Your search found 12 records
1 Fipps, G.; Skaggs, R. W. 1991. Simple methods for predicting flow to drains. Journal of Irrigation and Drainage Engineering, 117(6):881-896.
(Location: IWMI-HQ Call no: PER Record No: H09486)
2 Fipps, G.; New, L. 1993. Efficient grain sorghum irrigation on the Texas high plains. Irrigation Journal, 43(5):30-31.
(Location: IWMI-HQ Call no: PER Record No: H013437)
3 Fipps, G.; Skaggs, R. W. 1986. Effect of canal seepage on drainage to parallel drains. In American Society of Agricultural Engineers, Transactions of the ASAE: Special edition - Soil and Water, Vol.29. St. Joseph, MI, USA: ASAE. pp.1278-1283.
(Location: IWMI-HQ Call no: 631.4 G000 AME Record No: H013860)
4 Fipps, G.. 1993. Melons demonstrate drip under plastic efficiency. Irrigation Journal, 43(7):8-12.
(Location: IWMI-HQ Call no: PER Record No: H014084)
5 Fipps, G.; Perez, E. 1995. Microirrigation of melons under plastic mulch in the lower Rio Grande Valley of Texas. In Lamm, F. R. (Ed.), Microirrigation for a changing world: Conserving resources/preserving the environment: Proceedings of the Fifth International Microirrigation Congress, Hyatt Regency Orlando, Orlando, Florida, April 2-6, 1995. St. Joseph, MI, USA: ASAE. pp.510-515.
(Location: IWMI-HQ Call no: 631.7 G000 LAM Record No: H018896)
6 Fipps, G.; Dainello, F. J. 1996. Growing cantaloupes with drip irrigation and plastic mulch. Irrigation Journal, 46(4):8-10.
(Location: IWMI-HQ Call no: PER Record No: H019121)
7 Endale, D. M.; Fipps, G.. 1996. Modeling irrigation strategies and scheduling in irrigation districts. In Camp, C. R.; Sadler, E. J.; Yoder, R. E. (Eds.), Evapotranspiration and irrigation scheduling: Proceedings of the International Conference, November 3-6, 1996, San Antonio Convention Center, San Antonio, Texas. St. Joseph, MI, USA: ASAE. pp.639-643.
(Location: IWMI-HQ Call no: 631.7.1 G000 CAM Record No: H020640)
8 Fipps, G.; New, L. L. 1994. Improving the efficiency of center pivot irrigation with LEPA. In Garduño, H.; Arreguín-Cortés, F. (Eds.), Efficient water use. Montevideo, Uruguay: UNESCO. ROSTLAC. pp.201-212.
(Location: IWMI-HQ Call no: 333.91 G000 GAR Record No: H020871)
9 Fipps, G.; Pope, C. 1998. Implementation of a district management system in the Lower Rio Grande Valley of Texas. In Burns, J. I.; Anderson, S. S. (Eds.), Contemporary challenges for irrigation and drainage: Proceedings from the USCID 14th Technical Conference on Irrigation, Drainage and Flood Control, Phoenix, Arizona, June 3-6, 1998. Denver, CO, USA: USCID. pp.85-97.
(Location: IWMI-HQ Call no: 631.7.1 G430 BUR Record No: H023786)
10 Endale, D. M.; Fipps, G.. 2001. Simulation-based irrigation scheduling as a water management tool in developing countries. Irrigation and Drainage, 50(3):249-257.
(Location: IWMI-HQ Call no: PER Record No: H028717)
11 New, L.; Fipps, G.. 2001. Selecting suitable water applicators: Increasing the power of pivots. Irrigation Journal, 51(5):9-12.
(Location: IWMI-HQ Call no: PER Record No: H029097)
(Location: IWMI HQ Call no: e-copy only Record No: H049705)
(2.71 MB)
Rice yield responses forecast (YIELDCAST) is a very useful decision support tool in climate adaptation in Sahel, where crops are purely rainfed climate-stressors sensitive. This study aims to construct upland rice yield responses forecasting algebraic formulation code referred as YIELDCAST by using gene-expression programming (GEP) based on observed rainfall and temperatures data (1979–2011), and forcing with global climate model (GCM) downscaled outputs under CO2 emission scenarios SR-A1B, A2 and B1 (2012–2100) over Bobo-Dioulasso, a Sahelian region. Statistically, GEP is a capable tool to downscale climate variables in the region (R = 0.746-0.949), and construct reliable rice YIELDCAST tool (R = 0.930; MSE = 0.037 ton/ha; MAE = 0.155 ton/ha, RSE = 0.137 ton/ha). Yields forecasted (2012–2100) showed a noticeable statistically significant difference between scenarios; however, fluctuating with no substantial increase (average below 1.60 ton/ha); suggesting that the increase observed in temperatures and decrease in rains will either reduced or hindered yield to largely increase in Sahel. With no such YIELDCAST tool to support adaptation decision, Sahel will still be under the trap of the broad array of adaptation strategy, which is a trial and error, less specific and costly. The model can help anticipate adaptation decision support on-farm water management, shift to suitable planting periods, and use of improved drought resistant and short duration varieties adapted to a local weather pattern.
Powered by DB/Text
WebPublisher, from