U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.


Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Main content area

Relating topography and soil phosphorus distribution in litter-amended pastures in Arkansas

Adhikari Kabindra, Braden Indi S., Owens Phillip Ray, Ashworth Amanda J., Charles West
Agrosystems, geosciences & environment 2021 v.4 no.4 pp. e20207
Mehlich-3 phosphorus, algorithms, artificial intelligence, commercial farms, fertilizer rates, landscapes, nutrient management, pastures, phosphorus, phosphorus fertilizers, poultry, risk, runoff, soil, soil erosion, streams, Arkansas
Poultry producers in northwest Arkansas fertilize pastures with litter, leading to excessive P buildup on surface soils with risk of contaminating nearby surface waters. Information on the influence of pasture topography on P runoff is limited. Objectives were to assess soil P and P index status in pastures, quantify topographic influence on P distribution, and generate high-resolution P maps for site-specific nutrient management. Soil samples were collected from a commercial farm in a grid design and analyzed for Mehlich-3 P (STP), and dissolved reactive P (DRP). Gburek (GPI) and Sims P indices (SPI) were calculated by considering soil erosion and runoff potentials, STP, and P fertilizer application rate and source. A machine-learning algorithm, based on a random forest model, quantified spatial relationships of STP, DRP, and P indices with topography. The study area was highly variable in topography and soil P levels. High slope areas bordering streams and flat areas with lower elevation had greater GPI and SPI values. Topography explained up to 50% of variation in STP and DRP distribution and >70% variation in GPI and SPI. The key terrain attributes for STP, DRP, GPI, and SPI distribution were elevation, slope position, slope height, valley depth, and valley bottom flatness. Predicted P maps showed that areas along a stream had lower STP and DRP levels, but greater GPI and SPI. This analysis linked topographic relationships with P distribution, as topography controls the flow and distribution of water; therefore, future P management strategies should explicitly incorporate topographic risks.