SP1 will focus on the supply of water-related NCPs in the second phase of Kili-SES. In addition, the project will assess transformation using human-water system trajectories to investigate the effect of climate change, land use and management on the future supply and demand of water-related NCP, with a particular focus on the potential for riparian forest restoration.

During the first phase , a soil moisture sensor network was established at 26 study plots, covering all 13 ecosystem types on Mt. Kilimanjaro. These data were used to analyse plot-scale hydrological processes related to infiltration and preferential flow. Six discharge gauging stations in three catchments complemented our monitoring effort. SP1 will build on the latter work to address its first objective, to assess the regulation of water supply along climate and land use gradients (Work package WP1). Using data from the sensor network, we will develop tailor-made hydrological models using the Catchment Model Framework to simulate water dynamics from plot to catchment scale. Our second objective aims to disentangle the role of the surrounding landscapes in regulating water quality as well as linking terrestrial and aquatic biodiversity with stream integrity (WP2). To achieve this, we will assess various water quality parameters, macroinvertebrate diversity and leaf litter breakdown rates at sites with undisturbed, degraded, absent, and restored riparian zones in targeted sampling campaigns. Landscape analysis using random forest regression models will be applied to predict spatial variations in water quality and aquatic biodiversity. The third objective investigates human-water system trajectories to study the future of water-related NCP. Using the hydrological models from WP1, the spatial water quality models from WP2 and results obtained in Kili-SES-1, WP3 will project the supply of water-related NCP under different scenarios of climate change, land use and management as well as human preferences and demand.

In summary, SP1 will provide crucial information on the current state and potential future of water-related NCP, which were underrepresented in previous research, but valued highly by many stakeholders in the social-ecological system, through a combination of high-resolution monitoring, sampling campaigns for water quality and aquatic biodiversity, and modelling approaches.

Photo: S. Jacobs

Climate and land use change have a significant impact on hydrobiogeochemical processes in the tropics. For tropical Africa in particular, however, scientific knowledge about the possible impacts of global change is limited. Nevertheless, this knowledge is essential for sustainable management of water resources. In this project, an established monitoring programme is being continued in four catchments with different land uses (tea and tree plantations, smallholder agriculture, natural montane rainforest) in the Mau Forest complex in western Kenya. Since 2014, automatic measuring systems have been recording almost gap-free in 10-minute resolution the water level (converted to discharge via rating curves) as well as the concentrations of NO ₃ , DOC and turbidity (converted to suspended sediments via rating curves) by means of UV spectrometry. In addition, the concentrations of stable isotopes of water are measured weekly. While the measuring systems were established in the first project phase and basic knowledge about the relationship between land use and water quantity/quality was gained, the second project phase aims at an improved understanding of the underlying hydrobiogeochemical process and a projection of water fluxes (quantity and quality) with regard to climate and land use change. Three work packages (WP) are planned for this purpose. In WP1, the measurement programme and the necessary maintenance measures will be carried out. At the end of the project, a 10-year data set of the above parameters will be made available open access. WP2 focuses on process identification by means of statistical methods and analyses of systematic temporal patterns (diurnal variations, seasonal influences) using wavelet functions. Automated analyses of hysteresis loops of concentration-discharge dynamics will help to identify transport and mobilisation processes of water and its solutes. In addition, the established concept of "hydrological signatures" will be transferred to develop "hydro-biogeochemical signatures". This will allow to comparatively characterise the hydrochemistry of streams and describe their hydro-biogeochemical process behaviour. In WP3, data-based models will be developed using Deep Learning to simulate both runoff and water quality parameters. The latest Long Short-Term Memory (LSTM) methods will be used, which also take into account spatial (land use) and temporal (climate time series) predictors. For model validation, the wavelets, hysteresis loops and hydro-biogeochemical signatures calculated in WP2 on the basis of field measurements will be compared with those calculated on the basis of the LSTM models. Finally, using the LSTM models with spatio-temporal predictors, projections of climate and land use change will be made. For this purpose, the latest CORDEX simulations of regional climate models and in-house developed land use scenarios based on multitemporal land use classifications will be used.

Photos: S. Jacobs

This project aims to build a portfolio of appropriate strategies to improve integration of crop and livestock production, and to promote endangered local cattle breeds in Benin. The overarching goals are to enhance the resilience of farming systems to climate change and detrimental environmental impact (soil and water), and to improve nutrition security and income for smallholders. A combination of diverse participatory research approaches including focus group discussions, on-farm monitoring and modeling, will be applied to analyze the current systems, and to identify key indicators for socio-economic and agro-ecological sustainability. Digital data storage platforms and community-based breeding programs will be developed for farmer training, information sharing and the design of suitable cattle selection schemes. The overall methodology focuses on the valorization of farmer’s perceptions and knowledge, by considering scientifically screened and evaluated environmental, agro-ecological and socio-economic impacts and trade-offs of crop-livestock integration. The expected outcomes are the co-creation of sustainable frameworks for enhancing circularity and efficient use of resources in crop-livestock farming systems, and of market opportunities for animal products from local breeds.