Potential Evapotranspiration Values Research Articles

Flash drought monitoring using diurnal-provided evaporative demand drought index

Flash drought, as a relatively new concept, represents a rapidly evolving drought with sudden onset, short-term duration, and great destructiveness. With the warming of the planet in recent decades, the frequent occurrences of flash droughts have resulted in considerable losses to personnel and properties on a global scale. Nowadays, the emerging Evaporative Demand Drought Index (EDDI) has revealed its significant potential and adaptability in the early warning and quantification of flash droughts. In this study, an advanced method for improving the accuracy and temporal resolution of EDDI is proposed. The new set of EDDI estimates is calculated using diurnal-provided potential evapotranspiration values that have been calibrated with weather parameters and Global Navigation Satellite Systems (GNSS) atmospheric products. Then, the monitoring performances of flash droughts resulting from the diurnal-provided EDDIs are evaluated over the period 2010–2021 in Hong Kong. Results showed that the Probability Of Detection (POD) and False Alarm Rate (FAR) were 87.1 % and 16.7 %, respectively. By comparing with their counterparts obtained from the use of monthly EDDIs, it was found that the improvements made by the new method in the metrics of POD and FAR were 24.6 % and 11.2 %, respectively. In addition, with the use of diurnal-provided EDDI, the mean lead time for flash drought detection has been prolonged to 37.74 days, offering more time to prevent and mitigate the detrimental effects brought by flash drought events.

River Hydrology Analysis For Micro Hydro Power Plant

The Micro Hydro Power Plant (PLTMH) is a generator capable of fulfilling the electrical requirements of isolated regions. PLTMH serves as an alternative means of generating electrical energy for the community. This power facility offers numerous advantages, particularly for remote areas across Indonesia. Water is a crucial energy resource due to its ability to generate electricity, a cost-effective and environmentally friendly kind of energy. The micro-hydro type PLTMH (0.5–100 kilowatts) in Aceh Province is the Lhoong PLTMH, which was built with assistance from PT. Coca-Cola in 2005. This PLTMH is located in Krueng Kala Village, Lhoong District, Aceh Besar Regency. This research aims to determine the availability of the Krueng Kala Lhoong PLTMH's flow rate and the availability of power and energy produced by the Krueng Kala Lhoong PLTMH to meet the electricity needs of Lhoong residents. It is hoped that the benefits of this research will be able to provide development and knowledge, especially in the field of pyrotechnics, and can become reference material for further study, providing information about micro hydropower plants, especially the Krueng Kala Lhoong PLTMH. The research utilizes the Pearson III Log Method to calculate maximum rainfall frequency and Fj Mock for reliable discharge calculation. The research results showed that the full rain discharge with a return period of 25 years was 1152.68 mm/hour. The total potential evapotranspiration (ET0) value occurred in March, reaching 6,649 mm/day. The mainstay discharge with a probability of 85% is Q85% = 0.24 m3/second, obtaining power of 27,914 kW and energy for a year of 20787,644 kWh. The calculation results conclude that the Krueng Kala power plant is still classified as a PLTMH, producing power below 100 kW and generating an annual energy of 20,787,644 kWh. The electricity can be distributed to Meunasah Krueng Kala Village, Baroeh Krueng Kala Village, Tunong Krueng Kala Village, and small enterprises in these three communities.  

Spatiotemporal Changes in and Driving Factors of Potential Evapotranspiration in a Hyper-Arid Locale in the Hami Region, China

Potential evapotranspiration (PET) is a crucial variable for implementing adaptation measures to mitigate the potential impacts of climate change on water resources. In the context of global warming, PET is essential for predicting water resource supply and demand, guiding irrigation and water management decisions. However, there is limited understanding of the spatiotemporal changes in PET and its driving factors in the hyper-arid regions of Northwest China. In this study, the Hargreaves model was employed to estimate PET in the Hami region from 1991 to 2020. By combining relevant climate data and partial correlation analysis, we investigated the spatiotemporal distribution patterns of PET within the study area and analyzed the factors influencing these patterns. The results showed the following: (1) From 1991 to 2020, the overall PET in the Hami region demonstrated a tendency to rise. The interannual trend rates of PET for the full year, spring, summer, autumn, and winter were 0.933, 2.744, 0.906, 0.488, and −0.406 mm·a-1, respectively. Despite a decreasing trend in winter PET, the other seasonal PET values and the annual PET values exhibited an increasing trend. (2) The spatial distribution of both annual and seasonal PET showed significant regional heterogeneity, following a consistent pattern marked by lower values in the central part and higher values in the surrounding areas. The southern region tended to have relatively high PET, while the northwestern region experienced comparatively low PET. (3) Partial correlation analysis indicated significant differences in the impact of various climatic factors on PET. The maximum temperature emerged as the dominant factor influencing annual PET variation, while precipitation played a leading role in influencing autumn PET variation. This study underscores the influence of climate change on PET in the Hami region, contributing to an enhanced comprehension of PET variations.

Evaluation of ERA5, ERA5-Land, GLDAS-2.1, and GLEAM potential evapotranspiration data over mainland China

Study regionChina. Study focusAccurate estimation of potential evapotranspiration (PET) is essential for understanding climate change. Using ground-based pan evaporation measurements over continental China, the monthly scale PET data during 2000–2017 of ERA5, ERA5-Land, GLDAS-2.1/Noah, and GLEAM V3.8a are evaluated, from the perspectives of their consistency in spatiotemporal variation, and performance measures. Factors controlling the data quality of the four datasets are investigated from the perspective of their PET calculation models and meteorologically input data. New hydrological insights for the regionPETERA5 performs the best in mainland China among four gridded PET datasets with higher correlation coefficients (r) and smaller biases, which can well capture the temporal variation of Epan. The outstanding performance of PETERA5 in China mainly results from the utilization of the Penman-Monteith (P-M) equation which performs the best among several competing formulas for PET computation, as well as its better meteorological inputs for computing PET than other datasets. Although the PETERA5-Land is a replay of the land component of the ERA5 climate reanalysis, it exhibits substantial overestimation of PET values and temporal trends, particularly in coastal areas of Southern China and the eastern side of Northeastern China, mainly caused by the overestimation of its net radiation. The PETGLDAS shows significant overestimation, partly due to its overestimation of wind speed, but mostly due to its modified P-M equation with its parameterization of land surface conditions for computing PETGLDAS. The PETGLEAM underestimated PET generally mainly due to the joint effect of the use of the Priestley-Taylor equation with small P-T parameter α, and the underestimation of the net radiation input from ERA-Interim, especially in Northwest and Qinghai Tibet.

Evaluating the effect of the SPI and SPEI methods on drought monitoring over Turkey

Drought indices are one of the most widely used methods for drought monitoring because they are easy to apply and interpret. The two most widely used drought index methods are the Standardized Precipitation Index (SPI) method, using the precipitation parameter as input, and the Standardized Precipitation Evapotranspiration Index (SPEI) method, which uses the Potential Evapotranspiration (PET) values addition to precipitation. The primary goal of this study is to compare the two methods for determining drought characteristics in different climatic and geographical features in Turkey. The drought characteristics are calculated using meteorological data between 1970 and 2021 for 199 synoptic observation stations in seven geographical regions of Turkey with SPI and SPEI methods for the 3-, 6-, and 12-month time scales. The study's findings indicate that while the correlation coefficient (CC) between the two indices is generally high (ranging from 0.81 to 0.93, depending on the region and time scale), it is lower in regions with a low Aridity Index (AI) value, particularly for the 3-month time scale. For the 6- and 12-month time scales, no relationship is observed between AI and CC. Additionally, SPEI detected a higher occurrence percentage of moderate and severe droughts across all geographical regions (with an increase of up to 15 % compared to SPI), while SPI observed higher percentages of extreme droughts. The study results conclude that SPI and SPEI methods demonstrate significant differences in detecting certain drought characteristics after the 1990s, underscoring the necessity to consider temperature variations in drought monitoring, particularly in the context of ongoing climate change.

Potential Evapotranspiration in Merapi Aquifer System

Temperature variation due to climate change can give greatest impact on potential evapotranspiration. Increase of temperature in Yogyakarta Special Region can increase potential evapotranspiration. It is necessary to study potential evapotranspiration as one of indication impact of climate change to its potential evapotranspiration. Potential evapotranspiration (PET) can be estimated applying Hargreaves and Samani (1982) that requires limited meteorological parameter. Therefore, this research aims are: a) to analyze daily PET in  3 gauge station of Merapi Aquifer System, b) to analyze variation PET in the 3 gauge stations of Merapi Aquifer System.
 The largest values of PET is in Barongan station, while the lowest is in Adisucipto station. It is probably because Adisucipto station is located in urban and crowded areas. PET values are mostly 1.98 mm/day in rainy season, while 1.67 mm/day in dry season. Mostly, the correlation coefficient is low in dry season for Pluyon, Barongan and Adisucipto stations suggesting that drier and warmer temperature due to climate change do not have large impact to PET. The 5-month moving average trend also confirm the relatively stable line of PET variation from January 2005 to December 2016 reflecting that climate change do not greatly impact on PET in Merapi Aquifer System.

Effects of Atom Search-Optimized Thornthwaite Potential Evapotranspiration on Root and Shoot Systems in Controlled Carica papaya Cultivation

Potential evapotranspiration (PET) indicates if a cultivation area is suitable for planting. Currently, site-specific PET models that are based on large geographic regions are vulnerable to inaccurate predictions as a result of climate change and sudden changes in the environmental abiotic stressors that affect plant growth. For the aim of promoting the papaya Sinta F1 cultivar, the study optimized the standard Thornthwaite PET model by integrating three advanced physics-based metaheuristics and evolutionary computing, namely atom search (ASO), differential evolution (DE), and multiverse (MVO) optimizers. The PET value was optimized through minimization as a function of air temperature, light intensity, heat index, and extended heat index. As the PET value approaches 0, it indicates that there is more soil-water content that can be absorbed by plants. Based on the four cultivation treatments (uncontrolled, ASO, DE, and MVO) exposed in three replicates within 90 days, the ASO-optimized Thornthwaite PET-treated (ASOTh) papaya plants resulted in the highest chlorophyll a and b concentrations, densest stomatal density, concentrated root and stem xylem and phloem vessels, considerable root and stem length, most formed leaf count, and strongest action potentials coming from stem membrane for both light and dark periods. This proves the applicability of the intelligent process in modifying the Thornthwaite model for plant growth promotion. Also, through the developed ASOTh, the stem length and thickness ratio was improved for mechanical stability to facilitate more branching leaves and potential fruits during the fruiting stage, and the chlorophyll a and b ratio was enhanced, which naturally extended the light energy band for photosynthesis. Overall, the newly developed ASOTh model may be used to grow papaya seedlings year-round anywhere on Earth if there is a control system to regulate the environmental setting inside the growth chamber.

Quantifying evapotranspiration fluxes on green roofs: A comparative analysis of observational methods

Evapotranspiration (ET) is an important process in green stormwater infrastructure (GSI) aiming to reduce urban drainage, to promote cooling and/or to contribute to an urban hydrological balance restoration closer to the natural one. However, on these structures and particularly on green roofs (GR), its evaluation remains challenging and subject to discussion. Estimates of ET by water balance, energy balance, and an ET chamber were performed on five different plots of a full-scale experimental green roof in Trappes (France). Compared to both water balance (90th percentile range of daily ET values: 0.8 mm/d to 3 mm/d) and chamber methods (90th percentile range of daily ET values: 1 mm/d to 1.5 mm/d), the energy balance (90th percentile range of daily ET values is between 1.8 mm and 3.7 mm) produces higher values, 1 to 2 times higher in cumulative values during common periods. The chamber ET displays a similar trend to the energy balance on an hourly basis, and its values remain within the same range as the water balance evaluations on a daily time-step. All three assessments consistently fell below the potential ET values estimated with the Penman-Monteith formula. Critical issues in ET estimation through experimentation have arisen. Sensible heat flux (H) significantly increases ET values when using the energy balance approach compared to the other two methods. The Water Balance method is practical, but on days following rainfall events, the Chamber method may prove more reliable, albeit more time and labour-intensive. The three methods indicated that the substrate thickness was the main contributing factor to increase ET, with well-maintained herbaceous plants providing higher ET values than sedums in thick (15 cm) substrates. In addition, the substrate's nature, especially its organic content, is another factor that promotes ET in green roofs.

Temporal and Spatial Variations of Potential and Actual Evapotranspiration and the Driving Mechanism over Equatorial Africa Using Satellite and Reanalysis-Based Observation

This study investigated the actual evapotranspiration (AET) and potential evapotranspiration (PET) seasonality, trends, abrupt changes, and driving mechanisms with global sea surface temperature (SST) and atmospheric circulation patterns over Equatorial Africa (EQA) during 1980–2020. The spatiotemporal characteristics of mean ET were computed based on a 40-year average at annual and seasonal scales. The Mann-Kendall statistical test, the Sen slope test, and the Bayesian test were used to analyze trends and detect abrupt changes. The results showed that the mean annual PET (AET) for 1980–2020 was 110 (70) mm. Seasonal mean PET (AET) values were 112 (72) in summer, 110 (85) in autumn, 109 (84) in winter, and 110 (58) in spring. The MK test showed an increasing (decreasing) rate, and the Sen slope identified upward (downward) at a rate of 0.35 (0.05) mm yr−10. The PET and AET abrupt change points were observed to happen in 1995 and 2000. Both dry and wet regions showed observed weak (strong) correlation coefficient values of 0.3 (0.8) between PET/AET and climate factors, but significant spatiotemporal differences existed. Generally, air temperature, soil moisture, and relative humidity best explain ET dynamics rather than precipitation and wind speed. The regional atmospheric circulation patterns are directly linked to ET but vary significantly in space and time. From a policy perspective, these findings may have implications for future water resource management.

Revealing the trend and change point in Hargreaves equation based on potential evapotranspiration values with various statistical approaches.

Hotter and drier weather conditions due to climate change negatively affect water resources and agricultural production. For this reason, it is vital to analyze the change in potential evapotranspiration (PET) values, which is one of the most important parameters related to plant growth and agricultural irrigation planning. This study analyses the trends and changes in monthly and annual PET values between 1965 and 2018 at Erzincan, Bayburt and Gümüşhane meteorological stations in Turkey. For this purpose, monotonic trends in PET values were determined by Spearman's rho (SR), Mann-Kendall (MK), Şen slope (SS), and innovative trend analysis (ITA) tests and change points were analyzed with the sequential MK (SQMK) test. The Hargreaves equation was used to calculate the PET values. As a result of the study, according to MK and SR tests, while increasing trends at 95% and 99% significance levels were dominant at Erzincan and Bayburt stations, no statistically significant trends were found at Gümüşhane station except in February. ITA generally detected more than 5% increasing trends in PET data's low, medium, and high values. According to ITA slope analysis, there are significant increase trends in PET values at all periods, trend 1% significance level. According to the SQMK test, it was revealed that the trend started in PET values, especially in 1995, 2005, and 2010. The findings emphasized the importance of taking measures against decreased agricultural production and managing water resources effectively.

Spatiotemporal variation of potential evapotranspiration and meteorological drought based on multi-source data in Nepal

Quantifying the spatiotemporal dynamic of potential evapotranspiration (PET) in topographically complex country are often limited by the scarcity and difficulty in obtaining ground-based measured climate data. Remote sensing products have multiple advantage, which allows rapid acquisition of information and status over large areas and long time series. This study compared and explored the spatiotemporal variation of PET across Nepal using three widely-used remote sensing and reanalysis data PET products (CRU_PET, MODIS_PET and PML_PET), and PET estimation using Hargreaves-Samani method based on CHIRTS datasets. On the basis of this, the spatiotemporal dynamic at seasonal and annual level and the periodical change of PET and meteorological aridity index AI (precipitation P/PET) were identified using Mann-Kendall test and Morlet Wavelet method. These PET products showed general spatial consistency over most areas in Nepal with higher PET in the south and less in the north. However, great differences were also found in PET values for four different products. Compared with the three remote sensing and reanalysis data products, CHIRTS_PET performs better in Nepal. The AI based on CHIRTS_PET showed an insignificant increasing (wetting) trend in the western and southern regions, while an insignificant decreasing (drying) trend in the central and northeastern region, which is generally consistent with the spatial pattern of precipitation. In the western and southern regions, the positive impact of increasing precipitation on AI masked the negative effect of increasing PET, and thus making this region getting humid. However, in the central and northeastern region, the increase in PET aggravates the impact of reduced precipitation on the drying trend. Our investigation have broad implications for sustainable water resources management under climate change in a topographically complex country like Nepal.

Predicting Groundwater Level Using Climate Change Scenarios in the Southern Part of Mali

Groundwater is mainly demanded in all the activities for the population of the southern part especially in the Koda catchment, the studied area. These resources are affected by various factors especially climate change. Therefore, knowing the impact of projected climate change on groundwater recharge is an important issue for water resources management, especially for those responsible for the Koda catchment. In this work, the impact of climate change on groundwater resources in the study area in Mali, West Africa is investigated. The Hydrogeological modeling was performed using the Gardenia model, and the monthly precipitation and temperature data were used as the Baseline. These data considered the past 30-year period (1987-2016) and the projections for the next 30 years (2021-2050). Projected precipitation and air temperatures, extracted from the Rossby Centre regional Atmospheric climate model (RCA 4) statistically downscaled from the GCM-IHEC-EC-EARTH and the GCM-MPI-M-MPI-ESM-LR under the Representative Concentration Pathways RCP 4.5 and RCP 8.5 and corrected with the Multiscale Quantile Mapping bias correction method, were used as input data to the gardenia model. Potential evapotranspiration (PET) values estimated from Blaney Criddle method and groundwater levels measured in three piezometers were used to calibrate the Gardenia model. The outputs display the reduction of groundwater level in the three piezometers in the Koda catchment for all the two Regional Climate Models (RCMs) during the periods of rainy season from July to October. From the results of GCM IHEC-EC-EARTH, the projected decline in GWL reaches 1.09 m for the RCP 4.5 and it up to 1.26 m for the RCP 8.5 in the study area while the GCM MPI-M-MPI-ESM-LR presentes the decline in groundwater level (GWL) during winter season from about 0.62 m for the RCP 4.5 up to 1.93 m for the RCP 8:5. Both RCMs project a reduction trend of groundwater recharge over time. It is noticeable that this decline is greater in RCP8.5 for all the three piezometers. The results also show that the average groundwater recharge (90 mm) in the future (2021-2050) is lower (180 mm) than that of the current drought (1987-2016), which could lead to severe drought events. The projected impacts of climate change would have a significant impact on groundwater in the period of 2029-2039; this situation could have a negative impact the socioeconomic activities especially on agriculture, which depends on water resources. The results will help also to take some adaptation measures to climate change, the famers could have a possibility to know the period of groundwater recharge where they have more water infiltration therefore, where to seek crops that need less or more water. The study area presents numerous potential of groundwater, the results could be a tool for groundwater management and to determine the favorable sites to implant new boreholes.

Modeling the Water Balance of Agricultural Land in the Determination of the Growing Season in Buru Regency

This study aims to determine the value of surplus and water deviation of agricultural land in Namlea District, Buru Regency. The study was conducted in Namlea Subdistrict, Buru Regency, Maluku Province. Materials used, questionnaires, climate data, air temperature, precipitation, humidity, solar rays 10-20 years. Tools used, computer equipment, writing stationery and location maps. To obtain the surplus value and water deficit of the land used data on the average amount of monthly precipitation and the average monthly temperature using the calculation of the Thornthwaite method. The calculation of the groundwater balance is carried out using a bookkeeping system. The data used are monthly potential evapotranspiration values, climate station data, monthly average rainfall, and rainfall at a 50 percent chance level. The observation parameters calculated in this study are rainfall, evapotranspiration, and determination of land water balance. The results of this study showed that the difference in rainfall and evapotranspiration in Namlea District was highest in June at 85.40 mm, and the lowest in October at -99.83 mm. This value indicates that the evapotranspiration value is greater than the average monthly rainfall value during the period 2010 – 2019. Namlea Subdistrict experienced potential water loss for evaporation (APWL) in May of 35.30 mm, in August to November of August of 65.26 mm, in September of 156.24 mm, in October of 256.07 mm and in November of 303.45 mm. The land water balance in Namlea Subdistrict, namely rainwater deviation, occurs in May, then August to November, while the water surplus occurs in December to July, and continues in June and July. Namlea district annual runoff is 854.01 mm. Regarding agricultural irrigation development policies, this study recommends that it is necessary to pay attention to weaknesses in each food crop sub-sector.

FIRAT HAVZASI KARASU NEHRİNDEKİ AYLIK AKIMLARIN YAPAY SİNİR AĞLARI YAKLAŞIMINI İLE TAHMİNİ

This study aims to estimate streamflow values with artificial neural networks (ANN) using various meteorological parameters. In developing the ANN model, various combinations of precipitation, air temperatures, and potential evapotranspiration values were used as inputs, and streamflow values were obtained. Meteorological data is divided into 70% train, 15% test, and 15% validation. In the model's design, various training algorithms, network architecture, input combinations, and the number of iterations were tried, and the most suitable model was tested. Correlation coefficient (R), coefficient of determination (R2), absolute error (AE), and absolute relative error (ARE) coefficients were compared, and the most suitable model was selected. According to the analysis results, the optimal model was obtained using 2000 iterations, the architecture of the 4-4-1 model, and the Quasi-Newton algorithm. It was determined that the ANNs successfully modeled the rainfall-runoff relationship and produced reliable estimates. In addition, it was revealed that the inclusion of potential evapotranspiration values obtained by the Thornthwaite method into the model increases the model's success.

Estimation of diurnal-provided potential evapotranspiration using GNSS and meteorological products

In the context of global warming, extreme drought has seriously endangered the safety of human lives and assets, indicating an urgent need for its accurate monitoring and early detection. Since various types of drought monitoring indices are calculated from the variable of potential evapotranspiration (PET), thus the selection of models to derive PET has attracted broad attention in recent decades. Generally, the common-used Thornthwaite (TH) model possesses the features of calculation simplicity and great universality, however, its accuracy and temporal resolution (monthly) are relatively low, which greatly hinders the further uses of this model. Considering these restrictions, a novel method for estimating diurnal-provided PET values (DTH-PET) using the TH model was first proposed, in which a 31-day sliding window was adopted to improve its temporal resolution. The new method takes both the diurnal and “monthly” variation features into account. Verification results showed that, compared with the monthly TH model, the improvements in the mean root mean square (RMS) errors made by the new method was 3.1 mm. In addition, to further improve the accuracy of the DTH-PETs, a new high-order calibration function with the use of GNSS and meteorological measurements including ZTD, temperature and pressure was then constructed and fully validated. In comparison with the 29.95 mm mean RMS from the conventional TH model without calibration, the new method led to a 4.37 mm result, i.e., a 25.57 mm improvement (over 85%) was made after a thorough calibration process. In addition, the comparison of the newly-proposed method with the common-used first-order equation also further illustrates its superiority during the whole calibration process. Therefore, all these results suggest that, by using the new strategies proposed in this study, DTH-PET can be easily estimated with high accuracy using limited meteorological variables.

Estimating potential reference evapotranspiration using time series models (case study: synoptic station of Tabriz in northwestern Iran)

The potential evapotranspiration is considered as an important element of the hydrological cycle, which plays an important role in agricultural studies, management plans of irrigation and drainage networks, and hydraulic structures. Estimating the potential evapotranspiration reference of particular climatic regions at different time scales, which is one of the most important atmospheric parameters, is of a particular importance in the optimal use of resources. The time series analysis method, GARCH model, is applied in order to investigate changes and estimate the potential evapotranspiration. In the present study, the efficiency of GARCH series model related to processes of modeling and estimating potential evapotranspiration, which is estimated by FAO Penman–Monteith and Hargreaves methods, was investigated. Also, future values of potential evapotranspiration are modelled and estimated at the synoptic station of Tabriz. Results showed that Time Series is considered as a precise tool to estimate evapotranspiration values. It was found that GARCH (1.1) time series has better results for FAO Penman–Monteith and Hargreaves methods compared to other models; also, it simulates the process of time series changes with less error. Observed and predicted evapotranspiration charts of both methods indicated that observational evapotranspiration was highly close to the lower limit of estimated evapotranspiration. Therefore, applying lower limit estimation as a prediction value was suggested.

Evapotranspiration in hydrological models under rising CO2: a jump into the unknown

Many hydrological models use the concept of potential evapotranspiration (PE) to simulate actual evapotranspiration (AE). PE formulations often neglect the effect of carbon dioxide (CO2), which challenges their relevance in a context of climate change and rapid changes in CO2 atmospheric concentrations. In this work, we implement three options from the literature to take into account the effect of CO2 on stomatal resistance in the well-known Penman–Monteith PE formulation. We assess their impact on future runoff using the Budyko framework over France. On the basis of an ensemble of Euro-Cordex climate projections using the RCP 4.5 and RCP 8.5 scenarios, we show that taking into account CO2 in PE formulations largely reduces PE values but also limits projections of runoff decrease, especially under an emissive scenario, namely, the RCP 8.5, whereas the classic Penman–Monteith formulation yields decreasing runoff projections over most of France, taking into account CO2 yields more contrasting results. Runoff increase becomes likely in the north of France, which is an energy-limited area, with different levels of runoff response produced by the three tested formulations. The results highlight the sensitivity of hydrological projections to the processes represented in the PE formulation.

Estimation of Potential Evapotranspiration across Sri Lanka Using a Distributed Dual-Source Evapotranspiration Model under Data Scarcity

Evapotranspiration estimations are not common in developing countries though most of them have water scarcities for agricultural purposes. Therefore, it is essential to estimate the rates of evapotranspiration based on the available climatic parameters. Proper estimations of evapotranspiration are unavailable to Sri Lanka, even though the country has a significant agricultural contribution to its economy. Therefore, the Shuttleworth–Wallace (S-W) model, a process-based two-source potential evapotranspiration (PET) model, is implemented to simulate the spatiotemporal distribution of PET, evaporation from soil (ETs), and transpiration from vegetation canopy (ETc) across the total landmass of Sri Lanka. The country was divided into a grid with 6 k m × 6 k m cells. The meteorological data, including rainfall, temperature, relative humidity, wind speed, net solar radiation, and pan evaporation, for 14 meteorological stations were used in this analysis. They were interpolated using Inverse Distance Weighting (IDW), Universal kriging, and Thiessen polygon methods as appropriate so that the generated thematic layers were fairly closer to reality. Normalized Difference Vegetation Index (NDVI) and soil moisture data were retrieved from publicly available online domains, while the threshold values of vegetation parameters were taken from the literature. Notwithstanding many approximations and uncertainties associated with the input data, the implemented model displayed an adequate ability to capture the spatiotemporal distribution of PET and its components. A comparison between predicted PET and recorded pan evaporations resulted in a root mean square error (RMSE) of 0.75 mm/day. The model showed high sensitivity to Leaf Area Index (LAI). The model revealed that both spatial and temporal distribution of PET is highly correlated with the incoming solar radiation fluxes and affected by the rainfall seasons and cultivation patterns. The model predicted PET values accounted for 80–90% and 40–60% loss of annual mean rainfall, respectively, in the drier and wetter parts of the country. The model predicted a 0.65 ratio of annual transpiration to annual evapotranspiration.

Why the Effect of CO2 on Potential Evapotranspiration Estimation Should Be Considered in Future Climate

Potential evapotranspiration (PET) is an important factor that needs to be considered in regional water management and allocation; thus, the reasonable estimation of PET is an important topic in hydrometeorology and other related fields. There is evidence that increased CO2 concentration alters the physiological properties of vegetation and thus affects PET. In this study, changes in PET with and without the CO2 effect over China is investigated using seven CMIP6-GCMs outputs under seven shared socioeconomic pathways (SSPs) based scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5), as well as the contribution rate of CO2 on PET in different climatic regions. Changes in estimated PET based on modified Penman–Monteith (PM) method that considers the CO2 effect is compared with the traditional PM method to examine how PET quantity varies (differences) between these two approaches. The results show that the PET values estimated by the two methods explored opposite trends in 1961–2014 over entire China; it decreases with consideration of CO2 but increases without consideration of CO2. In the future, overall PET is projected to increase under all scenarios during 2015–2100 for China and its three sub-regions. PET generally tends to grow slower when CO2 is taken into account (modified PM approach), than when it is not (traditional PM method). In terms of differences in the estimated PET by the two methods, the difference between the two adopted methods increased in China and its sub-regions for the 1961–2014 period. In the future, the difference in estimated PET is anticipated to continuously increase under SSP3-7.0 and SSP5-8.5. Spatially, a much greater extent of difference is found in the arid region. Across the arid region, the PET difference is projected to be the highest at 138% in the mid-term (2041–2060) with respect to the 1995–2014 period, whereas it tends to increase slower in the long-term period (2081–2100). Importantly, CO2 is found to be the most dominant factor (−154.2% contribution) to have a great effect on PET changes across the arid region. Our findings suggest that ignorance of CO2 concentration in PET estimation will result in significant overestimation of PET in the arid region. However, consideration of CO2 in PET estimation will be beneficial for formulating strategies on future water resource management and sustainable development at the local scale.

Analysis of Groundwater Recharge in Mongolian Drylands Using Composite Vadose Zone Modeling

Knowledge of groundwater recharge (GR) is important for the effective management of water resources under semi-arid continental climates. Unfortunately, studies and data in Mongolia are limited due to the constraints in funding and lack of research infrastructures. Currently, the wide accessibility of freely available global-scale digital datasets of physical and chemical soil properties, weather data, vegetation characteristics, and depths to the water table offers new tools and basic information that can support low-cost physically based and process-oriented models. Estimates of GR over 41 study sites in Mongolia were obtained using HYDRUS-1D in a 2-m-thick soil profile with root depths of either 0.30 or 0.97 m by exploiting the daily precipitation and biome-specific potential evapotranspiration values. The GR simulated by HYDRUS-1D arrives at the water table and becomes the actual GR with a lag time that has been calculated using a simplified form of the Richards equation and a traveling wave model. The mean annual precipitation ranges from 57 to 316 mm year−1, and on average about 95% of it is lost by mean annual actual evapotranspiration. In the steppe region, the vegetation cover induces higher-than-normal actual transpiration losses and consequently lower GR. The mean annual GR rates span between 0.3 and 12.0 mm year−1, while travel times range between 4 and 558 years. Model prediction uncertainty was quantified by comparing actual evapotranspiration and GR with available maps and by a sensitivity assessment of lag time to the soil moisture in the deep vadose zone. The partial least squares regression (PLSR) was used to evaluate the impact of available environmental properties in explaining the 47.1 and 59.1% variability of the spatially averaged mean annual GR and travel time, respectively. The most relevant contributors are clay content, aridity index, and leaf area index for GR, and depth to the water table and silt content for the lag time. In data-poor, arid, and semi-arid regions such as Mongolia, where the mean annual GR rates are low and poorly correlated to precipitation, the ever-increasing availability of world databases and remote sensing products offers promise in estimating GR.