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FAO Irrigation and drainage paper No. 56
... Ensembles of the monthly climate data such as maximum, minimum, and air temperatures (Tmax, Tmin, Ta), relative air humidity (RH), wind speed at ten meters (u 10 ), and net radiation (R n ) which are crucial for the calculation of reference evapotranspiration (ETo) as well as precipitation (P), were calculated using averages of the monthly data obtained from the ve climate data sources. The reference evapotranspiration (ETo) was estimated using the Food and Agriculture Organization (FAO56) Penman-Monteith method, by Allen et al. (1998), as given below: ...
... Increasing ETo rates can lead to higher water demand, increasing the need for irrigation in agroforestry systems (Allen et al., 1998). ...
... The wettest and driest years were 1998 and 2002, respectively. The variability of precipitation expressed as standardized precipitation anomaly (SPA) identi ed wet years(SPA > 1;1998, 2000, and 2019) and dry years (SPA < -1; 1982, 1984, 1990, 2002, 2004, 2009, and 2015)(Fig. 7a). ...
This study investigated the variability and trends of precipitation (P), air temperature, and reference evapotranspiration (ET 0 ) in the Lake Tana sub-basin of Ethiopia from 1980 to 2023, assessing their implications for water resources, agriculture, and forestry development. The Lake Tana sub-basin, a crucial ecological and socio-economic zone within the Upper Blue Nile Basin, is increasingly vulnerable to climate change impacts. Using long-term monthly climate data from five sources, including MSWX-Past, MERRA-2, ERA-5, CRUTS4.06, and TerraClimate, spatiotemporal climate variability and trends were analyzed. The Penman-Monteith (FAO56) method was employed to estimate ET 0 , and statistical techniques, including the trend of linear regression, CV, and standardized precipitation anomaly, were used to assess trends and variability. Results indicate significant increasing trends in annual and Kiremt (June-September) rainfall, while Belg (February-May) and Bega (October-January) seasons showed non-significant decreasing trends. Air temperatures exhibited significantly increasing trends, with the highest monthly temperatures in March. ET 0 values were higher in the northern part of the sub-basin and during the Belg season. Rainfall variability was low for annual and Kiremt seasons but moderate to high for Belg and Bega, indicating higher unpredictability during drier seasons. The study also examined the climatic water balance which exhibited increasing seasonal and annual trends. Increased rainfall variability and rising temperature and annual & seasonal ET 0 pose challenges for sustainable resource management. Enhanced climate monitoring, integrated water management, and climate-resilient practices are crucial for sustainable forestry and mitigating climate change impacts in the Lake Tana sub-basin
... ET o is defined as the amount of water crops must consume to achieve maximum productivity at different growth stages under specific environmental conditions and current agricultural practices by FAO-56 [4]. It is not only a key link connecting soil water, crop water, and atmospheric water in the Soil-Plant-Atmosphere Continuum (SPAC) system ...
... This dataset partitioning strategy preserves the temporal structure of the time series and is consistent with best practices in time series forecasting evaluation [48][49][50], ensuring both robust model training and meaningful application-oriented validation [51]. At present, the traditional physics-based model (FAO-56 Penman-Monteith equation) is still considered the most effective method for estimating ETo because it takes into account both aerodynamics and thermodynamics [4], and the formula is as follows: Here, the daily meteorological data from 1980 to 2019 of Yulin meteorological station, including daily maximum temperature, daily minimum temperature, sunshine hours, relative humidity, and wind speed at 10 m height, were sourced from the China Meteorological Administration (http://data.cma.cn/, (accessed on 17 March 2025)), used to establish the ET o sequence data set (Equation (1)). ...
... At present, the traditional physics-based model (FAO-56 Penman-Monteith equation) is still considered the most effective method for estimating ET o because it takes into account both aerodynamics and thermodynamics [4], and the formula is as follows: ...
Accurate reference evapotranspiration (ETo) prediction is important for water resource management, particularly in arid regions where water availability is highly variable. However, the nonlinear and non-stationary characteristics of ETo time series pose challenges for conventional prediction models. Given this, in this study we evaluate eight decomposition-hybrid models that integrate various decomposition techniques with a long short-term memory (LSTM) network to enhance short-term (5-day, 7-day, and 10-day) ETo forecasting. Using a 40-year dataset from a meteorological station, we employ the Penman-Monteith equation to calculate ETo and systematically compare model performance. Results show that VMD-LSTM and EWT-LSTM achieve the highest accuracy in the testing set (R² = 0.983 and 0.992, respectively) but exhibit reduced robustness in the prediction phase due to excessive high-frequency components. In contrast, EMD-LSTM and ESMD-LSTM demonstrate superior predictive stability, with no significant differences from actual values (p > 0.05). These findings underscore the importance of selecting appropriate decomposition methods to balance high-frequency information and predictive accuracy, offering insights for improving ETo forecasting in arid regions.
... HYDRUS-1D (Simunek et al., 2005) has been sufficiently used to simulate the water movement between the water table and the crop root zone under various conditions (Skaggs et al., 2006;Sommer et al., 2003). The inter-seasonal climatic changes, refilled water in the soil profile (including irrigation water and rainfall), crop root uptake and water Gul et al., 2018;Allen et al., 1998). ...
This study was conducted to estimate the evapotranspiration and to probe the seasonal groundwater contribution in total crop water use by the sesame crop under different water table depths. The method of combining lysimeter was executed to investigate the groundwater contribution in total water used by the crop. The water table depths were maintained at 1.60, 2.0 and 2.40 m, respectively. Each water table depth was replicated for three times. Climate conditions under which crop was grown were monitored and all the water balance components were recorded accordingly. The obtained evapotranspiration (ET) from lysimeter experiment was compared with the predicted ET by CROPWAT model. The experimentally observed ET were 457.5, 452 and 428 mm under the water table depths of 1.60, 2.0 and 2.40 m, respectively. The predicted ET using CROPWAT model was 434 mm, which was very close to the observed values. Under the lysimeter experiment, the groundwater contribution in total crop water use was observed as 37%. The predicted crop coefficient was ranged from 0.38 to 0.98, whereas the experimental crop coefficient was 1.0. The trend of soil moisture balance predicted by the model revealed the same as that experimentally observed. Thus, the use of CROPWAT model is recommended to redesign irrigation amounts and to prevent soil salinity and waterlogging problems. Citation: Dahri, S.H., M. A. Mangrio, M. S. Mirjat, S. A. Dahri, Z. A. Aqlani, J. H. Jakhrani and G. M. Aghani. 2021. Assessing evapotranspiration rate and sesame (Sesamum indicum) crop water use under different water table depths. Agricultural Engineering International: CIGR Journal, 23 (1):57-67.
... The higher the volumetric soil moisture content, the higher is the permittivity (dielectric constant) of the soil and therefore the resulting total capacitance of the probe. Irrigation was scheduled in all treatments when 50% of the available soil moisture within the effective root depth was depleted 18 . ...
Freshwater scarcity has increased the reliance on low quality water for irrigation purposes. Brackish and/or high salinity irrigation water may increase soil salinity and reduce yields. This study was carried out for two consecutive seasons to study the effect of magnetic treatment of brackish water and soil mulching on strawberry growth and productivity and soil moisture-salinity distribution. For this purpose, three irrigation water types were used: tap water (W1), brackish water (W2), and magnetically treated brackish water (W3). Four different soil mulches were evaluated: rice straw mulch applied at rate of 3 t ha⁻¹ (M1), rice straw mulch applied at rate of 5 t ha⁻¹ (M2), white polyethylene plastic mulch (M3), and black polyethylene plastic mulch (M4) compared to bare soil (M0). The results revealed that magnetic water treatment (MWT) and soil mulching significantly enhanced crop growth and productivity and improved soil moisture-salinity distribution. The difference between M2 and M4 was not statistically significant in almost all the studied traits in both growing seasons. This result highlights the potential of using rice straw as a sustainable alternative to plastic mulch in strawberry cultivation. Strawberry marketable yield and water productivity increased significantly by 26.7% and 18.6% over the two growing seasons as a result of MWT, compared to untreated water. Moreover, MWT had a positive effect on reducing soil salinization. MWT led to a significant decrease in soil salinity by 17.8% compared to untreated water (W2) and the difference in soil salinity between W1 and W3 was not statistically significant. The integration of MWT and straw mulch at 5 t ha⁻¹ (W3M2) has resulted in marketable yield increase of 32.6 and 40.9% compared to brackish water irrigation and bare soil conditions (W2M0). Hence W3M2 could be adopted as a sustainable management practice for safe use of brackish irrigation water in strawberry cultivation
... Conversely, ET values were significantly lower in rainfed and pasture lands due to prevailing water shortage conditions, which restricted plant growth and water usage. The high spatial heterogeneity of ET across the study area, coupled with its vast expanse and diverse vegetation, posed a challenge for validating the calculated ET values using field measurements, but given that the crop coefficients are normalized, these values can be used for comparison in different regions (Allen et al., 1998). The crop coefficient (Kc) was computed as the ratio of actual ET (obtained from SEBAL) to the reference ET. (Agam et al., 2010;Allen et al., 2005;Grosso et al., 2018;Mkhwanazi et al., 2015;Zhou et al., 2014). ...
Agricultural drought is a natural and damaging phenomenon that is especially harmful to rainfed agriculture. It occurs when there is insufficient soil moisture in the root zone for plants to survive between two rainfall events. In the absence of soil moisture, a variety of losses, including soil evaporation and plant transpiration, cause an imbalance between water supply and water loss. An evapotranspiration-based index was used here to assess agricultural drought. We applied this framework to a less studied area near Fariman City in the northeast part of IRAN. Two time periods were selected for comparison including 2015 and 2016 spring season that are associated with dry and wet conditions, respectively. To calculate the drought index, actual and potential evapotranspiration were estimated by the Surface Energy Balance Algorithm for Land (SEBAL), the upgraded Priestley-Taylor method and remote sensing data. The Relative Water Deficit Index (RWDI) illustrated that lack of water in rainfed lands and pastures for the dry period was obtained from 80 to 100 percent, whereas this was between 50 and 70% for the wet period.
... The distributed taxonomy, depth and hydraulic parametrization of the soil is the one of the ACLA2 Apulian regional project (Caliandro et al., 2005), while the organic content is based on the European LUCAS database (de Brogniez et al., 2015). Potential evaporation has been estimated following the FAO procedure (Allen et al., 1998) interpolating the punctual measurement of wind speed and temperature with the ordinary kriging procedure. Vegetation dynamic over time has been considered variating the Leaf area index (LAI) every 4 days, namely the temporal resolution of the reference LAI-MODIS gridded products with 0.5 km spatial resolution (available online at https://lpdaac.usgs. ...
Identifying flood‐inducing processes remains a challenge in catchment hydrology due to the complex runoff dynamics, particularly in semi‐arid regions where surface and subsurface mechanisms alternatively drive streamflow across seasons. Tracer data can help identify hydrograph sources, but they are often unavailable or lack sufficient temporal resolution. To aid process identification at the event‐scale, we developed an integrated hydrological‐hydrodynamic framework and compared multiple model hypotheses informed by hydrological signatures. We systematically tested these hypotheses through falsification, meta‐evaluation, spatial validation, and posterior diagnostics, using the semi‐arid Salsola nested catchment in southern Italy as case study. While all model structures performed well on common calibration metrics, differences emerged in spatial transferability tests and alternative diagnostic assessments. Some models, despite strong performance, exhibited inconsistent representations of internal runoff mechanisms, indicating that they achieved good results for the wrong reasons. Furthermore, the choice of routing schemes significantly influenced high‐peak estimations and overall model performance, particularly when Horton‐type overland flow was considered. This underscores the need to treat routing methods as a key component in event‐scale modeling. Our findings reveal that during consecutive storm events in the study catchment, surface processes dominate the initial stages, whereas subsurface processes become more influential in later events, providing valuable insights that may be applicable to similar semi‐arid regions. Overall, we emphasize the importance of hypothesis testing in runoff process identification, which can compensate for the absence of hydrochemical data for hydrograph separation. Additionally, our results highlight the value of a landscape‐based modeling approach for distinguishing alternative runoff generation processes.
Precision irrigation requires reliable estimates of crop evapotranspiration (ET) using site-specific crop and weather data inputs. Such estimates are needed at high resolutions which have been minimally explored for heterogeneous crops such as orchards. In addition, weather information for estimating ET is very often selected from sources that do not represent conditions like heterogeneous site-specific conditions. Therefore, a study was conducted to map geospatial ET and transpiration (T) of a high-density modern apple orchard using high-resolution aerial imagery, as well as to quantify the impact of site-specific weather conditions on the estimates. Five campaigns were conducted in the 2020 growing season to acquire small unmanned aerial system (UAS)-based thermal and multispectral imagery data. The imagery and open-field weather data (solar radiation, air temperature, wind speed, relative humidity, and precipitation) inputs were used in a modified energy balance (UASM-1 approach) extracted from the Mapping ET at High Resolution with Internalized Calibration (METRIC) model. Tree trunk water potential measurements were used as reference to evaluate T estimates mapped using the UASM-1 approach. UASM-1-derived T estimates had very strong correlations (Pearson correlation [r]: 0.85) with the ground-reference measurements. Ground reference measurements also had strong agreement with the reference ET calculated using the Penman–Monteith method and in situ weather data (r: 0.89). UASM-1-based ET and T estimates were also similar to conventional Landsat-METRIC (LM) and the standard crop coefficient approaches, respectively, showing correlation in the range of 0.82–0.95 and normalized root mean square differences [RMSD] of 13–16%. UASM-1 was then modified (termed as UASM-2) to ingest a locally calibrated leaf area index function. This modification deviated the components of the energy balance by ~13.5% but not the final T estimates (r: 1, RMSD: 5%). Next, impacts of representative and non-representative weather information were also evaluated on crop water uses estimates. For this, UASM-2 was used to evaluate the effects of weather data inputs acquired from sources near and within the orchard block on T estimates. Minimal variations in T estimates were observed for weather data inputs from open-field stations at 1 and 3 km where correlation coefficients (r) ranged within 0.85–0.97 and RMSD within 3–13% relative to the station at the orchard-center (5 m above ground level). Overall, the results suggest that weather data from within 5 km radius of orchard site, with similar topography and microclimate attributes, when used in conjunction with high-resolution aerial imagery could be useful for reliable apple canopy transpiration estimation for pertinent site-specific irrigation management.
Climate change has intensified across Alpine regions, causing significant alterations in precipitation regimes and snowpack levels, with notable implications for ecosystems and water availability both locally and downstream. This study investigates meteorological and hydrological droughts in the western Alps using the Standardized Precipitation Evapotrans-piration Index (SPEI) and the Standardized Snowpack Index (SSPI). Drought duration, severity, and inter-index relationships were examined using the Seasonal Kendall (SK) test and the Bayesian Estimator of Abrupt change, Seasonality, and Trend (BEAST) to detect trends, seasonality, and abrupt shifts. The SK test revealed statistically significant decreasing trends across the region. More negative values of the SPEI index over longer timescales indicate worsening hydrological conditions , suggesting potential reductions in water availability and an increased risk of prolonged, severe droughts. Meanwhile, the BEAST analysis identified notable abrupt changes in both SPEI and SSPI, capturing increasing and decreasing shifts. These suggest that, while long-term trends indicate drying conditions, short-term increases likely associated with extreme weather events are also evident. These findings underscore the complexity of hydrological dynamics in the Alps and highlight the necessity for further detailed research to better understand and manage water resources resilience under changing climate conditions. Highlights − Climate change alters Alpine drought patterns, impacting water availability. − Western Alps analysis uses SPEI and SSPI indices to assess drought trends. − Trend analysis reveals drying trends, worsening hydrological conditions. − BEAST detects abrupt changes in drought linked to extreme weather events. − Findings highlight water resource risks, urging better resilience strategies. Graphical Abstract This Graphical Abstract Provides an Overview of the Investigation into Meteorological and Hydrological Droughts in the Western Alps, a Region Increasingly Affected by Climate change-induced Shifts in Precipitation and Snow Levels. The Study Employs the SPEI and SSPI Indices To Assess Drought Duration, Severity, and the Correlation between Atmospheric and Hydrological Conditions (highlighted in Red in the Graphical Abstract). To identify trends, seasonal patterns, and abrupt changes, the analysis integrates two statistical methods: the SK test (represented in blue) and the BEAST algorithm (represented in green). The findings highlight the complexity of Hydrological dynamics in the Alps, with significant drying trends detected by the SK test and abrupt Shifts captured by BEAST. More negative SPEI values over longer timescales indicate worsening Hydrological Conditions, suggesting an increased risk of prolonged Droughts. These results emphasize the need for continuous monitoring and adaptive water resource management To mitigate risks in a changing Climate
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