KcMod: a crop coefficient model

This Program was written in July 2009 (by R.L. Snyder and A. Swelam), and revised in July 2010 and 2018 (by R.L. Snyder and E. Guerra). It aims to provide a practical tool for crop coefficient calculation according to local climate conditions, for both academic and non academic purposes. Part of the same study is published online and can be found at the following web pages: Crop Coefficients: A Literature Review Journal of Irrigation and Drainage EngineeringMarch 2016 Volume 142, Issue 3. Online publication date: December 23, 2015 https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29IR.1943-4774.0000983 This publication includes the Kc data base and the Kc Report as supplemental material. Correcting Midseason Crop Coefficients for Climate Journal of Irrigation and Drainage EngineeringJune 2015 Volume 141, Issue 6. Online publication date: November 07, 2014 https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29IR.1943-4774.0000839 The book about the entire PhD thesis is available on: https://www.scholars-press.com

Statistical and Deep Learning Models for Reference Evapotranspiration Time Series Forecasting: A Comparison of Accuracy, Complexity, and Data Efficiency

Reference evapotranspiration (ETo) is an essential variable in agricultural water resources management and irrigation scheduling. An accurate and reliable forecast of ETo facilitates effective decision-making in agriculture. Although numerous studies assessed various methodologies for ETo forecasting, an in-depth multi-dimensional analysis evaluating different aspects of these methodologies is missing. This study systematically evaluates the complexity, computational cost, data efficiency, and accuracy of ten models that have been used or could potentially be used for ETo forecasting. These models range from well-known statistical forecasting models like seasonal autoregressive integrated moving average (SARIMA) to state-of-the-art deep learning (DL) algorithms like temporal fusion transformer (TFT). This study categorizes monthly ETo time series from 107 weather stations across California according to their length to better understand the forecasting models\u27 data efficiency. Moreover, two forecasting strategies (i.e., recursive and multi-input multi-output) are employed for machine learning and DL models, and forecasts are assessed for different multi-step horizons. Our findings show that statistical forecasting models like Holt-Winters\u27 exponential smoothing perform almost as well as complex DL models. Unlike statistical models, DL models generally suffer from low data efficiency and perform well only when enough data is available. Importantly, although the computational costs of most DL models are higher than statistical methods, this is not the case for all. Considering computational cost, data efficiency, and forecasting accuracy, our findings point to the superiority of the neural basis expansion analysis for interpretable time series forecasting (N-BEATS) architecture for univariate ETo time series forecasting. Moreover, our results suggest Holt-Winters and Theta methods outperform SARIMA – the most employed statistical model for ETo forecasting in the literature – in accuracy and efficiency

Responses of reference evapotranspiration to changes in atmospheric humidity and air temperature in Spain

We studied the sensitivity of reference evapotranspiration (ETo) to global warming in Spain at the end of the 21st century. The FAO-56 Penman-Monteith equation was used to estimate ETo, and we examined the sensitivity of the latter to changes in temperature and relative humidity. Changes in stomatal resistance in response to increased CO2 concentration were not evaluated, nor were the changes in wind velocity and solar radiation. Different scenarios were used for estimation of future ETo in different river basins as a consequence of trends in the maximum and minimum temperatures and maximum and minimum humidities during the period 1973–2002, as observed from 38 meteorological stations. The temperature increases ranged between 0.3 and 0.7°C decade – 1 , and the relative humidities fluctuated between 0.1 and –3.7% decade – 1 Four scenarios were simulated that . considered the variations in linear tendency of the maximum and minimum temperatures and maximum and minimum relative humidities. The trends of the 4 scenarios were incorporated with the data from 338 agrometeorological stations to estimate future ETo. In all cases, there was an annual increase in ETo of 11, 21, 36 and 7% above the annual ETo (1196 mm) for Scenarios 0, 1, 2 and 3, respectively. The river basin most affected by these changes was the Ebro River valley. The most affected months were May, June, July and August, while the least affected months were November, December and Januar

A numerical model for tracking populations through a time-dependent stochastic network

Units from a population arrive from an external source in a random or fixed pattern at an initial compartment of a D-compartment, linked, network. Once inside the network, individuals move in a statistically independent manner among compartments, finally entering absorbing compartments from which they never depart. A numerical adaptation of the model is described and demonstrated. The model is compared to the MacArthur-Wilson model of island biogeography with respect to differences in statistics of movements that each model is capable of generating. A numerical example is given.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31702/1/0000638.pd

The Ursinus Weekly, December 31, 1928

Ursinus debating league holds ninth conference • Debating very practical; a ladder to success • Some objections answered with a desire to help • The best ways to refute an opponents arguments • A baker\u27s dozen of helps for the young debater • How to fit debating into high school curriculum • How to get out audiences for our league debates • Report for last season: eleven trophies given • Importance of delivery in high school debatinghttps://digitalcommons.ursinus.edu/weekly/2170/thumbnail.jp

Future reference evapotranspiration in Duero Valley (Spain)

The impact of climate change and its relation with evapotranspiration was evaluated in the Duero River Basin (Spain). The study shows the possible future situations 50 years from now from the reference evapotranspiration (ETo). The maximum temperature (Tmax), minimum temperature (Tmin), dew point (Td), wind speed (U) and net radiation (Rn) trends during the 1980-2009 period were obtained and extrapolated with the FAO-56 Penman- Montheith equation to estimate ETo. Changes in stomatal resistance in response to increases in CO2 were also considered. Four scenarios were done, considering the concentration of CO2 and the period analyzed (annual or monthly). The scenarios studied showed the changes in ETo as a consequence of the annual and monthly trends in the variables Tmax, Tmin, Td, U and Rn with current and future CO2 concentrations (372 ppm and 550 ppm). The future ETo showed increases between 118 mm (11%) and 55 mm (5%) with respect to the current situation of the river basin at 1042 mm. The months most affected by climate change are May, June, July, August and September, which also coincide with the maximum water needs of the basin?s crop

Trends in climatic variables and future reference evapotranspiration in Duero Valley (Spain)

The impact of climate change and its relation with evapotranspiration was evaluated in the Duero River Basin (Spain). The study shows possible future situations 50 yr from now from the reference evapotranspiration (ETo). The maximum temperature (Tmax), minimum temperature (Tmin), dew point (Td), wind speed (U) and net radiation (Rn) trends during the 1980–2009 period were obtained and extrapolated with the FAO-56 Penman-Montheith equation to estimate ETo. Changes in stomatal resistance in response to increases in CO2 were also considered. Four scenarios were done, taking the concentration of CO2 and the period analyzed (annual or monthly) into consideration. The scenarios studied showed the changes in ETo as a consequence of the annual and monthly trends in the variables Tmax, Tmin, Td, U and Rn with current and future CO2 concentrations (372 ppm and 550 ppm). The future ETo showed increases between 118 mm (11 %) and 55 mm (5 %) with respect to the current situation of the river basin at 1042 mm. The months most affected by climate change are May, June, July, August and September, which also coincide with the maximum water needs of the basin’s crop

Impacts of climate change and rising atmospheric CO2 on future projected reference evapotranspiration in Emilia-Romagna (Italy)

The continuous increase of atmospheric CO2 content mainly due to anthropogenic CO2 emissions is causing a rise in temperature on earth, altering the hydrological and meteorological processes and affecting crop physiology. Evapotranspiration is an important component of the hydrological cycle. Thus, understanding the change in evapotranspiration due to global warming is essential for better water resources planning and management and agricultural production. In this study, the effect of climate change with a focus on the combined effect of temperature and elevated CO2 concentrations on reference evapotranspiration (ETo) was evaluated using the Penman–Monteith equation. A EURO-CORDEX regional climate model (RCM) ensemble was used to estimate ETo in five locations in the Emilia-Romagna region (Northern Italy) during the period 2021–2050. Then, its projected changes in response to different CO2 concentrations (i.e., 372 ppm and 550 ppm) under two Representative Concentration Pathways (RCP) scenarios (i.e., RCP4.5 and RCP8.5) were analyzed. Simulation results with both scenarios, without increasing CO2 levels (372 ppm), showed that the annual and summertime ETo for all locations increased by an average of 4 to 5.4% with regard to the reference period 1981–2005, for an increase of air temperature by 1 to 1.5 °C. When the effect of elevated CO2 levels (550 ppm) was also considered in combination with projected changes in temperature, changes in both annual and summer ETo demand for all locations varied from − 1.1 to 2.2% during the 2021–2050 period with regard to the reference period 1981–2005. This shows that higher CO2 levels moderated the increase in ETo that accompanies an increase in air temperature

Important factors to model climate change effects on evapotranspiration

Although growers have considerable control over crop production, a major concern is the anticipated increase in evapotranspiration (ET) due to global warming. ET rates, however, are also affected by radiation, humidity, wind speed, crop morphology, and crop physiology in addition to temperature. Crop ET (ETc) is commonly estimated as the product of reference ET (ET0) and a crop coefficient (Kc), and the main factors affecting Kc values are net radiation, aerodynamic resistance, and canopy resistance differences between the reference and crop surfaces. The standardized ET0 equation has fixed values for the canopy resistance (rc), and different values are likely for other crops. The rc values might also adjust with increasing CO2 and higher temperature. Aerodynamic resistance (ra) depends on atmospheric stability, wind speed, and surface roughness. The relative aerodynamic contributions of sensible heat to ET0 and ETc could change if the canopy development or the wind speed climatology are modified by global warming. In this paper, we will discuss how the ET0 and Kc values vary with microclimate and how Kc values and ET0 rates might react to global warming

Apportionment of primary and secondary organic aerosols in Southern California during the 2005 Study of Organic Aerosols in Riverside (SOAR-1)

Ambient sampling was conducted in Riverside, California during the 2005 Study of Organic Aerosols in Riverside to characterize the composition and sources of organic aerosol using a variety of state-of-the-art instrumentation and source apportionment techniques. The secondary organic aerosol (SOA) mass is estimated by elemental carbon and carbon monoxide tracer methods, water soluble organic carbon content, chemical mass balance of organic molecular markers, and positive matrix factorization of high-resolution aerosol mass spectrometer data. Estimates obtained from each of these methods indicate that the organic fraction in ambient aerosol is overwhelmingly secondary in nature during a period of several weeks with moderate ozone concentrations and that SOA is the single largest component of PM1 aerosol in Riverside. Average SOA/OA contributions of 70−90% were observed during midday periods, whereas minimum SOA contributions of ~45% were observed during peak morning traffic periods. These results are contrary to previous estimates of SOA throughout the Los Angeles Basin which reported that, other than during severe photochemical smog episodes, SOA was lower than primary OA. Possible reasons for these differences are discussed