Staged SWAT calibration with bias-corrected precipitation product for enhancing flow data continuity in tributaries of the Mekong River.

Accurate and continuous flow data are crucial for effective water management in large river basins worldwide. However, these catchments often face challenges regarding data continuity in the mainstream and their tributaries. This study proposes a methodological framework for enhancing flow data continuity that uses a staged calibration scheme of Soil and Water Assessment Tool (SWAT) modeling with an appropriate satellite precipitation product (SPP) for each watershed. This framework is successfully applied in the Mun-Chi River Basin, the largest tributary of the Lower Mekong River, over a 20-year period at 34 stations. The staged calibration involves partitioning the catchment into smaller sub-catchments, guided by the flow monitoring stations and flow discontinuity structures such as dams. The sequential calibration from upstream to downstream partitions the overall model calibration challenge into smaller problems and contributes to a more efficient and accurate calibration and validation. Alternative SPPs were considered to overcome monitoring gaps. Their bias was corrected using quantile mapping, and their performance was evaluated with flow simulations using the SWAT model. The assessment indicates that the CMORPH-CRT product, with a spatial resolution of 0.25°, demonstrates good suitability for hydrological modeling of the Mun-Chi River Basin. The proposed methodological framework provides a continuous time series of flow discharge at multiple stations within the watershed, offering valuable insights for sustainable water resource management strategies in river systems under changing climate and land use conditions, and supporting future studies on environmental issues.

Response of streamflow and nutrient loads in a small temperate catchment subject to land use change.

The aim of this study was to quantify the effect of land use change (LUC) implemented to meet nutrient load targets for a freshwater lake in New Zealand. We used the Soil and Water Assessment Tool (SWAT) model in combination with a non-parametric statistical test to determine whether afforestation of 15% of a subcatchment area was adequate to meet assigned nutrient load targets. A regional management authority set nutrient load targets of reduction in total nitrogen (TN) by 0.9 t yr-1 and reduction in total phosphorus (TP) by 0.05 t yr-1 to avoid eutrophication in the receiving waters of a freshwater lake. The load reduction was designed to be achieved through 200 ha of LUC from pasture to trees. Analysis of nutrient loads before, during, and following LUC shows that a 15% increase in forest cover decreased the annual flow (7.2%), TP load (33.3%), and TN load (13.1%). As flow and water quality observations were discrete and at irregular intervals, we used a parametric test and the SWAT model as different lines of evidence to demonstrate the effect of afforestation on flow and water quality. Policymakers concerned with decisions about LUC to improve the quality of receiving waters can benefit from applying our findings and using a statistical and numerical modelling framework to evaluate the adequacy of land use change to support improvements in water quality.

Optimal selection of daily satellite precipitation product based on structural similarity index at 1 km resolution for the Pra catchment, Ghana.

Thirteen satellite precipitation products (SPPs), re-gridded to 1 km resolution, were evaluated in terms of the structural similarity index (SSI) over the Pra catchment in Ghana. Three SPP scenarios were considered: Scenario one (S1) was the original SPPs; Scenario two (S2) was bias-corrected SPPs; and Scenario three (S3) was the better of S1 and S2 for each wet day. For each scenario, the best SPP was selected to constitute the 14th SPP referred to as the BEST SPP. Each SPP was evaluated in terms of SSI against the rain gauge rainfield for each wet day. For S1, the top three SPPs were TMPA, GSMAP and CMORPH; for S2, CMORPH, PERCCS and MSWEP were the top three; and for S3, CMORPH, PERCCS and TMPA came out on top in order of decreasing performance. Bias correction led to improvement in the overall SSI measure (SSIM) for 73% of wet days. The BEST SPP increased the SSIM of the best individual SPP by over 50% for S1, and over 30% for both S2 and S3. Comparing the BEST SPP of the three scenarios, S2 increased the SSIM statistic by 20% over that for S1, and SSIM was further improved by 4% for S3. It is highly recommended to use BEST SPP (S3) to generate the required 1 km × 1 km rainfields for the Pra, or other catchments around the world with a sparse rain gauge network, through conditional merging with rain gauge data as demonstrated.

Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution.

Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.

Global concurrent climate extremes exacerbated by anthropogenic climate change.

Increases in concurrent climate extremes in different parts of the world threaten the ecosystem and our society. However, spatial patterns of these extremes and their past and future changes remain unclear. Here, we develop a statistical framework to test for spatial dependence and show widespread dependence of temperature and precipitation extremes in observations and model simulations, with more frequent than expected concurrence of extremes around the world. Historical anthropogenic forcing has strengthened the concurrence of temperature extremes over 56% of 946 global paired regions, particularly in the tropics, but has not yet significantly affected concurrent precipitation extremes during 1901-2020. The future high-emissions pathway of SSP585 will substantially amplify the concurrence strength, intensity, and spatial extent for both temperature and precipitation extremes, especially over tropical and boreal regions, while the mitigation pathway of SSP126 can ameliorate the increase in concurrent climate extremes for these high-risk regions. Our findings will inform adaptation strategies to alleviate the impact of future climate extremes.

Individual and combined impacts of urbanization and climate change on catchment runoff in Southeast Queensland, Australia.

Assessing the impacts of climate change and land-use change is of critical importance, particularly for urbanized catchments. In this study, a novel framework was used to examine and quantify these impacts on the runoff in six catchments in Southeast Queensland, Australia. For each catchment, temporal variations in impervious areas were derived from six satellite images using a sub-pixel classification technique and incorporated into the SIMHYD hydrological model. This model was satisfactorily calibrated and validated with daily runoff observations (0.63 ≤ Nash-Sutcliffe efficiency coefficient ≤ 0.94, percent bias ≤ ±18 %) and was used to produce baseline runoff for 1986-2005 in these six catchments. The projected population increase was used to predict future imperviousness based on the linear relationship between the two. The projected rainfall and evapotranspiration were derived from the ensemble means of the eight general circulation models. Catchment runoff was projected under two climate change scenarios (RCP4.5 and 8.5), three urbanization scenarios (low, medium, and high), and six combined scenarios for two future periods (2026-2045 and 2046-2065). Comparing with the baseline, it was found that (1) climate change alone would lead to a -3.8 % to -17.6 % reduction in runoff among the six catchments, for all scenarios and both future periods; (2) a 11.8 % to 78 % increase in runoff was projected under the three urbanization scenarios, and (3) a decrease in runoff due to climate change would moderate the increase in runoff caused by urbanization. For example, the combined effect would be a 54 % increase in runoff, with a -17.2 % decrease due to climate change and 78 % increase due to urbanization. Overall, runoff in the six catchments may be significantly affected by urban expansion. From this study, decision makers could gain a better understanding of the relative importance of the effects of climate and land-use change, which can be applied when developing future long-term water management plans at the catchment scale.

Responses of macroinvertebrate assemblages to environmental variations in the river-oxbow lake system of the Zoige wetland (Bai River, Qinghai-Tibet Plateau).

The biodiversity value of river-oxbow lake systems in high plateau peatland has been little recognized, and there are many gaps in our understanding of their ecology. In this study, we investigated the river-oxbow lake system of the Bai River basin, the main tributary of the Yellow River Source in the Zoige wetland from 2015 to 2016, in attempt to show how the environmental variations, especially hydrological connectivity and macrophyte biomass in the river-oxbow lake system influenced macroinvertebrates. Habitat patches were investigated in 11 river cross-sections and 18 oxbow lakes in the Bai River basin. Through hierarchical clustering and non-metric multidimensional scaling, four main types of habitats were identified in the river-oxbow lake system in the plateau: sand-bed river, cobble-bed river, sparse-macrophyte oxbow lake, and luxuriant-macrophyte oxbow lake. The luxuriant-macrophyte oxbows were characterized by high dissolved oxygen concentrations, alkalinity, and higher macroinvertebrate richness, density, biomass, and the Improved Shannon-Wiener Index in comparison to the other habitat types. Additionally, influential patterns of environmental variables on macroinvertebrates were analyzed using redundancy analysis. Lasso regression models were established to describe how macroinvertebrate density responded to macrophyte biomass and other variables, and how macrophyte biomass responded to hydrological connectivity and oxbow size. It was revealed that reduced hydrological connectivity and reduced oxbow size played important roles in increasing the biomass of submerged macrophyte, and dense macrophyte was directly responsible for the high biodiversity of macroinvertebrates. Different from the commonly believed unimodal influential pattern that medium hydrological connectivity supports the highest biodiversity in oxbow lakes reported in previous studies, macroinvertebrates in the high plateau river-oxbow lake systems benefited from low connectivity and reduced size. Oxbow lakes, especially those covered with luxuriant macrophytes, diversified the macroinvertebrate assemblages and enhanced primary consumer biomass at the regional scale.

Influence of soil and water conservation measures on soil fertility in the Beijing mountain area.

Soil and water conservation (SWC) measures can be adopted to conserve soil and water and improve soil fertility. The degree to which SWC measures improve soil fertility is affected by the type of SWC measure, soil type, climate, etc. The purpose of this study was to study the effect of the main SWC measures implemented in the Beijing mountain area on soil fertility. Six runoff plots, including a fish pit (fallow) (FPF), fish pit (Platycladus orientalis L. Franco) (FPP), narrow terrace (fallow) (NTF), narrow terrace (Juglans regia L.) (NTJ), tree pan (Juglans regia L.) (TPJ), and fallow land (FL), were established to analyze the differences in soil fertility in the Beijing mountain area. Soil samples were collected in 2005 and 2015 from the six runoff plots. Soil particle size; soil total nitrogen (TN), total phosphorous (TP), total potassium (TK), alkali-hydrolysable nitrogen (Ah-N), available P (Av-P), and available K (Av-K); and soil organic matter (SOM) were measured. The soil integrated fertility index (IFI) was calculated. The results showed that the soil nutrient content and IFI significantly decreased from 2005 to 2015 in the FL plot and significantly increased in the five runoff plots with SWC measures. Compared to the other runoff plots with SWC measures, the FPP plot more significantly improved the soil nutrient content and IFI. The TN, Ah-N, Av-K, SOM, and IFI in the FPP plots increased by 98%, 113%, 61%, 69 and 47%, respectively, from 2005 to 2015. The IFI for the FPP, NTJ, and TPJ exceeded the average IFI of the farmland soil in the study region. The results indicated that the combination of engineering practices and vegetative measures effectively improved soil fertility. These results may be helpful for selecting SWC measures, land-use planning and monitoring and assessing soil fertility.

MINErosion 3: Using measurements on a tilting flume-rainfall simulator facility to predict erosion rates from post-mining landscapes in Central Queensland, Australia.

Open-cut coal mining in Queensland results in the formation of extensive saline overburden spoil-piles with steep slopes at the angle of repose (approximately 75% or 37o). These spoil-piles are generally found in multiple rows, several kilometers in length and heights of up to 50 or 60 m above the original landscape. They are highly dispersive and erodible. Legislation demands that these spoil piles be rehabilitated to minimize on-site and off-site discharges of sediment and salt into the surrounding environment. To achieve this, the steep slopes must be reduced, stabilized against erosion, covered with topsoil and re-vegetated. Key design criteria (slope gradient, slope length and vegetation cover) are required for the construction of post-mining landscapes that will result in acceptable erosion rates. A novel user-friendly hillslope computer model MINErosion 3.4 was developed that can accurately predict potential erosion rates from field scale hillslopes using parameters measured with a 3m laboratory tilting flume-rainfall simulator or using routinely measured soil physical and chemical properties. This model links MINErosion 2 with a novel consolidation and above ground vegetation cover factors, to the RUSLE and MUSLE equations to predict the mean annual and storm event erosion rates. The RUSLE-based prediction of the mean annual erosion rates allow minesites to derive the key design criteria of slope length, slope gradient and vegetation cover that would lead to acceptable erosion rates. The MUSLE-based prediction of storm event erosion rates will be useful as input into risk analysis of potential damage from erosion. MINErosion 3.4 was validated against erosion measured on 20 m field erosion plots established on post-mining landscapes at the Oakey Creek and Curragh coalmines, as well as on 120 and 70 m erosion plots on postmining landscapes at Kidston Gold Mine.

Global rainfall erosivity assessment based on high-temporal resolution rainfall records.

The exposure of the Earth's surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha-1 h-1 yr-1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.