Impact of On-farm Water Storage for Increasing Agricultural
Productivity of Rice Farms in Thailand
by
Sutapa Amornvivat
A.B., Applied Mathematics, Harvard-Radcliffe Colleges (1997)
Submitted to the Department of Civil and Environmental Engineering
in partial fulfillment of the requirements for the degree of
Master of Science
in Civil and Environmental Engineering
MASSACHUSETTS INSlTUTh
OF TECHNOLOGY
MAR 0 6 2002
at the
LIBRARIES
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
February 2002
@
Massachusetts Institute of Technology 2002
Signature of A uthor ...................................................................
Department of Civil and Environmental Engineering
.
C ertified by .. .,.
Accepted by.....
...
I
(\
January 15, 2002
..................................
Dennis B. McLaughlin
Resources
Management
H.M. King Bhumibol Professor of Water
Thesis Supervisor
.-...--...--...
- - -..
..................
Oral Buyukozturk
4V
Chairman, Department Committee on Graduate Studies
Impact of On-farm Water Storage for Increasing Agricultural Productivity
of Rice Farms in Thailand
by
Sutapa Amornvivat
Submitted to the Department of Civil and Environmental Engineering
on January 15, 2002, in partial fulfillment of the
requirements for the degree of
Master of Science
in Civil and Environmental Engineering
Abstract
The effect of local hydrology on the availability of water is critical to successful agriculture.
Both too much and too little water can adversely affect crop yields. Flooding can damage
crops through submergence or uprooting while drought can cause desiccation or poor plant
development. In central Thailand, both these conditions are sometimes experienced during the
growing season. This thesis demonstrates that construction of on-farm ponds, which collect
local runoff in order to mitigate these problems, can be both technically feasible and welfare
improving.
In order to test the technical viability of on-farm ponds, this thesis introduces a model
to predict crop yields given hydrologic variability and a certain set of farm characteristics. In
addition, the economic welfare implications of on-farm ponds are investigated for a hypothetical
farm in Saraburi Province, Thailand. The economic analysis compares operations without
supplemental irrigation and with an "optimally designed" irrigation system. Supplemental
irrigation is found to be welfare improving through the reduction of risk and the increase of net
income.
Thesis Supervisor: Dennis B. McLaughlin
Title: H.M. King Bhumibol Professor of Water Resources Management
2
Contents
1
1.1
1.2
1.3
2
3
10
Introduction
Thailand's agricultural challenges
. . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.1.1
Meteorological Variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1
1.1.2
Irrigation Development
1.1.3
Rice Availability and Prices . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5
1.1.4
Rice Production
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
His Majesty's "New Theory" Development Scheme . . . . . . . . . . . . . . . . . 17
1.2.1
Solution: the New Theory Project
1.2.2
Necessary Conditions
. . . . . . . . . . . . . . . . . . . . . . 17
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Objectives and Overall Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.3.1
Crop simulation model - CROP . . . . . . . . . . . . . . . . . . . . . . . . 2 1
1.3.2
Hydrologic model - HYDRO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1
1.3.3
Utility Evaluation - UTILITY . . . . . . . . . . . . . . . . . . . . . . . . . 23
24
Literature Review
2.1
Water Harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2
Crop simulation models
2.3
Agricultural Investment Under Risk
2.4
Summary of Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
. . . . . . . . . . . . . . . . . . . . . . . . . 26
28
Study Area
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.1
General Description
3.2
Soils & Surface Topography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1
3
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.3
Water Resources
3.4
Meteorological Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5
Agricultural Practices
. . . . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5.1
Types of Crop
. . . . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5.2
Irrigation System . . . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . 39
40
4 Methodology
4.1
4.2
4.3
4.4
5
Overview
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.1.1
HYDRO-CROP Integration . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.1.2
Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.1.3
UTILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Hydrologic Models - HYDRO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.2.1
Concept
4.2.2
Farm Configuration
4.2.3
HYDRO : Inputs and Outputs
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
. . . . . . . . . . . . . . . . . . . . . . . . 47
Crop Simulation Program - CROP . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.3.1
DSSAT Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.3.2
CROP: Experimental Setting . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.3.3
CROP: Inputs and Outputs
. . . . . . . . . . . . . . . . . . . . . . . . . 51
Utility Evaluation - UTILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.4.1
Constant Relative Risk Aversion . . . . . . . . . . . . . . . . . . . . . . . 53
4.4.2
Expected Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
55
Results
5.1
5.2
Simulated Yields . . . . . . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.1.1
Statistics
. . . . . . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.1.2
Model Validation . . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.1.3
Yield VS. Pond Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Implications for Investment . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.2.1
Price of Rice Production. . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.2.2
Optimal Pond Size . . ..
. . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4
5.3
6
5.2.3
Risk Aversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 5
5.2.4
Pond Construction/Maintenance Cost . . . . . . . . . . . . . . . . . . . . 6 7
5.2.5
Subsistence Constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Sensitivity Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
. . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.3.1
Risk Aversion Parameter
5.3.2
Rice Price . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1
5.3.3
Subsistence Constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Conclusions
78
6.1
Evaluation of On-farm Pond Installation . . . . . . . . . . . .
78
6.2
Recommendations for Future Research . . . . . . . . . . . . .
. 80
6.2.1
Multiple-cropping system . . . . . . . . . . . . . . . .
. 80
6.2.2
Supplementary Water Resources to the On-farm Pond
82
6.2.3
Opportunity Cost of Agricultural Labor . . . . . . . .
84
6.2.4
Household's Wealth Accumulation Beyond Subsistence
84
6.2.5
Government-aid Programs . . . . . . . . . . . . . . . .
84
A HYDRO - MATLAB Code
86
B CROP - DSSAT Code
89
5
List of Figures
1-1
Rainfall distribution and variability common to the semi-arid areas in the central
region of Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1-2
Annual rainfall distribution illustrating the extent of variability (dotted line)
associated with monsoon onset and withdrawal periods.
. . . . . . . . . . . . . . 13
1-3
In addition to irrigation, the pond can be utilized for fishery to enhance income.
1-4
New Theory demostration farm at Wat Mongkolchaipattana Royal Development
18
Study Center, Saraburi province. . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
. . . . . . . . . . . . . . . . . 22
1-5
Diagram illustrates overall approach of this study.
3-1
Location of the study site in Chaleom Phrakiat District Saraburi Province, north
of Bangkok.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
. . . . . . . . . . . . . . . 30
3-2
Topography of our study site and the watershed area.
3-3
Average monthly rainfall and Class-A pan evaporation in Saraburi Province.
3-4
Maximum and minimum temperature at the study site.
3-5
Crop pattern suggested by Praputthbaht Field Crop Experiment Station, Dept.
of Agricultural Extensions in Saraburi Province.
4-1
. . . . . . . . . . . . . . . . . . 38
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Plan view of model farm showing rice paddies with surrounding ditches. Arrows
. . . . . . . . . . . . . . . . . . . . . . . . 45
represent important horizontal fluxes.
4-3
. . . . . . . . . . . . . . 35
Interaction between the crop simulation program (CROP) and the water balance
analysis (HYDRO).
4-2
. . 34
HYDRO farm configuration: Vertical cross-sections through pond and rice paddy
water storage compartments showing fluxes into and out of each compartment.
6
. 46
4-4
Elements of the Decision Support System for Agrotechnology Transfer (DSSAT)
4-5
Timeline for rice planting processes with respect to growth. The period of each
phasic development is averaged over 35 simulated cropping seasons.
50
. . . . . . . 52
5-1
Histograms to fit normal distribution of yield: rainfed and irrigated rice farms.
5-2
A: CDFs of yield per unit area with and without irrigation.
57
B: CDF of yield
increase with pond installation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5-3
Simulated and observed grain yield for irrigated and rainfed condition.
5-4
Plot of yield per unit area versus pond size from our model simulation.
. . . . . 60
The
continuous curve fits the plot. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
5-5
Average revenue with respect to pond size. Optimal pond size is at the peak of
curve. ...........
5-6
64
..........................................
Plot of expected utility of revenue versus pond size.
The curve results from
interpolation of HYDRO-CROP simulated data (green dots).
5-7
. . . . . . . . . . 66
Histograms of revenue under irragated and rainfed conditions. The dotted line
represent estimated normal distributions using parameters derived from both
sets of revenue. ........
5-8
.....................................
Cumulative distribution functions for revenue (top) and utility (bottom) from
rice production under irrigated and rainfed conditions.
5-9
68
. . . . . . . . . . . . . . 69
Impact of the risk aversion coefficients on utility. . . . . . . . . . . . . . . . . . . 72
5-10 Maximum cost of a 5% pond in which the on-farm pond scheme is attractive to
investment in relation to different levels of farmer's attitude towards risk.
. . . 73
5-11 Relationship between the maximum cost of a 5% pond and price of rice production. Here we assume the price of rice equal to 4.3 baht/kg . . . . . . . . . . . . 74
6-1
Multi-cropping system in the New Thoery Study Center in Saraburi Province.
6-2
The complete irrigation network of the New Theory: A big reservoir supplies a
.
81
small; a small reservoir supplies a pond. . . . . . . . . . . . . . . . . . . . . . . . 83
7
List of Tables
3.1
Source: Department of Agriculture and Royal Irrigation Department, Ministry
of Agriculture and Cooperatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
. . . . . 76
5.1
Simulated and observed grain yield for irrigated and rainfed conditions.
5.2
Area allocated for rice paddy in an average Saraburi rice farm with respect to
percentage of pond area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.3
Statistics of simulated revenue for rice production, generated from 35 years of
actual weather data (1961-1995)
. . . . . . . . . . . . . . . . . . . . . . . . . . . 77
. . . . . . . . . . . . . . . . . . . . . . . 77
5.4
Input values used in sensitivity analysis
5.5
Summary of sensitivity analysis results . . . . . . . . . . . . . . . . . . . . . . . . 77
8
Acknowledgments
I would like to thank all of those who have taught and inspired me over the years: my
deepest appreciation goes to my advisor, Professor Dennis McLaughlin, for his patience and
support during my inevitably awkward early years of interdisciplinary research. This thesis
might have suffered a dismal existence were it not for our discussions-discussions that helped
me sort through the mental chaff and crystallized my ideas.
I feel deeply indebted to His Excellency Dr.Chaovana NaSylvanta and Dr.Sippanondha
Ketudat for their invaluable advice and continuing interest in my professional development. In
addition, I want to acknowledge Dr.Djitt Laowattana who gave me the opportunity to work on
this meaningful project and has done so much for my academic pursuits
Julie, Freddi, and other past and present members of Parsons Laboratory deserve special
thanks for directly influencing the course of my graduate project. Mon, Fred and Helani provide
unfailing friendship and quality times during our weekly dinners. P'Euay, P'Nong and everyone
else in TSMIT community has been a source of inspiration and comfort.
I am grateful to my dear friend Jan whom I owe many thanks for restoring my peace of
mind through tough times and sharing excitement and joy when things turn our all right.
This thesis is dedicated to my parents, Police General Sawat and Khunying Catliya, with the
hope that they see this as only a tiny part of the love and gratitude I feel. Their understanding
and dedication have made this long journey a rewarding success.
9
Chapter 1
Introduction
Monsoon Asia is generally characterized by distinct wet and dry seasons, which are associated
with wide seasonal fluctuations in agricultural production, farm income, labor use, wages, and
prices.
In Thailand, the most persistent constraint to increasing rice productivity has been
identified as the lack of water.
Although many of the rice cultivation areas in Thailand,
mainly those in the central region, receive fairly high total annual rainfall, the rains are highly
concentrated within the monsoon months.
Excess water that may be available during part
of the growing season is unavailable at critical rice development stages and cannot be used by
other crops.
Irrigation is perhaps the most obvious instrument for attempting to reduce the
fluctuations between peak and slack seasons.
The effect of local hydrology on the availability of water is critical to successful agriculture.
Both too much and too little water can adversely affect crop yields.
Flooding can damage
crops through submergence or uprooting while drought can cause desiccation or poor plant
development.
In central Thailand, both these conditions are sometimes experienced during the
growing season. Strong monsoon rains and low permeability soils combine to cause damaging
floods.
However, sporadic dry periods within the wet season and uncertainty in the time of
onset of the wet season create drought hazards for agriculture in this region. Proposals for the
development of irrigation in this region include the construction of numerous small farm ponds,
which collect local runoff and may be supplemented by larger storage reservoirs.
In order to test the viability of such a plan, this thesis models the hydrology and agricultural
response of the region. We introduce a model framework to predict crop yields given hydrologic
10
variability and a certain set of farm characteristics.
We also investigate the impact of pond
size on farmer's investment decisions.
This chapter examines the problems of water scarcity that Thai rice farmers in the central
region encounter and the ongoing government effort to tackle such challenges. The objectives
and overall approach of the thesis are also briefly summarized.
Chapter 2 surveys literature
on water harvesting schemes, crop simulation models, and agricultural planning under risk.
Chapter 3 describes the study site.
Chapter 4 explains the methodologies developed in this
thesis in detail while Chapter 5 discusses the results and carries out sensitivity analyses. Lastly,
Chapter 6 summarizes the study and suggests directions for future research.
1.1
1.1.1
Thailand's agricultural challenges
Meteorological Variation
Agricultural drought may be defined as an unfavorable water balance for optimum crop production. Since different crops require different soil-water regimes for optimum yields, drought
problems must be looked at in relation to the crops to be grown. Most often, rainfall variation
and unpredictability affect rainfed lowland rice yields more than the shortage of water does in
aggregate sense. In Thailand, even with the high concentrations of rainfall events during the
main rice season, rainfed rice in many areas and in most years suffers from in-season drought
and consequent loss of yield. Another constraint farmers face is the variation in the timing of
the onset and termination of the monsoon. The extent of such variations for Saraburi province
in the central region of Thailand is shown in Figures 1-1 and 1-2. Such a situation gives farmers
little choice but to adopt a very low-risk, low-input cropping system, which is directed to giving
a stable rather than a high production.
Water shortage prevents most farmers from growing
a non-rice cash/commercial crop during the post-rice season.
Even a marginal improvement
in the soil-water status in this season can make a significant difference in cropping opportunity
and/or yields.
11
40 n
I
I
I
I
I
I
I
I
I
35C-
I
I
std. deviation
30Cmean (1961-1997)
2 5 C-
0a
15C-
10+
500
J
I
I
A
F
M
A
J
M
i-
A
S
0
N
D
Figure 1-1: Rainfall distribution and variability common to the semi-arid areas in the central
region of Thailand.
12
35C
I
I
I I
Ithdawa
I
301
25C-
withdrawal
std.dev = 24 days
20CE
E
onset
3..y
std.dev = 36 ys
15C
10C
50-
0
J
F
M
A
M
J
J
A
S
0
N
D
Figure 1-2: Annual rainfall distribution illustrating the extent of variability (dotted line) associated with monsoon onset and withdrawal periods.
13
1.1.2
Irrigation Development
Early investments in irrigation schemes in Thailand were large projects and concentrated on
major water distribution systems in the Central Plain. The investments were largely to increase
the yield of the wet-season rice crop in the central region by improving the reliability of the
water supply. In the early 1970s the emphasis was shifted to smaller projects which provided
water distribution networks at the farm level.
The benefits of irrigation include not only double cropping of rice in the Central Plain and
a modest expansion of upland crop cultivation in certain parts of the north and northeast, but
also an increase in rice yield per hectare in both the wet and dry seasons.
The increase in
rice yield has come about because irrigation has induced a shift in planting technique from
broadcasting to transplanting, a shift from traditional to modern rice varieties, and increased
use of fertilizer and other chemical inputs.
The wet-season rice yield per hectare in irrigated
areas during the first half of the 1990s averaged 2.8 tons, almost double the rainfed yield of 1.7
tons. Total rice production increased from an average of 13.9 million tons in 1971-75 and 22.1
million tons in 1991-95.
Dry season rice yield increased from 6.3 percent of the total crop to
19.4 percent during the same period.
Conventional irrigation facilities, however, are not likely to be developed for the vast majority of cultivated areas in the foreseeable future. Investment in irrigation infrastructure has
been declining in the last decade and much of the rainfed lowland areas is unavailable for largescale irrigation projects because of topography, soil drainage, or water storage problems. Yet
the pressure to produce more crops from the land is increasing as the population continues to
grow at relatively high rates.
On-farm reservoir systems offer a promising way to alleviate drought.
These systems are
used to harvest rain falling on the pond and surplus runoff produced in the catchment area,
and to store the water for subsequent use.
ancient times.
Farm ponds have been in use in rural areas since
But today this time-tested technique has acquired a new critical dimension
because recent advances in agricultural technology has opened up new opportunities for farmers.
For instance, new crop cultivars which require less irrigation-intensive treatment have been
introduced and adopted by local farmers.
Recent research results have shown that scientific
management of water resources within a microwatershed, using an on-farm reservoir as the
14
centerpiece, is economically attractive and socially desirable [3, many examples of the on-farm
impoundment system are discussed ].
1.1.3
Rice Availability and Prices
The increased rice output resulting from irrigation has increased the supply of rice available
for domestic and foreign consumers. The growth rate in rice production has permitted modest
growth in Thailand's per capita domestic rice consumption, together with large increases in
export volume.
At an aggregated level, expansion of irrigated area may reduce seasonal rice price variation.
Two related effects may contribute to reducing the magnitude and increasing the predictability
of seasonal price spreads.
First, an increase in the absolute level of rice production in the
dry season may reduce the storage requirements and cost of holding much of the wet-season
production through to the following wet season. Second, seasonal price changes are influenced
by the deviations in rice production from expectations.
If irrigation can reduce variability in
production, and hence the deviations of actual from expected production, it will contribute to
mitigating the inter-year instability in seasonal price changes [36].
At the farm level, irrigation may have large effects on seasonality in cropping practices,
yield and production, farm income, and labor demand.
When irrigation permits dry-season
cropping, it will tend to smooth the seasonal pattern of production, income and labor use.
1.1.4
Rice Production
Planting Methods
In the rainfed rice-growing areas of Thailand, only dry soil broadcast planting is practiced, but
in irrigated areas there has been a shift to transplanting and, to a small extent, to puddled soil
broadcasting.
Land consolidation tends to reinforce the shift to puddled broadcasting.
This
new broadcasting method, coupled with increases in application of fertilizer and chemicals,
provides a high yield per hectare.
This technique requires a well-leveled field and a good water
control system to drain out water before broadcasting so that the water level can be increased
with the height of the growing plants.
In irrigated areas without land consolidation, puddled
15
soil broadcasting can be, and was, practiced over more limited areas (28 percent in the wet
season and 30 percent in the dry season) depending on the degree of water controllability.
Net Cash Income of Farm Households
The largest source of income to local farm households is the sale of paddy rice, contributing
over 90 percent of the total income in each cropping season in irrigated areas without land
consolidationi, 80-85 percent in land-consolidated areas, and only 65 percent in the wet-season
rainfed areas. Other crops and livestock account for 24 percent of total cash income in the rainfed areas in the wet season, and livestock alone contribute about 23 percent in the dry season.
Livestock and nonfarm employment are important sources of income for rainfed households, not
only in the dry season when rice cannot be grown, but also in the wet season, because paddy
sales bring in only 65 percent of total income2
For the land consolidated farms, other important sources of income are employment on
other rice farms, especially in the wet season, and tractor rentals, mainly in the dry season.
Since the broadcasting techniques used in land-consolidated areas require less labor than the
transplanting method, household laborers are hired to work on other farms in irrigated areas
without land consolidation. This hiring out occurs before and after broadcasting and harvesting
on these laborers' own farms. Income from tractor rentals is mainly derived from renting out
small tractors for land preparation, not only on rice farms but also in areas growing upland
crops in the dry season. Consequently cash income from sources other than paddy rice is much
larger for land-consolidated farms than for households in other areas.
This study, however,
emphasizes the impacts of on-farm reservoirs on non-consolidated rainfed farms in semi-arid
areas of the central region, where transplanted rice is predominant. Household income for such
farms comes mainly from the sale of rice.
Land consolidation under private farmland ownership refers to an exchange of the private ownership and
location of spatially dispersed parcels of farms to form new holdings containing just one (or as few as possible)
parcel(s), with the same (or similar) wealth in land as that before the exchange.
Land consolidation can turn farms from fragmented to compact enterprises, enlarge parcel size, and make
sale, lease, and other forms of joint use of land physically easier. But it does not enlarge farm size; e.g., a farm
previously composed of 10 dispersed parcels (on average 0.1 ha each) could now hold one compact parcel of 1 ha.
However, only farmers with a medium-size or larger land holding are likely to undertake such legal transactions.
2The statistics of husbandry and nonfarm incomes are adapted from Center for Agricaltural Information
(1998) and Somrith (1998).
16
1.2
His Majesty's "New Theory" Development Scheme
From past to present, the shortage of water supply for agricultural activities has been a major
problem facing Thai farmers. The impact has been more severe in agricultural areas where
farming activities depend heavily on rainwater.
Unfortunately, such areas constitute a pre-
dominant part of the country. Hydrologic variability enables farmers to plant only once a year
during the rainy season.
Moreover, farmers are exposed to risks and damages due to adverse
conditions of the soil, climate, and inconsistent rainfall patterns. Although efforts have been
made to counter the water shortage problem by digging ponds or enlarging channels to store
water, clear design guidelines have never been established.
Besides, there are also other fac-
tors that magnify the water shortage situation. Examples of such factors are unsystematically
planned crop cultivation and the mono-cropping farming system, under which only rice or field
crop is planted.
1.2.1
Solution: the New Theory Project
Aware of the situation, His Majesty King Bhumibol Adulyadej initiated a development scheme,
called "Trisadee Mai" or "New Theory" in direct translation, intended to provide guidelines for
small-scale farmers for optimum management of their land and water resources.
The concept
requires division of a small piece of land into distinct parts. It entails technical calculations to
determine the amount of water needed to support cultivation all year round. The idea provides
individual farmers with a comprehensive plan that consists of three phases:
Phrase I The first phase of the New Theory requires dividing the land into four parts under a
certain ratio: Part 1 is designated for the pond; Part 2 is set aside for rice cultivation;
Part 3 is used for multi-cropping farming; Part 4 is allocated for housing, animal raising,
and other activities.
Phrase II The second phase suggests that farmers pool together their efforts and resources in the
form of a group or cooperative to execute the following activities: 1) production (crop varieties, soil preparation, irrigation system, etc.); 2) marketing (sundry area, silo, rice mill,
product distribution); 3) welfare (public health, loan); 4) education (school, scholarships);
5) society and religion.
17
Figure 1-3: In addition to irrigation, the pond can be utilized for fishery to enhance income.
Phrase III The third phase involves making the necessary contacts and coordination to establish a
fund or ensure the source of funding from banks and companies in order to assist them
in the investment of activities to improve the quality of their lives.
This royal-initiative development scheme first started in 1995 at Wat Mongkol Chaipattana
Royally-initiated Development Study Center in Saraburi Province.
Since then, the program
3
has been extended to various geological areas in other Royal Development Study Centers [9,
The history and implementation of the New Theory concept is described]. This study, however,
uses the physical properties of Saraburi area as a case study for the model which is discussed
extensively in Chapter 3.
3
Royally-initiated Wat Mongkol Chaipattana Development Project in Saraburi Province, Khao Hin Sorn Royal
Development Study Centre in Chachoengsao Province, Royally-initiated Khlong Si Siad Reservoir Development
Project in Nakhon Nayok Province, Huai Sai Royal Development Study Centre in Phetchaburi Province, Kung
Krabaen Bay Royal Development Study Centre in Chanthaburi Province, Puparn Royal Development Study
Centre in Sakon Nakhon Province, Baan Dan Samakkee New Theory Demonstration Project in Kalasin Province,
Pak Thong Chai Royally-initiated New Theory Demonstration Project in Nakhon Ratchasima Province, Huai
Hong Khrai Royal Development Study Centre in Chiang Mai Province, Pikun Thong Royal Development Study
Centre in Narathiwat Province
18
*--U44
*
*
%*
-
-
-
-
Figure 1-4: New Theory demostration farm at Wat Mongkolchaipattana Royal Development
Study Center, Saraburi province.
19
1.2.2
Necessary Conditions
There are three necessary conditions for the success of the New Theory concept: (1) cooperation
among participating farmers, (2) technical feasibility and (3) economic feasibility.
The main idea of the New Theory is to serve as a production system that allows farmers
To be viable, this concept requires the unity and
to become self-sufficient and self-reliant.
willingness of the community to work with and assist each other in order to reduce expenses,
similar to the traditional rice harvesting practice.
However, this requirement is beyond the
scope of this study and is subject to research in the area of social sciences.
This study only
looks at the hydrologic and economic feasibility of this proposed project presuming the best
possible cooperative effort of participants.
Another important aspect of the New Theory is to use water storage to supply farming
during dry seasons or dry spells. Therefore, the concept requires that part of the land is set
aside for the construction of a pond. This study is to find guidelines for the suitable pond size
to suit each area's local characteristics, including soil characteristics, the amount of rainfall, and
the general environment.
For instance, in the southern region where rainfall is more plentiful
or in areas where sources of water are available to continuously replenish the pond, it will
be possible to reduce the size of the pond and allocate the surplus land for more productive
purposes.
1.3
Objectives and Overall Approach
The New Theory concept has been widely implemented in other areas beyond demonstration
farms.
It is necessary that operators thoroughly and clearly identify the conditions in which
this concept is technically viable and economically attractive. The main objective of this study
is to propose a simplistic approach for determining the feasibility and benefits of the on-farm
pond, suggested in Phase 1 of the New Theory concept.
This thesis brings together scientific
work on hydrology, as well as soil science and plant biology, with economic modeling.
The
goal is to model the physical system on its own, and then to integrate that system with the
investment decisions of the households.
Profit, risk, and variability of yields will all influence
choice of pond investment, as farm households are generally risk averse.
20
We focus on an area around the Wat Mongkol Chaipattana Study Center to demonstrate
our approach. More detailed methodology is discussed in Chapter 4. The work described here
is a stepping-stone to establish the link between hydrology and agricultural productivity under
the New Theory development scheme. More careful economic analyses are expected in future
research to extend the model.
Our model can be divided into three modules: CROP, HYDRO, and UTILITY. The first
two modules, CROP and HYDRO, operate simultaneously to simulate rice yields under rainfed
and irrigated irrigation systems. Then the process of utility evaluation is included to translate
agricultural production into household welfare and to determine whether the on-farm pond
The overall model interaction is illustrated in
irrigation system is an attractive investment.
Figure 1-5.
1.3.1
Crop simulation model - CROP
The crop simulation model integrates the aggregate effect of the underlying processes that determine the behavior of complex agricultural systems. It is based on CERES-Rice, a component
of the Decision Support System for Agrotechonology Transfer (DSSAT) software [57].
DSSAT
is a collection of crop models and computer programs integrated into a single software package
in order to facilitate the application of crop simulation models in research and decision making.
This software is a product of the International Bench-mark Sites Network for Agrotechnology
Transfer (IBSNAT) project and is widely used in agricultural planing and agronomic research.
CROP is a site-specific file, set up in DSSAT standard format, which enables use to investigate the effect of different irrigation schemes on rice yields in our study area.
The required
inputs consist of weather, cultivar, soil structure, irrigation management, fertilizer application,
planting and harvesting methods.
The CROP model simulates growth and development as
well as grain yield under different irrigation treatments: rainfed and irrigated under an on-farm
reservoir scheme.
1.3.2
Hydrologic model - HYDRO
HYDRO is a quantitative water balance analysis model which takes in hydrological information
and irrigation needs, computed in CROP. Its main function is to investigate the feasibility of
21
fluxes & storages
simulated
yields
F
r -
Figure 1-5: Diagram illustrates overall approach of this study.
22
supplying a small on-farm pond exclusively from runoff generated within the farm boundary.
Water stored in the pond is diverted to support rice field irrigation.
The HYDRO model
quantifies water fluxes entering and leaving the farm system assuming all runoff is harvested
and given a specified irrigation rule. Another task is to decide whether the irrigation rule can
be sustained.
If the pond cannot supply enough water to satisfy irrigation demand; a new
irrigation rule is assigned to the CROP module.
Crop and hydrologic information is shared as inputs by both modules while water fluxes
and storage values are passed between the two modules.
The CROP and HYDRO modules
operate simultaneously and complement each other in simulating grain yield from actual meteorological data.
All interactions are carried out manually; the two computer programs are
run independently.
The simulation process converges when water use in CROP is consistent
with water supply from HYDRO. After convergence, the results of the simulation are stored
for utility evaluation.
1.3.3
Utility Evaluation - UTILITY
The UTILITY module evaluates the impact of on-farm pond investment, given simulation
results from the HYDRO-CROP integrated model.
The assumed utility function is used to
determine the conditions in which on-farm investment is attractive to local farmers. The utility
evaluation module is a combination of break-even analysis and sensitivity analyses. The results
allow the analyst to understand how changes in parameters affect investment choices.
23
Chapter 2
Literature Review
There is an extensive literature concerned with the impact of investment in water resources to
alleviate drought and increase productivity in rainfed lowland rice farms. However, only a few
of the studies reviewed below establish a link between the technical viability and welfare implications of such investment.
The main objective of this thesis is to simultaneously investigate
the technical and economic feasibility of on-farm irrigation in central Thailand. The economic
analysis compares operations without the supplemental irrigation and with an "optimally designed" irrigation system.
Our overall approach combines the concepts of water harvesting,
on-farm storage, crop simulation, and agricultural investment in the presence of risk.
2.1
Water Harvesting
Water harvesting, defined in its broadest sense as the collection of runoff for productive use
[51], is an ancient art practiced in the past in many parts of North America, the Middle East,
North Africa, and Asia.
More precisely, water harvesting can be defined as the process of
concentrating rainfall as runoff from a larger catchment area to be used in a smaller target
area. This process may occur naturally or artificially [40].
Water harvesting supports a flourishing agriculture in many dry areas, where rainfall is low
and erratic in distribution. Examples are given, among others, by Oweis and Taimeh (1996),
Suleman et al. (1995), Krisna et al. (1987) and Oswal (1994).
However, for any agricultural
water development to be successful, it must be economically viable. The sustainability of the
24
various water harvesting techniques is found to depend largely upon the timing and the amount
of rainfall ([10],[48], and [4]).
A good historical review of rainwater harvesting for agriculture
is given in UNEP (1983).
Although the revival of water harvesting techniques began in the early 1930s, little construction and research activity began before the late 1950s [19]. In the 1960s, various governmental,
private, and university research organizations, particularly in arid and semiarid areas, initiated
studies to develop and evaluate water harvesting techniques with lower installation costs and
improved system reliability. As a result, new water harvesting techniques have appeared in the
literature during the last two decades [11].
Recently, there has been renewed interest in water
harvesting in South and Southeast Asia, probably as a result of the lack of water in times of
need, which is the dominant obstacle to increasing productivity of most rainfed ricelands [3].
2.2
Crop simulation models
Crop modeling enables researchers to integrate knowledge from different disciplines in a quantitative way. That, in turn, helps researchers understand the underlying processes that determine
Mathematical models are caricatures of real-
the behavior of complex agricultural systems.
world systems.
Solving the equations enables a numerical description of the system to be
produced. Ultimately, 'what if' questions can be asked about the functioning of a system, and
numerical answers are provided [42].
Hansen and Jones (2000) surveyed issues and approaches
related to applying crop models at scales larger than the plot.
Crop models are particularly useful in rainfed lowland rice ecosystems, which are characterized by high temporal variability and spatial heterogeneity. A limited number of field experiments cannot provide a reliable basis for management strategies under the myriad possible
conditions that exist. Simulation models can replace expensive and time-consuming experiments due to their ability to generalize experimental findings and help interpret the results of
a few selected experiments ([56], [49], [61], and [5], for examples).
Modeling is especially useful in yield gap analysis, a method for identifying constraints to
agricultural production in different agroclimatic zones. Pinnschmidt et al. (1996) concentrated
on ameliorating those factors that contribute to the gap between farm yield, potential farm yield,
25
and potential experiment station yield.
2.3
Agricultural Investment Under Risk
Previous studies have addressed the economic feasibility of on-farm impoundments.
Burt
and Stauber (1971) studied such investments. However, they focused on irrigation scheduling
without addressing water availability, water supply reliability, impoundment size or crop choice.
Krishna et al. (1987) studied the economic feasibility of on-farm ponds in east Texas, but
assumed deterministic water supply and irrigation demand along with fixed impoundment size
and irrigated land area. Dudley et al. (1971a, b, 1972) developed short, intermediate, and longrun optimizing models using stochastic water supply and demand to determine the combination
of reservoir size and irrigated acreage for a single crop.
Their approach did not allow for
irrigated/dryland crop substitution or multiple crop substitution. Other studies have assumed
availability of sufficient water ([1] and [41]).
Furthermore, the effect of risk attributes has not been comprehensively examined in the
irrigation system investment context. The reduction in income variability can be an important
impetus for irrigation adoption [1].
Pender (1992) proposes welfare analysis for investment
in shallow wells; whereas Featherstone and Goodwin (1993) discuss the risk aversion effect
on farmer's choice in soil conservation.
Ziari et al. (1995) uses a risk-sensitive model which
simultaneously considers water supply, irrigation system investment, irrigation scheduling, and
crop mix selection to evaluate the economic feasibility of small impoundments.
2.4
Summary of Contributions
In attempt to fulfill the gaps left in the aforementioned studies, this thesis has the following
objectives:
o to derive stochastic series of simulated yields directly from actual meteorological data;
o to derive an on-farm pond design for subsistence rice farms in central Thailand, accounting
for the roles of uncertainty and risk.
26
These objectives are achieved by using a modeling approach which simultaneously considers
impoundment size, irrigation technique, variable rainfall and farmers' attitudes towards risk.
27
Chapter 3
Study Area
In this Chapter we give a general description of the case study area's soil, water resources, and
agriculture. We then explain existing irrigation management in the rice fields.
3.1
General Description
Saraburi Province is located on the edge of the Chao Phraya Basin in the central region of
Thailand. Our study site is located to the south of Wat Mongkol Chaipattana Royally-initiated
Development Study Center in Chaleom Phrakiat District of Saraburi Province (Figure 3-1).
The land is a rice field that belongs to Mr. Tongsuk and Mrs. Sawang Pimsan.
Because the
farm is outside the Royal Projects Study Center, it is not directly connected to the Huai Hin
Khao reservoir supply system (Site B in Figure 3-2).
The Pimsan farm is suitable for a study site for a number of reasons:
1. The farm grows primarily transplanted lowland rice; its paddy fields used to be strictly
rainfed until recently.
2. It applies the New Theory concept and uses an on-farm pond which, since its construction,
has been able to contain sufficient water to insure a higher yield paddy rice crop during
the wet season and to irrigate some dry season and perennial cash crops.
3. Most of the water in the pond appears to be generated locally. It does not need supplemental irrigation from outside its boundary. It is uncertain whether some of the water in
28
Figure 3-1: Location of the study site in Chaleom Phrakiat District Saraburi Province, north
of Bangkok.
29
_t
e TeF1
4.7
117 r~
-
M
----
~K.;
-
bA1-
L
4-
-
-
;
-
.*#c~J~~j
m
-
mIFE
- -
V
-
-dwg~
SbfL*UtWa
N
WIen
g
0
-~~i~aw
1
bIW
M
-'
IAa.LE
N
3 Jeilometars
Figure 3-2: Site B illustrates the watershed area, downstream of Huai Hin Khao reservoir. Its
boundary concides with that of Wat Mongkol Chaipattana Development Study Center. Pimsan
farm is shown in a red star on the south border of the Royal Study Center.
30
the pond comes from runoff from adjacent farms supplied by the Huai Hin Khao system.
However, this issue is not important to our study because we only evaluate the feasibility
of an on-farm impoundment which captures runoff generated within the farm boundary.
If the pond system is feasible in the absence of supplemental irrigation, additional runoff
will add extra benefit to the system.
Physical characteristics and cultivation practice serve as inputs to our computer model,
which combines hydrologic model and crop simulation program.
3.2
Soils & Surface Topography
The farm and the Royal Projects site are on the northeastern edge of an extensive rice-growing
region or the Noi-Lopburi floodplain, approximately 8 km north of the main district of Saraburi
Province.
The watershed area of our study site occupies roughly 4.3 square kilometers; this
area is shown as site B in Figure 3-2.
Huai Hin Khao reservoir (14'36'N and 100'55'E) was
constructed in 1995 to collect runoff from the catchment area and limestone outcrops.
The
area further north of the Royal Study Center has somewhat different soil and is devoted mostly
to maize cultivation. From our interviews with local farmers, the area grew almost entirely rice
until the last decade when some farmers changed to maize for animal feeds in order to avoid
the adverse effects of dry spells.
The area is relatively flat with slopes of less than 30, except for scattered limestone outcrops
up in the north. It is situated approximately 15 meters above mean sea level (MSL).
The basic soil group is quite uniform across the Royal Study area.
suitable for transplanted paddy rice as the infiltration loss is quite low.
It is sandy clay loam
Low in organic matter
and soil nutrients, the soil is prone to waterlogging and seasonal flooding during the wet season.
The soil is categorized as Khao Yoi Series. Soil properties for the area in the Study Center
around Wat Mongkol Chaipattana is shown in Table 3.1.1
Both soil layers are slightly basic.
'Electrical Conductivity (EC) is water's ability to conduct an electrical current and is directly related to the
concentration of dissolved salts. The greater the EC, the more dissolved salts are present in solution.
Cation Exchange Capacity (CEC) is an indication of the number of exchange sites within a soil that may
temporarily hold positively charged ions. It is generally determined by the amount and type of clay and the
amount of organic matter.
31
Low cation exchange capacity (CEC) indicates inefficiency of chemical fertilizers and thus, lower
crop productivity
Depth from surface
pH
EC at 25 0 C
Organic Matter
P
K
CEC
Bulk Density
Particle Density
Porosity
[millihos]
[%]
[ppm]
[ppm]
[me/100gm]
[gm/cc]
[%}
0-1 m
below 1 m
7.6
0.113
1.24
2
20
9.5
1.78
2.17
34.32
7.8
0.075
0.64
1
15
6.5
2.36
2.17
13.56
Table 3.1: Source: Department of Agriculture and Royal Irrigation Department, Ministry of
Agriculture and Cooperatives
3.3
Water Resources
Water in the pond has ph = 7.5 because the lower soil layer (below 1 m) originates from
Calcareous soil. The level of calcium contamination in pond water is insufficient to be a hazard
to plant production and fishery.
Farms in the Study Center replenish their pond through a
pipeline network from Huai Hin Khao reservoir.
located uphill of the area.
Gravity does the work as the reservoir is
Nevertheless, our study area in practice is not directly connected
to the network. The pond captures in situ rainfall as well as runoff generated near and on the
farm.
The watershed in Site B of Figure 3-2 appears to be in an area where the clay is primarily
underlain by a layer of sandstone/shale/quartzile which has some interbedded layers of limestone.
There are also some regions with a marl deposit.
These marl and sandstone layers
range from 50 to 100 meters thick. Beneath these layers there is an extensive limestone deposit
which outcrops in isolated regions. The limestone is shown to extend at least to about 200 m
below the ground surface.
Further south-near Wat Mongkol Chaipattana and our study site,
To look at a larger region than the boundary
the marl and the sandstone layers are absent.
of Site B, the big area seems like a limestone bowl, which is filled in by other deposits in our
study site [6].
32
Hand-dug ponds can reportedly reach no deeper than 4-6 meters due to a limestone layer
which lies near the surface.
Local groundwater is inappropriate for crop use due to high
contamination of heavy metal elements and low yield.
the legal issues surrounding groundwater regulation.
Further complicating the matter are
The usage of groundwater for irrigation
Users are granted an entitlement to pump a
is regulated through a well licensing system.
fixed volume of water per year. However, since the pumped amount is difficult to monitor, the
groundwater system is at high risk of overuse. In addition to the common pool problem, the
fear that high usage of well water upstream may lead to the flow of saline groundwater into
downstream regions, particularly the Bangkok area, has put a moratorium on the issuing of
new pumping allocations.
3.4
Meteorological Profiles
Agroclimatological data was obtained from two closest stations operated under Meteorological
Department: Muang District, Saraburi (station 414001, 14'31'N and 100'56E and Phu Khae
Botanical Garden (station 414012, 14 0 40'N and 100'55E). Daily series are available for 46 years
(1952-1997) of rainfall; 17 years (1982-1998) of Class-A pan evaporation; 38 years (1961-1998)
of temperature.
The area has average annual rainfall of 1200 - 1400 mm with high variation
during wet seasons as shown in Figures 1-1 and 1-2.
The average number of rainy days is
84. Annual pan evaporation is slightly greater than the amount of annual precipitation. Like
rainfall and solar radiation, temperature shows an obvious seasonal cycle; this characteristic is
typical of monsoonal tropics. The wet season typically starts in June and lasts until November.
The monthly precipitation and pan evaporation are shown in Figure 3-3. Solar radiation during
the monsoonal period naturally drops due to cloudiness.
3.5
3.5.1
Agricultural Practices
Types of Crop
The type of crop that can be grown is constrained by the soil's nutrients. Rice seems to be a
prominent commercial crop in the study area since it is not as adversely affected by poor soil
33
30C
average pan evapora >
-
=
7waverage rainfall
250
200
00x0
-150
100-
50k
O'L0
J
F
M
A
M
J
J
A
S
0
N
D
Figure 3-3: Average monthly rainfall and Class-A pan evaporation in Saraburi Province.
34
40
+
average temperato
35-
30k
0
++
CD
)
a)
+
+ I
25-
20k
151
J
F
M
A
M
J
J
A
S
0
N
Figure 3-4: Maximum and minimum temperature at the study site.
35
D
nutrients as other cash and field crops [52].
However, as farmers have applied more fertilizers,
the nutrient constraint has naturally reduced. The area further north of the Royal Study Center
has somewhat different soil and is devoted mostly to maize cultivation.
From our interviews
with local farmers, the area grew almost entirely rice until the last decade when some farmers
changed to maize for animal feeds in order to avoid the effects of dry spells.
In this section,
we will discuss each important crop cultivated in this area and the time schedule for planting
and harvesting.
Lowland Rice
Rainfed lowland rice grows in a bunded fields that are flooded for at least part of the cropping
season to water depths that may exceed 50 cm for no more than 10 consecutive days. Rainfed
lowlands are characterized by lack of water control, with floods and drought being potential
problems. Adverse climate, poor soils, and a lack of suitable modern technologies keep farmers
from being able to increase productivity.
Currently, yield constraints for rainfed lowland
rice include frequent drought and flood, soil properties, diseases such as blast and bacterial
blight, and insect pests like gallmidge and stem borers. The current breeding objectives are to
develop cultivars that are tolerant to adverse environmental conditions and resistant to disease
and insects, while maintaining the superior grain characteristics of the traditional cultivars
and their appropriate maturity characteristics [53].
The most common cultivar for domestic
consumption and local market in the Central Plain is non-glutinous RD7 while that for export
is fragrant Khao Dawk Mali (KDML) 105. Since our study area mostly consists of small-scaled
farmers, very few of them grow rice for export.
Transplanting and direct seeding are the two primary methods of growing rice. For transplanting, seedlings are first grown in a seedbed for a month while the main fields are being
ploughed along the bunds surrounding each paddy.
When each field has been prepared, the
seedlings are pulled from the seedbed and then transplanted in the field by hand.
In broad-
casting, seeds are sown directly in an upland field or lowland paddy. In upland fields, seeds are
sown only by dibbling on dryland preparation. The reasons for changing from transplanting to
broadcasting are (1) to save time and labor cost, and (2) to avoid the adverse effects of drought
during the transplanting period.
36
Without irrigation, farmers wait for heavy rains to puddle the land before they transplant
seedlings, no matter how long rains are delayed. If the heavy rains do not come, the rice farms
are either not planted at all or the crop may fail after transplanting to dry soils.
To avoid
the problem of transplanting in dry soils, farmers may change to the dry-seed broadcasting at
the beginning of the rainy season or during the dry period.
If the crop fails due to adverse
conditions, reseeding is easier and less costly than retransplanting [37].
Most farmers prefer
the transplanting method. Transplanted rice usually yields higher productivity due to more
control over seedlings. Irrigation allows farmers in water-deprived areas to choose transplanting
methods.
Rainfed lowland rice ecosystems may be divided into five subecosystems:
(1) favorable
rainfed lowland, (2) drought-prone, (3) submergence-prone, (4) drought/submergence-prone,
and (5) medium-deep water. Technologies for the irrigated rice sector can be applied in both
the favorable rainfed lowland and drought/submergence-prone subecosystems. Our study area
belongs to drought/submergence-prone subecosystem.
Farmers can control their transplanting or broadcasting time if irrigation water is available,
regardless of the onset time of the rainy season. Lowland rice is grown mainly during July to
November as illustrated in Figure 3-5. Broadcasted rice matures approximately the same time
as transplanted rice. The second line in Figure 3-5 indicates broadcasted rice. Harvesting for
lowland rice generally starts in November. Upland rice is primarily planted by the broadcasting
method, which starts in June. With its maturity 50-day longer than that of lowland rice, upland
rice is harvested in December for 2-3 weeks.
Perennial Trees
From our field surveys, most farmers in the area keep a small orchard of perennial fruit trees:
banana, mango, and papaya 2 . Few orchards grow only one variety, while many keep a combination of many types of fruit even though the orchard area is usually small.
The produce is
largely for domestic consumption. In case of an abundant harvest, production excess is sold on
the spot. Since most farmers grow similar varieties of fruit, the price is normally low in years of
2Besides the three major fruits, examples of fruit trees and perennial plants observed in Saraburi area are
tamarind, jackfruit, sapodilla, orange, custard apple, santol, sesbania (Sesbania grandiflora), horseradish, neem
tree, and cassod tree.
37
JAN
FEB
MAR
APR
MAY
JUL
JUN
AUG
SEP
OCT
NOV
DEC
Upland Rice
Lowland Rice
L owland Ric
,,
..-
'Field Crop & Vegetabl_
Crop &VgSeedling growth
z
Growing period
Harvest
Figure 3-5: Crop pattern suggested by Praputthbaht Field Crop Experiment Station, Dept. of
Agricultural Extensions in Saraburi Province. The parallelograms represent farmer's adjustment to weather conditions.
abundant yield due to oversupply. As the orchard is not their prime source of income, farmers
rarely tend it or invest in fertilizer application. Therefore, irrigation for orchards mainly relies
on small shallow ditches surrounding each plot. These capture runoff from rainfall in excess of
infiltration and evapotranspiration, instead of diverting water from ponds or nearby canals.
Cash crop - flowers & vegetables
Local farmers who practice wet-rice agriculture in valley bottoms also cultivate vegetable gardens, mainly for domestic consumption.
late January and harvested in May-June.
Beans, corn, and native vegetables are planted in
Garden vegetables and herbal plants are gaining
more significance as a prime source of income for some households.
This option requires en-
trepreneurship and intensive labor as garden crops require considerably more care than field
crops or rice.
Research and promotion is much needed to find garden crops suitable for the
area's conditions and marketing infrastructure.
38
3.5.2
Irrigation System
The lowland communities in central Thailand have developed an agricultural system adapted
to, and partially determining, the distinctive ecosystems of their areas.
Water harvesting is
combined with well-selected crops to ensure sufficient water.
Farmers follow methodical rules of water harvesting for rice fields so long as there is enough
water to sustain the system. The seedbed occupies a very small plot of land with a water level
of 2-4 cm. After transplanting, the depth of water in the paddy is maintained at least 4.5 cm.
The bunds surrounding paddy plots are 12 cm in height. Excess water spills to the surrounding
ditches.
When the ditches run dry, water from the pond is diverted to the paddies.
If both
the pond and rice ditch system are full, the excess water is spilled off-farm (down-gradient.)
Farmers stop watering during the harvest period.
39
Chapter 4
Methodology
The model we use to determine the feasibility of the on-farm reservoir technique is divided into
three separate modules: HYDRO, CROP, and UTILITY. This Chapter begins by showing how
the hydrologic model (HYDRO) is integrated with the crop simulation program (CROP), and
then explains a formulation for each of the two modules. The coupled HYDRO-CROP system
provides simulated rice yields for a specified irrigation system and meteorological history. The
yield results are used in UTILITY to evaluate the utility provided by the farming enterprise.
4.1
4.1.1
Overview
HYDRO-CROP Integration
All three modules are bundled together as illustrated in Figure 1-5.
However, the first two
modules-HYDRO and CROP-operate simultaneously and deserve a special attention to understand the flow of information between them. Figure 4-1 shows input data and interactive
processes within the two modules.
The crop simulation program (CROP) relies on meteorological data series, soil properties,
plant variety, and agricultural management information.
In the diagram, the irrigation rule is
separated from other management practices because it is adjusted during the model convergence
process, which is carried out manually. In this study, transplanted rice is the only crop; CROP
uses the CERES-Rice model included in DSSAT to simulate crop development.
Section 4.3
discusses the simulation process in more detail. With all the required data, the model simulates
40
Weaiher
Gul~varPond
storage
fluxes and
FM
storages
Havesti..ngI
~Irrigation
Default
irrigation
maaeetor
reaclustment
og
irrigation?
Figure 4-1: Interaction between the crop simulation program (CROP) and the water balance
analysis (HYDRO). The final output produced by the HYDRO and CROP modules is simulated
yield per unit area.
grain yield of rice for each cropping season.
In addition, the crop simulation computes daily
water requirement for the specified irrigation rule.
Fluxes and storage values derived from CROP are passed on to an quantitative water balance
analysis model, called HYDRO. The required meteorological inputs for HYDRO include daily
series of Class-A pan evaporation and precipitation. The crop's evapotranspiration is calculated
in CROP. The hydrologic module calculates on-farm water storage in the pond and in ditches
surrounding the rice fields and indicates whether there is a water deficit for every daily step.
If the water remaining in the pond and ditches is not sufficient to support the irrigation rule
specified in CROP, this irrigation re-adjustment rule is manually changed, the CROP and
HYDRO modules are rerun, and the water deficit is checked again. We repeat the entire cycle
until the irrigation rule is satisfied and mass is conserved (i.e. until the simulation converges).
The final result is a simulated grain yield which satisfies the modified irrigation rule without
exceeding daily water supply.
It is important to note that uncertainty in simulated yields
results directly from meteorological variation.
41
4.1.2
Model Validation
An important facet of the modeling precess is to apply appropriate statistical tests to evaluate
model accuracy.
Dent and Blackie (1979) suggested a t-test to determine whether the slope
and intercept of linear regression between model simulated and observed values are different
from unity and zero.
Willmolt (1982) contended that although the model is less sensitive to
extreme values, bias (Equation 4.1) and root mean square error (RMSE) (Equation 4.2) which
provides the "best" overall measures of model performance.
1
Bias
N
(Si- Oi)
1N
RMSE
=
(S, - Oj)2
(4.1)
(4.2)
where Si = simulated value, Oi = observed value, and N = number of observations.
Graf et al. (1991) used a standardized bias (R) (Equation 4.3) and a standardized mean
square error (V) (Equation 4.4) to test goodness of fit and evaluate visual comparison simulated
data corresponding with observed data for dynamics of rice production.
N
E (S -0)
R
=
(4.3)
N
zoi
i=1
N
E (Si
V
-
0)2
(4.4)
= =1N
1
0?
i=1
Where N
number of field observation, Oi and Si are observed and simulated values,
respectively. At the ith observation R and V are estimate for the overall error of the method
with regard to field data.
pattern.
R quantifies the model's ability to reproduce the observed yield
Negative deviations (Si - Oi < 0) compensate for positive deviations (Si - Oi > 0)
and vice versa (Equation 4.3).
On the other hand, V is a measure that reveals the model's
42
tendency to generally overestimate or underestimate simulating field observation.
However,
both procedures give heaviest weighing to large values.
For the HYDRO-CROP model to be properly validated, the simulation results need to
be tested against observed data. We validated the simulated yield results from the HYDROCROP model by using experimental results from Praputthabaht Field Crop Experiment Station,
Saraburi Province.
The experiments were conducted from 1989 through 1994 during the wet
season under irrigated conditions.
For the rainfed condition, we gathered historic data on
average aggregate rice production in the non-irrigated areas of Saraburi and Lopburi Provinces,
reported from 1985-1995.
We performed a number of statistical tests to compare simulated
and real-world data. Bias and Root Mean Square Error (RMSE) in Equations 4.1 and 4.2 also
used as measures of model performance. In addition, goodness of fit was evaluated visually and
by computing a standardized bias (R) and a standardized mean square error (V); the formulas
are given in Equations 4.3 and 4.4. The results of these are discussed in Chapter 5.
Mankeb (1993) calibrated the genetic coefficient for rice cultivar RD7 by using data from
yield trial experiments which used RD7 from San Pa Tong Rice Experiment Station, San Pa
Tong, Chiangmai Province (18'37N and 98'54'E). Date on weather, soil, nitrogen fertilizers,
irrigation data and management practices were entered into the CERES-Rice model.
The
minimum requirement for daily weather data includes solar radiation, rainfall, maximum and
minimum temperature. Simulated and observed tiller numbers [m- 2], LAI, and above ground
biomass were compared to assess the model's ability to predice rice growth over time.
The
accuracy in predicting the phenology of selected rice cultivars in Thailand's condition was
statistically acceptable [34].
4.1.3
UTILITY
The final issue we consider in our simulation is the welfare or utility provided by on-farm water
harvesting and irrigation system.
Utility function notation may be used to describe how the
farmer values the yield obtained from a rice farm.
Generally, higher income means higher utility.
However, revenue can vary depending on
rainfall and other factors. This variability subjects the farmer to risk. Some years income may
be lower than average and some years it may be higher. A risk-averse farmer maximizes his
43
expected utility; he sacrifices high income in order to reduce variability and risk.
Our study
Few of these farms have enough savings to
analyzes a typical small subsistence rice farm.
smooth out their consumption during financial shortfalls caused by low agricultural productivity. Income generated from rice production is devoted mainly, if not all, to consumption and
agricultural inputs. We can compare the expected utilities of consumption from both irrigated
and rainfed cases. If utility from the irrigated case is greater, the pond is welfare improving.
In practice, a pond incurs maintenance as well as operational costs (for instance, electricity
for pumps.)
The UTILITY module, in addition to assessing impacts of the on-farm pond on
farmer's utility, estimates the maximum cost which the farmer is willing to pay to maintain the
pond.
Sensitivity and break-even analyses help to identify the extent to which the on-farm
pond scheme is a sound investment for a typical farmer in our study.
4.2
4.2.1
Hydrologic Models - HYDRO
Concept
The purpose of this submodel is to investigate the possibility of supplying small on-farm ponds
exclusively with water harvested from runoff generated within the farm boundary. The concept
is to divert local runoff to the pond and to rice paddies and ditches, where it is stored for
later use.
McLaughlin et al.
(1999) tested the New Theory project in Saraburi Province
and suggested that it is indeed possible to grow a reliable rice crop in the Saraburi region
without supplemental water from a large reservoir.
The report provides a quantitative water
balance analysis of on-farm water harvesting; which serves as a fundamental framework for our
hydrologic model (HYDRO) in this study. Note that our earlier study did not look into the
effect of the pond on crop yield or into the economic feasibility or risk [35].
4.2.2
Farm Configuration
HYDRO keeps track of water entering and leaving the pond and surrounding ditches in a riceonly farm.
This is illustrated in the simplified sketch of Figure 4-2.
The arrangement and
relative sizes of different land uses (i.e., non-farming, pond, paddies, and ditches) are similar
to those found in local rice farms in Saraburi.
The rice paddy is excluded from HYDRO since
44
paddy fluxes are computed by the crop simulation model (CROP).
I
itcheg
/
Rice/pond
spills
pond
housing
Irrigation
Runoff from
paddy
I
II
Tb
rice paddy
II
rice paddy
rice paddy
'I
01*
/
4-W,.
Off-farm
(down gradient)
Figure 4-2: Plan view of model farm showing rice paddies with surrounding ditches.
represent important horizontal fluxes.
Arrows
In order to understand the movement of water as shown in Figures 4-2 and 4-3, we should
begin during harvesting time when the water left in the paddy area is diverted to the pond.
In the following dry season, the paddy is kept fallow and parts of the surrounding bunds are
breached to allow water to drain out.
Precipitation on the paddy during the fallow period is
partitioned into infiltration, evaporation, and runoff to ditches which encircle the rice fields.
Ditches receive water from both runoff and rainfall, and lose water to evaporation and infiltration. If ditches are filled, though not likely in the dry season, water will spill over to pond. The
pond captures water from runoff generated in the non-crop area, precipitation, and spills from
ditches in addition to the water diverted from rice paddy during harvest. The pond loses water
to evaporation and infiltration. In most years, the pond can maintain some depth throughout
45
Pond and Non-crop Area
Precipitation
Evaporation
Rice irrigation
Runoff from
non-crop area
Spills to and frcm rice
ditches
*4m
I
_Pond storage
V
4
Groundwater
recharge
Rice and Rice Ditches
Precipitation
Spills from
paddy
Evaporation
frrigation
from pond
Spills to and from
pond
Q
irrig ation
fro n ditches
Puddle
30 cm
Ditch
storage
I
Paddy
Groundwater recharge
Figure 4-3: HYDRO farm configuration: Vertical cross-sections through pond and rice paddy
water storage compartments showing fluxes into and out of each compartment.
46
the dry season.
The monsoon can come as early as late April (Figure 1-2).
The pond starts to collect
water and almost reaches its full capacity at the onset of the rice growing season.
According
to local practice in rice cultivation, the bunded paddy is maintained at a depth of 45 mm while
the bund is 120 mm high. Whenever the paddy depth falls below the minimum level, farmers
pump water first from ditches and then from the pond as the last resort.
This operational
rule is followed throughout the growing season; it is violated only when the combined water in
the pond and ditches is insufficient to maintain the desired water level in the paddy.
When
pond and ditches are both full, the excess water spills off-farm. Finally, water is drained from
the paddy to the pond at the end of the growing season to prepare for harvesting. The entire
routine then comes to full circle.
4.2.3
HYDRO : Inputs and Outputs
Inputs for the hydrologic submodel (HYDRO) can be categorized into three sets. First, HYDRO requires daily weather information such as precipitation and pan evaporation.
These
meteorological data are also shared with the CROP module. Next are water inflows and outflows computed by CROP. These include (1) surface runoff from the non-crop area; (2) spill
from the paddy; and (3) water required for irrigation to maintain the specified operational rules.
The third set of inputs is the land use allocation.
We assume a fixed ratio of paddy to ditch
areas and a fixed area allocated for housing and walkways (non-crop.)
The pond can vary in
size. Evaluation of performance for each pond size entails a separate HYDRO run.
HYDRO records daily storage in the pond and ditches under the default irrigation rule.
The HYDRO submodel automatically indicates whether water stored in the pond and ditches
is enough to sustain the irrigation rule for every daily step.
If a water deficit occurs the
irrigation rule must be modified and both HYDRO and CROP rerun, as discussed in Section
4.1.1.1
1
HYDRO was written in MATLAB language; the codes are shown in Appendix A.
47
Crop Simulation Program - CROP
4.3
One application of crop simulation programs is to enable policy makers, farmers and other
decision makers to assess the consequences of actions today on outcomes in the future.
By
allowing users to explore the future, a model enables them to choose those actions which are
more likely to produce desirable outcomes.
Here, crop simulation allows us to predict grain
yields under irrigated as well as rainfed conditions by controlling all other factors.
Many
crop simulation programs are available commercially for agricultural research and development
projects. Here we describe the crop simulation package used in this thesis; then we discuss our
experiment file CROP, set up in DSSAT format, which simulates the potential values of the
on-farm pond investment.
4.3.1
DSSAT Software
Decision Support System for Agrotechnology Transfer (DSSAT) is a collection of crop models
and computer programs integrated into a single software package in order to facilitate the
application of crop simulation models in research and decision making.
This software is a
product of the International Bench-mark Sites Network for Agrotechnology Transfer (IBSNAT)
project and is widely used in agricultural planing and agronomic research. The DSSAT system
consists of several components: (1) crop models; (2) soil and weather data; (3) collaborators'
experimental data; and (4) application programs to enter and retrieve data, link the models
with site and experimental data files, and analyze the observed and simulated data for specific
objectives.
Figure 4-4 illustrates the linkage between the crop model and the collaborator
experiment, weather, and soil data; and the programs for providing graphical outputs and data
analysis results to collaborators.
The input and output files for crop models in DSSAT are arranged to facilitate comparisons
with field data and sensitivity analyses. For example, different weather, soil, cultivar, planting
date, irrigation management, row spacing, and fertilizer management can be changed.
Simu-
lated results can then be plotted from any of the runs for comparison with real experimental
treatments or for evaluation of hypothetical treatments [24]. The crop model of interest here is
48
CERES-Rice 2 , which is a part of DSSAT and has been tested over a wide range of environments
by the IBSNAT and its collaborative institutes.
The CERES-Rice was developed by International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT) [47] and modified for transplanted rice by researchers at the International Fertilizer Development Center (IFDC) [20].
The model can simulate the yield of
different rice varieties for different management and agroclimatic scenarios.
The following are
the main processes simulated in the model:
" Growth and development.
" Biomass production and partitioning
" Root system dynamics
" Effect of soil water deficit and nitrogen deficiency on the photosynthesis and photosynthate
partitioning in the plant system.
" Water and nitrogen budgets at the surface and in the root zone
The model assumes that growth limiting factors such as weeds, insects, diseases, and nutrient
deficits are completely controlled.
CERES-Rice requires the following inputs:
* Daily weather, at least for the duration of the cropping season, which includes solar
radiation, maximum and minimum air temperature, and precipitation
" Soil initial conditions and properties
* Management practices such as cultivar, plant density, planting date, irrigation, and fertilization
" Latitude of the production area to evaluate day length during the cropping season
" Variety-specific coefficients that account for differences in the response of different genotypes to environmental factors.
2
CERES is an acronym for Crop Environment REsource Synthesis.
49
Data Generating
Soil
Characterization
Collabordors
Collaborators
I
I
Expe ,mon,
SUrriMWY
D
Crop-Soil
Modeling
Collaboraors
I
-*p
4
|CropMode,
11v
-oCollaborators
Figure 4-4: Elements of the Decision Support System for Agrotechnology Transfer (DSSAT)
50
4.3.2
CROP : Experimental Setting
The CROP submodel is actually a collection of CERES-Rice inputs.
CROP simulations are considered in this thesis: (1)
Two different types of
rainfed cultivation and (2) pond-based
irrigation. Rice is cultivated in a paddy setting with the same cultivar, soil properties, weather,
and other crop managements in each scenario.
DSSAT allows us to carry out simulations
of crop sequences which alternate between rice and fallow conditions.
CROP keeps track of
soil moisture depletion during this sequence, rotating through 35 years (1961-1995) of actual
weather data.
4.3.3
CROP : Inputs and Outputs
In our simulations, all CERES-Rice inputs are based on data from the Saraburi study site.
According to Somrith (1996), the most popular rice genotype grown in this area is RD7. The
genetic coefficients for RD7 were calibrated to fit actual experiments for paddy rice in Thailand
by Mankeb (1993).
Crop management inputs such as planting date, fertilizer application rates
and harvesting date also follow local practice.
Figure 4-5 shows the cultivation and growth
stages for our case study. High fertilizer inputs are imposed to ensure that growth of stressed
plants was depressed by drought only. A basal application equivalent to 100 kg N, 40 kg P,
40 kg K ha- 1 , is mixed into each plot one day before transplanting.
sulphate equivalent to 60 kg N ha'
N at flowering.
Additional ammonium
is added at mid-tillering and panicle initiation and 40 kg
Harvesting is set at 100 days after transplanting to allow room for delay in
maturity for some dry years.
CROP produces four major outputs: (1) dates describing phasic development or growth
stage duration, (2) biomass production, (3) water and chemical balances, and (4) water and
chemical deficits. Water fluxes and storages are used to primarily determine the convergence of
the HYDRO-CROP integrated model. The converged HYDRO-CROP model delivers a series
These yields per unit area are then translated
of simulated annual yields for each pond size.
into total yield by multiplying by the paddy area, which is equal to total land holding area less
housing and pond.
Therefore, a farmer faces revenue loss for each unit of land he allocates
to the pond. On the other hand, his increase in revenue from higher yield per unit area may
sufficiently offset or even exceed that from the loss of cultivation land due to the pond.
51
panicle
initiation
seedling
25d
27d
maturity
flowering
34d
29d
harvesting
transplanting
GROWTH
STAGES
PLANTING
N fertilizer applications in paddy
Figure 4-5: Timeline for rice planting processes with respect to growth.
phasic development is averaged over 35 simulated cropping seasons.
The period of each
With results from HYDRO-CROP run, we can plot average yields vs. pond size.
Once
a proxy pond size is selected, two series of annual yields-one from an irrigated plot and the
other from a rainfed plot-are passed on to UTILITY which transforms yield to farmer's utility
(see diagram in Figure 1-5.)
The recommendation is then made about the adoption of this
on-farm surface storage. The sensitivity and break-even analyses will be discussed in the next
section.
4.4
3
Utility Evaluation - UTILITY
Economic theory states that an individual acts to maximize his utility or welfare. The farmer's
utility in our case depends on crop revenue and his attitude toward risk.
We can estimate
crop revenue from crop yield and the local market price of rice. Income in its own right gives
no direct utility. It is rather only when this income is spent on consumption goods that any
utility results.
Our surveys indicated that the farmers in our study area barely keep saving
accounts and devote most of their income to consumption.
For this reason, consumption and
income are essentially equivalent in our study.
Farmers are perceived to be risk averse.
That is, they are willing to accept less income in
order to avoid risk. In the context of agriculture, farmers are willing to invest in water storage
infrastructure if such investment can sufficiently reduce the uncertainty of crop yields.
3
Details of the CROP submodel are given in Appendix B.
52
4.4.1
Constant Relative Risk Aversion
We need to assume the nature of the farmer's attitude toward risk in order to see how he
trades off between risk and income. Economists make frequent use of the constant relative risk
aversion (CRRA) function, which describes how utility (U) depends on revenue (R)
U(R) =
.
(4.5)
1 - -Y
The degree of curvature of this function is determined by the value of -y. The more curved
the function the more the farmer is willing to pay to insure against risk.
The coefficient of
relative risk aversion is defined as the percentage change in the marginal utility of income or
consumption arising from a one percent change in the level of income or consumption, i.e. it is
equal to the following expression:
S
RU R)
(4.6)
U' (R)
If y
=
4.4.2
0, then U(R) is linear and the farmer is said to be risk neutral.
Expected Utility
We are considering evaluation of the mean utility when the revenue is a random variable. Any
differentiable utility function U(R) can be expanded about the mean revenue as follows:
U(R) = U(R)
OU(R)
OR
-
(R -R ))
8 2 U(R)
R
(R -R)
2
2
(4.7)
Equation 4.6 can be substituted into this expression and higher-order terms can be truncated
if the revenue is Gaussian with a sufficiently small variance. The mean utility is then:
U(R)
2
=U(R)
=
=
OR (R2
2
O U(R) 0.2
R
R
U(R) +
OR 2
2
U'(R) 0.2
U(R) - Y
R(4.8)
2
R
53
U(R)
(R - R)2
2
-
-7y
1-
R
2
2
=
R?
~-
-(4.9)
Since U'(R) in Equation 4.8 is always positive, this expression shows that mean utility is reduced
by a factor proportional to a2, the variance of the revenue.
This variance is often called the
income risk. As the income risk increases the farmer's average utility decreases. This effect is
greater for larger
7.
In our study, the on-farm pond increases the likelihood of sufficient water supply during
dry spells.
This lowers the income risk. When the farmer's risk measure (X)
likely to invest in an on-farm pond.
is higher he is
Of course, the pond also has a maintenance cost.
We
can disregard the construction cost for now as all pond construction is currently subsidized
by government agencies. This cost will be taken into consideration when we interpret results.
Factors relevant to the utility evaluation process include the price of rice production, the cost of
the pond, and the farmer's attitude towards risk (see Equation 4.9).
in the UTILITY submodel.
54
These are all considered
Chapter 5
Results
We now examine the results obtained by the methodology outlined in Chapter 4. To ensure the
accuracy of these results, we carry out a model validation by comparing our simulation outputs
with actual observations and with results from the literature.
We also assess the implication
of the simulation results for investment in the on-farm reservoir scheme.
The optimal pond
size is identified and we discuss the effect of a pond investment on the farming household.
Our results indicate that the on-farm water harvesting and storage strategy advocated in
the New Theory is technically and economically viable for a small-scale subsistence farm. We
perform sensitivity analyses to identify range of conditions for which the pond investment is
attractive.
5.1
5.1.1
Simulated Yields
Statistics
The HYDRO-CROP model produced simulated yields given 35 years of meteorological data,
crop and soil properties for both rainfed and irrigated conditions, for various pond sizes.
The
statistics of simulated yields, recorded in Table 5.2, indicate average yield per unit area increasing with pond size until the pond is expanded to 5% of the total area. As a typical land-holding
area of Saraburi farm households is 15 rail, or 2.4 hectare, a 5% pond requires 1200 square
'Rai is a Thai unit for land area. 1 rai is equal to 1600 square meters or 0.16 hectare.
55
meters of land.
This means an on-farm pond at 5% can adequately provide for the default
irrigation rule, specified in the HYDRO-CROP modules.
A 5% pond is used as the proxy size to represent the forecasted yields gained from the
on-farm scheme.
First, a 5% pond sufficiently provides for the default irrigation rule; which
means it maximizes expected yield per unit area.
larger area than 5% for a pond.
Secondly, a farmer should not allocate a
With a larger pond, he would forgo his precious cultivation
area without gaining higher yield per unit area.
His average revenue from rice production
immediately decreases as the marginal loss from smaller rice fields outweighs the marginal gain
from a pond. However, even if a 5% pond produces the highest expected revenue, it does not
necessarily maximize utility since it does not account for risk.
Figure 5-1 illustrates histograms of yield per unit area for both irrigated and rainfed plots.
These are derived from the sample of 35 years simulated for each alternative.
The dotted
lines represent a normal probability density fit to each histogram. The irrigated plot not only
generates a higher average yield, but also shows lower yield variability than the rainfed plot.
It follows that the on-farm reservoir scheme reduces risk on rice production.
This effect is
even more apparent in Figure 5-2a, which plots the two yield cumulative distribution functions.
Yields from the rainfed plot never exceed those from the irrigated plot and there are only a few
years that both plots give equal yield. Figure 5-2b shows the cumulative distribution function
of the increase in yield obtained when the on-farm reservoir is in place.
Note that one-fifth
of the 35 annual simulated yields exhibit no improvement in rice productivity.
Such events
occur in extremely wet growing seasons. In these years the paddy does not need supplementary
irrigation from the pond.
It is worth noting that these results consider only yield per unit area, not the total rice
production. The revenue from rice production will be discussed in section 5.2.
5.1.2
Model Validation
In terms of model validation, the rainfed case performed poorly but the irrigated case performed
exceptionally well.
The HYDRO-CROP integrated model overestimated grain yield across
years of available data by an average of 8.3% and 68.8% (bias of 471 and 2,048 kg/ha; and root
mean square error = 625 and 2,198) for irrigated and rainfed plots, respectively (Table 5.1).
56
7777
20
irrigate
15 C-,
Cr
10k
1
'4-
'.
5
00
0
-'9
.*
10F.
3000 3500 4000 4500 5000 5500 6000 6500 7000 7500 8000
kg/ha
20,
I
C3 rainfed
15C
C.
I
r
CD
5
0
.*0
*d-
3000 3500 4000 4500 5000 5500 6000 6500 7000 7500 8000
kg/ha
Figure 5-1: Histograms to fit normal distribution of yield: rainfed and irrigated rice farms.
57
1
A
0.81
0.61
LI.
0.4
0.2
-
C
3000
1
irrig ate<
rain fedl
3500
4000
4500
5500
5000
kg/ha
6000
6500
7000
7500
500
1000
1500
2500
2000
kg/ha
3000
3500
4000
4500
B
0.8
x
0.6
0.4
0.2
n
"0
Figure 5-2: A: CDFs of yield per unit area with and without irrigation.
increase with pond installation.
58
B: CDF of yield
Although both management alternatives (rainfed versus irrigated) exhibit positive deviations
(Si - Oi > 0) for all cropping season, the sharp difference in the magnitude of these deviations
is obvious in Figure 5-3.
Provided that all deviations were positive, V measures the model's
tendency to overestimate rice production.
The model's prediction performed more poorly in
the rainfed condition due to a potential downside bias of the observed data.
The irrigated experiments that we obtained from Praputthabaht Field Crop Experimental
Station used fertilizer inputs identical to our inputs for the CROP module.
Furthermore,
the rice plants were protected from pest and disease thanks to regular weeding and spraying of
pesticide. On the other hand, the large discrepancy between observed and simulated yield under
the rainfed condition appears to be a result of uncontrolled fertilizer application. Information
on rice yield from rainfed plots was adapted from aggregate rice production records from the
non-irrigated area of Saraburi and Lopburi provinces.
Although soil and crop properties and
planting/transplanting dates in the CROP module resembled the local practice, information on
fertilizer applications was not available and reportedly non-existent.
In addition, there was a
history of pests and diseases destroying rice production in parts of the survey area. For these
reasons, we can expect substantially higher estimates from the simulated data than from the
observed data.
In spite of these uncontrolled factors, the observed yields had a lower variation than the
simulated ones. Although the HYDRO-CROP simulation did not account for pest and disease
risk, the simulated result follows the same trend as the observed result. This is possibly because
soil nutrient limitation crippled plant development.
Since the simulation does not account for
these limitations it may be more sensitive to variability in rainfall, which the primary factor
controlling yield in the simulated case.
5.1.3
Yield VS. Pond Size
We separately ran HYDRO-CROP modules for different pond sizes; the simulation results are
reported in Table 5.2. At 5% of total area, the pond can provide the irrigation water required
for the default operation rule. Thus, there is no need to simulate for a larger pond. A larger
pond will only give yield as high as a 5% pond. Provided that there is no other benefits accrued
from pond (e.g., fishery), a farmer should not sacrifice more cultivation land for the pond area.
59
Irrigated
700c
Cu
0)
simulate
+
observej
600(
500
*0
a)
400
300c
5
I
86
I
87
I
88
I
89
90
I
91
I
92
I
93
I
94
95
91
92
93
94
95
Rainfed
700(
I-
Cu
-c
600C
0)
500C
*0
*13
400C
300(
200g
5
86
87
88
90
89
Year
Figure 5-3: Simulated and observed grain yield for irrigated and rainfed condition.
60
Figure 5-4 illustrates an attempt to fit a continuous curve to average yields obtained for several
different pond areas. As the average yield approaches the maximum level, a saturation function
of the following form seems appropriate for curve fitting:
2
Y = (Ymax - Ymin) - (1 - e ax ) + Ymin
where
x
a percentage of pond over total area
Y
rice yield per unit area
(5.1)
Ymax = 6, 123 kg/ha
Ymin = 5,277 kg/ha
a = 0.155.
This continuous curve is useful for the sensitivity analysis in section 5.3.
5.2
Implications for Investment
Now that we can forecast reasonably accurate yields from actual meteorological data, we can
judge the attractiveness of on-farm pond investment.
In order to do this, we need to consider
all parameters involved in utility maximization: (1) the rice price, (2) the optimal pond size,
(3) the farmer's risk aversion measure, (4) pond construction and maintenance cost, and (5)
the revenue required for subsistence.
The price of rice production is necessary for translating
rice yield into revenue. For practical purposes, the optimal size of an on-farm pond is chosen
for a typical rice farm in the study site.
The risk aversion measure can be estimated from
observations of farmers' behavior. Construction and maintenance costs can be amortized over
the time horizon of the pond's usage.
Subsistence constraint is defined as the income level
sufficient to sustain a household.
5.2.1
Price of Rice Production
The price of unmilled rice varies depending on existing supply in the market as well as on
proximity to a higher-priced market. In most cases, small-scale farmers sell their rice production
to the local millers because the transportation cost to town markets exceeds potential profit
gain [50].
Despite possible fluctuations of the rice price across time, we want to keep hydrologic
61
620C0
610C
alpha =0. 155
600C
CU
.-
5900
0)
CU
5800
_0
a)
5700
560C
5500
5400
5301
1
2
3
5
4
6
7
8
9
10
pond size %
Figure 5-4: Plot of yield per unit area versus pond size from our model simulation.
continuous curve fits the plot with respect to equation 5.1.
62
The
variability as the focus of our study. Consequently, we assume a constant price.
Rice was sold to local millers at 4,300 baht per metric ton for Saraburi province in 2000
under the guaranteed price regulation which is still in effect today [23].
That is, farmer's
income from rice production is guaranteed at 4.30 baht per kg unmilled rice. This is the price
used in our analysis.
However, an IRRI document stated that before devaluation of baht in
1997, the farm price was 4,800 baht per ton and after, 7,600 baht [26].
From our interviews
with local farmers in 1999, farm price ranged between 4.30 and 5.00 baht per kg of unmilled rice
depending on the market supply. During a high production season, the price of rice, like other
commodity goods, tends to be at the lower range.
Thus, we choose the lowest price possible
(4.30 baht per kg) to estimate the lower bound of price range at which the pond scheme is
economically feasible.
5.2.2
Optimal Pond Size
The average size of land holding areas for subsistence farms in Saraburi province is 15 rai, or
approximately 2.40 hectares. Housing and roadways cover 5% of total land; whereas, ditches
surrounding the paddy fields constitute approximately 5% of the total cultivation land left after
subtracting non-crop area.
Hence, the paddy area listed in Table 5.2 is calculated using the
formula:
A
=
(95
-
x)
100
100
where x is the percentage total land holding area devoted to pond
2.4 x 0.95 x
(5.2)
For the rice price specified above, expected yield estimates from Equation 5.1, and paddy
areas from Equation 5.2, we can plot a continuous curve of average revenue from rice production
as a function of pond size (see Figure 5-5). The maximum revenue under the on-farm reservoir
investment from our calculation is approximately 54,000 baths per rice season. The optimal
pond size, corresponding to the highest expected revenue, for a typical 15-rai rice farm is 4.22%
or 0.63 rai.
As discussed earlier, a farmer values both average income and low income variance.
63
The
5.x
5.4-
0
u
5.3-
Cl)
0.
0
S5.2-
5.10
5x*= 4.22%
"0
1
2
3
6
5
4
7
8
9
10
pond size (%)
Figure 5-5: Average revenue with respect to pond size.
curve.
64
Optimal pond size is at the peak of
coefficient of relative risk aversion (-y) estimated by Paulson and Townsend (2001) for households
similar to those in our study area is y = 0.671. The relationship of expected utility of revenue
U(R) for this value of -y is plotted versus pond size in Figure 5-6.
The utility-maximizing
pond is slightly bigger than the revenue-maximizing pond due to the effect of lower revenue
variability with a larger pond. The optimal size is 0.645 rai, or 1,032 square meters. However,
when we ran a HYDRO-CROP simulation with a pond size of 4.30%, the simulation result
yields a lower average utility than that of a 5% pond (see Table 5.2.)
A blue square in Figure
5-6 corresponds to the expected utility of a 4.30% pond, which is significantly lower than the
value estimated from curve. Accordingly, the optimal pond size lies somewhere between 4.30%
(1,032 M 2 ) and 5% (1,200 m2 ).
For simplicity, we choose a pond size of 5% as our candidate to represent the on-farm pond
alternative. We can then carry out a detailed comparison between performance with this pond
size and performance with no pond.
5.2.3
Risk Aversion
With a pond of the optimal size of 1,200 square meters, we can use our HYDRO-CROP model
to forecast yields for 35 years of actual weather data. After translating into baht terms, the
revenue probability density and cumulative distribution functions are plotted in Figures 5-7
and 5-8a, respectively.
In a few high rainfall years the rainfed alternative actually provides
higher yields and utility than the irrigated alternative because more land is available for rice
cultivation. Although the on-farm pond improves average revenue, the increase appears rather
insignificant.
By considering levels of expected revenue alone, investment in a pond seems
unattractive.
However, an individual's decision is based on utility rather than revenue.
The cumulative
distribution function of the farmer's instantaneous utility is plotted in Figure 5-8b using the
CRRA function in Equation 4.5.
As marginal utility is higher when the utility level is low, the
benefit of the pond is more pronounced at lower utility. Table 5.3 records statistics of simulated
revenues from a rice production with a 5% pond and without irrigation.
The expected gain
from a 5% pond in comparison with that under a rainfed condition is only 4,878 baths per
crop season.
Despite the fact that the gain on expected revenue looks unimpressively small,
65
I
I
I
I
I
I
I
(1)
I.3.
0
_0
x* = 4.30%
I
I
0
1
2
3
5
4
6
7
8
9
10
pond size (%)
Figure 5-6: Plot of expected utility of revenue versus pond size.
interpolation of HYDRO-CROP simulated data (green dots).
66
The curve results from
the variance in revenue is narrower by 54%.
Results of utility evaluation given farmer's E-V
objective function shows that a pond improves the expected utility level as plotted in Figure
Hence, the on-farm pond appears to be a considerably more attractive investment once
5-6.
risk is taken into account.
The results summarized above depend on several important parameters which are rather
difficult to estimate.
Furthermore, our study assumes that all variability in revenue is due
solely to meteorological uncertainty. We need to look at uncertain parameters separately and
determine the range of conditions under which this on-farm reservoir technique can be beneficial
to a rice farm.
5.2.4
Pond Construction/Maintenance Cost
In order to generalize our analysis, we need to identify the maximum cost for the pond such that
it does not become a bad investment. At this break-even cost (C), a farmer will be indifferent
between investing in a pond installation and doing nothing. The nominal value of C may be
considered as an annual payment for the pond; its total discounted sum across the pond's life
includes both maintenance and construction costs. We can incorporate cost (C) into Equation
4.9 by replacing R with R - C:
U(R - C)
(R
C)Y
R -C
1 - -y
2
-y
R
- 2 R- C
(5.3)
Assume that the actual cost (C) for each pond size is constant for each pond size (x), the
only uncertainty is in revenue from rice production. Therefore, the mean cost is equal to this
constant cost so R - C =
R - C and the variance of net profit-i.e., revenue less cost-is equal to
the variance of revenue alone; that is, o-C =
(.
To obtain the break-even cost, we equate
U(R - C) with the pond (x = 5%) to U(R - C) without the pond (x
0%).
The result is
equal to 5,326 baht for a 5% pond in spite of the fact that the gap between the average revenue
under a pond scheme and that without pond is only 4,878 baht.
installation results from the risk aversion of the farmer.
against uncertainty.
67
This premium for a pond
He is willing to pay more to insure
15
-**"%.
I
I
6
6.5
{
irrigate
C
**
4-
1-.
00S
- -
2.5
3
4
3.5
-
-
5.5
5
4.5
revenue (baht)
7
x id
C5
=3
13 rainfe
d-
cT
~
5.
-
C
2.5
3
-
3.5
4
4.5
5
revenue (baht)
5.5
6
6.5
7
x id
Figure 5-7: Histograms of revenue under irragated and rainfed conditions. The dotted line
represent estimated normal distributions using parameters derived from both sets of revenue.
68
-
0
irrigate
rainfed
10 .60 .40 .2-3
.5
3.5
4
4.5
5
5.5
Revenue (baht), R
6
6.5
7
1.---
ir rigate
ainfed
0.
0.4
0.20
Utility
Figure 5-8: Cumulative distribution functions for revenue (top) and utility (bottom) from rice
production under irrigated and rainfed conditions.
69
5.2.5
Subsistence Constraint
Each farm household faces a subsistence constraint on consumption and other expenses 2 . For
the on-farm pond to be viable, the revenue under the pond scheme must be sufficient to cover
both its cost and the necessary amount to sustain a household.
Sensitivity analysis indicates
that pond size and the expected utility level are independent of the changes in subsistence
constraint, but the maximum price of the pond farmers are willing to pay is linearly affected.
5.3
Sensitivity Analysis
Sensitivity analysis enables the analyst to determine how changes in parameters affect simulation results. In our application, sensitivity analysis identifies the range of parameters for which
the pond scheme is viable.
There are a number of parameters on which it is worthwhile to
undertake sensitivity analysis. Some of these are very uncertain while others are likely to have
a significant impact on our conclusions regarding the attractiveness of an on-farm pond.
For sensitivity analysis purposes we specify as a nominal case the 5% pond option discussed
on Section 5.2.
Three parameters are selected for our sensitivity analysis: the risk aversion
measure, the rice price, and the income threshold for a subsistence household.
Table 5.4
records the changes in these parameters; while Table 5.5 reports responses in utility level and
the break-even cost at which the pond scheme is an attractive investment ceteris paribus.
The results of sensitivity analysis indicate that utility is highly sensitive to the risk aversion
coefficient.
However, the maximum price the farmer is willing to pay only shifts slightly when
this coefficient is changed.
The rice price has an insignificant effect on the utility level but
a strong effect on the break-even pond price.
Although the farmer's utility is insensitive to
the changes in the subsistence constraint, the maximum pond price is highly and conversely
2
While the farmers wait for the harvest, they spent 3,500-4,000 baht per rai over the past four months on
water pumping, soil preparation, seed growing, pesticides and fertilizer [23]. Somrith (1998) estimated total
agricultural expenditure in the central region at 3,645 baht per rai. Therefore, a typical rice-only farming
household with a 5% pond and a 5% housing area keeps 90% of total area (13 rai) for rice fields. They require
46,700 baht for aggregate rice cultivation activities. In addition to agricultural inputs, a family of four eats 12
kilograms of milled rice a month. This consumption amounts to 144 kg of milled rice annually; price of which
lies in 10 baht per kg [26]. Rice consumption constitutes about 75% of food comsuption; as a result, total
household consumption sums up to 1,920 baht per household annually. Because farmers need to purchase the
rice after milling, we cannot simply subtract the rice out of their dry grain inventory. In sum, each household
needs to maintain an income of 48,500 baht annually.
70
correlated to such changes.
5.3.1
Risk Aversion Parameter
Without considering cost, the average revenue under an on-farm pond is higher than that
without a pond while the variance is lower (see Table 5.3.)
Consequently, a farmer who has
a normal upward-sloping utility function will prefer a pond regardless of his attitude toward
risk. When the pond cost is included, risk becomes more relevant. The farmer's risk aversion
coefficient measures his sensitivity to changes in income.
These curves in Figure 5-9 indicates
that a farmer with higher risk aversion measure is more sensitive to a small change in revenue
since the slope of the curve is greater.
Figure 5-10 illustrates that a more risk-averse person is willing to pay more for the pond
A risk-averse farmer is willing to pay the
in exchange for a lower variability of revenue.
difference between the break-even cost and the average revenue in order to reduce risk (in
the other word, income variance).
substantially.
A highly risk averse person values reduction in variance
Nevertheless, he would not want a pond larger than 5%, as the decline in risk
becomes insignificantly small. The optimal pond size remains within the same range of 4.30%
- 5% despite the change in risk aversion measure.
5.3.2
Rice Price
We can incorporate a constant price multiplier (p) into Equation 4.9 as follows:
U(pR)
U(pR) -2
U'()
S-
I
p-Y - U(R)
pR
2
7
pR
(5.4)
Since the price multiplier (p) is independent of pond area (x), x remains unchanged regardless
of p.
Although the level of the expected utility increases only slightly when the price of rice
71
10% increase
gamma = 0.6 1
0% decreas
3
I
I
SI
2.5
3.5
4
4.5
5.5
5
revenue (baht)
I
I
I
6
6.5
Figure 5-9: Impact of the risk aversion coefficients on utility.
72
7
7.5
x d
...
.....
...
550C
-e- average revenue
-4e-
break-even cost of p nd
530C-
520C
A
-c
(U
.0
51 Wpremium paid for
reduced risk
500490C
480(
0
0.2
0.8
0.6
0.4
multiplier of estimated risk aversion
1
Figure 5-10: Break-even cost of a 5% pond versus risk aversion coefficient
73
1.2
1100
1000--
2
900G-
C
o
8000-
0.
-6
0
0
E
.E
600(-
E
500(-
400G-
300A
.6
0.8
1
1.2
1.4
1.6
1.8
2
multiplier of the estimated price
Figure 5-11: Relationship between the maximum cost of a 5% pond and price of rice production.
Here we assume the price of rice equal to 4.3 baht/kg.
rises, the relationship between the price multiplier and the maximum cost (C) is positively and
linearly correlated as illustrated in Figure 5-11.
5.3.3
Subsistence Constraint
The results presented in Table 5.3 indicate that there is a nearly 50% chance that a rainfed
farming household will suffer a financial crisis.
This risk explains urban migration and the
cultivation of second crops during the dry season.
On the other hand, the expected income
from an irrigated farm is greater than the required expense by more than one standard deviation.
The income from rice less production cost and consumption (5,400 baht) is still higher than
74
the maximum price a farmer is willing to pay for an on-farm pond (5,326 baht). With a lower
pond cost, subsistence farmers attain a higher utility under the on-farm reservoir plan.
75
Table 5.1: Simulated and observed grain yield for irrigated and rainfed conditions.
Grain Yield [kg/ha]
Year
Irrigated
Rainfed
Simulated Observed Simulated
Observed
2792
5915
1985
2900
5550
1986
4651
2374
1987
5799
3414
1988
6222
4112
2934
6329
1989
5944
5582
5196
3119
1990
4694
5548
1991
3002
5700
4693
5349
5349
2998
1992
6240
5899
5543
3278
1993
2500
1994
7151
6898
3070
5988
3991
1995
Mean
Bias
RMSE
R
V
Source:
6119
5111
3027
5648
471
(eq 4.1)
2084
(eq 4.2)
625
2193
(eq 4.3)
0.0834
0.6883
0.0120
(eq 4.4)
0.5150
Irrigated - Praputthabaht Field Crop Experiment Station
Rainfed - Central of Agricultural Information, 1998
Table 5.2: Area allocated for rice paddy in an average Saraburi rice farm with respect to
percentage of pond area
Revenueb (R)
Average Yield (Y)
Pond Size (x) Paddy Areaa (Ap)
[baht]
[kg/ha]
[hectare]
[% of total area]
49,147
5,277
2.1660
0.00 %
50,804
5,572
2.1204
2.00 %
5,921
53,405
2.0976
3.00 %
6,042
53,728
2.0680
4.30 %
54,027
6,123
2.0520
5.00 %
6,123
53,427
6.00 %
2.0292
a total land-holding area is 2.40 hectare or 15 rai, with 5 % housing
b price of rice production is 4.3 baht per kg at local market
76
Table 5.3: Statistics of simulated revenue for rice production, generated from 35 years of actual
weather data (1961-1995)
Irrigated Plot 5%
Statistics of Rainfed Plot
without cost with maximum costa
Revenue
[x10 4 baht]
[x104baht]
[x104baht]
5.403
4.915
R
5.337
5.124
RN/2
6.341
6.693
Rmax
4.546
2.806
Rmin
0.482
0.945
O'R
-0.612
0.405
Skewness
a The maximum cost (C) of 5,326 baht is calculated
Equation 5.3 with risk aversion measure of 0.671.
4.870
4.804
5.808
4.013
0.482
0.405
according to
Table 5.4: Input values used in sensitivity analysis
CRRA (y)a Rice Price6 Subsistence Constraint'
Parameter
[baht/year]
[baht/kg]
[I
Change
-120%
-0.134
-100%
0
38,800
3.44
0.537
-20%
43,650
3.87
0.604
-10%
48,500
4.30
0.671
0%
53,350
4.73
0.738
10%
58,200
5.16
0.805
20%
8.60
100%
Source: The base case uses a 5% pond in a typical 15-rai farm.
a
estimated in Paulson and Townsend (2001).
b local price of unmilled rice in Saraburi.
C explained in footnote.
Table 5.5: Summary of sensitivity analysis results
Measures of Interest
Parameter
A Utility
A Maximum Cost (C)
slightly sensitive
highly sensitive
CRRA (y)
slightly sensitive highly sensitive (linear)
Rice Price
highly sensitive (linear)
Subsistence Constraint insensitive
Original Solution
109.51 util
77
5,326 baht
Chapter 6
Conclusions
In this final Chapter, we evaluate the on-farm reservoir investment in terms of technical and
economical feasibility and discuss directions for future work.
6.1
Evaluation of On-farm Pond Installation
This thesis proposes an integrated approach for investigating the feasibility of investing in an
on-farm reservoir.
The said investment follows the general principles outlined in Phase I of
His Majesty the King's New Theory concept; i.e., farming households allocate a certain area of
land for a pond which captures runoff generated within the farm boundary. Furthermore, since
the on-farm reservoirs are individually owned and managed, organizational problems inherent
to larger irrigation schemes are absent.
This study considers not only the pond's capacity
to harvest rainwater for supplemental irrigation to rice farms but also its economic impact
for farming households' welfare.
Our case study is based on the physical and hydrologic
characteristics of a typical small-scale rice farm in the semi-aria area of central Thailand.
The simulation results derived here confirm that the New Theory concept is technically
viable.
The pond can store enough rainwater to provide for successful rice farms during the
wet season. A farm with an optimal-sized pond has higher rice yields than a farm with no pond.
However, this high rice yield comes at a cost.
for the pond.
The farmer sacrifices valuable cultivation area
The improvement in total rice production and thus in the revenue is therefore
less than the improvement in the yield per unit area.
78
Despite the small revenue difference,
the variation of yield is reduced by half under the irrigated scheme.
Given higher expected
revenue and lower variance, risk-averse farmers find the on-farm pond alternative an attractive
investment if pond construction costs are ignored.
It is more interesting when the pond's cost is taken into consideration.
We performed a
break-even analysis to calculate the highest cost farmers are willing to pay for a pond given the
increase in their expected utility. This cost is estimated for a nominally equal annual payment
The
throughout the pond's life and includes both construction and maintenance expenses.
expected net profit from the pond is close to that of the rainfed case once cost is incorporated.
Nevertheless, the on-farm pond is still attractive since the revenue is still significantly lower.
Our sensitivity analysis computes the range of pond costs which farmers can afford. Naturally a more risk-averse person tends to assign higher value to an on-farm pond.
As the
level of farmer's risk aversion increases, the maximum price the farmer is willing to pay for a
pond rises.
Furthermore, even a risk-neutral farmer finds the on-farm reservoir an attractive
investment due to a slight increase in expected revenue from rice production.
Since we do not
take price uncertainty into account, changes in the price of unmilled rice at local market have
a linear effect on the price of the pond.
In accordance with the results from our sensitivity
analyses, the range of a pond's cost exceeds the actual cost of maintaining the pond. In sum,
the pond alternative meets the welfare utility criteria for a potentially good investment.
In topographically flat areas such as our study site, on-farm reservoirs are constructed as
dug-out ponds and maintained by hiring local labor to clean up sediments. Currently all costs
involving a pond's construction are subsidized by either government agencies or state banks
in various forms.
Farmers, in actual practice, only need to cover maintenance cost, which is
relatively low compared to the estimated break-even cost.
In reality, the reservoir projects
have selected or targeted farmers with relatively less cash, land, and labor resources.
As such,
these projects appear to have the positive strategy of improving small farmer equity.
The overall approach described here should be applied to farms and watersheds in other
parts of Thailand, including the more arid Northeastern region. Conclusions from the Saraburi
site should not be generalized to the rest of Thailand until such investigations have been carried
out.
79
6.2
Recommendations for Future Research
In recent years, several projects have applied the New Theory concept to various droughtprone locations. In spite of these advances, there is a lack of clear understanding of the range
of physical, social, economic, institutional, and environmental factors that favor successful
implementation of the on-farm pond system, and allow sustainable benefits to be achieved from
use of the concept.
6.2.1
The relevant issues are addressed below.
Multiple-cropping system
Several factors have to be considered in irrigation management, particularly in the case of
multiple cropping.
The relatively small gain in wet-season rice production from the pond
installation is limited by a favorable weather conditions.
Dry-season crops, on the other
hand, can increase agricultural income with the help of supplemental irrigation from the pond.
However, some pond adopters may not be able to plant a dry-season rice crop due to unfavorable
agroclimatic conditions. A careful analysis of crop production is needed for each subecosystem.
Multiple cropping, including cash crops and perennial trees, can also help to mitigate the risk
of rice-only production and provide for domestic consumption.
One of the key decisions to be made is how much water should be allocated to different
cropped areas. The decision must be based on (1) the availability of land and water resources,
(2) the reliability of the water supply and, (3) the expected benefit and uncertainty from crop
production.
There are two possible strategies for the application of water to the crops. The
first is to apply irrigation water at a level which gives maximum net incomes.
may be used when there is no constraint on irrigation supplies.
The approach
That is not the case in the
semi-arid subecosystem in central Thailand where water is in short supply.
When a water
constraint exists, it is useful to provide alternative levels of irrigation water and thus cover a
larger area, which may result in higher returns. In spite of an acute water shortage, a farmer
may, in actual practice, irrigate more than required even for maximum production. This calls
for optimum allocation and distribution of water along with scientific planning of cropping
patterns.
80
Figure 6-1: Cash crops such as perennial fruit trees and vegetables can increase incomes for
farm households, particularly during the dry season when water is insufficient to sustain rice.
81
6.2.2
Supplementary Water Resources to the On-farm Pond
Surface Reservoir
Different scales of water storage can jointly improve irrigation supplies for rice farms.
Re-
cent research results have shown that scientific management of water resources within a micro
watershed, using an on-farm reservoir as the centerpiece, is economically attractive and socially desirable.
Larger water storage facilities such as a communal reservoir similarly serve
as supplemental water supplies. These supplies mitigate the risk of rainfall variation and permit dry-season cropping.
A methodology appropriate for assessing the effect of alternative
technologies is needed to establish the long-term feasibility and profitability to participating
households. Combination of these storage facilities rather than a single one may be the optimal
choice.
Thai bureaucracies are in a transition from relying on large-scale hydraulic structures as
the hope for all the countries' irrigation needs toward recognizing the need for a range of
technologies and social organizations.
Large-scale alternatives are not feasible everywhere.
Small systems also cannot replace large systems in many circumstances, but large systems may
also be inappropriate where many small systems are feasible.
What is gained in engineering
efficiency with the large system is sometimes lost in the complexities of actually managing large
social systems. Small-scale alternatives which may be easier to manage, in practice, gain new
currency.
Groundwater
Water balance analyses of Saraburi and other prospective sites for the on-farm reservoir scheme
should include quantitative studies of shallow groundwater resources.
The combination of an
on-farm pond and a shallow groundwater pumping system for wider irrigation coverage should
be assessed. In theory, constructing an unlined rainwater storage structure markedly improves
groundwater recharge. Future studies should determine whether shallow aquifers in the region
of interest could supply significant amounts of irrigation water and whether conjunctive use is
more economically desirable than of either system used above.
82
0/0
~0
I/
0
9
*
0
0
0
__
0
0
*
0
big reservoir
*
0
V
Figure 6-2: The complete system of the New Theory: A big reservoir supplies a small; a small
reservoir supplies a pond. An experiment of this principle can be observed at Wat Monkol
Chaipattana, Saraburi Province. Source: Chaipattana Foundation's The New Theory [9].
83
6.2.3
Opportunity Cost of Agricultural Labor
The on-farm pond technique increases agricultural income but also requires high labor input in
farming and pond-maintenance. Labor inputs in crop farming conflict with the time required
for other activities. A farmer pays an opportunity cost by choosing not to work in town where
he can earn a fixed wage. Given the relatively less variable wage-earning labor, as compared
to the agricultural labor, farming households prefer regular seasonal farm labor.
We need to
study the extent to which the on-farm reservoir technique changes the occupational choice of
rural households so as to understand more realistic socio-economic impacts of this irrigated
scheme.
6.2.4
Household's Wealth Accumulation Beyond Subsistence
The main objective of the New Theory concept is to improve the living conditions of rural and
subsistence farming households. There is a need for economic impact evaluations of the on-farm
ponds in order to establish the long-term feasibility and profitability of these reservoirs. Even
though small ponds can provide irrigation water to temper the vagaries of the monsoon and thus
mitigate the risk of water shortage, evidence shows that poor farmers fail to undertake profitable
investment that they should, in principle, self-finance.
Without subsidies from government,
the non-divisibility of the pond investment puts it out of their reach.
We need to look at
credit structures that can encourage farmers to invest in desirable on-farm reservoirs.
Once
the financial infrastructure is in place, the farm household can attain wealth accumulation and
thus a better standard of living.
6.2.5
Government-aid Programs
Cooperative Activities
Thus far, we have only discussed the benefit-cost structure on the on-farm reservoir scheme
from an individual point of view. We also need to consider the aggregate effects of agricultural
improvement under the New Theory. The second phase of the New Theory suggests that farmers put together their efforts and resources in the form of a group or cooperative to execute the
agricultural activities. Cost-sharing activities such as soil preparation, irrigation management,
84
and product distribution can dramatically increase profit of each individual farming household.
Government can help coordinate farmers who share the same pool of resources and establish
such cooperative groups.
Financing
It is also necessary to identify under what conditions institutional credits are needed in order
for small-scale farmers to benefit from on-farm ponds.
Currently both on-farm and larger
reservoir projects in Thailand are fully-funded by the government.
irrigation project do so because of the lack of financing.
Most areas who reject
Small-scale irrigation systems are
available only to economically advantaged farmer groups and very few subsidized communities.
To make the system more applicable to other areas, government-aid programs may be needed
to jump start the process and encourage its use by economically disadvantaged groups.
For
example, the Bank of Agriculture and Agricultural Cooperatives is considering a low-interest
loan for a supplementary communal reservoir.
The approach to this issue is to compare
alternative financial options for funding the project.
Institutional Arrangement
The effectiveness of water management, including promoting adoption of new irrigation infrastructure, requires a well-structured administrative body. In Thailand, there is overlapping
of administration among the Royal Irrigation Department (RID), the Local Administration
The Chak leader elected by the water users
Department, and the water users association.
association takes charge of water supply, drainage, and maintenance work within his area to
ensure that water is allocated in an equitable manner.
Although this Chak leader is the key
to water use management, he can be directed by the chairman of the water users association,
by the zoneman of RID, or by the District officials of the Local Administration Department.
This complicated structure results in lack of unity and brings about inefficiency in water management.
Further study of the institutional impact of the use of on-farm reservoir is needed.
85
99
- -- - - - - - - -- - - - - ----------------------------------------AOQI @q
PO JI PH JH qTTnfo
-- %
UIJDT2
GAPS
pug
PuG
sqn
=
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=
(T+4) PO
(4)40Tino
( 0(T4)P
TTn; Gap2 sq4~TP
Y~pppd pup puod uat{m qflo aaqpm
9qT
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%
'(T+;)'7H
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83TJ JO PUG %
L 'E == (0001 '(4)x Oa)Pou JTa9TG
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'X
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'(T+-4)-H
'(T+-4)PH]
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do
UOS~S GOT3 % (L C >
'(q)iH
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';)xnTJ
'(8';)xnTl;
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0C6ZT:T
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=
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4
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)MCI
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Po
PH
uoTqoufl
0
*
OHIH
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!UdHOdO-DEHdSfOH-DEdONOd-OOT = DOddDIU
P03P @3J o
apuoaad %
!0 =3IddHD'dO
bUTPTO4 PUPT aayqua oq Paap papqoao go abpuaoaad %
bUTPTOq4 PuPI eJITcU@ 04l P~22 bU~snoq go e ;quaoIad %!9 = 3dWIdSflOH
aZTepTJod PPOT
PdPg= DdHJQNOd %%
bUTTq PuPT au~qua Oq Pecu puod go abpuaojad %
a
!009T =
uvbs UT UOT4POOTTP PuPT %
~
00000%%%
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%%%%%%%%%% %%000%%%0o0
oo%%%oo%%%
Iq NDTISSV
SINVISNOO
W'MVqddi 'dOq
%
%
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= PO
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=
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do+pv/JV*X+AE-U'd+T PH = PH
!=
o
(d+TPH.,TdS) -pV/dv*[
= PH
!Aa-pV/aV4XUE
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(T J~H
'AH
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PH
f,;suooddq4 una
aaqpm%
saqoq~p IApppd UT @3P~
'4)qO4TP = [II 'PO 'ZH 'PH] UOTqoufl
'3H) x~uI =
!'(o
!(HJdECCQNOd
(0
I
(Zds+Z T JH*Tds)-a/q*
qC+aV/PV*T
-.
'H~dSGGNOd
P+A9-U+T
H) uTUI
'
=
EH
a
= X
PUG
H) XeU
!0 =>21H JT
J~H = 21H
!(0'AE-UU) UTUI
=
rH
T==q JT
qsuooddq una
2TOAJG9ea UIP2-UO UP UT
(T
LlO
'TIPO
'T 'H
'A
luEj ';)puod
=
a~Pp
[X
'aH]
2[9Wm
%
uoT;Dunq
% rice paddy
Ap = .95*RICEPERC*rai;
Ad = RICEPERC*rai - Ap;
% ditches around paddy
Ah = HOUSPERC*rai;
% housing & road
% surface area and capacity of each reservoir in sq.m. and cu.m.
Ar = PONDPERC * rai;
% land elevation in mm
CULVERT = 300;
PONDDEPTH = 4000;
RICEROOT = 400;
K
= Ar*PONDDEPTH;
% drain from paddy ditches to pond
% reservoir depth
% root zone for rice, top layer
% pond capacity
% Seepage coefficient in reservoir/ditches, Sp(t) = Spl*depth^2 + Sp2 [mm/day]
% constant throughout the year due to assumption that there is water.
Spl
=
0.49e-6;
Sp2 = 0.005e-8;
% embankment for paddy fields varies on different
MINDIKE = 45;
MAXDIKE =
120;
88
stage of rice
(mm)
Appendix B
CROP - DSSAT Code
*EXP.DETAILS:
DTLP1004SN N-FERT.
MEASURED WTHER
F ACTOR LEVELS-----------------------CU FL SA IC MP MI MF MR MC MT ME MH SM
1
1
0
1
1 1 1 0 0 0 0 1 1
1 1 0 1 1 2 1 0 0 0 0 1 1
*TREATMENTS
@N R O C TNAME....................
1 1 0 0 IRRIGATED FERTI
3 1 0 0 NON-IRRIG.
*CULTIVARS
@C CR INGENO CNAME
1 RI IB0301 RD7, MANKEB
*FIELDS
FLDD
FLDS
FLST SLTX
SLDP ID SOIL
FLSA FLOB FLDT
@L IDFIELD WSTA....
0
0 00000 -99
0 DROOG
-99.0
51 IBRI910024
1 DTSPOO01 DTLP
AREA .Sl EN .FLWR .SLAS
YCRD .... .ELEV .............
@L ........... XCRD.. .........
0.00
0.0
0
0.0
0.0
0.00000
1
0.00000
*INITIAL
@C
PCR
1
RI
ICBL
@C
1
5
1
8
1
19
28
1
38
1
1
51
CONDITIONS
ICDAT
ICRT
100
61100
SH20 SNH4
1.0
0.332
1.0
0.332
0.5
0.341
0.5
0.369
0.5
0.369
0.344
0.5
ICND
-99
ICRN
1.00
ICRE
1.00
ICWD ICRES ICREN ICREP ICRIP ICRID
15
0.00
100
1.0
0
0.80
PLME
T
PLDS
H
PLRS
20
SN03
15.7
15.7
6.5
4.7
4.7
2.9
*PLANTING DETAILS
PPOP
@P PDATE EDATE
-99
75.0
1 61247
PPOE
25.0
*IRRIGATION AND WATER
ITHR
@I
EFIR IDEP
-99
1.00
-99
1
IROP IRVAL
IDATE
1 61247 IR009
120
1 61247 IR006
45
ITHR
@I
EFIR IDEP
2
1.00
-99
-99
@I IDATE
IROP IRVAL
2 61247 IR009
120
2 61247 IR003
0
MANAGEMENT
IAME
IEPT IOFF
IR001
-99 -99
IIRV
8
0
IAME
IEPT IOFF
IR001
-99
-99
IIRV
0
0
*FERTILIZERS (INORGANIC)
FACD FDEP
@F FDATE
FMCD
15
1 61246 FE002
1 61273 FE002
15
1 61307 FE002
15
FAMN
100
60
40
FAMP
0
0
0
PLRD
0
PLDP
5.0
PLWT
0
FAMC
0
0
0
FAMO
0
0
0
FOCD
IAMT
1
IAMT
1
FAMK
0
0
0
89
PAGE
25
PENV
25.0
PLPH
3.0
SPRL
0.0
*HARVEST DETAILS
HPC
HCOM HSIZE
@H HDATE HSTG
100.0
1
100
*SIMULATION CONTROLS
NYERS NREPS START
@N GENERAL
I
35
1
1 GE
WATER NITRO SYMBI
@N OPTIONS
Y
Y
Y
1OP
WTHER INCON LIGHT
@N METHODS
E
M
M
1ME
PLANT IRRIG FERTI
@N MANAGEMENT
R
R
R
1 MA
FNAME OVVEW SUMRY
@N OUTPUTS
OPOUT
A
Y
Y
1OU
N
@N
@N
1
@N
1
1
@N
1
@N
1
AUTOMATIC MANAGEMENT
PFRST PLAST
PLANTING
97159 97173
PL
IRRIGATION IMDEP ITHRL
50
30
IR
NMDEP NMTHR
NITROGEN
30
50
NI
RIPCN RTIME
RESIDUES
1
100
RE
HFRST HLAST
HARVEST
0 97365
HA
PH2OL
40
ITHRU
100
NAMNT
25
RIDEP
20
HPCNP
100
HBPC
0.0
SDATE
61100
PHOS P
N
EVAPO
P
RESID
N
FROPT
RSEED
2480
POTAS
N
INFIL
R
HARVS
D
GROUT
1
Y
PH2OU
100
IROFF
IB001
NCODE
IB001
SNAME ....................
RICE MIT
CHEM TILL
DISES
N
N
N
PHOTO HYDRO
R
C
CAOUT WAOUT NIOUT MIOUT DIOUT
N
Y
PH2OD PSTMX PSTMN
10
30
40
IMETH IRAMT IREFF
0.75
IB001
10
NAOFF
IB001
HPCNR
0
90
Y
N
N
LONG CHOUT
N
N
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