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The growing competition for finite land and water resources and the need to feed an ever-growing population require new techniques to monitor the performance of irrigation schemes and improve land and water productivity. Datasets from FAO's portal to monitor Water Productivity through Open access Remotely sensed derived data (WaPOR) are increasingly applied as a cost-effective means to support irrigation performance assessment and identify possible pathways for improvement. This study presents a framework that applies WaPOR data to assess irrigation performance indicators, including uniformity, equity, adequacy, and land and water productivity differentiated by irrigation method (furrow, sprinkler, and centre pivot) at the Xinavane sugarcane estate, Mozambique. The WaPOR data on water, land, and climate are in near-real time and spatially distributed, with the finest spatial resolution in the area of 100gm. The WaPOR data were first validated agronomically by examining the biomass response to water, and then the data were used to systematically analyse seasonal indicators for the period 2015 to 2018 on g1/48000gha. The WaPOR-based yield estimates were found to be comparable to the estate-measured yields with ±20g% difference, a root mean square error of 19±2.5gtgha-1 and a mean absolute error of 15±1.6gtgha-1. A climate normalization factor that enables the spatial and temporal comparison of performance indicators are applied. The assessment highlights that in Xinavane no single irrigation method performs the best across all performance indicators. Centre pivot compared to sprinkler and furrow irrigation shows higher adequacy, equity, and land productivity but lower water productivity. The three irrigation methods have excellent uniformity (g1/494g%) in the four seasons and acceptable adequacy for most periods of the season except in 2016, when a drought was observed. While this study is done for sugarcane in one irrigation scheme, the approach can be broadened t, Water Resources

The growing competition for finite land and water resources and the need to feed an ever-growing population require new techniques to monitor the performance of irrigation schemes and improve land and water productivity. Datasets from FAO's portal to monitor Water Productivity through Open access Remotely sensed derived data (WaPOR) are increasingly applied as a cost-effective means to support irrigation performance assessment and identify possible pathways for improvement. This study presents a framework that applies WaPOR data to assess irrigation performance indicators, including uniformity, equity, adequacy, and land and water productivity differentiated by irrigation method (furrow, sprinkler, and centre pivot) at the Xinavane sugarcane estate, Mozambique. The WaPOR data on water, land, and climate are in near-real time and spatially distributed, with the finest spatial resolution in the area of 100gm. The WaPOR data were first validated agronomically by examining the biomass response to water, and then the data were used to systematically analyse seasonal indicators for the period 2015 to 2018 on g1/48000gha. The WaPOR-based yield estimates were found to be comparable to the estate-measured yields with ±20g% difference, a root mean square error of 19±2.5gtgha-1 and a mean absolute error of 15±1.6gtgha-1. A climate normalization factor that enables the spatial and temporal comparison of performance indicators are applied. The assessment highlights that in Xinavane no single irrigation method performs the best across all performance indicators. Centre pivot compared to sprinkler and furrow irrigation shows higher adequacy, equity, and land productivity but lower water productivity. The three irrigation methods have excellent uniformity (g1/494g%) in the four seasons and acceptable adequacy for most periods of the season except in 2016, when a drought was observed. While this study is done for sugarcane in one irrigation scheme, the approach can be broadened to c

The concept of integrated water resource management (IWRM) attempts to integrate all elements of water resources. Different tools are developed to assist in developing sound IWRM plans. One such tool is multiobjective analysis using an integrated hydro-economic model (IHEM). However, IHEM mainly deals with the optimization of river flow (blue water) in a river basin. This paper linked a distributed model of green water (landscape water uses) in the upper catchment with mainly blue water uses in the lower catchment of the Pangani Basin. The results show that agricultural water use has the highest water productivity and competes with all other objective functions in the catchment. The generation of firm energy competes with the downstream ecosystem requirements. The integrated study shows that improving rainfed cropping through supplementary irrigation has comparable marginal water values to full-scale irrigation but are much higher compared with hydropower. However, hydropower has more benefits if used in conjunction with the environment. The methodological approach has increased the understanding of trade-offs between green and blue water uses that are highly interdependent in African landscapes., Water Resources

Land-use and land-cover changes are driving unprecedented changes in ecosystems and environmental processes at different scales. This study was aimed at identifying the potential land-use drivers in the Jedeb catchment of the Abbay basin by combining statistical analysis, field investigation and remote sensing. To do so, a land-use change model was calibrated and evaluated using the SITE (SImulation of Terrestrial Environment) modelling framework. SITE is cellular automata based multi-criteria decision analysis framework for simulating land-use conversion based on socio-economic and environmental factors. Past land-use trajectories (1986–2009) were evaluated using a reference Landsat-derived map (agreement of 84%). Results show that major land-use change drivers in the study area were population, slope, livestock and distances from various infrastructures (roads, markets and water). It was also found that farmers seem to increasingly prefer plantations of trees such as Eucalyptus by replacing croplands perhaps mainly due to declining crop yield, soil fertility and climate variability. Potential future trajectory of land-use change was also predicted under a business-as-usual scenario (2009–2025). Results show that agricultural land will continue to expand from 69.5% in 2009 to 77.5% in 2025 in the catchment albeit at a declining rate when compared with the period from 1986 to 2009. Plantation forest will also increase at a much higher rate, mainly at the expense of natural vegetation, agricultural land and grasslands. This study provides critical information to land-use planners and policy makers for a more effective and proactive management in this highland catchment., Water Resources