Prediction of solar radiation with air temperature data in a coastal location in Tamilnadu

The objective of this study is to evaluate the performance of the Hargreaves’ Radiation formula in estimating daily solar radiation for an Indian coastal location namely Annamalainagar in Tamilnadu State. Daily solar radiation by Hargreaves’ Radiation formula was computed using the observed data of maximum temperature, Tmax and minimum temperature, Tmin, sourced from the India Meteorological Observatory located at Annamalainagar and employing the adjustment coefficient KRS of 0.19. Daily solar radiation was also computed using Angstrom-Prescott formula with the measured daily sunshine hour data. The differences between the daily solar radiation values computed using the formulae were more pronounced in year around. Hence, the adjustment coefficient KRS is calibrated for the study location under consideration so that the calibrated KRS could be used to better predict daily solar radiation and hence better estimation of reference evapotranspiration.

Outflow adjustment coefficient for the design of storage facilities using the rain envelope method applied to Brazilian state capitals

Detention devices are often used as alternative measures for stormwater control. The Envelope Curve Method is widely used in Brazil to estimate detention device volumes. This method estimates the storage volume based on inlet and outlet balance, where the inlet is obtained by the Rational Method and the outlet by orifice bottom discharge. Usually, the outlet flow is adopted as a constant and equivalent to the maximum allowed, and this procedure can cause reservoir undersizing. This paper evaluates detention control measures’ hydraulic behavior for the Envelope Curve Method and proposes the inclusion of an outflow adjustment coefficient (Cout), seeking to compensate for the adoption of constant outlet flow simplification. Values for this coefficient were estimated for several Brazilian state capitals, ranging from 0.62 up to 0.65. The undersizing hypothesis due to the adoption of constant outlet flow was confirmed, as the simulations showed the need for an increase between 8.4% to 16.8% in the device size. This undersizing may be compensated for by applying the outflow adjustment coefficient (Cout). Keywords: adjustment coefficient, detention facilities, envelope curve, hydrologic design outflow adjustment coefficient.

An Improved Artificial Potential Field Escape Method with Weight Adjustment

Aiming at the problems of obstacle avoidance and bullet avoidance during the patrol swarm, this paper analyzed the defects of the classical artificial potential field, proposed an adjustable escape method, which establish the relationship between the adjustment coefficient and the distance. This method avoid too large or too small escape force that get the bullet into new local shock problem near the target. Then given the weight calculation and parameter selection method, restricted the escape motion by kinematics according to the constraints in the actual motion. This improved method can effecting solve the problem of avoidance in dynamic and complex environment.

Utilization of Weather Radar Data for the Flash Flood Indicator Application in the Czech Republic

In the past few years, demands on flash flood forecasting have grown. The Flash Flood Indicator (FFI) is a system used at the Czech Hydrometeorological Institute for the evaluation of the risk of possible occurrence of flash floods over the whole Czech Republic. The FFI calculation is based on the current soil saturation, the physical-geographical characteristics of every considered area, and radar-based quantitative precipitation estimates (QPEs) and forecasts (QPFs). For higher reliability of the flash flood risk assessment, calculations of QPEs and QPFs are crucial, particularly when very high intensities of rainfall are reached or expected. QPEs and QPFs entering the FFI computations are the products of the Czech Weather Radar Network. The QPF is based on the COTREC extrapolation method. The radar-rain gauge-combining method MERGE2 is used to improve radar-only QPEs and QPFs. It generates a combined radar-rain gauge QPE based on the kriging with an external drift algorithm, and, also, an adjustment coefficient applicable to radar-only QPEs and QPFs. The adjustment coefficient is applied in situations when corresponding rain gauge measurements are not yet available. A new adjustment coefficient scheme was developed and tested to improve the performance of adjusted radar QPEs and QPFs in the FFI.

Estimation of Reference Evapotranspiration during the Irrigation Season Using Nine Temperature-Based Methods in a Hot-Summer Mediterranean Climate

The FAO-56 Penman–Monteith (PM) equation is regarded as the most accurate equation to estimate reference evapotranspiration (ETo). However, it requires a broad range of data that may not be available or of reasonable quality. In this study, nine temperature-based methods were assessed for ETo estimation during the irrigation at fourteen locations distributed through a hot-summer Mediterranean climate region of Alentejo, Southern Portugal. Additionally, for each location, the Hargreaves–Samani radiation adjustment coefficient (kRs) was calibrated and validated to evaluate the appropriateness of using the standard value, creating a locally adjusted Hargreaves–Samani (HS) equation. The accuracy of each method was evaluated by statistically comparing their results with those obtained by PM. Results show that the calibration of the kRs, a locally adjusted HS method can be used to estimate daily ETo acceptably well, with RMSE lower than 0.88 mm day−1, an estimation error lower than 4% and a R2 higher than 0.69, proving to be the most accurate model for 8 (out of 14) locations. A modified Hargreaves–Samani method also performed acceptably for 4 locations, with a RMSE of 0.72–0.84 mm day−1, a slope varying from 0.95 to 1.01 and a R2 higher than 0.78. One can conclude that, when weather data is missing, a calibrated HS equation is adequate to estimate ETo during the irrigation season.

The Characteristics of Runoff Process Structure Changes under the Influence of Climate Change and Human Activities and the Decomposition of Contribution Rate of Impact Factors

The research of the runoff structure and its influencing factors in the Xilinhe River Basin not only provides indispensable basic data for the economic development, but also has long-term significance for the protection of grasslands. Based on the runoff data of Xilinhot Hydrological Station from 1960 to 2010 and the daily meteorological data of three surrounding weather stations from 1960 to 2010, the paper calculated the potential evapotranspiration with Penman’s formula and used the combination of Mann-Kendall and Pettitt to diagnose the variation points of characteristic value of runoff distribution during the year. The cumulant slope change rate method is used to quantitatively analyze the contribution rate of climate change and human activities to the uneven distribution coefficient and the complete adjustment coefficient of runoff during the year. The results show that (1) the monthly distribution of runoff in the Xilinhe River Basin is obviously “bimodal” during the year, and the uneven coefficient, complete adjustment coefficient, and concentration in the 2000s are significantly higher than those of 60s-90s. (2) In 1998, the coefficient of uneven distribution of runoff in the Xilinhe River Basin and the coefficient of complete adjustment both showed abrupt changes. (3) Climate change and human activities contributed 11.48% and 88.52% and 9.35% and 90.65% to the uneven distribution coefficient and the complete adjustment coefficient, respectively, of the runoff in the Xilinhe River Basin. Human activities are the main driving factors for changes in the distribution of runoff in the Xilinhe River Basin during the year.

A Simple Procedure to Estimate Reference Evapotranspiration during the Irrigation Season in a Hot-Summer Mediterranean Climate

The Food and Agricultural Organization of the United Nations (FAO) Penman–Monteith (PM) method is widely regarded as the most effective reference evapotranspiration (ETo) estimator; however, it requires a wide range of data that may be scarce in some rural regions. When feasible relative humidity, solar radiation and wind speed data are unavailable, a temperature-based method may be useful to estimate ETo and provide suitable data to support irrigation management. This study has evaluated the accuracy of two ETo estimations methods: (1) a locally and monthly adjusted Hargreaves–Samani (HS) equation; (2) a simple procedure that only uses maximum temperature and a temperature adjustment coefficient (MaxTET). Results show that, if a monthly adjusted radiation adjustment coefficient (kRs) is calibrated for each site, acceptable ETo estimations (RMSE and R2 equal to 0.79 for the entire region) can be achieved. Results also show that a procedure to estimate ETo based only on maximum temperature performs acceptably, when compared with ETo estimation using PM equation (RMSE = 0.83 mm day−1 and R2 = 0.77 for Alentejo). When comparing these results with the ones attained when adopting a monthly adjusted HS method, the MaxTET procedure proves to be an accurate ETo estimator. Results also show that both methods can be used to estimate ETo when weather data are scarce.

A Novel Method for Thermal Modelling of Photovoltaic Modules/Cells under Varying Environmental Conditions

Temperature has a significant effect on the photovoltaic module output power and mechanical properties. Measuring the temperature for such a stacked layers structure is impractical to be carried out, especially when we talk about a high number of modules in power plants. This paper introduces a novel thermal model to estimate the temperature of the embedded electronic junction in modules/cells as well as their front and back surface temperatures. The novelty of this paper can be realized through different aspects. First, the model includes a novel coefficient, which we define as the forced convection adjustment coefficient to imitate the module tilt angle effect on the forced convection heat transfer mechanism. Second, the new combination of effective sub-models found in literature producing a unique and reliable method for estimating the temperature of the PV modules/cells by incorporating the new coefficient. In addition, the paper presents a comprehensive review of the existing PV thermal sub-models and the determination expressions of the related parameters, which all have been tested to find the best combination. The heat balance equation has been employed to construct the thermal model. The validation phase shows that the estimation of the module temperature has significantly improved by introducing the novel forced convection adjustment coefficient. Measurements of polycrystalline and amorphous modules have been used to verify the proposed model. Multiple error indication parameters have been used to validate the model and verify it by comparing the obtained results to those reported in recent and most accurate literature.

Ruin Probability for Stochastic Flows of Financial Contract under Phase-Type Distribution

This paper examines the impact of the parameters of the distribution of the time at which a bank’s client defaults on their obligated payments, on the Lundberg adjustment coefficient, the upper and lower bounds of the ruin probability. We study the corresponding ruin probability on the assumption of (i) a phase-type distribution for the time at which default occurs and (ii) an embedding of the stochastic cash flow or the reserves of the bank to the Sparre Andersen model. The exact analytical expression for the ruin probability is not tractable under these assumptions, so Cramér Lundberg bounds types are obtained for the ruin probabilities with concomitant explicit equations for the calculation of the adjustment coefficient. To add some numerical flavour to our results, we provide some numerical illustrations.

Logarithmic Asymptotics for Probability of Component-Wise Ruin in a Two-Dimensional Brownian Model

We consider a two-dimensional ruin problem where the surplus process of business lines is modelled by a two-dimensional correlated Brownian motion with drift. We study the ruin function P ( u ) for the component-wise ruin (that is both business lines are ruined in an infinite-time horizon), where u is the same initial capital for each line. We measure the goodness of the business by analysing the adjustment coefficient, that is the limit of - ln P ( u ) / u as u tends to infinity, which depends essentially on the correlation ρ of the two surplus processes. In order to work out the adjustment coefficient we solve a two-layer optimization problem.