Academic literature on the topic 'Crop water budget'
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Journal articles on the topic "Crop water budget"
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CHAUDHARI, SHIV SHANKER, SUSAMA SUDHISHIRI, MANOJ KHANNA, ANCHAL DASS, K. G. ROSIN, RANJAN BHATTACHARYA, and RAGHAV MAURYA. "Water budgeting in major rabi crops under surface irrigation in Western Indo-Gangetic Plains." Indian Journal of Agricultural Sciences 90, no. 11 (December 16, 2020): 2185–91. http://dx.doi.org/10.56093/ijas.v90i11.108592.
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A water budget confers the relationship between input, output and changes in the amount of water at an individual farm level to the watershed level depending upon point of interest. Basic components of water budgets are precipitation, evapotranspiration, change in soil moisture storage, deep percolation and runoff. However, non-availability of water balance parameter is the main problem for achieving the more crop per drop. Therefore, the current study was undertaken at ICAR-Indian Agricultural Research Institute, New Delhi farm (Mid-block, MB) during rabi 2016-17 to study the water budget of different major rabi crops (wheat, mustard, chickpea) under surface irrigation. Water budget components like soil moisture were measured by gravimetric method periodically, and daily crop-evapotranspiration (ETc) and stage-wise effective rainfall (Pe) for the test crops were estimated using FAO-CROPWAT- 8.0 model. Irrigation scheduling was done on the basis of soil moisture depletion method and total volume of water applied measured through star flow meter. The total volume of irrigation water applied during the entire crop period was 337.75, 211.54 mm and 182.90 mm, for wheat, mustard and chickpea, respectively. The results revealed that both in late- and timely - sown mustard (MB-3A-1 and 3A-2), chickpea (MB-9-A) and wheat crops (MB-3A-3, 6-A and 12-A), the highest ETc was recorded during mid-season stage (i.e. 82.90, 79.50, 94.07, 126.04, 114.02, 132.61 mm, respectively). The deep- percolation losses varied from 29.3-31.8 % for sandy loam soil to 40.2-42.2 % for clay loam soil under different crops due to larger amount of irrigation water applied in clay soil. These water budgeting parameters are location and crop specific and so to be estimated for crops, seasons and regions.
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Sarpong, E. Ofori. "Water budget characteristics, availability of water periods and crop production in Ghana." JOURNAL OF THE GEOGRAPHICAL ASSOCIATION OF TANZANIA 27 (July 7, 2021): 1–22. http://dx.doi.org/10.56279/jgat.v27i.57.
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Sanders, D. C. "Drip-irrigation System Component and Design Considerations for Vegetable Crops." HortTechnology 2, no. 1 (January 1992): 25–27. http://dx.doi.org/10.21273/horttech.2.1.25.
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The following should be considered when installing and maintaining a drip irrigation system for vegetable crops: water source (surface or ground water); water quality (salinity, particulate matter, contaminants); size of area to be irrigated; pump size; soil type; drip tape type; crop to be irrigated; management skill of the operator; automation needs; water meter and budget. Use a professional designer.
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MALL, R. K., B. R. D. GUPTA, and K. K. SINGH. "Application of SP AW model parameters - optimum sowing date and water stress to explain wheat yield variability." MAUSAM 52, no. 3 (January 11, 2022): 567–74. http://dx.doi.org/10.54302/mausam.v52i3.1727.
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The Soil-Plant-Atmosphere- Water (SPA W) model has been calibrated and validated using field experiment data from 1991-92 to 1993-94 for wheat crop at Varanasi district. Long-term (1973-74 to 1995-96) daily weather data were combined with general observation of wheat growth and soils to provide daily water budgets for 23 years. The model was calibrated with one year detailed crop growth characteristics and soil water observations and validated with another year soil water observations. The daily-integrated water stress index (WSI) values at the end of crop season correlated quite well with observed grain yield in this region.
The water budget analysis shows a distinct optimum sowing period from 5th to 25th November and an optimum sowing date on 15th November with minimal water stress index. These results demonstrate the potential of SPA W model for planning irrigation scheduling and water management for wheat crop in this region.
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Zamora Re, Maria I., Sagarika Rath, Michael D. Dukes, and Wendy Graham. "Water and Nitrogen Budget Dynamics for a Maize-Peanut Rotation in Florida." Transactions of the ASABE 63, no. 6 (2020): 2003–20. http://dx.doi.org/10.13031/trans.13916.
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HighlightsDSSAT simulations of final N uptake, biomass, and yield for a maize-peanut rotational field experiment with three irrigation treatments and three N fertilizer rates had good performance for the irrigated treatments (average nRMSE of 9%) but greater error for the rainfed treatments (average nRMSE of 15%).Experiments and DSSAT simulations demonstrated that N fertilizer and irrigation applications were reduced by 26% and 60%, respectively, when using a 247 kg N ha-1 fertilizer rate and a sensor-based irrigation schedule rather than conventional practices of 336 kg N ha-1 and a calendar-based irrigation method, with no impact on yield.Simulations demonstrated that N leaching during the crop rotation was reduced by 37% when an N fertilizer rate of 247 kg N ha-1 and sensor-based irrigation scheduling were used versus conventional practices.Soil N increased (=15 mg kg-1) when maize and peanut residues decayed and then leached during the fallow season. Cover or cash crops planted immediately after the maize and peanut harvests have potential to take up this N and reduce leaching.Abstract. Nitrogen (N) is an essential element for crop growth and yield; however, excessive N applications not taken up by crops can result in N leaching from the root zone, increasing N loads to waterbodies and leading to a host of environmental problems. The main objective of this study was to simulate water and N balances for a maize-peanut (Zea mays L. and Arachis hypogaea L.) rotational field experiment with three irrigation treatments and three N fertilizer rates. The irrigation treatments consisted of mimicking grower irrigation practices in the region (GROW), using soil moisture sensors to schedule irrigation (SMS), and non-irrigated (NON). The N fertilizer rates were low, medium, and high (157, 247, and 336 kg N ha-1, respectively) for maize with a constant 17 kg ha-1 for all peanut treatments. DSSAT maize genetic coefficients were calibrated using the SMS-high treatment combination under the assumption of no water or N stress. The other eight treatment combinations were used as independent data for model validation of the crop coefficients. All soil hydrologic parameters were specified based on measured values, and default DSSAT peanut genetic coefficients were used with no calibration. For the irrigated treatments, DSSAT models had good performance for N uptake, biomass, and yield (average nRMSE of 8%) and moderate performance for soil water content (average nRMSE of 18%). Soil nitrate RMSE was 21% lower than the standard deviation of the observed data (5.8 vs. 7.2 mg kg-1). For the rainfed treatments, DSSAT had greater error (average nRMSE of 15% for N uptake, biomass, and yield, and average nRMSE of 31% for soil water). Soil nitrate RMSE was 11% greater than the standard deviation of the observed data (8.0 vs. 7.2 mg kg-1), and nRMSE was >30% during the crop rotation. Simulations estimated that N leaching over the crop rotation was reduced by 24% on average when using the 247 kg N ha-1 fertilizer rate compared to 336 kg N ha-1 across the irrigation treatments. Furthermore, N leaching was reduced by 37% when using SMS to schedule irrigation and the 247 kg N ha-1 fertilizer rate for maize and 17 kg N ha-1 for peanut compared to conventional practices (GROW and 336 kg N ha-1 for maize and 17 kg N ha-1 for peanut). Moreover, this management practice reduced N fertilizer use by 26% and irrigation water use by up to 60% without negative impacts on yield. Observed and simulated soil N increased during maize and peanut residue decay, with simulations estimating that this soil N would leach below the root zone during the fallow season. This leaching could potentially be reduced if a cover crop or cash crop were planted between the maize and peanut crops to take up the mineralized N. Keywords: Agricultural best management practices, Bare fallow, BMPs, Maize-peanut rotation, N balance, N fertilization, N leaching, Sandy soils, Sensor-based irrigation scheduling, Water balance.
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Hirwa, Hubert, Qiuying Zhang, Fadong Li, Yunfeng Qiao, Simon Measho, Fabien Muhirwa, Ning Xu, et al. "Water Accounting and Productivity Analysis to Improve Water Savings of Nile River Basin, East Africa: From Accountability to Sustainability." Agronomy 12, no. 4 (March 28, 2022): 818. http://dx.doi.org/10.3390/agronomy12040818.
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Complete water accounting (WA) and crop water productivity (CWP) analysis is crucial for evaluating water use efficiency (WUE). This study aims to evaluate the contributions of hydro-meteorological factors to the changes of WA and CWP and subsequent WUE based on the data from 2009–2020 in the Nile River Basin (NRB), East Africa (EA). The Mann-Kendall (MK) statistical test and Sen’s slope estimator were applied to detect the trends of climatic factors, and the AquaCrop model was used to simulate the crop yields in response to water balance and consumption based on crop physiological, soil water, and salt budget concepts. For the years 2012 and 2019, the mean of climatic water deficit P − ETa was 71.03 km3 and 37.03 km3, respectively, which was expected to rise to ~494.57 km3 by 2050. The results indicated that the basin water budget was unbalanced due to the coupled impact of year-to-year hot and dry conditions and increase in water abstraction, an indication of water deficit or stress. CWP and WUE increased during the study period with different changing patterns. CWP was also found to correlate to the yield of major crops (p-value > 0.05). It was concluded that climatic factors influenced the crop yield, CWP, and WUE in the study area. Thus, the improvement of CWP and WUE should rely on advanced water-saving innovations. The findings of this study could help water managers to improve water productivity by focusing on water account potentials and creating regional advantages by deploying water in combination with surplus flow from upstream to downstream consumption.
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Sepaskhah, A. R., Sh Rezaee-pour, and A. A. Kamgar-Haghighi. "Water Budget Approach to quantify Cowpea Yield using Crop Characteristic Equations." Biosystems Engineering 95, no. 4 (December 2006): 583–96. http://dx.doi.org/10.1016/j.biosystemseng.2006.08.003.
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Hartz, T. K. "Water Management in Drip-irrigated Vegetable Production." HortTechnology 6, no. 3 (July 1996): 165–67. http://dx.doi.org/10.21273/horttech.6.3.165.
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Many factors influence appropriate drip irrigation management, including system design, soil characteristics, crop and growth stage, and environmental conditions. The influences of these factors can be integrated into a practical, efficient scheduling system that determines quantity and timing of drip irrigation. This system combines direct soil moisture measurement with a water budget approach using evapotranspiration estimates and crop coefficients.
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Pradhan, Deepa, and Ram Ranjan. "Do Institutional Programs Aimed at Groundwater Augmentation Affect Crop Choice Decisions under Groundwater Irrigation? Empirical Evidence from Andhra Pradesh, India." Water Economics and Policy 01, no. 02 (June 2015): 1550002. http://dx.doi.org/10.1142/s2382624x15500022.
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Crop choices made by farmers can make important contributions toward the sustainable management of groundwater resources in drought prone regions. However, farmers who would tend to maximize profits under normal circumstances face a trade-off between the choices of risky but more profitable high water intensive (HWI) crops on one hand and the low risk but less profitable low water intensive (LWI) and drought resistant (DR) crops on the other. In drought-hit regions of South India, institutional programs, such as crop water budgeting and farmer schools, have been promoted to provide support and information to the farmers in helping them make judicious crop choices. A multivariate probit (MVP) analysis reveals that crop water budget exercise and farmer field school participation, in fact, are positively associated with HWI crop choices, whereas participation in soil moisture conservation efforts is positively associated with growing LWI and DR crops. Our findings indicate that the objective of groundwater augmentation through institutional interventions that are solely based on educating and training farmers have been ineffective and have even been providing perverse incentives, and that there is a need for adding water extraction compliance components to such support programs in order for them to be efficacious.
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Elamri, Y., B. Cheviron, J. M. Lopez, C. Dejean, and G. Belaud. "Water budget and crop modelling for agrivoltaic systems: Application to irrigated lettuces." Agricultural Water Management 208 (September 2018): 440–53. http://dx.doi.org/10.1016/j.agwat.2018.07.001.
Full textDissertations / Theses on the topic "Crop water budget"
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Moberly, Joseph. "Crop water production functions for grain sorghum and winter wheat." Thesis, Kansas State University, 2016. http://hdl.handle.net/2097/32560.
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Master of ScienceAgronomy
Robert Aiken
Xiaomao Lin
Productivity of water-limited cropping systems can be reduced by untimely distribution of water as well as cold and heat stress. The research objective was to develop relationships among weather parameters, water use, and grain productivity to produce production functions to forecast grain yields of grain sorghum and winter wheat in water-limited cropping systems. Algorithms, defined by the Kansas Water Budget (KSWB) model, solve the soil water budget with a daily time step and were implemented using the Matlab computer language. The relationship of grain yield to crop water use, reported in several crop sequence studies conducted in Bushland, TX; Colby, KS and Tribune, KS were compared against KSWB model results using contemporary weather data. The predictive accuracy of the KSWB model was also evaluated in relation to experimental results. Field studies showed that winter wheat had stable grain yields over a wide range of crop water use, while sorghum had a wider range of yields over a smaller distribution of crop water use. The relationship of winter wheat yield to crop water use, simulated by KSWB, was comparable to relationships developed for four of five experimental results, except for one study conducted in Bushland that indicated less crop water productivity. In contrast, for grain sorghum, experimental yield response to an increment of water use was less than that calculated by KSWB for three of five cases; for one study at Colby and Tribune, simulated and experimental yield response to water use were similar. Simulated yield thresholds were consistent with observed yield thresholds for both wheat and sorghum in all but one case, that of wheat in the Bushland study previously mentioned. Factors in addition to crop water use, such as weeds, pests, or disease, may have contributed to these differences. The KSWB model provides a useful analytic framework for distinguishing water supply constraints to grain productivity.
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Spank, Uwe, Barbara Köstner, Uta Moderow, Thomas Grünwald, and Christian Bernhofer. "Surface Conductance of Five Different Crops Based on 10 Years of Eddy-Covariance Measurements." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-214307.
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The Penman-Monteith (PM) equation is a state-of-the-art modelling approach to simulate evapotranspiration (ET) at site and local scale. However, its practical application is often restricted by the availability and quality of required parameters. One of these parameters is the canopy conductance. Long term measurements of evapotranspiration by the eddy-covariance method provide an improved data basis to determine this parameter by inverse modelling. Because this approach may also include evaporation from the soil, not only the ‘actual’ canopy conductance but the whole surface conductance (gc) is addressed. Two full cycles of crop rotation with five different crop types (winter barley, winter rape seed, winter wheat, silage maize, and spring barley) have been continuously monitored for 10 years. These data form the basis for this study. As estimates of gc are obtained on basis of measurements, we investigated the impact of measurements uncertainties on obtained values of gc. Here, two different foci were inspected more in detail. Firstly, the effect of the energy balance closure gap (EBCG) on obtained values of gc was analysed. Secondly, the common hydrological practice to use vegetation height (hc) to determine the period of highest plant activity (i.e., times with maximum gc concerning CO2-exchange and transpiration) was critically reviewed. The results showed that hc and gc do only agree at the beginning of the growing season but increasingly differ during the rest of the growing season. Thus, the utilisation of hc as a proxy to assess maximum gc (gc,max) can lead to inaccurate estimates of gc,max which in turn can cause serious shortcomings in simulated ET. The light use efficiency (LUE) is superior to hc as a proxy to determine periods with maximum gc. Based on this proxy, crop specific estimates of gc,maxcould be determined for the first (and the second) cycle of crop rotation: winter barley, 19.2 mm s−1 (16.0 mm s−1); winter rape seed, 12.3 mm s−1 (13.1 mm s−1); winter wheat, 16.5 mm s−1 (11.2 mm s−1); silage maize, 7.4 mm s−1 (8.5 mm s−1); and spring barley, 7.0 mm s−1 (6.2 mm s−1).
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Spank, Uwe, Barbara Köstner, Uta Moderow, Thomas Grünwald, and Christian Bernhofer. "Surface Conductance of Five Different Crops Based on 10 Years of Eddy-Covariance Measurements." Schweizerbart Science Publishers, 2016. https://tud.qucosa.de/id/qucosa%3A29981.
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The Penman-Monteith (PM) equation is a state-of-the-art modelling approach to simulate evapotranspiration (ET) at site and local scale. However, its practical application is often restricted by the availability and quality of required parameters. One of these parameters is the canopy conductance. Long term measurements of evapotranspiration by the eddy-covariance method provide an improved data basis to determine this parameter by inverse modelling. Because this approach may also include evaporation from the soil, not only the ‘actual’ canopy conductance but the whole surface conductance (gc) is addressed. Two full cycles of crop rotation with five different crop types (winter barley, winter rape seed, winter wheat, silage maize, and spring barley) have been continuously monitored for 10 years. These data form the basis for this study. As estimates of gc are obtained on basis of measurements, we investigated the impact of measurements uncertainties on obtained values of gc. Here, two different foci were inspected more in detail. Firstly, the effect of the energy balance closure gap (EBCG) on obtained values of gc was analysed. Secondly, the common hydrological practice to use vegetation height (hc) to determine the period of highest plant activity (i.e., times with maximum gc concerning CO2-exchange and transpiration) was critically reviewed. The results showed that hc and gc do only agree at the beginning of the growing season but increasingly differ during the rest of the growing season. Thus, the utilisation of hc as a proxy to assess maximum gc (gc,max) can lead to inaccurate estimates of gc,max which in turn can cause serious shortcomings in simulated ET. The light use efficiency (LUE) is superior to hc as a proxy to determine periods with maximum gc. Based on this proxy, crop specific estimates of gc,maxcould be determined for the first (and the second) cycle of crop rotation: winter barley, 19.2 mm s−1 (16.0 mm s−1); winter rape seed, 12.3 mm s−1 (13.1 mm s−1); winter wheat, 16.5 mm s−1 (11.2 mm s−1); silage maize, 7.4 mm s−1 (8.5 mm s−1); and spring barley, 7.0 mm s−1 (6.2 mm s−1).
Books on the topic "Crop water budget"
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Tarasovich, Kirsta Bogdan, Orlovskiĭ N. S, and Chȯller instituty (Tu̇rkmenistan SSR ylymlar akademii͡a︡sy), eds. Osobennosti vodno-teplovogo rezhima i agroprognozov v Turkmenistane: Sbornik stateĭ. Ashkhabad: Ylym, 1988.
Find full textBook chapters on the topic "Crop water budget"
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SCHEPERS, J. S., and R. H. FOX. "Estimation of N Budgets for Crops." In Nitrogen management and ground water protection, 221–46. Elsevier, 1989. http://dx.doi.org/10.1016/b978-0-444-87393-4.50014-9.
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Gage, Stuart H. "Climate Variability in the North Central Region: Characterizing Drought Severity Patterns." In Climate Variability and Ecosystem Response in Long-Term Ecological Research Sites. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195150599.003.0010.
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This chapter examines the spatial and temporal variability and patterns of climate for the period 1972–1991 in the North Central Region of North America (NCR). Since the mid-1970s, climate has become more variable in the region, compared to the more benign period 1950–1970. The regional perspective presented in this chapter characterizes the general climatology of the NCR from 1972 to 1991 and compares the climate to a severe drought that occurred in 1988. This one-year drought was one of the most substantial in the region’s recent history, and it had a significant impact on the region’s agricultural economy and ecosystems. Petersen et al. (1995) characterize the 1988 drought with respect to solar radiation, and Zangvil et al. (2001) consider this drought from the perspective of a large-scale atmosphere moisture budget. A major reason for the seriousness of the drought in 1988 was the fact that May and June were unusually dry and hot (Kunkel and Angel 1989). Drought is defined as a condition of moisture deficit sufficient to adversely affect vegetation, animals, and humans over a sizeable area (Warwick 1975). The condition of drought may be considered from a meteorological, agricultural, and hydrologic perspective. Meteorological drought is a period of abnormally dry weather sufficiently prolonged to a point where the lack of water causes a serious hydrologic imbalance in the affected area (Huschke 1959). Agricultural drought is a climatic digression involving a shortage of precipitation sufficient to adversely affect crop production or the range of production (Rosenberg 1980). Hydrologic drought is a period of below-average water content in streams, reservoirs, groundwater aquifers, lakes, and soils (Yevjevich et al. 1977). All of these drought conditions are mutually linked. The objectives of this chapter are to (1) address the issues of climatic spatial scale to quantify variability of climate in the NCR, (2) examine the characteristics of the 1988 drought as it relates to characteristics of an ecoregion, (3) illustrate a means to quantify drought through a potential plant stress index, and (4) examine the link of regional drought to ecosystem processes. This analysis will provide background and methodology for ecologists, agriculturalists, and others interested in spatial and temporal characterization of climate patterns within large geographic regions.
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Michel, Janet, and Marcel Tanner. "Poverty Is Not Poverty: The Reality on the Ground Including the Rural-Urban Divide and How We Can Turn the Tide on NCDs." In Lifestyle and Epidemiology - Poverty and Cardiovascular Diseases a Double Burden in African Populations [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.95901.
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Cardiovascular diseases (CVDs) tend to occur in younger sub-Saharan African (SSA) populations, about 20 years earlier as compared to high income countries (HIC). Weak health systems and infrastructure, scarce cardiac professionals, skewed budget away from non-communicable diseases (NCD), high treatment costs and reduced access to health care. On top of that, hypertension diagnosis, treatment and control are low, less than 40%, less than 35% and 10-20% respectively. SSA has 23% of the worlds rheumatic disease, while 80% of CVD deaths occur in low to middle income countries. Poverty is not poverty. The rural–urban divide is one reality that has to be acknowledged among others, particularly in Africa. Being poor, while owning land and having the possibility to grow crops and rear livestock, goats and chickens, is different from being an unemployed young man or young woman, renting one room, in a crowded township with dilapidated infrastructure, intermittent or untreated water and surrounded by leaking sewers. Understanding the dynamics in different contexts is important for us to identify and address the different challenges affecting health in general, and heart health of people in these contexts in particular. For example, the detection, treatment and control rates of hypertension are higher in semi-urban as compared to rural areas. Detection rates for both men and women are suboptimal particularly in rural areas. Diet, sedentary life, loneliness and stress, insecure environments rather and unsafe places to walk are issues more common in urban settings. The conditions in which people are born, live, grow and work affect their health. The rural conditions are very different from the urban ones. The quality of air, access and types of food, stress levels, isolation, loneliness and fear not to mention violence, vary. All these factors affect heart health in one way or the other. Addressing heart health issues therefore ought to be context specific. The burdens might be treble or more for some -economically, environmentally (climate change, political instability), socially and historically-apartheid and colonialism.
Conference papers on the topic "Crop water budget"
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GRYBAUSKIENE, Vilda, and Gitana VYČIENĖ. "EVAPOTRANSPIRATION-BASED IRRIGATION SCHEDULING FOR PICEA ABIES (SPRUCE) SEEDLINGS." In Rural Development 2015. Aleksandras Stulginskis University, 2015. http://dx.doi.org/10.15544/rd.2015.062.
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The water balance of agro ecological systems is a key parameter for most physical and physiological processes with the system soil–crop–climate. Therefore it is of great importance to calculate the water budget parameters in the required scale. The field study was conducted in the period of 2002–2005. Seedlings were planted in Irrigation engineering department experimental fields at the Lithuanian University of Agriculture. Seedlings were grown under standard nursery cultural practices until being transplanted into new fields in mid April 2002 and 2004. The research site contains evaporators and 8 lysimeters in which spruce seedlings were grown and studied. Lysimeters amount 42 m2 and 30 m2. At 2002, field No.1 was irrigated 8 times, irrigation norm was 250 m3 ha-1 and seedling got 2000 m3 ha-1 water. Field No.2 was irrigated 6 times, irrigation norm – 1500 m3 ha-1. In 2003 fields No. 1 and No. 2 were irrigated 4 times and seedlings got 1000 m3 ha-1 water. At 2004, field No.1 was irrigated 8 times, irrigation norm was 250 m3 ha-1 and seedling got 2000 m3 ha-1 water. Field No.2 was irrigated 6 irrigation norm – 1500 m3 ha-1. The total evapotranspiration of the first year seedlings planted in the field No.1 in 2004 made up 323 mm. The total evapotranspiration of the seedlings growing in variant No. 2 was 307 mm in 2004 and it is by 16 mm less as compared to variant No.1.
Reports on the topic "Crop water budget"
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Hurlow, Hugh A., Paul C. Inkenbrandt, and Trevor H. Schlossnagle. Hydrogeology, Groundwater Chemistry, and Water Budget of Juab Valley, Eastern Juab County, Utah. Utah Geological Survey, October 2022. http://dx.doi.org/10.34191/ss-170.
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Juab Valley is a north-south-trending basin in the eastern Basin and Range Province. Juab Valley is bounded on the east by the Wasatch normal fault and the Wasatch Range and San Pitch Mountains, bounded on the west by Long Ridge and the West Hills. Juab Valley is at the southern end of Utah’s Wasatch Front, an area of projected rapid population growth and increased groundwater use. East-west-trending surface-water, groundwater, and water-rights boundaries approximately coincide along the valley’s geographic midline at Levan Ridge, an east-west trending watershed divide that separates the north and south parts of Juab Valley. The basin includes, from north to south, the towns of Mona, Nephi, and Levan, which support local agricultural and light-industrial businesses. Groundwater use is essential to Juab Valley’s economy. The Juab Valley study area consists of surficial unconsolidated basin-fill deposits at lower elevations and various bedrock units surrounding and underlying the basin-fill deposits. Quaternary-Tertiary basin-fill deposits form Juab Valley’s primary aquifer. Tertiary volcanic rocks underlie some of the basinfill deposits and form the central part of Long Ridge on the northwest side of the valley. Paleozoic carbonate rocks that crop out in the Mount Nebo area of the Wasatch Range, which receives the greatest average annual precipitation in the study area, likely accommodate infiltration of snowmelt and subsurface groundwater flow to the basin-fill aquifer. The Jurassic Arapien Formation also crops out in the Wasatch Range and San Pitch Mountains, and dissolution of gypsum and halite in the formation and sediments derived from it increases the sulfate, sodium, and total-dissolved-solids concentrations of surface water and groundwater. We grouped the stratigraphy of the Juab Valley study area into 19 hydrostratigraphic units based on known and interpreted hydraulic properties.