scholarly journals Historical gridded reconstruction of potential evapotranspiration for the UK

2018 ◽  
Author(s):  
Maliko Tanguy ◽  
Christel Prudhomme ◽  
Katie Smith ◽  
Jamie Hannaford
Keyword(s):  
Input Data ◽  
Potential Evapotranspiration ◽  
Temperature Data ◽  
Accurate Estimation ◽  
Polynomial Method ◽  
Minor Effect ◽  
Hydrological Models ◽  
Time Step ◽  
Naive Method ◽  
The Uk

Abstract. Potential Evapotranspiration (PET) is a necessary input data for most hydrological models and is usually needed at a daily or shorter time-step. An accurate estimation of PET requires many input climate variables which are in most cases not available prior to the 1960s for the UK, nor indeed most parts of the world. Therefore, when applying hydrological models for reconstructing earlier periods, modellers have to rely on PET estimation derived from simplified methods. Given that only monthly observed temperature data is readily available for the late 19th and early 20th century at a national scale for the UK, the objective of this work was to derive the best possible UK-wide gridded PET dataset with the limited data available. To that end, firstly, a combination of (i) seven temperature-based PET equations, (ii) four different calibration approaches and (iii) seven input temperature data were evaluated against a gridded daily PET product based on the physically-based Penman-Monteith equation (the CHESS PET dataset), the rationale being that this provides a reliable ground-truth PET dataset for evaluation purposes, given that no directly observed, distributed PET datasets exist. The performance of the models was also compared to the simplest possible estimation of PET (naïve method) in the absence of any available climate data, the CHESS PET daily long term average (the period from 1961 to 1990 was chosen for this study), or CHESS-PET daily climatology. The analysis revealed that the type of calibration and the input temperature dataset had only a minor effect in the accuracy of the PET estimations at catchment scale. From the seven equations tested, only the calibrated version of the McGuinness-Bordne equation was able to outperform the naïve method and was therefore used to derive the gridded, reconstructed dataset. The equation was calibrated using 43 catchments across Great Britain. The dataset produced is a 5-km gridded PET dataset for the period 1891 to 2015, using as input data for the PET equation the Met Office 5-km monthly gridded temperature data available for that time period, which was disaggregated to daily temperature using pchip (piecewise cubic hermite interpolating polynomial) method. The dataset includes daily and monthly PET grids and is complemented with a suite of mapped performance metrics to help users assess the quality of the data spatially. The data can be accessed here: https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c.

scholarly journals Historical gridded reconstruction of potential evapotranspiration for the UK

2018 ◽  
Vol 10 (2) ◽  
pp. 951-968 ◽  
Author(s):  
Maliko Tanguy ◽  
Christel Prudhomme ◽  
Katie Smith ◽  
Jamie Hannaford
Keyword(s):  
Input Data ◽  
Performance Metrics ◽  
Potential Evapotranspiration ◽  
Temperature Data ◽  
Accurate Estimation ◽  
Minor Effect ◽  
Hydrological Models ◽  
Time Step ◽  
Naive Method ◽  
The Uk

Abstract. Potential evapotranspiration (PET) is a necessary input data for most hydrological models and is often needed at a daily time step. An accurate estimation of PET requires many input climate variables which are, in most cases, not available prior to the 1960s for the UK, nor indeed most parts of the world. Therefore, when applying hydrological models to earlier periods, modellers have to rely on PET estimations derived from simplified methods. Given that only monthly observed temperature data is readily available for the late 19th and early 20th century at a national scale for the UK, the objective of this work was to derive the best possible UK-wide gridded PET dataset from the limited data available. To that end, firstly, a combination of (i) seven temperature-based PET equations, (ii) four different calibration approaches and (iii) seven input temperature data were evaluated. For this evaluation, a gridded daily PET product based on the physically based Penman–Monteith equation (the CHESS PET dataset) was used, the rationale being that this provides a reliable “ground truth” PET dataset for evaluation purposes, given that no directly observed, distributed PET datasets exist. The performance of the models was also compared to a “naïve method”, which is defined as the simplest possible estimation of PET in the absence of any available climate data. The “naïve method” used in this study is the CHESS PET daily long-term average (the period from 1961 to 1990 was chosen), or CHESS-PET daily climatology. The analysis revealed that the type of calibration and the input temperature dataset had only a minor effect on the accuracy of the PET estimations at catchment scale. From the seven equations tested, only the calibrated version of the McGuinness–Bordne equation was able to outperform the “naïve method” and was therefore used to derive the gridded, reconstructed dataset. The equation was calibrated using 43 catchments across Great Britain. The dataset produced is a 5 km gridded PET dataset for the period 1891 to 2015, using the Met Office 5 km monthly gridded temperature data available for that time period as input data for the PET equation. The dataset includes daily and monthly PET grids and is complemented with a suite of mapped performance metrics to help users assess the quality of the data spatially. This dataset is expected to be particularly valuable as input to hydrological models for any catchment in the UK. The data can be accessed at https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c.

scholarly journals A new approach to estimating Mean Flow in the UK

2002 ◽  
Vol 6 (4) ◽  
pp. 709-720 ◽  
Author(s):  
M. G. R. Holmes ◽  
A. R. Young ◽  
A. Gustard ◽  
R. Grew
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Accurate Estimation ◽  
Mean Flow ◽  
Time Step ◽  
Runoff Water ◽  
Data Set ◽  
Water Balance Models ◽  
The Uk ◽  
Drying Curve

Abstract. Traditionally, the estimation of Mean Flow (MF) in ungauged catchments has been approached using conceptual water balance models or empirical formulae relating climatic inputs to stream flow. In the UK, these types of models have difficulty in predicting MF in low rainfall areas because the conceptualisation of soil moisture behaviour and its relationship with evaporation rates used is rather simplistic. However, it is in these dry regions where the accurate estimation of flows is most critical to effective management of a scarce resource. A novel approach to estimating MF, specifically designed to improve estimation of runoff in dry catchments, has been developed using a regionalisation of the Penman drying curve theory. The dynamic water balance style Daily Soil Moisture Accounting (DSMA) model operates at a daily time step, using inputs of precipitation and potential evaporation and simulates the development of soil moisture deficits explicitly. The model has been calibrated using measured MFs from a large data set of catchments in the United Kingdom. The performance of the DSMA model is superior to existing established steady state and dynamic water-balance models over the entire data set considered and the largest improvement is observed in very low rainfall catchments. It is concluded that the performance of all models in high rainfall areas is likely to be limited by the spatial representation of rainfall. Keywords: hydrological models, regionalisation, water resources, mean flow, runoff, water balance, Penman drying curve, soil moisture model

scholarly journals Hydrological signatures describing the translation of climate seasonality into streamflow seasonality

2019 ◽  
Author(s):  
Sebastian J. Gnann ◽  
Nicholas J. K. Howden ◽  
Ross A. Woods
Keyword(s):  
Model Building ◽  
Amplitude Ratio ◽  
Potential Evapotranspiration ◽  
Relevant Information ◽  
Sine Wave ◽  
Hydrological Models ◽  
Seasonal Climate ◽  
Using Data ◽  
The Uk ◽  
Hydrological Signatures

Abstract. Seasonality is ubiquitous in nature, and it is closely linked to water quality, ecology, hydrological extremes, and water resources management. Hydrological signatures aim at extracting relevant information about hydrological behaviour, and they can be used to better understand hydrological processes and to evaluate hydrological models. Commonly used seasonal hydro-climatological signatures consider climate or streamflow seasonality, but not how climate seasonality translates into streamflow seasonality. We propose and test hydrological signatures based on the attenuation of the seasonal climate input by a catchment. We approximate the seasonality in the input (precipitation minus potential evapotranspiration) and the output (streamflow) by sine waves. A catchment alters the input sine wave by reducing its amplitude and by shifting its phase. We use these quantities, the amplitude ratio and the phase shift, as seasonal hydrological signatures. We present analytical solutions describing the response of linear reservoirs to periodic forcing to interpret the seasonal signatures in terms of configurations of linear reservoirs. Using data from the UK and the US, we show that the seasonal signatures exhibit hydrologically interpretable patterns and that they are a function of both climate and catchment attributes. Wet, rather impermeable catchments hardly attenuate the seasonal climate input. Drier catchments, especially if underlain by a productive aquifer, strongly attenuate the input sine wave leading to phase shifts up to several months. Finally, we test whether two commonly used hydrological models (IHACRES, GR4J) can reproduce the observed ranges of seasonal signatures in the UK. The results show that the seasonal signatures can aid model building and evaluation.

scholarly journals Simulation of Daily Mean Soil Temperatures for Agricultural Land Use Considering Limited Input Data

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 441
Author(s):  
Philipp Grabenweger ◽  
Branislava Lalic ◽  
Miroslav Trnka ◽  
Jan Balek ◽  
Erwin Murer ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Input Data ◽  
Agricultural Land ◽  
Soil Column ◽  
Soil Conditions ◽  
Snow Layer ◽  
Time Step ◽  
Soil Temperatures ◽  
Dimensional Simulation ◽  
Limited Input Data

A one-dimensional simulation model that simulates daily mean soil temperature on a daily time-step basis, named AGRISOTES (AGRIcultural SOil TEmperature Simulation), is described. It considers ground coverage by biomass or a snow layer and accounts for the freeze/thaw effect of soil water. The model is designed for use on agricultural land with limited (and mostly easily available) input data, for estimating soil temperature spatial patterns, for single sites (as a stand-alone version), or in context with agrometeorological and agronomic models. The calibration and validation of the model are carried out on measured soil temperatures in experimental fields and other measurement sites with various climates, agricultural land uses and soil conditions in Europe. The model validation shows good results, but they are determined strongly by the quality and representativeness of the measured or estimated input parameters to which the model is most sensitive, particularly soil cover dynamics (biomass and snow cover), soil pore volume, soil texture and water content over the soil column.

scholarly journals Comparison of Genotypic and Phenotypic Correlations: Cheverud’s Conjecture in Humans

2018 ◽  
Author(s):  
Sebastian M. Sodini ◽  
Kathryn E. Kemper ◽  
Naomi R. Wray ◽  
Maciej Trzaskowski
Keyword(s):  
Evolutionary Biology ◽  
Genetic Correlations ◽  
Accurate Estimation ◽  
Human Populations ◽  
Phenotypic Correlations ◽  
Recent Developments ◽  
Genotypic And Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Selected Traits ◽  
The Uk

AbstractAccurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. 17 traits were selected based on sample size, distribution and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or non-morphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.

A simple approach to mimic the effect of active vegetation in hydrological models to better estimate hydrological variables under climate change

2021 ◽  
Author(s):  
Thedini Asali Peiris ◽  
Petra Döll
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Hydrological Models ◽  
Net Radiation ◽  
Ensemble Mean ◽  
The Impact

<p>Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO<sub>2</sub> concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO<sub>2</sub> and climate. This active vegetation response consists of three components. With higher CO<sub>2</sub> concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.</p><p>Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.</p><p>The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.</p><p>We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).</p><p>Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.</p>

Comparison between dynamic and static sensitivity analysis approaches for impact assessment of different potential evapotranspiration methods on hydrological models performance

2021 ◽  
Author(s):  
Rodric Mérimé Nonki ◽  
André Lenouo ◽  
Christopher J. Lennard ◽  
Raphael M. Tshimanga ◽  
Clément Tchawoua
Keyword(s):  
Sensitivity Analysis ◽  
Impact Assessment ◽  
Hydrological Modeling ◽  
Potential Evapotranspiration ◽  
Model Performance ◽  
Estimation Methods ◽  
Model Parameters ◽  
Hydrological Models ◽  
Sensitivity Approach ◽  
Static Sensitivity

AbstractPotential Evapotranspiration (PET) plays a crucial role in water management, including irrigation systems design and management. It is an essential input to hydrological models. Direct measurement of PET is difficult, time-consuming and costly, therefore a number of different methods are used to compute this variable. This study compares the two sensitivity analysis approaches generally used for PET impact assessment on hydrological model performance. We conducted the study in the Upper Benue River Basin (UBRB) located in northern Cameroon using two lumped-conceptual rainfall-runoff models and nineteen PET estimation methods. A Monte-Carlo procedure was implemented to calibrate the hydrological models for each PET input while considering similar objective functions. Although there were notable differences between PET estimation methods, the hydrological models performance was satisfactory for each PET input in the calibration and validation periods. The optimized model parameters were significantly affected by the PET-inputs, especially the parameter responsible to transform PET into actual ET. The hydrological models performance was insensitive to the PET input using a dynamic sensitivity approach, while he was significantly affected using a static sensitivity approach. This means that the over-or under-estimation of PET is compensated by the model parameters during the model recalibration. The model performance was insensitive to the rescaling PET input for both dynamic and static sensitivities approaches. These results demonstrate that the effect of PET input to model performance is necessarily dependent on the sensitivity analysis approach used and suggest that the dynamic approach is more effective for hydrological modeling perspectives.

scholarly journals Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River

2019 ◽  
Vol 23 (3) ◽  
pp. 1453-1467 ◽  
Author(s):  
Bart van Osnabrugge ◽  
Remko Uijlenhoet ◽  
Albrecht Weerts
Keyword(s):  
Radiative Forcing ◽  
Potential Evapotranspiration ◽  
Global Radiation ◽  
Forecast Skill ◽  
Meteorological Variables ◽  
Potential Evaporation ◽  
Streamflow Forecasting ◽  
Time Step ◽  
Streamflow Forecast ◽  
Rhine Basin

Abstract. Medium-term hydrologic forecast uncertainty is strongly dependent on the forecast quality of meteorological variables. Of these variables, the influence of precipitation has been studied most widely, while temperature, radiative forcing and their derived product potential evapotranspiration (PET) have received little attention from the perspective of hydrological forecasting. This study aims to fill this gap by assessing the usability of potential evaporation forecasts for 10-day-ahead streamflow forecasting in the Rhine basin, Europe. In addition, the forecasts of the meteorological variables are compared with observations. Streamflow reforecasts were performed with the daily wflow_hbv model used in previous studies of the Rhine using the ECMWF 20-year meteorological reforecast dataset. Meteorological forecasts were compared with observed rainfall, temperature, global radiation and potential evaporation for 148 subbasins. Secondly, the effect of using PET climatology versus using observation-based estimates of PET was assessed for hydrological state and for streamflow forecast skill. We find that (1) there is considerable skill in the ECMWF reforecasts to predict PET for all seasons, and (2) using dynamical PET forcing based on observed temperature and satellite global radiation estimates results in lower evaporation and wetter initial states, but (3) the effect on forecasted 10-day streamflow is limited. Implications of this finding are that it is reasonable to use meteorological forecasts to forecast potential evaporation and use this is in medium-range streamflow forecasts. However, it can be concluded that an approach using PET climatology is also sufficient, most probably not only for the application shown here, but also for most models similar to the HBV concept and for moderate climate zones. As a by-product, this research resulted in gridded datasets for temperature, radiation and potential evaporation based on the Makkink equation for the Rhine basin. The datasets have a spatial resolution of 1.2×1.2 km and an hourly time step for the period from July 1996 through 2015. This dataset complements an earlier precipitation dataset for the same area, period and resolution.

scholarly journals Estimation of Groundwater Evapotranspiration Using Diurnal Groundwater Level Fluctuations under Three Vegetation Covers at the Hinterland of the Badain Jaran Desert

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Wenjia Zhang ◽  
Liqiang Zhao ◽  
Xinran Yu ◽  
Lyulyu Zhang ◽  
Nai’ang Wang
Keyword(s):  
Groundwater Level ◽  
Potential Evapotranspiration ◽  
Vegetation Coverage ◽  
Accurate Estimation ◽  
Badain Jaran Desert ◽  
Arid Environments ◽  
Vegetation Types ◽  
Groundwater Evapotranspiration ◽  
Regional Water ◽  
Lake Basins

Accurate estimation of groundwater evapotranspiration (ETG) is the key for regional water budget balance and ecosystem restoration research in hyper-arid regions. Methods that use diurnal groundwater level (GWL) fluctuations have been applied to various ecosystems, especially in arid or semi-arid environments. In this study, groundwater monitoring devices were deployed in ten lake basins at the hinterland of the Badain Jaran Desert, and the White method was used to estimate the ETG of these sites under three main vegetation covers. The results showed that regular diurnal fluctuations in GWL occurred only at sites with vegetation coverage and that vegetation types and their growth status were the direct causes of this phenomenon. On a seasonal scale, the amplitudes of diurnal GWL fluctuations are related to vegetation phenology, and air temperature is an important factor controlling phenological amplitude differences. The estimation results using the White method revealed that the ETG rates varied among the observation sites with different vegetation types, and the months with the highest ETG rates were also different among the sites. Overall, ETG was 600∼900 mm at observation sites with Phragmites australis during a growing season (roughly early May to late October), 600∼650 mm in areas with Achnatherum splendens, and 500∼650 mm in areas with Nitraria tangutorum and Achnatherum splendens. Depth to water table and potential evapotranspiration jointly control the ETG rates, while the influence of these two factors varied, depending on the specific vegetation conditions of each site. This study elucidated the relationship between diurnal GWL fluctuations and vegetation in desert groundwater-recharged lake basins and expanded the application of the White method, providing a new basis for the calculation and simulation of regional water balance.

scholarly journals Essential BIM Input Data Study for Housing Refurbishment: Homeowners’ Preferences in the UK

Buildings ◽  
2014 ◽  
Vol 4 (3) ◽  
pp. 467-487 ◽  
Author(s):  
Kenneth Park ◽  
Ki Kim
Keyword(s):  
Input Data ◽  
The Uk
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