Your search found 3 records
1 Organisation for Economic Co-operation and Development (OECD). 2013. OECD compendium of agri-environmental indicators. Paris, France: OECD Publishing. 181p. [doi: https://doi.org/10.1787/9789264186217-en.]
Agricultural production ; Environmental factors ; Indicators ; OECD countries ; Water resources ; Water use ; Water extraction ; Water quality ; Greenhouse gas emissions ; Ammonia ; Acidification ; Eutrophication ; Soil erosion ; Wind erosion ; Water erosion ; Climate change ; Land cover ; Land use ; Farmland ; Organic agriculture ; Pesticides ; Irrigation water ; Nutrients ; Nitrates ; Nitrogen ; Phosphorus ; On-farm consumption ; Energy consumption ; Biofuels ; Methyl bromide ; Ozone depletion ; Transgenic plants ; Biodiversity ; Birds ; Economic aspects ; Markets ; Trends ; Policies ; Monitoring and evaluation
(Location: IWMI HQ Call no: e-copy only Record No: H050073)
(2.45 MB)
2 Sishu, F. K.; Tilahun, Seifu A.; Schmitter, Petra; Steenhuis, T. S. 2023. Investigating nitrate with other constituents in groundwater in two contrasting tropical highland watersheds. Hydrology, 10(4):82. (Special issue: Editorial Board Members’ Collection Series: Integrated Surface Water and Groundwater Resources Management) [doi: https://doi.org/10.3390/hydrology10040082]
Groundwater table ; Nitrates ; Watersheds ; Highlands ; Volcanic areas ; Aquifers ; Wells ; Precipitation ; Rainfall ; Chlorides ; Ammonia ; Fertilizers ; Runoff / Africa South of Sahara / Ethiopia / Lake Tana Basin / Dangishta Watershed / Robit Bata Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H051839)
https://www.mdpi.com/2306-5338/10/4/82/pdf?version=1680523739
https://vlibrary.iwmi.org/pdf/H051839.pdf
https://vlibrary.iwmi.org/pdf/H051839.pdf
(8.28 MB) (8.28 MB)
Nitrate is globally the most widespread and widely studied groundwater contaminant. However, few studies have been conducted in sub-Saharan Africa, where the leaching potential is enhanced during the rainy monsoon phase. The few monitoring studies found concentrations over drinking water standards of 10 mg N-NO3 - L -1 in the groundwater, the primary water supply in rural communities. Studies on nitrate movement are limited to the volcanic Ethiopian highlands. Therefore, this study aimed to evaluate the transport and fate of nitrate in groundwater and identify processes that control the concentrations. Water table height, nitrate, chloride, ammonium, reduced iron, and three other groundwater constituents were determined monthly in the groundwater in over 30 wells in two contrasting volcanic watersheds over two years in the Ethiopian highlands. The first watershed was Dangishta, with lava intrusion dikes that blocked the subsurface flow in the valley bottom. The water table remained within 3 m of the surface. The second watershed without volcanic barriers was Robit Bata. The water table dropped rapidly within three months of the end of the rain phase and disappeared except near faults. The average nitrate concentration in both watersheds was between 4 and 5 mg N-NO3 - L -1 . Hydrogeology influenced the transport and fate of nitrogen. In Dangishta, water was blocked by volcanic lava intrusion dikes, and residence time in the aquifer was larger than in Robit Bata. Consequently, nitrate remained high (in several wells, 10 mg N-NO3 - L -1 ) and decreased slowly due to denitrification. In Robit Bata, the water residence time was lower, and peak concentrations were only observed in the month after fertilizer application; otherwise, it was near an average of 4 mg N-NO3 - L -1 . Nitrate concentrations were predicted using a multiple linear regression model. Hydrology explained the nitrate concentrations in Robit Bata. In Dangishta, biogeochemistry was also significant.
3 Kumar, K.; Parihar, C. M.; Nayak, H. S.; Sena, Dipaka R.; Godara, S.; Dhakar, R.; Patra, K.; Sarkar, A.; Bharadwaj, S.; Ghasal, P. C.; Meena, A. L.; Reddy, K. S.; Das, T. K.; Jat, S. L.; Sharma, D. K.; Saharawat, Y. S.; Singh, U.; Jat, M. L.; Gathala, M. K. 2024. Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system. Scientific Reports, 14:11743. [doi: https://doi.org/10.1038/s41598-024-61976-6]
Maize ; Plant growth ; Modelling ; Nitrogen ; Ammonia ; Volatilization ; Conservation agriculture ; Wheat ; Zero tillage ; Leaf area index ; Biomass ; Grain ; Crop yield ; Forecasting / India / New Delhi
(Location: IWMI HQ Call no: e-copy only Record No: H052860)
(2.40 MB) (2.40 MB)
Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.
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