Exploring socio-hydrological determinants of crop yield in under-performing irrigation schemes: pathways for sustainable intensification

ABSTRACT

Understanding the human–water–food–climate nexus is central to achieving sustainable intensification (SI) in agriculture. This research uses a socio-hydrological approach to understand the underpinning for implementing SI in the Gezira Irrigation Scheme, Sudan, by integrating vegetation indices derived from remote sensing, ancillary, gridded soil and precipitation data, supplemented by interviews with 393 farmers. The productivity gap was estimated as the difference between the potential and actual productivities. Based upon data on farmers’ socio-economic status and field practices, a regression tree model was built to determine the factors that control the sorghum yield. The model revealed that the financial status of farmers and access to water are the most influential factors on sorghum yield. A conceptual framework that elucidates SI and its bi-directional feedback to the environment, society and the economy is proposed. Implementing SI in the scheme has implications on water and food security in Sudan and beyond its borders.     

Near‐infrared spectroscopy of a hydroecological indicator: new tool for determining sustainable yield for Floridan aquifer system

Pond‐cypress (Taxodium ascendens Brong.) is a dominant canopy species in depressional wetlands of the south‐eastern Coastal Plain. Unsustainable withdrawals from the karst Floridan aquifer system have caused premature decline and death of pond‐cypress trees, presumably owing to altered hydroperiods (which alter the flow of water and nutrients in trees). There has been no scientifically based means to determine sustainable yield from this regional aquifer system or to detect early stages of physical/ecological damage associated with groundwater mining and aquifer storage and recovery (ASR, which also can alter natural hydroperiods). In this study, the relationship between visual symptoms (indicators) of stress or premature decline, and spectral reflectance was evaluated using dried, milled branch tips collected from natural stands of mature pond‐cypress. Depressional systems evaluated represented four of the six aquifer system subregions where subsurface perturbations from groundwater mining: (i) were presumed not to be occurring (reference wetlands); (ii) may be occurring but are not documented; and (iii) have been confirmed. Sampled trees were assigned to one of three stress classes (1, no/minimal; 2, moderate; 3, severe) based on the visual indicators. Partial least squares–linear discriminant analysis of second derivative spectral transformations in the visible/shortwave near‐infrared (NIR) region (400–1100 nm) and the NIR region (1100–2500 nm) was used to evaluate the samples in assigned classes. Class 1 samples were discriminated from combined class 2 and 3 samples in the NIR region with 100% and 97% accuracy for consecutive winter sample periods (before bud‐break). The percentage of correctly classified samples in this spectral region was lower (85%) for summer samples (full leaf‐out). Second‐derivative models for the NIR region developed from the winter data sets predicted assigned classes for alternate winter's samples with an accuracy of 97% and 100%. High correlation between spectral reflectance of dried, milled branch tips collected from mature pond‐cypress in winter and visual indicators of premature decline suggests in situ pond‐cypress are hydroecological indicators of anthropogenic subsurface hydroperiod perturbations. This approach provides objective means for early detection of unsustainable aquifer yield and adverse impacts from ASR activities in the south‐eastern Coastal Plain. Used in conjunction with hydrological monitoring and modelling, the hydroecological indicators should provide the means with which sustainable yield in the south‐eastern Coastal Plain can be achieved and maintained. Copyright © 2003 John Wiley & Sons, Ltd.