Assessing Threshold Benefits of Conservation Tillage During Drought Years: Implications for Nutrient Use Efficiency and Water Quality
1. Assessing threshold benefits of conservation tillage during drought years:
Implications for nutrient use efficiency and water quality
Pierre-Andre Jacinthe1, Lin Li1, Lixin Wang1, Jia Du1, Pam Martin1, Juan Sesmero2, Dev Niyogi3
1Department of Earth Sciences, Indiana University Purdue University, Indianapolis; 2Department of Agricultural Economics, Purdue University; 3Indiana State Climate Office, Purdue University
Intensive agriculture in the US Midwest has been linked to various water quality
problems including eutrophication of surface waters, proliferation of nuisance algae,
and expansion of the hypoxic zone in the Gulf of Mexico. Several climate models
have predicted that the regionโs climate will be marked by frequent periods of
summer droughts interspaced with periods of excessive rainfall. These hydro-
climatic alterations could exacerbate nutrient export and water quality problems in
the region and beyond. For example, in the fall following the summer drought of
2012 (>90 rainless days during the critical months of May-August), unusually high
nitrate (20-40 mg N L-1) were measured in streams draining agricultural landscapes
in Iowa, Illinois and Indiana.
Land-use and management can modulate the impact of climate extremes on nutrient
dynamics and export. In no-till farming (NT), crop residue left on land surface can
moderate soil temperature and water loss via evaporation. Thus, in drought years,
crops can withstand rainfall deficit better when grown under NT than under
conventional tillage (CT). Data from the long-term experimental tillage plots in
Wooster (OH) has shown that the difference in corn yield between NT and CT tends
to grow wider as the summer rainfall deficit increases (Fig. 1).
No-till (NT) farming could provide an effective option to achieving sustainable
water quality, and mitigate the impact of climate variability on crop yield, nutrient
uptake, and consequently nutrient export during post-drought periods. Yet, despite
growing adoption in recent decades, the total land acreage under NT remains much
below the total area under CT management perhaps due to lack of awareness, among
producers, of the economic and potential water quality benefits of the practice
during severe droughts.
Hypothesis: Due to the greater water-holding capacity of NT soils, crops can
more efficiently utilize available nutrients when grown under NT compared to
CT. Thus, at the end of a summer drought, the amount of residual soil mineral
nutrients is significantly less in fields under NT than CT.
1. Assess the effect of NT on nutrient use efficiency, and leaching potential through
simulation of drought in experimental plots under NT and CT.
2. Determine the impact of drought severity on crop yield in fields under different
tillage practices through satellite-based monitoring of root-zone soil moisture and
spectral analysis of vegetation canopy.
3. Conduct an analysis of the probability distribution of benefits associated with
different tillage practices, and identify incentives and barriers to NT adoption.
4. Evaluate the general awareness, among producers, of the connection between
climate variability, land management, crop yield and water quality.
Objectives
Introduction
Research has been conducted in the Eagle Creek watershed in Indiana, a mixed land-use watershed predominantly
agricultural in the upper reaches and suburban downstream (Fig. 2).
Experimental plots have been established and fitted with rain shelters to artificially create water deficit (Fig. 2; Obj
1). Although 70-80 % rainfall reduction has been achieved, drought conditions could not be created in 2015 due an
unusually wet spring and summer.
Current and archived (2000-2014) satellite images from various platforms (Landsat, MODIS) have been collected.
Satellite data have been used to generate maps of crop residue cover (RC). Field measurements of crop residue
were made in Spring 2015 using the line-transect method. Algorithms linking spectral data and RC have been
developed.
Mapping of tillage practices (Fig. 3) is based either on: (i) the temporal variation in residue cover between previous
yearโs fall and current yearโs spring, or (ii) residue cover in the weeks leading to spring planting (if RC < 30% ๏จ
CT). Results obtained with the 30% RC approach are within the range reported by state agencies for this watershed
(Table 2). Mapping results are validated through on-site visits and farmer interviews (Obj. 2).
We will continue the analysis of archived satellite images to develop root-zone soil moisture and drought severity
distribution maps across the watershed during past seasons, especially drought years (2007, 2012). Relationships
will be drawn between drought severity and crop yield in fields under NT and CT and, from that analysis, a drought
threshold for yield reduction will be derived for each tillage practice (higher threshold expected under NT; Obj. 3).
Summary of Activity and Outlook
Fig. 3. Crop residue cover map from
satellite data acquired on April 7 (A) and
May 23, 2015 (B). Distribution of tillage
practices across the watershed at the
beginning of the 2015 cropping season as
determined by the 30 % RC criteria (C)
and the fall-spring comparison method
(D).
May-August rainfall, mm
200 300 400 500 600
Yielddifference(NT-CT),Mgha-1y-1
-2
0
2
4
1999 and 2012
Fig. 1. Difference in corn yield measured in no-till (NT) and
plowed-till (CT) plots in Wooster, OH. Normal rainfall
between May-August: 400 mm. Data from W.A. Dick.
Year % NT
IDA
surveyโ
2010 31 14 - 30
2013 35.1 11 - 35
2014 35.7
2015โก 32.5
2015 44.8
Fig. 2. Rain shelters installed at a
CT and NT field to artificially
created water deficit
Table 1. Percent of cropland under NT in
the watershed as determined by satellite
data. In 2015, tillage practice was
identified using both the 30% RC criteria,
and the comparison method.
โ Indiana department of agricultureโs biennial survey in adjoining counties.
Till (CT)
No Till (NT)
(A) (B)
(C) (D)
April7,2015
May23,2015
NT:32.5%
NT:44.8%