary cell of field fire model. A description of simulation tests of the model was given for several different input data, differing by mean diameters of droplets. This enabled a study of their effects on such output parameters as received heat flux, temperature and rate of its growth. For one selected computational cell located on the axis of the nozzle at floor level having the coordinates [10, 10, 1], the obtained results were presented in the form of heat flux and temperature. To simplify the analysis, characteristic parameters of particular curves were listed in the table. Conclusions formulated on the basis of results obtained during tests were specified at the end of work. They confirmed the expected regularity assuming that the extinguishing process was more effective in the case of droplets of a smaller diameter and greater sprinkling intensity. This allows assessing the degree, to which these stream parameters affect the extinguishing effectiveness.

scholarly journals Multicriteria Fuzzy Sets Application in Economic Clustering Problems

2017 ◽  
Vol 17 (3) ◽  
pp. 29-46
Author(s):  
Irina Radeva
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Input Data ◽  
Multi Criteria Decision Making ◽  
Promethee Ii ◽  
Specific Input ◽  
Clustering Problems ◽  
Data Requirements

Abstract This paper presents an approach for small and medium-sized enterprises selection in economic clusters, where the problem of integration is defined as “ill structured under condition of uncertainty”. The proposed solution demonstrates applying several fuzzy multi-criteria decision making algorithms along with discussion over specific input data requirements. The results are compared with classical multi-criteria decision-making algorithm PROMETHEE II.

scholarly journals Intercomparison of Machine-Learning Methods for Estimating Surface Shortwave and Photosynthetically Active Radiation

2020 ◽  
Vol 12 (3) ◽  
pp. 372
Author(s):  
Meredith G. L. Brown ◽  
Sergii Skakun ◽  
Tao He ◽  
Shunlin Liang
Keyword(s):  
Machine Learning ◽  
Photosynthetically Active Radiation ◽  
Input Data ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Learning Methods ◽  
Active Radiation ◽  
Machine Learning Methods ◽  
Robust Model ◽  
Data Requirements

Satellite-derived estimates of downward surface shortwave radiation (SSR) and photosynthetically active radiation (PAR) are a part of the surface radiation budget, an essential climate variable (ECV) required by climate and vegetation models. Ground measurements are insufficient for generating long-term, global measurements of surface radiation, primarily due to spatial limitations; however, remotely sensed Earth observations offer freely available, multi-day, global coverage of radiance that can be used to derive SSR and PAR estimates. Satellite-derived SSR and PAR estimates are generated by computing the radiative transfer inversion of top-of-atmosphere (TOA) measurements, and require ancillary data on the atmospheric condition. To reduce computational costs, often the radiative transfer calculations are done offline and large look-up tables (LUTs) are generated to derive estimates more quickly. Recently studies have begun exploring the use of machine-learning techniques, such as neural networks, to try to improve computational efficiency. Here, nine machine-learning methods were tested to model SSR and PAR using minimal input data from the Moderate Resolution Imaging Spectrometer (MODIS) observations at 1 km spatial resolution. The aim was to reduce the input data requirements to create the most robust model possible. The bootstrap aggregated decision tree (Bagged Tree), Gaussian Process Regression, and Neural Network yielded the best results with minimal training data requirements: an R 2 of 0.77, 0.78, and 0.78 respectively, a bias of 0 ± 6, 0 ± 6, and 0 ± 5 W / m 2 , and an RMSE of 140 ± 7, 135 ± 8, and 138 ± 7 W / m 2 , respectively, for all-sky condition total surface shortwave radiation and viewing angles less than 55°. Viewing angles above 55° were excluded because the residual analysis showed exponential error growth above 55°. A simple, robust model for estimating SSR and PAR using machine-learning methods is useful for a variety of climate system studies. Future studies may focus on developing high temporal resolution direct and diffuse estimates of SSR and PAR as most current models estimate only total SSR or PAR.

scholarly journals Development and Application of a SWMM-Based Simulation Model for Municipal Scale Hydrologic Assessments

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1644
Author(s):  
Tyler Dell ◽  
Mostafa Razzaghmanesh ◽  
Sybil Sharvelle ◽  
Mazdak Arabi
Keyword(s):  
Input Data ◽  
Processing Time ◽  
Simulation Analysis ◽  
Control Measure ◽  
Storm Events ◽  
Storm Water Management Model ◽  
Continuous Simulation ◽  
Stormwater Control ◽  
Data Requirements ◽  
Hydrologic Performance

There is growing interest for the installation of green stormwater infrastructure (GSI) to improve stormwater control, increase infiltration of stormwater, and improve receiving water body quality. Planning level tools are needed to inform municipal scale decisions on the type and extent of GSI to apply. Here, a modified methodology is developed for the EPA Storm Water Management Model (SWMM) to create SWMM for Low Impact Technology Evaluation (SWWM-LITE) that enables municipal scale assessment of stormwater control measure (SCM) performance with minimal input data requirements and low processing time. Hydrologic outputs of SWMM-LITE are compared to those for SWMM and the National Stormwater Calculator (SWC) to assess the performance of SWMM-LITE. Three scenarios including the baseline without SCMs and the installation of varying SCMs were investigated. Across the three scenarios, SWMM-LITE estimates of annual average hydrologic performance (runoff, infiltration, and evaporation) were within +/−0.1% of estimates from a rigorously developed SWMM model in the City of Fort Collins, CO, for an evaluation of 30 years of continuous simulation. Analysis conducted for 2 year (y), 10 y, and 100 y storm events showed less than +/−2.5% difference between SWMM and SWMM-LITE hydrologic outputs. SWC provided reasonable estimates of hydrologic parameters for the case study area, but was designed for site level analyses of performance of SCMs rather than on the municipal scale. A sensitivity analysis revealed that the most sensitive parameters were primarily consistent for the SWMM-LITE and the complete SWMM. SWMM-LITE has low input data requirements and processing time and can be applied for assessing the hydrologic performance of SCMs to inform planning level decisions.

scholarly journals Modeling hydrologic processes and potential responses to climate change in an agro-silvo-pastoral watershed in the Mediterranean area

2020 ◽  
Vol 383 ◽  
pp. 151-158
Author(s):  
Youssef Brouziyne ◽  
Lahcen Benaabidate ◽  
Aziz Abouabdillah ◽  
Rachid Bouabid ◽  
Abdelghani Chehbouni
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Balance ◽  
Assessment Tool ◽  
Flow Direction ◽  
Swat Model ◽  
Water Yield ◽  
Climate Change Scenarios ◽  
Climate Conditions ◽  
Hydrologic Processes

Abstract. Precipitation changes and water use patterns are two factors affecting the water quantity; obviously, hydrologic processes are always linked to many elements in the watershed scale, so to understand water management issues it is fundamental to analyze the different elements of hydrologic processes occurring in the watershed. In this study, the “SWAT” model (Soil and Water Assessment Tool) has been used to simulate the water balance for the present climate conditions on a semi arid watershed located in the central North of Morocco (R'dom). The study watershed covers an area of 1993 km2, and is hosting farming, pasture and forestry related activities. The water stress situation in the R'dom watershed can be summarized as limited resource facing increasing water demand. SWAT model was first run and calibrated under current climate; and was driven with downscaled climate simulations to generate future hydrological projections for R'dom watershed in the 2031 to 2050 horizon under two Representative Concentration Pathways (RCPs): 4.5 and 8.5. The results of the study showed that the water balance in R'dom watershed is dominated by evapotranspiration and the water resources distribution within the watershed is uneven and follows a decreasing gradient matching the flow direction. The main results of climate change scenarios showed that R'dom watershed will undergo significant decrease of water resources availability with more economic impact under the scenario RCP8.5 as all areas hosting the economical activities will be affected and the highest changes of water yield should be under this scenario.

scholarly journals A computer model designed to evaluate the firefighting effectiveness of solid jet produced by water nozzle

2018 ◽  
Vol 24 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Jerzy GAŁAJ ◽  
Tomasz DRZYMAŁA ◽  
Ritoldas ŠUKYS ◽  
Piotr TOFIŁO
Keyword(s):  
Mathematical Model ◽  
Numerical Model ◽  
Computer Model ◽  
International Research ◽  
Input Data ◽  
General Concept ◽  
Main Program ◽  
Jet Streams ◽  
Input And Output ◽  
Water Nozzle

The paper begins with a brief introduction and review of international research in the area of water jet streams and their effectiveness in firefighting. Then a general concept of a new numerical model for firefighting process using solid jet produced by water nozzle is presented. The provided description of the model includes main assumptions for extinguishing process and a set of relationships representing a mathematical model. The paper also includes block diagrams of the main program algorithms and procedures designed to determine the value of the surface and sprinkling intensity depending on the input data like nozzle dimensions, position etc. Input parameters which are necessary for the calculation are discussed, together with a general concept of the users input and output interfaces and simulation tests that can be performed using the developed model. Some selected simulation tests in tabular and graphical forms are included. Summary and general conclusions can be found at the end.

scholarly journals Meteorological input data requirements to predict cross-pollination of GMO Maize with Lagrangian approaches

2006 ◽  
Vol 5 (3) ◽  
pp. 151-168 ◽  
Author(s):  
Kai Lipsius ◽  
Ralf Wilhelm ◽  
Otto Richter ◽  
Klaus Jürgen Schmalstieg ◽  
Joachim Schiemann
Keyword(s):  
Input Data ◽  
Cross Pollination ◽  
Meteorological Input ◽  
Data Requirements
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