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Topography-derived wetness indices are associated with household-level malaria risk in two communities in the western Kenyan highlands
Justin M Cohen, Kacey C Ernst, Kim A Lindblade, John M Vulule, Chandy C John, Mark L Wilson
Malaria Journal , 2008, DOI: 10.1186/1475-2875-7-40
Abstract: Hydrologic modelling techniques were adapted to predict the flow of water across the landscape surrounding households in two communities in the western Kenyan highlands. These surface analyses were used to generate indices describing predicted water accumulation in regions surrounding the study area. Households with and without malaria were compared for their proximity to regions of high and low predicted wetness. Predicted wetness and elevation variables were entered into bivariate and multivariate regression models to examine whether significant associations with malaria were observable at small spatial scales.On average, malaria case households (n = 423) were located 280 m closer to regions with very high wetness indices than non-malaria "control" households (n = 895) (t = 10.35, p < 0.0001). Distance to high wetness indices remained an independent predictor of risk after controlling for household elevation in multivariate regression (OR = 0.93 [95% confidence interval = 0.89–0.96] for a 100 m increase in distance). For every 10 m increase in household elevation, there was a 12% decrease in the odds of the house having a malaria case (OR = 0.88 [0.85–0.90]). However, after controlling for distance to regions of high predicted wetness and the community in which the house was located, this reduction in malaria risk was not statistically significant (OR = 0.98 [0.94–1.03]).Proximity to terrain with high predicted water accumulation was significantly and consistently associated with increased household-level malaria incidence, even at small spatial scales with little variation in elevation variables. These results suggest that high wetness indices are not merely proxies for valley bottoms, and hydrologic flow models may prove valuable for predicting areas of high malaria risk in highland regions. Application in areas where malaria surveillance is limited could identify households at higher risk and help focus interventions.Elevation has long been recognized to be ass
Investments in Land Conservation in the Ethiopian Highlands: A Household Plot-level Analysis of the Roles of Poverty, Tenure Security, and Market Incentives  [cached]
GENANEW Bekele Worku,ALEMU Mekonnen
International Journal of Economics and Finance , 2012, DOI: 10.5539/ijef.v4n6p32
Abstract: Land degradation is a major problem undermining land productivity in the highlands of Ethiopia. This paper analyses the decisions made by individual household to adopt and intensify land conservation investment. The paper used a Box-Cox Double Hurdle specification and offers the advantage of exploiting panel data collected in a household survey of 6,408 plots in Ethiopia. The results suggest that adoption and intensification decisions appear to be explained by different processes, justifying the use of Box-Cox double hurdle approach over more restrictive models. Poverty-related factors seem to have mixed effect on both adoption and intensification decisions. While farmer's adoption decision is affected by expectation of the certainty of cultivating the land for the next five years (risk for long term), intensification of land conservation investment is determined by whether or not the plot is owner-operated (risk for immediate period) and plot-home distance. A lesson for policymakers is that major changes in land conservation investments will require attention to many factors because no single factor can be used as a major policy leverage instrument. Some of these factors (such as land tenure security, plot size, and total farm holdings) can be directly influenced by government policies and programs.
Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
Emmanuel Mushinzimana, Stephen Munga, Noboru Minakawa, Li Li, Chen-chieh Feng, Ling Bian, Uriel Kitron, Cindy Schmidt, Louisa Beck, Guofa Zhou, Andrew K Githeko, Guiyun Yan
Malaria Journal , 2006, DOI: 10.1186/1475-2875-5-13
Abstract: Panchromatic aerial photos, Ikonos and Landsat Thematic Mapper 7 satellite images were acquired for a study area in Kakamega, western Kenya. Supervised classification of land-use and land-cover and visual identification of aquatic habitats were conducted. Ground survey of all aquatic habitats was conducted in the dry and rainy seasons in 2003. All habitats positive for anopheline larvae were identified. The retrieved data from the remote sensors were compared to the ground results on aquatic habitats and land-use. The probability of finding aquatic habitats and habitats with Anopheles larvae were modelled based on the digital elevation model and land-use types.The misclassification rate of land-cover types was 10.8% based on Ikonos imagery, 22.6% for panchromatic aerial photos and 39.2% for Landsat TM 7 imagery. The Ikonos image identified 40.6% of aquatic habitats, aerial photos identified 10.6%, and Landsate TM 7 image identified 0%. Computer models based on topographic features and land-cover information obtained from the Ikonos image yielded a misclassification rate of 20.3–22.7% for aquatic habitats, and 18.1–25.1% for anopheline-positive larval habitats.One-metre spatial resolution Ikonos images combined with computer modelling based on topographic land-cover features are useful tools for identification of anopheline larval habitats, and they can be used to assist to malaria vector control in western Kenya highlands.Malaria is a major health problem in sub-Saharan Africa, where it is estimated to be responsible for over 1 million deaths every year in children younger than five and pregnant women [1]. Out of the total human population in Africa, 15% live in highlands, where there are increasing risks for epidemics [1]. Current strategies for malaria control involve treating infected individuals with anti-malarial drugs to clear the parasites, and reducing human-mosquito contact rates through vector control efforts. Anti-malarial drugs have little impact on the
On the calculation of the topographic wetness index: evaluation of different methods based on field observations
R. S rensen, U. Zinko,J. Seibert
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2006,
Abstract: The topographic wetness index (TWI, ln(a/tanβ)), which combines local upslope contributing area and slope, is commonly used to quantify topographic control on hydrological processes. Methods of computing this index differ primarily in the way the upslope contributing area is calculated. In this study we compared a number of calculation methods for TWI and evaluated them in terms of their correlation with the following measured variables: vascular plant species richness, soil pH, groundwater level, soil moisture, and a constructed wetness degree. The TWI was calculated by varying six parameters affecting the distribution of accumulated area among downslope cells and by varying the way the slope was calculated. All possible combinations of these parameters were calculated for two separate boreal forest sites in northern Sweden. We did not find a calculation method that performed best for all measured variables; rather the best methods seemed to be variable and site specific. However, we were able to identify some general characteristics of the best methods for different groups of measured variables. The results provide guiding principles for choosing the best method for estimating species richness, soil pH, groundwater level, and soil moisture by the TWI derived from digital elevation models.
Numerical Modelling of the Topographic Wetness Index: An Analysis at Different Scales  [PDF]
Anderson Luis Ruhoff, Nilza Maria Reis Castro, Alfonso Risso
International Journal of Geosciences (IJG) , 2011, DOI: 10.4236/ijg.2011.24050
Abstract: A variety of landscape properties have been modeled successfully using topographic indices such as topographic wetness index (TWI), defined as ln(a/tanβ), where a is the specific upslope area and β is the surface slope. In this study, 25 m spatial resolution from digital elevation models (DEM) data were used to investigate the scale-dependency of TWI values when converting DEMs to 50 and 100 m. To investigate the impact of different spatial resolution, the two lower resolution DEMs were interpolated to the original 25 m grid size. In addition, to compare different flow-direction algorithms, a second objective was to evaluate differences in spatial patterns. Thus the values of TWI were compared in two different ways: 1) distribution functions and their statistics; and 2) cell by cell comparison of DEMs with the same spatial resolution but different flow- directions. As in previous TWI studies, the computed specific upstream is smaller, on average, at higher resolution. TWI variation decreased with increasing grid size. A cell by cell comparison of the TWI values of the 50 and 100 m DEMs showed a low correlation with the TWI based on the 25 m DEM. The results showed significant differences between different flow-diretction algorithms computed for DEMs with 25, 50 and 100 m spatial resolution.
New records of Anopheles arabiensis breeding on the Mount Kenya highlands indicate indigenous malaria transmission
Hong Chen, Andrew K Githeko, Guofa Zhou, John I Githure, Guiyun Yan
Malaria Journal , 2006, DOI: 10.1186/1475-2875-5-17
Abstract: A survey on 31 aquatic sites for the malaria-vector mosquitoes was carried out along the primary road on the highlands around Mount Kenya and the nearby Mwea lowland during April 13 to June 28, 2005. Anopheline larvae were collected and reared into adults for morphological and molecular species identification. In addition, 31 families at three locations of the highlands were surveyed using a questionnaire about their history of malaria cases during the past five to 20 years.Specimens of Anopheles arabiensis were molecularly identified in Karatina and Naro Moru on the highlands at elevations of 1,720 – 1,921 m above sea level. This species was also the only malaria vector found in the Mwea lowland. Malaria cases were recorded in the two highland locations in the past 10 years with a trend of increasing.Local malaria transmission on the Mount Kenya highlands is possible due to the presence of An. arabiensis. Land use pattern and land cover might be the key factors affecting the vector population dynamics and the highland malaria transmission in the region.More than 3 million malaria cases, with one million deaths due to malaria, are reported in sub-Saharan Africa, each year [1]. Historically, no malaria case has been reported on the Mount Kenya highlands in central Kenya [2]. The residents on the highlands west of the mountain began to notice this disease about 10 years ago. Originally, it was believed that malaria was introduced from the Mwea lowland where most vehicular traffic passes through onto the highlands, and where the vector is Anopheles arabiensis. An alternative hypothesis was that a vector and parasite were introduced and malaria was transmitted locally on the highlands. However, no malaria-vector mosquito has so far been recorded on the Mount Kenya highlands [3,4], thereby arguing against this hypothesis. A third possibility was that the malaria was latent in the highlands until ecological and climatic changes modify the transmission patterns.The emergen
Quantitative Error Assessment of Topographic Wetness Index Algorithms

BAO Lili,QIN Chengzhi,ZHU Axing,

地理科学进展 , 2011,
Abstract: Topographic Wetness Index (TWI) is a widely-used topographic attribute which can predict the control of terrain on spatial distribution of soil moisture. Diverse TWI algorithms might get very different results; therefore, it is necessary to assess the algorithms. Traditional error assessment method applies TWI algorithms to 'real-world' DEM, but the error from DEM quality might interfuse the error from algorithms and thus influence the accuracy of evaluation. To solve the problem, this paper proposes an assessment method of error from TWI algorithm with artificial DEMs which can avoid data source error. Four typical TWI algorithms, i.e. TWI algorithm based on a typical single flow direction algorithm (D8), TWI algorithm based on a typical multiple flow direction algorithm (FD8), TWI algorithm based on an adaptive multiple flow direction algorithm (MFD-md), and TWI algorithm using MFD-md in which the maximum downslope, instead of traditional slope gradient, is used to estimate the tanβ in equation of TWI, are evaluated by the proposed assessment method. First, four artificial surfaces are constructed to simulate typical compound terrain conditions, i.e. convex-centred slope, concave-centred slope, saddle-centred slope, and ridge-centred slope, respectively. Secondly, the artificial surfaces are converted to three sets of artificial DEM data with different cell size (1 m, 10 m, and 30 m) to apply TWI algorithms to compute TWI. Third, the theoretical TWIs for every artificial surface are calculated to quantitatively assess the error from TWI algorithms based on RMSE. Assessment result shows that TWI algorithms based on multiple flow direction algorithm (MFD) perform better than TWI algorithm based on single flow direction algorithm (SFD), i.e. D8, under terrain conditions of convex-centred slope, concave-centred slope and saddle-centred slope. Under ridge-centred slope terrain condition, the result of TWI algorithm based on SFD is just inferior to the result of TWI algorithm which combines MFD-md with maximum downslope algorithm. As the resolution becomes coarser, errors of TWI algorithms based on MFD become larger on the whole, while the trends of results of TWI algorithm based on SFD vary with different terrain conditions. The proposed quantitative assessment method for TWI algorithm can be similarly used to assess algorithms of other compound topographic attributes, such as specific catchment area, stream power index, and so on.
Reducing Land Degradation on the Highlands of Kilimanjaro Region: A Biogeographical Perspective  [PDF]
Christine Noe
Open Journal of Soil Science (OJSS) , 2014, DOI: 10.4236/ojss.2014.413043

In 2012, governments across the world adopted “The Future We Want” outcome document in Rio De Janeiro as a commitment to achieve a land-degradation-neutral world. This document reasserts the importance of sustainable land management in the top of the debates on sustainable development. This paper provides an overview of Tanzania’s preparedness towards achieving these global objectives. The paper is based on a keynote address which was presented in the conference on reducing land degradation on the highlands of Kilimanjaro Region in Tanzania. Using a biogeographical perspective, the paper assesses challenges of adopting programmatic approach to sustainable land management in Tanzania. It also presents some opportunities that exist through Global Mechanism of the United Nations Convention to Combat Desertification, which promote actions leading to coordination, mobilization and channeling of financial resources to assist member countries to coordinate and sustain sustainable land management projects.

Computation Method of Topogr aphic Wetness Index in Low Relief Ar ea

QIN Chengzhi,YANG Lin,ZHU AXing,LI Baolin,PEI Tao,ZHOU Chenghu,

地理科学进展 , 2006,
Abstract: Topographic wetness index, which is designed for modeling the status ("dry" or "wet") of the soil moisture quantitatively, is an important index for both predictive soil mapping and distributed hydrological modeling in a catchment. Current methods for calculating topographic wetness index have evident problems when applied in low relief area. Outside the positions of narrow accumulation line with high topographic wetness index, the topographic wetness index dramatically jumps down in other parts of wide valley area. This is unreasonable because the soil moisture should be comparatively average and high in the wide and flat valley, and the value of topographic wetness index should be high. This problem is caused by both the flow accumulation algorithm and the slope gradient used during computing the topographic wetness index. A new method for computing topographic wetness index is proposed in this paper to address this problem. Firstly, flow accumulation is calculated by a multiple flow direction algorithm(MFD-fg). Topographic wetness index is then computed by the flow accumulation and maximum downslope. The maximum downslope used in the computation of topographic wetness index is matched with the idea of both MFD-fg and topographic wetness index. Furthermore, a post-processing method is also proposed to compute the topographic wetness index in valley area. The topographic wetness index in the valley area is interpolated by a Gaussian function based on the value of the topographic wetness index on the nearest position on extracted flow accumulation line. The application in a small watershed shows that the method proposed in this paper can get a comparatively reasonable distribution of topographic wetness index for not only the hillslope but also the wide valley area. The value of topographic wetness index in valley area is averagely high and with a smooth transition, which reflects the natural status of the soil moisture in application area. In the future research, the method proposed in this paper will be evaluated by both artificial surfaces and the real applications.
Assimilation of Soil Wetness Index and Leaf Area Index into the ISBA-A-gs land surface model: grassland case study
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, C. Albergel,S. Lafont
Biogeosciences (BG) & Discussions (BGD) , 2011,
Abstract: The performance of the joint assimilation in a land surface model of a Soil Wetness Index (SWI) product provided by an exponential filter together with Leaf Area Index (LAI) is investigated. The data assimilation is evaluated with different setups using the SURFEX modeling platform, for a period of seven years (2001–2007), at the SMOSREX grassland site in southwestern France. The results obtained with a Simplified Extended Kalman Filter demonstrate the effectiveness of a joint data assimilation scheme when both SWI and Leaf Area Index are merged into the ISBA-A-gs land surface model. The assimilation of a retrieved Soil Wetness Index product presents several challenges that are investigated in this study. A significant improvement of around 13 % of the root-zone soil water content is obtained by assimilating dimensionless root-zone SWI data. For comparison, the assimilation of in situ surface soil moisture is considered as well. A lower impact on the root zone is noticed. Under specific conditions, the transfer of the information from the surface to the root zone was found not accurate. Also, our results indicate that the assimilation of in situ LAI data may correct a number of deficiencies in the model, such as low LAI values in the senescence phase by using a seasonal-dependent error definition for background and observations. In order to verify the specification of the errors for SWI and LAI products, a posteriori diagnostics are employed. This approach highlights the importance of the assimilation design on the quality of the analysis. The impact of data assimilation scheme on CO2 fluxes is also quantified by using measurements of net CO2 fluxes gathered at the SMOSREX site from 2005 to 2007. An improvement of about 5 % in terms of rms error is obtained.
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