Estimates Of Water Use Research Articles

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6–8 mm/day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm/day, METRIC 6 mm/day, and VISW 8 mm/day. For alfalfa, the ET values from TSEB were 8.0 mm/day, METRIC 5 mm/day, and VISW 6 mm/day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from −10% to +18%, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators—potential ET (ET ∘ ), FAO-56 ET, and USDA-SW gravimetric-ET— showed still greater deviations, up to 35% of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

ESTIMATION OF INSTANTANEOUS EVAPOTRANSPIRATION USING REMOTE SENSING BASED ENERGY BALANCE TECHNIQUE OVER PARTS OF NORTH INDIA

Abstract. Evapotranspiration (ET) is an essential element of the hydrological cycle and plays a significant role in regional and global climate through the hydrological circulation. Estimation and monitoring of actual crop evapotranspiration (ET) or consumptive water use over large-area holds the key for better water management and regional drought preparedness. In the present study, the remote sensing based energy balance (RS-EB) approach has been used to estimate the spatial variation of instantaneous evapotranspiration (ETinst). The (ETinst) is evaluated as the residual value after computing net radiation, soil heat flux and sensible heat flux using multispectral remote sensing data from Landsat-8 for the post-monsoon and summer season of 2016–2017 over the parts of North India. Cloud free temporal remote sensing data of October 12, 2016; November, 13, 2016; March 05, 2017 and May 24, 2017 were used as primary data for this study. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of (ETinst).

Model parameters of four important vegetable crops for improved water use and yield estimation

High-value vegetable crops are typically grown under irrigation to reduce production risk. For water resource planning it is essential to be able to accurately estimate water use of irrigated crops under a wide range of climatic conditions. Crop water use models provide a means to make water use and yield estimates, but need crop- and even cultivar-specific parameters. There is generally a lack of crop-specific model parameters for some important commercially grown vegetable crops, especially parameters determined over both summer and winter seasons. The experimental site used in this study was on the Steenkoppies Aquifer, a catchment under stress and an important vegetable production area in South Africa. Crop-specific growth parameters and water use for 4 selected high-value vegetable crops (beetroot, cabbage, carrots and broccoli) were measured over multiple seasons (two summers and one winter). These were used to parameterise the Soil Water Balance (SWB) generic crop growth model for both summer and winter seasons. In seasons where the same cultivar was planted, a single set of model parameters could be used to successfully simulate crop growth and water use. Results show that the amount of irrigation water required is dependent on season and rainfall, with broccoli having the lowest (1.8–2.7 kg m−3) and beetroot the highest (12.2–23.4 kg m−3) water productivity (WPFM), defined as fresh mass of marketable product per unit water consumed. The root crops had a greater harvest index (HIDM) than cabbage and broccoli. The parameters obtained expand the current database of SWB crop growth parameters for vegetables and can be used in a wide range of mechanistic simulation models to improve water management at field and catchment levels.

A comparative assessment of water use by Acacia longifolia invasions occurring on hillslopes and riparian zones in the Cape Agulhas region of South Africa

The detrimental impacts of invasive alien plants on ecosystems and water resources have raised concerns in arid and semi-arid countries like South Africa where the average precipitation is approximately 500 mm/yr, which is below the world average of around 860 mm/yr. Several studies have examined the effects of invasive alien plants such as the Australian Acacias on the water resources. However, few studies have quantified the differences in water use between hillslope and riparian Acacia longifolia invasions. A. longifolia is one of the aggressive invader species in South Africa even on hillslopes that contribute substantially to runoff generation. Therefore, the encroachment of invasive alien plants has the potential to reduce runoff, thereby adversely affecting the available water downstream. This paper aims to; 1) compare transpiration rates of A. longifolia growing on hillslopes and along riparian areas, 2) establish the key drivers for water use by this species, and 3) estimate the hydrological impacts of the invasions at the catchment scale in the Heuningnes catchment, in the Western Cape Province of South Africa. Transpiration by the trees was measured using the heat pulse velocity sap flow method. Automatic weather stations and soil moisture sensors were used to monitor weather and soil water content variations at each site. The results showed that, at the stand level the riparian A. longifolia transpired two times more water (∼596 mm/yr) than on the hillslope (∼242 mm/yr). During years with above average rainfall, the water use rates by the invasions was estimated to be ∼579 mm/yr on the hillslope and could be as much as ∼1348 mm/yr at the riparian site. Thus, the hypothesis that riparian trees use more water than invasions on non-riparian areas was accepted in this study. At the catchment scale (740 km2), the estimated water use by the invasions was 20.5 Mm3. Clearing of all the invasions in the study catchment is likely to make 17 Mm3/yr of water available. Hence the clearing of A. longifolia along the riparian corridors should be prioritised as this will lead to water savings at the catchment scale.

Water use in electricity generation for water-energy nexus analyses: The European case

With almost 40% of the global population suffering from water scarcity, the need to manage water resources is evidently urgent. While water and energy systems are intrinsically linked, the availability of comprehensive, integrated data sets across the domains of water and energy is generally lacking. As a result, estimated indicators representing volumes of water usage per unit of electricity or fuel produced are often required to analyse the water-energy nexus. In this paper, an “ensemble” of indicators is assembled representing water usage spanning different electricity-generation technologies based on previously published works in an attempt to depict the level or lack of detail in current large-scale energy-sector water-usage data. Based on these, the degree in which using such estimates is suitable for reproducing electricity-production water-usage at coarser spatio-temporal scales is assessed. The performance of the ensemble median/min/max as a predictor of water use is evaluated for the period from 1980 to 2015 using additional information about the constituents of the European energy system. Comparing with the reported values for 1980–2015, the median provides a skillful reproduction of historical yearly water use for the EU (EU28) as a whole. A further analysis for 2015 indicates that reasonable agreement is also seen at the country level. Thus, the results suggest that an “ensemble-based approach” has the potential to provide sturdy estimates of yearly water use by energy systems for analyses at both the country and regional levels.

Coupling stated preferences with a hydrological water resource model to inform water policies for residential areas in the Okanagan Basin, Canada

To improve the behavioural realism of a water resource model, this study coupled hydrologic modelling with stated preference research, thereby incorporating an empirical estimate of behavioural parameters to represent residents’ landscape decisions in an urban environment. The stated preference data came from a discrete choice experiment in which residents were asked to choose among several possible lawn plots — varying in size, turf variety, and aesthetic qualities. The discrete choice experiment also included subsidies for lawn replacement, and information about estimated water use and watering costs for each lawn choice. We prepared a behavioural model utilizing coefficients from a mixed logit model estimated from the stated preference data, and then coupled it with a water resources model of the Okanagan Basin using the Water Evaluation and Planning System. We then conducted a scenario analysis using the coupled socio-hydrological model to simulate the extent to which residents would adopt alternative lawns under varying incentives and subsequently computed corresponding changes in water demand. The results indicate that proposing alternative lawn configurations to residents and providing site-specific information about the potential for reduced watering costs, along with a small subsidy, could lead to considerable reduction of outdoor water use through voluntary adoption. Under a scenario in which the attributes of the suggested lawn configuration matched those most preferred by residents in the choice experiment, the suggested configuration was widely adopted in the Okanagan, but a scenario with a more extreme water conserving lawn configuration reduced overall outdoor water use by a greater amount even though the configuration was adopted by a smaller percentage of residents. This study illustrates the relationship between lawn preferences and water use and supports calls to integrate hydrological and social modelling in order to capture the complex interactions between human behaviour and water use.

Industrial water use, income, trade, and employment: environmental Kuznets curve evidence from 17 Taiwanese manufacturing industries.

This paper investigated the relationships between industrial water use, income, trade, and employment for 17 Taiwanese industries from 1998 to 2015. We explored cross-sectional dependent unit root, panel cointegration, and causality tests to estimate their long-term relationships and causal nexus. There existed long-term equilibrium relationships among the variables. The long-term elasticity estimates of industrial water use with respect to income, squared income, trade, and employment are 4.27, - 0.15, 0.22, and 0.92, respectively. The results do not confirm an inverted U-shaped environmental Kuznets curve. A unidirectional causal relationship is found between water use and income, and a bidirectional causal relationship is identified between water use and employment. Exports cause industrial water use. As expected, both employment and exports lead to income. Hence, policy makers should promote investment into water efficiency and water recycling. Various governments reward firms for water efficiency and lower consumption without negative long-term effects on economic growth.

Water Use Efficiency and Its Influencing Factors in China: Based on the Data Envelopment Analysis (DEA)—Tobit Model

Water resources are important and irreplaceable natural and economic resources. Achieving a balance between economic prosperity and protection of water resource environments is a major issue in China. This article develops a data envelopment analysis (DEA) approach with undesirable outputs by using Seiford’s linear converting method to estimate water use efficiencies for 30 provinces in China, from 2008–2016,and then analyzes the influencing factors while using a DEA-Tobit model. The findings show that the overall water use efficiency of the measured Chinese provinces, when considering sewage emissions as the undesirable output, is 0.582. Thus, most regions still need improvement. Provinces with the highest water efficiency are located in economically developed Eastern China. The spatial pattern of water use efficiency in China is consistent with the general pattern of regional economic development. This study implies that factors like export dependence, technical progress, and educational value have a positive influence on water use efficiency. Further, while industrial structure has had a negative impact, government intervention has had little impact on water use efficiency. These research results will provide a scientific basis for the government to make plans for water resource development, and it may be helpful in improving regional sustainable development.

Quantification of uncertainties in conifer sap flow measured with the thermal dissipation method.

Trees play a key role in the global hydrological cycle and measurements performed with the thermal dissipation method (TDM) have been crucial in providing whole-tree water-use estimates. Yet, different data processing to calculate whole-tree water use encapsulates uncertainties that have not been systematically assessed. We quantified uncertainties in conifer sap flux density (Fd ) and stand water use caused by commonly applied methods for deriving zero-flow conditions, dampening and sensor calibration. Their contribution has been assessed using a stem segment calibration experiment and 4yr of TDM measurements in Picea abies and Larix decidua growing in contrasting environments. Uncertainties were then projected on TDM data from different conifers across the northern hemisphere. Commonly applied methods mostly underestimated absolute Fd . Lacking a site- and species-specific calibrations reduced our stand water-use measurements by 37% and induced uncertainty in northern hemisphere Fd . Additionally, although the interdaily variability was maintained, disregarding dampening and/or applying zero-flow conditions that ignored night-time water use reduced the correlation between environment and Fd . The presented ensemble of calibration curves and proposed dampening correction, together with the systematic quantification of data-processing uncertainties, provide crucial steps in improving whole-tree water-use estimates across spatial and temporal scales.

Life cycle water use of a biomass-based pyrolysis polygeneration system in China

Water is essential for bioenergy production. Characterized as low carbon technology, crop-based bioenergy technology witnesses rapid development, inevitably putting pressure on global water resources. Therefore, it is crucial to carefully assess bioenergy technology’s overall impact on scarce water source for a sustainable bioenergy future. In this regard, this study aims to evaluate the life cycle water use of bioenergy from agricultural residues via the first pilot moving-bed pyrolysis polygeneration system in China. By using a tiered hybrid life cycle assessment, both direct and indirect water use are calculated. Results show life cycle water use is 3.89 L H2O/MJ and agricultural process dominates the total water use. Scenarios analysis shows different feedstock allocation ratios during agricultural production have striking influence on water use intensity. In addition, the choice of feedstock is another important influential factor. Under the 2020 Scenario in China’s 13th Five Year Plan, if all the bioenergy target could be met by polygeneration the estimated annual water use will be 6.6 billion m3, in magnitude up to around ten times the total water consumption in Denmark in 2013. In global scenario of potential feedstock available in 2060, the estimated water use for bioenergy produced by polygeneration will be 179–369 billion m3. Although the water use intensity of bioenergy production from agricultural residues by polygeneration is lower than that for other biomass conversion pathways, it is still higher than water intensity of conventional fossil energy products. Large-scale bioenergy production will have macroscopic effects on water demand. Finally, suggestions such as selecting high water-efficient biomass feedstock and reinforcing water-saving irrigation management to minimize water use in agriculture stage are proposed.

Farm field monitoring and irrigation automation using IOT

The Agricultural farming crops are produced in low qualitydue to lack of knowledge of farmers and crops destroyed by insects. To overcome that, many implemented factors are used. The factors can be temperature,soil,humidity,etc.,In biotechnology,some techniques are used withthe help of IoT. It is mainly used to increase the crops productivity in good quality.Existing related research works on sensor cloud have primarily focused on the challenges that wireless sensor network (WSN)-based applications. A direct estimate of water use by subsurface measurements of soil water content has been limited by the high cost of reliable soil moisture sensors. Using some sensors and techniques water can be irrigated automatically.IOT plays a vital role in smart farming.By using set of specified sensors,the irrigation man-agement can be done properly.The sensed data from the sensors and the irrigation controller are interfaced with Wi-Fi connection. In naive Bayes, by using decision making process the farmer can decide when and where to irrigate with the help of mobile application. An algo-rithm was developed with threshold values of temperature and soil moisture that was programmed into a microcontroller-based gateway to control water quantity.

Water source niche overlap increases with site moisture availability in woody perennials

Classical niche partitioning theory posits increased competition for and partitioning of the most limiting resource among coexisting species. Coexisting plant species may vary in rooting depth, reflecting niche partitioning in water source use. Our goal was to assess the soil water partitioning of woody plant communities across northern Arizona along an elevational moisture gradient using stem and soil water isotopes from two sampling periods to estimate the use of different water sources. We hypothesized that niche overlap of water sources would be higher and monsoon precipitation uptake would be lower at sites with higher moisture availability. Pairwise niche overlap of coexisting species was calculated using mixing model estimates of proportional water use for three sources. Across the moisture gradient, niche overlap increased with site moisture index (precipitation/potential evapotranspiration) across seasons, and site moisture index explained 37% of the variation in niche overlap of intermediate and deeper sources of water. Desert trees utilized more winter source water than desert shrubs, suggesting the partitioning of water sources between functional groups. However, seasonal differences in surface water use were primarily found at intermediate levels of site moisture availability. Our findings support classical niche partitioning theory in that plants exhibit higher overlap of water sources when water is not a limiting resource.

Water Use Efficiency in Rice Production: Implications for Climate Change Adaptation in the Vietnamese Mekong Delta

Water scarcity and competition in the Vietnamese Mekong Delta becomes a great matter of concern under the contexts of climate change and tributary dam construction in upstream countries. Moreover, water productivity or water use efficiency in rice production was quite low in the region due to free-rider problem. Therefore, the study was aimed at measuring water use efficiency at farm level and investigating the factors affecting water use efficiency. The study applied stochastic frontier analysis to estimate water use efficiency for 159 rice farmers in the upstream of the Vietnamese Mekong Delta. The study shows that the average water use efficiency was 18.81%, indicating that rice farmers did consume water very inefficiently. On the average, the rice farmers could reduce their water consumption about 81.19%, keeping their output level and other inputs constant. To improve water use efficiency, the study found that land accumulation or large-scaled production is essential.

Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two Source Energy Balance Model (TSEB) II—Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images

Dehesas are highly valuable agro-forestry ecosystems, widely distributed over Mediterranean-type climate areas, which play a key role in rural development, basing their productivity on a sustainable use of multiple resources (crops, livestock, wildlife, etc.). The information derived from remote sensing based models addressing ecosystem water consumption, at different scales, can be used by institutions and private landowners to support management decisions. In this study, the Two-Source Energy Balance (TSEB) model is analyzed over two Spanish dehesa areas integrating multiple satellites (MODIS and Landsat) for estimating water use (ET), vegetation ground cover, leaf area and phenology. Instantaneous latent heat (LE) values are derived on a regional scale and compared with eddy covariance tower (ECT) measurements, yielding accurate results (RMSDMODIS Las Majadas 44 Wm−2, Santa Clotilde RMSDMODIS 47 Wm−2 and RMSDLandsat 64 Wm−2). Daily ET(mm) is estimated using daily return interval of MODIS for both study sites and compared with the flux measurements of the ECTs, with RMSD of 1 mm day−1 over Las Majadas and 0.99 mm day−1 over Santa Clotilde. Distributed ET over Andalusian dehesa (15% of the region) is successfully mapped using MODIS images, as an approach to monitor the ecosystem status and the vegetation water stress on a regular basis.

Crop Evapotranspiration, Irrigation Water Requirement and Water Productivity of Maize from Meteorological Data under Semiarid Climate

Under the semiarid climate of the Southwest United States, accurate estimation of crop water use is important for water management and planning under conservation agriculture. The objectives of this study were to estimate maize water use and water productivity in the Four Corners region of New Mexico. Maize was grown under full irrigation during the 2011, 2012, 2013, 2014 and 2017 seasons at the Agricultural Science Center at Farmington (NM). Seasonal amounts of applied irrigation varied from 576.6 to 1051.6 mm and averaged 837.7 mm and the total water supply varied from 693.4 to 1140.5 mm. Maize actual evapotranspiration was estimated using locally developed crop coefficient curve and the tabulated United Nations Food and Agriculture Organization (FAO) crop coefficients, and from this maize water productivity was determined. Maize actual daily evapotranspiration (ETa) varied from 0.23 to 10.2 mm and the seasonal ETa varied with year and ranged from 634.2 to 697.7 mm averaging 665.3 mm by the local Kc curve, from 687.3 to 739.3 mm averaging 717.8 mm by the non-adjusted FAO Kc values, and from 715.8 to 779.6 mm averaging 754.9 mm with the FAO adjusted Kc values. Maize irrigation requirements varied from 758.4 to 848.3 mm and averaged 800.2 mm using the local developed Kc and varied from 835.5 to 935.6 mm and averaged 912.2 mm using FAO Kc. The net irrigation requirement varied from 606.8 to 678.6 using local Kc curve, and from 682.78 to 748.5 mm when adopting the FAO Kc values. Average irrigation requirement was 641 mm under the local Kc option and 730 mm under FAO Kc values option. Maize crop water use efficiency (CWUE) ranged from 1.3 to 1.9 kg/m3 and averaged 1.53 kg/m3, evapotranspiration water use efficiency (ETWUE) values were higher than CWUE and varied from 2.0 to 2.3 kg/m3, averaging 2.1 kg/m3. Maize irrigation water use efficiency (IWUE) was varied with years and averaged 1.74 kg/m3. There were strong relationships between maize CWUE and maize seasonal irrigation amounts of IWUE and the seasonal irrigation amounts with R2 of 0.97 and 0.92, respectively. Maize CWUE increased linearly with maize IWUE with a coefficient of determination R2 of 0.99, while IWUE showed a strong quadratic relationship with ETWUE (R2 = 0.94). The results of this study can be used as a guideline for maize water management under the semiarid conditions in northwestern New Mexico and other locations with similar climate and management conditions. Irrigation requirements for maize should be adjusted to the local meteorological conditions for optimizing maize irrigation requirement and improving maize water productivity.

Spatial Patterns of Development Drive Water Use

AbstractWater availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.

Do household surveys estimate tap water use accurately? Evidence from pressure-sensor based estimates in Coimbatore, India

Abstract Quantifying domestic water use at the household scale is crucial for any policy interventions towards ensuring adequate, equitable and safe water access. In developing country contexts, piped water supply is often one of several sources from which households access water and this is often unmetered. The most common approach to quantifying household water use from multiple sources is through household surveys. But there is no evidence that household surveys accurately estimate water use. This study utilized high-resolution pressure-sensor data as a reference to evaluate the effectiveness of conventional household survey methods through a sample of 82 households in Coimbatore city in South India. The pressure sensors produced detailed, continuous and accurate information on all sources of water accessed through the household storage infrastructure, but they were expensive and intrusive. Compared with pressure-sensor derived estimates of tap water use, household surveys alone fared very poorly. However, household surveys and well-designed water diaries of supply and pumping, coupled with simple one-time field measurements, emerged as a valid approach to quantifying household water use from taps under multiple source dependence.

Applicability of cadastral data to support the estimation of water use in private swimming pools

Studies addressing outdoor water use in residential areas rely on surveying methods, the manual digitization of aerial imagery and remote sensing-based approaches to estimate water consumption by different land uses. Publicly available cadastral data potentially offer a more efficient avenue for researchers to obtain information on land use parameters, but few assessments of their quality and applicability have been conducted. A sample of three local areas, encompassing more than 12,000 plots in low-density residential areas and representative of different socioeconomic profiles, were selected in the metropolitan area of Barcelona and along the Mediterranean coast of Catalonia. The reliability and sufficiency of the Spanish cadastre were assessed for the identification of swimming pools against the ground truth evidence provided by high-resolution aerial imagery and the support of object-based image analysis. Omission and commission errors of the cadastre were measured, the delimitation of digitized pool areas was statistically tested for accuracy, and the condition of the facilities was compared in the three study sites. The results do not support the use of the Spanish cadastre as a source of data for uses requiring a high level of detail and completeness. Plot size, socioeconomic and cultural factors affect pool size, the frequency of empty pools and the installation of pool covers in different communities. The study demonstrates that researchers need to complement cadastral data with qualitative information about the condition of the swimming pools to successfully estimate their cumulative water consumption at larger scales. Implications for water use research and spatial planning are discussed.

Productivity and Water Use Efficiency of Sorghum [Sorghum bicolor (L.) Moench] Grown under Different Nitrogen Applications in Sudan Savanna Zone, Nigeria

Nitrogen (N) is an essential nutrient for sorghum growth and development but often becomes limiting due to low availability and loss. The effects of N fertilization on water use efficiency (WUE) and physiological and yield traits of sorghum were investigated in two locations over two cropping seasons (2014 and 2015) in the Sudan Savanna zone of Nigeria. Three sorghum varieties were evaluated under six (6) N-levels (0, 20, 40, 60, 80, and 100 kg ha−1) at a constant phosphorus and potassium level of 30 kg ha−1. Results showed that N increased grain yield by 35–64% at the Bayero University Kano (BUK) and 23–78% at Minjibir. The highest mean grain yield in the N-fertilizer treatments (2709 kg ha−1 and 1852 kg ha−1 at BUK and Minjibir, resp.) was recorded at 80 kg N ha−1. ICSV400 produced the highest mean grain yields (2677 kg ha−1 and 1848 kg ha−1 at BUK and Minjibir, resp.). Significant differences were observed among the N-levels as well as among the sorghum varieties for estimated water use efficiency (WUE). The highest mean value coincided with the highest mean grain yield at an optimum application rate of 80 kg ha−1. N-fertilizer treatments increased WUE by 48–55% at BUK and increased WUE by 54–76% at Minjibir over control treatment. Maturity and physiological trait have a significant effect on WUE. The extra early maturing variety (ICSV400) recorded the highest mean WUE while late maturing variety (CSR01) recorded the lowest WUE.

Water Supply Rates for Recirculating Evaporative Cooling Systems

Abstract. Evaporative cooling (EC) is an important tool to reduce heat stress in animal housing systems. Expansion of ventilation capacity in tunnel ventilated poultry facilities has resulted in increased water demand for EC systems. As water resources become more limited and costly, proper planning and design of water supply systems is critical to ensure demand is met during periods of heat stress which increase EC use and bird water consumption. Few estimates of EC water use in animal housing applications are available in the literature and available estimates are geographically limited or rely on extreme weather events. The goal of this analysis was to provide guidance for EC water supply design to accommodate estimates of peak demand, rather than average consumption rates. Keywords: Ventilation, Broiler house, Water conservation, Housing design.