Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management

被引:284
作者
Mango, L. M. [1 ]
Melesse, A. M. [1 ]
McClain, M. E. [1 ,2 ]
Gann, D. [3 ]
Setegn, S. G. [1 ]
机构
[1] Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA
[2] UNESCO IHE Inst Water Educ, Dept Water Sci & Engn, Delft, Netherlands
[3] Florida Int Univ, Geog Informat Syst Remote Sensing Ctr, Miami, FL 33199 USA
关键词
SWAT MODEL; WATER-RESOURCES; RAINFALL; VULNERABILITY; UNCERTAINTY; CATCHMENT; QUALITY;
D O I
10.5194/hess-15-2245-2011
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5-10%) accompanied by increases in temperature (2.5-3.5 degrees C). Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (-3%) and high (+25%) extremes of projected precipitation changes, but under median projections (+7%) there is little impact on annual water yields or mean discharge. Modest increases in precipitation are partitioned largely to increased evapotranspiration. Overall, model results support the existing efforts of Mara water resource managers to protect headwater forests and indicate that additional emphasis should be placed on improving land management practices that enhance infiltration and aquifer recharge as part of a wider program of climate change adaptation.
引用
收藏
页码:2245 / 2258
页数:14
相关论文
共 39 条
  • [1] Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT
    Abbaspour, Karim C.
    Yang, Jing
    Maximov, Ivan
    Siber, Rosi
    Bogner, Konrad
    Mieleitner, Johanna
    Zobrist, Juerg
    Srinivasan, Raghavan
    [J]. JOURNAL OF HYDROLOGY, 2007, 333 (2-4) : 413 - 430
  • [2] Abbaspour KC, 2004, VADOSE ZONE J, V3, P1340
  • [3] Anderson J.R., 1976, A land use and land cover classification system for use with remote sensor data, P1
  • [4] [Anonymous], 2005, 8 INT RIVER S
  • [5] [Anonymous], SCI CLIM CHANG
  • [6] Characteristic 20th and 21st century precipitation and temperature patterns and changes over the Greater Horn of Africa
    Anyah, Richard O.
    Qiu, Weini
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2012, 32 (03) : 347 - 363
  • [7] Large area hydrologic modeling and assessment - Part 1: Model development
    Arnold, JG
    Srinivasan, R
    Muttiah, RS
    Williams, JR
    [J]. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 1998, 34 (01): : 73 - 89
  • [8] Christensen JH, 2007, CLIMATE CHANGE 2007
  • [9] Di Luzio M, 2002, J AM WATER RESOUR AS, V38, P1127, DOI 10.1111/j.1752-1688.2002.tb05551.x
  • [10] EFFECTIVE AND EFFICIENT GLOBAL OPTIMIZATION FOR CONCEPTUAL RAINFALL-RUNOFF MODELS
    DUAN, QY
    SOROOSHIAN, S
    GUPTA, V
    [J]. WATER RESOURCES RESEARCH, 1992, 28 (04) : 1015 - 1031