Wami river basin experiences a lot of human disturbances due to agricultural expansion, and increasing urban demand for charcoal, fuel wood and timber; resulting in forest and land degradation. Comparatively little is known about factors that affect runoff behaviour and their relation to landuse in data poor catchments like Wami. This study was conducted to assess the hydrological response of land use/cover change on Wami River flows. In data poor catchments, a promising way to include landuse change is by integrating Remote Sensing and semi-distributed rainfall-runoff models. Therefore in this study SWAT model was selected because it applies semi-distributed model domain. Spatial data (landuse, soil and DEM-90m) and Climatic data used were obtained from Water Resources Engineering Department, government offices and from the global data set. SWAT model was used to simulate streamflow for landuse/landcover for the year 1987 and 2000 to determine the impact of land use/cover change on Wami streamflow after calibrating and validating with the observed flows. Land use maps of 1987 and 2000 were derived from satellite images using ERDAS Imagine 9.1 software and verified by using 1995 land use which was obtained from Institute of Resource Assessment (IRA). Findings show that there is decrease of Forest area by 1.4%, a 3.2% increase in Agricultural area, 2.2% increase in Urban and 0.48% decreases in Waterbody area between 1987 and 2000. The results from SWAT model simulation showed that the average river flows has decreased from 166.3 mm in 1987 to 165.3 mm in 2000. The surface runoff has increased from 59.4mm (35.7%) in 1987 to 65.9mm (39.9%) in 2000 and the base flow decreased from 106.8mm (64.3%) to 99.4mm (60.1%) in 1987 and 2000 respectively. This entails that the increase of surface runoff and decrease of base flows are associated with the land use change.
Abstract. This study was designed to investigate the dynamics of current and future surface water availability for different water users in the upper Pangani River Basin under changing climate. A multi-tier modeling technique was used in the study, by coupling the Soil and Water Assessment Tool (SWAT) and Water Evaluation And Planning (WEAP) models, to simulate streamflows under climate change and assess scenarios of future water availability to different socio-economic activities by year 2060. Six common Global Circulation Models (GCMs) from WCRP-CMIP3 with emissions Scenario A2 were selected. These are HadCM3, HadGEM1, ECHAM5, MIROC3.2MED, GFDLCM2.1 and CSIROMK3. They were downscaled by using LARS-WG to station scale. The SWAT model was calibrated with observed data and utilized the LARS-WG outputs to generate future streamflows before being used as input to WEAP model to assess future water availability to different socio-economic activities. GCMs results show future rainfall increase in upper Pangani River Basin between 16-18 % in 2050s relative to 1980-1999 periods. Temperature is projected to increase by an average of 2 • C in 2050s, relative to baseline period. Long-term mean streamflows is expected to increase by approximately 10 %. However, future peak flows are estimated to be lower than the prevailing average peak flows. Nevertheless, the overall annual water demand in Pangani basin will increase from 1879.73 Mm 3 at present (2011) to 3249.69 Mm 3 in the future (2060s), resulting to unmet demand of 1673.8 Mm 3 (51.5 %). The impact of future shortage will be more severe in irrigation where 71.12 % of its future demand will be unmet. Future water demands of Hydropower and Livestock will be unmet by 27.47 and 1.41 % respectively. However, future domestic water use will have no shortage. This calls for planning of current and future surface water use in the upper Pangani River Basin.
Evapotranspiration (ET) plays a crucial role in integrated water resources planning, development and management, especially in tropical and arid regions. Determining ET is not straightforward due to the heterogeneity and complexity found in real-world hydrological basins. This situation is often compounded in regions with limited hydro-meteorological data that are facing rapid development of irrigated agriculture. Remote sensing (RS) techniques have proven useful in this regard. In this study, we compared the daily actual ET estimates derived from 3 remotely-sensed surface energy balance (SEB) models, namely, the Surface Energy Balance Algorithm for Land (SEBAL) model, the Operational Simplified Surface Energy Balance (SSEBop) model, and the Simplified Surface Balance Index (S-SEBI) model. These products were generated using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery for a total of 44 satellite overpasses in 2005, 2010, and 2015 in the heterogeneous, highly-utilized, rapidly-developing and data-limited Kilombero Valley (KV) river basin in Tanzania, eastern Africa. Our results revealed that the SEBAL model had a relatively high ET compared to other models and the SSEBop model had relatively low ET compared to the other models. In addition, we found that the S-SEBI model had a statistically similar ET as the ensemble mean of all models. Further comparison of SEB models’ ET estimates across different land cover classes and different spatial scales revealed that almost all models’ ET estimates were statistically comparable (based on the Wilcoxon’s test and the Levene’s test at a 95% confidence level), which implies fidelity between and reliability of the ET estimates. Moreover, all SEB models managed to capture the two spatially-distinct ET regimes in KV: the stable/permanent ET regime on the mountainous parts of the KV and the seasonally varied ET over the floodplain which contains a Ramsar site (Kilombero Valley Floodplain). Our results have the potential to be used in hydrological modelling to explore and develop integrated water resources management in the valley. We believe that our approach can be applied elsewhere in the world especially where observed meteorological variables are limited.
Evaluation of river basins requires land-use and land-cover (LULC) change detection to determine hydrological and ecological conditions for sustainable use of their resources. This study assessed LULC changes over 28 years (1990–2018) in the Wami–Ruvu Basin, located in Tanzania, Africa. Six pairs of images acquired using Landsat 5 TM and 8 OLI sensors in 1990 and 2018, respectively, were mosaicked into a single composite image of the basin. A supervised classification using the Neural Network classifier and training data was used to create LULC maps for 1990 and 2018, and targeted the following eight classes of agriculture, forest, grassland, bushland, built-up, bare soil, water, and wetland. The results show that over the past three decades, water and wetland areas have decreased by 0.3%, forest areas by 15.4%, and grassland by 6.7%, while agricultural, bushland, bare soil, and the built-up areas have increased by 11.6%, 8.2%, 1.6%, and 0.8%, respectively. LULC transformations were assessed with water discharge, precipitation, and temperature, and the population from 1990 to 2018. The results revealed decreases in precipitation, water discharge by 4130 m3, temperature rise by 1 °C, and an increase in population from 5.4 to 10 million. For proper management of water-resources, we propose three strategies for water-use efficiency-techniques, a review legal frameworks, and time-based LULC monitoring. This study provides a reference for water resources sustainability for other countries with basins threatened by LULC changes.
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