A high-resolution global SWATplus water quality model: Harmonizing local and global perspectives

Surface water pollution has emerged as one of the predominant environmental challenges of this century, as human activities and climate change considerably alter the natural quality of freshwater ecosystems. However, gauging the true extent of how polluted or impacted freshwaters are remains challenging globally simply due to limited spatial and temporal water quality observations. To address this gap, we present a high-resolution global water quality model utilizing the Soil Water and Assessment Tool (SWAT+). Our objectives are twofold: (1) to offer locally relevant water quality estimates on a global scale and (2) to understand how human activities and climate change are influencing the water quality of rivers on the globally. In this study, we examine future spatial patterns and temporal trends in river nutrients (Total Nitrogen – TN and Total Phosphorus – TP) and sediment load concentrations until 2100, considering changing climate and socioeconomic conditions. Additionally, we attribute the primary contributing drivers to nutrient water pollution, shedding light on the key factors shaping the future of global water quality

Can Turbidity Data from Remote Sensing Explain Modelled Spatial and Temporal Sediment Loading Patterns? An Application in the Lake Tana Basin

Understanding the spatial and temporal patterns of sediment loading in water bodies is crucial for effective water quality management. Remote sensing (RS) has emerged as a valuable and reliable tool for monitoring turbidity, which can provide insights into sediment dynamics in water bodies. In this study, we investigate the potential of turbidity data derived from RS to explain simulated spatial and temporal sediment loading patterns in the Lake Tana basin, Ethiopia. Utilizing existing RS lake turbidity data from Copernicus Global Land Service (CGLS) and simulated seasonal and multiyear trends of river sediment loadings into Lake Tana from the Soil and Water Assessment Tool (SWAT + model), we estimate correlations at different river inlets into Lake Tana. The results reveal a strong positive correlation (R2 > 0.66) between the multiyear monthly average sediment load from inflow rivers and RS lake turbidity at most river inlets. This indicates that the simulated river sediment loads and lake turbidity at river inlets exhibit similar seasonal patterns. Notably, higher turbidity levels are observed at the river inlet with the highest sediment load export. These findings highlight the potential of RS turbidity products in characterizing temporal and spatial patterns of sediment loadings, particularly in data-scarce regions, contributing to a better understanding of water quality dynamics in such areas

One third of African rivers fail to meet the ’good ambient water quality’ nutrient targets

The ambition of Sustainable Development Goal (SDG) target 6.3 is to improve global water quality by 2030. SDG indicator 6.3.2 monitors progress towards this target by assessing water bodies against ‘good’ ambient water quality criteria, with nutrients (nitrogen and phosphorus) as part of the key metrics. However, large data gaps present a fundamental challenge, especially for Africa on how to assess the progress being made with respect to both the current and desired future situations. Here, a continental water quality model for Africa is presented to simulate river sediment load, Total Nitrogen (TN) and Total Phosphorus (TP) loads and concentrations. Furthermore, critical areas and hotspots of TN and TP pollution are mapped for the period 2017 – 2019, in relation to the United Nations Environment Programme (UNEP) target thresholds used for the assessment of SDG indicator 6.3.2. Utilizing the UNEP’s criteria, which designates a water body as having “good ambient water quality” if 80% or more of its monitored values meet their targets, it is estimated that 44 % and 15 % of African rivers fail to meet the set water quality thresholds for simulated TP and TN, respectively. When synthesizing data for both TP and TN, 34 % of the rivers do not qualify as having “good ambient water quality”. Geographically, the most pronounced nutrient pollution hotspots were in North Africa, Niger River Delta, Nile River basin, Congo River basin and specific zones in Southern Africa. These areas correlate with regions characterized by high inputs of fertilizers, manure and wastewater discharge

Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models

Participatory water resource management requires modeling techniques that are accurate and flexible yet stakeholder-friendly. While different modeling frameworks offer advantages and disadvantages, system dynamics (SDs) models have seen sustained use as a stakeholder-friendly approach for participatory water resource modeling. Physically based models (e.g., SWAT+) have seen sustained use to model the hydrological components of water systems. Proposed as a way to combine the relative strengths of both modeling paradigms, model coupling allows researchers to, for example, build participatory SD models with stakeholders, while delegating the hydrological components of the overall model to an external hydrological model. Recently developed to facilitate model coupling, the Tinamït Python package presents an extensible, outward-facing application programming interface (API). It allows for the development of extensions (wrappers) that expand compatibility with different physically based models. However, no watershed hydrological model has yet been connected to this API. In the present study, a socket and JavaScript Object Notation (JSON)-based communication protocol was developed with the goal of facilitating the coupling of models written in languages such as Fortran. This novel protocol served to develop a Tinamït-compatible wrapper for the hydrological model SWAT+, allowing it to be coupled to human–water SD models. The novel coupling protocol was then applied to a case study of Tanzania's Usa river catchment. This approach provides the modeler with the benefits of both physically based and SD models, thereby allowing the detection of potentially far-reaching effects of policy-makers' decisions.</p

Impacts of climate change and vegetation response on future aridity in a Mediterranean catchment

The climate in the Mediterranean region is expected to become warmer and drier but future projections of precipitation are uncertain, especially in the Northern part. Additionally, the difficulty in determining the plant physiological responses caused by CO2 rising complicates the estimation of future evaporative demand, increasing the uncertainty of future aridity assessments. Vegetation responses to rising CO2 are expected to increase radiation use efficiency and reduce stomatal conductance, hence increasing plant's water use efficiency. These effects are often neglected when estimating future drought and aridity. Hence, the main objective of this study is to estimate the effect of climate change and vegetation stomatal conductance reduction on projected water balance components and the resulting impact on aridity in a medium-sized catchment of Central Italy. We validate and couple a hydrological model with climate projections from five regional climate models and perform simulations considering the vegetation responses or not. Results show that their inclusion significantly affects potential evapotranspiration. The other water balance components, namely actual evapotranspiration, water yield, percolation, and irrigation, are also influenced but with less significant changes. Considering or not the CO2 suppression effect on stomatal conductance, coupled with the uncertainty related to precipitation, highly affects the estimation of future aridity as the future climate classification ranges from “humid” to “semi-arid” depending on the simulation and climate model, even if model outputs need to be evaluated cautiously with CO2 concentration higher than 660 ppm

The IAHS Science for Solutions decade, with Hydrology Engaging Local People IN one Global world (HELPING)

The new scientific decade (2023-2032) of the International Association of Hydrological Sciences (IAHS) aims at searching for sustainable solutions to undesired water conditions – whether it be too little, too much or too polluted. Many of the current issues originate from global change, while solutions to problems must embrace local understanding and context. The decade will explore the current water crises by searching for actionable knowledge within three themes: global and local interactions, sustainable solutions and innovative cross-cutting methods. We capitalise on previous IAHS Scientific Decades shaping a trilogy; from Hydrological Predictions (PUB) to Change and Interdisciplinarity (Panta Rhei) to Solutions (HELPING). The vision is to solve fundamental water-related environmental and societal problems by engaging with other disciplines and local stakeholders. The decade endorses mutual learning and co-creation to progress towards UN sustainable development goals. Hence, HELPING is a vehicle for putting science in action, driven by scientists working on local hydrology in coordination with local, regional, and global processes

Can the cropping systems of the Nile basin be adapted to climate change?

Climate change poses a fundamental threat to agriculture within the Nile basin due to the magnitude of projected impacts and low adaptive capacity. So far, climate change impacts on agriculture for the basin have mostly been assessed for single-cropping systems, which may bias the results considering that the basin is dominated by different cropping systems, with about one-third of the crop area under double cropping. In this study, we simulate single- and double-cropping systems in the Nile basin and assess the climate change impacts on different cropping systems under two scenarios, i.e. “no adaptation” and “adaptation to a late-maturing cultivar”. We find that the mean crop yields of maize, soybean and wheat decrease with future warming without cultivar adaptation. We attribute this to the shortening of the growing season due to increased temperature. The decrease is stronger in all single-cropping systems (12.6–45.5%) than in double-cropping systems (5.9–26.6%). The relative magnitude of yield reduction varies spatially with the greatest reduction in the northern part of the basin experiencing the strongest warming. In a scenario with cultivar adaptation, mean crop yields show a stronger increase in double-cropping systems (14.4–35.2%) than single-cropping systems (8.3–13.7%). In this scenario, farmers could possibly benefit from increasing cropping intensities while adapting to late-maturing cultivars. This study underscores the importance of accounting for multiple-cropping systems in agricultural assessments under climate change within the Nile basin

Regionalization of the SWAT+ model for projecting climate change impacts on sediment yield: An application in the Nile basin

Study region Nile basin. Study focus Several studies have shown a relationship between climate change and changes in sediment yield. However, there are limited modeling applications that study this relationship at regional scales mainly due to data availability and computational cost. This study proposes a methodological framework using the SWAT+ model to predict and project sediment yield at a regional scale in data-scarce regions using global datasets. We implement a framework that (a) incorporates topographic factors from high/medium resolution DEMs (b) incorporates crop phenology data (c) introduces an areal threshold to linearize sediment yield in large model units and (d) apply a hydrological mass balance calibration. We test this methodology in the Nile Basin using a model application with (revised) and without (default) the framework under historical and future climate projections. New hydrological insights for the region Results show improved sediment yield estimates in the revised model, both in absolute values and spatial distribution when compared to measured and reported estimates. The contemporary long term (1989 – 2019) annual mean sediment yield in the revised model was 1.79 t ha−1 yr−1 and projected to increase by 61 % (44 % more than the default estimates) in the future period (2071 – 2100), with the greatest sediment yield increase in the eastern part of the basin. Thus, the proposed framework improves and influences modeled and predicted sediment yield respectively