Investigation of Temporal and Spatial Variations of Water Balance Components and Hydrograph Separation of Arazkouse Watershed through Groundwater Recharge Modeling using WetSpass Model

Document Type : Complete scientific research article

Authors

1 gorgan univrsity

2 Associate Professor, Faculty of Water Resource Engineering, Shahrekord University

3 Gorgan University of Agricultural Sciences and Natural Resources

4 Assistant Professor, Faculty of Agriculture Sciences, Department of Water Engineering, University of Jiroft

5 Faculty member / Gorgan University of Agricultural Sciences and Natural Resources

Abstract

Background and aims: Groundwater recharge is one of the most important factors in sustainable development and management of groundwater resources. Obviously, other hydrological, social and economic factors should also be considered. Estimation of recharge is a complex and challenging process. This is due to this fact that recharge is dependent on variables such as land use, topography, soil, climatic conditions, as well as on other hydrological factors. In this research, the monthly water balance components were estimated using distributed WetSpass model.

Materials and methods: In this research, water balance components including evapotranspiration, interception, runoff, and groundwater recharge for the Arazkouse Watershed during the years 2001–2015 on a monthly basis at spatial resolution of 100 m * 100 m were simulated using WetSpass model and rainfall, temperature, evaporation, wind velocity, groundwater depth data and soil texture, topography and land use maps of the area.

Results: The findings in this research are based on evaluation criteria used in calibration and validation periods of flow hydrograph components including direct runoff, base flow, and total flow simulated by WetSpass model and hydrographs separated by WHAT software. The WetSpass model had a relatively satisfactory performance for simulating groundwater recharge and other hydrologic components of the Arazakouse watershed. It should be noted that the Nash-Sutcliffe coefficient values for the calibration and validation periods ​​as standard criteria of evaluation in the hydrological simulations for direct runoff are 0.6 and 0.51, respectively. In addition, considering the base flow, Nash-Sutcliffe coefficients for the calibration and validation periods were 0.55 and 0.50, respectively. The values for total runoff for calibration and validation periods were 0.63 and 0.53, respectively. After investigating the efficiency of the model, the temporal-spatial distribution of water balance components for different land use types and slope classes was investigated. The analysis shows that the variability of the hydrologic components is significantly affected by climate and its seasonal changes and also by characteristics of physiography, vegetation and land use.
The annual volume of recharge and runoff in the forest areas are 23115791 m3 and 1776217 m3 respectively. The highest proportion of runoff in this land use belongs to slopes above 30%. The highest volume of annual runoff in the Arazkoush watershed is in the residential areas in medium and high slopes with 156300 m3.

Conclusions: According to the research, it can be stated that the amount of water balance components, especially the amount of recharge as an important factor in the investigation of surface and groundwater interaction are influenced by climatic, physiographic, and land use/land cover factors . Therefore proper estimation of water balance components can play an important role in sustainable management and development of surface and groundwater resources.

Keywords

References

1.Abdollahi, K. 2015. Basin scale water balance modelling for variable hydrological regimes and temporal scales. PhD Thesis, Department of Hydrology and Hydraulic Engineering, Faculty of Engineering, VrijeUniversiteitBrusel, 176p.
2.Abdollahi, K., Bashir, I., Verbeiren, B., Harouna, M.R., Griensven, A.V., Husmans, M., and Batelaan, O. 2017.
A distributed monthly water balance model: formulation and application on Black Volta Basin. Environ. Earth Sci. J. 76: 198. 1-18.
3.Afkhami, M., and NassiriSaleh, F.2015. Evaluation of the application distributed and lumped hydrologic models in simulation of mean daily flow discharge in Gharasoo River Basinin Ardebil. Modares Civil Engin. J.15: Supplementary Issue. 31-40.
4.Arnold, J.G., and Allen, P.M. 1999. Automated methods for estimating base-flow and groundwater recharge from stream-flow records. Amer. Water Resour. Assoc. J. 35: 2. 411-424.
5.Arnold, J.G., Muttiah, R.S., Srinivasan, R., and Allen, P.M. 2000. Regional estimation of base- flow and groundwater recharge in the Upper Mississippi River Basin. Hydrol. J. 227: 1-4: 21-40. doi: 10.1016/S0022-1694(99)00139-0.
6.Bahremand, A., De Smedt, F., Corluy,
J., Liu, Y.B., Poorova, J., Velcicka, L., and Kunikova, E. 2007. WetSpa model application for assessing reforestation impacts on floods in Margecany-Hornad Watershed, Slovakia. Water Resources Management. J. 21: 8. 1373-1391.
7.Batelaan, O., and De Smedt, F. 2001. WetSpass: a flexible, GIS based, distributed recharge methodology for regional groundwater modeling. Impact of Human Activity on Groundwater Dynamics (Proceedings of a symposium held during the Sixth IAHS Scientific Assembly at Maastricht, The Netherlands, July 2001). IAHS. 269: 11-18.
8.Batelaan, O., and De Smedt, F. 2007. GIS-based recharge estimation by coupling surface-subsurface water balances. Hydrol. J. 337: 3. 337-355.
9.Bayati, S., Nasr Esfahani, A., and Abdollahi, Kh. 2018. An investigation on spatial distribution of runoff and groundwater recharge in land use and slope classes of Vanak Watershed, Water. Engin. Manage. J. 11: 4. 866-878, DOI: 10.22092/ ijwmse. 2018. 120332.1431. (In Persian)
10.Chen, J., Lee, F., Yeh, C.H., and Yu, J.L. 2005. A water budget model for the Yun-Lin Plain, Taiwan. Water Resour. Manage. J. 19: 5. 483-504.
11.Faryabi, M., and Chitsazan, M. 2016. Evaluation of river–aquifer interaction using physicochemical parameters, Case study: the north part of Dezful-Andimeshk district. Environ. Geol. J. 10: 34. 101-115. (In Persian)
12.Gebre, S.L. 2015. Application of the HEC-HMS Model for runoff simulation of upper Blue Nile RiverBasin. Hydrology Current Research, 6: 2. 1-8.
13.Ghiglieri, G., Carletti, A., and Pittalis, D. 2014. Runoff coefficient and average yearly natural aquifer recharge assessment by physiography-based indirect methods for the island of Sardinia (Italy) and its NW area (Nurra). Hydrol. J. 519: 2. 1779-1791.
14.Gupta, V., Kling, H., Yilmaz, K.K., and Martinez, G.F. 2009. Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Hydrol. J. 377: 1-2. 80-91. DOI: 10.1016/j. jhydrol.2009.08.003.
15.Kendy, E., Gerard, P., Todd Walter, M., Zhang, Y., Liu, C., and Steenhuis,T.S. 2003. A soil water balance approach to quantify groundwater recharge from irrigated cropland in the North China Plain. Hydrological Processes, 17: 10. 2011-2031.
16.Kling, H., Fuchs, M., and Paulin, M. 2012. Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Hydrol. J. 424: 4. 264-277. DOI:10.1016/ j.jhydrol. 2012.01.011.
17.Lin, Y.C., Yang, S.Y., Fen, C.S., and Yeh, H.D. 2016. A general analytical model for pumping tests in radial finite two-zone confined aquifers withRobin-type outer boundary. Hydrol. J.540: 9. 1162-1175.
18.Manfreda, S., Fiorentino, M., and Iacobellis, V. 2005. DREAM: a distributed model for runoff, evapotranspiration, and antecedent soil moisture simulation. Advances in Geosciences, 2: 2. 31-39.
19.Melki, A., Abdollahi, Kh., Fatahi, R., and Abida, H. 2017. Groundwater recharge estimation under semi-arid climate: Case of Northern Gafsa watershed, Tunisia. J. Afric. Earth Sci. J. 132:8. 37- 46. doi: 10.1016/j.jafrearsci. 2017.04.020.
20.Mustafa, S.M., Abdollahi, K., and Verbeiren, B. 2017. Identification of the influencing factors on groundwater drought and depletion in north-western Bangladesh. Hydrogeol. J. 25: 5. 1357-1375. DOI 10.1007/s10040-017-1547-7.
21.Nash, J.E., and Sutcliffe, J.V. 1970. River flow forecasting through conceptual models. 1. A Discussion of Principles. Hydrol. J. 10: 3. 282-290.
22.Nathan, R.J., and McMahon, T.A. 1990. Evaluation of automated techniques for baseflow and recession analysis. Water Resour. Res. J. 26: 7. 1465-1473.
23.Pandian, M., Balasubramaniam, R., and Saravanavel, J. 2014. Identification of groundwater potential recharge zones using WetSpass model in parts of Coimbatore and districts in Tamil Nadu, India. Inter. J. Water Res. J.98: 2. 27-32.
24.Pechlivanidis, I., Jacson, B., Mcintyre, N., and Wheater, H. 2011. Catchment scale hydrological modeling. A review of model types, calibration approaches and uncertainty methods in the context of recent developments in technology and applications. Global Network Environ. Sci. Technol. J. 13: 3. 193-214.
25.Shiklomanov, I.A. 2000. Appraisal and assessment of world water resources. Water Int. J. 25: 1. 11-32.
26.Seiler, K.P., and Gat, J.R. 2007. Groundwater recharge, runoff, infiltration and percolation. Springer, Dordrecht (Netherlands). 241p.
27.Soleimani-Motlagh, M., Ghasemieh, H., Talebi, A., Abdollahi, K., and Dragoni, W. 2020. Groundwater budget deficit caused by drought and overexploitation, Water Supply. 20: 2. 621-632.
28.Sophocleous, M. 2004. Groundwater recharge. In: Luis Silveira, Usunoff, E.J. (Eds.), Groundwater, in Encyclopedia of Life Support Systems (EOLSS), Vol. I. Developed under the auspices of the UNESCO, EOLSS, Publishers, Oxford, UK, 41p. (http://www.eolss.net/).
29.Wang, Z.M., Batelaan, O., and de Smedt, F. 1997. A distributed model
for water and energy transfer between soil, plants and atmosphere (WetSpa). Physics and Chemistry of the Earth. J. 21: 3. 189-193.
30.Yun, P., Huili, G., Demin, Z., Xiaojuan, L., and Nobukazu, N. 2011. Impact of land use change on groundwater recharge in Uishui River Basin, China. Chinese Geograph. Sci. J. 21: 6. 734-743.
31.Zomlot, Z., Verbiren, B., Huysmans,M., and Batelaan. O. 2015. Spatial distribution of groundwater recharge and base flow: Assessment of controlling factors. Hydrol. J. 531: 2. 349-368.
Journal of Water and Soil Conservation
Volume 27, Issue 1
March and April 2020
Pages 25-47

Files

Share

How to cite

Statistics