Eco-hydrological modeling of soil wetting pattern dimensions under drip irrigation systems.

Reliable information on the horizontal and vertical dimensions of the wetted soil beneath a point source is critical for designing accurate, cost-effective, and efficient surface and subsurface drip irrigation systems. Several factors, including soil properties, initial soil conditions, dripper flow rate, number of drippers, spacing between drippers, irrigation management, plant root characteristics, and evapotranspiration, influence the dimensions and shape of wetting patterns. The objective of this study was to briefly review previous studies, collect the analytical, numerical, and empirical models developed, and evaluate the effectiveness of the most common empirical method for predicting the dimensions of soil wetted around drippers using measured data from field surveys. With this review study, we aim to promote a better understanding of soil water dynamics under point-source drip irrigation systems, help improve soil water dynamics under point-source drip irrigation systems, and identify issues that should be better addressed in future modeling efforts. A drip irrigation system was configured with three different emitters with different capacities (2, 4, and 8 l h-1) in the point source to determine the soil wetting front under the point source. The five most selected empirical equations (Al-Ogaidi, Malek and Peters, Amin and Ekhmaj, Li and Schwartzman and Zur) were statistically analyzed to test the efficiency in sandy loam soil. According to the results of the field investigation, statistical comparisons of the empirical models with the field investigation data were performed using the mean absolute error (MAE), root mean square error (RMSE), Nash-Sutcliffe model efficiency (CE), and coefficients of determination (R2). The advanced simulation of the wetting front was used based on the best accuracy of the selected empirical model. In general, the Li model (MAE, RMSE, EF, and R2 were 0.698 cm, 0.894 cm, 0.970 cm2 cm-2, and 0.970, respectively, for the wetted soil width and 1.800 cm, 1.974 cm, 0.927 cm2 cm-2, and 0.986, for the vertical advance) proved to be the best after statistical analysis with field data.

Identification of risk factors for malaria control by focused interventions in Ranchi district, Jharkhand, India.

BACKGROUND & OBJECTIVES: Ranchi, the capital of Jharkhand state is endemic for malaria, particularly the Bundu Primary Health Centre (PHC) is the worst affected. Therefore, a study was initiated during 2009 using remote sensing (RS) and geographical information system (GIS) to identify risk factors responsible for high endemicity in this PHC. METHODS: Bundu and Angara in Ranchi district were identified as high and low malaria endemic PHCs based on epidemiological data of three years (2007-09). The habitation, streams, other water body, landform, PHC and village boundary thematic maps were prepared using IRS-P6/LISS III-IV imageries and macro level breeding sites were identified. Digital elevation model (DEM) of the PHCs was generated using Cartosat Stereo Pair images and from DEM, slope map was derived to calculate flat area. From slope, aspect map was derived to indicate direction of water flow. Length of perennial streams, area under rocky terrain and buffer zones of 250, 500 and 750 m were constructed around streams. High resolution remote sensing imageries were used to identify micro level breeding sites. Based on macro-micro breeding sites, six villages from each PHC were selected randomly having combination of different parameters representing all ecotypes. Entomological data were collected during 2010-11 in pre- and post-monsoon seasons following standard techniques and analyzed statistically. Differential analysis was attempted to comprehend socioeconomic and other determinants associated with malaria transmission. RESULTS: The study identified eight risk factors responsible for higher malaria endemicity in Bundu in comparison to Angara PHC based on ecological, entomological, socioeconomic and other local parameters. CONCLUSION: Focused interventions in integrated vector management (IVM) mode are required to be carried out in the district for better management and control of disease.

Impact of deforestation on known malaria vectors in Sonitpur district of Assam, India.

BACKGROUND & OBJECTIVES: An alarming rate of deforestation has been reported from Sonitpur district of Assam, India therefore, a study was initiated during 2009 using remote sensing (RS) to assess deforested areas in the district and to study the impact on malaria vectors in order to formulate appropriate control strategy. METHODS: RS imageries of 2000 and 2009 were used to assess deforested areas in the selected district. Entomological data were collected in four surveys during 2009-2011. The data were analyzed statistically using test of single proportions (χ 2 ) and pair-wise comparison. Vector incrimination was done using enzyme-linked immunosorbent assay (ELISA) and entomological inoculation rate (EIR) was calculated to estimate transmission intensity. RESULTS: The deforested areas were identified in north-western parts of Sonitpur district falling in Dhekiajuli Primary Health Centre (PHC). The forest cover of the PHC decreased >50% during 2000-2009. Five species of anopheline vectors were collected. Anopheles minimus sensu lato (s.l.) was collected least abundantly while An. culicifacies s.l. prevailed most abundantly and significant difference was observed between proportions of the collected vector species. Pair-wise comparison between An. culicifacies s.l. and An. minimus s.l. was also found statistically significant indicating that An. culicifacies s.l. is establishing its population in deforested areas. An. culicifacies s.l. was found ELISA positive and EIR was measured as 4.8 during transmission season. CONCLUSION: An. culicifacies s.l. replaced An. minimus s.l., the vector of malaria in northeast India and was found ELISA positive, therefore could have possible role in malaria transmission in the deforested areas of the district.