Crop Evapotranspiration Research Articles

Maize response to different subsurface drip irrigation management strategies: Yield, production functions, basal and crop evapotranspiration

Grain yield, irrigation-yield production functions (IYPFs), evapotranspiration-yield production functions (ETYPFs), total soil water-yield production function (TSWYPF), crop evapotranspiration (ETc), and basal ET (ETb) response of subsurface drip-irrigated (SDI) maize were investigated under full irrigation treatment (FIT), 75 % FIT, 50 % FIT, and rainfed (RF). Yield response to irrigation differed significantly (P<0.05) between the treatments with FIT having the highest grain yield, followed by 75 % FIT, 50 % FIT, and RF in all growing seasons. There was a 14, 6, and 12 % yield reduction in 75 % FIT, 50 % FIT, and RF with respect to FIT, respectively. FIT had the highest ETc, followed by 75 % FIT, 50 % FIT, and RF. ETc reduction with 75 % FIT, 50 % FIT and RF with respect to FIT had similar reductions between the years. Under these experimental conditions, ETc of SDI-irrigated maize can be expected to be reduced by 5.2 % (25 mm), 13 % (65 mm), and 26 % (130 mm) with the limited irrigation (75 % FIT and 50 % FIT) and RF, respectively. The amount of irrigation water required for maximum grain yield varied between the growing seasons as a function of climatic conditions (262, 225, and 173 mm in 2004, 2005, and 2006, respectively). Based on the IYPFs, a 25.4 mm of irrigation application resulted in 0.061, 0.063, and 0.066 t/ha yield increase (beyond the intercept) in 2004, 2005, and 2006, respectively, with a 3-yr average of 0.063 t/ha. A 25.4 mm of irrigation application resulted in 15.6, 16.0, and 13.7 mm of increase in ETc (beyond the intercept) in 2004, 2005, and 2006 seasons, respectively, with a 3-yr average of 15.1 mm. On a three-year average basis, 10.7, 29.1, and 67 % yield reduction in 75 % FIT, 50 % FIT, and RF treatments with respect to FIT can be expected under these climate, soil-water, and crop management conditions with SDI-irrigated maize. A strong dependence of the ETYPF slopes on RF treatment’s yield was observed. ETb had substantial inter-annual variation as 356, 230, and 315 mm in 2004, 2005, and 2006, respectively. ETb was strongly and positively correlated (R2=0.99) with the seasonal precipitation and strongly, but negatively correlated (R2=0.89) with seasonal cumulative thermal unit (Growing Degree Days). Based on the pooled ETYPFs, a 25.4 mm of ETc resulted in 1.86, 1.72, and 2.61 t/ha grain yield (beyond the intercept) in 2004, 2005, and 2006, respectively, with a seasonal average of 2.1 t/ha. Data and information of this research can provide guidance for irrigation professionals, managers, advisors, engineers, agronomists, economists, and other professionals and can be incorporated into the planning, forecasting, allocating and managing of water resources availability-demand-actual use analyses and decisions to enhance crop production efficiency.

Use of Biofertilizers as an Effective Management Strategy to Improve the Photosynthetic Apparatus, Yield, and Tolerance to Drought Stress of Drip-Irrigated Wheat in Semi-Arid Environments

Irrigation scheduling, coupled with the use of biofertilizers, constitutes an effective management strategy to overcome soil drought. This study aimed to assess the individual and combined effects of three selected biofertilizers—(R) Bacillus sp. and Bacillus subtilis, (M) native arbuscular mycorrhizal fungi, and (C) compost—on Triticum durum L. The agro-physiological and biochemical traits, along with the soil properties, were evaluated under two different water regimes, 100% crop evapotranspiration (ETc) for the well-watered regime and 30% ETc for the drought-stressed regime under field conditions, using a drip irrigation system. Drought stress (DS) led to significant reductions in the biomass, physiological parameters, and biochemical markers. Furthermore, the application of CM and MR significantly boosted the shoot and root dry weight by 137% and 72%, respectively, under DS compared to the control. Moreover, CM and R resulted in a notable increase of 167% and 130% in the grain and straw yield, respectively, under the same conditions. The normalized difference vegetation index showed improved values in the plants inoculated with MR and CMR, respectively, under DS conditions. Additionally, the soil quality was positively influenced by the application of M and/or R and/or C biofertilizers. These findings provide valuable insights into the intricate soil–plant interactions and the beneficial effects of combined biofertilizers in enhancing wheat’s resilience to drought stress.

Silicon drip fertigation improved sugar beet root and canopy growth and alleviated water deficit stress in arid areas

Crop growth is highly susceptible to drought stress due to water scarcity in arid areas. Silicon (Si) fertilizer could improve the tolerance of crops to drought stress, but the effect of drip fertigation of Si fertilizer on the growth and yield of sugar beets under drought stress is still unclear. In this field experiment conducted in 2022 and 2023 in the arid northwest China, the effects of different Si fertilizer application rates (0 kg ha−1 (Si0), 15 kg ha−1 (Si1), 38 kg ha−1 (Si2), 75 kg ha−1 (Si3)) on the growth, yield, and resource use efficiency of sugar beets (cultivars Beta356 (BT) and Strube13092 (ST)) under deficit irrigation (60 % of crop evapotranspiration (ETc), W2) were explored. The results showed that deficit irrigation (W2Si0) reduced the taproot and fibrous root growth, leaf net photosynthetic rate (Pn), leaf relative water content (LRWC), and leaf area index (LAI) of cultivar BT compared with full irrigation (100 % of ETc, W1). Under deficit irrigation, Si application (W2Si1, W2Si2, and W2Si3) alleviated the drought stress by increasing the number of fibrous roots in 17.5–70.0 cm soil layer and promoted the growth of taproots. Besides, it also increased the leaf moisture and photoassimilate production by increasing plant Si uptake, LRWC, LAI, and Pn. This finally increased the taproot yield (TY), irrigation water use efficiency (IWUE), and partial factor productivity of nitrogen (PFPN) by 11.2 % - 22.9 %, 6.5 % - 19.3 %, and 6.3 % - 19.3 %, respectively in cultivar BT and by 8.8 % - 27.1 %, 13.4 % - 30.8 %, and 13.4 % - 30.8 %, respectively in cultivar ST, compared with W2Si0. Regression analysis showed that the Si fertilizer application rate 64 kg ha−1 could maximize the TY of cultivar BT, but the net revenue (NR) was significantly lower than that of the W1 treatment. The Si fertilizer application rate 71 kg ha−1 could increase the TY of cultivar ST and achieve a NR similar to that of the W1 treatment. Therefore, in arid regions, Si application could alleviate the adverse effects of drought stress on drip-irrigated sugar beet root and shoot growth and improve yield, but the Si application rate varied with sugar beet cultivars.

Effects of Deep Vertical Rotary Tillage on Soil Water Use and Yield Formation of Forage Maize on Semiarid Land

Forage maize is one of the most important feed crops for livestock production, and is mainly grown in northwest China. However, their growth is often stressed by limited soil water availability due to the arid climate. To provide more soil moisture, a high-efficiency tillage technique was required to make crops effectively use soil moisture in deep soil layers. Deep vertical rotary tillage is a promising choice for this purpose. In this study, a long-term (2020–2022) field experiment consisting of three treatments, i.e., traditional tillage (TT), deep rotary tillage (DT), and deep vertical rotary tillage (VRT), was carried out in semiarid areas of Loess Plateau, northwest China, to investigate the effects of VRT on soil water storage (SWS), phase crop evapotranspiration (ETc) during the pre- and post-flowering periods, dry matter accumulation, grain yields and the water use efficiency (WUE) of forage maize. The results showed that VRT significantly improved the absorption of soil moisture from deep layers, especially in dry years. During the pre-flowering period of a dry year (2020), VRT decreased SWS by 7.6%–10.0% in the 60–180 cm layer, and by 17.6%–18.5% in the 180–300 cm layer, respectively, compared to DT and TT. As a result, VRT increased ETc during the pre-flowering period by 6.1% and 9.2%, respectively. In wet years (2021 and 2022), VRT increased total ETc by 2.0%–7.9% in 2021, and by 10.1%–14.9% in 2022, respectively. On average, VRT increased the dry matter weight per plant by 1.0%–7.8%, grain yields by 2.4%–38.6%, biomass yields by 3.4%–16.2%, and WUE by 10.1%–30.0%, respectively. Particularly, the benefit of VRT for increasing yields and WUE was more noticeable in dry years. It can be concluded that VRT is a drought-tolerant and yield-boosting tillage technique that is suitable for rain-fed forage maize in semiarid areas of Loess Plateau, northwest China.

Climate-Informed Management of Irrigated Cotton in Western Kansas to Reduce Groundwater Withdrawals

The Ogallala aquifer, underlying eight states from South Dakota to Texas, is practically non-recharging south of Nebraska, and groundwater withdrawals for irrigation have lowered the aquifer in western Kansas. Subsequent well-yield declines encourage deficit irrigation, greater reliance on precipitation, and producing profitable drought-tolerant crops like upland cotton (Gossypium hirsutum (L.)). Our objective was to evaluate deficit irrigated cotton growth, yield, and water productivity (CWP) in northwest, west-central, and southwest Kansas in relation to El Niño southern oscillation (ENSO) phase effects on precipitation and growing season cumulative thermal energy (CGDD). Using the GOSSYM crop growth simulator with actual 1961–2000 location weather records partitioned by the ENSO phase, we modeled crop growth, yield, and evapotranspiration (ET) for irrigation capacities of 2.5, 3.75, and 5.0 mmd−1 and periods of 4, 6, and 8 weeks. Regardless of location, the ENSO phase did not influence CGDD, but precipitation and lint yield decreased significantly in southwest Kansas during La Niña compared with the Neutral and El Niño phases. Simulated lint yields, ET, CWP, and leaf area index (LAI) increased with increasing irrigation capacity despite application duration. Southwestern Kansas producers may use ENSO phase information with deficit irrigation to reduce groundwater withdrawals while preserving desirable cotton yields.

Enhancement in Tomato Yield and Quality Using Biochar Amendments in Greenhouse under Salinity and Drought Stress.

Enhancing saline water productivity in arid regions is essential for sustainable agriculture. Adding biochar can improve the quantity and quality of tomato yield under higher levels of salinity and lower levels of irrigation. The experiment aimed to evaluate the effects of biochar on enhancing tomato fruit quality and yield under salinity and drought stress. The experiment combines two treatments for irrigation water quality (0.9 and 2.3 dS m-1), four irrigation levels (40, 60, 80, and 100%) of crop evapotranspiration (ETc), and the addition of 5% of biochar to treated soil (BC5%) and untreated soil (BC0%). The results showed that the decrease in the water quality and irrigation levels negatively impacted the yield and properties of tomato fruit, while 5% of biochar application positively improved the yield. Adding biochar decreased the tomato yield by 29.33% and 42.51% under lower-saline-irrigation water than the control, negatively affecting the fruit's physical parameters and mineral content. In contrast, adding biochar and irrigating with saline water at 60% of ETc improved the firmness and quality characteristics of the fruit by 56.60%, 67.19, 99.75, and 73.57% for vitamin C (VC), total titratable acidity (TA), total soluble solids (TSS), and total sugars (TS), respectively, compared to the control, and also reduced the sodium content of the fruits under all irrigation levels compared to untreated plants by biochar. Generally, biochar with saline water under deficit irrigation with 80 and 60% of ETc could be an excellent strategy to enhance the qualitative characteristics of tomato fruits and save approximately 20-40% of the applied water.

Incorporation of compost and biochar enhances yield and medicinal compounds in seeds of water-stressed Trigonella foenum-graecum L. plants cultivated in saline calcareous soils

BackgroundThe combination of compost and biochar (CB) plays an important role in soil restoration and mitigation strategies against drought stress in plants. In the current study, the impact of CB was determined on the characteristics of saline calcareous soil and the productivity of fenugreek (Trigonella foenum-graecum L.) plants. The field trials examined CB rates (CB0, CB10 and CB20 corresponding to 0, 10, and 20 t ha‒1, respectively) under deficit irrigation [DI0%, DI20%, and DI40% receiving 100, 80, and 60% crop evapotranspiration (ETc), respectively] conditions on growth, seed yield (SY), quality, and water productivity (WP) of fenugreek grown in saline calcareous soils.ResultsIn general, DI negatively affected the morpho-physio-biochemical responses in plants cultivated in saline calcareous soils. However, amendments of CB10 or CB20 improved soil structure under DI conditions. This was evidenced by the decreased pH, electrical conductivity of soil extract (ECe), and bulk density but increased organic matter, macronutrient (N, P, and K) availability, water retention, and total porosity; thus, maintaining better water and nutritional status. These soil modifications improved chlorophyll, tissue water contents, cell membrane stability, photosystem II photochemical efficiency, photosynthetic performance, and nutritional homeostasis of drought-stressed plants. This was also supported by increased osmolytes, non-enzymatic, and enzymatic activities under DI conditions. Regardless of DI regimes, SY was significantly (P ≤ 0.05) improved by 40.0 and 102.5% when plants were treated with CB10 and CB20, respectively, as similarly observed for seed alkaloids (87.0, and 39.1%), trigonelline content (43.8, and 16.7%) and WP (40.9, and 104.5%) over unamended control plants.ConclusionsOverall, the application of organic amendments of CB can be a promising sustainable solution for improving saline calcareous soil properties, mitigating the negative effects of DI stress, and enhancing crop productivity in arid and semi-arid agro-climates.

Supplemental greenhouse lighting increased the water use efficiency, crop growth, and cutting production in Cannabis sativa.

The expanding cannabis production sector faces economic challenges, intensified by freshwater scarcity in the main US production areas. Greenhouse cultivation harnesses sunlight to reduce production costs, yet the impact of greenhouse light levels on crucial production components, such as plant growth, branching, and water use efficiency (WUE), remains poorly understood. This study aimed to assess the effects of combined sunlight and supplemental lighting on the crop's main production components and leaf gas exchange of Cannabis sativa 'Suver Haze' in the vegetative stage. Within a greenhouse, LED lighting provided at intensities of ~150, 300, 500, and 700 µmol m-2 s-1 (18-hour photoperiod), combined with solar radiation, resulted in average daily light integrals of 17.9, 29.8, 39.5, and 51.8mol m-2 d-1. Increasing light levels linearly increased biomass, leaf area, and the number of branches per plant and square meter, with respective rates of 0.26g, 32.5 cm2, and 0.41 branches per mole of additional light. As anticipated, crop evapotranspiration increased by 1.8-fold with the increase in light intensity yet crop WUE improved by 1.6-fold when comparing the lowest and highest light treatments. Moreover, water requirements per unit of plant biomass decreased from 0.37 to 0.24 liters per gram when lighting increased from ~18 to 52mol m-2 d-1, marking a 35% reduction in evapotranspiration. These results were supported by increments in leaf photosynthesis and WUE with light enhancement. Furthermore, our findings indicate that even 52mol m-2 d-1 of supplemental lighting did not saturate any of the crop responses to light and can be economically viable for cannabis nurseries. In conclusion, light supplementation strongly enhanced photosynthesis and plant growth while increasing WUE. Additionally, a comprehensive discussion highlights the shared physiological mechanisms governing WUE in diverse plant species and their potential for water conservation under enhanced lighting conditions.

Microsprinkler irrigation in combination with nutrient management influences crop and water productivity and water-nutrient dynamics in large cardamom-growing soils in the hilly sub-Himalayan region of India

ABSTRACT A field experiment designed with three tiers of irrigation viz., I0: rainfed, I1: 100% crop evapotranspiration (1.0 ETc) and I2: 0.75 ETc and four tiers of soil nutrition viz., N0: control (no farmyard manure and fertilizer), N1: 100% recommended dose of fertilizer (RDF) as FYM, N2: 50% RDF as FYM +50% RDF as chemical fertilizers and N3: 100% RDF as chemical fertilizers was conducted for four consecutive years (2015–2018) on large cardamom at the hilly terrain of Gitdubling lower beyong busty in Kalimpong Block II in Darjeeling district of WB India. The results showed that I1N3 treatment combination providing microsprinkler irrigation at 1.0 ETc and full RDF (20:40:40::N:P2O5:K2O kg ha−1) recorded highest growth, yield attributes, fresh yield (665.2 kg ha−1) and dry yield (282.0 kg ha−1) of capsules, greatest water productivity (1.8 × 100 kg m−3) and largest soil availability and leaf accumulation of N, P and K. The soil water distribution along the phenological stages was inconsistent and followed the trend according to the rainfall amounts; however, the contents increased with an increase in soil depth and irrigation regime. The predictive regressive models showed the linear relationships between the dry capsule yield and irrigation water and total water use by the plant.

Parameterization of Four Models to Estimate Crop Evapotranspiration in a Solar Greenhouse.

Working to simplify mechanistic models on the basis of reliability for estimating crop evapotranspiration (ET) in a greenhouse is still worthwhile for horticulturists. In this study, four ET models (Penman-Monteith, Priestley-Taylor, and Shuttleworth-Wallace models, and the Crop coefficient method) were parameterized after taking the restriction effect of resistance parameters in these models on ET into account, named as PA-PM, PA-PT, PA-CC, and PA-SW, respectively. The performance of these four parameterized models was compared at different growth stages, as well as the entire growing season. Tomatoes that were ET-grown in a solar greenhouse without a heating device were measured using weighting lysimeters during 2016-2017 and 2019-2021, in which data from 2016 were used to adjust the model parameters, and data from the other four study years were used to examine the model performance. The results indicated that the PA-PT and PA-CC models have a better performance in estimating tomato ET at four growth stages, while the PA-PM and PA-SW performed well only at the development and middle stages. Compared to the ET that was measured with the weighting lysimeters, the ET that was predicted using the PA-PM model was 27.0% lower at the initial stage, and 8.7% higher at the late stage; the ET that was computed using the PA-SW model was 19.5% and 13.6% higher at the initial and late stages, respectively. The PA-PT model yielded the lowest root mean square error and the highest index of agreement against the other models over the entire growing season, indicating that the PA-PT model is the best recommended model for estimating tomato ET in a solar greenhouse.

Vegetation Indices Based Spatial Water Demand of Rabi Onion Crop

There are numerous methods for estimating the water requirements of crops. However, the FAO Penman-Monteith Method has been adopted worldwide but it lacks spatial variability. The accuracy can be improved by adopting VI based method. Therefore, the present study was planned to investigate the use of vegetation indices (VIs) as a surrogate of crop coefficients in place of tabulated crop coefficients and find the best VI in the case of onion crops which require the amount of water. The study was conducted in 3 districts of Maharashtra i.e. Nashik, Dhule, and Jalgaon where onion is a major rabi crop grown on a large scale, for two consecutive rabi seasons of the year 2020-21 and 2021-22. Multitemporal vegetation indices such as NDVI, NDWI, SAVI, MSAVI2, and RVI were estimated using temporal images of Sentinel 2A satellite during the growth period of onion and week-wise values were obtained by using ERDAS Imagine. Linear regression was applied on VI values versus Kc recommended by MPKV, Rahuri which resulted in linear models. NDWI-Kc model showed the strongest relation with high R2 values. The spatial crop evapotranspiration (ETc) was then calculated by applying this model. For the 2020–21 growing season, the total crop evapotranspiration for onions in Dhule, Jalgaon and Nashik was calculated to be 486.5 mm, 482.7 mm, and 488.7 mm, respectively. Whereas during 2021–22, it was estimated to be 493.7 mm, 473.9 mm, and 477.2 mm, respectively in these districts. For getting water demand crop evapotranspiration values were multiplied by the acreage estimated by remote sensing. Total water demand for rabi onion for the districts Dhule, Jalgaon and Nashik was found to be 70.54 Mm3, 43.8 Mm3 and 693.2 Mm3, respectively and 128.1 Mm3, 33.9 Mm3, and 825.7Mm3 respectively for the years 2020-21 and 2021-22, respectively.

Water requirement and single and dual crop coefficients of sesame cultivated in the coastal tablelands of Brazil

AbstractSesame irrigation is essential in drought‐prone regions. However, information about the water needs of sesame is scarce. Therefore, the objective of this study was to determine crop evapotranspiration (ETc) and the sesame crop coefficient (Kc) during the rainy (S1) and dry (S2) seasons in the coastal tablelands of Alagoas, Brazil. The BRS Seda cultivar was grown in Rio Largo, Alagoas, Brazil, between 2021 and 2022. A system with 25 drainage lysimeters was installed to estimate the daily and cumulative ETc and the Kc for the entire crop cycle. The ETc was partitioned into transpiration (T) and evaporation (E), and the basal crop coefficients (Kcb) and soil evaporation coefficients (Ke) were subsequently estimated. The daily and cumulative ETc were 3.04 mm day−1 and 450.4 mm cycle−1, respectively, in S1 and 3.52 mm day−1 and 440.1 mm cycle−1, respectively, in S2. Regardless of the season, T was the main water flux (74%–80% of the ETc). The mean values of Kc were similar for S1 (0.79) and S2 (0.75), and Kcb and Ke followed the same trend as T and E, respectively. The accumulated ETc and Kc of sesame cultivated in the coastal tablelands of Alagoas, Northeast Brazil, are similar for the rainy and dry seasons.

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

AbstractThe use of high-resolution aerial imagery for assessing actual crop evapotranspiration $$ \left({ET}_{a}\right)$$ holds the potential to optimize the use of limited water resources in agriculture. Despite this potential, there is a shortage of information regarding the effectiveness of energy balance algorithms, initially designed for satellite remote sensing in estimating $$ {ET}_{a}$$ using aerial imagery. This study addresses this gap by employing the remote sensing model pySEBAL (Surface Energy Balance Algorithm for Land) in conjunction with high-resolution aerial imagery to estimate $$ {ET}_{a}$$ for processing tomatoes. Throughout the 2021 growing season, an aircraft captured multispectral and thermal imagery over a processing tomato field near Esparto, California, USA. Simultaneously, an eddy covariance flux tower within the field measured high-frequency turbulent fluxes and low-frequency biometeorology variables essential for evaluating the energy balance. The comprehensive assessment of energy balance components, including $$ {ET}_{a}$$, yielded compelling evidence that pySEBAL accurately estimated $$ {ET}_{a}$$ at high spatial resolution. The root mean square error (RMSE) and normalized RMSE for various energy balance components were as follows: 33 W m− 2 (12%) for latent heat flux, 29 W m− 2 (35%) for sensible heat flux, 24 W m− 2 (4%) for net radiation, and 10 W m− 2 (15%) for soil heat flux. Additionally, $$ {ET}_{a}$$ exhibited an RMSE and NRMSE of 0.26 mm d− 1 (6%). Moreover, the spatial mapping of $$ {ET}_{a}$$ across the processing tomato field visually depicted the spatial variability associated with irrigation scheduling, crop development, areas affected by disease, and soil heterogeneity. This research underscores the value of high resolution spatial aerial imagery and pySEBAL algorithm for estimating $$ {ET}_{a}$$ variability in the field, a crucial aspect for guiding precision irrigation management and ensuring the optimal use of limited water resources in agriculture.

Production and economic viability of ‘Kent’ mango subjected to regulated deficit irrigation in the semi-arid

Mango (Mangifera indica L.) production has great importance for Brazilian agriculture, being concentrated in the states of Bahia and Pernambuco. Although mango is a drought-tolerant crop, inadequate irrigation management reduces its yield. Thus, the objective was to evaluate production parameters and economic viability of ‘Kent’ mango subjected to controlled water deficit in the phenological stages of flowering, fruit growth and maturation. The experiment was conducted in the municipality of Petrolina/PE, semi-arid region of the São Francisco Valley, in a ultisol. The experimental design was randomized blocks, in a triple factorial scheme, with application of four irrigation depths (40, 60, 80 and 100% of crop evapotranspiration - ETc), three phenological stages (F1 - flowering, F2 - fruit growth, F3 - fruit maturation) and two production cycles (2018 and 2019 seasons), with four replicates, each of which consisting of four plants. The irrigation with 40% ETc in the flowering stage and 80% of the ETc in the growing and ripening of fruits phases promoted higher yield, water use efficiency and benefit/cost ratio in the cultivation of ‘Kent’ mango in the Brazilian semi-arid region.

Hybrid machine learning system based on multivariate data decomposition and feature selection for improved multitemporal evapotranspiration forecasting

Evapotranspiration is an essential component of the hydrological cycle. Forecasting the reference crop evapotranspiration (ETo) using a reliable and generalized framework is crucial for agricultural operations, especially irrigation. This study was aimed at evaluating the performance of a hybrid system including the K-Best selection (KBest), multivariate variational mode decomposition (MVMD), and Machine learning (ML) models for 1-, 3-, 7-, and 10-day-ahead forecasting of the daily ETo in twelve stations of California. The analysis covered a span of 20 years, from 2003 to 2022. Three stand-alone ML models, namely Cascade Forward Neural Network (CFNN), Extreme Learning Machine (ELM), and Bagging Regression Tree (BRT) are used and were integrated with various preprocessing techniques to construct three hybrid models, i.e., MVMD-KBest-CFNN, MVMD-KBest-ELM, and MVMD-KBest-BRT. According to the results obtained in the testing phase, averaged across all stations, all three stand-alone models (CFNN, ELM, and BRT) yielded similar outcomes. In contrast, the hybrid models exhibited significantly enhanced performances compared with the standalone models, and MVMD-KBest-CFNN and MVMD-KBest-ELM models outperformed MVMD-KBest-BRT model. The BRT-based models were vulnerable to overfitting. The performance of the best models is superior compared to similar existing studies. Examining the variations across stations, it was found that the stations located further from the coast and in arid regions could be susceptible to prediction errors and necessitate more attention.

Climatic trends and its impact on reference evapotranspiration and crop water requirement of rice crop in Arunachal Pradesh, India

Climatic trends and its impact on reference evapotranspiration and crop water requirement of rice crop in Arunachal Pradesh, India

Implementation of the AquaCrop Model for Forecasting the Effects of Climate Change on Water Consumption and Potato Yield Under Various Irrigation Techniques

In this study, the AquaCrop model was employed to analyze the impact of projected future climate changes on the water usage and biomass production of potato crops in Babylon, Iraq, under varying irrigation methods. The irrigation techniques evaluated included sprinkler irrigation, surface drip irrigation, and subsurface drip irrigation at depths of 10 cm and 20 cm. The study involved simulating and forecasting conditions for the year 2050, comparing them to current conditions. The model measured and predicted the evapotranspiration (ETa) and actual biomass of potato crops for 2050 using the RCP 8.5 scenarios, which outline different trajectories for greenhouse gas emissions. The AquaCrop model was calibrated and validated using statistical measures such as the R2, RMSE, CV, EF, and D, achieving a 99% accuracy level in its performance. The findings suggest that using drip irrigation systems and applying the AquaCrop model significantly mitigates the adverse effects of environmental stress on desert soils and enhances sustainable agricultural practices in arid regions.

The Relationship between Reference Crop Evapotranspiration Change Characteristics and Meteorological Factors in Typical Areas of the Middle of the Dry-Hot Valley of Jinsha River

The Relationship between Reference Crop Evapotranspiration Change Characteristics and Meteorological Factors in Typical Areas of the Middle of the Dry-Hot Valley of Jinsha River

Optimizing Irrigation and Fertilization to Simultaneously Improve Potato Tuber Yield, Water and Fertilizer Use Efficiency and Net Income in Northwest China

Irrigation, fertilization, and variety are important factors affecting potato production in northwest China. Field experiments (2021 and 2022) were performed to investigate the effects of irrigation and fertilization on the plant growth and soil microbial population of different potato varieties. Three irrigation levels were used, i.e., 100% ETc (W1), 80% ETc (W2), and 60% ETc (W3), with ETc standing for crop evapotranspiration. Three fertilization levels were used (N-P-K), i.e., 240-120-300 kg ha−1 (F1), 180-90-225 kg ha−1 (F2), and 120-60-150 kg ha−1 (F3). Three variety types were used, i.e., Feiurita (V1), Longshu 7 (V2), and Qingshu 9 (V3). These factors significantly influenced tuber yield (TY), net income (NI), and water productivity (WP). TY, NI, WP, total nitrogen accumulation (TNA), and nitrogen use efficiency (NUE) peaked at F2. Fertilization significantly impacted soil bacteria quantity (SBQ), fungi quantity (SFQ), and actinomycetes quantity (SAQ). TY, NI, SBQ, SFQ, and SAQ were highest at W2. Soil microbial population was strongly correlated with TY, NI, WP, TNA, and NUE. Comprehensively, this study suggests that irrigation that is varied from 248 to 266 mm, and fertilization (N-P-K) that is varied from 149.09-74.55-186.36 to 212.73-106.36-265.91 kg ha−1 can promote the potato industry’s sustainable development and provide important references for the optimal field management of potato cultivation in northwest China.

Water use of Guinea grass as affected by rainfed local conditions and practices in Sub-Saharan Africa

Ongoing efforts are currently being made to rehabilitate drought-affected pastures in Sub-Saharan Africa. One approach being explored is the introduction of non-native grass species, such as Megathyrsus maximus (Guinea grass). This study aims to investigate the water use of Guinea grass in semi-arid environments under rainfed conditions. Additionally, it aims to a better understanding of the variability of water use in Guinea grass through the utilization of the Bagging machine learning algorithm. Split-plot field experiments were carried out over two consecutive rainy seasons (2020-2021). The treatments included two in-situ rainwater harvesting practices, RWH (ridging plus terracing and terracing alone), three seeding rates, SR (1.5, 2.5, and 3.5 kg ha-1), and two soil nitrogen fertilization rates, SF (95 kg N ha-1 and 0 kg N ha-1). These treatments were compared to a control plot that involved zero-tillage, no fertilization, and no rainwater harvesting. The collected datasets were analyzed using R, SPSS 15, and spreadsheets. The results showed significant differences in plant indices and soil moisture content among the treatments. However, the treatments had insignificant effects on seasonal actual crop evapotranspiration (ETa), which ranged from 1.93 to 3.29 mm day-1. The interactions between SR and RWH were found to have significant impacts on water use. The Bagging algorithm revealed that the variability in ETa could be attributed to SR (42%), RWH (31%), and SF (26%), respectively. The implementation of rainwater harvesting practices resulted in a significant reduction in water usage, saving 86% of the green water used with a water footprint of 0.25 m3 kg-1, compared to 1.7 m3 kg-1 for no adoption of RWH conditions. The water use of rainfed Guinea grass was also found highly sensitive to dry spells. Further detailed studies using multiple-layer models are recommended to gain a better understanding of the non-linear interactions in semi-arid environments.