Effectiveness of Hapa as Small Rainwater Harvesting Ponds for Sustainable Agricultural Development in Diversified Arid Regions: Comparative Case Studies From Bankura in India
DOI:
https://doi.org/10.25175/jrd/2023/v42/i3/173263%20Keywords:
Arid Region, Water Scarcity, Rainwater Harvesting, Hapa, Remote Sensing; Z-score, Sustainability.Abstract
Water is a unique constituent, which is essential for the survival of humans, animals and plants. Agriculture needs water in large quantities. Supplying irrigation water is a crucial factor in preserving groundwater, determining the water balance and subsequent cropping pattern of any region. The challenge is even greater when it is dryland. The present study is confined to the Bankura district, the arid region of West Bengal in India. Here, for irrigation, small customised ponds, known as hapa, are dug up by individual farmers to store the rainwater. The government encourages farmers by providing funds for hapa creation. In the last 10 years, about 2900 hapas, which can harvest a large quantity of water, have been dug up in croplands. This harvested water indirectly helps in recharging groundwater too. The present study aims to highlight the need for hapas in such arid regions. This study demonstrates a positive link between hapa creation with changing land use land cover patterns, increasing agricultural areas, growing population, and declining rainfall patterns. In support of this, spatial and statistical analyses were performed according to certain key remote sensing indices VCI, NDWI, and Z Scores of the pre-hapa and post-hapa creation periods. The study found that the implementation of the hapa irrigation technique has significantly increased the yield of crops besides generating agricultural labour. Land owners started cultivating multiple crops on their lands which helped to increase annual income. The complete research shows the noteworthiness of hapa irrigation technique as an alternative to a sustainable development programme in arid areas.
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Adwubi, A., Amegashie, B. K., Agyare, W. A., Tamene, L., Odai, N. S., Quansah, C., & Vlek, P. (2009). Assessing Sediment Inputs to Small Reservoirs in Upper East Region, Ghana. Lakes & Reservoirs: Science, Policy and Management for Sustainable Use, 14(4), 279–287.
Banerjee, P. S. (2012). Impact Study of Hapa and Its Multiple Uses in Bankura District. AgWater Solutions Project Case Study. International Water Management Institute. Colombo, Srilanka. https:// doi.org/10.21955/gatesopenres.1115653.1.
Bhattacharya, S. (2015). Traditional Water Harvesting Structures and Sustainable Water Management in India: A Socio-Hydrological Review. International Letters of Natural Sciences, 37, 30–38.
Boers. T., & Ben-Asher, J. (1982). A Review of Rainwater Harvesting. Agricultural Water Management, 5 (2), 145–158.
Chatterjee, U. (2018). Impacts of Hapas in Rural Development of Drought Prone Areas in Hirbandh Block, West Bengal. Indian Journal of Spatial Science, 9(1), 91–95.
Chen, X. L., Zhao, H. M., Li, P. X., & Yin, Z. Y. (2006). Remote Sensing Image-Based Analysis of the Relationship between Urban Heat Island and Land Use/Cover Changes. Remote Sensing of Environment, 104(2), 133–146.
CPCB (2016). Rainwater Harvesting in India - An Appraisal. ENVIS Centre at CPCB on Control of Pollution, 1–22.
Dhawan, V. (2017). Water and Agriculture in India. Background paper for the South Asia expert panel during the Global Forum for Food and Agriculture (GFFA) 2017. Federal Ministry of Food and Agriculture, 3–27.
Downing, J. A., Prairie, Y. T., Cole, J. J., Duarte, C. M., Tranvik, L. J., Striegl, R. G., McDowell, W. H., Kortelainen, P., Caraco, N. F., Melack, J. M., & Middelburg, J. J. (2006). The Global Abundance and Size Distribution of Lakes, Ponds, and Impoundments. Limnology and Oceanography, 51(5), 2388– 2397.
Fowe, T., Karambiri, H., Paturel, J-E., Poussin, J-C., & Cecchi, P. (2015). Water Balance of Small Reservoirs in the Volta Basin: A Case Study of Boura Reservoir in Burkina Faso. Agricultural Water Management, 152, 99–109.
Gao, B. (1996). NDWI—A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Remote Sensing of Environment, 58(3), 257–266.
Guha, R. K. (2018). HAPA: Dreaming with Small Pond. Conference on “Rural India: Blossoming in Neglect?”. VikasAnvesh Foundation, Pune, August 2018.
Gupta, R., Tyagi, N. K., & Abrol, I. (2020). Rainwater Management and Indian Agriculture: A Call for a Shift in Focus from Blue to Green Water. Agricultural Research, 9, 429–443.
Jana, S. K. (2011). Sustainable Small Scale Irrigation Experiment in the Dry Zones: A Case Study on Happa (Small Tank) Model in the State of West Bengal, India. APN Conference on “Innovation and Sustainability Transitions in Asia”, at University of Malaya, Malaysia, during 9-11 January 2011.
Khullar, D. R. (2018). India: A Comprehensive Geography. Kalyani Publication, India.
Kogan, F., Stark, R., Gitelson, A., Jargalsaikhan, L., Dugrajav, C., & Tsooj, S. (2010). Derivation of Pasture Biomass in Mongolia from AVHRR-based Vegetation Health Indices. International Journal of Remote Sensing, 25(14), 2889–2896.
Li, Q., & Gowing, J. (2005). A Daily Water Balance Model Approach for Simulating Performance of Tank- Based Irrigation Systems. Water Resources Management, 19, 211–231.
Liebe, J., Giesen, N. V. D., & Andreini, M. (2005). Estimation of Small Reservoir Storage Capacities in a Semi-Arid Environment—A Case Study in the Upper East Region of Ghana. Physics and Chemistry of the Earth, Parts A/B/C, 30(6–7), 448–454.
Liebe, J. R., Giesen, N. V. D., Andreini, M., Walter, M. T., & Steenhuis, T. S. (2009). Determining watershed response in data poor environments with remotely sensed small reservoirs as runoff gauges. Water Resources Research, 45(7), W07410.
Machiwal, D., Dayal, D., & Kumar, S. (2017). Estimating Water Balance of Small Reservoirs in Arid Regions: A Case Study from Kachchh, India. Agricultural Research, 6, 57–65.
Mahmood, A. (1999). Statistical Methods in Geographical Studies. Rajesh; New edition, India.
Mandal, S. P., & Gupta, K. (2012). Agricultural Water Utilization through Hapa System: A Study on
Bankura District West Bengal. Geo-Analyst, 2(2), 146-150.
Minhas, P. S., & Reddy, O. G. P. (2017). Edaphic Stresses and Agricultural Sustainability: An Indian
Perspective. Agricultural Research, 6, 8–21.
Mustapha, M. K. (2009). Problems, Challenges and Management of Small, Shallow Tropical African Reservoirs–A Case Study of Oyun Reservoir, Offa, Nigeria. International Journal of Lakes and Rivers, 2(1), 163–174.
Myers, L.E. (1975) Water Harvesting – 2000 BC to 1974 AD. In Proceedings of the Water Harvesting Symposium, 1974, Phoenix Arizona. p1-7. Berkley, California. Ag. Research Service, Western Region,1975.
Narain, S. (2021). MGNREGA Waternomics. Down to Earth, March 31, 2021.
Oweis., T., & Hachum, A. (2006). Water Harvesting and Supplemental Irrigation for Improved Water Productivity of Dry Farming Systems in West Asia and North Africa. Agricultural Water Management, 80(1–3), 57–73.
Pani, A., & Mishra, P. (2021). Hapa Irrigation for Promoting Sustainable Agricultural Intensification: Experience from Bankura district of India. GeoJournal, 86, 109-132.
Rawat, J. S., & Kumar, M. (2015). Monitoring Land Use/Cover Change Using Remote Sensing and GIS Techniques: A Case Study of Hawalbagh Block, District Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 77–84.
Rhee, J., Im, J., & Carbone, G. J. (2010). Monitoring Agricultural Drought for Arid and Humid Regions Using Multi-Sensor Remote Sensing Data. Remote Sensing of Environment, 114(12), 2875–2887.
Saha, T. K., & Pal, S. (2019). Exploring Physical Wetland Vulnerability of Atreyee River Basin in India and Bangladesh Using Logistic Regression and Fuzzy Logic Approaches. Ecological Indicators, 98, 251– 265.
Sarp, G., & Ozcelik, M. (2017). Water Body Extraction and Change Detection Using Time Series: A Case Study of Lake Burdur, Turkey. Journal of Taibah University for Science, 11(3), 381-391.
Strahler, A. H. (1980). The Use of Prior Probabilities in Maximum Likelihood Classification of Remotely Sensed Data. Remote Sensing of Environment, 10(2),135-163.
