Abstract
Most of the popular hydrological models are intensive data driven hence, it has become a constraint in computing runoff of river basins where the meteorological data availability is scant. Studying environmental impact assessment on runoff has also become complex in many basins due to non-availability of sufficient historic meteorological data. Directly or indirectly, major components of hydrological cycle such as evapotranspiration and soil moisture are dependent on land use pattern at basin scale. Keeping in view of this, in this paper, an attempt was made to propose modification to simple monthly water balance model by integrating potential evapotranspiration with land use coefficients that were derived from the temporal satellite remote sensing data to compute runoff at basin scale. Godavari Basin, India was selected as study basin to demonstrate the approach. Monthly land use coefficients of all land use classes were computed during the calibration process of the model by matching the computed runoff with field runoff. Runoff during the last 18 years (1990–91 to 2007–08) was computed using the developed methodology. Four years datasets were used for model calibration and the rest of the data for model validation. Spatial annual groundwater flux, reservoir flux and domestic water consumption grids were computed using the field data and integrated with the model in computing runoff. From the Nash-Sutcliffe efficiency coefficient, it is found that computed runoff is very well matching the field runoff. The demonstrated approach is found to be more accurate and simple in computing runoff at basin scale in absence of high intensity meteorological data.
Similar content being viewed by others
References
Beven KJ (2002) Towards an alternative blueprint for a physically-based digitally simulated hydrologic response modeling system. Hydrol Process 16:189–206
Black PE (2007) Revising the Thornthwaite and Mather Water Balance. JAWRA 43(6):1604–1605
Canadell J, Jackson RB, Ehleringer JR, Mooney HA, Sala OE, Schulze ED (1996) Maximum rooting depth of vegetation types at the global scale. Oecologia 108:583–595
Citakoglu H, Cobaner M, Haktanir T, Ozgur K (2014) Estimation of monthly mean reference evapotranspiration in Turkey. Water Resour Manag 28:99–113
CWC (1999) Reassessment of water resources potential of India. CWC, New Delhi
Descheemaeker K, Raes D, Allen R, Nyssen J, Poesen J, Muys B, Haile M, Deckers J (2011) Two rapid appraisals of FAO-56 crop coefficients for semiarid natural vegetation of the northern Ethiopian highlands. J Arid Environ 75:353–359
Entekhabi D, Asrar GS, Wood EF (1999) An agenda for land-surface hydrology research and a call for the second hydrologic decade. Bull Am Meteorol Soc 80(10):2043–2058
FAO: Crop evapotranspiration—guidelines for computing crop water requirements. FAO Corporate Document Repository. www.fao.org/docrep/x0490e/x0490e0h.htm
Jain MK, Kothyari UC, Ranga Raju KG (2004) A GIS based distributed rainfall–runoff model. J Hydrol 299:107–135
Jianbiao L, Sun G, McNulty SG, Amatya DM (2005) A comparison of six potential evapotranspiration methods for regional use in the Southeastern United States. J Am Water Resour Assoc 41(3):621–633
Krause P, Boyle DP, Base F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97
Majone B, Bovolo CI, Bellin A, Blenkinsop S, Fowler HJ (2012) Modeling the impacts of future climate change on water resources for the Ga’llego river basin (Spain). Water Resour Res 48:1–18
Mohan S, Arumugam N (1994) Crop coefficients of major crops in South India. Agric Water Manag 26:67–80
NRSC (2009) Water Resources Assessment the National Perspective—a technical guide for research and practice, NRSC-RSGIS AA-WRG-WRD-Oct2009-TR98
Rahimikhoob A, Behbahani RM, Javad F (2012) An evaluation of four reference evapotranspiration models in a subtropical climate. Water Resour Manag 26:2867–2881
Rahimikhoob A, Asadi M, Mashal M (2013) A comparison between conventional and M5 model tree methods for converting pan evaporation to reference evapotranspiration for semi-arid region. Water Resour Manag 27:4815–4826
Rajeevan M, Jyote B (2008) A high resolution daily gridded rainfall data set (1971–2005) for mesoscale meteorological studies. National Climate Centre Report, India Meteorological Department, Pune
Ray SS, Dadhwal VK (2001) Estimation of crop evapotranspiration of irrigation command area using remote sensing and GIS. Agric Water Manag 49:239–249
Scherer FT, Seelig B, Franzen D (1996) Soil, water and plant characteristics important to irrigation. www.ag.ndsu.edu/pubs/ageng/irrigate/eb66w.htm
Sokolov AA, Champan TG (edited 1994) Methods for water balance computations—an international guide for research and practice. The Unesco Press, Paris
Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (edited 2000). Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007
Thronthwaite CW, Mather JR (1957) Instructions and tables for computing potential evapotranspiration and water balance. Laboratory of Climatology, Publication No. 10, Centerton
Traore S, Guven A (2012) Regional-specific numerical models of evapotranspiration using gene-expression programming interface in Sahel. Water Resour Manag 26:4367–4380
US Army Corps of Engineers (2000) Hydrological modeling system HEC-HMS technical reference manual, US army corps of engineers. Hydrologic Engineering Centre, USA
Vangelis H, Tigkas D, Tsakiris G (2013) The effect of PET method on Reconnaissance Drought Index (RDI) calculation. J Arid Environ 88:130–140
Xu CY, Singh VP (1998) A review on monthly water balance models for water resources investigation and climatic impact assessment. Water Resour Manag 12:31–50
Yuan W, Shuguang L, Shunlin L, Zhengxi T, Heping L, Claudia Y (2012) Estimations of evapotranspiration and water balance with uncertainty over the Yukon River Basin. Water Resour Manag 26:2147–2157
Acknowledgments
The first author sincerely acknowledges the DD-RSA, NRSC for providing continuous support and guidance during the project. The first author sincerely acknowledges the support and guidance provided by Dr. J R Sharma, then GD, WRG, NRSC during the project. The authors sincerely thank Member (WP&P)-CWC, and CE (BPMO)-CWC for their support. The authors deeply acknowledge The CE-CWC, Hyderabad and the Director, IMD for providing the hydro-meteorological data. The first author sincerely acknowledges Ashis Benarjee and Lalit Kumar, CWC, New Delhi for their support in executing the project and participating in the discussions. The first author acknowledges P V Raju and B Simhadri Rao for participating in discussions during the project.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Durga Rao, K.H.V., Rao, V.V. & Dadhwal, V.K. Improvement to the Thornthwaite Method to Study the Runoff at a Basin Scale Using Temporal Remote Sensing Data. Water Resour Manage 28, 1567–1578 (2014). https://doi.org/10.1007/s11269-014-0564-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-014-0564-8