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

Intensification of agricultural land use and population growth from 1990-2017 has caused changes in land cover and land use of the Mbarali River sub-catchment which is located in the Upper Great Ruaha Sub basin, Tanzania. This has affected the magnitude of the surface runoff, total water yield and the groundwater flow. This study assesses the impacts of the land cover and land use changes on the stream flows and hydrological water balance components (surface runoff, water yield, percolation and actual evapotranspiration). The land use and land cover (LULC) maps for three window period snapshots, 1990, 2006 and 2017 were created from Landsat TM and OLI_TIRS with the help of QGIS version 2.6. Supervised classification was used to generate LULC maps using the Maximum Likelihood Algorithm and Kappa statistics for assessment of accuracy. SWAT was set up and run to simulate stream flows and hydrological water balance components. The assessment of the impacts of land use and land cover changes on stream flows and hydrological water balance component was performed by comparing hydrological parameters simulated by SWAT using land use scenarios of 2006 and 2017 against the baseline land use scenario of 1990. Accuracy of LULC classification was good with Kappa statistics ranging between 0.9 and 0.99. There was a drastic increase in areal coverage of cultivated land, for periods 1990-2006 (5.84%) and 2006-2017 (12.05%) compared to other LULC. During 2006 and 2017 surface runoff increased by 4% and 9% respectively;however, water yield increased by only 0.5% compared to 1990 baseline period. This was attributed to increased proportion of cultivated land in the sub-catchment which has a high curve number (59.60) that indicates a higher runoff response and low infiltration rate.

Land Cover Change and Its Socio-Economic Impact on the Residents of the Mara River, Kenya

Anthropogenic activities are increasingly catalyzing natural climatic factors that drive land cover change at different spatial scales. Available land cover data of the Mara River basin however give a broader picture of the entire basin regardless of the heterogeneity that exists at the sub-catchment level. This study sought to establish sub-catchment specific information on land cover changes through examination of satellite images of four Mara River sub-catchments (Amala, Nyangores, Talek and Sand River) for the period 1987-2017. The relationship between temperature, rainfall and land cover was also computed. In addition, a household survey and focus group discussions were conducted in each sub-catchments to establish the socio-economic impacts of land cover change on the community’s wellbeing. Forest cover was dominant in Amala (39.8%) and Nyangores (43.7%) sub-catchments in 1987 but by 2017 crop lands had surpassed forest cover in the two sub-catchments, accounting for 53.2% and 45.7%, respectively. However, in Talek (52.8%) and Sand River (47.4%) sub-catchments, grassland was the dominant land cover type in 1987 and after the 30 year period, grasslands remained dominant in Sand River, while shrub land became dominant in Talek sub-catchment. A weak positive correlation was observed between rainfall and forest cover, shrub land and cropland, while a negative correlation was observed between rainfall and bare land. Average temperature showed a positive moderate correlation with bare land and built up areas. Analysis of survey data revealed that livestock keeping, temperature increase, type of trees, education level of household head and weak environmental laws were the main drivers of land cover change (P −0.587), beans (r = −0.5459), sorghum (r = −0.351), cow peas (r = −0.544), and pigeon peas (r = −0.337). Focus group discussions participants were supportive of environmental protective measures to reverse negative land cover changes, while planting drought resistant trees, crop diversification and awareness creation among community members were recommended as the most ideal environmental management strategies.

Subtle Impacts of Temperature and Rainfall Patterns on Land Cover Change Overtime and Future Projections in the Mara River Basin, Kenya

The interactive and cumulative effect of temperature and rainfall on land cover change is a priority at global, regional and local scale. This study examined changes in six land cover categories (forestland, grasslands, shrub land, bare land, built-up areas and agricultural lands) in four sub-catchments (Amala, Nyangores, Talek and Sand River), of the Mara River basin over a 30-year period (1987-2017) and made predictions of future land cover change patterns. Landsat Imageries of 90 m resolution were retrieved and analyzed using ArcGIS 10.0 software. Relationship between NDVI, temperature and precipitation was determined using Pearson’s correlation coefficient, while Markov chains analyses were performed on different land cover categories to project future trends. Results showed low to moderate (R2 = 0.002 to 0.6) trends of change in NDVI of different land cover categories across all sub-catchments. The greatest change (R2 0.34 to 0.5) was recorded in bare land in three of the four sub-catchments studied. Precipitation showed a strong positive correlation with built-up areas, forestlands, croplands, bare land, grasslands and shrub lands, while temperature correlated strongly but negatively with the same land cover categories. The change detection matrix projected significant but varying changes in land cover categories across the four sub-catchments by 2027. This study underscores the impact of changing climatic factors on various land cover categories in the Mara River basin sub-catchments, with different land cover categories exhibiting strong positive sensitivity to high precipitation and low temperature and vice-versa.

Analyzing the Mara River Basin Behaviour through Rainfall-Runoff Modeling

Hydrological models are considered as necessary tools for water and environmental resource management. However, modelling poorly gauged watersheds has been a challenge to hydrologists and hydraulic engineers. Research done recently has shown the potential to overcome this challenge through incorporating satellite based hydrological and meteorological data in the measured data. This paper presents results for a study that used the semi-distributed conceptual HBV Light Model to model the rainfall-runoff in the Mara River Basin, Kenya. The model simulates runoff as a function of rainfall. It is built on the basis established between satellite observed and in-situ rainfall, evaporation, temperature and the measured runoff. The model’s performance and reliability were evaluated over two sub-catchments namely: Nyangores and Amala in the Mara River Basin using the Nash-Sutcliffe Efficiency which the model referred to as Reff and the coefficient of determination (R2). The Reff for Nyangores and Amala during the calibration and (validation) period were 0.65 (0.68) and 0.59 (0.62) respectively. The model showed good flow simulations particularly during the recession flows, in the Nyangores sub-catchment whereas it simulated poorly the short term fluctuations of the high-flow for Amala sub-catchment. Results from this study can be used by water resources managers to make informed decision on planning and management of water resources.

Effects of Land Use Change on Land Degradation Reflected by Soil Properties along Mara River, Kenya and Tanzania

Human-induced changes to natural landscapes have been identified as some of the greatest threats to freshwater resources. The change from natural forest cover to agricultural and pastoral activities is rampant especially in the upper Mara River catchment (water tower), as well as along the course of the Mara River. The objective of this study was to determine the effect of land use change on the physico-chemical properties of soil (bulk density, carbon, nitrogen, phosphorus and pH) along the course of the Mara River. Five major land uses (agricultural lands, livestock/pastoral lands, forested lands, conservancy/game reserves, and natural wetland) were explored. Results revealed that the mean soil bulk density was 0.956 g/cm3 and differed significantly between sites (p < 0.001). Live biomass values differed significantly between sampling sites (land use types) within the Mara River Basin (F(4, 147) = 8.57, p < 0.001). The mean infiltration over a period of 150 minutes differed, not only among sampling sites, but also between different sides of the river (left and right) within the same sampling site. Soil pH was generally acidic across the five sites and varied significantly (F(4, 63) = 19.26, p tween sites along the Mara River Basin. The mean percentage soil nitrogen across all sampling blocks was 4.87%, with significant differences observed in percentage soil nitrogen (F (4, 63) = 3.26, p < 0.006) between sampling sites. The results indicated that the five land use types affected land degradation differently along the Mara River, while adjacent land degradation affected water physico-chemical properties. These results point to the need to have focused policies on integrated land and water resource management strategies in the Mara River Basin.

Relationship between Land Cover Changes with Water Quantity in Lake Victoria—A Case Study of Mara River Basin in Tanzania

LV(Lake Victoria)is valuable to the East African sub region and Africa in general,sources of water for LV are from its catchment areas and tributaries e.g.Kagera and Mara Rivers on Tanzania part.Apparently,catchment areas in proximities of LV and on MR(Mara River),indeed on MRB(Mara River Basin)in particular,are experiencing increased anthropogenic activities such as mining,fishing,settlements,agriculture etc.,which lead to increased water usage,land degradation and environmental pollution.Such activities threaten the sustainability of the environment surrounding MRB and impliedly LV and its ecosystem.The level of water in LV is reported to be declining threatening its extinction.This paper is reporting on a study undertaken to establish the relationship between land cover changes with ground water discharge from specifically MRB into LV over the period of 24 years,i.e.1986 to 2010.Methodology used is assessment of vegetation changes by using remote sensing through analysis of TM(Thematic Mapper)Landsat Images of 1986,1994,2002 and 2010 ETM(Enhanced Thematic Mapper)Landsat images,from which respective land cover change maps were generated and compared with ground water levels from MRB.Results indicates that there is a significant decline of land cover and ground water flowing into LV from MRB,and that there is positive correlation between land cover changes and the quantity of ground water flowing from MRB to LV.This phenomenon is common to all tributaries of LV,thus leading to decline of water in LV.It is recommended that relevant government institutions should endeavor formulating policies to control excessive use of wetlands and drylands in the proximity of LV and MRB in particular,such that the flow of water to LV may be sustained.

Modeling Surface Water Availability for Irrigation Development in Mbarali River Sub-Catchment Mbeya, Tanzania

Although Tanzania has a large land suitable for irrigation development, only 4.2% of the arable land which is potential for irrigation has been developed. Mbarali District is characterized by commercial and small-scale irrigation activities for paddy production. Currently, surface water availability for irrigation in Mbarali District is dwindling due to high water demands. Inadequate studies that estimate water availability for irrigation is one of the underlying factors to the lack of irrigation development in many parts of Tanzania including in Mbarali District. This study, therefore, aimed to model surface water availability for irrigation development in Mbarali River sub-catchment Mbeya, Tanzania. The Soil and Water Analysis Tool (SWAT) model and field observations were used to accomplish the study. The model estimates that Mbarali River sub-catchment receives about 631 mm of total mean precipitation annually. About 53% of received precipitation is lost through evapotranspiration, 12% recharged to deep aquifer and the remaining 35% discharged to the stream flow through surface runoff, lateral flow and return flow from unconfined aquifer. Discharge to the steam flow contributes to the total annual means of river discharge ranging from 0 - 10 cubic meters per second at upper catchment to 120 - 140 cubic meters per second at lower catchment. The study recommends that the lower reach of the Mbarali River sub-catchment is potential for irrigation than the upper reach as it has potential river flow that can support irrigation activities. The study also notes the urgent need for water reallocation plan to meet competing water needs in the lower reach of Mbarali River sub-catchment. Moreover, the study addresses the potentiality of irrigation in upper catchment under sustainable water management practices including excavation of small ponds to capture and store surface runoff for dry season use or to supplement irrigation as the rainfall declines.

Institutional Structures and Sustainability of Projects in Nyangores River Sub-Catchment Basin in Bomet County, Kenya

Integrated basin management approach has been applied in Nyangores River sub-catchment basin, since the year 2009 but with minimal success. Sub catchment degradation, organizational weakness, the flow and quality of water had started to diminish, creating challenges for local livelihoods, wildlife in the Maasai Mara Game Reserve, and in maintaining biodiversity and healthy ecosystem functioning. Water resources can be successfully managed only if the natural, social, economic and political environments, in which water occurs and used, are taken fully into consideration. The aim of this study is to determine the influence of institutional structures influence on sustainability of projects in Nyagores river sub-catchment basin in Bomet County, Kenya. The research designs used were descriptive survey and correlational research design. Stepwise and purposive sampling formed the sampling procedure. The results are presented descriptively using Tables while for qualitative data, narrative statements were used. Questionnaires, Interview guide and document analysis were used for data collection. The sample size was 371, from a targeted a population of 56,508 household heads and 10 informants, purposively selected from the water concerned institutions and ministries of Water and Agriculture. Total of 371 questionnaires were given out to the respondents and only 321, were duly filled and returned representing (86.5%). The objective was to establish the extent to which institutional structures influence sustainability of projects in Nyangores River sub-catchment Basin. The results indicated that there was a positive correlation r = 0.552, (p is was rejected and concluded that there is a significant relationship between the institutional structures and sustainability of projects in Nyangores river sub-catchment basin. R2 was 0.304;hence, 30.4% of changes in sustainability of projects are explained by institutional structures. Recommendations are;ensure a stringent policy for robust planning and management, and more robust forum for the stakeholders to complement the efforts of WRUA. It is suggested for further research, similar studies are done for the other adjacent river basins and to investigate ways of raising the level of community participation in the basin.

马拉河流域植被生态需水特征及估算

生态需水是生态用水控制和区域生态环境恢复建设的基本依据。马拉河流域拥有世界著名的生态系统,植被生态需水占流域总需水量的很大一部分。基于1980—2020年ERA5气象数据、叶面积指数(LAI)与世界土壤数据库数据,采用Penman-Monteith法计算了马拉河流域四个季节(短旱季、长雨季、长旱季、短雨季)植被生态需水量的时空变化特征。在此基础上,使用支持向量机(SVM)、随机森林(RF)和卷积神经网络(CNN)3种机器学习方法与7个环境因子(气温、降水、10 m风速、LAI、太阳辐射、相对湿度、地形)建立了回归模型,分别估算了2011—2020年逐年不同季节的植被生态需水量,并与Penman-Monteith法计算结果进行时间序列拟合度和空间相似性的比较。结果表明:马拉河流域植被生态需水量在过去40年所有季节都呈现为波动变化,植被生态需水量长雨季>长旱季>短雨季>短旱季,长雨季的植被生态需水量约为短旱季的1.5倍。不同季节均呈现出上下游高、中游低的植被生态需水量空间分布格局。LAI为最大的正影响因子,风速为最大的负影响因子。就不同方法估算的植被生态需水量准确性而言,RF表现最为优异,主要体现在最值估算误差最小,时间变化序列的拟合度最高,空间分布最为相似,相对误差最小,而SVM的预测结果相对最差。RF是相对最适用于马拉河流域植被生态需水量估算的算法。使用3种不同的机器学习方法估算马拉河流域不同季节植被生态需水量,并对结果进行比较,可为生态需水的估算提供技术参考。

Spatial distribution and habitat characterization of mosquito species during the dry season along the Mara River and its tributaries,in Kenya and Tanzania

Background:Vector-borne diseases are increasingly becoming a major health problem among communities living along the major rivers of Africa.Although larger water bodies such as lakes and dams have been extensively researched,rivers and their tributaries have largely been ignored.This study sought to establish the spatial distribution of mosquito species during the dry season and further characterize their habitats along the Mara River and its tributaries.Methods:In this cross-sectional survey,mosquito larvae were sampled along the Mara River,its two perennial tributaries(Amala and Nyangores),drying streams,and adjacent aquatic habitats(e.g.swamps,puddles that receive direct sunlight[open sunlit puddles],rock pools,hippo and livestock hoof prints,and vegetated pools).Each habitat was dipped 20 times using a standard dipper.Distance between breeding sites and human habitation was determined using global positioning system coordinates.The collected mosquito larvae were identified using standard taxonomic keys.Water physico-chemical parameters were measured in situ using a multiparameter meter.Mean mosquito larvae per habitat type were compared using analysis of variance and chi-square tests,while the relationship between mosquito larvae and physicochemical parameters was evaluated using a generalized linear mixed model.The Cox-Stuart test was used to detect trends of mosquito larvae distribution.The test allowed for verification of monotonic tendency(rejection of null hypothesis of trend absence)and its variability.Results:A total of 4001 mosquito larvae were collected,of which 2712(67.8%)were collected from river/stream edge habitats and 1289(32.2%)were sampled from aquatic habitats located in the terrestrial ecosystem about 50 m away from the main river/streams.Anopheles gambiae s.s,An.arabiensis,and An.funestus group,the three most potent vectors of malaria in Sub-Saharan Africa,together with other anopheline mosquitoes,were the most dominant mosquito species(70.3%),followed by Culex quinquefasciatus and Cx.pipiens complex combined(29.5%).Drying streams accounted for the highest number of larvae captured compared to the other habitat types.A stronger relationship between mosquito larvae abundance and dissolved oxygen(Z=7.37,P≤0.001),temperature(Z=7.65,P≤0.001),turbidity(Z=−5.25,P≤0.001),and distance to the nearest human habitation(Z=4.57,P≤0.001),was observed.Conclusions:Presence of malaria and non-malaria mosquito larvae within the Mara River basin calls for immediate action to curtail the insurgence of vector-borne diseases within the basin.A vector control program should be conducted during the dry period,targeting drying streams shown to produce the highest number of larval mosquitoes.

Time lag effect of vegetation response to seasonal precipitation in the Mara River Basin

Background Mara River Basin is an ecologically fragile area in East Africa,with a pattern of alternating wet and dry seasons shaped by periodic precipitation.Considering the regional biological traits and climatic change,the vegetation’s response to seasonal variation is complicated and frequently characterized by time lags.This study analyzed the variation of the Normalized Difference Vegetation Index(NDVI)and investigated its time lag to precipitation at the monthly scale.NDVI characteristic peaks were proposed from the perspective of seasonal mechanisms and were quantified to assess the lag effect.Results The results showed that the Anomaly Vegetation Index could identify low precipitation in 2006,2009,and 2017.The NDVI showed an increasing trend in 75%of areas of the basin,while showed a decreased significance in 3.5%of areas,mainly in savannas.As to the time lag,the 1-month lag effect dominated most months,and the spatiotemporal disparities were noticeable.Another method considering the alternations of wet and dry seasons found that the time lag was approximately 30 days.Based on the time distribution of NDVI characteristic peaks,the average time lag was 35.5 days and increased with the range of seasons.Conclusions The findings confirmed an increasing trend of NDVI in most regions from 2001 to 2020,while the trends were most obvious in the downstream related to human activities.The results could reflect the time lag of NDVI response to precipitation,and the 1-month lag effect dominated in most months with spatial heterogeneity.Four NDVI characteristic peaks were found to be efficient indicators to assess the seasonal characteristics and had a great potential to quantify vegetation variation.