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Reliable estimates of evaporative water loss are required to assess the urban water budget in support of division of water resources among various needs, including heat mitigation measures in cities relying on evaporative cooling....
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Reliable estimates of evaporative water loss are required to assess the urban water budget in support of division of water resources among various needs, including heat mitigation measures in cities relying on evaporative cooling. We report on urban evaporative water loss from Arnhem and Rotterdam in the Netherlands, using eddy covariance, scintillometer and sapflow observations. Evaporation is assessed at daily to seasonal and annual timescale. For the summer half-year (April-September), observations from Arnhem and Rotterdam are consistent regarding magnitude and variability of evaporation that typically varies between 0.5 and 1.0 mm of evaporation per day. The mean daily evaporative cooling rate was 20 -25 Wm~(-2),11-14% of the average incoming solar radiation. Evaporation by trees related to sapflow was found to be a small term on the water budget at the city or neighbourhood scale. However, locally the contribution may be significant, given observed maxima of daily sap flows up to 170 1 per tree. In Arnhem, evaporation is strongly linked with precipitation, possibly owing to building style. During the summer season, 60% of the precipitation evaporated again. In Rotterdam, the link between evaporation and precipitation is much weaker. An analysis of meteorological observations shows that estimation of urban evaporation from routine weather data using the concept of reference evaporation would be a particularly challenging task. City-scale evaporation may not scale with reference evaporation and the urban fabric results in strong microweather variability. Observations like the ones presented here can be used to evaluate and improve methods for routine urban evaporation estimates.
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The most precise equation in order to estimate the evapotranspiration (ET) of crops is the Penman-Monteith (PM). However, the PM equation needs specific data that, in the majority of Mexico's irrigation districts, it is not availa...
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The most precise equation in order to estimate the evapotranspiration (ET) of crops is the Penman-Monteith (PM). However, the PM equation needs specific data that, in the majority of Mexico's irrigation districts, it is not available because there are few automated weather stations. For this reason, it is convenient to develop simple methods that allow to precise estimation of ET. A reliable way to estimate ET is by using the pan evaporation that, according to the revised literature, continues to be used nowadays. Investigators like to include its use in irrigation water management projects in various parts of the world. However, this method uses Kp from the FAO that is not calibrated in Mexico. The use of FAO Kp affects the precision of the results, since some variables like radiation, wind, temperature and relative humidity vary from place to place; therefore ET is under estimated or overestimated. This paper presents an original contribution across method to estimate "Kp pan evaporation and ETo monthly maps", using information from 60 weather observatories included in The Climate Normals (1941-1970) from Mexico, based on the PM method and the class A pan evaporation. Once the Kp values were obtained from each weather observatory, the Kringing method was used. This way, by interpolating data of the triad "latitude, longitude and Kp" and "latitude, longitude and ET", monthly normalized maps of Kp and ET were established for Mexico, except the upland areas (Sierra Madre Occidental and Sierra Madre Oriental), as well as other highland zones above 2700 meters over sea level, for the highest observatory is located in Toluca, State of Mexico (key 14-0039), at 2680 m over sea level.
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In a globally warming climate, observed rates of atmospheric evaporative demand have declined over recent decades. Several recent studies have shown that declining rates of evaporative demand are primarily governed by trends in th...
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In a globally warming climate, observed rates of atmospheric evaporative demand have declined over recent decades. Several recent studies have shown that declining rates of evaporative demand are primarily governed by trends in the aerodynamic component (primarily being the combination of the effects of wind speed (u) and atmospheric humidity) and secondarily by changes in the radiative component. A number of these studies also show that declining rates of observed near-surface u (termed 'stilling') is the primary factor contributing to declining rates of evaporative demand. One objective of this paper was to review and synthesise the literature to assess whether stilling is a globally widespread phenomenon. We analysed 148 studies reporting terrestrial u trends from across the globe (with uneven and incomplete spatial distribution and differing periods of measurement) and found that the average trend was -0.014ms ~(-1)a ~(-1) for studies with more than 30 sites observing data for more than 30years, which confirmed that stilling was widespread. Assuming a linear trend this constitutes a -0.7ms ~(-1) change in u over 50years. A second objective was to confirm the declining rates of evaporative demand by reviewing papers reporting trends in measured pan evaporation (E _(pan)) and estimated crop reference evapotranspiration (ET _o); average trends were -3.19mma ~(-2) (n=55) and -1.31mma ~(-2) (n=26), respectively. A third objective was to assess the contribution to evaporative demand trends that the four primary meteorological variables (being u; atmospheric humidity; radiation; and air temperature) made. The results from 36 studies highlighted the importance of u trends. We also quantified the sensitivity of rates of evaporative demand to changes in u and how the relative contributions of the aerodynamic and radiative components change seasonally over the globe. Our review: (i) shows that terrestrial stilling is widespread across the globe; (ii) confirms declining rates of evaporative demand; and (iii) highlights the contribution u has made to these declining evaporative rates. Hence we advocate that assessing evaporative demand trends requires consideration of all four primary meteorological variables (being u, atmospheric humidity, radiation and air temperature). This is particularly relevant for long-term water resource assessment because changes in u exert greater influence on energy-limited water-yielding catchments than water-limited ones.
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Daily evapotranspiration (ET) integration is essential to various applications of agricultural water planning and management, ecohydrology, and energy balance studies. The constant reference evaporative fraction (EFr) temporal ups...
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Daily evapotranspiration (ET) integration is essential to various applications of agricultural water planning and management, ecohydrology, and energy balance studies. The constant reference evaporative fraction (EFr) temporal upscaling method has been proven to be efficient in extrapolating instantaneous ET to a daily timescale. Unlike upscaling methods, the direct calculation (DC) method developed in our previous study directly estimates daily ET without calculating instantaneous ET. The present study aimed to compare daily estimations of ET using the EFr and DC methods based on field and MODIS data at a site from the ChinaFLUX network. The estimation results were validated by eddy covariance (EC) ET both with and without the correction of energy imbalance. Based on field data, the results show that (i) the DC method performed with higher accuracy when compared to uncorrected EC measurements, while daily ET from both methods was overestimated; (ii) the DC method still performed better after the EC ET was corrected by the Residual Energy scheme, and the overestimations were significantly decreased; (iii) both methods performed best when compared with corrected ET by the Bowen Ratio scheme. The results from satellite data reveal that (i) the constant EFr method overestimated daily ET by a mean-bias-error (MBE) of 5.6 W/m2, and a root-mean-square error (RMSE) of 18.6 W/m2; and (ii) the DC method underestimated daily ET by a smaller MBE of ?4.8 W/m2 and an RMSE of 22.5 W/m2. Therefore, the DC method has similar or better performance than the widely used constant EFr upscaling method and can estimate daily ET directly and effectively.
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Study regionGreat Lakes region of North AmericaStudy focusReference Evapotranspiration (ETo) is a key variable in water use management and irrigation of agricultural crops. This study describes the development of a gridded histori...
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Study regionGreat Lakes region of North AmericaStudy focusReference Evapotranspiration (ETo) is a key variable in water use management and irrigation of agricultural crops. This study describes the development of a gridded historical ETo dataset for the period 1983–2012 derived from North American Data Assimilation System Phase 2 (NLDAS-2) forcing fields for the Great Lakes region of North America. The gridded dataset is intended to fill a gap in the resource toolbox available to growers in this region of rapidly expanding irrigation. As a prerequisite for development of the ETo dataset, a correction procedure is applied to the NLDAS-2 downward solar radiation to account for overall bias and a tendency to underestimate the range of solar radiation on hourly and daily timescales.New hydrological insightsAnalyses of spatial and temporal variability reveal that the lakes play an important role in modulating seasonal and geographical variability in evaporative demand. An example application of the gridded historical ETo dataset to irrigation management is provided. A 30-year climatology of crop irrigation for field maize is developed from the ETo dataset and is applied in a hypothetical irrigation-scheduling scenario. Overall, the study illustrates the utility of the NLDAS-2 ETo dataset in describing spatial and temporal patterns of evaporative demand across the Great Lakes region, and as a source of reference climatological information for irrigation management.
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Evapotranspiration (ETo) forecasts can play an important role in irrigation scheduling and water resource management. Three state-of-the-art deep learning models, including long short-term memory (LSTM), one-dimensional convolutio...
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Evapotranspiration (ETo) forecasts can play an important role in irrigation scheduling and water resource management. Three state-of-the-art deep learning models, including long short-term memory (LSTM), one-dimensional convolutional neural networks (1D-CNN), and convolutional LSTM (ConvLSTM), were tested to forecast ETo on a daily time scale for seven days period. Daily air temperature (maximum, minimum and mean values), solar radiation, relative humidity, and wind speed data were collected for the 2011-2017 period from three weather stations (Harrington, North Cape, and Saint Peters) across Prince Edward Island (PEI), Canada. The relative importance method was used to determine the best-suited input variables for the models. The deep learning models were evaluated with the walk-forward validation technique using statistical measures of root mean square error (RMSE) and coefficient of determination (R-2). The FAO Penman-Monteith modified equation (FAO-56) was used as the reference method for comparison purposes. For calibration and validation evaluation in annually daily ETo forecasts, the hybrid ConvLSTM model recorded lower errors than CNN and LSTM with the lowest calibration and validation daily RMSE of 0.64 and 0.62, 0.81 and 0.81, and 0.81 and 0.70 mm/day for Harrington, North Cape, and Saint Peters weather stations, respectively. The robustness and accuracy of these forecasted models may help farmers, water resource managers, and irrigation planners with improved and sustainable water management at the basin level, and for irrigation scheduling at farm/field level.
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As an important constituent of hydrological cycle, estimation of Reference Evapotranspiration (ETo) is essential for planning of projects related to water resources. This article compares the results obtained from the available pa...
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As an important constituent of hydrological cycle, estimation of Reference Evapotranspiration (ETo) is essential for planning of projects related to water resources. This article compares the results obtained from the available pan evaporation based equations to estimate ETo from pan evaporation (E-p) and proposes a new simplified methodology for estimation of ETo, which needs only the data of relative humidity (H). The resulting model is based upon the collected meteorological data of a selected study area i.e. Nagpur District in Maharashtra State, which lies in western plateau and hills region of India. In the proposed methodology, E-p rates are adjusted to the values expected for 50 % relative humidity. Then, the relationship between ETo and the adjusted E-p is established. The validation of the proposed new model has been carried out by comparing its results with the results obtained by the pan evaporation method, for the study area as well as for the data set of another area. This new model is found to be reasonably accurate for estimation of reference evapotranspiration for the study area and as such, is expected to be applicable to the river basins located in the regions having climatic conditions similar to that of the study area. Although, if the conditions are different then another site specific model can be developed by adopting the methodology proposed in this article.
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The reliability of estimates of reference evapotranspiration (ETo) using pan evaporation (E-pan) depends on the accurate determination of pan coefficients (K-pan). Six ETo models were evaluated for their usefulness using 33-year c...
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The reliability of estimates of reference evapotranspiration (ETo) using pan evaporation (E-pan) depends on the accurate determination of pan coefficients (K-pan). Six ETo models were evaluated for their usefulness using 33-year climatological dataset of a semi-arid region of the Gujarat state of India. The equations compared include Cuenca (1989), Allen and Pruitt (1991), Snyder (1992), Modified Snyder (Grismer et al., 2002), Orang (1998), and Pereira et al. (1995). The ET data, calculated using daily K-pan values from these equations, were compared to the Food and Agricultural Organization (FAO)-Penman-Monteith (FA056-PM) method as a reference. Based on the visual comparison as well as from the statistical criteria, ETo values computed using Modified Snyder and Orang model have very close agreement with the FA056-PM method for daily, monthly, and annual estimates as compared to other approaches. The sequential performances of the explored models was found as: Modified Snyder (Eqn. 5) > Orang (Eqn. 6) > Cuenca Eqn. (2) > Allen & Pruitt (Eqn. 3) > Snyder (Eqn. 4) > Pereira et al. (Eqn. 7) model. Therefore, the Modified Snyder model (Grismer et al., 2002) could be recommended as the best model for ETo computations under these prevailing climatic conditions for a semi arid region.
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The evaporation (Er) of a US Class A pan (C) with submerged, freshwater aquatic macrophytes (Potamogeton perfoliatus, Myriophyllum spicatum and Najas marina), hereafter macrophytes (P-s) and a sediment-covered bottom (S) was measu...
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The evaporation (Er) of a US Class A pan (C) with submerged, freshwater aquatic macrophytes (Potamogeton perfoliatus, Myriophyllum spicatum and Najas marina), hereafter macrophytes (P-s) and a sediment-covered bottom (S) was measured in Hungary during 2014-2015 using reference E of Shuttleworth (E-o) and Penman-Monteith crop reference evapotranspiration (crop ETo). There were two main climatic controls affecting variation in E: direct (air and water temperature) and indirect (wind mediated change affecting the penetration of sunlight; precipitation inflow, impacting plant emergence). Lower seasonal mean E-p rates of 2.75 +/- 0.89, 2.83 +/- 0.91 and 3.06 +/- 1.14 mm day(-1) were observed in C, S and P-s, respectively, during the wet 2014. In the 2015 season, higher overall daily mean E-p rates for C, S and P-s were 3.76 +/- 1.3, 4.19 +/- 1.34 and 4.65 +/- 1.52 mm day(-1), respectively. A comparison of US Class A pan E containing macrophytes/sediments with that of a standard US Class A pan showed that pan coefficients (K-ap and K-as) might allow for more accurate on-site lake E estimates. In 2014, seasonal mean Km and K-ap were 1.04 +/- 0.14 and 1.09 +/- 0.18, respectively. Slightly higher K-a values were observed during the warm and dry 2015 (K-as: 1.15 +/- 0.22; K-ap: 1.26 +/- 0.23). A K-a value greater than 1 indicates that the E of a US Class A pan containing macrophytes and sediment is always higher than that of C. The calculated E-o overestimated measured E-p of P-s during the course of this study. During the warm-dry growing season, crop ETo was closest to E-p of P-s. Empirical coefficients can be useful for estimating E of lakes with submerged macrophytes more precisely. The accuracy of the estimate of Keszthely Bay's E improved by 9.85% when K-a was determined on site. (C) 2016 Elsevier B.V. All rights reserved.
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An attempt has been made to estimate evaporation from a water body by developing a new approach based on the energy balance model. For this purpose, a new energy balance method for two surfaces was established: water (evaporating ...
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An attempt has been made to estimate evaporation from a water body by developing a new approach based on the energy balance model. For this purpose, a new energy balance method for two surfaces was established: water (evaporating surface) and dry bare soil (non-evaporating surface as reference). An identical aerodynamic resistance ratio was assumed for both surfaces due to their similar conditions. With this assumption, a new form of energy balance was obtained which only depends on net radiation and temperature. The derived reference and water surface energy balance (RWEB) method was applied to estimate evaporation from Doosti dam reservoir in Iran. In order to evaluate the performance of the RWEB, comparison was performed with Bowen ratio energy balance (BREB) method as well as some conventional methods. According to the evaluations, the evaporation results of RWEB from 2011 to 2012 were satisfactory with RMSD value of 1.026 mm month(-1) and R-2 = 0.937. Furthermore, the RWEB sensitivity analysis showed the highest sensitivity to air temperature and the lower sensitivity to net radiation. Thus, evaporation from a water body can be estimated accurately by precise measurements of air temperature and relatively reasonable estimations of other parameters (reference, water temperature and net radiation).
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