Your search found 16 records
1 1991. Arkansas farmer rises to pump efficiency challenge. Irrigation Science, 41(4):22-23.
(Location: IWMI-HQ Call no: PER Record No: H08664)
2 Baker, N. T. 1993. Utilization of a Geographic Information System to identify the primary aquifer providing ground water to individual wells in Eastern Arkansas. Water Resources Bulletin, 29(3):445-448.
(Location: IWMI-HQ Call no: PER Record No: H013766)
3 VanDevender, K.; Tacker, P. 1994. Irrigation as a utilization/disposal method for livestock slurry. Irrigation Journal, 44(7):18-21, 24.
(Location: IWMI-HQ Call no: PER Record No: H016081)
(Location: IWMI-HQ Call no: PER Record No: H016995)
5 Peralta, A. W.; Peralta, R. C. 1986. Sustained groundwater yield and consumptive use via target levels in a reasonable use state. In ASAE, Water resources law: Proceedings of the National Symposium on Water Resources law, Hyatt Regency, Chicago, Illinois, 15-16 December 1986. St. Joseph, MI, USA: ASAE. pp.235-243.
(Location: IWMI-HQ Call no: 333.91 G430 ASA Record No: H017430)
(Location: IWMI-HQ Call no: PER Record No: H017446)
(Location: IWMI-HQ Call no: PER Record No: H017447)
(Location: IWMI-HQ Call no: PER Record No: H019137)
9 Tacker, P.; Ashlock, L.; Vories, E.; Earnest, L.; Cingolani, R.; Beaty, D.; Hayden, C. 1996. Field demonstration of Arkansas Irrigation Scheduling Program. 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.974-979.
(Location: IWMI-HQ Call no: 631.7.1 G000 CAM Record No: H020690)
10 Britton, C. R.; Ford, R.K. 2001. Weather and legislation: The effect of drought and flood on water laws. The Social Science Journal, 38:503-514.
(Location: IWMI-HQ Call no: P 6157 Record No: H031146)
11 Graening, G. O.; Brown, A. V. 2003. Ecosystem dynamics and pollution effects in an Ozark cave stream. Journal of the American Water Resources Association, 39(6):1497-1507.
(Location: IWMI-HQ Call no: PER Record No: H034077)
(Location: IWMI-HQ Call no: PER Record No: H035021)
13 Stavins, R. N.; Jaffe, A. B. 1990. Unintended impacts of public investments on private decisions: The depletion of forested wetlands. The American Economic Review, 80(3):337-352.
(Location: IWMI-HQ Call no: P 7585 Record No: H039154)
14 Shukla, M. K. (Ed.) 2011. Soil hydrology, land use and agriculture: measurement and modelling. Wallingford, UK: CABI. 455p.
(Location: IWMI HQ Call no: e-copy SF Record No: H045772)
15 Saraswat, D.; Pai, N. 2011. Spatially distributed hydrological modelling in the Illinois river drainage area, Arkansas [USA], using SWAT. In Shukla, M. K. (Ed.) Soil hydrology, land use and agriculture: measurement and modelling. Wallingford, UK: CABI. pp.196-210.
(Location: IWMI HQ Call no: e-copy SF Record No: H045780)
(Location: IWMI HQ Call no: e-copy only Record No: H048717)
(1.36 MB)
The USDA Natural Resources Conservation Service (NRCS) developed the Mississippi River Basin Healthy Watersheds Initiative (MRBI) program to improve the health, water quality and wildlife habitat within the Mississippi River Basin. Lake Conway Point Remove (LCPR) watershed was identified as one of the watersheds for the MRBI program implementation. The goal of this paper is to evaluate the effectiveness of the MRBI program in LCPR watershed using a computer simulation model. Seven best management practices (BMPs) (pond, wetland, pond and wetland, cover crops, vegetative filter strips, grassed waterways and forage and biomass planting) were modelled under four placement strategies: random placement in 30% of the watershed, random placement in 30% hydrologic response units (HRUs) of the high priority hydrological unit code (HUCs), placement in the top 30% of the high priority HUCs, and top 30% of the HRUs in the HUCs near the outlet of the watershed. The model was calibrated for flow for the period 1987–2006 and validated for the period 2007–2012. Sediment and nutrients were validated from 2011 to 2012. Out of the BMPs evaluated, grassed waterways proved to be the most effective BMP in reducing sediment and nutrient loads from row crop (soy beans) and pasture fields. Reductions at the watershed outlet ranged 0–1% for flow, 0.28–14% for sediment, 0.3–10% for TP and 0.3–9% for TN. Relatively higher reductions were observed at the subwatershed level, flow reductions ranged 0–51%, sediment reductions -1 to 79%, TP -1 to 65% and TN -0.37 to 66% depending on BMP type, placement scenario, and watershed characteristics. The results from this study provide the data to help prioritize monitoring needs for collecting watershed response data in LCPR and BMP implementation evaluations, which could be used to inform decisions in similar studies.
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