Evaluation of methods for calculating potential evapotranspiration in climate change scenarios

2021 ◽  
Author(s):  
Maria-Carmen Vicente-Torres ◽  
Miguel Angel Perez Martin
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Moisture Content ◽  
Temperature Increase ◽  
Soil Moisture Content ◽  
Potential Evapotranspiration ◽  
Climate Change Scenarios ◽  
Future Scenarios ◽  
Mitigation And Adaptation ◽  
The Mediterranean

<p>Despite uncertainties involved by future scenarios, the acknowledgement of climate change problem (WMO 2019/1248 reinforces the past five years as the warmest in industrial records, part of the warmest decade on record 2010-2019, and the need for urgent mitigation and adaptation actions have only grown in recent years. In the European Territory (EEA 1/2017), a significant decrease in summer soil moisture content in the Mediterranean region, while increases in north-eastern countries are projected for the coming decades. The current temperature increase derived from the emission of gases to the atmosphere, in the range of 0.1-0.3 ºC per decade by the IPCC experts Special Report 2018, obliges a deep review of the agricultural productivity factors, according to the FAO-56 /2006.</p><p>Soil moisture content is thus approached as a dynamic variable, with changes in temperature as well as precipitation constantly affecting evapotranspiration and infiltration rates. In this paper, five computing methods for crop water evapotranspiration (Penman-Monteith proposed by FAO-56, Thornwaite, and three temperature-based methods: Hargreaves 1975, Hargreaves-Samani 1985, Samani 2000) are not only scientifically compared but also applied to a Spanish Study Case at Valencian Community in the Mediterranean Basin. Results are affected by local single crops coefficient (also proposed by FAO-56) for citrus trees in upper Palancia River catchment, representative of intensive agriculture in the area, and calculated under four future scenarios (from +1ºC to 4ºC of unitary temperature increase).</p><p>Analysed results by percentual comparison with Penman-Monteith estimation, demonstrate a similar application range (from -1% of variation in +1ºC scenario to -4% of variation in 4ºC scenario) for scarcer data-based methods (Hargreaves 1975, Hargreaves-Samani 1985 and Samani 2000) except Thornthwaite. Allowing to conclude that Thornthwaite projections in the Mediterranean Climate overestimate up to 3% (+1ºC scenario), 6% (+2ºC scenario), 11% (+3ºC scenario) and 16% (+4ºC scenario) the monthly values of crop evapotranspiration.</p>

scholarly journals Reusing Grey Water to Lower Temperatures in the Mediterranean Basin Cities

Earth ◽  
2022 ◽  
Vol 3 (1) ◽  
pp. 72-75
Author(s):  
Giuseppe Maggiotto
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Moisture Content ◽  
Air Temperature ◽  
Mediterranean Basin ◽  
Soil Moisture Content ◽  
Hot Spot ◽  
Grey Water ◽  
The Mediterranean ◽  
The Mediterranean Basin

The Mediterranean region is a hot spot for climate change, and cities of this area will be exposed to both increasing temperatures and decreasing precipitations. Green Infrastructures (GIs) can lower urban temperatures through evapotranspiration with an adequate soil moisture content. Grey water reuse can both guarantee the right soil moisture content and reduce freshwater exploitation. In order to test the effectiveness of soil moisture on reducing air temperature, two modelling simulations ran with the microclimate CFD-based model ENVI-met 4.0. The chosen day was a registered heat wave (7 July 2019) in Lecce, a city of south Italy, which was selected as case study for the Mediterranean area. The results demonstrated the effectiveness of soil moisture on evapotranspiration in reducing air temperature. From a circular economy perspective, the supply of grey water for urban GIs represents a strategic adaptation strategy to the expected effects of climate change on the Mediterranean basin.

Climate Change Impact on the Water Resources of the Limpopo Basin

2018 ◽  
pp. 177-200
Author(s):  
Berhanu F. Alemaw ◽  
Thebeyame Ronald Chaoka
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Resources ◽  
Potential Evapotranspiration ◽  
Annual Runoff ◽  
Climate Change Scenarios ◽  
Atmospheric Processes ◽  
Hydrologic Regimes ◽  
Change Impact ◽  
High Runoff

This chapter aims to evaluate the impacts of climate change on both hydrologic regimes and water resources of the Limpopo River Basin in southern Africa. Water resources availability in the basin, in terms of, seasonal and annual runoff (R), soil moisture (S) and actual evapotranspiration (Ea) is simulated and evaluated using the hydrological model, HATWAB. These water balances were computed from precipitation (P), potential evapotranspiration (Ep) and other variables that govern the soil-water-vegetation-atmospheric processes at 9.2km latitude/ longitude gird cells covering the basin. The 1961-90 simulated mean annual runoff reveals mixed patterns of high and low runoff across the region. Although relatively small changes in runoff simulations are prevalent among the three climate change scenarios, generally the OSU simulated relatively high runoff compared to the UKTR and HADCM2 GCMs.

Climate Change Impact on the Water Resources of the Limpopo Basin

2018 ◽  
pp. 656-680
Author(s):  
Berhanu F. Alemaw ◽  
Thebeyame Ronald Chaoka
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Resources ◽  
Potential Evapotranspiration ◽  
Annual Runoff ◽  
Climate Change Scenarios ◽  
Atmospheric Processes ◽  
Hydrologic Regimes ◽  
Change Impact ◽  
High Runoff

This chapter aims to evaluate the impacts of climate change on both hydrologic regimes and water resources of the Limpopo River Basin in southern Africa. Water resources availability in the basin, in terms of, seasonal and annual runoff (R), soil moisture (S) and actual evapotranspiration (Ea) is simulated and evaluated using the hydrological model, HATWAB. These water balances were computed from precipitation (P), potential evapotranspiration (Ep) and other variables that govern the soil-water-vegetation-atmospheric processes at 9.2km latitude/ longitude gird cells covering the basin. The 1961-90 simulated mean annual runoff reveals mixed patterns of high and low runoff across the region. Although relatively small changes in runoff simulations are prevalent among the three climate change scenarios, generally the OSU simulated relatively high runoff compared to the UKTR and HADCM2 GCMs.

scholarly journals Some results of field determinations of the moisture content of soil from thermal conductivity measurements.

1953 ◽  
Vol 1 (2) ◽  
pp. 115-121
Author(s):  
D.A. De Vries
Keyword(s):  
Thermal Conductivity ◽  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Potential Evapotranspiration ◽  
Sandy Soils ◽  
Clay Soils ◽  
Conductivity Measurements ◽  
General Increase ◽  
Moisture Contents

The soil-moisture content at 4-I6-cm depth is compared with precipitation and potential evapotranspiration for periods of one month. During May the moisture contents fluctuated under the influence of frequent rainfall. From the end of May evapotranspiration exceeded precipitation and, during the dry months June and July, rainfall affected only the measurements at 4-cmdepth; moisture contents at 8 and I6 cm became constant after initial drying. During August, rainfall exceeded evapotranspiration and there was a general increase in moisture content. Diurnal variation in moisture content is shown in graphs. For accurate determinations of soil-moisture content from thermal conductivity measurements sandy soils are more suitable than clay soils. (Abstract retrieved from CAB Abstracts by CABI’s permission)

Analysis on Soil Moisture Content in the Middle Reaches of the Yellow River

2011 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Run-chun LI ◽  
Xiu-zhi ZHANG ◽  
Li-hua WANG ◽  
Xin-yan LV ◽  
Yuan GAO
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Yellow River ◽  
The Yellow River

Distribution of soil moisture content and its effect on the potential growth of the over-story species in North-East Chalkidiki

2001 ◽  
Vol 66 ◽  
Author(s):  
M. Aslanidou ◽  
P. Smiris
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Moisture Distribution ◽  
Taxus Baccata ◽  
Mixed Stands ◽  
Potential Growth ◽  
North East ◽  
Soil Moisture Distribution

This  study deals with the soil moisture distribution and its effect on the  potential growth and    adaptation of the over-story species in north-east Chalkidiki. These  species are: Quercus    dalechampii Ten, Quercus  conferta Kit, Quercus  pubescens Willd, Castanea  sativa Mill, Fagus    moesiaca Maly-Domin and also Taxus baccata L. in mixed stands  with Fagus moesiaca.    Samples of soil, 1-2 kg per 20cm depth, were taken and the moisture content  of each sample    was measured in order to determine soil moisture distribution and its  contribution to the growth    of the forest species. The most important results are: i) available water  is influenced by the soil    depth. During the summer, at a soil depth of 10 cm a significant  restriction was observed. ii) the    large duration of the dry period in the deep soil layers has less adverse  effect on stands growth than in the case of the soil surface layers, due to the fact that the root system mainly spreads out    at a soil depth of 40 cm iii) in the beginning of the growing season, the  soil moisture content is    greater than 30 % at a soil depth of 60 cm, in beech and mixed beech-yew  stands, is 10-15 % in    the Q. pubescens  stands and it's more than 30 % at a soil depth of 60 cm in Q. dalechampii    stands.

scholarly journals Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rehman S. Eon ◽  
Charles M. Bachmann
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Moisture Content ◽  
Layer Thickness ◽  
Soil Moisture Content ◽  
Hyperspectral Imagery ◽  
Barrier Island ◽  
Water Layer ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractThe advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.

scholarly journals Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

2021 ◽  
Vol 13 (8) ◽  
pp. 1562
Author(s):  
Xiangyu Ge ◽  
Jianli Ding ◽  
Xiuliang Jin ◽  
Jingzhe Wang ◽  
Xiangyue Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Soil Moisture ◽  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Fractional Order ◽  
Arid Regions ◽  
Soil Moisture Content ◽  
Order Derivative ◽  
Imaging Data ◽  
Strategy I

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

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