Evapotranspiration from a forest clearcut was measured over two growing seasons as part of a larger study of the microclimate of forest clearcuts and microclimate modification by site preparation. Pinegrass is the dominant species on clearcuts in the dry southern interior and is the major competitor with coniferous seedlings. This paper examines the water use of a pinegrass dominated clearcut and the response of surface conductance to environmental variables. Evapotranspiration was derived from eddy correlation measurements of sensible heat flux and measurements of net radiation and soil heat flux. 419 hours of daytime energy balance data from the summers of 1987 and 1988 were analyzed. A rearranged form of the Penman-Monteith equation was used to calculate hourly mean surface conductances for the clearcut. Leaf area measurements were used to calculate stomatal conductance from surface conductances. Stomatal conductance was modelled using boundary-line and non-linear optimization techniques. The most successful model (R² = 0.71) was obtained using non-linear optimization with stomatal conductance as a non-linear function of saturation deficit at the leaf surface (D₀) and solar irradiance. D₀ was calculated from measured evapotranspiration and surface conductance. Response of stomata to saturation deficit would be expected to be better correlated to D₀ than D measured at a reference height above the canopy. Stomatal conductance was also modelled as a function of D (measured at 1.3 m) and solar irradiance. The resulting model (R² = 0.50) was poor compared to that based on D₀. Saturation deficit and temperature were found to be highly correlated both at 1.3 m above the canopy and at the leaf surface. Use of air temperature in the conductance model caused R² to decrease. No relationship between stomatal conductance and volumetric soil water content was found. Hourly evapotranspiration rates calculated using modelled surface conductances agreed well with measured rates.(R² = 0.89). Evapotranspiration was also modelled using the Priestley-Taylor approach. The mean hourly a for all daylight data was found to be 0.81. This simple model was found to give comparable results to the stomatal conductance based model (R² = 0.85). / Land and Food Systems, Faculty of / Graduate

Orientador: Jansle Vieira Rocha / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola / Made available in DSpace on 2018-08-27T18:50:19Z (GMT). No. of bitstreams: 1 Silva-Fuzzo_DanielaFernandada_D.pdf: 5617023 bytes, checksum: 66aec2c01b924f9a01062f6d76617169 (MD5) Previous issue date: 2015 / Resumo: A agricultura é uma atividade econômica de alta dependência das condições do tempo e do clima e quando associada às geotecnologias espaciais e à modelagem agrometeorológica, permitem otimizar sistemas eficientes para estimativa da produtividade agrícola em escala regional e nacional, permitindo a obtenção de melhores informações. Estimativas precisas vêm surgindo com o avanço tecnológico em sensoriamento remoto; o método do triângulo, baseado em temperatura de superfície e índice de vegetação, vem demonstrando ser uma ferramenta útil para a estimativa de evapotranspiração (EF). Sob essa premissa, o objetivo foi estimar evapotranspiração por meio do método do triângulo, e substituir os valores de evapotranspiração relativa (ETr/ETp) do modelo agrometeorológico de estimativa de produtividade, proposto por Doorenbos e Kassam (1979), pelos valores estimados de EF, ou seja, desta forma o modelo terá somente dados espectrais como variável de entrada. O período de análise foram os anos-safras de 2002/03-2011/12, para o estado do Paraná, Brasil. Os resultados mostraram que o método do triângulo estimou evapotranspiração e validou acuradamente os dados estimados, com os obtidos por balanços hídricos climatológicos de Thorntwaite e Matter (1955), apresentaram, para alguns municípios, valores de "d1" ("d" de Willmott modificado) acima de 0,8, sendo que os valores de R² ficaram aproximadamente entre 0,6 e 0,7; os erros analisados e o teste de Mann-Whitney mostraram que os dados estimados estão muito próximos dos dados observados. Os resultados apresentados referentes ao modelo agrometeorológico foram de d1 entre 0,8 e 0,9 na maioria dos municípios. O RMSE, que indica a acurácia do modelo, mostrou que, em média houve variação entre 30,81 kg/ha a 116,88 kg/ha. O p-valor foi utilizado como indicador da significância do modelo ao nível de 5%, indicando que não houve diferença estatística significativa entre os dados estimados e observados, ou seja, os dados estimados pelo modelo foram estatisticamente iguais à média dos dados observados. Desta forma, imagens de sensoriamento remoto podem ser utilizadas como ferramentas na ausência de informações de superfície, servindo como entrada de dados para auxiliar em modelagem agrometeorológica de estimativa de produtividade agrícola da soja / Abstract: Agriculture is an economic activity with high dependence on weather and climate and when associated with spacial geotechnology and agrometeorological modeling, can optimize the structure more efficient and dynamic to estimate agricultural yield in regional and national systems, allowing obtaining accurate information and cost. Condition of soil moisture is a key parameter in agricultural modeling, which directly influences the exchange of water and energy fluxes between the atmosphere / surface. Accurate estimates are emerging with technological advances in Remote Sensing and Triangle Method based surface temperature and vegetation index, has proven to be a useful tool for estimating evapotranspiration. The objective of this study was to estimate evapotranspiration Fractionated (EF) by the Triangle Method, regionally, and replace the values of Relative Evapotranspiration (ETr/ETp) of agrometeorological model for estimating yield proposed by Doorenbos and Kassam (1979), by valore EF, it means, the model with only spectral data as an input variable. The period of analysis were the crop years 2002/03-2011/12, for the state of Paraná - Brazil. The results showed that the triangle method estimated evapotranspiration and validated accurately the estimated data, with observed data obtained by Balance Water Climatological Thorntwaite and Matter (1955), showed for some counties values of "d1" ("d" modified Willmott) above 0.8, and the R² values were approximately 0.6 and 0.7; the analyzed errors and the Mann-Whitney test showed that the estimated data are very close to the observed data. The results shown for the agro-meteorological model were d1 between 0.8 and 0.9 in most counties. The RMSE, which indicates the accuracy of the model, showed that on average there was variation between 30.81 kg/ha to 116.88 kg/ha. The p-value was used as the indicator significance of the model at the level of 5%, indicating that there was no statistically significant difference between the estimated and observed data, this means that the average of the data estimated by the model were statistically equal the average of the observed data. Thus, we can say that images of Remote Sensing can be used as tools in the absence of surface information, serving as input data to assist in agrometeorological modeling to estimate crop soybean yield / Doutorado / Planejamento e Desenvolvimento Rural Sustentável / Doutora em Engenharia

Wetland ecological function greatly depends on the wetland hydrology. As a result, correctly estimating the wetland water budget, is essential to the success of created wetlands. A wetland water budget model, Wetbud, was developed by collaborators from Virginia Tech, Old Dominion University, and the Technical University of Crete for estimating wetland water budgets to assist wetland design in the Virginia Piedmont. The Wetbud model has basic and advanced modules. The basic module uses level pool routing to compute average monthly water levels. Based on the groundwater model MODFLOW, the advanced module estimates groundwater interactions and vegetative resistance to surface flows on a daily timestep. The overall goal of this research was to assess Wetbud as an uncalibrated design model for mitigation wetland water budget estimation in the Virginia Piedmont. Specific objectives were to compare predictions using the basic and advanced modules and to compare the Thornthwaite and the FAO-56 Penman-Monteith potential evapotranspiration estimation methods for the design of created wetlands. The Wetbud model was tested using data from two existing mitigation wetlands. Both modules produced reasonable results; however, the basic module did not accurately predict drawdown occurring during dry periods. Results showed that the Wetbud advanced module produced more accurate and detailed results when compared to the basic module: Nash-Sutcliffe model efficiency ratings for the advanced module ranged from to 0.44 to 0.63. Potential evapotranspiration estimates by the FAO-56 Penman Monteith method were more accurate than those from the Thornthwaite method in nearly every model scenario / Master of Science

Hydrological changes in catchments world over have affected regional climate and pose serious challenge to future water resource management. The Ganges drainage basin (GDB) is one such region which has undergone rapid transformation in land and water use, more specifically in the latter half of 20th century. GDB has a population of more than half a billion people and is spread across India, China (Tibet), Nepal and Bangladesh. Further, hydrological investigations accounting land and water use changes in GDB are rare. This study is an attempt to resolve hydrological changes in the Ganges basin using the fundamental water balance, focusing particularly on water use changes through irrigation. Between the period 1951-1959 and 1991- 2000, precipitation (P) in the Ganges basin has reduced by 11.25 % while evapotranspiration (ET) has only reduced by 3.61 %. In addition, the ET/P has increased from 0.483 to 0.525 during the same period suggesting a larger partitioning of P towards ET. This suggests greater utilization of P to release water vapor in the atmosphere and thus causing a reduced water flow downstream. With water availability at the fulcrum of future concern for regional and national water security, these findings should encourage policy makers to account for hydrological changes in the GDB in planning sustainable water use.

Modern agriculture, the basis of our civilization, provides sustenance for over 7.9 billion people. However, considering the increasing global population and rising living standards, our food production must to grow by ~50% by 2050. Further constraints of limited arable land, freshwater resources, and the threatening effects of climate change, put our food security at risk and call for multifaceted technological intervention. Currently, irrigated agriculture, while only accounting for 20% of cultivated land, contributes 33%-40% of the total food production. Therefore, irrigated agriculture in arid and semi-arid lands can help us address this complex food–water–climate challenge. However, aridlands are characterized by low precipitation, immense evapotranspiration losses, which is often compensated unsustainably by colossal amounts of freshwater. Evaporation from the topsoil in aridlands remains inadequately tackled. For instance, while plastic mulches have been demonstrated to restrict evaporation, their cost, fragility, lack of reuse, and eventual disposal in landfills limit widespread acceptance. In response, we have conceptualized, developed, and field-tested superhydrophobic sand (SHS), a bio-inspired enhancement of common sand with a nanoscale coating of wax. When a 5-10 mm mulch of SHS is applied on top of subsurface-irrigated soil, the evaporation is dramatically reduced; higher soil moisture boosts plant health, biomass, and yields. Our multi-year field trials of SHS application on tomato (Solanum lycopersicum), barley (Hordeum vulgare), and wheat (Triticum aestivum) crops have consistently demonstrated significant enhancement in grain yields ranging from 17%–73%. In this dissertation, we present our translational surface science research spanning materials development and characterization, mass transfer studies and mathematical modeling, and greenhouse and field experiments. To gain insights into the mulching capacity of water-repellent granular media such as SHS, we present an encompassing novel modeling approach based on particle–particle and liquid–particle forces to accurately capture the fate of evaporating liquid marbles. Then, we explain the origins of SHS superhydrophobicity and provide mechanistic insights into SHS mulching action. Subsequently, we present the data from the field trials to demonstrate how SHS shifts the water balance towards higher crop yields. We close the dissertation with SHS lifecycle analysis and environmental impact and practicality considerations.

This research focused on estimating evapotranspiration (i.e., the amount of water vaporizing into the atmosphere through processes of surface evaporation and plant transpiration) under both theoretical and actual conditions. There were two study areas involved: one, on a large scale where 704 agriculturally-representative, electronic weather stations were used to evaluate the drivers and calculated reference evapotranspiration of a NASA gridded weather forcing model in the 17 western states in the contiguous U.S.; and two, transpiration of invasive saltcedar (Tamarix sp.) in the floodplain of the lower Colorado River, California, with Bowen ratio, eddy covariance, and groundwater fluxes. In this study, a fire destroyed the saltcedar forest, which allowed comparison of evapotranspiration before and after\ this event Comparison of the input weather parameters showed some variance between the electronic weather stations and the gridded model, but calculated reference evapotranspiration performed well by relying on the better input and more highly weighed variables of air temperature and downward shortwave radiation. Only in the southern portions of California, Arizona, and New Mexico were the evapotranspiration estimates using the gridded dataset not well correlated with the electronic weather stations and not recommended for prediction. Saltcedar evapotranspiration was found to match more recent and conservative estimates for the phreatophyte than what was historically portrayed in the literature. Horizontal advection from the surrounding desert was also observed to affect the riparian energy balance. Annual average total evapotranspiration before a fire varied from 0.60-1.44 meters/year to 0.25-1.00 meters/year post fire.

Vineyards are often grown in semi-arid climates, such as California’s central valley, where water resources can be limited. Summer weather conditions result in high water use by these plants. For wine grapes, a high-value commodity, there are known benefits to fruit quality in irrigating grapevines with slightly below optimum for the plant. Growers would like to be able to precisely irrigate without overusing water or overstressing the vines. This calls for improving ways to monitor vineyard water use by estimating the combined soil evaporation and plant transpiration known as evapotranspiration (ET). A computer model developed by the USDA called the Two-Source Energy Balance model (TSEB) can estimate ET through satellite or aircraft measurements of land surface temperature. The model has been successful for simple, uniform vegetation such as maize, soybeans, and grasslands. The ability of TSEB to estimate vineyard ET has been tested through a field experiment called the Grape Remote sensing, Atmospheric Profile,& Evapotranspiration eXperiment or GRAPEX. Water is primarily transported away from the ground and plants by turbulent swirls in the wind. Models such as TSEB assume these swirls occur in a consistent manner over a few minutes to hours. Yet, interactions between the wind, the complex vineyard canopy, and heating near the ground can cause them to be episodic or intermittent. There are questions of if and how intermittent water vapor transport might happen in vineyards, and whether the TSEB model will still estimate ET well in such cases. In this study wind, humidity, air temperature, and surface temperatures are used to examine when intermittent behavior occurs, how it affects ET from the vineyard canopy, and how TSEB performs for intermittent versus more steady conditions. Results show that intermittent turbulence significantly alters the microclimate in the vineyard canopy compared to more ideal, steady behavior. The TSEB model was successful but showed reduced ability to estimate ET during times of intermittent behavior. The knowledge gained is an important step toward using TSEB as a powerful tool for sustainable water management, not only in vineyards, but other cash crops with complicated canopies such as orchards, as well as natural ecosystems.

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Over the coming decades, both food consumption and agricultural water use are expected to increase in response to growing populations. In light of these concerns, there has been a growing awareness and appreciation of the objectives of agricultural sustainability, which has the broad aim of securing food and water resources, without adversely affecting the environment or disenfranchising future generations. To ensure that irrigated fields optimize their water use towards a more sustainable application while remaining compliant with any imposed restrictions on access to water supplies (i.e. through water licensing), it is necessary to understand and quantify the water consumption of crops at appropriate spatial and temporal scales. Evaporation (E), also commonly referred to as evapotranspiration (ET), is the physical process of water vapor transport from the surface into the atmosphere. Evaporation can be estimated via interpretive modeling approaches that combine meteorological, radiative, vegetation, and other related properties to estimate land surface fluxes at any given time. The research presented herein aims to investigate the evaporative response of agricultural croplands across a range of spatial and temporal scales, with a focus on high-resolution and field-scale estimation. In particular, we explore the utility of novel CubeSat imagery to produce the highest spatial resolution (3 m) crop water use estimates ever retrieved from space. These high-resolution results are expanded through time by retrieving a daily evaporation product, offering an enhanced capacity to provide new insights into precision agriculture. The effects and implications of higher spatiotemporal resolutions are explored and contrasted against governmental satellite missions that operate at lower resolutions. An exploratory study on the use of unmanned aerial vehicles (UAVs) is also performed, specifically in the context of their capacity to mount miniaturized thermal sensors: with the accuracy and limitations of these sensors for deriving evaporation-type products examined. The overarching goal of this research is to advance the utility of space-based estimates of evaporation for precision agricultural applications, and to provide new high-spatial and temporal agricultural insights that can be directed towards improving water management and address food security concerns in a more sustainable manner.