Soil Nutrient Depletin Modelling using Remote Sensig and GIS:
A Case Study in Chonburi, Thailand
Soe Win Myint1, Chakkrit Thongthap2 and Dr. Apisit Eiumnoh3
1UNEP Environment Assessment Program for Asia and the Pacific
Tel: 66-2 5246238, Fax : 662 5246233,
Email : swamyint@ait.ac.th
2Space Technology Application and Research Program
Tel: 66-2-52445584 , Fax" 662 52445597,
Email: nrd48826@ait.ac.th
AIT, P. O. Box 4, Klong Luang 12120 Thailand
Abstract
In this study soil nutrient depletion modeling of 3 major agricultural crop areas in Chonburi province were undertaken. Total N storage, and nutrient removal by crop and by soil less for a particular year are considered for this study. Land use map derived from TM acquired in 1995 was used in this study to identify cassava, paddy and sugarcane areas. Soil mass was obtained by calculating an area of a soil series, bulk density (BD) and an effective soil depth of a crop. As there is not direct measurement of N content in a soil system, organic carbon percent was used to calculate N amount in effective soil depth. The amount of P and K were obtained based on the available P and K value in PPM and soil mass in effective soil depth. N, P, and K taken up by tropical crops stated in UN-ESCAP, 1993 were used to compute the crop undertakes. Soil loss in the study area was obtained employing Universal Soil Loss Equation. A set of factors identified in USLE with several different approaches were reviewed, selected and applied, N, P, and K depletion due to soil erosion was obtained by the same method use for the availability of N, P, and K in a soil system by using organic carbon percent and P and K content from top 30 cm soil layer for all crops.
1. Introduction
The cause of nutrient depletion is due to the imbalance between the input and output of a soil system. Maintenance of proper nutrient status in soil is a key factor for high yield production. The inputs include nutrients in the soil profile, fertilizer application, nutrients derived from rainfall or from water apply to the crop, sediments accumulated on the soil and bio fixation. Nutrient removal from soil is due to uptake by crops, soil erosion, leaching, and volatization. The ability of soil to provide nutrients for crop production of fertility of a soil system is enhanced by systematic returns of nutrients. In order to properly manage nutrient balance of a soil system in a sustainable way it is necessary first to know availability, depletion and balance of nutrient in a soil system. This paper describes a study carried out to assess oil nutrient balance based on nutrient loss from two main sources: crop uptake and soil erosion. As far as possible other sources of nutrient input into the soil such as fertilizer use should be evaluated and included in the assessment of nutrient level. It seems that there is not much study and modeling for prediction of nutrient loss from leaching and volatization. Since the assessment of soil nutrient level, nutrient uptake by crops, and nutrient loss by soil erosion are very much related to spatial data GIS is a very effective tool in modeling nutrient status at various locations of a given study area. Spatial data used in this study includes land use/land cover, rainfall, soil characteristics (texture, depth, type, organic carbon percent, and Phosphorous and Potassium content of a soil system), topography (DEM, slope percent, slope length, and slope height), and nutrient uptake by crop for a unit area. Remote sensing is also required for preparing the land use/land cover map of an area for a given area for a give time. Since land use/land cover is a major factor in assessing nutrient depletion by crop uptakes and analyzing soil erosion, the importance of land use/land cover classification is obviously evident.
2. Study Area
This study area, Chonburi province of Thailand, is located between 100°50' N to 101° 43' and 12° 35' to 13° 36' in eastern part of Thailand. It has an area of 4,363.0 sq. km with population 977,000. Besides Forest, Rubber plantation and Mangrove major land use includes Paddy, cassava, sugarcane, pineapple, and orchard.
3. Materials and Supporting Data
Rainfall data (1995), Soil series map (1:100,000), Associates soil series information, Topographic map of Chonburi province (1:250,000), and Land use/land cover map of Chonburi Province derived from Landsat TM (1995) were used in this study.
4. Methodology
This study assumes that the nutrient uptakes by crops in a soil system is only from the nutrient in effective soil depth. The effective sol depth considered for cassava/sugarcane and paddy are 50 cm and 30 cm respectively. This can vary slightly due to the presence of hard rock, hard pan, water table and acid toxicity. Regarding nutrient loss from soil erosion, organic carbon percent, Phosphorous and Potassium in PPM (gm/ton) were taken from 30 cm soil depth. As the total nutrient loss was considered, the percentage of N available to plant was omitted in calculating nutrient loss from soil erosion. Soil loss assessment for the study area is based on the Universal Soil Loss Equation. Different calculation methods for each factor in Universal Soil Loss Equation were reviewed, selected and employed in this study. SLAMSA was also reviewed.
4.1 The Level of N, P, and K in Soil Series
From the soil series maps and associated soil series information organic carbon percent, Phosphorous and Potassium in PPM for respective soil depths were obtained.
4.1.1 Calculation of Available Nitrogen
There is not direct measurement about Nitrogen level in soils. Therefore, organic carbon percent was used to calculate the Nitrogen content in soil. From soil series map and associated description about soil series, information on organic carbon percent for each and every soil series from 30 cm soil depth for paddy and 50 cm soil depth for sugarcane and cassava were collected.Effective soil depth itself for each crop was also applied in obtaining soil mass. Nitrogen was given in the form of percentage of organic carbon which can be transferred in the form of organic matter by multiplication with the coefficient of 1.724. Five percent of total organic matter is estimated as Nitrogen content but only three percent of the total Nitrogen contained in matter is estimated as Nitrogen content but only three percent of the total Nitrogen contained in soil was computed as the weight of available Nitrogen which can be absorbed by crops. Bulk density in ton per cubic meter for each soil series was also obtained from soil series information. The calculation carried out for the availability of Nitrogen from a soil system is as follows:
| Total amount of soil mass(kg) |
= area extent x soil depth x Bulk Density x 103 |
| The amount of organic matter (kg) |
= soil mass x Organic Carbon % x 10-2 x 1.724 |
| The total of Nitrogen contained in a soil system (kg) |
= organic matter content x 0.05 |
| The amount of Nitrogen available to plant (kg/ha) |
= total Nitrogen x 0.03 x area extent of a 10-4 soil series in sq. m |
4.1.2 Calculation of Availbe Phosphorous
The content of phosphorous gram in one ton of soil expresses as PPM was obtained for paddy and sugarcane/cassava from 30 cm and 50 cm respectively. The Phosphorous and Potassium content vary from soil series to series. The calculation carried out for availability of Phosphorous is as follows:
| The amount of Phosphorous (kg) in 1 ha of soil |
= (soil mass x P content / (area extent of a)) x 10 soil series in sq.m |
4.1.3 Calculation of Availabe Potassium
The same calculation process applied to obtain Phosphorous was also applied here.
