Net Requirements Research Articles

Irrigation development as a booster of the multifunctional roles of paddy rice

AbstractTo promote sustainable production and the multiple roles of paddy rice, it is essential to expand our understanding of the impacts of different management options, with particular emphasis on irrigation development. The impact of various management practices (supplementary irrigation during the rainy season, improved fertilization, cropping during the dry season and mulching practices) on irrigation water requirements, crop productivity and the multifunctional roles of irrigated paddy rice was evaluated in diverse agro‐ecological zones of Zambia, by using the AquaCrop model. Irrigation development has been demonstrated to boost paddy rice production (by 8%) in the southern districts by providing supplementary irrigation (about 150 mm) during the rainy season. Additionally, supplementary irrigation during the rainy season can make improved fertilization more attractive, doubling the yield rise under rainfed conditions. The required irrigation development would also enable paddy rice cropping intensification by allowing for dry season sowing (with net irrigation requirements from 700 to 800 mm). Moreover, the associated straw production increase could also play an important role as mulch during the dry season, reducing the net irrigation requirements by 15%. These findings will enable policymakers to make informed decisions regarding investment strategies and policies.

Impact of climatic changes on future irrigation water requirement in the Middle East and North Africa's region: a case study of upper Egypt

Freshwater shortages in the Middle East and North Africa's region (MENA) cause serious issues, while climate change causes even more issues. The current study examines how climate change may impact future irrigation requirements in Egypt's Upper Region using the medium greenhouse emission RCP 4.5 and high emission RCP 8.5 scenarios. Based on the Intergovernmental Panel on Climate Change (IPCC) and the Fifth Assessment Report, the climatic projections for RCPs 4.5 and 8.5 for the years 2023–2080 and 2081–2100 were used to determine the patterns of temperature and rainfall in the upper Egypt territory. The CROPWAT model was employed to estimate reference evapotranspiration (ETo) and net irrigation water requirement (NIWR) for the upper Egypt territory key crops sugar cane, potatoes, berseem clover (alfalfa), dry bean, wheat, cotton, maize, and tomato based on the predicted meteorological conditions. Five different scenarios for the key crops' future irrigation needs were calculated. The results reveal that under RCP 4.5 greenhouse emission for the periods 2023–2080 and 2081–2100, respectively, the overall NIWR for all examined crops increases by 5.1 and 5.9% in comparison to the current (2022) total NIWR for all crops. The total NIWR for all crops analyzed increases by 7.7 and 9.7% under the RCP 8.5 greenhouse emission scenario for the periods 2023–2080 and 2081–2100, respectively, in contrast to the current total NIWR for all crops. It is important to consider changes in water resource management in the MENA region, such as applying modern irrigation systems, using crop pattern rotation strategies with minimal water demands, and changing crop calendars or the times and locations of cropping activities.

Creation of Geospatial Database and Estimation of Irrigation Water Requirement of a Canal Command in Gayathri Irrigation Project, Kerala

The water requirement of crops in the canal command of distributaries of Gayathri Irrigation Project in Palakkad district, Kerala was estimated using GIS and CROPWAT 8 model. The geospatial data base for canal network, land use, soil and climate were prepared using Geographic Information System (GIS) tools. This data base was used as input to CROPWAT model to estimate irrigation water requirement of different distributaries of the canal command. The gross irrigation requirement was estimated for the historical climate data (2004-2018) as well as the predicted climate data for the years 2026 and 2031. The net irrigation water requirement of different crops in the distributary command was found to vary spatially depending on soil, crop and climate. The net irrigation water requirement of paddy (mundakan) in distributaries located at head to tail reaches varied from 1004.5 to 1573.6 mm. The high value of net irrigation requirement in tail reach was due to the influence of soil series with high infiltration rate compared to head reach soil. The net irrigation requirement also varied for the same crop in same soil series in different distributaries depending upon the climatic conditions. The net irrigation water requirement of paddy (mundakan) in distributaries located at head to middle reaches for the same soil series varied from 1056.5 to 1004.5 mm due to the influence of variations in rainfall. The gross estimated irrigation water requirement showed that distributaries at the middle and tail reaches required more water than the distributaries at the head end. The maximum gross irrigation water requirement of 25369.7 m3/ha was observed for Peringhotukavu distributary in tail reach and lowest of 4390.9 m3/ha for Parakkalchalla distributary in head reach. The estimation of irrigation requirement for projected climate data also showed the same trend as that of historical data.

Advancements in solar technology, markets, and investments – A summary of the 2022 ISA World Solar Reports

This paper provides a summary of the Annual World Solar Reports on Technology, Markets, and Investments published by the International Solar Alliance (ISA) in October 2022. Solar has emerged as the technology of choice to drive the renewable energy transition. This preference for solar has been driven by technology maturity and improvements, cost reductions, and improved methods for grid integration of solar generation. Globally, solar has grown nearly 20 fold in the last decade to reach 920 GW of installed capacity in 2021. As solar approaches and crosses into Terawatt scale of deployment, a number of technological innovations are emerging to continue improving generation efficiency, power output, and material consumption. Additionally, manufacturing capacity is growing rapidly to meet demand for installations. The market for solar installations continues to grow around the world but will need to scale rapidly to meet net zero requirements. The growth in solar markets will also require a significant scale up in solar investments across the world through a wide range of instruments. The deployment of the correct solar related interventions can ensure that the world can achieve multi terawatt scale of solar deployment in the coming decades, thus supporting the global energy transition.

An Integrated Approach to Evaluating Crop Water Requirements and Irrigation Schedule for Optimizing Furrow Irrigation Design Parameters in Kurnool District, India

In Kurnool district, due to the hot, arid climatic conditions, proper study of crop evapotranspiration and its effect on crop water demand for various crops is an extremely important issue. More focus will be given to the design and development of surface irrigation systems based mostly on furrow irrigation, as the rainfall pattern for this district was irregular in 2005. The crop water requirement and furrow irrigation design parameters for optimising the beneficial utilisation of available water resources and field performances are studied in this research. Some major crops, such as cotton, sugarcane, sorghum, maize, and sunflower, are considered when adopting a suitable furrow irrigation system for soil conditions of the types black clay, red loamy, and medium loam. The reference crop evapotranspiration was estimated for 2005 based on the Penman–Monteith equation as per FAO guidelines by the CROPWAT 8.0 model. Crop Water Requirement (CWR), Net Irrigation Requirement (NIR), and Gross Irrigation Requirement (GIR) were determined for available climatic and soil conditions. Soil surface characteristics were studied using AQUACROP 6.1 and compared with CROPWAT 8.0 for model accuracy. Various conservative and non-conservative crop characteristics were studied under limited set conditions, and correlation equations were developed between different parameters. Moreover, different furrow irrigation design parameters were considered by FURDEV (a module of the SURDEV model) for three modes of operation (i.e., fixed flow, cutback flow, and tailwater reuse method) under modified SCS (Soil Conservation Service) families of soil infiltration characteristics. NIR values were 200 mm, 1423.2 mm, 220 mm, 150 mm, and 150 mm for cotton, sugarcane, maize, sorghum, and sunflower, respectively. A maximum significant dry yield was observed for maize (13.586 tonnes/ha). Additionally, the maximum application efficiency and storage efficiency were obtained at 95.5% for sorghum and 99.3% for sunflower, which would be a beneficial outcome of this research. In general, the results of this research might be very effective for the irrigation authority of Kurnool District to plan suitable approaches for designing and developing proper water management systems.

Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080)

This study aims to predict the effect of climate change on net irrigation water requirements (NIWR) and agricultural productivity from five common crops (wheat, barley, summer maize, and sorghum) in the Al-Najaf Governorate in Iraq. GFDL-ESM2M mode was used to predict the lower and upper temp and precipitation for two time periods (2020-2080) with 30 years for two periods (P1 and P2) under representative concentrations paths (RCP 2.5, RCP6, and RCP8.5). The CROPWAT model is used to determine NIWR, and the extreme learning model was used to estimate agricultural yields using previous crop yield production and weather data, supported vectors machine (SVM) is executed as a Machines Learns algorithm. Results showed NIWR increment to consider cropping owing to climate change. Barley is the crop most affected by climate change under the (RCP2.5, RCP6, and RCP8.5) scenarios, with increasing crop water requirements (NIWR) of (22%, 23%, and 24% ) for P1 and (23%, 24%, and 29%) for P2, respectively. Summer maize is the crop least affected by climate change under all climate change scenarios, with increasing crop water requirements of (1%, 2%, and 4%) for P1 and (1%, 2%, and 5% for P2. Climate change negatively affects the crop yield of all crops under the different climate change scenarios. The findings of this study could be used as a guide to developing adaptation strategies for dealing with potential changes in water availability and agricultural water productivity due to climate change.

Projection of net irrigation requirement over India using a bias-corrected spatially downscaled dataset

Abstract With the country's economy directly dependent on food grain production, accurate estimation of the net irrigation requirement (NIR) of crops is essential for maximizing production. The daily IMD precipitation (0.25° × 0.25°) and temperature (1° × 1°) gridded datasets (1971–2010) were considered for the present scenario. Two satellite-based crop coefficient layers were prepared for the study: (i) kc_EEFlux, the evaporative fraction layer from earth engine evapotranspiration flux (EEFlux) and (ii) kc_FEWS, the ratio of the famine early warning system network (FEWSNET) monthly actual evapotranspiration (ET) (ETa) to ET0_FEWSNET layers. The NIR was estimated for three different cropping pixels derived from the land-use land cover (LULC) map of India, namely, Kharif-only, Rabi-only, and double/triple pixels using ‘ET0 and NIR toolbar’. The National Aeronautics and Space Administration (NASA)'s Earth Exchange Global Daily Downscaled Projections dataset were employed for projecting the future scenario. Results showed discrepancies in the extreme values of FAO56-Penman–Monteith (PM) and Hargreaves–Samani's estimated reference ET (ET0) but followed a similar trend in all months (R2 = 0.88). Results also suggested that FEWSNET offered more reliable estimates of NIR over EEFlux. The projected ensemble NIR indicated a probable negative relative change during the Kharif season (RCP4.5: from −14.47 to −7.25%; RCP8.5: from −11.45 to −5.59%) while a probable positive relative change during the Rabi season (RCP4.5: 3.30–5.21%; RCP8.5: 2.34–8.83%).

Exploring hydrogen fuel cell and battery freight locomotive options using train dynamics simulation

As efforts are being made to quickly adopt zero carbon technologies and replace fossil fuel powered trains, the design requirements are explored using train dynamics simulations to establish energy needs. The test case was a freight train of 3030 gross tonnes consisting of two locomotives and thirty wagons operating on a relatively flat coastal rail route. Then, assuming rapid deployment of existing and near market technologies, speculative locomotive designs are proposed for both battery only and hydrogen-battery systems. Batteries were assumed as rack mounted systems and hydrogen assumed at 250 bar gaseous. The results showed that full recovery of dynamic braking required only a very small amount of storage to capture and allow re-use, requiring a battery of only 6% of the trip total of recovered energy. The haulage task was found to require traction energy of 10.7 MWh per locomotive but reduced to a net requirement of 7.6 MWh per locomotive with recovery of dynamic braking energy. The large mass of batteries needed for the operating trip, however, limits the practical operating range. The results showed that, although hydrogen storage and equipment occupy considerable space and the containment systems have large mass, the space and mass requirements for a hydrogen system in this case study could be as low as half that required for batteries, while higher pressure or cryogenic approaches to hydrogen storage will allow the scaling for longer range.

Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT

Abstract The study is conducted to examine the climate change impact on rice Crop Water Requirement (CWR) and Net Irrigation Requirement (NIR) using the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) coupled with the CROPWAT 8.0 model. The maximum temperature (Tmax), minimum temperature (Tmin), and rainfall projections for the baseline (years 1981–2015) and future (years 2030 and 2040) under Representative Concentration Pathway (RCP) 4.5 were derived from NEX-GDDP. To reduce the bias, linear scaling (LS) and the modified difference approach (MDA) were employed. Results show that LS performed better than the MDA along with improved statistical measures such as mean (μ), standard deviation (σ), and percent bias (Pbias), in the case of Tmax and Tmin (μ = 31.14 and 19.63 °C, σ = 5.75 and 6.78 °C, Pbias = 1.43 and 0.33%), followed by rainfall (μ = 2.67 mm, σ = 4.94 mm, and Pbias = 2.4%). The future climatic projections showed an increasing trend in both Tmax and Tmin, which are expected to increase by 1.7 °C by 2040. This would cause an increased range of 1.2 and 2% in 2030 and 2040, respectively. Due to a wide variation in effective rainfall (Peff), NIR could increase by 4 and 9% in 2030 and 2040, respectively. The above results may help formulate adaptation measures to alleviate the impacts of climate change on rice production.

Macromineral requirements for maintenance and growth in male and female hair sheep

A better understanding of the nutritional requirements of sheep, especially in terms of minerals, is crucial for improving production. We estimated the net requirements for Ca, P, K, Mg, and Na for gain (NCag, NPg, NKg, NMgg, and NNag) and maintenance (NCam, NPm, NKm, NMgm, and NNam) in male and female hair sheep. Six datasets with 248 individual records of hair sheep (139 non-castrated males, 75 castrated males and 34 females) were used to estimate the net macromineral requirements for gain. To estimate the net macromineral requirements for maintenance, 52 observations (26 non-castrated and 26 castrated males) were used. A meta-analytical approach was applied, using non-linear mixed effects models and the study as a random effect. Based on information criteria for model selection, heterogeneous variance functions were more likely to describe mineral requirements with a low level of model selection uncertainty. The adopted criteria allowed the choice of the best models to represent the macromineral requirements. The chosen models explained the observed variability in the sex, and the choices were based on a low level of uncertainty (w ≥ 0.90). Irrespective of sex, NCag and NPg decreased with increasing BW from 10 to 30 kg and average daily gain (ADG) of 150 g/day, ranging from 1.71-1.38; 1.83-1.57; 1.82-1.51 of Ca and 0.86-0.66; 0.92-0.78; 0.92-0.75 of P for non-castrated males, castrated males, and females, respectively. The NKg remained constant, with mean values of 0.26 g/day. The NNag range was 0.17 to 0.14 g/day for non-castrated males, 0.20 to 0.25 g/day for females, and constant (0.18 g/day) for castrated males with an increase in BW from 10 to 30 kg and an ADG of 150 g/day. Macromineral requirements for maintenance (mg/kg BW) and retention (%) were 23.70 and 54.30 for Ca, 25.33 and 79.80 for P, 11.74 and 5.00 for K, 2.63 and 8.50 for Mg, and 7.01 and 8.10 for Na for males. The International Committees did not provide inferences about the sex influence on mineral requirements. Our study indicates that sex is one factor that influences the macromineral requirements for gain. The information generated in this study can be used to optimize the mineral management of hair sheep in the growing phase in tropical regions.

Climate Change Impacts on Water Resources in Arid and Semi-Arid Regions: A Case Study in Saudi Arabia

In the coming years, climate change is predicted to impact irrigation water demand considerably, particularly in semi-arid regions. The aim of this research is to investigate the expected adverse impacts of climate change on water irrigation management in Saudi Arabia. We focus on the influence of climate change on irrigation water requirements in the Al Quassim (97,408 ha) region. Different climate models were used for the intermediate emission SSP2-4.5 and the high emission SSP5-8.5 Coupled Model Intercomparison Project Phase 6 (CMIP6) scenarios. The FAO-CROPWAT 8.0 model was used to calculate reference evapotranspiration (ETo) using weather data from 13 stations from 1991 to 2020 and for both the SSP2-4.5 and SSP5-8.5 scenarios for the 2040s, 2060s, 2080s, and 2100s. The findings indicated that, for the 2100s, the SSP2-4.5 and SSP5-8.5 scenarios forecast annual average ETo increases of 0.35 mm/d (6%) and 0.7 mm/d (12.0%), respectively. Net irrigation water requirement (NIWR) and growth of irrigation water requirement (GIWR) for the main crops in the Al Quassim region were assessed for the current, SSP2-4.5, and SSP5-8.5 scenarios. For SSP5-8.5, the GIWR for the 2040s, 2060s, 2080s, and 2100s are expected to increase by 2.7, 6.5, 8.5, and 12.4%, respectively, compared to the current scenario (1584.7 million m3). As a result, there will be higher deficits in 2100 under SSP5-8.5 for major crops, with deficits of 15.1%, 10.7%, 8.3%, 13.9%, and 10.7% in the crop areas of wheat, clover, maize, other vegetables, and dates, respectively. Optimal irrigation planning, crop pattern selection, and modern irrigation technologies, combined with the proposed NIWR values, can support water resources management. The findings can assist managers and policymakers in better identifying adaptation strategies for areas with similar climates.

Estimation of Crop Water Requirements and Irrigation Scheduling for Major Crops Grown in India's North-Eastern Region

The water demand of some agricultural crops grown in Assam was assessed in this research. To estimate the crop water requirements of potato, chili, and brinjal, the FAO-CROPWAT model was used. The climatic parameters like rainfall, solar radiation, wind speed, sun hours, relative humidity, minimum and maximum temperature were collected for 30 years from the Indian Meteorological Department (IMD) to estimate the crop water requirement (CWR). The reference evapotranspiration (ETo) was computed by using the Food and Agriculture Organization (FAO)-recommended Penman-Monteith method and was found to vary from 1.84 mm/day to 4.49 mm/day. The calculated ETo was further used to compute the CWR, the net irrigation requirement (NIR), and the gross irrigation requirement (GIR) to plan for irrigation application during the growing stages of the selected crops. The total CWR of potato, chili, and brinjal was estimated to be 260.6 mm, 262.1 mm, and 274.2 mm, respectively, and the total NIR of potato, chili, and brinjal sowed on the 1st of October was found to be 162.8 mm, 149.0 mm, and 167.2 mm, respectively, with an irrigation efficiency of 70%. In December, the CWR and NIR of potato and brinjal were found to be the highest. The month with the least effective rainfall (8.5 mm) was December. The findings of the study showed that efficient irrigation water management and irrigation scheduling can be achieved by using the CROPWAT model to maximize crop yield and minimize crop water stress.

A new protein requirement system for dairy cows

Accurate prediction of protein requirements for maintenance and lactation is needed to develop more profitable diets and reduce N loss and its environmental impact. A new factorial approach for accounting for net protein requirement for maintenance (NPM) and metabolizable protein (MP) efficiency for lactation (EMPL) was developed from a meta-analysis of 223 N balance trials. We defined NPM as the sum of the endogenous protein fecal and urinary excretion and estimated it from the intercept of a nonlinear equation between N intake and combined total N fecal and urinary excretion. Our model had a strong goodness-of-fit to estimate NPM (6.32 ± 0.15 g protein/kg metabolic body weight; n = 807 treatment means; r = 0.91). We calculated the EMPL as a proportion of the N intake, minus N excreted in feces and urine, that was secreted in milk. A fixed-EMPL value of 0.705 ± 0.020 was proposed. In a second independent data set, nonammonia-nonmicrobial-N and microbial-N ruminal outflows were measured, and the adequacy of the MP prediction (51 studies; n = 192 means treatments) was assessed. Our system based on the fixed-EMPL model predicted the MP requirement for lactation and maintenance with higher accuracy than several North American and European dairy cattle nutrition models, including the INRA (2018) and NASEM (2021). Only the NRC (2001), CNCPS 6.5, and Feed into Milk (2004) models had similar accuracy to predict MP requirement. Our system may contribute to improve the prediction for MP requirements of maintenance and lactation. However, most refined predictive models of intestinal digestibility for rumen undegradable protein and microbial protein are still needed to reduce the evaluation biases in our model and external models for predicting the MP requirements of dairy cows.

An Artificial Intelligence Approach to Manage Crop Water Requirements in South Africa

Estimation of crop water requirements is of paramount importance towards the management of agricultural water resources, which is a major mitigating strategy against the effects of climate change on food security. South Africa water shortage poses a threat on agricultural efficiency. Since irrigation uses about 60% of the fresh water available, it therefore becomes important to optimise the use of irrigation water in order to maximize crop yield at the farm level in order to avoid wastage. In this study, combined application of an artificial neural network (ANN) and a crop – growth simulation model for the estimation of crop irrigation water requirements and the irrigation scheduling of potatoes at Winterton irrigation scheme, South Africa was investigated. The crop-water demand from planting to harvest date, when to irrigate, the optimum stage in the drying cycle when to apply water and the amount of irrigation water to be applied per time, were estimated in this study. Five feed –forward backward propagation artificial neural network predictive models were developed with varied number of neurons and hidden layers and evaluated. The optimal ANN model, which has 5 inputs, 5 neurons, 1 hidden layer and 1 output was used to predict monthly reference evapotranspiration (ETo) in the Winterton area. The optimal ANN model produced a root-mean-square error (RMSE) of 0.67, Pearson correlation coefficient (r) of 0.97 and coefficient of determination (R2) of 0.94. The validation of the model between the measured and predicted ETo shows a r value of 0.9048. The predicted ETo was one of the input variables into a crop growth simulation model, called CROPWAT. The results indicated that the total crop water requirement was 1259.2 mm/decade and net irrigation water requirement was 1276.9 mm/decade, spread over a 5-day irrigation time during the entire 140 days of cropping season for potatoes. A combination of the artificial neural networks and the crop growth simulation models have proved to be a robust technique for estimating crop irrigation water requirements in the face of limited or no daily meteorological datasets.

Content and gain of macro minerals in the empty body and body tissues of growing bulls

This research aimed to generate basic data for specifying the macro mineral requirements of beef bulls. Hence, the contents of the macro minerals calcium, phosphorus, sodium, potassium, sulfur, and magnesium in the empty body and body tissue fractions of growing Fleckvieh (German Simmental) bulls with 120–780 kg live weight were determined. Results were used to calculate mineral gain rates in bulls within a wide weight range from 100 to 800 kg live weight. Calcium and phosphorus represented the largest shares in the animals' bodies. Body mineral content changed during animal growth due to progressing bone mineralization and increasing amounts of fat in all body tissues. Peak mineral gain rates were observed for calcium, phosphorus, and magnesium during the 200–400 kg live weight range. The gain rates of sodium, potassium, and sulfur declined steadily during cattle growth. The provided data allow to adjust the existing values of net mineral requirements of growing Fleckvieh bulls within the factorial requirement calculation method.

Net zero emission buildings: next generation of benchmarks and calculation rules

The definition of ambitious life cycle-based benchmarks and target values to limit the GHG emissions of buildings is seen as one of the most important steps in pushing the construction and real estate sector in significantly reducing its contribution to global warming. Especially target values are no longer only developed from a bottom-up perspective. There is now an interest by governments and sustainability assessment system providers in supplementing bottom-up approaches with science-based top-down approaches as part of their responsibility to respect planetary boundaries. The creation of GHG emission budgets in combination with target values, as well as the introduction of strict enough legal binding requirements already today is critical for achieving a climate-neutral building stock. Achieving these tasks requires tackling still open methodological issues. Following the work of IEA EBC Annex 72 and current developments in Germany, the paper presents main questions, key steps, modelling aspects that can cause variation and uncertainties, as well as clarifies key terms and definitions. It is highlighted that although a net zero emission requirement is a universal benchmark, information on system boundaries and calculation rules are still necessary to provide evidence of its fulfilment.

Water Requirement of Selected Crops for Sangareddy District of Telangana Using CROPWAT 8.0

The precise selection of appropriate crops that are compatible with the soil and crop water requirements (CWR) in a particular area is necessary for effective land and water management. A study was conducted to ascertain the agricultural water requirements of a few chosen crops for the Sangareddy District of Telangana. The crops include Rice, Sugarcane, Soybean, Maize, Cotton, Black gram, Green gram, and Bengal gram. Using meteorological data from the past 10 years stored in CROPWAT, the amount of water needed by each crop was calculated. The FAO Penman-Monteith method was used to determine reference crop evapotranspiration (ET0). The study shows that reference crop evapotranspiration, ETo varied from 7.96 mm/day to 3.14 mm/day in the years between 2010 – 2021. The crop water requirement (CWR) and Net irrigation requirement for Rice were 595.5 mm and 331.9 mm, Maize was 366.6 mm and 64.3 mm, Cotton was 612.7 mm and 283.8 mm, Sugarcane was 1902.1 mm and 1189.3 mm, Soybean was 270.9 mm and 0.0mm, the Black gram was 332.1 mm and 22.1 mm, Green gram was 342.7 mm and 13.3 mm and Bengal gram was 344.9 mm and 316.1 mm. The results were accurate R2 was 0.84 compared with the Class A pan. This study demonstrates that the CROPWAT model is helpful for computing the crop water requirement which needs for the appropriate administration of water assets.

Net irrigation requirement under different climate scenarios using AquaCrop over Europe

Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70 % of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5∘lat×0.5∘long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06 m3 m−3, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015–2016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015–2020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031–2060 and 2071–2100) is compared to the baseline period of 1985–2014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22 mm per month (+30 %) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3–7.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1–2.6), the increase in Inet will stabilize at around 13 mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.

Estimation of Irrigation Requirement and Schedule in Southern Odisha for Major Rabi Cereal Crops using FAO CROPWAT 8.0 Model

Background: The increasing population and need for higher quantity of food grain production necessitates efficient use of limited water in the country, as agriculture sector alone uses 78% of water resources of India. During rabi season, mostly the crops are grown with irrigation in southern Odisha. There is no enough information on water and irrigation requirement of maize, sorghum and pearl millet crops grown in the region, which necessitated this study. Methods: The model-based study involving FAO CROPWAT 8.0 was used for the estimation of gross and net irrigation requirement and scheduling of maize, sorghum and pearl millet grown in southern Odisha. Result: The water requirement estimated with FAO CROPWAT 8.0 model during rabi for maize, sorghum and pearl milletgrown in Southern Odisha was 252.3, 197.9 and 172 mm and irrigation requirement was 231.2, 178.8 and 156.3 mm respectively.

Effects on Net Irrigation Water Requirement of Joint Distribution of Precipitation and Reference Evapotranspiration

To establish the uncertain influence that the joint distribution of precipitation and reference evapotranspiration has on net irrigation water requirement, a Copula function–Monte Carlo method (CFMC) was proposed to calculate the probability of irrigation water requirement. Taking the Jingdian Irrigation District in Northwest China as an example, the distribution laws of precipitation and reference evapotranspiration were studied. Furthermore, five typical years under different crop planting structure conditions were selected, and the variation characteristics of net irrigation water requirement in each typical year under the conditions of climate uncertainty were analyzed. The results revealed the optimal distribution functions of precipitation and reference evapotranspiration to be gamma distribution and lognormal distribution. The probability density map of the joint distribution of precipitation and reference evapotranspiration has a “saddle” shape; that is, irrigation water requirement and reference evapotranspiration are usually inversely related. As the probability of the irrigation water requirement increases, the net irrigation water requirement in the irrigation area also increases. The CFMC method can determine the design value of the net irrigation water requirement under a specific probability for typical years under different crop planting structure conditions, which can provide a reference for agricultural water resource allocation in irrigation areas.