Generating reference evapotranspiration surfaces from the Hargreaves equation at watershed scale

Abstract. In this study, Hargreaves' formulation is considered to be appropriate for the water and energy balance at a daily scale due to its simplicity of application once the distributed values of temperature are available at cell scale. However, the coefficient of the Hargreaves equation must be previously calibrated. The interplay of different factors at different temporal scales became evident in the calibration process at the local scale of weather stations. The best fits against daily estimates by ASCE-PM were achieved when differentiating between the wet and the dry season. For the spatial distribution of Hargreaves coefficient at watershed scale, a regionalization in the area around each weather station was proposed in terms of areas of influence. The best results at watershed scale were obtained after a spatial correction for alpine areas, when the average of the difference cell by cell between ASCE-PM and Hargreaves's distributed daily estimates were 0.02 and 0.15 mm day−1 for the wet and the dry seasons, respectively. In all the cases, the best interpolation results were obtained using C-I (calculate and interpolate) procedures.

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Calculation of reference evapotranspiration surfaces in distributed hydrological modelling at different temporal scales

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-4813-2011 ◽

2011 ◽

Vol 8 (3) ◽

pp. 4813-4850 ◽

Cited By ~ 3

Author(s):

C. Aguilar ◽

M. J. Polo

Keyword(s):

Soil Water ◽

Reference Evapotranspiration ◽

Hydrological Modelling ◽

Watershed Scale ◽

Temporal Scales ◽

Daily Scale ◽

Dry Seasons ◽

Weather Stations ◽

Distributed Hydrological Modelling ◽

The Difference

Abstract. Each individual process in the soil water balance affected by evaporation processes has a certain representative temporal scale (e.g. canopy evapotranspiration, snowmelt or soil water loss). In this study, the implementation in distributed hydrological modelling at cell scale of the ASCE-Peman-Monteith (ASCE-PM) equation is proposed at hourly time steps whilst the Hargreaves formulation was considered to be appropriate for the water and energy balance at a daily scale due to its simplicity of application once the distributed values of temperature are available at cell scale. However, the coefficient of Hargreaves equation must be previously calibrated. The interplay of different factors at different temporal scales became evident in the calibration process at the local scale of weather stations. However, the best fits against daily estimates by ASCE-PM were achieved when differentiating between the wet and the dry season. For the spatial distribution of Hargreaves coefficient at watershed scale, a regionalization in the area around each weather station was proposed in terms of areas of influence. The best results at watershed scale were obtained after a spatial correction for alpine areas, when the average of the difference cell by cell between ASCE-PM and Hargreaves distributed daily estimates were 0.02 and 0.15 mm day−1 for the wet and the dry seasons respectively. In all the cases, the best interpolation results were obtained using C–I (calculate and interpolate) procedures.

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Comparison of meteorological data, related to reference evapotranspiration, from conventional and automatic stations in the Sertão and Agreste regions of Pernambuco, Brazil

DYNA ◽

10.15446/dyna.v88n216.86372 ◽

2021 ◽

Vol 88 (216) ◽

pp. 176-183

Author(s):

Iug Lopes ◽

Miguel Julio Machado Guimarães ◽

Juliana Maria Medrado de Melo ◽

Ceres Duarte Guedes Cabral de Almeida ◽

Breno Lopes ◽

...

Keyword(s):

Reference Evapotranspiration ◽

Meteorological Data ◽

Global Solar Radiation ◽

Concordance Index ◽

Good Relationship ◽

Food And Agriculture ◽

Food And Agriculture Organization ◽

Daily Scale ◽

Weather Stations ◽

Meteorological Elements

The objective was to perform a comparative study of the meteorological elements data that most cause changes in the reference Evapotranspiration (ETo, mm) and its own value, of automatic weather stations AWS and conventional weather stations CWS of the Sertão and Agreste regions of Pernambuco State. The ETo was calculated on a daily scale using the standard method proposed by the Food and Agriculture Organization (FAO), Penman-Monteith (FAO-56). The ETo information obtained from AWS data can be used to update the weather database of stations, since there is a good relationship between the ETo data obtained from CWS and AWS, statistically determined by the Willmott's concordance index (d > 0.7). The observed variations in the weather elements: air temperature, relative humidity, wind speed, and global solar radiation have not caused significant changes in the ETo calculation.

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Evaluación de dos modelos para la estimación de la evapotranspiración de referencia con datos CERES

Revista de Teledetección ◽

10.4995/raet.2018.9259 ◽

2018 ◽

pp. 87 ◽

Cited By ~ 4

Author(s):

F. Carmona ◽

M. Holzman ◽

R. Rivas ◽

M.F. Degano ◽

E. Kruse ◽

...

Keyword(s):

Temporal Variability ◽

Reference Evapotranspiration ◽

Important Variable ◽

Spatial And Temporal Variability ◽

Suitable Alternative ◽

Pampean Region ◽

Daily Scale ◽

Weather Stations ◽

Good Agreement

Evapotranspiration is the most important variable in the Pampas plain. Information provided by sensors onboard satellite missions allows represent the spatial and temporal variability of evapotranspiration, which cannot be achieved using only measurements of weather stations. In this work, the Priestley and Taylor (PT) and FAO Penman Monteith (FAO PM) equations were adapted to estimate the reference evapotranspiration, ET0 , using only CERES satellite products (SYN1 and CldTypHist). In order to evaluate the reference evapotranspiration from CERES, a comparison with in situ measurements was conducted. We used ET data provided by the Oficina de Riesgo Agropecuario, corresponding to 24 stations placed in the Pampean Region of Argentina (2001-2016). Results showed very good agreement between the estimates with CERES products and in situ values, with errors between ±0.8 and ±1.1 mm d–1 and r2 greater than 0.75 at daily scale, and errors between ±14 and ±19 mm month–1 and r2 greater than 0.9, at monthly scale better results were obtained with adapted model FAO PM than PT. Finally, ET0 monthly maps for the Pampean Region of Argentina were elaborated, which allowed knowing the temporal-spatial variation in the validation area. In conclusion, the methods presented here are a suitable alternative to estimate the reference evapotranspiration without requiring ground measurements.

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Evaluation of temperature-based solar radiation models and their impact on penman-monteith reference evapotranspiration in a semiarid climate

International Journal of Hydrology ◽

10.15406/ijh.2020.04.00230 ◽

2020 ◽

Vol 4 (2) ◽

pp. 84-90

Author(s):

Koffi Djaman

Keyword(s):

New Mexico ◽

Solar Radiation ◽

Reference Evapotranspiration ◽

Mean Bias Error ◽

Maintenance Cost ◽

Efficiency Coefficient ◽

Weather Station ◽

Data Set ◽

Weather Stations ◽

The Impact

Solar radiation is one of the most important climatic parameters that is involved in different environmental, hydrological, agricultural applications while not always measured at all weather stations due to the high equipment and maintenance cost. The objectives of this study were to evaluate the performance and accuracy of twenty temperature based solar radiation models at five weather stations (Alcalde, Fabian Garcia, Farmington, Leyendecker and Tucumcari) in New Mexico and to evaluate the impact of solar radiation prediction on the Penman-Monteith grass reference evapotranspiration (ETo) for the global period of 2009-2017. New constants of each model at each weather station were retrieved using the optimization procedure Solver in Excel that maximizes the Kling-Gupta Efficiency (KGE). The root mean squared error (RMSE), mean absolute error (MAE), mean bias error (MBE) and the Nash-Sutcliffe model efficiency coefficient (NSE) were used for model performance evaluation. The results showed that the Hargreaves and Samani (1982), improved by Allen 1995, Bristow-Campbell (1984), Hunt et al. (1998), Fan et al. (2018), Hassan et al. (2016), Samani (2000); Nage et al. (2018) 2 and the Richardson et al (2018) models were the most accurate and the best performing ones across all five research sites. The EL-Sabaii, Ert Yal and Clemence models showed the poorest performance at all five stations. The evaluation of the impact of the predicted solar radiation on the Penman-Monteith ETo showed that predicted solar radiation had non-significant effect of the daily ETo with a regression slope varying from 0.978 to 1.022, RMSE from 0.24 to 0.48 mm/day, MAE from 0.15 to 0.31 mm/day and MBE from -0.03 to 0.09 mm/day. All solar radiation models showed best performance at Farmington and Tucumcari while they registered the poorest performance at Alcalde. The Student T-test revealed non-significant differences between the daily ETo using the measured solar radiation data set and the predicted solar radiation by each of the twenty solar radiation models at each weather station. The new models developed in this study could be used to estimate daily solar radiation across the semiarid environment of New Mexico for satisfactory estimation of ETo.

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Twenty-first century regional temperature response in Chile based on empirical-statistical downscaling

Climate Dynamics ◽

10.1007/s00382-020-05620-9 ◽

2021 ◽

Author(s):

Sebastian G. Mutz ◽

Samuel Scherrer ◽

Ilze Muceniece ◽

Todd A. Ehlers

Keyword(s):

Statistical Models ◽

Temperature Response ◽

Local Scale ◽

First Century ◽

Local Temperature ◽

Future Climate Change ◽

Weather Station ◽

Temperature Changes ◽

Scale Temperature ◽

Twenty First Century

AbstractLocal scale estimates of temperature change in the twenty-first century are necessary for informed decision making in both the public and private sector. In order to generate such estimates for Chile, weather station data of the Dirección Meteorológica de Chile are used to identify large-scale predictors for local-scale temperature changes and construct individual empirical-statistical models for each station. The geographical coverage of weather stations ranges from Arica in the North to Punta Arenas in the South. Each model is trained in a cross-validated stepwise linear multiple regression procedure based on (24) weather station records and predictor time series derived from ERA-Interim reanalysis data. The time period 1979–2000 is used for training, while independent data from 2001 to 2015 serves as a basis for assessing model performance. The resulting transfer functions for each station are then directly coupled to MPI-ESM simulations for future climate change under emission scenarios RCP2.6, RCP4.5 and RCP 8.5 to estimate the local temperature response until 2100 A.D. Our investigation into predictors for local scale temperature changes support established knowledge of the main drivers of Chilean climate, i.e. a strong influence of the El Niño Southern Oscillation in northern Chile and frontal system-governed climate in central and southern Chile. Temperature downscaling yields high prediction skill scores (ca. 0.8), with highest scores for the mid-latitudes. When forced with MPI-ESM simulations, the statistical models predict local temperature deviations from the 1979–2015 mean that range between − 0.5–2 K, 0.5–3 K and 2–7 K for RCP2.6, RCP4.5 and RCP8.5 respectively.

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Spatial distribution and source identification of heavy metals (As, Cr, Cu and Ni) at sub-watershed scale using geographically weighted regression

International Soil and Water Conservation Research ◽

10.1016/j.iswcr.2019.01.005 ◽

2019 ◽

Vol 7 (3) ◽

pp. 308-315 ◽

Cited By ~ 1

Author(s):

Maziar Mohammadi ◽

Abdulvahed Khaledi Darvishan ◽

Nader Bahramifar

Keyword(s):

Heavy Metals ◽

Spatial Distribution ◽

Geographically Weighted Regression ◽

Source Identification ◽

Weighted Regression ◽

Watershed Scale

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Optimizing spatial distribution of watershed-scale hydrologic models using Gaussian Mixture Models

Environmental Modelling & Software ◽

10.1016/j.envsoft.2021.105076 ◽

2021 ◽

pp. 105076

Author(s):

Tessa Maurer ◽

Francesco Avanzi ◽

Carlos A. Oroza ◽

Steven D. Glaser ◽

Martha Conklin ◽

...

Keyword(s):

Spatial Distribution ◽

Mixture Models ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Watershed Scale ◽

Hydrologic Models

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Mapping and verification of the snow cover timing in the Baikal region by remote sensing data MODIS “snow cover”

Geodesy and Cartography ◽

10.22389/0016-7126-2021-973-7-21-31 ◽

2021 ◽

Vol 973 (7) ◽

pp. 21-31

Author(s):

Е.А. Rasputina ◽

A.S. Korepova

Keyword(s):

Remote Sensing ◽

Snow Cover ◽

Spatial Resolution ◽

Baikal Region ◽

Remote Sensing Data ◽

Meteorological Station ◽

Sensing Data ◽

Modis Data ◽

Weather Stations ◽

The Difference

The mapping and analysis of the dates of onset and melting the snow cover in the Baikal region for 2000–2010 based on eight-day MODIS “snow cover” composites with a spatial resolution of 500 m, as well as their verification based on the data of 17 meteorological stations was carried out. For each year of the decennary under study, for each meteorological station, the difference in dates determined from the MODIS data and that of weather stations was calculated. Modulus of deviations vary from 0 to 36 days for onset dates and from 0 to 47 days – for those of stable snow cover melting, the average of the deviation modules for all meteorological stations and years is 9–10 days. It is assumed that 83 % of the cases for the onset dates can be considered admissible (with deviations up to 16 days), and 79 % of them for the end dates. Possible causes of deviations are analyzed. It was revealed that the largest deviations correspond to coastal meteorological stations and are associated with the inhomogeneity of the characteristics of the snow cover inside the pixels containing water and land. The dates of onset and melting of a stable snow cover from the images turned out to be later than those of weather stations for about 10 days. First of all (from the end of August to the middle of September), the snow is established on the tops of the ranges Barguzinsky, Baikalsky, Khamar-Daban, and later (in late November–December) a stable cover appears in the Barguzin valley, in the Selenga lowland, and in Priolkhonye. The predominant part of the Baikal region territory is covered with snow in October, and is released from it in the end of April till the middle of May.

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Spatial Distribution of Snow Storage and Snowmelt Dynamics in Central Yenisei Siberia

Meteorologiya i Gidrologiya ◽

10.52002/0130-2906-2021-1-82-92 ◽

2021 ◽

pp. 82-92

Author(s):

I. V. Danilova ◽

◽

A. A. Onuchin ◽

◽

Keyword(s):

Spatial Distribution ◽

Snow Cover ◽

Sea Level ◽

Thermal Regime ◽

Regression Models ◽

Weather Station ◽

Digital Maps ◽

Independent Variables ◽

Snow Storage

In this paper the spatial distribution of water reserves in the snow cover and the dynamics of snow cover melting due to the peculiarity of the thermal regime were analyzed for the central part of Yenisei Siberia. To create digital maps of water reserves in the snow cover, regression models were developed. The geographic coordinates, elevation above sea level and the distance from the orographic boundaries were used as independent variables in regression models. Based on the created maps, the dynamics of snow cover melting was obtained in the study area, taking into account the thermal regime at a key weather station.

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