UBC Theses and Dissertations

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UBC Theses and Dissertations

Rainfall, runoff and soil degradation in the Hindu Kush-Himalayas - a case study in Hilkot watershed Pakistan Zokaib, Suhail


Surface runoff and sediment transport are often considered as the two most important hydrological parameters in water resources engineering. Surface soil erosion from most of the areas is a serious threat to sustainable agriculture and sediment accumulation in reservoirs. An extensive runoff and soil erosion study was conducted in Hilkot watershed, Pakistan. The watershed consists of four major land uses including degraded, forests, agricultural, and pasture lands. The main objective of this dissertation was to provide a better understanding of the hydrologic and land use behavior of the watershed. Moreover, the goals were: 1) to calculate and compare annual rainfall, runoff and soil losses with their seasonal distribution from different land uses; 2) to establish rainfall, runoff and soil loss relationships; and 3) to develop a calibrated mathematical model for runoff and soil loss estimation. Overall, the results obtained from this research demonstrated that the Hilkot watershed falls in the monsoon region with about 38% rainfall occurred in the monsoon period (July to September). The average annual rainfall found in the study area was 1160 mm. In all the erosion plots, almost 50% of the runoff and soil loss occurred during the monsoon period. The mean maximum runoff was from the degraded plot (674 m³/ha/y), while the minimum was observed at the pasture plot (310 m³/ha/y). The average runoffs on other land uses were 529 and 460 m³/ha/y from the forest and agriculture plots, respectively. The average maximum soil loss was recorded from the degraded plot (6.5 t/ha/y) and the average minimum (1.8 t/ha/y) was on the pasture plot. Similarly, the average soil losses were 3.3 and 3.4 t/ha/y measured from the forest and agricultural plots, respectively. Polynomial regression analyses were developed for predicting rainfall, runoff and soil loss relationships and showed a reasonable correlation among the parameters. A mathematical model was also developed and calibrated with field data (using a genetic algorithm approach) to estimate the total runoff and soil loss for various land uses. The model reproduced the measured field data reasonably well and it indicated the highest and lowest runoff and soil loss for degraded and pasture lands, respectively.

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