Your search found 22 records
1 Lee, M.-J. 2005. Micro-econometrics for policy, program and treatment effects. New York, NY, USA: Oxford University Press. 248p.
Econometrics ; Economic policy ; Mathematical models ; Statistical methods ; Multivariate analysis ; Regression analysis ; Sensitivity analysis
(Location: IWMI HQ Call no: 519.5 G000 LEE Record No: H044058)
(0.45 MB)
This book brings to the fore recent advances in econometrics for treatment effect analysis. It aims to put together various economic treatment effect models in a coherent fashion, determine those that can be parameters of interest, and show how these can be identified and estimated under weak assumptions. The emphasis throughout the book is on semi- and non-parametric estimation methods, but traditional parametric approaches are also discussed. This book is ideally suited to researchers and graduate students with a basic knowledge of econometrics.
2 Bangwayo-Skeete, P. F.; Zikhali, Precious. 2011. Social tolerance for human diversity in Sub-Saharan Africa. International Journal of Social Economics, 38(6):516-536. [doi: https://doi.org/10.1108/03068291111131382]
Social problems ; Tolerance ; Economic growth ; Statistics ; Public health ; AIDS ; Policy ; Multivariate analysis / Africa South of Sahara
(Location: IWMI HQ Call no: e-copy only Record No: H044434)
(0.14 MB)
Purpose – This paper seeks to investigate the individual-level determinants of self-declared social tolerance towards six groups/practices in Sub-Saharan Africa (SSA): tolerance to linguistic differences, racial distinction, religious dissimilarity, homosexuality, acquired immuno deficiency syndrome (AIDS) victims and immigrants.Design/methodology/approach – Using individual-level data from the 2005 World Values Survey, the paper simultaneously estimates multivariate probit models for all six dimensions of social tolerance.Findings – Apart from the strong interdependency among all social tolerance indicators, the analysis reveals that individual attributes affect tolerance towards the six groups differently. For instance, education enhances social tolerance for all groups except homosexuals while access to media increase tolerance for people living with AIDS.Research/limitations/implications – Effective social tolerance policies can be enhanced through joint targeting of the indicators considered. Moreover, tolerance-enhancing policies generally benefit from improved access to education while improved access to media could increase tolerance for AIDS victims.Originality/value – The originality of the analysis lies in the joint analysis or determination of a wider spectrum of social tolerance indicators. This paper can help to inform policies that are aimed at reducing SSA’s recurrent inter- and intra-group conflicts attributed primarily to the region’s high levels of ethnic and cultural fragmentation.
3 Demissie, Solomon, S.; Awulachew, Seleshi Bekele; Molden, David; Yilma, Aster Denekew. 2012. Spatial characterization of the Nile Basin for improved water management. In Awulachew, Seleshi Bekele; Smakhtin, Vladimir; Molden, David; Peden D. (Eds.). The Nile River Basin: water, agriculture, governance and livelihoods. Abingdon, UK: Routledge - Earthscan. pp.47-60.
River basins ; Nomenclature ; Water management ; Climate change ; Topography ; Hydrological factors ; Vegetation ; Indicators ; Ecology ; Environmental effects ; Multivariate analysis / Africa / Nile River Basin
(Location: IWMI HQ Call no: IWMI Record No: H045311)
(1007.22KB)
4 Crase, L.; Gandhi, V. P. (Eds.) 2009. Reforming institutions in water resource management: policy and performance for sustainable development. London, UK: Earthscan. 364p.
Water resources development ; Water management ; Institutions ; Legal aspects ; Rain water management ; Sustainable development ; Developing countries ; Irrigation management ; Participatory management ; Privatization ; Decision making ; Multivariate analysis ; Poverty ; Households ; Land ownership ; Investment ; Water user associations / Australia / India / Australian Capital Territory / New South Wales / Andhra Pradesh / Maharashtra / Gujarat
(Location: IWMI HQ Call no: 363.61 G000 CRA Record No: H045793)
(0.30 MB)
5 Wooldridge, J. M. 2010. Econometric analysis of cross section and panel data. 2nd ed. Cambridge, MA, USA: MIT Press. 1064p.
Statistical methods ; Econometrics ; Mathematical models ; Linear models ; Cross sectional analysis ; Simultaneous equation analysis ; Single equation analysis ; Regression analysis ; Multivariate analysis ; Non linear programming ; Estimation ; Data analysis ; Cluster sampling ; Testing
(Location: IWMI HQ Call no: 330.015195 G000 WOO Record No: H047137)
(0.88 MB)
6 Wooldridge, J. M. 2010. Econometric analysis of cross section and panel data. 2nd ed. Cambridge, MA, USA: MIT Press. 1064p.
Statistical methods ; Econometrics ; Mathematical models ; Linear models ; Cross sectional analysis ; Simultaneous equation analysis ; Single equation analysis ; Regression analysis ; Multivariate analysis ; Non linear programming ; Estimation ; Data analysis ; Cluster sampling ; Testing
(Location: IWMI HQ Call no: 330.015195 G000 WOO c2 Record No: H047138)
(0.88 MB)
7 Mustafa, M. G. 2015. Community-based fisheries management: improving fish biodiversity in inland fisheries of Bangladesh. In Humphreys, E.; Tuong, T. P.; Buisson, Marie-Charlotte; Pukinskis, I.; Phillips, M. (Eds.). Proceedings of the CPWF, GBDC, WLE Conference on Revitalizing the Ganges Coastal Zone: Turning Science into Policy and Practices, Dhaka, Bangladesh, 21-23 October 2014. Colombo, Sri Lanka: CGIAR Challenge Program on Water and Food (CPWF). pp.290-302.
Fishery management ; Fishery production ; Community involvement ; Projects ; Inland fisheries ; Habitat ; Biodiversity ; Species ; Sustainability ; Rivers ; Floodplains ; Wetlands ; Multivariate analysis / Bangladesh
(Location: IWMI HQ Call no: IWMI Record No: H047207)
https://cgspace.cgiar.org/bitstream/handle/10568/66389/Revitalizing%20the%20Ganges%20Coastal%20Zone%20Book_Low%20Version.pdf?sequence=1
https://vlibrary.iwmi.org/pdf/H047207.pdf
https://vlibrary.iwmi.org/pdf/H047207.pdf
(0.56 MB) (11.9 MB)
8 Perera, K. C.; Western, A. W.; George, B.; Nawarathna, B. 2015. Multivariate time series modeling of short-term system scale irrigation demand. Journal of Hydrology, 531(Part 3):1003-1019. [doi: https://doi.org/10.1016/j.jhydrol.2015.11.007]
Irrigation systems ; Water demand ; Forecasting ; Performance evaluation ; Multivariate analysis ; Time series analysis ; Models ; Weather ; Precipitation ; Irrigation canals ; Flow discharge ; Farmers attitudes / Australia / Goulburn-Murray Irrigation District
(Location: IWMI HQ Call no: e-copy only Record No: H047570)
(6.17 MB)
Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi,OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1–5 days ahead daily IDCGi,ASP and IDCGi,OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash–Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi,OTR across 5 command areas were ranged 0.98–0.78. These models were capable of generating skillful forecasts (MSSS P 0.5 and ACC P 0.6) of IDCGi, ASP and IDCGi,OTR for all 5 lead days and IDCGi, ASP and IDCGi,OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi,OTR forecasts have improved the operators’ ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers’ face, such as changing water policy, continued development of water markets, drought and changing technology.
9 Gning, A. A.; Orban, P.; Gesels, J.; Ngom, F. D.; Dassargues, A.; Malou, R.; Brouyere, S. 2017. Factors controlling the evolution of groundwater dynamics and chemistry in the Senegal River Delta. Journal of Hydrology: Regional Studies, 10:133-144. [doi: https://doi.org/10.1016/j.ejrh.2017.01.005]
Groundwater table ; Surface water ; Water levels ; Monitoring ; Saline water ; Soil salinization ; Irrigation water ; Rain ; Hydrogeology ; Geochemistry ; Chemical composition ; Hydrodynamics ; Models ; Multivariate analysis ; Rivers ; Deltas / Senegal / Senegal River Delta
(Location: IWMI HQ Call no: e-copy only Record No: H048129)
http://www.sciencedirect.com/science/article/pii/S221458181730037X/pdfft?md5=fba6295f07cffdb349955306459bdffd&pid=1-s2.0-S221458181730037X-main.pdf
https://vlibrary.iwmi.org/pdf/H048129.pdf
https://vlibrary.iwmi.org/pdf/H048129.pdf
(3.14 MB) (3.13 MB)
Study region: Senegal River Delta.
Study focus: The Senegal River Delta is a strategic region for the development of irrigated agriculture. Despite a Sahelian climatic context, the management of the river with dams ensures water availability throughout the year. With the intensification of agriculture, degradation of cultivated soils is observed, mostly linked to the existence of a shallow salty aquifer. In this context, regional surveys were performed to characterize groundwater–surface water interactions and to identify the impact of artificial river management and agricultural intensification on the evolution of groundwater dynamics and chemistry.
New hydrological insights for the region: Results show that groundwater far away from rivers and outside irrigated plots has evolved from marine water to brines under the influence of evapotranspiration. Near rivers, salinity of groundwater is lower than seawater and groundwater mineralization seems to evolve in the direction of softening through cationic exchanges related to permanent contact with fresh water. Despite large volumes of water used for rice cultivation, groundwater does not show any real softening trend in the cultivated parcels. Results show that the mechanisms that contribute to repel salt water from the sediments correspond to a lateral flush near permanent surface water streams and not to vertical drainage and dilution with rainfall or irrigation water. It is however difficult to estimate the time required to come back to more favorable conditions of groundwater salinity.
Study focus: The Senegal River Delta is a strategic region for the development of irrigated agriculture. Despite a Sahelian climatic context, the management of the river with dams ensures water availability throughout the year. With the intensification of agriculture, degradation of cultivated soils is observed, mostly linked to the existence of a shallow salty aquifer. In this context, regional surveys were performed to characterize groundwater–surface water interactions and to identify the impact of artificial river management and agricultural intensification on the evolution of groundwater dynamics and chemistry.
New hydrological insights for the region: Results show that groundwater far away from rivers and outside irrigated plots has evolved from marine water to brines under the influence of evapotranspiration. Near rivers, salinity of groundwater is lower than seawater and groundwater mineralization seems to evolve in the direction of softening through cationic exchanges related to permanent contact with fresh water. Despite large volumes of water used for rice cultivation, groundwater does not show any real softening trend in the cultivated parcels. Results show that the mechanisms that contribute to repel salt water from the sediments correspond to a lateral flush near permanent surface water streams and not to vertical drainage and dilution with rainfall or irrigation water. It is however difficult to estimate the time required to come back to more favorable conditions of groundwater salinity.
10 Mehra, M.; Singh, C. K.; Abrol, I. P.; Oinam, B. 2017. A GIS-based methodological framework to characterize the Resource Management Domain (RMD): a case study of Mewat district, Haryana, India. Land Use Policy, 60:90-100. [doi: https://doi.org/10.1016/j.landusepol.2016.10.018]
Resource management ; Groundwater ; Irrigation water ; Water quality ; GIS ; Socioeconomic environment ; Mapping ; Biophysics ; Soil fertility ; Erosion ; Crop management ; Land ownership ; Population density ; Multivariate analysis ; Models ; Case studies / India / Haryana / Mewat
(Location: IWMI HQ Call no: e-copy only Record No: H048305)
(3.78 MB)
Resource Management Domains (RMD) represent a way to characterize land units, based on biophysical and socioeconomic characteristics. This concept has been applied to delineate and characterize sustainable land units for agricultural use in the Mewat District of Haryana, India. A GIS-based framework was conceptualized to characterize RMD and appropriate biophysical and socioeconomic parameters were identified based on local conditions and expert opinion. The biophysical characteristics of the region were represented by soil (soil erosion and fertility) and groundwater (groundwater quality, potential and vulnerability) parameters. Population density, landholding, cropping pattern, irrigation source, fertilizer type, sprinkler density, tubewell type and tractor density were considered for socioeconomic characterization. Each of these parameters was modelled and mapped using well established methods The biophysical and socioeconomic parameters were integrated using a multivariate clustering method. The integration modelling results in the delineation of the region into seven RMDs, which were validated with two focus group discussions (FGD) in each of the RMD’s. The correlation between the RMD modelling results and the FGD was found to be more than 90% in five RMDs and 65% and 39% in the remaining two RMDs respectively. The result was also validated with feedback from the local administrative authorities. The study charts a sound basis for policy makers for taking the necessary steps to address location-specific differential agricultural needs in any region.
11 Monaco, F.; Sali, G. 2018. How water amounts and management options drive irrigation water productivity of rice. A multivariate analysis based on field experiment data. Agricultural Water Management, 195:47-57. [doi: https://doi.org/10.1016/j.agwat.2017.09.014]
Water management ; Irrigation water ; Water productivity ; Agricultural production ; Rice ; Crop yield ; Irrigation methods ; Strategies ; Field experimentation ; Multivariate analysis ; Regression analysis ; Models
(Location: IWMI HQ Call no: e-copy only Record No: H048468)
(1.03 MB)
Rice cultivation is globally hampered by several conditions, which urge farmers to maintain adequate production levels while properly managing irrigation water. This has noticeable repercussions on the efficient use of the resource and on water productivity. Nonetheless, more often, this latter topic is addressed by estimating the respective values, without deeply investigating the possible causes behind such discrepancies. The main objective of this paper is to overcome such limitations, by (i) providing a comprehensive and updated overview of Irrigation Water Productivity (IWP) for rice, and (ii) exploring the role of irrigation water in determining IWP value. The analysis of experimental data collected from 51 studies reveals IWP to vary between 0.09 and 8.10 kg m-3, with mean and median values of 1.36 and 0.85 kg m-3 respectively; moreover, a non-linear relationship between irrigation water amounts and IWP (r2 = 0.81) is depicted. Further on, data are analyzed using an econometric approach. Specifically, a multivariate linear regression model is used to shed light on the joint contribution of water inputs, regime and irrigation method to productivity. This demonstrates the significant roles of irrigation ( = -1.006) and rainfall ( = 0.062) amounts, while aerobic regime and irrigation method is proved to be a further key driver ( = -0.305). Such results enable identifying the elements to be enforced, if increasing IWP for rice is the prime objective. Finally, some implications are derived for water policy and the connections with weather-climatic and environmental conditions that are globally affecting the availability of water in agriculture.
12 Nigussie, Z.; Tsunekawa, A.; Haregeweyn, N.; Adgo, E.; Nohmi, M.; Tsubo, M.; Aklog, D.; Meshesha, D. T.; Abele, S. 2017. Factors influencing small-scale farmers’ adoption of sustainable land management technologies in north-western Ethiopia. Land Use Policy, 67:57-64. [doi: https://doi.org/10.1016/j.landusepol.2017.05.024]
Small scale farming ; Farmer participation ; Sustainable land management ; Technology ; Water conservation ; Soil conservation ; Land degradation ; Watersheds ; Drought ; Socioeconomic environment ; Multivariate analysis ; Models / Ethiopia / Upper Blue Nile Basin
(Location: IWMI HQ Call no: e-copy only Record No: H048585)
(0.54 MB)
Land degradation is a serious global problem because it leads to losses in food production and thus jeopardizes food security worldwide, particularly in developing countries. Despite numerous efforts to introduce sustainable land management (SLM) strategies and practices, their adoption by the primary target group, small-scale farmers in developing countries, has been [s]low. This study assesses the problem for the case of Ethiopia. The aim was to analyze the underlying factors that affect the adoption of SLM technologies in the Upper Blue Nile Basin. A detailed survey of 300 households and 1010 farm plots was conducted. Data were analyzed by using both descriptive and econometric analyses. Results show that farmers’ adoption of interrelated SLM measures depended on a number of socio-economic and farm-related factors in combination with the characteristics of the technologies themselves. For example, plot size and the availability of labor, as well as the gender of the household head, affected which SLM technologies were adopted by certain types of households. The adoption of SLM measures depended on the adaptive economic capacity of the farmers, which can be quite diverse even within a small region and can differ from the adoption potential in other regions. Our results suggest that SLM policies and programs have to be individually designed for specific target groups within specific regions, which in turn means that “one size fits all” and “across the board” strategies – which are quite common in the field of SLM – should be abandoned by development agencies and policymakers.
13 Jampani, M.; Huelsmann, S.; Liedl, R.; Sonkamble, S.; Ahmed, S.; Amerasinghe, Priyanie. 2018. Spatio-temporal distribution and chemical characterization of groundwater quality of a wastewater irrigated system: a case study. Science of the Total Environment, 636:1089-1098. [doi: https://doi.org/10.1016/j.scitotenv.2018.04.347]
Wastewater irrigation ; Irrigation systems ; Groundwater ; Water quality ; Water pollution ; Periurban areas ; Multivariate analysis ; Statistical analysis ; Models ; River basins ; Irrigation water ; Aquifers ; Irrigated land ; Periurban agriculture ; Monsoon climate ; Case studies / India / Hyderabad / Musi River
(Location: IWMI HQ Call no: e-copy only Record No: H048766)
Wastewater irrigation is a common livelihood practice in many parts of the developing world. With the continuous irrigation supply, groundwater systems in these regions perceive adverse impacts due to inadequate infrastructure to treat the wastewater. The current study area, Musi River irrigation system, is one such case study located in the peri-urban Hyderabad of South India. The Musi River water, which is used for irrigation, is composed of untreated and secondary treated wastewater from Hyderabad city. Kachiwani Singaram micro-watershed in the peri-urban Hyderabad is practicing wastewater irrigation for the last 40 years. The current quality of (untreated) wastewater used for irrigation is expected to have adverse impacts on the local aquifers, but detailed investigations are lacking. To elucidate the groundwater quality dynamics and seasonality of the wastewater irrigation impacts on the peri-urban agricultural system, we analyzed the groundwater quality on a monthly basis for one hydrological year in the wastewater and groundwater irrigated areas, which exist next to each other. The spatio-temporal variability of groundwater quality in the watershed was analyzed with respect to wastewater irrigation and seasonality using multivariate statistical analysis, multi-way modeling and self-organizing maps. This study indicates the significance of combining various statistical techniques for detailed evaluation of the groundwater processes in a wastewater irrigated agricultural system. The results suggest that concentrations of the major ionic substances increase after the monsoon season, especially in wastewater irrigated areas. Multi-way modeling identified the major polluted groundwaters to come from the wastewater irrigated parts of the watershed. Clusters of chemical variables identified by using self-organizing maps indicate that groundwater pollution is highly impacted by mineral interactions and long-term wastewater irrigation. The study recommends regular monitoring of water resources and development of sustainable management strategies to mitigate the aquifer pollution in wastewater irrigation systems.
14 Trinh, T. Q.; Ranola, R. F. Jr; Camacho, L. D.; Simelton, E. 2018. Determinants of farmers’ adaptation to climate change in agricultural production in the central region of Vietnam. Land Use Policy, 70:224-231. [doi: https://doi.org/10.1016/j.landusepol.2017.10.023]
Climate change adaptation ; Agricultural production ; Farmers ; Strategies ; Extreme weather events ; Decision making ; Monitoring ; Training courses ; Households ; Living standards ; Weather forecasting ; Logit analysis ; Models ; Multivariate analysis / Vietnam / Ky Son commune
(Location: IWMI HQ Call no: e-copy only Record No: H049317)
(0.53 MB)
This paper discusses the likely changes in farm cultural practices that farmers would adopt to minimize agricultural production losses as a response to the increasing occurrence of extreme weather conditions due to climate change in the Central Region of Viet Nam. Using binary logit model and multivariate probit model, this paper examined different factors influencing farmers decision on adaptation to climate change in their agricultural production. Training attendance, farm size, damage level, educational level, farming experience, access to credit, and gender were the factors that influenced significantly the probability that farmers would adapt to climate change. Of these factors, attendance in climate change training and farm size were the most important factors affecting the farmers decision on adaptation to climate change, while labor availability and membership in local organizations were not. Three policy recommendations were proposed to enhance small-scale farmers adaptive capacity to climate change in the region. These include: i). broadening of training courses on climate change; ii). institute policies that would promote consolidation of farmlands; and, iii). integrate concepts of climate change and climate change adaptation into the operation of the local organizations.
15 Akhtar, N.; Syakir, M. I.; Rai, S. P.; Saini, R.; Pant, N.; Anees, M. T.; Qadir, A.; Khan, U. 2020. Multivariate investigation of heavy metals in the groundwater for irrigation and drinking in Garautha Tehsil, Jhansi District, India. Analytical Letters, 53(5):774-794. [doi: https://doi.org/10.1080/00032719.2019.1676766]
Groundwater pollution ; Groundwater assessment ; Groundwater irrigation ; Drinking water ; Heavy metals ; Water quality ; Anthropogenic factors ; Hydrogeology ; Principal component analysis ; Multivariate analysis / India / Jhansi / Garautha
(Location: IWMI HQ Call no: e-copy only Record No: H049649)
(2.42 MB)
Groundwater is an important source for drinking and irrigation purposes. Due to anthropogenic activities, heavy metals have been leaching due to industrial waste and agricultural activities to the groundwater causing pollution. The assessment of groundwater quality is necessary to reduce the pollution to acceptable levels. Therefore, the aim of this study is to investigate heavy metal concentrations in the groundwater of the villages of Garautha Tehsil, Jhansi where the anthropogenic activities are active. The groundwater samples were analyzed by inductively coupled plasma – mass spectrometry (ICP-MS) and the results were compared to the 2012 Bureau of Indian Standard limits. Three multivariate statistical methods were used to analyze the groundwater quality for irrigation and drinking purposes and to investigate the geological and hydrogeological processes. The results of principal component analysis (PCA) identified four factors responsible for the data structure by illuminating the total variance of 77.83% of the dataset. The majority of groundwater samples contained Al, Co, Cu, Mn, Ni, Cr, Pb, and Fe within the acceptable limits except at few locations. However, the Al, Fe, and Mn concentration were high at a few sites due to rock–water interactions, whereas the concentration of As, Cd, and Zn were lower than their respective permissible limits in all groundwater samples. Furthermore, the groundwater quality for the use of irrigation is found to be acceptable at 19 locations, with only one high result.
16 Rana, V. K.; Suryanarayana, T. M. V. 2020. Performance evaluation of MLE [Maximum Likelihood Estimation], RF [Random Forest Tree] and SVM [Support Vector Machine] classification algorithms for watershed scale land use/land cover mapping using sentinel 2 bands. Remote Sensing Applications: Society and Environment, 19:100351. [doi: https://doi.org/10.1016/j.rsase.2020.100351]
Watersheds ; Land use mapping ; Land cover mapping ; Hydrology ; Models ; Performance evaluation ; Remote sensing ; Satellites ; Vegetation ; Cultivated land ; Rain ; Machine learning ; Principal component analysis ; Multivariate analysis / India / Gujarat / Vishwamitri Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H049839)
(14.80 MB)
The land use and land cover map plays a significant role in agricultural, water resources planning, management, and monitoring programs at regional and national levels and is an input to various hydrological models. Land use and land cover maps prepared using satellite remote sensing techniques in conjunction with landform-soil-vegetation relationships and ground truth are popular for locating suitable sites for the construction of water harvesting structures, soil and water conservation measures, runoff computations, irrigation planning and agricultural management, analyzing socio-ecological concerns, flood controlling, and overall watershed management. Here we use a novel approach to analyze Sentinel–2 multispectral satellite data using traditional and principal component analysis based approaches to evaluate the effectiveness of maximum likelihood estimation, random forest tree, and support vector machine classifiers to improve land use and land cover categorization for Soil Conservation Service Curve Number model. Additionally, we use stratified random sampling to evaluate the accuracies of resulted land use and land cover maps in terms of kappa coefficient, overall accuracy, producer's accuracy, and user's accuracy. The classifiers were used for classifying the data into seven major land use and land cover classes namely water, built-up, mixed forest, cultivated land, barren land, fallow land with vertisols dominance, and fallow land with inceptisols dominance for the Vishwamitri watershed. We find that principal component analysis with support vector machine is able to produce highly accurate land use and land cover classified maps. Principal component analysis extracts the useful spectral information by compressing redundant data embedded in each spectral channel. The study highlights the use of principal component analysis with support vector machine classifier to improve land use and land cover classification from which policymakers can make better decisions and extract basic information for policy amendments.
17 Dembele, M.; Zwart, Sander; Ceperley, N.; Mariethoz, G.; Schaefli, B. 2020. Multivariate and spatially calibrated hydrological model for assessing climate change impacts on hydrological processes in West Africa. [Abstract only]. Paper presented at the European Geosciences Union (EGU) General Assembly 2020, Online, 4-8 May 2020. 2p. [doi: https://doi.org/10.5194/egusphere-egu2020-9143]
Climate change ; Assessment ; Hydrology ; Models ; Calibration ; Multivariate analysis / West Africa
(Location: IWMI HQ Call no: e-copy only Record No: H050011)
https://meetingorganizer.copernicus.org/EGU2020/EGU2020-9143.html?pdf
https://vlibrary.iwmi.org/pdf/H050011.pdf
https://vlibrary.iwmi.org/pdf/H050011.pdf
(0.29 MB) (292 KB)
18 Ramilan, T.; Kumar, S.; Haileslassie, Amare; Craufurd, P.; Scrimgeour, F.; Kattarkandi, B.; Whitbread, A. 2022. Quantifying farm household resilience and the implications of livelihood heterogeneity in the semi-arid tropics of India. Agriculture, 12(4):466. [doi: https://doi.org/10.3390/agriculture12040466]
Households ; Resilience ; Livelihoods ; Strategies ; Semiarid climate ; Crops ; Irrigation ; Farmers ; Multivariate analysis / India / Telangana / Maharashtra
(Location: IWMI HQ Call no: e-copy only Record No: H051087)
https://www.mdpi.com/2077-0472/12/4/466/pdf?version=1648435207
https://vlibrary.iwmi.org/pdf/H051087.pdf
https://vlibrary.iwmi.org/pdf/H051087.pdf
(1.03 MB) (1.03 MB)
The vast majority of farmers in the drylands are resource-poor smallholders, whose livelihoods depend heavily on their farming systems. Therefore, increasing the resilience of these smallholders is vital for their prosperity. This study quantified household resilience and identified livelihoods and their influence on resilience in the semiarid tropics of India by analysing 684 households. A resilience capacity index was devised based on the composition of household food and non-food expenditure, cash savings, and food and feed reserves. The index ranged from 8.4 reflecting highly resilient households with access to irrigation characteristics, to -3.7 for households with highly limited resilience and low household assets. The livelihoods were identified through multivariate analysis on selected socioeconomic and biophysical variables; households were heterogeneous in their livelihoods. Irrigated livestock and rainfed marginal types had the highest and lowest resilience capacity index with the mean score of 0.69 and -1.07, respectively. Finally, we quantified the influence of livelihood strategies on household resilience. Household resilience was strengthened by the possession of livestock, crop diversification and access to irrigation. Low resilience is predominantly caused by low household assets. The resilience capacity index and derived livelihood strategies helps to understand the complexity of household resilience, and will aid in targeting technology interventions for development.
19 Msaki, G. L.; Njau, K. N.; Treydte, A. C.; Lyimo, T. 2022. Social knowledge, attitudes, and perceptions on wastewater treatment, technologies, and reuse in Tanzania. Water Reuse, 12(2):223-241. [doi: https://doi.org/10.2166/wrd.2022.096]
Wastewater treatment ; Water reuse ; Recycling ; Technology ; Social aspects ; Attitudes ; Health hazards ; Constructed wetlands ; Irrigation ; Water supply ; Economic activities ; Households ; Multivariate analysis / United Republic of Tanzania / Kilimanjaro / Arusha / Iringa / Dar es Salaam
(Location: IWMI HQ Call no: e-copy only Record No: H051259)
https://iwaponline.com/jwrd/article-pdf/12/2/223/1067484/jwrd0120223.pdf
https://vlibrary.iwmi.org/pdf/H051259.pdf
https://vlibrary.iwmi.org/pdf/H051259.pdf
(0.75 MB) (764 KB)
This study assessed the social knowledge, attitude, and perceptions (KAPs) on wastewater treatment, the technologies involved, and its reuse across different wastewater treatment areas in four regions of Tanzania. We used both quantitative and qualitative data collection methods in a household-level questionnaire (n=327) with structured and semi-structured questions, which involved face-to-face interviews and observation. Our results show that social KAPs surrounding wastewater treatment and reuse were sufficient based on KAP scores achieved from asked questions. However, the general knowledge on treatment technologies, processes, and reuse risks was still low. Of the respondents, over 50% approved using treated wastewater in various applications, while the majority (93%) were reluctant if the application involved direct contact with the water. Furthermore, over 90% of interviewees did not know the technologies used to treat wastewater and the potential health risks associated with its use (59%). Multivariate analysis of variance revealed significant differences (P<0.05) in the KAPs on treated wastewater across different studied demographic variables, i.e., age, sex, and education level. Therefore, we recommend that more effort be spent on providing public education about the potential of wastewater treatment and existing technologies in order to facilitate their adoption for the community's and environment's benefit.
20 Diro, S.; Tesfaye, A.; Erko, B. 2022. Determinants of adoption of climate-smart agricultural technologies and practices in the coffee-based farming system of Ethiopia. Agriculture and Food Security, 11:42. [doi: https://doi.org/10.1186/s40066-022-00385-2]
Climate-smart agriculture ; Technology ; Agricultural practices ; Farming systems ; Coffee ; Intercropping ; Minimum tillage ; Water management ; Water conservation ; Crop production ; Smallholders ; Farmers ; Forage ; Households ; Multivariate analysis ; Econometrics ; Models / Ethiopia / Oromia / Southern Nations, Nationalities, and Peoples' Region (SNNPR) / Gedeo / Sidama / Kafa / Sheka / Ilubabor / Jimma / West Wollega / Kellem Wollega
(Location: IWMI HQ Call no: e-copy only Record No: H051226)
https://agricultureandfoodsecurity.biomedcentral.com/track/pdf/10.1186/s40066-022-00385-2.pdf
https://vlibrary.iwmi.org/pdf/H051226.pdf
https://vlibrary.iwmi.org/pdf/H051226.pdf
(1.62 MB) (1.62 MB)
Objectives: This study explored the adoption status of different Climate Smart Agricultural (CSA) practices and factors that influence their adoption for sustainable soil resource utilization in the changing climate.
Methodology: We used quantitative and qualitative primary data collected from smallholder farmers and other stakeholders from major coffee-growing regions of Ethiopia: Oromia, and Southern Nations, Nationalities, and Peoples (SNNP). We used the multivariate probit (MVP) model to study factors that influence the adoption of climate-smart agricultural technologies, namely, manure application, minimum tillage, intercropping, use of improved forage, and physical soil and water management practices.
Results: The study result shows that 35% of farmers apply manure on their farm plots. Minimum tillage is also applied to 36% of farms. Intercropping improved forages and physical soil and water management structures are adopted by 45, 19, and 47% of farmers, respectively. The finding of the study indicates the positive and significant effect of education, extension (access to extension services and participation on field days), and ownership of communication devices specifically radio on the adoption of climate-smart agricultural practices.
Recommendations: Concerning bodies must pay due attention to problems affecting effective farmers-extension linkage. The positive effect of radio ownership on technology adoption also suggests the need for increased accessibility of FM radio channels to farmers to be aware of climate change and innovative agricultural technologies, practices, and information that mitigate the problem.
Methodology: We used quantitative and qualitative primary data collected from smallholder farmers and other stakeholders from major coffee-growing regions of Ethiopia: Oromia, and Southern Nations, Nationalities, and Peoples (SNNP). We used the multivariate probit (MVP) model to study factors that influence the adoption of climate-smart agricultural technologies, namely, manure application, minimum tillage, intercropping, use of improved forage, and physical soil and water management practices.
Results: The study result shows that 35% of farmers apply manure on their farm plots. Minimum tillage is also applied to 36% of farms. Intercropping improved forages and physical soil and water management structures are adopted by 45, 19, and 47% of farmers, respectively. The finding of the study indicates the positive and significant effect of education, extension (access to extension services and participation on field days), and ownership of communication devices specifically radio on the adoption of climate-smart agricultural practices.
Recommendations: Concerning bodies must pay due attention to problems affecting effective farmers-extension linkage. The positive effect of radio ownership on technology adoption also suggests the need for increased accessibility of FM radio channels to farmers to be aware of climate change and innovative agricultural technologies, practices, and information that mitigate the problem.
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