The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilities than a simple grey box or black-box model. But complexity may not necessarily translate to better prediction accuracy or might be unfeasible in data scarce areas or when computer power is limited. Therefore, the shift of hydrological science towards the more process-based models needs to be justified. To answer this, the paper compares 2 hydrological models: (a) the simpler tank model; and (b) the more complex TOPMODEL. More precisely, the difference in performance between tank model as a lumped model and the TOPMODEL concept as a semi-distributed model in Atari River catchment, in Eastern Uganda was conducted. The objectives were: (1) To calibrate tank model and TOPMODEL; (2) To validate tank model and TOPMODEL; and (3) To compare the performance of tank model and TOPMODEL. During calibration, both models exhibited equifinality, with many parameter sets equally likely to make acceptable hydrological simulations. In calibration, the tank model and TOPMODEL performances were close in terms of ‘Nash-Sutcliffe efficiency’ and ‘RMSE-observations standard deviation ratio’ indices. However, during the validation period, TOPMODEL performed much better than tank model. Owing to TOPMODEL’s better performance during model validation, it was judged to be better suited for making runoff forecasts in Atari River catchment.

This paper reviews the consideration of the operation of agricultural water control structures (AWCSs) as sources of bundles of ecosystem services (ESs) and the subsequent design of payment for ecosystem service (PES) programs around these ESs. It is thought that PES schemes for AWCSs can complement irrigation service fees (ISFs) in funding the operation and maintenance of irrigation schemes. Case studies from Japan, the United States of America and Tanzania, representing a variety of socio-economic, geographic and climatic conditions, are discussed. In countries where the PES programs had legal backing, they showed evidence of sustainability and success. The measurement of marginal ESs flows from AWCSs proved to be one of the challenges to PES programs. There is a need to improve the measurement and modelling of hydro-meteorological and water quality parameters to ensure the transparency and success of the programs. In general, there was a realisation that ESs flow from irrigated agriculture, but there was no systematic design of PES programs around these ESs flows. An opportunity is seen to complement ISF through the design of PES programs around ES flows from the operation of AWCSs.

Climate change adaptation (CCA) is an emerging topic in recent years since global temperature is continuing to rise and posing threats to natural biodiversity and human life. Its diverse nature requires efforts from a broad range of sectors to cope or adjust. This review paper aims to systematically study the cross-sectoral approaches in CCA decision making and develop probable strengths and shortcomings of those approaches. Literatures concerned with Multi-Criteria Decision-Making Method, or Multi-Criteria Analysis (MCA) are reviewed since it is considered as a holistic approach to integrate multiple sectors and combine monetary and non-monetary terms prevailing in sectoral and regional aspects, mainly in agriculture and water resource management. The literatures were searched through Scopus and PRISMA method was adopted to systematically refine the published articles based on our criteria. Out of 383 articles discovered, 139 were related to CCA out of which, 33 articles which applied MCA as their methodological approach were shortlisted for the core study. The result showed that MCA is extensively used in CCA decision making, prioritizing options, and formulating adaptation strategies at local and regional scale and considered as a flexible, transparent, and effective method because of an active engagement of stakeholders and experts’ judgement. But its inability to address the underlying uncertainties of climate change scenario is one of the major drawbacks seen. Thus, many literatures suggest incorporating Sensitivity analysis, Dynamic Adaptive Pathways, Real Option Analysis, or Robust Decision-Making Analysis with MCA to overcome those deep uncertainties.