Geology Reports⌕ Search

Geology topics

Research about Kenya

Source-linked reports with geographic coverage including Kenya.

At least 19 recordsLinked to original sources
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2023

Sustainable aquifer management for food security

In aquifer-dependent regions, balancing aquifer protection, desalination, economic development, agricultural irrigation, and food security can be better managed through discovery and development of sources of sustainable groundwater pumping. Aquifer desalination for irrigation to protect food security can mitigate pressure on local freshwater aquifers. Despite its importance, little peer reviewed work to date has identified the economic capacity to pay for aquifer desalination for irrigation to mitigate freshwater aquifer drawdown. The novel contribution of this work is the development and application of an innovative method to assess the economic capacity to pay for aquifer desalination for irrigation for a recently discovered large saline aquifer. It develops an original framework to assess the capacity to pay for aquifer desalination, the results of which can help guide policymakers on efficient and sustainable pumping approaches across users, aquifers, and time periods. A mathematical programming model is developed to economically analyze the 200 billion cubic meter Lotikipi Aquifer, discovered in 2013 in northern Kenya using modern remote sensing methods. While initial pumping of the Lotikipi Aquifer was halted due to high groundwater salinity levels, interest remains strong in assessing the economic capacity to pay for groundwater desalination because of its potential role in protecting regional food security generated by aquifer pumping for irrigation. The model is formulated by calibrating optimized pumping patterns in two existing freshwater aquifers to replicate observed historical pumping levels. Based on that exercise, a second model is developed to identify a least cost set of pumping restrictions that return each of three regional aquifers to starting conditions over a seven-year time period. A third model extends the second by adding a constraint of a minimum required level of food grain security supported by irrigation pumping from the aquifer system. Results show that the economic capacity to pay for aquifer desalination for irrigated agriculture lies in the range of $0.08 - $0.18 USD per cubic meter under current economic conditions and desalination technologies available. While this economic capacity to pay is lower than its current cost in most places, the future could be more optimistic. Advances in desalination technology, higher crop prices, technical advance in agriculture, and development of drought-resistant crops can all contribute to a future capacity to economically justify the expense of desalination.

Agricultural Systems Journal↗
USGS2021

Grassland live fractional cover map creation and Geographic Information System (GIS) analysis for rangeland management supporting Kenya Northern Rangelands Trust Conservancies

The handbooks and synchronized MP4 recordings provide hands-on instruction for creating and analyzing vegetation live fractional cover (LFC) maps. The methods and protocols used in the instruction materials follow those developed and recorded in Rangoonwala and Ramsey (2019). The LFC mapping and geographic information system (GIS) analyses highlight the consortium of rangeland conservancies covering the semiarid central region of Kenya (approximately 44,000 square kilometers). The instruction materials are separated into two parts: processing and map-product creation based on remote-sensing images and GIS analyses of the created maps for rangeland management. The image processing is conducted using the advanced and professional software package SeNtinels Application Platform (SNAP) that is supported and maintained by the European Space Agency. SNAP is a free image analyses software package available for download. It is largely icon driven but offers simple to advanced program inserts and batch processing. The GIS analyses are conducted using the software package Quantum Geographic Information System (QGIS), another free and downloadable software. QGIS is compatible with numerous software, including the Esri suite of ArcGIS software and database structure. The image data includes both high-spatial-resolution Sentinel-2 optical data and Sentinel-1 synthetic aperture radar (SAR). Both datasets are freely available via a public portal that is maintained by the European Space Agency. The image-processing instruction handbook covers all aspects of acquiring and processing satellite-image data and importing vector-data sources into SNAP. The GIS analysis handbook covers final creation of map products from the maps created in SNAP and creation of GIS procedures in QGIS that are needed to manage the rangeland resources for wildlife and pastoral grazing. Although focused on the Kenyan conservancies and their semiarid environment, the processing methods and procedures are applicable for similar environments and management, and to a large part, even for integrated mapping and GIS functionality of any managed landscape resource. The instruction handbooks are synchronized to MP4 training videos created with U.S. Geological Survey-licensed Camtasia 9 software. The workbook and MP4 video combinations are suitable for a single user or a workshop setting.

Open-File Report↗
USGS2019

Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya

As part of the U.S. Department of the Interior’s (DOI) commitment to provide technical assistance to the Kenyan Northern Rangelands Trust (NRT), the U.S. Geological Survey, in collaboration with the DOI International Technical Assistance Program and the U.S. Agency for International Development’s regional mission in East Africa, created a high spatial and time-sensitive live vegetation monitoring system for NRT. The system built with advanced field and sensor technologies produced directly calibrated and highly accurate satellite mapping that is extendable both forward and backward in time. The maps are produced in a simple 0–100-percent representation of live vegetation status and change over time. The backbone of the mapping is the Sentinel satellite remote sensing systems with 5-day collection frequencies and ground spatial resolutions of 10 meters. The European Space Agency (ESA) offers free Sentinel satellite image data through conveniently accessed websites and free user-friendly image processing software downloadable directly onto a personal workstation. ESA provides free online software support. The mapping capability was extended from the forward mapping of Sentinel back in time with the Landsat satellite remote sensing system that has an available and free data archive back to 1983. Although Landsat has coarser spatial resolution, the Landsat to Sentinel live vegetation mapping comparison supports the use of Landsat to provide NRT the historical recreation of prominent live vegetation changes.

Open-File Report↗
USGS2019

Financing agricultural drought risk through ex-ante cash transfers

Despite advances in drought early warning systems, forecast information is rarely used for triggering and financing early actions, such as cash transfer. Scaling up cash transfer pay-outs , and overcoming the barriers to actions based on forecasts, requires an understanding of costs resulting from False Alarms, and the potential benefits associated with appropriate early interventions. On this study, we evaluate the potential cost-effectiveness of cash transfer responses, comparing the relative costs of ex-ante cash transfers during the maize growing season to ex-post cash transfers after harvesting in Kenya. For that, we developed a forecast model using Fast-and Frugal Trees that unravels early warning relationships between climate variability, vegetation coverage, and maize yields at multiple lead times. Results indicate that our models correctly forecast low maize yield events 85% of the time across the districts studied, some already six months before harvesting. The models’ performance improves towards the end of the growing season driven by a decrease of 39% in the probability of False Alarms. Overall, we show that timely cash transfers ex-ante to a disaster can often be more cost-effective than investing in ex-post expenditures. Our findings suggest that early response can yield significant cost savings, and can potentially increase the effectiveness of existing cash transfer systems.

Science of the Total Environment↗
USGS2018

How will East African maize yields respond to climate change and can agricultural development mitigate this response?

We analyze the response of Kenyan maize yields to near-term climate change and explore potential mitigation options. We model county level yields as a function of rainfall and temperature during a period of increased regional warming and drying (1989–2008). We then do a counter factual analysis by comparing existing maize yields from 2000 to 2008 to what yields might have been if observed warming and drying trends had not occurred. We also examine maize yields based on projected 2026–2040 climate trends. Without the observed warming and drying trends, Eastern Kenya would have had an 8% increase in maize yields, which in turn would have led to a net production increase of 500,000 metric tons. In Western Kenya, the magnitude of change is higher but the relative changes in predicted values are smaller. If warming and drying trends continue, we expect future maize yields to decline by 11% in Eastern Kenya (vs. 7% in Western Kenya). We also examine whether these future losses might be offset through agricultural development. For that analysis, we use a household panel dataset (2000, 2005) with measurements of individual farm plot yields, inputs, and outputs. We find that under a scenario of aggressive adoption of hybrid seeds and fertilizer usage coupled with warming and drying trends, yields in Western Kenya might increase by 6% while those in Eastern Kenya could increase by 14%. This increase in yields might be larger if there is a corresponding increase in usage of drought-tolerant hybrids. However, wide prediction intervals across models highlight the uncertainty in these outcomes and scenarios.

Climatic Change↗
USGS2012

Group takes a fresh look at the lithosphere underneath southern Kenya

Since the turn of the century the well-developed Kenya rift has been a crucial location for studying the interrelationships between extension, uplift, and magmatism. In 1989–1990, an experiment conducted by the Kenya Rift International Seismic Project (KRISP) focused on the central and northern portions of Kenya (Figure 1) and provided a rich base of information regarding the structure and evolution of the rift, which answered many key questions and raised others. Does the crust thin to the south of the Kenya dome as it does to the north?, and if it does, which crustal layer would be mainly affected? How is the Chyulu Hills Quaternary volcanism related to the rifting process? What is the relationship between the crust and lithospheric mantle during extension?

East African Rift, Great Rift Valley, Gregory Rift↗
USGS2012

Strategies for soil quality assessment using VNIR gyperspectral spectroscopy in a western Kenya Chronosequence

Visible and near-infrared reflectance spectroscopy (VNIRS) is a rapid and nondestructive method that can predict multiple soil properties simultaneously, but its application in multidimensional soil quality (SQ) assessment in the tropics still needs to be further assessed. In this study, VNIRS (350–2500 nm) was employed to analyze 227 air-dried soil samples of Ultisols from a soil chronosequence in western Kenya and assess 16 SQ indicators. Partial least squares regression (PLSR) was validated using the full-site cross-validation method by grouping samples from each farm or forest site. Most suitable models successfully predicted SQ indicators (R 2 ≥ 0.80; ratio of performance to deviation [RPD] ≥ 2.00) including soil organic matter (OM LOI ), active C, Ca, cation exchange capacity (CEC), and clay. Moderately-well predicted indicators (0.50 ≤ R 2 < 0.80; 1.40 ≤ RPD < 2.00) were water stable aggregation (WSA), Cu, silt, Mg, pH, sand, water content at permanent wilting point (Θ pwp ), and field capacity (Θ fc ). Poorly predicted indicators (R 2 < 0.50; RPD < 1.40) were EC, S, P, available water capacity (AWC), K, Zn, and penetration resistance. Combining VNIRS with selected field- and laboratory-measured SQ indicator values increased predictability. Furthermore, VNIRS showed moderate to substantial agreement in predicting interpretive SQ scores and a composite soil quality index (CSQI) especially when combined with directly measured SQ indicator values. In conclusion, VNIRS has good potential for low cost, rapid assessment of physical and biological SQ indicators but conventional soil chemical tests may need to be retained to provide comprehensive SQ assessments.

Western Kenya↗
USGS2012

A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.

Lake Turkana↗
USGS2010

Roosting, social organization and the annual cycle in a Kenya population of the bat Pipistrellus nanus

The tiny (3.1–3.8 g) vespcrtilionid bat Pipistrellus nanus was studied in Kenya palm-thatched roofs from May 1973 to July 1974. Roosting social organization and related activities and behavior are described. ♂♂ held diurnal roosting territories where ♀♀ gathered in small and compositionally labile groups, attracted to the most vocal ♂♂. Annual variation in population-wide aspects of social organization follows predictable seasonal changes in climate and predator abundance. Variability between individuals follows a common mammalian pattern: high male competition for ♀, variance in presumed male reproductive success, and a mating system resembling one based on resource defense polygyny. Social organization in this population contrasts with that known from studies of other P. nanus populations.

Ethology↗
USGS2008

Savanna tree density, herbivores, and the herbaceous community: Bottom-up vs. top-down effects

Herbivores choose their habitats both to maximize forage intake and to minimize their risk of predation. For African savanna herbivores, the available habitats range in woody cover from open areas with few trees to dense, almost‐closed woodlands. This variation in woody cover or density can have a number of consequences for herbaceous species composition, cover, and productivity, as well as for ease of predator detection and avoidance. Here, we consider two alternative possibilities: first, that tree density affects the herbaceous vegetation, with concomitant “bottom‐up” effects on herbivore habitat preferences; or, second, that tree density affects predator visibility, mediating “top‐down” effects of predators on herbivore habitat preferences. We sampled sites spanning a 10‐fold range of tree densities in an Acacia drepanolobium‐dominated savanna in Laikipia, Kenya, for variation in (1) herbaceous cover, composition, and species richness; (2) wild and domestic herbivore use; and (3) degree of visibility obstruction by the tree layer. We then used structural equation modeling to consider the potential influences that tree density may have on herbivores and herbaceous community properties. Tree density was associated with substantial variation in herbaceous species composition and richness. Cattle exhibited a fairly uniform use of the landscape, whereas wild herbivores, with the exception of elephants, exhibited a strong preference for areas of low tree density. Model results suggest that this was not a response to variation in herbaceous‐community characteristics, but rather a response to the greater visibility associated with more open places. Elephants, in contrast, preferred areas with higher densities of trees, apparently because of greater forage availability. These results suggest that, for all but the largest species, top‐down behavioral effects of predator avoidance on herbivores are mediated by tree density. This, in turn, appears to have cascading effects on the herbaceous vegetation. These results shed light on one of the major features of the “landscape of fear” in which African savanna herbivores exist.

Laikipia County↗
USGS2006

Kenya Rift International Seismic Project, 1989–1990 experiment

Ever since Gregory's work at the turn of the century, the extensional structures extending through central Kenya have been recognized as the classic example of a continental rift zone. Because of the scale and variety of rift features present, this locality has fascinated geologists and geophysicists since its discovery.

Eos, Earth and Space Science News↗
USGS1994

Optimization of wide-angle seismic signal-to-noise ratios and P-wave transmission in Kenya

In previous refraction and wide-angle reflection experiments in the Kenya Rift there were problems with poor signal-noise ratios which made good seismic interpretation difficult. Careful planning and preparation for KRISP 90 has substantially overcome these problems and produced excellent seismic sections in a difficult environment. Noise levels were minimized by working, as far as possible, at times of the day when conditions were quiet, while source signals were optimized by using dispersed charges in water where it was available and waterfilled boreholes in most cases where it was not. Seismic coupling at optimum depth in water has been found to be more than 100 times greater than it is in a borehole in dry loosely compacted material. Allowing for the source coupling, a very marked difference has been found between the observation ranges in the rift and those on the flanks, where the observation ranges are greater. These appear to indicate a significant difference in seismic transmission through the two types of crust.

Tectonophysics↗
USGS1994

Crustal structure beneath the Kenya Rift from axial profile data

Modelling of the KRISP 90 axial line data shows that major crustal thinning occurs along the axis of the Kenya Rift from Moho depths of 35 km in the south beneath the Kenya Dome in the vicinity of Lake Naivasha to 20 km in the north beneath Lake Turkana. Low P n velocities of 7.5–7.7 km/s are found beneath the whole of the axial line. The results indicate that crustal extension increases to the north and that the low P n velocities are probably caused by magma (partial melt) rising from below and being trapped in the uppermost kilometres of the mantle. Along the axial line, the rift infill consisting of volcanics and a minor amount of sediments varies in thickness from zero where Precambrian crystalline basement highs occur to 5–6 km beneath the lakes Turkana and Naivasha. Analysis of the P g phase shows that the upper crystalline crust has velocities of 6.1–6.3 km/s. Bearing in mind the Cainozoic volcanism associated with the rift, these velocities most probably represent Precambrian basement intruded by small amounts of igneous material. The boundary between the upper and lower crusts occurs at about 10 km depth beneath the northern part of the rift and 15 km depth beneath the southern part of the rift. The upper part of the lower crust has velocities of 6.4–6.5 km/s. The basal crustal layer which varies in thickness from a maximum of 2 km in the north to around 9 km in the south has a velocity of about 6.8 km/s.

Tectonophysics↗
USGS1994

Seismic structure of the uppermost mantle beneath the Kenya rift

A major goal of the Kenya Rift International Seismic Project (KRISP) 1990 experiment was the determination of deep lithospheric structure. In the refraction/wide-angle reflection part of the KRISP effort, the experiment was designed to obtain arrivals to distances in excess of 400 km. Phases from interfaces within the mantle were recorded from many shotpoints, and by design, the best data were obtained along the axial profile. Reflected arrivals from two thin (< 10 km), high-velocity layers were observed along this profile and a refracted arrival was observed from the upper high-velocity layer. These mantle phases were observed on record sections from four axial profile shotpoints so overlapping and reversed coverage was obtained. Both high-velocity layers are deepest beneath Lake Turkana and become more shallow southward as the apex of the Kenya dome is approached. The first layer has a velocity of 8.05-8.15 km/s, is at a depth of about 45 km beneath Lake Turkana, and is observed at depths of about 40 km to the south before it disappears near the base of the crust. The deeper layer has velocities ranging from 7.7 to 7.8 km/s in the south to about 8.3 km/s in the north, has a similar dip as the upper one, and is found at depths of 60-65 km. Mantle arrivals outside the rift valley appear to correlate with this layer. The large amounts of extrusive volcanics associated with the rift suggest compositional anomalies as an explanation for the observed velocity structure. However, the effects of the large heat anomaly associated with the rift indicate that composition alone cannot explain the high-velocity layers observed. These layers require some anisotropy probably due to the preferred orientation of olivine crystals. The seismic model is consistent with hot mantle material rising beneath the Kenya dome in the southern Kenya rift and north-dipping shearing along the rift axis near the base of the lithosphere beneath the northern Kenya rift. This implies lithosphere thickening towards the north and is consistent with a thermal thinning of the lithosphere from below in the south changing to thinning of the lithosphere due to stretching in the north.

Tectonophysics↗
USGS1994

Composition of the crust beneath the Kenya rift

We infer the composition of the crust beneath and on the flanks of the Kenya rift based on a comparison of the KRISP-90 crustal velocity structure with laboratory measurements of compressional-wave velocities of rock samples from Kenya. The rock samples studied, which are representative of the major lithologies exposed in Kenya, include volcanic tuffs and flows (primarily basalts and phonolites), and felsic to intermediate composition gneisses. This comparison indicates that the upper crust (5-12 km depth) consists primarily of quartzo-feldspathic gneisses and schists similar to rocks exposed on the flanks of the rift, whereas the middle crust (12-22 km depth) consists of more mafic, hornblende-rich metamorphic rocks, probably intruded by mafic rocks beneath the rift axis. The lower crust on the flanks of the rift may consist of mafic granulite facies rocks. Along the rift axis, the lower crust varies in thickness from 9 km in the southern rift to only 2-3 km in the north, and has a seismic velocity substantially higher than the samples investigated in this study. The lower crust of the rift probably consists of a crust/mantle mix of high-grade metamorphic rocks, mafic intrusives, and an igneous mafic residuum accreted to the base of the crust during differentiation of a melt derived from the upper mantle.

Tectonophysics↗