scholarly journals An effective evapotranspiration estimation scheme based on statistical indicators for sustainable environments in humid and semi-arid area of Khyber Pakhtunkhwa, Pakistan

2021 ◽  
Author(s):  
Sajid Gul ◽  
Jingli Ren ◽  
Neal N. Xiong ◽  
Muhammad Fawad
Keyword(s):  
Environmental Parameters ◽  
Absolute Error ◽  
Irrigated Agriculture ◽  
Local Climate ◽  
Khyber Pakhtunkhwa ◽  
Irrigation Design ◽  
Wide Range ◽  
Estimation Scheme ◽  
Evapotranspiration Estimation ◽  
Semi Arid

Abstract Reference evapotranspiration (ETo) is critical for irrigation design and water management in rainfed and irrigated agriculture. The Penman-Monteith (FAO-56(PM)) equation was demonstrated to be the most reliable and adaptive to a wide range of humid to semi-arid climates. However, it requires several environmental parameters (e.g., wind speed, solar radiation), rarely available in developing countries. Therefore, numerous temperature-based formulas have been designed to address this issue for various environments. Their calibration and validation against the local climate frequently lead to increases in performance. We revised the Hargreaves exponent (EH) and substituted a value of (0.16) for the original value (0.5). The modified Hargreaves formula enhances the ETo predictions with a mean absolute error ranging from (0.791) mm per day for Balakot to (2.36) mm per day in Risalpur, averaging (3.797) mm per day, as compared to the Hargreaves-Samani (16.827) mm per day. In general, all the selected models showed high accuracy. However, the modified Hargreaves equation appeared to be the most promising results. It ranked first in (50%) of the whole area based on the standard error of estimate for estimating ETo in Khyber Pakhtunkhwa. Additional research must be conducted to determine the study's relevance to other regions.

Understanding Conformational Entropy in Small Molecules

2020 ◽  
Author(s):  
Lucian Chan ◽  
Garrett Morris ◽  
Geoffrey Hutchison
Keyword(s):  
Small Molecules ◽  
Degrees Of Freedom ◽  
Absolute Error ◽  
Low Energy ◽  
Standard Entropy ◽  
Free Energies ◽  
Conformational Entropy ◽  
Wide Range ◽  
High Degree ◽  
Empirical Corrections

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Forecasting the impacts of climate variability: lessons from the rainfed corn market in Ceará, Brazil

2008 ◽  
Vol 13 (2) ◽  
pp. 201-227 ◽  
Author(s):  
ARIASTER B. CHIMELI ◽  
FRANCISCO DE ASSIS DE SOUZA FILHO ◽  
MARCOS COSTA HOLANDA ◽  
FRANCIS CARLO PETTERINI
Keyword(s):  
Climate Variability ◽  
Developing Economies ◽  
Arid Zone ◽  
Well Being ◽  
Policy Makers ◽  
Local Climate ◽  
The World ◽  
Forecast Models ◽  
Climatic Impacts ◽  
Semi Arid

ABSTRACTA number of studies show that climatic shocks have significant economic impacts in several regions of the world, especially in, but not limited to, developing economies. In this paper we focus on a drought-related indicator of well-being and emergency spending in the Brazilian semi-arid zone – rainfed corn market – and estimate aggregate behavioral and forecast models for this market conditional on local climate determinants. We find encouraging evidence that our approach can help policy makers buy time to help them prepare for drought mitigating actions. The analysis is applicable to economies elsewhere in the world and climatic impacts other than those caused by droughts.

scholarly journals Comparative verification in complex topography

2021 ◽  
Author(s):  
Jonas Bhend ◽  
Jean-Christophe Orain ◽  
Vera Schönenberger ◽  
Christoph Spirig ◽  
Lionel Moret ◽  
...  
Keyword(s):  
Weather Forecasting ◽  
Absolute Error ◽  
Time Of Day ◽  
Probabilistic Forecasts ◽  
Wide Range ◽  
Direct Model ◽  
Forecasting System ◽  
The Mean ◽  
Update Frequency ◽  
Core Activity

<p>Verification is a core activity in weather forecasting. Insights from verification are used for monitoring, for reporting, to support and motivate development of the forecasting system, and to allow users to maximize forecast value. Due to the broad range of applications for which verification provides valuable input, the range of questions one would like to answer can be very large. Static analyses and summary verification results are often insufficient to cover this broad range. To this end, we developed an interactive verification platform at MeteoSwiss that allows users to inspect verification results from a wide range of angles to find answers to their specific questions.</p><p>We present the technical setup to achieve a flexible yet performant interactive platform and two prototype applications: monitoring of direct model output from operational NWP systems and understanding of the capabilities and limitations of our pre-operational postprocessing. We present two innovations that illustrate the user-oriented approach to comparative verification adopted as part of the platform. To facilitate the comparison of a broad range of forecasts issued with varying update frequency, we rely on the concept of time of verification to collocate the most recent available forecasts at the time of day at which the forecasts are used. In addition, we offer a matrix selection to more flexibly select forecast sources and scores for comparison. Doing so, we can for example compare the mean absolute error (MAE) for deterministic forecasts to the MAE and continuous ranked probability scores of probabilistic forecasts to illustrate the benefit of using probabilistic forecasts.</p>

scholarly journals Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World

2021 ◽  
Vol 13 (19) ◽  
pp. 3865
Author(s):  
Yongqiang Zhang ◽  
Dongryeol Ryu ◽  
Donghai Zheng
Keyword(s):  
Remote Sensing ◽  
Anthropogenic Impacts ◽  
The Earth ◽  
Wide Range ◽  
Important Challenge ◽  
Flood Simulations ◽  
Remote Sensing Techniques ◽  
Evapotranspiration Estimation ◽  
Ecohydrological Processes ◽  
Changing World

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions, on how to make the most out of the state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world.

Factors contributory to fire occurrences in two populated areas in the American southwest

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Susanna T.Y. Tong ◽  
Shitian Wan ◽  
Yuhe Gao
Keyword(s):  
Population Growth ◽  
Fire Regimes ◽  
American Southwest ◽  
Arid Areas ◽  
Vegetative Cover ◽  
Content Type ◽  
Clark County ◽  
Temporal Relationships ◽  
Wide Range ◽  
Semi Arid

PurposeThis study aims to further understand the factors contributory to fire occurrences in two semi-arid regions in the American Southwest, Clark County in Nevada and Maricopa and Pinal Counties in Arizona.Design/methodology/approachStatistical and geographic information system analyses were employed to examine the spatial and temporal relationships of various natural and human-caused factors with fire incidences.FindingsAngström fire danger index, average amount of rainfall one month prior, extent of forests and grasslands, and proximities to secondary roads and population centers have significant relationships with fire events.Research limitations/implicationsThe importance of the factors contributory to fire occurrence is site-specific even in areas with similar climatic regimes and varies among different geographic regions; as such, researchers will need to conduct specific investigation of each study area.Practical implicationsThe findings of this study can be instrumental in facilitating fire managers to derive more informed strategies in fire prevention and management.Originality/valueWhile there are many studies on fire, most of them are conducted in wet regions with a lot of vegetative cover; not much work is done on arid areas. This paper considered and compared the spatial and temporal relationships of a wide range of natural and human-caused factors with fire events in two semi-arid areas. The intent was to assess the relative importance of these factors in areas even with similar climatic regimes. As our world is facing unprecedented changes in terms of climate and population growth, it is paramount to have an enhanced understanding of the impacts of these changes on fire regimes. The study areas are hot and dry, and they are located in the wildland–urban interfaces with rapid population growth and urbanization; as such, the research findings may contribute to existing literature.

Understanding Conformational Entropy in Small Molecules

2021 ◽  
Author(s):  
Lucian Chan ◽  
Garrett Morris ◽  
Geoffrey Hutchison
Keyword(s):  
Small Molecules ◽  
Degrees Of Freedom ◽  
Absolute Error ◽  
Low Energy ◽  
Standard Entropy ◽  
Free Energies ◽  
Conformational Entropy ◽  
Wide Range ◽  
High Degree ◽  
Empirical Corrections

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Support Irrigation Water Management of Cereals Using Optical Remote Sensing and Modeling in a Semi-Arid Region

2019 ◽  
pp. 124-145 ◽  
Author(s):  
Tarik Benabdelouahab ◽  
Hayat Lionboui ◽  
Rachid Hadria ◽  
Riad Balaghi ◽  
Abdelghani Boudhar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Near Infrared ◽  
Irrigated Agriculture ◽  
Optical Remote Sensing ◽  
Crop Modeling ◽  
Management Tools ◽  
Irrigated Perimeter ◽  
Semi Arid Region ◽  
Semi Arid

Irrigated agriculture is an important strategic sector for Morocco, contributing to food security and employment. Nowadays, irrigation scheme managers shall ensure that water is optimally used. The main objective was to support the irrigation monitoring and management of wheat in the irrigated perimeter using optical remote sensing and crop modeling. The potential of spectral indices derived from SPOT-5 images was explored for quantifying and mapping surface water content changes at large scale. Indices were computed using the reflectance in red, near infrared, and shortwave infrared bands. A field crop model (AquaCrop) was adjusted and tested to simulate the grain yield and the temporal evolution of soil moisture status. This research aimed at providing a scientific and technical approach to assist policymakers and stakeholders to improve monitoring irrigation and mitigating wheat water stress at field and irrigation perimeter levels in semi-arid areas. The approach could lead to operational management tools for an efficient irrigation at field and regional levels.

scholarly journals Trends and Challenges in Irrigation Scheduling in the Semi-Arid Area of Spain

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 785 ◽  
Author(s):  
Irene Fernández García ◽  
Sergio Lecina ◽  
M. Carmen Ruiz-Sánchez ◽  
Juan Vera ◽  
Wenceslao Conejero ◽  
...  
Keyword(s):  
Irrigation System ◽  
Irrigation Scheduling ◽  
Living Standards ◽  
Spatiotemporal Variability ◽  
Irrigated Agriculture ◽  
Decision Making Processes ◽  
Current Water ◽  
Economic Capacity ◽  
Review Current ◽  
Semi Arid

A growing international human population and rising living standards are increasing the demand for agricultural products. Under higher pressure over natural resources, environmental concerns are increasing as well, challenging current water use decision-making processes in irrigated agriculture. Higher agricultural productivity means water should be applied more efficiently, which requires instant information on weather, soil, and plant conditions throughout the growing season. An information-based irrigation scheduling application tightened to the spatiotemporal variability of the fields is critical for enhancing the current irrigation system and making better irrigation scheduling decisions. The aim of this study is to review current irrigation scheduling methodologies based on two case studies (woody and field crops) located in semi-arid areas of Southeast Spain. We realize that optimal irrigation programming requires consistent investment in equipment, expenditure on operation and maintenance, and qualified technical and maintenance services. These technological approaches will be worthwhile in farms with low water availability, high profitability, and significant technical-economic capacity.

scholarly journals Non-contact vital-sign monitoring of patients undergoing haemodialysis treatment

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mauricio Villarroel ◽  
João Jorge ◽  
David Meredith ◽  
Sheera Sutherland ◽  
Chris Pugh ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Reference Values ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Recording Time ◽  
Wide Range ◽  
Auto Regressive ◽  
The Mean ◽  
Haemodialysis Treatment

Abstract A clinical study was designed to record a wide range of physiological values from patients undergoing haemodialysis treatment in the Renal Unit of the Churchill Hospital in Oxford. Video was recorded for a total of 84 dialysis sessions from 40 patients during the course of 1 year, comprising an overall video recording time of approximately 304.1 h. Reference values were provided by two devices in regular clinical use. The mean absolute error between the heart rate estimates from the camera and the average from two reference pulse oximeters (positioned at the finger and earlobe) was 2.8 beats/min for over 65% of the time the patient was stable. The mean absolute error between the respiratory rate estimates from the camera and the reference values (computed from the Electrocardiogram and a thoracic expansion sensor—chest belt) was 2.1 breaths/min for over 69% of the time for which the reference signals were valid. To increase the robustness of the algorithms, novel methods were devised for cancelling out aliased frequency components caused by the artificial light sources in the hospital, using auto-regressive modelling and pole cancellation. Maps of the spatial distribution of heart rate and respiratory rate information were developed from the coefficients of the auto-regressive models. Most of the periods for which the camera could not produce a reliable heart rate estimate lasted under 3 min, thus opening the possibility to monitor heart rate continuously in a clinical environment.

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