Abstract
In the present study, a Cumulative corrected Antecedent Precipitation Index (CCAPI) as an index of profile moisture has been derived which correlates well with the Normalised Difference Vegetation Index
(NDVI) of satellite based remote sensing data in parts of Western Rajasthan. Daily rainfall data and monthly average data of other weather parameters along with soil moisture holding informations were used to calculate
CCAPI. The correlation between CCAPI and NDVI was highly significant (r=0.74*). API values when compared with some field soil measurement showed correlation of 0.80 and 0.78 with volumetric and gravimetric soil moisture respectively. NDVI was found to relate well during peak growing season with natural desert vegetation. These comparisons helped in assessing CCPI as a single substitute for variable attributes to be used in GIS locust control and surveillance.
Introduction
Real time information of soil surface and profile moisture is a formidable task to predict different hydrological processes in advance. Large number of efforts have been made to arrive at soil moisture information from rainfall and other bioclimatic factors. The gravimetric soil sampling has its own limitations by having highly heterogeneous matric and also needs a large number of sample which require lot of time and manpower for analysis. Any method which can be used readily with sufficient accuracy is what is actually required to predict unforeseen circumstances in desert terrain. An index which includes rainfall, soil parameters and meteorological variables would claim as a practical and realistic approach for instant information on soil moisture. The cumulative information of soil moisture as profile storage can also be used to predict the probable growth and development of ephemeral vegetations.
Western districts of Rajasthan are prone to locust breeding and migration. The present study integrates the three most important variable attributes, viz. rainfall, soil moisture and vegetation which are directly responsible for locust breeding and proliferation by a single parameter, API. Considerable effort have been made by other scientists to relate API with microwave brightness temperature
(Choudhary et.al., 1988; Wang, J.R 1985) but meager informations are available regarding the relation between API and satellite based NDVI especially in arid desertic tracks of Western Rajasthan having sparse vegetation cover and difficult accessibility. Hence it was decided to find a relation among the tree parameters in order to use Antecedent Precipitation Index (API) in absence of intensive soil moisture sampling of to arrive at a Geographic information system for locust control and surveillance.
Study Area
The study are lies between 70030 to 72025E longitude & 26045 to 28000 N latitude covering parts of Jaisalmer district. The area is mostly covered by loose mentle of Aeolian sand with texture varying from sandy to sandy loam. The soils are characteristically stratified belonging to Torrifluvents and Torripsamments type. General topography in the area varies from dunes and interdunal plains to river plains.
Landuse/wastelands n the form of sandy area, rock outcrops and land with or without scrub. Agricultural land and plantations are observed along the canal running across the study area.
The entire study area was geographically stratified into five different zones by Thiessen polygon method and all the soil sampling sites were put together under different outpost rainfall recording stations.
Table 1 : Distribution of soil sampling sites under the influence zone of different rainfall stations.
|
Rainfall Stations
|
Sites under the influence zone
|
|
Sri Mohangarh
|
5,6,7,8,9,10,12,14,15,25
|
|
Jaisalmar
|
1,2,3,4,16,24
|
|
Ramgarh
|
17,18,19,20
|
|
Sam
|
21,22,23,
|
|
Pokran
|
11
|
Methodology
Antecedent Precipitation Index (API)
API is a measure of soil moisture condition on the day under consideration & was calculated using Linsely et. al. (1949) model :
I
t = K
t * I
t-1 + P
t
Where,
I
t = API on t the day (mm)
I
t1 = API on t-1 the day (mm)
P
t = Precipitation on t the day (mm)
K
t = recession constant
Again , the recession constant kt was calculated following the method given by Chodhury and Blanchard (1983):
K
t = EXP (-E
t/Wm)
Where,
Et = Potential evaporation on t th day
Wm = maximum soil moisture available for evaporation (mm)
= WHC/100) * BD * 100 (mm)
Monthly average potential evaporation of Jaisalmar station was calculated using Thornthwaite (1948) model as a representative for all stations and presented in Table 2.
Monthly soil moisture available upto 10 cm top soil available upto 10cm top soil for evaporation for different sites were calculated and listed in table 3
Table 2 : Average daily potential evapotranspiration (PET) over Jaisalmar station.
|
Month |
PET (mm) |
Month |
PET (mm) |
|
Jan |
0.3 |
Jul |
5.3 |
|
Feb |
0.4 |
Aug |
5.7 |
|
Mar |
1.3 |
Sep |
5.1 |
|
Apr |
4.5 |
Oct |
4.1 |
|
May |
13.4 |
Nov |
1.5 |
|
Jun |
11.1 |
Dec |
0.7 |
Table 3 : Maximum available soil moisture (Wm) of surface soil (0-10 cm)
|
Site No |
Wm |
Site No |
Wm |
Site No |
Wm |
|
1 |
33.2 |
9 |
32.8 |
18 |
71.3 |
|
2 |
28.9 |
10 |
49.1 |
19 |
49.3 |
|
3 |
64.8 |
11 |
38.3 |
20 |
35.3 |
|
4 |
36.6 |
12 |
37.4 |
21 |
34.8 |
|
5 |
41.1 |
14 |
36.6 |
22 |
33.9 |
|
6 |
30.5 |
15 |
38.4 |
23 |
35.8 |
|
7 |
35.1 |
16 |
44.8 |
24 |
37.6 |
|
8 |
36.2 |
17 |
39.5 |
25 |
42.5 |
Table 4 gives the average recession constant values for different months using the meteorological data of Jaisalmar station.
Table 4: Monthly recession constant (Kt) values
|
Month |
PET (mm) |
Month |
PET (mm) |
|
Jan |
0.99 |
Jul |
0.86 |
|
Feb |
0.98 |
Aug |
0.86 |
|
Mar |
0.96 |
Sep |
0.87 |
|
Apr |
0.88 |
Oct |
0.89 |
|
May |
0.69 |
Nov |
0.96 |
|
Jun |
0.74 |
Dec |
0.98 |
Datewise rainfall value (in mm) has been recorded (1st Pre-monsoon rain onward till lat monsoon shower) from regional centre of Central Arid Zone Research Institute located at
Jaisalmar. From 1st rain onward API was calculated from each date and site upto 5th October (date of soil sampling) and finally corrected cumulative API
(CCAPI) was computed fro three satellite DOP since 1st onset of rain as follows :
CCAPI = (API WP)
Where, WP = Silting point of the soil at given location
This CCAPI was considered as an index which determines the growth and vigour of ephemeral desert vegetation.
Soil analysis
Representative soil samples (0-20 cm depth) from different locust breeding sites were collected on 5th October 92 for gravimetric moisture
(
qg), field bulk density and water holding capacity and brought back to laboratory with due care to prevent any moisture loss during transit. Soils were analysed using methods given by Black (1965). Permanent wilting point (WP) was determined at 1.5 MPa metric potential using pressure membrane apparatus.
