Document Type: CASE STUDY


Department of Geology, College of Natural and Applied Sciences, University of Dar es Salaa, Tanzania


The lack of hydrological data for urbanizing watersheds in developing countries is one of the challenges facing decision making. Msimbazi River is located in the city center of Dar es Salaam and is highly influenced by human activities; this includes dense populations that are characterized by informal settlements. The catchment is currently undergoing flooding, which triggers a dilemma in its surface runoff trending. This study aimed to simulate rainfall-runoff of an urbanizing Msimbazi watershed that will provide an understanding of hydrological data including peak flows and discharge volumes of Msimbazi River. The data used in the study include soil, rainfall, DEM and land use. HEC-GeoHMS and ArchHydro tools in ArcGIS were used to generate hydrological inputs to be used in the HEC-HMS interface. The resulted sub-watersheds have high CN values ranging from 70 to 90 implying the possibility of high runoff potential. Sub-watershed W620 indicates the highest runoff, among others with the highest runoff of 290mm for the year 2015. The peak flow on the river indicates the value ranging from 7.2 m3/s to 30m3/s with the highest values being on the downstream. The overall trend indicates an increasing surface runoff and peak flow in sub-watersheds from 1985 to 2015. Simulated results in this study were validated with the observational data of the catchment recorded in 2017. Given that most of the rivers in Tanzania are ungauged, the approach applied in this study can be used to enhance decision making on settlement planning, water resource, and disaster management in the currently observed urbanizing areas.

Graphical Abstract


  • Urbanising Msimbazi River watershed has been experiencing an increase in flood events;
  • Sub-watersheds indicated high CN values ranging from 70 to 90 in 2015 implying the possibility of high runoff potential;
  • The simulated peak flow on the river indicates the value ranging from 7.2 m3/s to 30m3/s, with the highest values being on the downstream;
  • The simulated surface runoff in sub-watersheds indicates an overall increasing trend from 1985 to 2015.


Main Subjects

Ali, M.; Khan, S.J.; Aslam, I.; Khan, Z., (2011). Simulation of the impacts of land-use change on surface runoff of Lai Nullah Basin in Islamabad, Pakistan. Landscape Urban Plann., 102(4): 271-279 (9 pages).

Armstrong, A.M., (1987). Master plans for Dar-es-Salaam, Tanzania: The shaping of an African city. Habitat Int., 11(2): 133-145 (13 pages).

Bera, A.K.; Singh, V.; Bankar, N.; Salunkhe, S.S.; Sharma, J., (2014). Watershed delineation in flat terrain of Thar desert region in north west India–A semi automated approach using DEM. J. Indian Soc. Remote Sens., 42(1): 187-199 (13 pages).

Beven, K.; O'Connell, P., (1982). On the role of physically-based distributed modelling in hydrology ( 40 pages).

Blöschl, G., (2006). Rainfall‐runoff modeling of ungauged catchments. Encycl. Hydrol. Sci., (13 pages).

Devia, G.K.; Ganasri, B.; Dwarakish, G., (2015). A review on hydrological models. Aquat. Procedia, 4: 1001-1007 pages(5 pages).

Ebrahimian, A.; Gulliver, J.S.; Wilson, B.N., (2016). Effective impervious area for runoff in urban watersheds. Hydrol. Processes, 30(20): 3717-3729 (19 pages).

El Alfy, M., (2016). Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling. Hydrol. Res., 47(6): 1142-1160(19 pages).

Fleming, M.J.; Doan, J.H., (2010). HEC-GeoHMS geospatial hydrologic modeling extension. Davis: US. Army Corps of Eng., USA: (197 pages).

Franchini, M.; Lamberti, P., (1994). A flood routing Muskingum type simulation and forecasting model based on level data alone. Water Resour. Res., 30(7): 2183-2196 (14 Pages).

Gumindoga, W.; Rwasoka, D.T.; Nhapi, I.; Dube, T., (2017). Ungauged runoff simulation in Upper Manyame Catchment, Zimbabwe: Application of the HEC-HMS model. Phys. Chem. Earth Part A/B/C, 100: 371-382 (12 pages).

Hirabayashi, Y.; Mahendran, R.; Koirala, S.; Konoshima, L.; Yamazaki, D.; Watanabe, S.; Kim, H.; Kanae, S., (2013). Global flood risk under climate change. Nat. Climate Change., 3(9): (816 pages).

Kebede, A.S.; Nicholls, R.J., (2012). Exposure and vulnerability to climate extremes: population and asset exposure to coastal flooding in Dar es Salaam, Tanzania. Reg. Environ. Change., 12(1): 81-94 (14 pages).

Kombe, W.J., (2005). Land use dynamics in peri-urban areas and their implications on the urban growth and form: the case of Dar es Salaam, Tanzania. Habitat Int., 29(1): 113-135 (23 pages).

Loch, R., (2000). Effects of vegetation cover on runoff and erosion under simulated rain and overland flow on a rehabilitated site on the Meandu Mine, Tarong, Queensland. Soil Res., 38(2): 299-312 (14 pages).

Magesh, N.; Chandrasekar, N.; Soundranayagam, J.P., (2011). Morphometric evaluation of Papanasam and Manimuthar watersheds, parts of Western Ghats, Tirunelveli district, Tamil Nadu, India: a GIS approach. Environ. Earth Sci., 64(2): 373-381 (9 pages).

Mangan, P.; Haq, M.A.; Baral, P., (2019). Morphometric analysis of watershed using remote sensing and GIS—a case study of Nanganji River Basin in Tamil Nadu, India. Arabian J. Geosci., 12(6): (202 pages).

Mtoni, Y. E., Mjemah, I., Msindai, K., Van Camp, M.,  Walraevens, K. (2012). Saltwater intrusion in the Quaternary aquifer of the Dar es Salaam region, Tanzania. Geol. Belg., 15(1-2): 16-25 (10 pages).

Mutayoba, E.; Kashaigili, J.J.; Kahimba, F.C.; Mbungu, W.; Chilagane, N.A., (2018). Assessing the Impacts of Land Use and Land Cover Changes on Hydrology of the Mbarali River Sub-Catchment. The Case of Upper Great Ruaha Sub-Basin, Tanzania. J. Eng., 10(09): (616 pages).

Ndetto, E.L.; Matzarakis, A., (2013). Basic analysis of climate and urban bioclimate of Dar es Salaam, Tanzania. Theor. Appl. Climatol., 114(1-2): 213-226  (14 pages).

Ngailo, T.J.; Shaban, N.; Reuder, J.; Mesquita, M.D.; Rutalebwa, E.; Mugume, I.; Sangalungembe, C., (2018). Assessing Weather Research and Forecasting (WRF) Model Parameterization Schemes Skill to Simulate Extreme Rainfall Events over Dar es Salaam on 21 December 2011. J. Geosci. Environ. Protect., 6(01): (36 pages).

Ngana, J. (2010). Ruvu Basin: A Situation Analysis: Report for the Wami/Ruvu Basin Water Office: IUCN., (89 pages).

Pareta, K.; Pareta, U., (2011). Quantitative morphometric analysis of a watershed of Yamuna basin, India using ASTER (DEM) data and GIS. Int. J. Geomatics Geosci., 2(1): 248-269 (57 pages)..

Rao, G.S.; Giridhar, M.; Mohan, S.; Sowmya, P., (2017). Estimation Of SCS Curve Number For Kaddam Water Shed Using Remote Sensing And Gis. Int. J. Creative Res. Thoughts, 5: 203-208 pages(6 pages).

Sardoii, E.R.; Rostami, N.; Sigaroudi, S.K.; Taheri, S., (2012). Calibration of loss estimation methods in HEC-HMS for simulation of surface runoff (Case Study: Amirkabir Dam Watershed, Iran). Adv. Environ. Biol., 6(1): 343-348 (6 pages).

Satheeshkumar, S.; Venkateswaran, S.; Kannan, R., (2017). Rainfall–runoff estimation using SCS–CN and GIS approach in the Pappiredipatti watershed of the Vaniyar sub basin, South India. Model. Earth Syst. Environ., 3(1): (8 pages).

Scharffenberg, W.; Harris, J., (2008). Hydrologic Engineering Center Hydrologic Modeling System, HEC-HMS: Interior Flood Modeling. Paper presented at the World Environmental and Water Resources Congress 2008: Ahupua'A (3 Pages).

Schofield, D.; Gubbels, F., (2019). Informing notions of climate change adaptation: a case study of everyday gendered realities of climate change adaptation in an informal settlement in Dar es Salaam. Environ. Urban. 31(1): 93-114 (22 pages).

Smiley, S.L.; Hambati, H., (2019). Impacts of flooding on drinking water access in Dar es Salaam, Tanzania: implications for the Sustainable Development Goals. J. Water Sanitation Hygiene, 9(2): 392-396 (5 pages).

Tachikawa, T.; Hato, M.; Kaku, M.; Iwasaki, A., (2011). Characteristics of ASTER GDEM version 2. In 2011. IEEE Int. Geosci. Remote Sens. Symp. 3657-3660 (4 pages).

Van Dijk, A.I.; Brakenridge, G.R.; Kettner, A.J.; Beck, H.E.; De Groeve, T.; Schellekens, J., (2016). River gauging at global scale using optical and passive microwave remote sensing. Water Resour. Res., 52(8): 6404-6418 (15 pages).

Winsemius, H.C.; Aerts, J.C.; van Beek, L.P.; Bierkens, M.F.; Bouwman, A.; Jongman, B.; Kwadijk, J.C.; Ligtvoet, W.; Lucas, P.L.; Van Vuuren, D.P., (2016). Global drivers of future river flood risk. Nat. Clim. Change., 6(4): (381 pages).

Zhang, J., Li, Q., Gong, H., Li, X., Song, L., Huang, J. (2010). Hydrologic information extraction based on arc hydro tool and DEM. Paper presented at the 2010 Int. Conference on Challenges in Environ. Sci. Comput. Eng., (4 pages).

Letters to Editor

GJESM Journal welcomes letters to the editor for the post-publication discussions and corrections which allows debate post publication on its site, through the Letters to Editor. Letters pertaining to manuscript published in GJESM should be sent to the editorial office of GJESM within three months of either online publication or before printed publication, except for critiques of original research. Following points are to be considering before sending the letters (comments) to the editor.

[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.
[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.
[3] Letters can be no more than 300 words in length.
[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.
[5] Anonymous letters will not be considered.
[6] Letter writers must include their city and state of residence or work.
[7] Letters will be edited for clarity and length.