On-Farm Water Storage as a Tool to Reduce Risk Domena Agyeman Graduate Student, Mississippi State University Brian Williams Assistant Professor, Mississippi State University Mary Love Tagert Assistant Professor, Mississippi State University Bryon Parman Assistant Professor, Mississippi State University Mississippi Water Resource Conference 2017 1
250 Introduction On-Farm Water Storage (OFWS) is a best management practice which involves capturing runoff on-site and making it available for irrigation Design of OFWS Advantages Reduce stress on ground water (e.g Ouyang et al. 2016) Prevent nutrient loads into water bodies (e.g,tagert et al.2015:paz et al. 2012) 2
Introduction cont d With 1.7 million acres of irrigated land, Mississippi ranked 9 th in top irrigation states (USDA-NASS, 2012) Only 30% of annual rainfall occur during growing periods in Mississippi (Kebede et al. 2014) Poor access to irrigation water in East Mississippi Southeastern Coastal Plain Aquifer System Over 1000 feet of well depth High cost of drilling Motivation Uncertain rainfall pattern High cost of drilling Nutrient and Sediment loads to water bodies ( NRCS, 2010) 3
Previous studies Falconer, Lewis, and Krutz (2015): Economic feasibility of Tailwater Recovery (TWR) systems in MS Delta Loss of production land High investment cost 4
FOCUS Determine net present values (NPV) of OFWS over the investment period Perform sensitivity analysis on different pond sizes and irrigated acres Risk assessment 5
Site Field size is about 408 acres with about 339 irrigated acre Pond size: 17 acres, 25 feet deep Crop prices and yields USDA Weather PRISM Budgets From MSU Planning Budgets, 2016 Study site and Data Noxubee A map showing Mississippi counties and the study area 6
Approach 1. log ( y ) PP T T tc 2 2 nt 1 nt 2 nt 3 nt 4 nt 5 n nt P T c nt nt nt monthly mean precipitation, county n monthly mean temperature, county n county fixed effects t time nt stochastic error term Richardson, (2006): 2. p Mean price 1 Emp s, f x,cusd jt j d where: j crop s d = sorted deviates f( x) commulative probability of sorted deviates cusd correlated uniform standard matrix 7
3. E( ) E R F ti ti ti Approach cont d ( ) ( ) ER ( ) E0.5 ( p y ) z ( p y ) z ti A ct w cti cti st w sti sti i EF ( ) E0.5 ( ) ( ) A ti cti cti sti sti i 4. ENPV ( ) inv t1 ECF ( ) 1 inv initial investment cost ECF ( ) expected annual cash flows it L useful life span discount rate L it t E( ) expected annual returns ti ER ( ) expected annual revenue ti EF ( ) expected annual cost ti t time = dummy variable premium payment z indemnity i = either irrigation or rain-fed A land size i 8
Stochastic Efficiency with Respect to a Function (SERF) CE U ( NPV, RAC) F( N) is prefered to G( N) if CE CE F( N) is indifferent to G( N) if CE CE Fk Fk Gk Gk Where, RAC Risk Aversion Coefficient F( N) and G( N) are cummulative NPV distributions CE and CE are Certainty Equivalence at RAC Fk Gk k Hardaker et al. (2004) 9
Simulated Net Present Value for Rain-fed and Irrigation productions for a 408 acre farm in Noxubee county No Insurance 7% 8% 9% 10% Irrigation Rain-fed Irrigation Rain-fed Irrigation Rain-fed Irrigation Rain-fed Mean($/acre) 609 585 469 532 353 490 253 447 SD($/acre) 421 370 387 332 365 313 353 308 Min($/acre) (533) (557) (777) (366) (685) (540) (794) (502) Max($/acre) 2,113 1,844 1,698 1,576 1,407 1,489 1,342 1,417 70% CL 75% CL 80% CL 85% CL Mean($/acre) 787 780 629 718 497 663 381 611 SD($/acre) 387 313 357 304 356 279 320 266 Min($/acre) (226) (268) (381) (272) (531) (90) (613) (204) Max($/acre) 2,116 1,883 1,997 1,854 1,789 1,546 1,433 1,478 Mean($/acre) 763 769 610 706 486 641 379 609 SD($/acre) 384 323 360 279 337 286 315 254 Min($/acre) (496) (186) (469) (59) (425) (155) (511) (141) Max($/acre) 1,913 1,894 1,668 1,644 1,720 1,864 1,483 1,474 Mean($/acre) 728 730 585 674 457 616 359 581 SD($/acre) 374 313 338 284 339 264 319 263 Min($/acre) (429) (101) (800) (177) (514) (162) (692) (77) Max($/acre) 2,083 1,861 1,931 1,572 1,576 1,745 1,366 1,557 Mean($/acre) 650 669 515 610 387 551 294 508 SD($/acre) 349 298 335 276 324 261 303 244 Min($/acre) (524) (289) (418) (214) (501) (253) (619) (228) Max($/acre) 1,830 1,715 1824 1844 1,328 1,483 1,408 1,675 10
Certainty Equivalent 900 800 700 600 500 400 300 200 100 0 SERF Analysis with Relative Risk Aversion Coefficients 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 RRAC i ni i 70% i 75% i 80% i 85% Certainty Equivalent SERF Analysis with Relative Risk Aversion Coefficients 500.0 400.0 300.0 200.0 100.0 0.0 100.0 200.0 300.0 400.0 500.0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 RRAC i ni i 70% i 75% i 80% i 85% Irrigation production at 7% Irrigation production at 10% Anderson and Dijon, (1992): RRAC, 0-4 11
SERF Analysis with Relative Risk Aversion Coefficients 800 SERF Analysis with Relative Risk Aversion Coefficients Certainty Equivalent 900 800 700 600 500 400 300 200 100 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 RRAC Certainty Equivalent 600 400 200 0 200 400 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 i-ni r-ni i-70% r-70% i-75% r-75% i-80% r-80% i-85% r-85% 600 RRAC i-ni r-ni i-70% r-70% i-75% r-75% i-80% r-80% i-85% r-85% SERF chat for both irrigation and rain-fed at 7% SERF chat for both irrigation and rain-fed at 10% 12
Conclusion Including government incentives will make irrigation more attractive Society may also benefit from protection of water quality (not accounted for in this study) 13
Thank You Suggestions and Comments Name: Domena Agyeman Email: daa205@msstate.edu Phone: 662-497-1124 14