Crop Consumptive Use Research Articles

Fertigation under different irrigation and nitrogen levels modulates the growth, physiology, nitrogen and fruit productivity of greenhouse tomato

AbstractExperiments were conducted to evaluate the interactive effects of different nitrogen and irrigation levels in 2017 and 2018 (April–July) on greenhouse‐grown tomato considering irrigation water, growth, physiology and productivity parameters. A randomized block design with three replications and two factors, water (W1, 100% of the requirement; W2, 90%; W3, 70%) and nitrogen fertilizer (F1 225 kg/ha, F2 180 kg/ha), was established. The highest values of crop consumptive use (ET) were observed under the W1F1 treatment during both seasons (266 and 226 mm during 2017 and 2018, respectively). The highest values of stem and root biomass were also observed under W1F1 during both experimental seasons, followed by W1F2 and W2F1, without significant differences. Compared with W1F1, W1F2 and W2F1 had no significant difference, but other treatments decreased the photosynthesis rate and stomatal conductance significantly during both seasons. The highest irrigation level, W1, increased fruit yield under both nitrogen levels (W1F1 yielded 91 and 102 t ha−1, followed by W1F2, with 90 and 99 t ha−1 during 2017 and 2018, respectively). W2 increased fruit yield under higher nitrogen levels (F1) but decreased fruit yield under lower nitrogen levels (F2). W3 decreased yield drastically under both nitrogen levels. W3 significantly decreased water use efficiency and irrigation water use efficiency. The highest partial factor productivity values of 23% and 22% were obtained under W1F2 in 2017 and 2018, respectively, when compared with the control treatment. It was concluded that W1F2 could be the best strategy for improving greenhouse‐grown tomato productivity.

Kebutuhan Air Irigasi pada D.I Krueng Pasee Aceh Utara

Water demand is the amount of water volume that must be met for irrigation, in the Krueng Pasee irrigation area of North Aceh has an irrigation network area of 5579 Ha. The purpose ofthis research is to obtain the maximum and minimum irrigation water demand discharge in the study area. This research can be an additional source of knowledge for writers in particular and for readers in general. As well as the results of this study can be known the value of rice planting water needs. The data used in the research is rainfall data sourced from BMKG (Meteorology, Climatology, and Geophysics Agency) Malikussaleh, used to calculate effective rainfall and climate data sourced from BMKGMalikussaleh in the form of temperature data, solar irradiation data, wind speed data and humidity or temperature data used to calculate evapotranspiration (ETo). ETo is a combination of evaporation and transpiration which is defined as the event of water loss from plant tissue and the surface of the soil usedas a place to grow plants. In analyzing ETo using the Penman Modification Methodology. The Penman method by adjusting the wind function according to local conditions produces the best approach to the evapotranspiration rate of the lysimeter results. The consumptive use of plants (ETc) during the land preparation period uses the results of the calculation of water requirements for land preparation (IR). Crop consumptive use (ETc) after land preparation is a calculation between evapotranspiration and cropcoefficient. The calculated irrigation water requirement (NFR) results in water requirement in the form of mm/day. Irrigation water requirements are converted to l/dt/ha with a conversion rate of 1/8.64. The smallest water demand calculation discharge was obtained in November-1 at Q = 4.32 m3/det and thelargest water demand in February -1 at Q = 13.40 m3/det. At the research location, rice planting begins in January-I, with a rice-soybean planting pattern. From the calculation of water demand, Krueng Pasee Irrigation Area has the smallest water demand in November-1 and the largest water demand in February-1.

Novel Salinity Modeling Using Deep Learning for the Sacramento–San Joaquin Delta of California

Water resources management in estuarine environments for water supply and environmental protection typically requires estimates of salinity for various flow and operational conditions. This study develops and applies two novel deep learning (DL) models, a residual long short-term memory (Res-LSTM) network, and a residual gated recurrent unit (Res-GRU) model, in estimating the spatial and temporal variations of salinity. Four other machine learning (ML) models, previously developed and reported, consisting of multi-layer perceptron (MLP), residual network (ResNet), LSTM, and GRU are utilized as the baseline models to benchmark the performance of the two novel models. All six models are applied at 23 study locations in the Sacramento–San Joaquin Delta (Delta), the hub of California’s water supply system. Model input features include observed or calculated tidal stage (water level), flow and salinity at model upstream boundaries, salinity control gate operations, crop consumptive use, and pumping for the period of 2001–2019. Meanwhile, field observations of salinity at the study locations during the same period are also utilized for the development of the predictive use of the models. Results indicate that the proposed DL models generally outperform the baseline models in simulating and predicting salinity on both daily and hourly scales at the study locations. The absolute bias is generally less than 5%. The correlation coefficients and Nash–Sutcliffe efficiency values are close to 1. Particularly, Res-LSTM has slightly superior performance over Res-GRU. Moreover, the study investigates the overfitting issues of both the DL and baseline models. The investigation indicates that overfitting is not notable. Finally, the study compares the performance of Res-LSTM against that of an operational process-based salinity model. It is shown Res-LSTM outperforms the process-based model consistently across all study locations. Overall, the study demonstrates the feasibility of DL-based models in supplementing the existing operational models in providing accurate and real-time estimates of salinity to inform water management decision making.

Quantifying global agricultural water appropriation with data derived from earth observations

Agricultural water appropriation has undergone rapid changes in recent decades, but estimates of global water appropriation have not been updated with the latest data and consistent methods. Documenting these changes is challenging given the heterogeneous water use landscape and the growing influence of human activities worldwide, and this complexity cannot be well addressed with the existing methodology, which is subject to large model uncertainties. Here, a spatial analysis and aggregated method was proposed to quantify and refine estimates of global agricultural water appropriation (GAWA) in terms of consumptive freshwater use, with data derived from Earth observations, independent of estimates from hydrological models. The results show the global water appropriation at the pixel scale, in agroecological zones and in the main water-consuming countries, including global maps of rainfed and irrigated cropland evapotranspiration (ET), net water consumption due to irrigation, natural ET and renewable freshwater resources (RFWR), and indicate that agriculture remains the largest user in terms of both water consumption and withdrawals worldwide, representing 87% of global water consumption, with approximately 60% of global freshwater withdrawals devoted to irrigation circa 2015. The percentage of withdrawals devoted to irrigation has decreased in recent decades when compared to the previous estimate of 70%. The results reveal the actual global crop consumptive use (8053.6 km3/yr) of blue and green water and the total human water consumption (8442 km3/yr), which represents the part of the water cycle affected by human intervention, mainly (95.4%) by agriculture. This study reveals that high-resolution irrigated croplands are essential for accurate estimations of water use appropriation and demonstrates that earth observation-derived data can provide a new understanding of global water use landscape. The study can support decision making in sustaining food and water security, and implementing water-adapted sustainable agricultural policies.

Long-Term (1986–2015) Crop Water Use Characterization over the Upper Rio Grande Basin of United States and Mexico Using Landsat-Based Evapotranspiration

The evaluation of historical water use in the Upper Rio Grande Basin (URGB), United States and Mexico, using Landsat-derived actual evapotranspiration (ETa) from 1986 to 2015 is presented here as the first study of its kind to apply satellite observations to quantify long-term, basin-wide crop consumptive use in a large basin. The rich archive of Landsat imagery combined with the Operational Simplified Surface Energy Balance (SSEBop) model was used to estimate and map ETa across the basin and over irrigated fields for historical characterization of water-use dynamics. Monthly ETa estimates were evaluated using six eddy-covariance (EC) flux towers showing strong correspondence (r2 > 0.80) with reasonable error rates (root mean square error between 6 and 19 mm/month). Detailed spatiotemporal analysis using peak growing season (June–August) ETa over irrigated areas revealed declining regional crop water-use patterns throughout the basin, a trend reinforced through comparisons with gridded ETa from the Max Planck Institute (MPI). The interrelationships among seven agro-hydroclimatic variables (ETa, Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), maximum air temperature (Ta), potential ET (ETo), precipitation, and runoff) are all summarized to support the assessment and context of historical water-use dynamics over 30 years in the URGB.

Managed aquifer recharge through off‐season irrigation in agricultural regions

AbstractOptions for increasing reservoir storage in developed regions are limited and prohibitively expensive. Projected increases in demand call for new long‐term water storage to help sustain agriculture, municipalities, industry, and ecological services. Managed aquifer recharge (MAR) is becoming an integral component of water resources around the world. However, MAR faces challenges, including infrastructure costs, difficulty in enhancing recharge, water quality issues, and lack of available water supplies. Here we examine, through simulation modeling of a hypothetical agricultural subbasin in the western U.S., the potential of agricultural managed aquifer recharge (Ag‐MAR) via canal seepage and off‐season field irrigation. Weather phenomenon in many regions around the world exhibit decadal and other multiyear cycles of extreme precipitation. An ongoing challenge is to develop approaches to store greater amounts of water during these events. Simulations presented herein incorporate Ag‐MAR programs and demonstrate that there is potential to enhance regional recharge by 7–13%, increase crop consumptive use by 9–12%, and increase natural vegetation consumption by 20–30%, where larger relative increases occur for lower aquifer hydraulic conductivity and higher specific yield values. Annual increases in groundwater levels were 7 m, and sustained levels following several years of drought were greater than 2 m. Results demonstrate that Ag‐MAR has great potential to enhance long‐term sustainability of water resources in agricultural basins.

Yield Response Factor for Onion (Allium Cepa L) Crop Under Deficit Irrigation in Semiarid Tropics of Maharashtra

The present study deals with the study of yield response factor (Ky) for onion crop cultivated under deficit irrigation for Rahuri region (Maharashra). The field experiment was conducted to determine the yield response factor of the onion (Allium cepa L.) cv. N-2-4-1 crop under the deficit irrigation approach during summer season of 2012 and 2013 at Instructional Farm of the Department of Irrigation and Drainage Engineering, Dr. Annasaheb Shinde College of Agricultural Engineering, Mahatma Phule Krishi Vidyapeeth Rahuri. Experiment was carried out in Randomized Block Design (RBD) with 27 treatments and two replications based on different combinations of the quantity of water stress during different crop growth stages. Water applied per irrigation and soil moisture contents before and after irrigation were monitored throughout the season, while onion bulbs were harvested at the end of season and weighed. Average daily crop water use (crop consumptive use) were estimated from the soil moisture content using the soil moisture depletion method. The seasonal yield response factor (Ky) was obtained by relating relative yield decreases to relative crop water use deficit by the regression analysis. The relative yield decreases of the onion crop were proportionally greater with increase in evapotranspiration deficit. It shows the response of yield with respect to the decrease in water consumption. In other words, it explains the decrease in yield caused by the per unit decrease in water consumption. Seasonal crop response factor for onion crop was determined as 1.58, 1.48 and 1.54 during 2012, 2013 and average of both year (2012 &2013) respectively. The yield response factors developed in this study could be used in irrigation design and scheduling for onion in the study area.

Crop coefficients and yield response factors for onion (Allium Cepa. L) under deficit irrigation and mulch practices in Samaru, Nigeria

This report presents a study of crop coefficient (Kc) and yield response factors (Ky) for onion crop cultivated under deficit irrigation and different mulch covers in Samaru, Northern Nigeria. The field experiments were conducted at the irrigation fields of the Institute for Agricultural Research (IAR) irrigation field in 2008/2009 and 2009/2010 irrigation seasons using surface irrigation method. The experiments consisted of 16 treatments in each season. They comprised of four levels of water application depths (25, 50, 75, and 100% of weekly reference evapotranspiration (WRET)) and four levels of mulching (no-mulch, using rice straws, black and transparent polyethylene materials). Water applied per irrigation and soil moisture contents before and after irrigation was monitored throughout the seasons, while onion bulbs were harvested at the end of season and weighed. Average daily crop water use (crop consumptive use) were estimated from the soil moisture content using the soil moisture depletion method, while daily reference evapotranspiration (ETo) were computed from weather data using the FAO-Penman Montieth method. Crop coefficient values (Kc) were computed as the ratio of crop water use to ETo. The water stress coefficients (Ks) were computed by relating crop coefficient of the fully irrigated treatments to the deficit irrigated treatments. The yield response factor (Ky) were obtained by relating relative yield decreases to relative crop water use deficits. The study showed that crop water use of the onion crop decreased with increase in irrigation deficit. Applying water at 50% WRET reduced peak consumptive use of the onion crop by about 20%, while applying water at 25% WRET reduced crop water use by about 40%. Kc values of fully irrigated treatments ranged from 0.39 to 1.15, while Kc values of the deficit irrigated treatments varied from 0.24 to 1.13. Mulch materials did not significantly influence crop coefficient, but deficit irrigation did. Kc decreased with increase in water deficit with resultant water stress coefficients (Ks) ranging from 0.59 to 0.96. The relative yield decreases of the onion crop were proportionally greater with increase in evapotranspiration deficit for both mulched and no-mulch conditions. However, the proportional decrease in yield under the no-mulch condition was much higher than the mulched condition. Among the mulch materials, the proportional decrease in yield in the polyethylene materials were over 10% lower than the rice straw mulch. The Ky of the onion crop under no-mulch condition was 1.15, while Ky values for the mulched treatments were 1.13, 1.00 and 1.05 for rice straw-, white polyethylene-, and black polyethylene- mulch, respectively. The crop coefficients and yield response factors developed in this study are reliable as they had similar trends in two seasons, and could be used in irrigation design and scheduling for onion in the study area. Key words: Onion, deficit irrigation, mulching, crop coefficient (Kc), yield response factor (Ky), crop water use.

Assessing the Impact of Irrigation Return Flow on River Salinity for Colorado’s Arkansas River Valley

A river salinity model has been developed on the 21 major canal areas in the lower Arkansas River Basin in Colorado to address the impact of irrigation return flow on the river. The quantity of the return flow is predicted by constructing response functions for tailwater, canal leakage, and in-field deep percolation so that the spatial and temporal distribution of the return flow can be simulated. A groundwater table surface is generated using water table elevation data from 974 wells in the study area to establish flow paths and travel time for groundwater. The quality of the return flow is predicted by simulating the evapoconcentration process in the root zone soil in which hydro-chemical reactions occur and affect the salinity of in-field deep percolation water. The effects of shallow water table and high soil salinity on crops are simulated to account for the impacts that these two factors have on crop consumptive use. Model calibration and validation over a 192-month period from January 1986 to December 2001 show strong agreement between the observed and simulated values of river flow volume and river salinity. The simulation results show that irrigation return flows, including tailwater and groundwater return flows, significantly increase river quantity, but that groundwater return flow is also a major component of river salinity. There is significant seasonal fluctuation in river salinity and soil water salinity. The increase of soil water salinity from the soil surface to the bottom of the root zone is significant and will cause salt to be loaded to the groundwater. The simulation from 1991–2001 indicates that 20.9% of the 19,944 million m3 of irrigation water applied to Colorado’s lower Arkansas Valley becomes canal leakage, 22.5% is in-field deep percolation, and 22.9% becomes tailwater. This study assesses the effect of reducing agricultural irrigation on river salinity. Consider the scenario of three major canals stopping irrigation and transferring a portion of the curtailed water to off-basin cities with the remaining portion released to the river. The results indicate that, in order not to increase river salinity for downstream reaches, the portion of water transferred to cities should not exceed 50%.

Analysis of cotton water productivity in Fergana Valley of Central Asia

Cotton water productivity was studied in Fergana Valley of Central Asia during the years of 2009, 2010 and 2011. Data was collected from 18 demonstration fields (13 in Uzbekistan, 5 in Tajikistan). The demonstration field farmers implemented several improved agronomic and irrigation water management practices. The average values of crop yield, estimated crop consumptive use (ETa) and total water applied (TWA) for the demonstration sites were, respectively, 3700 kg/ha, 6360 m3/ha, and 8120 m3/ha. The range of values for TWA and ETa were, respectively, 5000 m3/ha to 12,000 m3/ha and 4500 m3/ha to 8000 m3/ha. A quadratic relationship was found between TWA and ETa. The average yield of the adjacent fields was 3300 kg/ha, whereas the average yield of cotton in Fergana Valley as a whole was 2900 kg/ha, indicating 28% and 14% increase in crop yield, respectively, from, demonstration fields and adjacent fields. There was no significant difference in crop yields between the wet years (2009 and 2010) and the dry year (2011), which is explained by the quadratic relationship between TWA and ETa. The water productivity values ranged from 0.35 kg/m3 to 0.89 kg/m3, indicating a significant potential for improving water productivity through agronomic and irrigation management interventions. The ratio of average ETa divided by average TWA gave an average application efficiency of 78% (some fields under-irrigated and some fields over-irrigated), the remaining 22% of water applied leaving the field. Since more than 60% of the water used for irrigation in Tajikistan and Uzbekistan is pumped from, even if all this 22% of water returns to the stream, substantial energy savings would accrue from improving the average application efficiency at field level. The range of values for TWA indicates the inequity in water distribution/accessibility. Addressing this inequity would also increase water productivity at field and project level.

한국의 농산물 가상수 산정

가상수는 농산물, 가공식품 또는 제품을 만들기 위해서 필요한 물의 총량을 의미한다. 우리나라의 곡물자급율은 27 %에 불과하며, 농산물 수입에 의한 가상수 수입이 다른 나라들에 비해 매우 큰 편에 속하며, 우리나라에 적합한가상수를 산정할 필요가 있다. 본 논문은 Chapagain과 Hoekstra가 제안한 방법을 이용하여, 1991년부터 2007년까지의 연간 농업 가상수 사용량(agricultural virtual water use, AWU)과 작물 1 톤을 생산하기 위하여 필요한 가상수량(virtual water content, VWC)을 산정하는 데 목적을 두고 있다. 가상수 사용량을 산정하기 위하여 44가지 작물에 대해 17년간의 작물 생산량과 재배면적 데이터를 수집하고, FAO Penman-Monteith식을 이용하여 작물소비수량을 산정하였다. 산정 결과를 살펴보면, 농업 가상수 사용량은 151억 <TEX>$m^3$</TEX>으로 산정되었고, 점차 그 양이 줄어드는 경향을 보였다. 작물 중 논벼가 가장 많은 양의 농업 가상수를 사용하였고, 전체 농업 가상수 사용량 중 75 %에 해당하는 연간 101억 <TEX>$m^3$</TEX>을 사용하였으며, 논벼를 1톤을 생산하기 위해 필요한 가상수량은 1600.1 <TEX>$m^3$</TEX>/ton으로 산정되었다. 작물을 생산하는 데 있어 필요한 가상수량이 큰 작물 종류는 채유종실이 가장 큰 값을 나타내었고, 엽채류 및 근채류가 가장 작은 것으로 나타났다. 산정된 원료 작물의 가상수량은 원료 작물과 가공 생산물의 중량비를 이용하여 농산물 가공품이나 축산물 등 2차 생산물의 가상수를 산정할 수 있다. 이에 따라 본 연구에서 산정된 결과는 우리나라의 농업 분야의 물발자국을 산정하는 데 있어서 기초자료로 활용할 수 있을 것으로 기대된다. Virtual water is defined as the volume of water required to produce a commodity or service. The degree of food self-sufficiency is currently about 27 % in South Korea, so that Korea is one of the largest net virtual water import countries for agricultural product, thus it is necessary to estimate suitable virtual water for South Korea. The objective of this paper is to quantify the agricultural virtual water use (AWU) and virtual water content (VWC) using the method suggested by Chapagain and Hoekstra during the period 1991-2007. To calculate the virtual water content, 44 different crop production quantity and harvested area data were collected for 17 years and FAO Penman-Monteith equation was adapted for computing crop consumptive use of water. As the results, AWU has been estimated at 15.1 billion <TEX>$m^3$</TEX> in average showing a tendency to decrease. Rice has the largest share in the AWU, consuming about 10.1 billion <TEX>$m^3$</TEX>/yr which is about 75 % of gross AWU, and the VWC is 1600.1 <TEX>$m^3$</TEX>/ton for paddy rice. The largest VWCs of crops are oilseed and tuber crop, and the smallest are leaf and root vegetables. The primary crop production VWC can be used for calculating the VWC of various secondary products using the contribution ratio, therefore the results of this study are expected to be used as basic data for national agricultural water footprint.

INFLUENCE OF DIFFERENT SUBSTRATES AND NUTRIENT SOLUTIONS ON THE YIELDS AND THE INCIDENCE OF ABIOTIC DISORDERS OF BROCCOLI

INFLUENCE OF DIFFERENT SUBSTRATES AND NUTRIENT SOLUTIONS ON THE YIELDS AND THE INCIDENCE OF ABIOTIC DISORDERS OF BROCCOLI

Determination of crop consumptive use and development of crop coefficient curve for summer groundnut

Determination of crop consumptive use and development of crop coefficient curve for summer groundnut

Modeling Reservoir Irrigation in Uncertain Hydrologic Environment

In a detailed model for reservoir irrigation taking into account the soil moisture dynamics in the root zone of the crops, the data set for reservoir inflow and rainfall in the command will usually be of sufficient length to enable their variations to be described by probability distributions. However, the potential evapotranspiration of the crop itself depends on the characteristics of the crop and the reference evaporation, the quantification of both being associated with a high degree of uncertainty. The main purpose of this paper is to propose a mathematical programming model to determine the annual relative yield of crops and to determine its reliability, for a single reservoir meant for irrigation of multiple crops, incorporating variations in inflow, rainfall in the command area, and crop consumptive use. The inflow to the reservoir and rainfall in the reservoir command area are treated as random variables, whereas potential evapotranspiration is modeled as a fuzzy set. The model's application is illustrated with reference to an existing single-reservoir system in Southern India.

NEW METHODS OF MODELING WATER AVAILABILITY FOR AGRICULTURE UNDER CLIMATE CHANGE: THE U.S. CORNBELT1

ABSTRACT: This paper reports on new methods of linking climate change scenarios with hydrologic, agricultural an water planning models to study future water availability for agriculture, an essential element of sustainability. The study is based on the integration of models of water supply and demand, and of crop growth and irrigation management. Consistent modeling assumptions, available databases, and scenario simulations are used to capture a range of possible future conditions. The linked models include WATBAL for water supply; CERES, SOYGRO, and CROPWAT for crop and irrigation modeling; and WEAP for water demand forecasting, planning and evaluation. These models are applied to the U.S. Cornbelt using forecasts of climate change, agricultural production, population and GDP growth.Results suggest that, at least in the near term, the relative abundance of water for agriculture can be maintained under climate change conditions. However, increased water demands from urban growth, increases in reservoir evaporation and increases in crop consumptive use must be accommodated by timely improvements in crop, irrigation and drainage technology, water management, and institutions. These improvements are likely to require substantial resources and expertise. In the highly irrigated basins of the region, irrigation demand greatly exceeds industrial and municipal demands. When improvements in irrigation efficiency are tested, these basins respond by reducing demand and lessening environmental stress with an improvement in system reliability, effects particularly evident under a high technology scenario. Rain‐fed lands in the Cornbelt are not forced to invest in irrigation, but there is some concern about increased water‐logging during the spring and consequent required increased investment in agricultural drainage. One major water region in the Cornbelt also provides a useful caveat: change will not necessarily be continuous and monotonic. Under one GCM scenario for the 2010s, the region shows a significant decrease in system reliability, while the scenario for the 2020s shows an increase.

Growth and yield responses of almond (Prunus amygdalus) to trickle irrigation

Growth and yield responses of developing almond trees (Prunus amygdalus, Ruby cultivar) to a range of trickle irrigation amounts were determined in 1985 through 1987 (the fifth through seventh year after planting) at the University of California's West Side Field Station in the semi-arid San Joaquin Valley. The treatments consisted of six levels of irrigation, ranging from 50 through 175% of the estimated crop evapotranspiration (ETc), applied to a clean-cultivated orchard using a line source trickle irrigation system with 6 emitters per tree. ETc was estimated as grass reference evapotranspiration (ET0) times a crop coefficient with adjustments based upon shaded area of trees and period during the growing season. Differential irrigation experiments prior to 1984 on the trees used in this study significantly influenced the initial trunk cross-section area and canopy size in the 50% ETc treatment and 125% ETc treatment. In these cases, treatment effects must be identified as relative effects rather than absolute. The soil of the experimental field was a Panoche clay loam (nonacid, thermic, Typic Torriorthents). The mean increase in trunk cross-sectional area for the 3-year period was a positive linear function (r 2 = 0.98) of total amounts of applied water. With increases in water application above the 50% ETc treatment, nut retention with respect to flower and fertile nut counts after flowering, was increased approximately 10%. In 1985 and 1987, the nut meat yields and mean kernel weights increased significantly with increasing water application from 50% to 150% ETc. Particularly in the higher water application treatments, crop consumptive use was difficult to quantify due to uncertainty in estimates of deep percolation and soil water uptake. Maintenance of leaf water potentials higher than −2.3 MPa during early nut development (March through May) and greater than −2.5 MPa the remainder of the irrigation season (through August) were positively correlated with sustained higher vegetative growth rates and higher nut yields.

ASSESSING POTENTIAL CLIMATE CHANGE IMPACTS ON WATER SUPPLY AND DEMAND IN SOUTHERN ALBERTA

The potential effects of climate warming due to increasing atmospheric levels of greenhouse gases are poorly defined. The predicted time frame for significant warming to occur is within the time frame of concern to most water resource planning and development. Some estimates must be made of the potential effects, so that managers and planners may adjust middle and long term policies and programs to deal with reasonable warming scenarios.This study presents a water balance assessment of supply and demand variations for the Oldman River basin in Alberta under a range of climate warming scenarios. The Oldman River basin, as a semi-arid region with intensive water-based development, is regarded as a region with a high-risk of adverse effects due to greenhouse warming. A crop consumptive use model is used to simulate the soil water demands for irrigated crops over the basin under five climate scenarios. Historical irrigation diversion demands are adjusted to reflect the increased crop demands under warming. Th...

Modelling Irrigation Water Consumptions and Needs. Application to River Ave Basin

The assessment of present and future water consumptions and needs for irrigation is of prime importance for water resources planning and management at basin level. As river Ave basin is being used as a Portuguese case study, a model has been developed for assessing present situation: agrometeorological data and crop systems and yield data provides the estimation of real evapotranspiration which can be used for a sequential water balance inside each homogeneous agricultural sub-region, so giving crop's consumptive use; estimated global irrigation efficiencies allows the calculation of total irrigation requirements; a final aggregation of results gives regional water consumption and needs. For forecasting future conditions another model has been developed: it uses the same agrometeorological and soil data but agricultural inputs are considered according scenarios of crop pattern evolution, development of agricultural technologies, crop yields increases and modernization of irrigation technologies. Results of application of such models are presented and discussed, showing their usefulness for coupling decisions on water and land use.

A REMOTE SENSING APPROACH FOR MODELING WATER RESOURCE USE1

ABSTRACTRemote sensing data combined with other spatially referenced data were used to predict water resource use in an irrigated area of Central Oregon. Crop type and irrigation method were determined using color infrared aerial photography and thermal infrared imagery, respectively. These data were combined with crop consumptive use and irrigation method application efficiency values to determine total water applied to a transect sample through the heart of the study area. This information, when integrated with data on canal leakage and storage reservoir seepage, allowed the researcher to predict total water use for the entire management unit. The model developed allowed the researcher to attain results accurate to within 92.0 percent of actual values, suggesting that predictive water use models which use such techniques have tremendous potential for providing water resource managers with near real‐time statistics required for making wise management decisions.

Irrigation Management—A Tool for Agribusiness

Irrigation Management is a tool whereby timely application of water can improve irrigation efficiencies. Irrigation Management has been made possible by adaptation of a computer program to the Jensen-Haise method of computing crop consumptive use. A daily soil moisture level balance is available by inserting climatic parameters for a computer printout at a specific time. These printouts are presented to irrigators and they can be shown when the next irrigation application will be required for a specific field. This will improve irrigation efficiencies because the water will be applied when the soil moisutre level is deficient. Data previously collected indicated that irrigators were unaware of soil mosture levels when applying water. Irrigation Management Services being conducted by Bureau of Reclamation personnel in Kansas and Wyoming are presented in this publication. Data for the Irrigation Management have been analyzed showing results during 1971. The future of Irrigation Management is exploited and incorporated with operation of irrigation systems.