P. K. Pandey, S. Biswas / Journal of Agricultural Chemistry and Environment 3 (2014) 16-19
Table 1. Water balance parameters of catchment area, culti-
vated land, and crop yields.
Conditions
Parameters
AMe
(mm) ETa
(mm) Ya/Ym Ya
(kg/ha) TS
(mm) GW
(mm)
Irr. 90.2 268.7 1.0 6000 128 73.53
Rain. 33.2 130.5 0.36 2141 0.0 130.48
Parameters
OWUE
(kg/m3)
UA CA
R (m3/yr) ET (m3/yr)
R (m3/yr) ET (m3/yr)
Irr. 2.98 28101 21588 5907 7842
Rain. 1.64 33060 25397 5498 6298
**Note: Irr. = irrigated; rain. = rainfed; AMe = availab le moistur e at the end
of croppi ng seas on 1; Ya = actual cr op yiel d; Y m = maximum crop yield; TS
= total supplemental irrigation applied; GW = green water use; OWUE =
overall water use efficiency; R = recharge; ET = Evapotranspiration; UA =
Uncultivated land area (catchment area of 5 ha); CA = Catchment area
(cultivated land area of 1 ha).
value in rainfed condition was 93% of the irrigated con-
dition, and ET value in rainfed condition was approx-
imately 80% of the irrigated condition. In summary, the
results of the study showed that rainwater harvesting
approach can be an effective alternative for enhancing
agricultural water availability in the rainfed regions.
5. CONCLUSION
A water balance model was used to estimate the im-
pacts of rainwater harvesting appr o ach on enhancing
rainfed crop land soil moistures and crop yield for a
southwestern district of Bangladesh. The model esti-
mated rainwater storages in water storage tank (designed
in the farm land). The model uses algorithms to estimate
the water requirement of the crop land as well as water
availability in the tanks. This decision making allows
model to estimate the supplemental irrigation require-
ment in the crop land as well as supplemental irrigation
availability in the tanks. There sults showed th at the r ain-
water harvesting approach presented here increased crop
yield considerably in the studied rainfed region of the
Bangladesh. The model requires four major parameters:
precipitation, temperature, evaporation, and evapotrans-
piration. To run the model, daily input data are required.
In this study, daily data were estimated from the availa-
ble monthly data and used to feed the model. We antic-
ipate that the availability of daily observed data will im-
prove the model predictions significantly, therefore, fur-
ther studies utilizing the daily observed data for predict-
ing supplemental irriga tion, soil moisture, and crop yield
will be necessary. We suggest future studies utilizing the
climate data of multiple locations (rainfed) to enhance
the model as well as model predictions.
ACKNOWLEDGEMENTS
We than k to Dr. Pieter van der Zaag, Professor, UNESCO-IHE Insti-
tute for Water Education, Delft, Netherlands, Water Resources Section,
Delft University of Technology, Delft, Netherlands for his help in mod-
el development, which is already published elsewhere [8].
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