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General function for soil evaporation reduction coefficient K r , for two-stage linear model ( from Allen et al. 1998 )
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The crop coefficient during the initial period K c ini varies with wetting frequency, evaporative demand, and water-holding capacity of the upper soil layer. It is possible to develop a semitheoretical integrated function to predict the average K c ini representing the initial period of a growing season when the soil is mostly bare and that incorpo...
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... K r = dimensionless evaporation reduction coefficient that is dependent on the cumulative depth of water depleted ( evaporated ) from the soil surface layer. The second stage, when K r is decreasing, begins when D e exceeds REW. At this point, the soil surface is visibly dry, and evaporation from the soil in the linear model is presumed to de- crease in proportion to the amount of water remaining in the surface soil layer. In the following derivation, the K r is expressed using cumulative evaporation D e from the surface soil layer ( the depth of the layer is defined later . TEW − D e K r = ͑ 3 ͒ TEW − REW for when D e Ͼ REW, where total evaporable water ͑ TEW ͒ = maximum depth of water that can be evaporated from the surface soil layer when the layer has been initially completely wetted. Units for TEW, REW, and D e are in millimeters. In Eq. ( 3 ) , REW Ͻ TEW and is contained in TEW. The general form for the K r function is illustrated in Fig. 1. An advantage to basing Stage 2 drying on D e , with limits of TEW, is that the conservation of mass is implicitly adhered to. In other words, total evaporation per wetting event is limited to TEW as specified by the user. In the FAO-56 application, the soil surface layer is presumed ca- pable of drying during evaporation to nearly an air dry soil water content. This content is estimated in the procedure as halfway between wilting point WP and oven dry ( no water left ) . In other words, 0.5 WP is presumed to approximate the air dry soil of the layer. This assumption can, of course, be modified to follow local observation. The maximum total depth of water that can be re- moved by evaporation during a complete drying cycle during summer conditions is estimated as TEW max = 1000 FC − 0.5 WP Z e 4 where TEW max = maximum depth of water that can be evaporated from the surface soil layer when the layer has been initially completely wetted ( mm ) . When the surface soil layer has been completely recharged, TEW= TEW max . Otherwise, the value for TEW is reduced from TEW max as described in Eqs. ( 6 ) – ( 8 ) . Field capacity FC and WP are expressed in ͑ m 3 m −3 ͒ and Z e = effective depth of the surface soil subject to drying by way of evaporation to the 0.5 WP content. Because Z e is an effective depth, some evaporation or soil drying will be observed to occur below Z . FAO-56 recommended values for Z e of 0.10– 0.15 m, with 0.1 m for coarse soil and up to 0.15 m for fine soil. The basis for these values was experimental data from Ritchie ( 1972 ) , Hanks and Hill ( 1980 ) and Wright ( 1982 ) . Typical values for FC , WP , and TEW are given in Allen et al. ( 1998, 2005 ) . The value for Z e can be changed to fit local observation. Readily evaporable water represents the cumulative evaporation at the end of Stage 1 drying. The REW is generally highest for medium textured soils having a pore size distribution that pro- motes both high moisture retention and moderate hydraulic conductivity. The REW is lower for coarse soils having low moisture retention capacity and for clays that have low hydraulic conductivity, which is needed to supply the soil surface with water during evaporation. Ritchie et al. ( 1989 ) suggested the following equations to estimate potential values of REW ͑ REW max ͒ according to soil ...
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It has long been recognized that reliable, robust, and automated instrumentation for the measurement of soil moisture content can be extremely useful, if not essential, in hydrological, environmental, and agricultural applications. A number of automated techniques for point measurement of soil water content have been developed to operational level...
The moisture status of the surface cover in Sicily is monitored by the evaporative fraction, EF. An energy balance modelling is performed in order to describe the energy partitioning at the land surface. Estimates of actual evapotranspiration derived from EF agree well with standard methods and highlight the advantage of using remote sensing data t...
Reference crop evapotranspiration (ET
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o and EP often result in unreliable estimate of crop evapotranspiration. This study investigated the relationship between measured and estimated crop eva...
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... Consequently, the calibration of the model has been performed on the sub-basins of available data on water volumes recorded in daily discharges from gauging stations in 28 sub-basins, which were transformed to volume per unit area and year (Table 4). We have calibrated the watersheds grouping basins according to the similarity of characteristics, resulting in three main zones: Tangier, Loukkous, Mediterranean and Sebou catchments were categorised as 'North' basins; Bouregreg, Oum Er Rabie, Tensift and Souss-Massa as 'Atlantic' basins; and Moulouya, Draa, Guelmim-Tiznit, and Ziz-Rheris as 'Southeast' basins The values of Kc and the Z parameter as well as the areas of the land cover classes were fitted from the SA results to calibrate the "Water Yield" model within the ranges encountered in the review literature (Allen et al., 1998(Allen et al., , 2005. In addition, a comparison of simulation results with observed data was carried out using the mean absolute percentage error (MAPE) (eq. ...
Morocco urgently needs an updated understanding of its water resources, considering the current knowledge's insufficient and uncertain state. Incorporating the latest Shared Socioeconomic Pathways (SSPs) is crucial for a more accurate and informed assessment. This study aims to bridge this gap by examining the hydrological dynamics of major basins, offering insights vital for strategic water resource management. To unravel Morocco's hydrological future, we employed an integrative methodology encompassing advanced spatial analyses, watershed hydrological modeling through the 'Water Yield' module of InVEST, and climate change scenario projections from CMIP6. Leveraging reputable databases for land cover, soil, and climate data, we ensured a robust foundation for the projections applied. This comprehensive approach facilitated a nuanced examination of water availability, considering the intricate interplay of various factors. The findings unveil a concerning projection, anticipating water yield declines between 23% and 51% by 2080 and 43%-61% by 2100 across the 12 basins. The northwest and north areas, currently endowed with better water availability, face the most substantial reductions. Economic repercussions loom, with potential losses ranging from − 0.8 to − 8.5 billion USD by 2100, urging strategic interventions to avert potential GDP declines of 2.8%-17.1%. The study highlights the scenario-dependent sensitivity of water supply to varying levels of climate change. In the context of the North African region, Morocco's hydroclimatic challenges assume heightened significance. As a pivotal player in the region, Morocco's water resource management impacts its socioeconomic landscape as well as resonates regionally. The outcome of proactive measures and strategic planning can potentially set a precedent for neighboring countries grappling with similar hydrological uncertainties, fostering regional resilience in the face of escalating water stress. The study's insights, therefore, carry broader implications, positioning Morocco as a key influencer in shaping sustainable water management practices across North Africa.
... The Ke was estimated using Eq. (5) and it is minimum (dry soil) and maximum (wet soil) (Allen et al. 2005) ...
... where Kcb, Kcmax, Kr, and few = basal crop coefficient, maximum value of Kc, evaporation reduction coefficient, and fraction of the soil that is both exposed and wetted, respectively. The depth of evaporation water (De) is the actual soil water evaporated from soil and the readily evaporable water (REW) is the maximum soil water available for evaporation (Allen et al. 2005). Following rain or irrigation, the Kr value is set to be 1 when the soil is starting to dry and as the soil moisture decreases, Kr drops below 1, eventually reaching zero when there is no water left for evaporation from the upper soil layer and this was determined through Eqs. ...
Single crop coefficient-based crop water estimation challenges watermelon irrigation agriculture in Arba Minch, Ethiopia. This study aimed to estimate the adjusted dual crop coefficient of watermelon under deficit irrigation with straw mulching, alongside validating the AquaCrop model for watermelon cultivation improvement. This experimental research followed a randomized complete block design with four treatments: full irrigation (T1), full irrigation with straw mulching (T2), 50% deficit irrigation (T3), and 50% deficit irrigation with straw mulching (T4). Average actual total water consumption of watermelon was 419.2 mm (T1), 338.4 mm (T2), 227.8 mm (T3), and 187.8 mm (T4), respectively. The straw mulching with full irrigation level (T2) of the present study reduced water consumption of watermelon by 20.1% compared with control treatment. Additionally, mulching decreased total water use by 17% under a 50% deficit compared with nonmulched treatment (T3). The average adjusted dual crop coefficient of watermelon varied from 0.17 (T4) to 0.42 (T1), 0.31 (T4) to 0.75 (T1), 0.41 (T4) to 1.04 (T1), and 0.34 (T4) to 0.84 (T1) in initial, development, mid, and late stages of watermelon growth, respectively. The average coefficient of variation for the dual crop coefficient was 9.45% (initial stage), 3.90% (development stage), 3.66% (mid-stage), and 4.72% (late stage), highlighting the variability within each growth stage. The AquaCrop model was evaluated for simulating evaporation, transpiration, and evapotranspiration, yielding a mean root mean square error (RMSE) of 1.6 mm. Similarly, evaporation, basal crop coefficient, and dual crop coefficient simulations also exhibited a mean RMSE of 1.6. The model demonstrated favorable performance with average R2 and Nash–Sutcliffe coefficient of efficiency (NSE) values of 0.84 and 0.74, respectively. This study demonstrates that combining modified dual crop coefficients with deficit irrigation and straw mulching can reduce watermelon water consumption in Arba Minch. The AquaCrop model, validated with high accuracy, offers a reliable tool to predict the dual crop coefficient of watermelon-irrigated agriculture with or without mulching field management practices.
... The water yield module of the InVEST model is based on the Budyko theory and water balance principle, utilizing geographic information systems and remote sensing data, combined with multiple factors such as land cover, precipitation, vegetation cover, and terrain, to simulate the hydrological cycle within the watershed. Through the model operation, a pixel-based flow rate can be obtained (Yang et al., 2008;Allen et al., 2005;Donohue et al., 2012;Xu et al., 2013). InVEST has a wider application in water conservation. ...
Urban progression influences water conservation by altering surface characteristics and local climate regimes, potentially posing significant risks to water sustainability and ecological integrity. Since 2015, the Chinese government has championed a new development philosophy aimed at promoting harmonious coexistence between human and nature. Based on the green connotation of the new development philosophy, this study simulated the spatial and temporal distribution of water conservation in five plateau lakeside cities (Plateau Lakeside City-PLC: Dianchi Lake Basin-DCB, Fuxian Lake Basin-FXB, Erhai Lake Basin-EHB, Qilu Lake Basin-QLB and Xingyun Lake Basin-XYB), established a comprehensive framework of indicators affecting water conservation , and quantified the changes in the drivers of water conservation. The results indicated that, except for DCB, the spatial distribution of water conservation in PLC exhibits similarity, but overall demonstrates a declining trend over time. The average importance of the factors in the PLC was weighed using Geodetector's q value. The most critical factors affecting water conservation in PLC included climate change (precipitation: q_ PRE =0.66; evaporation: q_ ET =0.57) and land cover (q_ LC =0.45). In addition, the topography (slope: q_ SLOPE =0.39; elevation: q_ DEM =0.43), vegetation coverage (q_ NDVI =0.30), and soil (plant available water content: q_ PAWC =0.38; root restricting layer depth: q_ ROOT =0.18) were influential factors followed climate change and land cover. Among the social factors, population density (q_ POP =0.37) has a small impact on water conservation, while economic activities and human-related land activities (q_ CROP ,q_ NTL, and q_ CITY are all less than 0.1) do not show a significant impact, due to the government's implementation of the new development philosophy, which balances development and conservation.
... The second consequence of "saving" water in the soil for up to several months is that it cannot all be saved for late-season transpiration, and thus, some fraction of this "banked" soil water will be lost to competing sinks (e.g., evaporation, saturated and unsaturated flow out of the rhizosphere, uptake by weeds), rather than passing through crop stomata. Importantly, the magnitude of these soil water losses are strongly climate-and soil-dependent (Monteith and Unsworth 1990;Allen et al. 2005;Passioura 2006), e.g., evaporative losses are expected to range between 20 and 87% of total crop evapotranspiration, depending on soil and atmospheric conditions (Fulton, J.M. 1966;Allen et al. 2005;Logsdon et al. 2014;Unkovich et al. 2018). Taken together, the monotonic increasing relationship between net CO 2 assimilation and stomatal conductance, the potential (which was not certified by peer review) is the author/funder. ...
... The second consequence of "saving" water in the soil for up to several months is that it cannot all be saved for late-season transpiration, and thus, some fraction of this "banked" soil water will be lost to competing sinks (e.g., evaporation, saturated and unsaturated flow out of the rhizosphere, uptake by weeds), rather than passing through crop stomata. Importantly, the magnitude of these soil water losses are strongly climate-and soil-dependent (Monteith and Unsworth 1990;Allen et al. 2005;Passioura 2006), e.g., evaporative losses are expected to range between 20 and 87% of total crop evapotranspiration, depending on soil and atmospheric conditions (Fulton, J.M. 1966;Allen et al. 2005;Logsdon et al. 2014;Unkovich et al. 2018). Taken together, the monotonic increasing relationship between net CO 2 assimilation and stomatal conductance, the potential (which was not certified by peer review) is the author/funder. ...
Limited transpiration (LT) traits aim to conserve early-season water to benefit late-season grain development. While theoretical and modeling efforts support LT efficacy, empirical tests directly measuring water loss from leaves and canopies are scarce. This study evaluates the performance of LT genotypes in achieving reduced early-season water use and improved late-season growth and yield in semi-arid Colorado. The research involved near-isogenic lines (NILs) derived from sorghum inbred lines, subjected to different irrigation treatments. Measurements included stomatal conductance, net CO2 assimilation, and photosystem II (PSII) efficiency. Results indicate that LT genotypes did not consistently exhibit lower early-season water use or higher late-season growth compared to non-LT genotypes. Early-season water use was positively correlated with above-ground biomass, challenging the assumption that early-season water conservation can be leveraged for late-season benefits. We question the efficacy of LT traits, highlighting the physiological link between water use and carbon gain, and the potential opportunity costs of reduced early-season growth. We suggests that breeding strategies should focus on enhancing deep soil water access and maximizing carbon gain rather than merely reducing transpiration or shifting water use in arid and semi-arid environments.
... where Kr is the soil evaporation reduction coefficient, Kc max is the maximum value of the crop coefficient, and few is the fraction of the soil that is wetted and exposed. The evaporable soil layer, which is subject to soil evaporation, was defined to have a thickness of 0.15 m, according to the soil characteristics, as proposed by [82]. The SIMDualKc SWB model was employed to compute Ks and Ke separately for each treatment (F, D, and R) and year of the experiment (2021 and 2022). ...
A two-year experiment was conducted with a local maize hybrid under full (F) and deficit (D) drip irrigation and rainfed conditions (R) to estimate maize evapotranspiration in Bosnia and Herzegovina (BiH). Three approaches, namely, A&P, SIMDualKc (SD), and vegetation index (VI), to estimate the actual crop coefficient (Kc act), the actual basal crop coefficient (Kcb act), and the actual crop evapotranspiration (ETc act), were applied with the dual crop coefficient method and remote sensing (RS) data for the first time. While Kcb act from all approaches matched FAO56 tabulated values, SD showed differences in comparison to A&P of up to 0.24 in D and R conditions, especially in the initial and mid-season stages. VI demonstrated very good performance in all treatments. In F, the obtained Kc act for all approaches during the initial and end stages were higher than the tabulated values, ranging from 0.71 to 0.87 for the Kc ini act and from 0.80 to 1.06 for the Kc end act, while the mid-season period showed very good agreement with the literature. The maize crop evapotranspiration range is 769–813 mm, 480–752 mm, and 332–618 mm for F, D, and R, respectively. The results confirmed the suitability of both approaches (SD and VI) to estimate maize crop evapotranspiration under F, with the VI approach demonstrating an advantage in calculating Kcb act, Kc act, and ETc act values under water stress conditions. The higher observed yields (67.6%) under irrigation conditions emphasize the need to transition from rainfed to irrigation-dependent agriculture in BiH, even for drought-resistant crops like maize.
... Second, the InVEST model has a small number of parameters, and the selection of these parameters can greatly affect the accuracy of the results. The biophysical table used in this study was mainly obtained from a literature review (Allen et al. 2005;Hu et al. 2014;Li et al. 2014;Sharp et al. 2018;Wu et al. 2013), and there was a lack of local data from NYC. Further research can improve the model by obtaining more refined parameters specifically for the study area. ...
Flood risk has become a serious challenge for many cities, including New York City (NYC). Evaluating urban flood adaptability evaluation is crucial for regulating storm and rain risks. In this study, we proposed an integrated framework based on the Integrated Valuation of Ecosystem Services (InVEST) model and Geographic Information System (GIS). First, the InVEST model was used to assess the water yield, soil conservation, and water quality purification in NYC. Second, the entropy weighting method was employed to determine the weights of indicators for computing the flood adaptability evaluation (FAE). Third, a spatial correlation of FAE was conducted and finally delineated the flood adaptability zones in GIS. The results show that: (1) The spatial distribution of FAE was uneven, high in the surrounding area and low in the center. (2) The Moran's I for FAE was 0.644, showing an overall positive spatial relationship of FAE. High-scoring clusters were located in the southeastern area while low-scoring clusters were in the northern, central, and southwestern areas. (3) The FAE in NYC can be divided into five categories: the lower-adapted zone (0.22–0.27), low-adapted zone (0.28–0.31), medium-adapted zone (0.32–0.36), high-adapted zone (0.37–0.43) and higher-adapted zone (0.44–0.50). These results of the study can provide evidence and recommendations for flood risk management in NYC and other cities worldwide.
... Daily reference evapotranspiration (ET 0 ) was calculated according to the FAO-56 Penman-Monteith equation (Allen et al., 1998). The ET 0 was multiplied by a crop coefficient (K c ) to estimate the crop evapotranspiration (ET c ) of FR and BS (0.90 and 1.15, respectively) (Allen et al., 2005). Root water uptake was calculated by applying the plant water stress response function proposed by Feddes et al. (1976), with 80% of the root density in the top 40 cm of soil (Parvin et al., 2023). ...
The benefits of using cover crops for improving soil and water quality are well known. Less clear is whether cover crops, especially those forming a taproot system, can favor solute transport down to the groundwater by modifying soil hydraulic properties and solute dynamics. In this study, we employed 12 lysimeters to conduct a comparative analysis between a taproot cover crop, specifically forage radish (FR), and bare soil (BS), under three water table management conditions. Our objective was to evaluate whether the enhancement of root‐derived macroporosity could have modified water and solute dynamics, and offset the benefits provided by FR that is commonly used to mitigate solute leaching. A tracer solution of bromide (Br⁻) was added to lysimeters, and solute flux concentrations were determined at different depths during a 25‐day test. Soil moisture and pressure heads were monitored. Water and solute transport parameters were estimated by inverse modeling using HYDRUS‐1D. A complementary laboratory experiment was performed to quantify the effect of FR root apparatus on the macropore structure by using noninvasive X‐ray microtomography (µCT). Results showed that the growth of FR within the lysimeters induced alterations in water and solute dynamics compared with BS. This is primarily attributed to its proficiency as solute scavenger, with an uptake capacity of up to 47% of the total injected tracer. Our comparative analysis instead revealed subtle differences in soil structure and hydraulic properties brought about by the presence of FR. Major changes were observed for the saturated hydraulic conductivity (Ks), which increased from an average of 8.4–49.8 cm day⁻¹ within the 20–45 cm layer in BS and FR, respectively. Additionally, there was a difference in immobile water content (θim), with the values in FR averaging 21% lower than those in BS. These modifications can be attributed to the formation of fissures and channels, primarily concentrated in the proximity of taproot development, without extending into deep preferential flow pathways. These structural changes were supported by the nondestructive µCT analyses. Upon aggregating the effects observed, solute movement to groundwater was not affected by FR compared to BS conditions.
... Firstly, WC is obtained by adding correction factors such as RO to the water yield calculated by InVEST, and its applicability has not been verified [13,57]. Second, the variable water yield is derived from some immutable reference data [58][59][60]. After that, the empirical coefficient Z factor, which cannot be precisely determined, introduces a large bias in the WC evaluation [17]. ...
The Yellow River Basin in China has the world's most serious soil erosion problem. The Yellow River Basin in Sichuan Province (YRS), as the upper reaches of the Yellow River, and its water conservation (WC) capacity greatly affects the ecological environment of the downstream basin. In recent years, YRS has received more and more attention, and numerous policies have been developed to improve local WC. However, there is a vacancy in the long-term research of WC in the YRS due to the lack of in-situ data. This study quantitatively evaluated the WC of YRS from 2001 to 2020 through Google Earth Engine (GEE) and analyzed the spatio-temporal variations of WC and land cover (LC). CA-Markov predicted the LC and WC in 2025 under three scenarios to assess the contribution of different scenarios to WC. The WC in YRS fluctuated from 1.93 to 6.77 billion m 3. The climate is the dominant factor of WC change, but the effect of LC on WC is also evident. The WC capacity increases with vegetation coverage and height. The WC capacity of forests per km 2 exceeds 600 mm, while that of grasslands is about 250 mm, and barren can cause around 300 mm of WC loss. In 2025, the WC in YRS may exceed 7.5 billion m 3 , but the past ecological management mode should be transformed. Improving the quality of land use and converting grasslands to forests is better than reducing cropland to improve WC.
... Another explanation for the lack of significant difference in the panel temperature between the two treatments may be a comparison of ET rates between the two PV treatments. Crop evapotranspiration ET c can be estimated as per the following equation: ET c = ET ref × K c , where ET ref is reference ET, and K c is crop coefficient (Allen, Pruitt, et al., 2005). This model of ET divides the ET process into energy-limited (or atmosphere controlled) Stage 1 and water-limited (soil controlled) Stage 2. For the study sites where the average rainfall interval during the growing season is between 1 and 2 days and soil surface is consistently wet, K c for the bare PV treatment can be higher than or comparable to that of a vegetated surface (Figure 6a), and the resulting evaporation may exceed or equal the ET rate in the vegetated PV treatment. ...
... Evapotranspiration (ET)-driven panel cooling effects are site specific: (a) Crop coefficient (K c ) of bare soil as a function of reference ET depth and rainfall intervals. The shaded area represents the typical range of K c for grazing pastures, and the vertical dotted line represents an example daily value of growing season reference ET in the study region (modified from Allen, Pruitt, et al. (2005) and Allen, Walter, et al. (2005)); (b) Evapotranspiration as a function of air temperature at high soil moisture (field capacity) and water stress conditions (Penman-Monteith equation combined with Stewart (1988) model of leaf conductance to include environmental controls on canopy resistance). The vertical dotted line represents the optimal air temperature for ET. ...
Co‐locating solar photovoltaics with vegetation could provide a sustainable solution to meeting growing food and energy demands. However, studies quantifying multiple co‐benefits resulting from maintaining vegetation at utility‐scale solar power plants are limited. We monitored the microclimate, soil moisture, panel temperature, electricity generation and soil properties at a utility‐scale solar facility in a continental climate with different site management practices. The compounding effect of photovoltaic arrays and vegetation may homogenize soil moisture distribution and provide greater soil temperature buffer against extreme temperatures. The vegetated solar areas had significantly higher soil moisture, carbon, and other nutrients compared to bare solar areas. Agrivoltaics in agricultural areas with carbon debt can be an effective climate mitigation strategy along with revitalizing agricultural soils, generating income streams from fallow land, and providing pollinator habitats. However, the benefits of vegetation cooling effects on electricity generation are rather site‐specific and depend on the background climate and soil properties. Overall, our findings provide foundational data for site preservation along with targeting site‐specific co‐benefits, and for developing climate resilient and resource conserving agrivoltaic systems.
... This model took into account the dynamic change of crop coefficient in the studied area. In the case of K c , the values vary based on the crop development stages and climate conditions [68]. So, this study confirms the capability of the hybrid MLP-RSO model for improved prediction of K c . ...
The crop coefficient (Kc) is a scaling factor to calculate crop evapotranspiration (ETc). Accurate prediction of Kc affects planning to allocate water resources, especially in arid and semi-arid areas with limited water sources availability. The conventional FAO approach has some limited applications due to using plant characteristics. However, existing artificial intelligence approaches have high performances, but encounter some instability in prediction. In the present study, the generalized likelihood uncertainty estimation (GLUE) approach was applied to assess uncertainties arising from both model structure and input parameters. In addition, this study aims to derive the explicit predictive and usable equation for calculating the monthly Kc of maize. The equations were developed from the best hybrid MLP model using minimal meteorological data in four regions of Egypt. For this, the predictive utility of MLP-based models that hybridized with meta-heuristic optimization algorithms was examined. The rat swarm optimization (RSO), firefly algorithm (FFA), bat algorithm (BA), and genetic algorithm (GA) hybridized with MLP (MLP-RSO, MLP-FFA, MLP-BA, and MLP-GA) are used as equation derivation tools. The results showed that a unique hybrid Gamma Test-RSO is a powerful approach for determining the optimal combination (Tmax, Tmin, Rs) as the best input vector. The results showed that the hybrid MLP-RSO model decreased the average RMSE by 13.87, 39.95, 45.68, and 53.09% than MLP-BA, MLP-FFA, MLP-GA, and MLP models, respectively. In addition, the uncertainty results showed that the Kc predictions were more stable and confident in MLP-RSO, while the average of 95PPU covered 94.5 and 91.5% of actual Kc for input parameters and model structure uncertainties, respectively. In conclusion, the developed hybrid model and the techniques illustrated in the current study suggest substantial benefits for other researchers to derive mathematical equations from easily available meteorological variables in different regions and climates. Also, the findings provide a fundamental guideline for the local water users and agricultural development planners to achieve accurate and fast irrigation scheduling.
