CWEEE  Vol.11 No.2 , April 2022
Using SWAT Model and Field Data to Determine Potential of NASA-POWER Data for Modelling Rainfall-Runoff in Incalaue River Basin
Abstract: Incalaue is a tributary of Lugenda River in NSR (Niassa Special Reserve) in North-Eastern Mozambique. NSR is a data-poor remote area and there is a need for rainfall-runoff data to inform decisions on water resources management, and scientific methods are needed for this wide expanse of land. This study assessed the potential of a combination of NASA-POWER (National Aeronautics and Space Administration and Prediction of Worldwide Energy Resources) remotely sensed rainfall data and FAO (Food and Agriculture Organization of the United Nations) soil and land use/cover data for modelling rainfall-runoff in Incalaue river basin. DEM (Digital Elevation Model) of 1:250,000 scale and a grid resolution of 30 m × 30 m downloaded from USGS (the United States Geological Survey) website; clipped river basin FAO digital soil and land use/cover maps; and field-collected data were used. SWAT (Soil and Water Assessment Tool) model was used to assess rainfall -runoff data generated using the NASA-POWER dataset and gauged rainfall and river flow data collected during fieldwork. FAO soil and land use/cover datasets which are globally available and widely used in the region were used for comparison with soil data collected during fieldwork. Field collected data showed that soil in the area is predominantly sandy loam and only sand content and bulk density were uniformly distributed across the soil samples. SWAT model showed a good rainfall-runoff relationship using NASA-POWER data for the area (R2 = 0.7749) for the studied period (2019-2021). There was an equally strong rainfall-runoff relationship for gauged data (R2 = 0.8131). There were uniform trends for the rainfall, temperature, and relative humidity in NASA-POWER meteorological data. Timing of peaks and lows in rainfall and river flow observed in the field and modelled were confirmed by residents as the trend in the area. This approach was used because there was no historical rainfall and river flow data since the river basin is ungauged for hydrologic data. The study showed that NASA-POWER data has the potential for use for modelling the rainfall-runoff in the basin. The difference in rainfall-runoff relationship with field-collected data could be because of landscape characteristics or topsoil layer not catered for in the FAO soil data.
Cite this paper: Natumanya, E. , Ribeiro, N. , Mwanjalolo, M. and Steinbruch, F. (2022) Using SWAT Model and Field Data to Determine Potential of NASA-POWER Data for Modelling Rainfall-Runoff in Incalaue River Basin. Computational Water, Energy, and Environmental Engineering, 11, 65-83. doi: 10.4236/cweee.2022.112004.

[1]   Chen, Z., Weiguang, W. and Fu, J. (2020) Vegetation Response to Precipitation Anomalies under Different Climatic and Biogeographical Conditions in China. Scientific Reports, 10, Article No. 830.

[2]   Istanbulluoglu, E. and Bras, R.L. (2005) Vegetation-Modulated Landscape Evolution: Effects of Vegetation on Landscape Processes, Drainage Density, and Topography. Journal of Geophysical Research, 110, F02012.

[3]   Istanbulluoglu, E., Tarboton, D.G., Pack, R.T. and Luce, C.H. (2004) Modeling of the Interactions between Forest Vegetation, Disturbances, and Sediment Yields. Journal of Geophysical Research, 109, F01009.

[4]   Lu, Z., Zou, S., Qin, Z., Yang, Y., Xiao, H., Wei, Y., Zhang, K. and Xie, J. (2015) Hydrologic Responses to Land Use Change in the Loess Plateau: Case Study in the Upper Fenhe River Watershed. Advances in Meteorology, 2015, Article ID: 676030.

[5]   Cuo, L. and Zhang, Y. (2013) The Impacts of Climate Change and Land Cover/Use Transition on the Hydrology in the Upper Yellow River Basin, China. Journal of Hydrology, 502, 37-52.

[6]   Zhang, L., Nan, Z., Xu, Y. and Li, S. (2016) Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China. PLoS ONE, 11, e0158394.

[7]   Sivapalan, M., Takeuchi, K., Franks, S.W., Gupta, V.K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J.J., Mendiondo, E.M., O’Connell, P.E., Oki, T., Pomeroy, J.W., Schertzer, D., Uhlenbrook, S. and Zehe, E. (2003) IAHS Decade on Predictions in Ungauged Basins (PUB), 2003-2012: Shaping an Exciting Future for the Hydrological Sciences. Hydrological Sciences Journal, 48, 857-880.

[8]   Young,P. and Romanowicz, R.J. (2004) PUB and Data-Based Mechanistic Modelling: The Importance of Parsimonious Continuous-Time Models. International Congress on Environmental Modelling and Software. 20.

[9]   Hrachowitz, M., Savenije, H.H.G., Blöschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E. and Cudennec, C. (2013) A Decade of Predictions in Ungauged Basins (PUB)—A Review. Hydrological Sciences Journal, 58, 1198-1255.

[10]   Piedallu, C., Lebourgeois, F., Perez, V. and Lebourgeois, F. (2012) Soil Water Balance Performs Better than Climatic Water Variables in Tree Species Distribution Modelling. Global Ecology and Biogeography, 22, 470-482.

[11]   Fereydan, C., Eghdami, H., Azhdari, G., Lebailly, P. and Azadi, H. (2019) Impact of Land Use Changes on Soil and Vegetation in Fereydan, Iran. Agriculture, 9, Article 58.

[12]   Allen, A.M. and Singh, N.J. (2016) Linking Movement Ecology with Wildlife Management and Conservation. Frontiers in Ecology and Evolution, 3, Article 155.

[13]   Osei, M.A., Amekudzi, L.K., Wemegah, D.D., Preko, K., Gyawu, E.S. and Obiri-Danso, K. (2017) Hydro-Climatic Modelling of an Ungauged Basin in Kumasi, Ghana. Hydrology Earth System Sciences Discussions, 2017, 1-19.

[14]   Pandey, A., Bishal, K.C., Kalura, P., Chowdary, V.M., Jha, C.S. and Cerdà, A. (2021) A Soil Water Assessment Tool (SWAT) Modeling Approach to Prioritize Soil Conservation Management in River Basin Critical Areas Coupled with Future Climate Scenario Analysis. Air, Soil and Water Research, 14, 1-17.

[15]   Tudose, N.C., Marin, M., Cheval, S., Ungurean, C., Davidescu, S.O., Tudose, O.N., Mihalache, A.L. and Davidescu, A.A. (2021) SWAT Model Adaptability to a Small Mountainous Forested Watershed in Central Romania. Forests, 12, Article 860.

[16]   Wu, Y., Xu, Y., Yin, G., Zhang, X., Li, C., Wu, L., Wang, X., Hu, Q. and Hao, F. (2021) A Collaborated Framework to Improve Hydrologic Ecosystem Services Management with Sparse Data in a Semi-Arid Basin. Hydrology Research, 52, 1159-1172.

[17]   Näschen, K., Id, B.D., Leemhuis, C., Steinbach, S., Seregina, L.S., Id, F.T. and Van Der Linden, R. (2018) Hydrological Modeling in Data-Scarce Catchments: The Kilombero Floodplain in Tanzania. Water, 10, Article 599.

[18]   Mishra, H., Mario, D., Shakti, D., Mukesh, S., Kumar, S., Anjelo, S., Denis, F. and Kumar, R. (2017) Hydrological Simulation of a Small Ungauged Agricultural Watershed Semrakalwana of Northern India. Applied Water Science, 7, 2803-2815.

[19]   Amatya, D.M., Williams, T.M., Skaggs, R.W. and Nettles, J.E. (2011) Advances in Forest Hydrology: Challenges and Opportunities. American Society of Agricultural and Biological Engineers, 54, 2049-2056.

[20]   Allan, J.R., Grossmann, F., Craig, R., Nelson, A., Flower, K., Bampton, J., Deffontaines, J., Miguel, C., Araquechande, B. and Watson, J.E.M. (2017) Patterns of Forest Loss in One of Africa’s Last Remaining Wilderness Areas: Niassa National Reserve (Northern Mozambique). PARKS, 23, 39-50.

[21]   Ministry for Co-Ordination of Environmental Affairs—MICOA (2003) Mozambique Initial National Communication to the United Nations Framework Convention on Climate Change. No. April, 1-120.

[22]   Fundação, I.G.F. (Vernon Booth) (2012) Intermediate Working Paper on Contribution of Tourism Hunting to the Economy in Mozambique. Projecto DNAC/AFD 01.

[23]   Souirji, A. (1997) Soil and Terrain Database of Mozambique. Scale 1:1,000,000. Consultant Report.

[24]   Timberlake, J., Golding, J. and Clarke, P. (2004) Niassa Botanical Expedition—June 2003. Occasional Publications in Biodiversity, Bulawayo.

[25]   Ribeiro, N., Matos, C.N., Moura, I.R., Washington-Allen, R.A. and Ribeiro, A.I. (2013) Monitoring Vegetation Dynamics and Carbon Stock Density in Miombo Woodlands. Carbon Balance and Management, 8, Article No. 11.

[26]   Bourdin, D.R., Fleming, S.W. and Stull, R.B. (2012) Streamflow Modelling: A Primer on Applications, Approaches and Challenges. Atmosphere-Ocean, 50, 507-536.

[27]   Ribeiro, N.S., Matos, C.N., Moura, I.R., Washington-Allen, R.A. and Ribeiro, A.I. (2013) Monitoring Vegetation Dynamics and Carbon Stock Density in Miombo Woodlands. Carbon Balance and Management, 8, Article No. 11.

[28]   Ribeiro, N.S., Saatchi, S.S., Shugart, H.H. and Washington-Allen, R.A. (2008) Aboveground Biomass and Leaf Area Index (LAI) Mapping for Niassa Reserve, Northern Mozambique. Journal of Geophysical Research: Biogeosciences, 113, G02S02.

[29]   Wolf, U. and Lorenzini, M. (2007) Land Unit-Land System Mapping of Moçambique.

[30]   Van Wart, J., Grassini, P., Yang, H., Claessens, L., Jarvis, A. and Cassman, K.G. (2015) Creating Long-Term Weather Data from Thin Air for Crop Simulation Modeling. Agricultural and Forest Meteorology, 209-210, 49-58.

[31]   Tadesse, W., Whitaker, S., Crosson, W. and Wilson, C. (2015) Assessing the Impact of Land-Use Land-Cover Change on Stream Water and Sediment Yields at a Watershed Level Using SWAT. Open Journal of Modern Hydrology, 5, 68-85.

[32]   Asseng, S., Cammarano, D., Basso, B., Chung, U., Alderman, P.D., Sonder, K., Reynolds, M. and Lobell, D.B. (2017) Hot Spots of Wheat Yield Decline with Rising Temperatures. Global Change Biology, 23, 2464-2472.

[33]   Anaba, L.A., Banadda, N., Kiggundu, N., Wanyama, J., Engel, B. and Moriasi, D. (2017) Application of SWAT to Assess the Effects of Land Use Change in the Murchison Bay Catchment in Uganda. Computational Water, Energy, and Environmental Engineering, 6, 24-40.

[34]   Qi, J., Wang, Q. and Zhang, X. (2019) On the Use of NLDAS2 Weather Data for Hydrologic Modeling in the Upper Mississippi River Basin. Water (Switzerland), 11, Article 960.

[35]   Ceradini, J., Keinath, D., Abernethy, I., Andersen, M. and Wallace, Z. (2021) Crossing Boundaries in Conservation: Land Ownership and Habitat Influence the Occupancy of an At-Risk Small Mammal. Ecosphere, 12, e03324.

[36]   Holthuijzen, M.F., Beckage, B., Clemins, P.J., Higdon, D. and Winter, J.M. (2021) Constructing High-Resolution, Bias-Corrected Climate Products: A Comparison of Methods. Journal of Applied Meteorology and Climatology, 60, 455-475.

[37]   Hermann, S., Miketa, A. and Fichaux, N. (2014) Estimating the Renewable Energy Potential in Africa. IRENA-KTH Working Paper, International Renewable Energy Agency, Abu Dhabi.

[38]   Emam, A.R., Kappas, M., Nguyen, L.H.K. and Renchin, T. (2016) Hydrological Modeling in an Ungauged Basin of Central Vietnam Using SWAT Model. Hydrology and Earth System Sciences Discussions.

[39]   Kondo, M.C., Bream, K.D., Barg, F.K. and Branas, C.C. (2014) A Random Spatial Sampling Method in a Rural Developing Nation. BMC Public Health, 14, Article No. 338.

[40]   Von der Heyden, C.J. and New, M.G. (2003) The Role of a Dambo in the Hydrology of a Catchment and the River Network Downstream. Hydrology and Earth System Sciences, 7, 339-357.