Hurst’s seminal characterisation of long-term persistence (LTP) in geophysical records more than seven decades ago continues to inspire investigations into the Hurst phenomenon, not just in hydrology and climatology, but in many other scientific fields. Here, we present a new theoretical development based on stochastic Hurst–Kolmogorov (HK) dynamics that explains the recent finding that the Hurst coefficient increases with the spatial scale of averaging for regional annual precipitation. We also present some further results on the scale dependence of H in regional precipitation, and reconcile an apparent inconsistency between sample results and theory. LTP in average basin scale precipitation is shown to be consistent with LTP in the annual flows of some large river basins. An analysis of the crossing properties of precipitation deficits in regions exhibiting LTP shows that the Hurst coefficient can be a parsimonious descriptor of the risk of severe precipitation deficits. No evidence is found for any systematic trend in precipitation deficits attributable to anthropogenic climate change across the regions analysed. Future precipitation deficit risk assessments should, in the first instance, be based on stochastic HK simulations that encompass the envelope of uncertainty synonymous with LTP, and not rely exclusively on GCM projections that may not properly capture long-term natural variability in the climate. Some views and opinions are expressed on the implications for policy making in sustainable water resources management.

The impact of stormwater drainage and detention ponds on flooding is assessed using statistical analysis and physically based computer simulation of a 45-year case study for a peri-urban catchment. In 1978, the 54 km² Ouseburn catchment in Newcastle upon Tyne was impacted by the connection of a new 2.1 km² residential development, directly to the Ouseburn River, via a stormwater drain, which reduced the time to peak and increased flood risk. Further residential developments of 1.6 km² have been built since 2004, again with separated sewer systems, but this time linked to stormwater detention ponds before draining into the Ouseburn River. Detailed analysis of the data, confirmed with computer simulation, shows that in contrast with the 1978 intervention, these new developments had only a minimal effect on the flows in the Ouseburn River, in fact achieving a small reduction in peak flows for large events. This study assesses the post-construction efficiency of such systems, and we show that the stormwater detention ponds are working as designed.

East Africa is highly vulnerable to climate change due to limited adaptive capacity and strong reliance on rain-fed agriculture. Ethiopia, in particular, experiences recurrent socio-economic losses from droughts and floods. This study presents a national-scale assessment of observed (1981–2010) and projected (2041–2100) changes in extreme seasonal precipitation across Ethiopia using ten ETCCDIs. High-resolution Enhancing National Climate Services (ENACTS) observations and bias-corrected outputs from a selected ensemble of CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios are used to assess historically trends and future extreme precipitation, respectively. Historical trends show increases in extreme precipitation during the Kiremt (JJAS) season, particularly over the northwestern, western, and southwestern highlands; however, most of these increases are not statistically significant. In contrast, the Belg (FMAM) season exhibits widespread declines, which are also largely not statistically significant. Future projections suggest increases in total precipitation (PRCPTOT), heavy (R10) and very heavy rainfall days (R20), very wet days (R95p) and extremely wet days (R95p), and rainfall intensity (SDII) over northwestern, western, southwestern, and parts of northeastern Ethiopia during JJAS. During FMAM, PRCPTOT is projected to increase in the northern and northwestern regions, while decreases are expected in the northeastern and southeastern regions. The Awash and Tekeze basins emerge as key hotspots of change, indicating potential seasonal shifts and an increased likelihood of extreme weather in these regions. Despite inter-model uncertainty, the results highlight the need for flexible, uncertainty-informed adaptation strategies to enhance climate resilience in Ethiopia.

Spatiotemporal climate variability is a leading environmental constraint to the rain-fed agricultural productivity and food security of communities in the Abbay basin and elsewhere in Ethiopia. The previous one-size-fits-all approach to soil and water management technology targeting did not effectively address climate-induced risks to rain-fed agriculture. This study, therefore, delineates homogenous climatic regions and identifies climate-induced risks to rain-fed agriculture that are important to guide decisions and the selection of site-specific technologies for green water management in the Abbay basin. The k-means spatial clustering method was employed to identify homogenous climatic regions in the study area, while the Elbow method was used to determine an optimal number of climate clusters. The k-means clustering used the Enhancing National Climate Services (ENACTS) daily rainfall, minimum and maximum temperatures, and other derived climate variables that include daily rainfall amount, length of growing period (LGP), rainfall onset and cessation dates, rainfall intensity, temperature, potential evapotranspiration (PET), soil moisture, and AsterDEM to define climate regions. Accordingly, 12 climate clusters or regions were identified and mapped for the basin. Clustering a given geographic region into homogenous climate classes is useful to accurately identify and target locally relevant green water management technologies to effectively address local-scale climate-induced risks. This study also provided a methodological framework that can be used in the other river basins of Ethiopia and, indeed, elsewhere.

Non-point sources of pollution (NPSPs) originating from runoff from contaminated agricultural and populated areas are becoming a growing concern in developing countries, endangering the environment and public health. This requires systematic investigation, including modelling the likely impact using an appropriate hydrological model. This study quantified the spatiotemporal variation of the NPSP and prioritised the most vulnerable sub-watersheds for intervention planning. We investigated the effects of land use and cover (LULC) conversion on runoff generation and NPSP loads in terms of sediment, phosphate, total nitrogen, total phosphorus, and nitrate loading using the SWAT model. The principal source of data utilised to assess the change in NPSP loads was the 2003 and 2023 LULC. The analysis of the results showed that grassland and shrubland substantially changed, with 96.7% and 74.4% reductions, respectively, while the increase in agricultural land was 147.3% and that of built-up areas increased by 80.14%. The mean yearly increase in sediment yield ranges from 25.46 to 27,298.75 t, while the mean yearly increase in surface runoff ranges from 183.1 mm to 487.9 mm. The minimum recorded runoff was 10.69 mm (5.1%) in WS03, while the highest was 123.3 mm (66.5%) in WS02. The NO₃⁻ load increased from 127.6 to 20,739.7 kg, and the PO₄³⁻ load increased from 3.12 to 2459.7 kg. The TN load increased from 4465.5 to 482,014.5 kg, and the TP load increased from 1383.5 to 133,641.3 kg. The monthly analysis of nitrate loading revealed that the “Belg” season has the highest nitrate load than the rainy season, probably due to nitrification. The findings clearly showed that the inputs applied to the farms were not effectively utilised for the intended purpose. Hence, efforts must be made to ensure that nutrients remain in the catchment through an appropriate land management intervention.