2026-09-26T10:56:18Zhttps://dspace.unza.zm/server/oai/request

oai:dspace.unza.zm:123456789/47422019-08-19T14:28:20Zcom_123456789_18col_123456789_82

Mtonga, Christopher 2017-07-25T15:10:05Z 2017-07-25T15:10:05Z 2016 Post Grad. Dip. in integrated Water Resources Management This study embarked on trend analysis to understand the relationship that exists in weather, precipitation and river flow using time series data. The study area was the entire country of Zambia. Secondary hydrological and weather data used was representative of the six catchment areas of the country and the three agro-ecological zones. Weather records were obtained from SWAT- soil, an internet based software that stores daily meteorological data across the globe from 1979 to 2009 were temperature was extracted and used as reference for weather data. For stream flows, 40 hydrological gauge data sets were acquired from DWA for the same period across the country. The hydrological data sets were then classified into clusters using the five indicators of hydrologic alterations namely; the frequency of flows, the magnitude of flows, the duration of flows, the timing of flows and the rates of change in flows. The metrics for these indicators of hydrologic alterations were obtained using time series analysis (TSA) in river analysis package (RAP). Stream-flows of each station were grouped in three clusters according to precipitation patterns in agro-ecological zones and according to the area each stream drained. These clusters were used together with the corresponding temperature data sets for trend analyses and linear regressions. It was found that firstly, there was an upward trend in temperature across the clusters for the temporal window period of the study. Secondly, temperature is a predictor of precipitation and discharge in streams across the country based on the P values (0.10 – 0.50) and r2 values (0.008 – 0.336) obtained from regression and trend analysis. This was observed in 39 hydrological and meteorological gauge stations used. Thirdly, temperature predicts stream-flow in rivers with large catchment areas (>40,000km2) across all agro-ecological zones and perennial rivers in Agroecological zone III. It was further found that temperature does not predict stream-flow of ephemeral streams based on the P values (>0.50) obtained on temperature-discharge relationship of these streams. Based on the findings, it is concluded that temperature has been increasing with time and that it predicts precipitation negatively across the agro-ecological zones in Zambia. Climate variables are characteristic of increasing or decreasing trend in Zambia. http://dspace.unza.zm/handle/123456789/4742 en University of Zambia Climate Changes-Zambia Precipitation Forecasting-Zambia Characteristics of trends and relationships among climate variables in Zambia Thesis