Semi-arid Agricultural Water Management Challenges (SAWMAC): Mitigation by GIS
Increasing demand for water and the scarce supply of water is a growing concern in semiarid regions of the world. These regions lose a tremendous amount of water to evapotranspiration. As a result, soil water for optimal agricultural productivity is a major limitation. Characterization of aridity patterns aids in seeking affordable techniques to mitigate this constraint. However, conventional field methods are costly and laborious when considered on a regional basis hence the need for GIS techniques to bridge this gap and adequately overcome both labor and spatial limitations. This annotated bibliography therefore seeks to find studies that use GIS as a tool to solve the water problem in semi-arid settings.
Ayala, R; Becerra, A; Iribarne, L.F; Bosch, A; Díaz, J.R. GIS System as a Decision Support Tool for Agricultural Planning in Arid Zones of Spain.[PDF]
This study assessed an arid region in Spain. The study developed a decision support system for agricultural planning using four pivotal areas which included: (a) Information preparation, (b) Data integration, (c) Construction of GIS tool (d) Exploitation of the information stored at the national level. With this decision support tool, they were able to determine the zones with least agricultural resources, identify optimum areas for the development of intensive agriculture and determination of fire danger areas. However, the study did not explicitly state the methodology employed in arriving at this decision support tool at the national level.Nasir Mahmood Khan and Yohei Sato. Land degradation due to hydro-salinity in semi-arid regions Using GIS and Remote Sensing.[ARTICLE]
The study described an attempt to monitor land and water management scenarios that caused deterioration of vast productive land, using satellite data. Digitally acquired data was analyzed along with other field data sets and topographical maps. The study found that Normalized Difference Vegetation Index (NDVI) tended to be lower along drainage and higher along the irrigation canals which was attributed to the inequity water distribution and locational disadvantage of the down-stream farmers. The extent of waterlogged soils was also estimated through GIS analysis from more than 150 peizometers locations lying within the study area. The study presented evidence that the reuse of poor quality water to supplement irrigation supplies by the downstream farmers and the failure of a few drainage pumps are likely to disturb the water balance resulting into increased risk of waterlogging and salinity in the area.Abu Syed, Abdulali Mohammed, Sadiq Abdulla. Assessing desert vegetation cover using remotely sensed data: A case study from the state of Qatar.[PDF]
This study presented vegetation estimation in arid Qatar using satellite imagery. Although remote sensing technology had been in use in this region since 1983, none of them went beyond georeferencing and map production from rectified images with no classification. Hence this dent of knowledge regarding vegetation cover in Qatar was the motivation of this study. This study estimated desert vegetation using both remote sensing and GIS and revealed that optical remote sensing techniques could effectively be used to assess desert vegetation in Qatar and map them accordingly with a reliable accuracy of ~71 %. Radar images did not yield encouraging results which was attributed to sparse dwarf vegetation.Jonas Ardo and Lennart Olssonw. Assessment of soil organic carbon in semi-arid Sudan using GIS and the CENTURY model. Journal of Arid Environments (2003) 54: 633–651.
This study describes the use of GIS and CENTURY model to estimate soil organic carbon (SOC) changes during the period 1900–2100. They used a spatially explicit database of climate, land cover and soil texture which was compiled for a 262,000km2 region in semi-arid Sudan. This database was integrated with the CENTURY ecosystem model, and these workers were able to estimate historical, current and future pools of SOC as a function of land management and climate. I found this as a valuable study to assess soil carbon changes in vulnerable ecosystems.Oumarou Badini and Lassana Dioni. Application of Rainfall Analysis, Biophysical Modeling and GIS to Agroclimatic Decision Support In Madiama Commune, Mali (West Africa). SANREM CRSP Research Scientific Synthesis Conference, November 28-30, 2001, Athens, GA.
The authors of this article combined GIS and biophysical simulation modeling of soil water balance and crop production functions to assess the agro-climatic performances of a 90-day millet cultivars in semi-arid Madiama, Mali. The authors present knowledge from the analysis of historical rainfall records and predictive information based on the “response farming”. From the analysis of rainfall records, good relationships were found between rain onset dates and seasonal rain amounts and duration. Also, the Cropping System Simulation Model (CropSyst) was used in combination with the weather analysis and was a useful tool in aiding determination of soil suitability of crops, screen technologies and building of recommendation packages for a response farming type approach.L. L. Tieszen, G. G. Tappan and A. Touré. Sequestration of carbon in soil organic matter in Senegal: an overview . Journal of Arid Environments, 59 (3) pp. 409-425.
This study addressed the potential role developing countries in semi-arid areas can play in climate mitigation activities. It further emphasized that multiple benefits to smallholders could accrue as a result of management practices to re-establish soil carbon content lost because of land use changes or management practices that are not sustainable. This study was found to be pertinent to the region it was conducted because the Sahel is highly vulnerable to climate change yet it has impoverished rural societies.M. E. Budde, G. Tappan, J. Rowland, J. Lewis and L. L. Tieszen. Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis. Journal of Arid Environments, 59 (3) pp. 481-498.
The authors of this study report local variance analysis as a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992–93, 1995) and SPOT Vegetation (1998–2001) sensors. They then used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. Thereafter, they summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analyzed using Landsat TM imagery and extensive ground knowledge to assess the results. The study reports that this technique identified anomalies which can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow.Jeremy L. Weiss, David S. Gutzler, Julia E. Allred Coonrod and Clifford N. Dahm. Long-term vegetation monitoring with NDVI in a diverse semi-arid setting, central New Mexico, USA. Journal of Arid Environments Volume 58, (2) pp. 249-272.
In this article, authors describe a time-series of normalized difference vegetation index (NDVI) which they used to capture essential features of seasonal and inter-annual vegetation variability in vegetation communities in semi-arid New Mexico, USA. NDVI values tended to follow a uniform order across communities and essentially related directly to local vegetation. All communities exhibited a bimodal growing season on average, with peaks in springtime and summer. NDVI fluctuations were more spatially uniform in spring than in summer. The variability in observed NDVI corresponded to precipitation variability from the North American monsoon and El Niño-Southern Oscillation, and showed agreement with regional ground measurements. I found this exciting that observations from satellite imagery were in close agreement to ground data. Overall thought: An analysis and understanding of the intimate relationships between the weather, soils and agricultural production systems in semi-arid lands is essential. Of specific importance are the complexities associated with the variability, distribution of rainfall and soil type all of which are essential elements in improving crop production, agricultural planning and decision making in fragile and vulnerable regions. GIS can form a vital component in providing the desired solution! Related Links GIS-Information development in Africa.[PDF] GIS-Arid Zone Management. [PDF]