scholarly journals Comparing Evapotranspiration Estimates from the GEOframe-Prospero Model with Penman–Monteith and Priestley-Taylor Approaches under Different Climate Conditions

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1221
Author(s):  
Michele Bottazzi ◽  
Marialaura Bancheri ◽  
Mirka Mobilia ◽  
Giacomo Bertoldi ◽  
Antonia Longobardi ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Goodness Of Fit ◽  
Hydrological Cycle ◽  
Calibration Procedure ◽  
Experimental Models ◽  
Climatic Conditions ◽  
Prediction Errors ◽  
Fit Indices ◽  
Direct Estimate ◽  
Climate Conditions

Evapotranspiration (ET) is a key variable in the hydrological cycle and it directly impacts the surface balance and its accurate assessment is essential for a correct water management. ET is difficult to measure, since the existing methods for its direct estimate, such as the weighing lysimeter or the eddy-covariance system, are often expensive and require well-trained research personnel. To overcome this limit, different authors developed experimental models for indirect estimation of ET. However, since the accuracy of ET prediction is crucial from different points of view, the continuous search for more and more precise modeling approaches is encouraged. In light of this, the aim of the present work is to test the efficiency in predicting ET fluxes in a newly introduced physical-based model, named Prospero, which is based on the ability to compute the ET using a multi-layer canopy model, solving the energy balance both for the sunlight and shadow vegetation, extending the recently developed Schymanski and Or method to canopy level. Additionally, Prospero is able to compute the actual ET using a Jarvis-like model. The model is integrated as a component in the hydrological modelling system GEOframe. Its estimates were validated against observed data from five Eddy covariance (EC) sites with different climatic conditions and the same vegetation cover. Then, its performances were compared with those of two already consolidated models, the Priestley–Taylor model and Penman FAO model, using four goodness-of-fit indices. Subsequently a calibration of the three methods has been carried out using LUCA calibration within GEOframe, with the purpose of prediction errors. The results showed that Prospero is more accurate and precise with respect to the other two models, even if no calibrations were performed, with better performances in dry climatic conditions. In addition, Prospero model turned to be the least affected by the calibration procedure and, therefore, it can be effectively also used in a context of data scarcity.

scholarly journals Modelling the evolution of Djankuat Glacier, North Caucasus, from 1752 until 2100 CE

2020 ◽  
Vol 14 (11) ◽  
pp. 4039-4061
Author(s):  
Yoni Verhaegen ◽  
Philippe Huybrechts ◽  
Oleg Rybak ◽  
Victor V. Popovnin
Keyword(s):  
Surface Area ◽  
Flow Line ◽  
Calibration Procedure ◽  
Climatic Conditions ◽  
Balance Model ◽  
North Caucasus ◽  
Initial State ◽  
Climate Conditions ◽  
The North ◽  
Debris Cover

Abstract. We use a numerical flow line model to simulate the behaviour of the Djankuat Glacier, a World Glacier Monitoring Service reference glacier situated in the North Caucasus (Republic of Kabardino-Balkaria, Russian Federation), in response to past, present and future climate conditions (1752–2100 CE). The model consists of a coupled ice flow–mass balance model that also takes into account the evolution of a supraglacial debris cover. After simulation of the past retreat by applying a dynamic calibration procedure, the model was forced with data for the future period under different scenarios regarding temperature, precipitation and debris input. The main results show that the glacier length and surface area have decreased by ca. 1.4 km (ca. −29.5 %) and ca. 1.6 km2 (−35.2 %) respectively between the initial state in 1752 CE and present-day conditions. Some minor stabilization and/or readvancements of the glacier have occurred, but the general trend shows an almost continuous retreat since the 1850s. Future projections using CMIP5 temperature and precipitation data exhibit a further decline of the glacier. Under constant present-day climate conditions, its length and surface area will further shrink by ca. 30 % by 2100 CE. However, even under the most extreme RCP 8.5 scenario, the glacier will not have disappeared completely by the end of the modelling period. The presence of an increasingly widespread supraglacial debris cover is shown to significantly delay glacier retreat, depending on the interaction between the prevailing climatic conditions, the debris input location, the debris mass flux magnitude and the time of release of debris sources from the surrounding topography.

scholarly journals Modelling the evolution of Djankuat Glacier, North Caucasus, from 1752 until 2100 AD

2020 ◽  
Author(s):  
Yoni Verhaegen ◽  
Philippe Huybrechts ◽  
Oleg Rybak ◽  
Victor V. Popovnin
Keyword(s):  
Surface Area ◽  
Calibration Procedure ◽  
Climatic Conditions ◽  
Balance Model ◽  
Climatic Data ◽  
North Caucasus ◽  
Initial State ◽  
Climate Conditions ◽  
The North ◽  
Debris Cover

Abstract. We use a numerical 1.5D model to simulate the behaviour of the Djankuat Glacier, a WGMS reference glacier situated in the North Caucasus (Republic of Kabardino-Balkaria, Russian Federation), in response to past, present and future climate conditions (1752–2100 AD). The model consists of a coupled ice flow−mass balance model that also takes into account the evolution of a supraglacial debris cover. After simulation of the past retreat by applying a dynamic calibration procedure, the model was forced with climatic data for the future period under different scenarios regarding temperature, precipitation and debris input. The main results show that the glacier length and surface area have decreased by 1.4 km and 1.6 km2 respectively between the initial state in 1752 AD and present-day conditions. Some minor stabilization and/or readvancements of the glacier have occurred, but the general trend shows an almost continuous retreat since the 1850s. Future projections exhibit a further decline of the glacier. Under constant present-day climate conditions, its length and surface area will further shrink by ca. 50 % by 2100 AD. However, even under the most extreme RCP 8.5 scenario, the glacier will not have disappeared completely. The presence of an increasingly widespread supraglacial debris cover is shown to significantly delay glacier retreat, depending on the interaction between the prevailing climatic conditions, the debris input location, the debris mass flux magnitude and the time of release of debris sources from the surrounding topography.

Confirmatory Factor Analysis of the Long and Short Forms of the Worry Domains Questionnaire

2009 ◽  
Vol 25 (4) ◽  
pp. 239-243
Author(s):  
Roberto Nuevo ◽  
Andrés Losada ◽  
María Márquez-González ◽  
Cecilia Peñacoba
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Goodness Of Fit ◽  
Factorial Validity ◽  
Fit Indices ◽  
Short Forms ◽  
Confirmatory Factor ◽  
Positive Correlations ◽  
Future Work

The Worry Domains Questionnaire was proposed as a measure of both pathological and nonpathological worry, and assesses the frequency of worrying about five different domains: relationships, lack of confidence, aimless future, work, and financial. The present study analyzed the factor structure of the long and short forms of the WDQ (WDQ and WDQ-SF, respectively) through confirmatory factor analysis in a sample of 262 students (M age = 21.8; SD = 2.6; 86.3% females). While the goodness-of-fit indices did not provide support for the WDQ, good fit indices were found for the WDQ-SF. Furthermore, no source of misspecification was identified, thus, supporting the factorial validity of the WDQ-SF scale. Significant positive correlations between the WDQ-SF and its subscales with worry (PSWQ), anxiety (STAI-T), and depression (BDI) were found. The internal consistency was good for the total scale and for the subscales. This work provides support for the use of the WDQ-SF, and potential uses for research and clinical purposes are discussed.

Ecological specificities of the interaction between animal breeding and climate changes, caused by greenhouse gas emissions

2017 ◽  
Vol 4 (3) ◽  
pp. 62-72
Author(s):  
O. Zhukorsky ◽  
O. Nykyforuk ◽  
N. Boltyk
Keyword(s):  
Greenhouse Gases ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Climatic Conditions ◽  
Animal Breeding ◽  
Gas Emissions ◽  
Climate Conditions ◽  
Emissions Inventory ◽  
Theoretical Substantiation ◽  
Global Problems

Aim. Proper development of animal breeding in the conditions of current global problems and the decrease of anthropogenic burden on environment due to greenhouse gas emissions, caused by animal breeding activity, require the study of interaction processes between animal breeding and external climatic conditions. Methods. The theoretical substantiation of the problem was performed based on scientifi c literature, statistical informa- tion of the UN Food and Agriculture Organization and the data of the National greenhouse gas emissions inventory in Ukraine. Theoretically possible emissions of greenhouse gases into atmosphere due to animal breeding in Ukraine and specifi c farms are calculated by the international methods using the statistical infor- mation about animal breeding in Ukraine and the economic-technological information of the activity of the investigated farms. Results. The interaction between the animal breeding production and weather-and-climate conditions of environment was analyzed. Possible vectors of activity for the industry, which promote global warming and negative processes, related to it, were determined. The main factors, affecting the formation of greenhouse gases from the activity of enterprises, aimed at animal breeding production, were characterized. Literature data, statistical data and calculations were used to analyze the role of animal breeding in the green- house gas emissions in global and national framework as well as at the level of specifi c farms with the consid- eration of individual specifi cities of these farms. Conclusions. Current global problems require clear balance between constant development of sustainable animal breeding and the decrease of the carbon footprint due to the activity of animal breeding.

scholarly journals Relationship between Relative Maturity and Grain Yield of Maize (Zea mays L.) Hybrids in Northwest New Mexico for the 2003–2019 Period

Agriculture ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 290
Author(s):  
Koffi Djaman ◽  
Curtis Owen ◽  
Margaret M. West ◽  
Samuel Allen ◽  
Komlan Koudahe ◽  
...  
Keyword(s):  
New Mexico ◽  
Grain Yield ◽  
Sprinkler Irrigation ◽  
Growing Season ◽  
Climatic Conditions ◽  
Agricultural Science ◽  
Production Optimization ◽  
Science Center ◽  
Early Season ◽  
Climate Conditions

The highly variable weather under changing climate conditions affects the establishment and the cutoff of crop growing season and exposes crops to failure if producers choose non-adapted relative maturity that matches the characteristics of the crop growing season. This study aimed to determine the relationship between maize hybrid relative maturity and the grain yield and determine the relative maturity range that will sustain maize production in northwest New Mexico (NM). Different relative maturity maize hybrids were grown at the Agricultural Science Center at Farmington ((Latitude 36.69° North, Longitude 108.31° West, elevation 1720 m) from 2003 to 2019 under sprinkler irrigation. A total of 343 hybrids were grouped as early and full season hybrids according to their relative maturity that ranged from 93 to 119 and 64 hybrids with unknown relative maturity. The crops were grown under optimal management condition with no stress of any kind. The results showed non-significant increase in grain yield in early season hybrids and non-significant decrease in grain yield with relative maturity in full season hybrids. The relative maturity range of 100–110 obtained reasonable high grain yields and could be considered under the northwestern New Mexico climatic conditions. However, more research should target the evaluation of different planting date coupled with plant population density to determine the planting window for the early season and full season hybrids for the production optimization and sustainability.

Simple Index to Assess the Calibration Quality of Safety Performance Functions Based on Multiple Goodness-of-Fit Metrics

2021 ◽  
pp. 036119812110088
Author(s):  
Raul E. Avelar ◽  
Karen Dixon ◽  
Boniphace Kutela ◽  
Sam Klump ◽  
Beth Wemple ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Synthetic Data ◽  
Calibration Procedure ◽  
Safety Performance ◽  
Absolute Deviation ◽  
Data Set ◽  
Safety Database ◽  
Simple Index ◽  
Safety Performance Functions

The calibration of safety performance functions (SPFs) is a mechanism included in the Highway Safety Manual (HSM) to adjust SPFs in the HSM for use in intended jurisdictions. Critically, the quality of the calibration procedure must be assessed before using the calibrated SPFs. Multiple resources to aid practitioners in calibrating SPFs have been developed in the years following the publication of the HSM 1st edition. Similarly, the literature suggests multiple ways to assess the goodness-of-fit (GOF) of a calibrated SPF to a data set from a given jurisdiction. This paper uses the calibration results of multiple intersection SPFs to a large Mississippi safety database to examine the relations between multiple GOF metrics. The goal is to develop a sensible single index that leverages the joint information from multiple GOF metrics to assess overall quality of calibration. A factor analysis applied to the calibration results revealed three underlying factors explaining 76% of the variability in the data. From these results, the authors developed an index and performed a sensitivity analysis. The key metrics were found to be, in descending order: the deviation of the cumulative residual (CURE) plot from the 95% confidence area, the mean absolute deviation, the modified R-squared, and the value of the calibration factor. This paper also presents comparisons between the index and alternative scoring strategies, as well as an effort to verify the results using synthetic data. The developed index is recommended to comprehensively assess the quality of the calibrated intersection SPFs.

scholarly journals Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3030
Author(s):  
Simon Liebermann ◽  
Jung-Sup Um ◽  
YoungSeok Hwang ◽  
Stephan Schlüter
Keyword(s):  
Neural Network ◽  
Goodness Of Fit ◽  
Renewable Energy Sources ◽  
Weather Conditions ◽  
Solar Irradiation ◽  
Weather Data ◽  
Short Term ◽  
Climate Conditions ◽  
Lstm Network ◽  
The Time Domain

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models’ performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations it shows that combining an LSTM network with a CNN yields the best performance. However, regarding the chosen GoF measures, differences to the alternative approaches are fairly small. The hybrid model’s advantage lies not in the improved GoF but in its versatility: contrary to an LSTM or a CNN, it produces good results under all tested weather conditions.

Psychometric Assessment of the Persian Translated Version of the Romantic Perfectionism Scale Among Couples

2021 ◽  
pp. 003329412110360
Author(s):  
Abbas Abdollahi ◽  
Kelly A. Allen
Keyword(s):  
Content Validity ◽  
Goodness Of Fit ◽  
Factor Loading ◽  
Face Validity ◽  
Fit Indices ◽  
Depression Anxiety Stress Scale ◽  
Confirmatory Factor ◽  
Married Men ◽  
Iranian Version ◽  
Acceptable Internal Consistency

Romantic perfectionismi can be disruptive to relationships, yet no validated measure for assessing romantic perfectionism in Iranian couples has been developed. Therefore, the purpose of this study was to translate and validate the Romantic Perfectionism Scale (RPS) among Iranian couples. Participants in the study were 200 married men and 320 married women from Tehran, Iran, who completed the translated RPS, the Almost Perfect Scale-Revised, and the Depression Anxiety Stress Scale-21 online. Item impact scores were used to calculate face validity. Impact score values for all items were greater than 1.5, signaling appropriate face validity.. The Content Validity Index (CVI) and the Content Validity Ratio (CVR) were used to measure content validity. Values of the CVI were above the cut-off score of 0.7, implying satisfactory content validity of the items. The CVR values were greater than the Lawshe table (0.78) cut-off score, demonstrating that all items were essential. Confirmatory Factor Analysis (CFA) using AMOS software was used to evaluate the construct validity. The results of the goodness of fit indices confirmed the RPS with two subscales (i.e., self-oriented romantic perfectionism and other-oriented romantic perfectionism) as per the original scale. All items remained in the scale as all factor loading values were greater than 0.45. The findings showed that the two subscales, and the scale as a whole, had acceptable internal consistency, as the construct reliability values for self-oriented romantic perfectionism (0.81), other-oriented romantic perfectionism (0.72), and the whole scale (0.74) were greater than 0.7. The results support the psychometric properties of the Iranian version of the RPS, which could be used by future researchers and clinicians to assess romantic perfectionism in Iranian couples.

scholarly journals Quanto Pricing beyond Black–Scholes

2021 ◽  
Vol 14 (3) ◽  
pp. 136
Author(s):  
Holger Fink ◽  
Stefan Mittnik
Keyword(s):  
Option Pricing ◽  
Goodness Of Fit ◽  
Calibration Procedure ◽  
Barrier Options ◽  
Pricing Models ◽  
Modeling Framework ◽  
Double Barrier ◽  
Parameter Stability ◽  
Comprehensive Data ◽  
Black Scholes

Since their introduction, quanto options have steadily gained popularity. Matching Black–Scholes-type pricing models and, more recently, a fat-tailed, normal tempered stable variant have been established. The objective here is to empirically assess the adequacy of quanto-option pricing models. The validation of quanto-pricing models has been a challenge so far, due to the lack of comprehensive data records of exchange-traded quanto transactions. To overcome this, we make use of exchange-traded structured products. After deriving prices for composite options in the existing modeling framework, we propose a new calibration procedure, carry out extensive analyses of parameter stability and assess the goodness of fit for plain vanilla and exotic double-barrier options.

Catchment-scale evaluation of pollution potential of urban snow at two residential catchments in southern Finland

2013 ◽  
Vol 68 (10) ◽  
pp. 2164-2170 ◽  
Author(s):  
Nora Sillanpää ◽  
Harri Koivusalo
Keyword(s):  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Cold Climate ◽  
Road Maintenance ◽  
Catchment Scale ◽  
Small Surface ◽  
Climate Conditions ◽  
Snow Water ◽  
High Level ◽  
Mass Loads

Despite the crucial role of snow in the hydrological cycle in cold climate conditions, monitoring studies of urban snow quality often lack discussions about the relevance of snow in the catchment-scale runoff management. In this study, measurements of snow quality were conducted at two residential catchments in Espoo, Finland, simultaneously with continuous runoff measurements. The results of the snow quality were used to produce catchment-scale estimates of areal snow mass loads (SML). Based on the results, urbanization reduced areal snow water equivalent but increased pollutant accumulation in snow: SMLs in a medium-density residential catchment were two- to four-fold higher in comparison with a low-density residential catchment. The main sources of pollutants were related to vehicular traffic and road maintenance, but also pet excrement increased concentrations to a high level. Ploughed snow can contain 50% of the areal pollutant mass stored in snow despite its small surface area within a catchment.

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