Evapotranspiration Research Articles

Comprehensive evaluation of nine evapotranspiration products from remote sensing, gauge upscaling and land surface model over China

Benefiting from the advancements in monitoring and measuring terrestrial evapotranspiration (ET), diverse ET products have been proliferated. This study evaluated nine ET products from three types, namely remote sensing-based retrievals (GLEAM, PML and PLSH), gauge-based upscaling (FCCRU, FCGSW and FCWFD) and land surface model-based reanalysis (ERA5-Land, GLDAS and MERRA) over China and its seven climate zones. Both spatial and temporal change trends in ET were investigated, and period feature were analyzed. Then, in-situ ET observations were used for validating the performances of ET products. The results demonstrate that all products show comparable performances in spatial distribution over China, but the mean ET values present evident discrepancies (433–563 mm/a). Among them, reanalysis ET products reproduce higher ET, but with less difference. In terms of climate sub-regions, the most significant discrepancies are located in QT. In addition, PLSH, MERRA and GLDAS present substantial increasing trends, while all three gauge-based upscaling ET products display decreasing trends. Regionally, all the ET products show positive trends in QT. Moreover, most of ET products present apparent periodic oscillation ranging from 2.0–5.5 year scales. At point scale, most ET products perform well at NMG and CBS sites (CC > 0.80, RMSE < 20 mm/month). However, general underestimations appear in northwestern China sites (HB and DX), and systematical overestimation exist in southern China sites (DHS and XSBN). By comparison, remote sensing-based ET products performs best, followed by gauge-based upscaling ET, comparatively, reanalysis-based ET products have poorest performances against in-situ ET observations. This study can provide valuable reference information for the selection of proper ET datasets for the hydrological simulation and analysis over China.

Combined effects of urbanization and climate variability on water and carbon balances in a rice paddy-dominated basin in southern China

Abstract Urbanization is known to elevate storm runoff, but how it influences carbon cycle and ecosystem productivity through altering the evapotranspiration (ET) process is less clear. We examined the combined effects of urbanization including change in impervious surface area (ISA) and climate variability on the water and carbon balances of the Qinhuai River Basin (QRB) over 2001–2018. QRB represents a typical rice paddy-dominated region that experienced rapid urbanization in southern China. We improved a monthly scale water supply stress index ecosystem service model by integrating local eddy flux measurements and high-resolution remote sensing data. We found a significant downward trend in both ET (−4.6 mm yr−1, p < 0.05) and gross primary productivity (GPP) (−10.4 gC m−2 yr−1, p < 0.05) but a significant upward trend in water yield (Q) (+28.6 mm yr−1, p < 0.05). These ecosystem function changes coincided with a 96% increase in urban areas, 1.9-fold increase in ISA, and a 37% reduction in rice paddy fields. The mean annual watershed GPP decreased from 1048 gC m−2 to 998 gC m−2 while the annual Q increased from 284 mm to 669 mm from 2001 to 2018. Scenario modeling experiments suggested that the negative impacts of loss of rice paddy fields and increase in ISA on ET and GPP overwhelmed the positive impacts of climate warming. The reduction in GPP and increase in Q were largely attributed to the increases in ISA, not necessarily due to changes in land use types (e.g. urban area). The expansion of urban area, increase in ISA and reduction in leaf area index, and increase in precipitation explained the increase in Q. Our research offers insight about the interactions of carbon and water cycles through the critical ET processes under a changing climate and land surface characteristics at a watershed level. Our modeling tool and analysis provides land managers and policy makers information for designing effective ‘Urban Nature-based Solutions’ to mitigate the negative environmental effects of urbanization on carbon and water resources.

Investigating Effective Reconnaissance Drought Index Ability to Reproduce Drought Signature over the Massili Basin (Burkina Faso)

Drought is a significant natural hazard particularly in arid and semi-arid regions where water resources management is already challenging. Burkina Faso, a landlocked country located in the Sahel region, is highly vulnerable to drought due to its arid climate. The country has experienced recurrent droughts since the 1970s, with significant impacts on its population and economy. To develop effective drought mitigation strategies, a comprehensive understanding of drought characteristics is required. This study investigates historical long-term drought trends in the Massili basin located in central Burkina Faso. For this purpose, drought features has been analyzed based on the Effective Reconnaissance Drought Index (eRDI) at various months of accumulation. To calculate the Effective Reconnaissance Drought Index for the Massili Basin, monthly precipitation (Prct), minimum temperature (Tmin), and maximum temperature (Tmax) data spanning from 1960 to 2021 were obtained from the National Meteorological Agency of Burkina Faso. The Potential evapotranspiration (ETP) was estimated using the Hargreaves method. Our findings indicate that under eRDI-3, 1964 (1.86), 2020 (1.53), and 2021 (0.63) are the wettest years, while 1963 (-0.65) and 1998 (-0.76) are the driest. Under eRDI-12, a significant portion of the values falls within the range of -0.14 to 0.03. In the case of eRDI-24, a substantial number of the values cluster between -0.08 and 0.08. This distribution highlights near-normal drought conditions (-0.99 to 0.99) as the most frequent occurrence within the watershed. The desertification of the Sahel area has been a topic of discussion for decades. However, these findings of this study reinforce the prevailing belief in a partial re-greening of the Sahel region.

Comprehensive Review of Crop Water Requirement Estimation Techniques: Approaches, Challenges, and Future Directions

In order to meet the growing demand for water, water scarcity is a significant issue that needs attention. Agriculture crops are not getting enough water because of this problem. Consequently, figuring out how much water a given crop needs requires using the right method. Accurate crop water requirements must be measured in order to schedule irrigation effectively, which in turn leads to efficient crop water management. To restore the lost moisture and promote the best possible growth for plants, irrigation is used. Water management and irrigation scheduling fundamentally depend on an accurate calculation of the crop's crop water requirements (ETc). Accurate evapotranspiration measurements are necessary for effective irrigation water management. Evapotranspiration (ET), a process that measures the amount of water lost from soil and crops through transpiration and evaporation processes, respectively, is dependent on a variety of meteorological factors. A significant factor in determining crop water requirements and irrigation schedules is reference evapotranspiration. There exist multiple theories and methodologies for estimating reference evapotranspiration, ranging from empirical to physical based. Reference Evapotranspiration is referred to the idea behind ET is to calculate ET based on a reference surface that is comparable to a deep surface of green grass that is consistently growing, completely covering the surface with enough water, and looking stable. The goal of irrigation futures is to choose a suitable model for estimating reference crop evapotranspiration. In order to calculate the amount of water needed for a crop, multiply ETo by the crop coefficient (Kc), which is dependent on the phases and length of a crop's growth. Regression, fuzzy logic, Penman-Monteith, Blaney-Criddle, Hargreaves, ANN and WNN, and other conventional and non-traditional methods are used to estimate ETo.

Divergent Drying Mechanisms in Humid and Non-Humid Regions Across China

Understanding the drying mechanism is critical for formulating targeted mitigation strategies to combat drought impacts. This study aimed to reveal divergent drying mechanisms in humid and non-humid regions across China from the multidimensional perspectives of climate, vegetation, and energy balance. During the period 1982–2012, the Standardized Precipitation Evapotranspiration Index (SPEI) revealed non-significant drying trends across China. Simultaneously, temperature and precipitation indicated a warming and drying pattern in the humid regions, contrasted with a warming and moistening pattern in the non-humid areas. The coupling effects of declined precipitation, increased vegetation coverage, and elevated temperature exacerbated dryness in the humid regions, while pronounced warming dominantly caused dryness in the non-humid regions. The inverse correlations between the actual evapotranspiration (ET) with precipitation and potential ET (PET) highlighted the principal role of moisture availability in divergent drying mechanisms over humid and non-humid regions. Random Forest models recognized precipitation and PET as the primary factors influencing SPEI in the humid and non-humid regions, respectively. Ongoing warming from 2013 to 2022 mitigated dryness in the humid regions due to the increased latent heat at the expense of sensible heat. Conversely, warming, amplified by the heightened sensible heat, exacerbated drought in the non-humid regions. By identifying the contrasting responses of humid and non-humid regions to warming and moisture availability, this study provides crucial insights for policymakers to mitigate drought impacts and enhance resilience in vulnerable non-humid areas.

Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition

AbstractVarious critical applications, spanning from watershed management to agricultural planning and ecological sustainability, hinge upon the accurate prediction of reference evapotranspiration (ETo). In this context, our study aimed to enhance the accuracy of ETo prediction models by combining a variety of signal decomposition techniques with an Artificial Bee Colony (ABC)–artificial neural network (ANN) (codename: ABC–ANN). To this end, historical (1979–2014) daily climate variables, including maximum temperature, minimum temperature, mean temperature, wind speed, relative humidity, solar radiation, and precipitation from four arid and semi-arid regions in Egypt: Al-Qalyubiyah, Cairo, Damietta, and Port Said, were used. Six techniques, namely, Empirical Mode Decomposition, Variational Mode Decomposition, Ensemble Empirical Mode Decomposition, Local Mean Decomposition, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, and Empirical Wavelet Transform were used to evaluate signal decomposition efficiency in ETo prediction. Our results showed that the highest ETo prediction accuracy was obtained with ABC-ANN (Train R2: 0.990 and Test R2: 0.989), (Train R2: 0.986 and Test R2: 0.986), (Train R2: 0.991 and Test R2: 0.989) and (Train R2: 0.988 and Test R2: 0.987) for Al-Qalyubiyah, Cairo, Damietta, and Port Said, respectively. The impressive results of our hybrid model attest to its importance as a powerful tool for tackling the problems associated with ETo prediction.

Downscaling MODIS evapotranspiration into finer resolution using machine learning approach on a small scale, Ribb watershed, Ethiopia.

By monitoring evapotranspiration (ET), the exchange of water and energy between the soil, plants, and the atmosphere can be controlled. Routine estimations of ET on a daily, monthly, and seasonal basis can give relevant information on small-scale agricultural practices, such as the Ribb watershed in Ethiopia. However, MODIS sensors have recently given high temporal resolution ET products across large areas, but their low spatial resolution limits its application on a local scale. The primary goal of the study was to downscale the MODIS ET (1km) product to a finer spatial resolution at the watershed level. The model's 12 predictor variables (NDVI, EVI, LAI, FVC, SAVI, NDMI, NDWI, Albedo, emissivity, LST, and DEM: slope and elevation) were produced using the random forest (RF) algorithm using Sentinel-2 (S-2) 20m and Landsat-8 (L-8) 30m. The RF regression model was used to assess the relationship between predicted variables and downscaled MODIS ET. The FAO-PM ET model, developed from meteorological stations, was validated by and RMSE for three seasons (rainy, post-rainy, and dry) in 2022. The results were in good agreement with MODIS ET, with an RMSE of 0.22 for S-2 and 0.28 for L-8. In the FAO-PM ET model, the downscaled result showed greater spatial details and better agreement with gage station readings ( and ). Thus, considering the effectiveness and simplicity of machine learning techniques, our study demonstrated the potential for ET downscaling. Furthermore, the study suggests integrating spatiotemporal time series data to reach higher resolution.

Intraurban spatial configuration, hydrologic similarity areas and their roles in urban drainage dynamics

ABSTRACT Hydrologic Similarity Areas (HSA) were delimited in the Belém catchment, and their responses on the water balance were evaluated. A cluster analysis of intraurban spatial configuration was conducted to delimit six HSA. The urban water balance was performed in the Aquacycle model, whose calibration resulted in satisfactory adherence to the measured streamflow. Indeed, the modeling results show that the intraurban spatial heterogeneity is reflected in the annual and daily water balance. The evapotranspiration rates can represent 25% to 50% precipitation in the different HSA. Moreover, infiltration and runoff can range five times among the HSA. In analyzing the daily events, we identified the areas that most contributed to runoff and those with higher infiltration capacity during flood events. Such results may support future studies on understanding flood dynamics and guide the implementation of sustainable urban drainage solutions that aim to reduce runoff and control flood risk.

Climate-Smart Drip Irrigation with Fertilizer Coupling Strategies to Improve Tomato Yield, Quality, Resources Use Efficiency and Mitigate Greenhouse Gases Emissions

Background: Integrated water and fertilizer management is important for promoting the sustainable development of agriculture. Climate-smart drip irrigation with fertilizer coupling strategies plays an important role to mitigate greenhouse gas emissions, ensuring food production, and alleviating water scarcity and excessive use of fertilizers. Methods: The greenhouse experiment consists of three drip irrigation treatments which include D1: drip irrigation (100 mm); D2: drip irrigation (200 mm); D3: drip irrigation (300 mm) under three different fertilizer management practices N1: nitrogen level (150 kg N ha−1); N2: nitrogen level (300 kg N ha−1); N3: nitrogen level (450 kg N ha−1). Results: The results showed that significantly improved soil moisture contents, quality and tomato yield, while reduced (38.6%) greenhouse gas intensity (GHGI) under the D3N3 treatment. The D2 and D3 drip irrigation treatments with 450 kg nitrogen ha−1 considerably improved NH4+-N contents, and NO3−-N contents at the fruit formation stage. The improve in net primary productivity (NPP), net ecosystem productivity (NEP), evapotranspiration (ET), and ecosystem crop water productivity (CWPeco) through D3N3 treatment is higher. The D3N3 treatment improved (28.2%) the net global warming potential (GWP), but reduced GHGI, due to improved (18.4%) tomato yield. The D3N3 treatment had significantly greater irrigation water productivity (IWP) (42.8%), total soluble sugar (TSS) (32.9%), vitamin C content (VC) (39.2%), soluble sugar content (SSC) (44.2%), lycopene content (41.3%) and nitrogen use efficiency (NUE) (52.4%), as compared to D1N1 treatment. Conclusions: Therefore, in greenhouse experiments, the D3N3 may be an effective water-saving and fertilizer management approach, which can improve WUE, tomato yield, and quality while reducing the effect of global warming.

Vegetation Greening Promoted the Precipitation Recycling Process in Xinjiang

Under the combined influences of climate and vegetation change, land–atmosphere interactions have enhanced, and precipitation recycling is an important part of this. Previous studies of the precipitation recycling process have focused on calculating the precipitation recycling rate (PRR) and analyzing the influencing factors. However, the climate-driven and vegetation-induced precipitation recycling process variations were not quantified. This study has systematically examined the precipitation recycling process in a typical arid region using the Eltahir and Bras model, random forest algorithm, and partial least-squares structural equation modeling. During 1982–2018, the leaf area index (LAI) and evapotranspiration (ET) rate both increased significantly, with growth rates of 0.06 m2m−2/decade and 13.99 mm/decade, respectively. At the same time, the average PRR in Xinjiang was 13.92% and experienced significant growth at a rate of 1.28%/decade. The climate-driven and vegetation-induced PRR variations were quantified, which contributed 79.12% and 20.88%, respectively. In addition, the positive effects of both of these on PRR variations through ET did not increase with the increase in ET, but rather decreased sharply and then stabilized. This study can provide favorable theoretical support for mitigating the contradiction in water use and balancing economic development and ecological security by quantifying the regulation of precipitation by vegetation.

Impact scenarios on groundwater availability of southern Italy by joint application of regional climate models (RCMs) and meteorological time series.

Nowadays the phenomenon of global warming is unequivocal, as confirmed by the latest reports of the IPCC and studies of the climate-change impacts on ecosystems, global economy, and populations. The effect of climate change on groundwater is a very relevant task especially for regions dependent chiefly on groundwater availability, as for the southern Italy. In such a territorial framework, to achieve a detailed hydro-climatological characterization, an Ensemble of 15 RCMs (E15) derived from the EURO-CORDEX project was analyzed considering two IPCC Representative Concentration Pathways (RCP4.5 and RCP8.5). The E15 was calibrated over the period (1950-1996) by a statistical comparison with data observed by the regional meteorological network managed by the former National Hydrological Service (SIMN), Department of Naples. The effects of climate change on air temperature (T), precipitation (P) and, consequently, on actual evapotranspiration (ETR) and effective precipitation Pe (P - ETR) were analyzed until 2100. The latter was considered as a proxy of groundwater recharge of the principal aquifer systems, represented chiefly by the karst aquifers. As a principal result, it was found that the E15 is basically able to reproduce the observed annual precipitation (OBSP) and mean annual air temperature (OBST), being characterized by a very similar frequency distribution. Accordingly, an inferential statistical approach was performed for calibrating E15 precipitation (E15P) and air temperature (E15T) based on the compensation of the difference with OBSP (+ 7%) and OBST (-16%). The E15 projects a reduction in precipitation and an increase in air temperature under both RCPs, with a divergence point between the two scenarios occurring by about 2040. As a principal result, Pe shows declining trends for both RCP scenarios, reaching a decrease of the 11-yrs moving average down to -20%, for RCP4.5, and -50%, for RCP8.5, even if characterized by relevant inter-annual fluctuations.

Land Suitability Assessment and Crop Water Requirements for Twenty Selected Crops in an Arid Land Environment

Expanding projects to reclaim marginal land is the most effective way to reduce land use pressures in densely populated areas, such as Egypt’s Nile Valley and Delta; however, this requires careful, sustainable land use planning. This study assessed the agricultural potential of the El-Dabaa area in the northern region of the Western Desert, Egypt. It focused on assessing land capability, evaluating crop suitability, mapping soil variability, and calculating crop water requirements for twenty different crops. In this work, we evaluated land capability using the modified Storie index model and assessed soil suitability using the land use suitability evaluation tool (LUSET). We also calculated crop water requirements (CWRs) utilizing the FAO-CROPWAT 8.0 model. Additionally, we employed ArcGIS 10.8 to create spatial variability maps of soil properties, land capability classes, and suitability classes. Using a systematic sampling grid, 100 soil profiles were excavated to represent the spatial variability of the soil in the study area, and the physicochemical parameters of the soil samples were analyzed. The results indicated that the study area is primarily characterized by flat to gently sloping surfaces with deep soils. Furthermore, there are no restrictions on soil salinity or alkalinity, no sodicity hazards, and low CaCO3 levels. On the other hand, the soils in the study area are coarse textured and have low levels of CEC and organic matter (OM), which are the major soil limiting factors. As a result, the land with fair capability (Grade 3) accounted for the vast majority of the study area (87.3%), covering 30599.4 ha. Land with poor capability (Grade 4) accounted for 6.5% of the total area, while non-agricultural land (Grade 5) accounted for less than 1%. These findings revealed that S2 and S3 are the dominant soil suitability classes for all the studied crops, indicating moderate and marginal soil suitabilities. Furthermore, there were only a few soil proportions classified as unsuitable (N class) for fruit crops, maize, and groundnuts. Among the crops studied, barley, wheat, sorghum, alfalfa, olives, citrus, potatoes, onions, tomatoes, sunflowers, safflowers, and soybeans are the most suitable for cultivation in the study area. The reference evapotranspiration (ETo) varied between 2.6 and 5.9 mm day−1, with higher rates observed in the summer months and lower rates in the winter months. Therefore, the increase in summer ETo rates and the decrease in winter ones result in higher CWRs during the summer season and lower ones during the winter season. The CWRs for the crops we studied ranged from 183.9 to 1644.8 mm season−1. These research findings suggest that the study area is suitable for cultivating a variety of crops. Crop production in the study area can be improved by adding organic matter to the soil, choosing drought-resistant crop varieties, employing effective irrigation systems, and implementing proper management practices. This study also provides valuable information for land managers to identify physical constraints and management needs for sustainable crop production. Furthermore, it offers valuable insights to aid investors, farmers, and governments in making informed decisions for agricultural development in the study region and similar arid and semiarid regions worldwide.

Distribution of evapotranspiration components along vertical layers and their controls in dry days of larch plantation in the Liupan Mountains of northwest China

Precise quantification of forest evapotranspiration (ETf) including transpiration from tree (Tt), shrub (Ts), and herb (Th) layers, as well as evaporation from litter (El) and soil (Es) layers, and elucidating their responses to environmental conditions and stand structures are crucial for forest water management in water-limited forests. In this study, we observed the Tt, Ts, Th, El, and Es, reference evapotranspiration (ETo), soil volumetric water content (SWC), litter water content (LWC), leaf area index (LAI) in tree, shrub, and herb layers, and canopy shade (Ksc) from tree layer of the Larix principis-rupprechtii plantation during the dry days from May to October of 2021 and 2022 to elucidate the distribution of evapotranspiration along vertical layers and their environmental and structural determinants. The results indicated that the contributions of Tt, Ts, Th, El, and Es to ETf during the dry days in 2021 (2022) were 42.1 % (44.7 %), 9.2 % (8.1 %), 8.2 % (8.6 %), 15.0 % (13.1 %), and 25.5 % (25.5 %), respectively. Although Tt and Ts demonstrated quadratic relationships with ETo, Th, El, and Es exhibited linear relationships. All ETcs demonstrated a saturated exponential relationship with either SWC or LWC. Furthermore, Tt, Ts, and Th showed a saturated exponential relationship with their respective LAI, whereas El and Es exhibited a cubic relationship with LAI in tree layers. All understory ETcs (Ts, Th, El, and Es) decreased exponentially with the Ksc. The multi-factor models of evapotranspiration component (ETc) from different vertical layers, which coupled the impacts of environmental conditions and vertical structure, were developed, and provided superior accuracy (R2 = 0.78–0.88, NSE = 0.78–0.86, RSME = 0.03–0.16). Such insights deepened the understanding of vertical structural distribution and multi-factor responses of ETcs in forest ecosystems and hold the potential to inform and optimise forest water management strategies.

Identification of thresholds and key drivers on Water Use Efficiency in different maize ecoregions in Yellow River Basin of China

Identifying the constrains on water use efficiency (WUE) of crops along a wet-to-dry gradient is important due to irrigation water scarcity, as well as the increasing drought risk under climate change in China. This study coupled five high-resolution climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6) with the Decision Support System for Agrotechnology Transfer (DSSAT)-CERES-Maize model to quantify drought risk and the drivers affecting WUE in five major maize ecoregions of the Yellow River Basin (YRB) under three future scenarios (SSP126, SSP370, and SSP585) for both the historical baseline (1985-2014) and three future periods: 2021-2040 (2030s), 2041-2070 (2050s), and 2071-2100 (2080s). And a bias correction method was implemented for the crop model to analyze optimal WUE thresholds for maize across varying dry-wet gradients. The results indicated that future drought risk will likely persist in the YRB under all scenarios, but with regional differences in drought severity and frequency. The southwestern region (V) experienced the highest frequency of drought (62.50%-SSP126), while the northwestern region (III) exhibited the lowest frequency (33.00%-SSP585) in 2030s, and 83.30% of areas in the southwestern (V) showed significant wetting in the 2080s under SSP126. The bias-corrected CERES-Maize model effectively simulated crop yield and evapotranspiration (ET), resulting in an average reduction of 4.00% and 9.73% in normalized root mean square error (nRMSE) respectively. Distinct WUE thresholds ranging from 1.96 to 8.41 kg ha−1 mm-1 were observed across various scenarios-periods in the maize regions, mostly under slight and moderate dry/wet conditions. Notably, all SSP585 scenarios demonstrated a decrease in WUE thresholds compared to the baseline. Across all scenarios and periods, WUE was mainly driven by yield in the eastern regions (I and II) but by ET in the western regions (III, IV, and V). These findings suggest that regions experiencing varying degrees of drought severity should undergo differentiated management and optimization of agricultural practices to improve WUE under future climate scenarios.

Quantification of the Effect of Soil and Biophysical Parameters on Water Balance Modelling Using SWAT+ in Forested Catchments

ABSTRACTAccurate simulation of water balance components is crucial for effective water and land management practices. The performance of process‐based hydrological models relies on the accurate determination of input variables. The objective of this study is to quantify the magnitude of the effect of soil properties (depth and texture) and biophysical parameters on water balance simulation for a forested catchment using the Soil and Water Assessment Tool (SWAT+). Simulations were carried out for a baseline scenario using the default soil inputs, followed by extending the soil profile depth up to 15 m under three different rainfall scenarios. Sensitivity analysis of model outputs was performed using the SENSitivity ANalysis (SENSAN) programme of the Parameter ESTimation (PEST) suite, coupled with SWAT+. The results showed that increasing soil profile depth to 15 m led to around 50% increase in water yield, and around 20% reduction in percolation with slight variations across the three rainfall scenarios. Evapotranspiration rates were slightly increased in deeper soil profiles. The sensitivity of evapotranspiration, surface runoff, and percolation to LAI‐related biophysical parameters was pronounced, highlighting the need to include such parameters in SWAT+ model calibration. The water uptake from deeper soil layers by deep roots, even in rocky substrates, as documented in the literature, is not adequately captured by the SWAT+ model. Our work showed that in general, developing local soil databases with detailed information on deeper layers is needed, to improve the accuracy and reliability of hydrological models in predicting water fluxes, thereby supporting informed water resources management decisions.

Modeling carbon dynamics from a heterogeneous watershed in the mid-Atlantic USA: A distributed-calibration and independent verification (DCIV) approach

The terrestrial ecosystem plays a vital role in regulating regional and global carbon budgets. Ecosystem models are extensively employed to estimate carbon fluxes across different spatial scales. However, there remains a need to reduce the uncertainties associated with model parameterization and input data. To address these limitations, we assessed a distributed-calibration and independent-verification (DCIV) approach that uses (1) remotely sensed net primary production (NPP) and evapotranspiration (ET) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), (2) multi-site eddy covariance net ecosystem exchange (NEE) data; and (3) field sampling of soil organic carbon (SOC) and aboveground biomass (ABG) data to improve the overall predictability of carbon fluxes for the different land use and land cover (LULC) types at a watershed scale. The DCIV approach was applied to an advanced version of the Soil and Water Assessment Tool (SWAT)-Carbon (or SWAT-C), equipped with Century-based SOC algorithms to simulate carbon dynamics for watersheds with heterogeneous vegetation. The objective of the modeling effort was to assess carbon stocks and fluxes under different land management scenarios for a 3000-acre experimental farm and forest preserve in the northeastern United States. Our study showed that a large SOC stock of at least 100 tons ha−1 is stored under mixed forest, deciduous, shrubland, and floodplain (grass). Our study also showed that converting floodplain (grass) to deciduous forest has the potential to increase CO2 uptake (-NEE) by an order of three magnitude and ABG by 77 %, leading to an increased SOC stock of 23 % after twenty years. Similarly, we found that converting ungrazed grassland to grazed pasture leads to a non-statistically decreasing trend of SOC, especially in the 0–30 cm soil layer. Thus, the methodology used in this study can be applied to improve carbon dynamic prediction from a heterogeneous watershed at a regional scale.

Irrigation rates and turfgrass evapotranspiration in cities with contrasting water availability

AbstractAs water scarcity is worsened by drought and climate change, there is more interest in efficient management of urban irrigation, requiring understanding of the drivers of evapotranspiration (ET) and the role of irrigation inputs. We developed and validated a method to accurately measure ET of turfgrass lawns in contrasting climates using portable static chambers. We made in situ measurements of ET and irrigation inputs in lawns across three metropolitan areas in the United States with varying climatic conditions, water availability, and water conservation policies: Salt Lake Valley, Utah; San Fernando Valley, California; and Tallahassee, Florida. In full sun, mean daily ET estimates (ETsun) were 0.7 ± 0.4 mm day−1 in Tallahassee, 1.6 ± 0.8 mm day−1 in Los Angeles, and 3.3 ± 1.1 mm day−1 in Salt Lake Valley. In the shade, daily ET estimates (ETshade) were two to three times lower. In all three regions, ET was primarily driven by solar radiation (I0) and atmospheric vapor pressure deficit (D). Across the cities, irrigation rates were a key driver of ET, along with I0 and D. Daily irrigation ranged from 0 mm day−1 in Tallahassee (most were unirrigated) to 1.9 ± 1.2 mm day−1 in Los Angeles and 5.1 ± 2.9 mm day−1 in Salt Lake Valley. ET increased linearly with irrigation up to ~3 mm day−1, after which ET remained relatively constant despite irrigation increases. Our results highlight the importance of accounting for nonlinear responses and shading effects on ET in developing accurate irrigation recommendations.

Assessment of upscaling methodologies for daily crop transpiration using sap flows and two-source energy balance models in almonds under different water statuses and production systems

Abstract. Daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote-sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, and so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies used to retrieve Td in almond trees with different production systems and water statuses. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th–TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo), and potential evapotranspiration (ETp). These approaches were first evaluated with in situ sap flow (T–SF) data and were then applied to the Th–TSEB. Daily T–SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T–SF and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water-stressed trees. However, the daily upscaling approaches applied in the TSEB (Td–TSEB) failed to detect differences between production systems. The lack of sensibility of Th–TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The use of ETp as a reference variable could address this issue as it incorporates various aerodynamic and radiative properties associated with different canopy architectures that influence the daily Th–SF pattern. However, more accurate ETp estimates or more advanced ETp models are needed.

Long-term analysis of reference evapotranspiration variations in the lower Bhavani basin

Evapotranspiration is a crucial component of the hydrological cycle and is profoundly influenced by climate change. Assessing regional evapotranspiration changes is essential for effective water resource management. The study investigated the dynamics of reference evapotranspiration in the Lower Bhavani Basin, a region with diverse landscapes increasingly vulnerable to climatic variability. Reference evapotranspiration data from the Food and Agriculture Organization using the AgERA5 dataset was analyzed to assess annual and seasonal trends from 2000 to 2022. The result showed that the mean yearly reference evapotranspiration in the basin is 1672.87 mm, with a significant decline of 3.53 mm per year. Seasonal analysis revealed a consistent decreasing trend across all seasons, with the southwest monsoon season showing the most significant reduction in evapotranspiration rates. The notable shift in the annual evapotranspiration rate was observed in 2016, highlighting the impact of climate change. Further, temperature, solar radiation and relative humidity were identified as the dominant factors influencing evapotranspiration rates in the basin. The relative moisture index indicated prevalent dry conditions, making the region susceptible to water stress. The findings provide critical insights for regional water resources management and accentuate the need for sustainable water management strategies to mitigate the impacts of climate change.

Variation Characteristics of Actual Evapotranspiration and Uncertainty Analysis of Its Response to Local Climate Change in Arid Inland Region of China

Exploring the variation characteristics of actual evapotranspiration (ETa) and its response to climate change in the arid inland region of China is of great significance for strengthening regional water resources management and maintaining ecological environment security and stability. Taking the Dulan River Basin as the research area, based on the meteorological data from the Wulan Station and hydrological data from the Shanggaba Station from 1981 to 2020, the variation characteristics of ETa at the annual scale were analyzed. The ETa estimation model and joint distribution model of P and potential evapotranspiration (ET0) was constructed based on climate factors, and the uncertainty of ETa response to climate change was explored with the water balance method, multiple linear regression, marginal distribution function, Copula function, and Monte Carlo algorithm. The results showed that the multi-year mean value of ETa in the study area was 261.6 mm, and the interannual process showed an insignificant upward trend, and had no abrupt change during the period. There were two obvious main cycles, which were 19-year periodic changes on the 30-year time scale and 6-year periodic changes on the 9-year time scale. The ETa estimation model based on precipitation (P) and ET0 had good simulation accuracy. The optimal marginal distributions of P and ET0 were Pearson-III (P-III) distribution and Generalized Extreme Value (GEV) distribution, respectively. The Copula joint distribution probability density of P and ET0 was a symmetric saddle-shaped distribution. ETa showed an inverted ‘S’ distribution with the change in joint guarantee rate of P and ET0, ranging from 116.9 mm to 498.6 mm. ETa was an interval range under a certain joint guarantee rate. The research results can provide support for the assessment of ETa, and help to further understand the driving mechanism of climate change on ETa in the arid inland region of China.