Key Hydrological Processes Research Articles

Nature-based solutions for effective flood mitigation: potential design criteria

Few studies attempt to measure changes to discharge hydrographs during floods resulting from nature-based Solutions (NbS) for risk mitigation. The Q-NFM project in the UK has sought to measure and compare such changes for a wide range of NbS pilots applied to managed grasslands and woodlands. Also measured were underlying shifts in key hydrological processes leading to flood hydrograph changes of enhanced evaporation, hillslope-, channel- and floodplain-storage, and infiltration. How well particular NbS pilots changed these processes to reduce flood hydrographs was found to depend on the attributes of the NbS features and scheme. This learning is presented for the first time to highlight, with supporting evidence, seven potential criteria to help practitioners of flood risk management to improve existing and future designs of NbS for more effective flood mitigation within temperate grassland and woodland environments.

Aboveground biomass determines canopy rainfall interception loss in Semiarid Grassland Communities

AbstractCanopy rainfall interception is one key hydrological process, affecting rainwater redistribution and effectiveness in semiarid regions. Canopy rainfall interception loss is jointly influenced by meteorology, vegetation and topography. The canopy water storage capacity (S), rainfall interception depth (Im) and ratio (I%) and vegetation characteristics, together with topographic factors of three grassland communities (dominated by Bothriochloa ischaemum, Lespedeza davurica and Artemisia gmelinii, respectively) were investigated on the Loess Plateau of China during the main growing season (June to September). Results showed that Im ranged from 0.55 to 0.89 mm and I% ranged from 6.14% to 12.1%, with the maximum values occurring in August for three communities, and A. gmelinii community had the largest Im (0.89 mm) and I% (12.1%). The Im and I% were positively correlated with aboveground biomass (AGB), coverage (Cov), leaf area index (LAI), community‐weighted mean height (CWMH) and altitude (Alt), but negatively correlated with slope degree and rainfall intensity (RI). Hierarchical partitioning analysis (HPA) showed that AGB had the highest contribution for Im (20.3%), while Alt had the highest contribution for I% (18.2%). The regression models based on forward selection could effectively predict the values of Im (R2 = 0.802, RMSE = 0.049) and I% (R2 = 0.546, RMSE = 1.434). Topographic factors (altitude, slope degree and aspect) indirectly influenced both Im and I% by modulating vegetation characteristics (AGB, Cov, etc.). All these indicated that aboveground biomass mainly determines grassland community rainfall interception loss in the semiarid Loess Plateau.

Modelling impacts of climate change on snow drought, groundwater drought, and their feedback mechanism in a snow-dominated watershed in western Canada

Snow accumulation and its melt are key hydrological processes in cold watersheds, which can affect groundwater (GW). With climate change projected to alter snow processes in these regions, understanding their impacts on the development of droughts is vital. A deficit in snow precipitation or accelerated snowmelt due to warming can trigger snow drought, potentially leading to GW drought. To investigate this relationship at a watershed scale, we coupled the Soil and Water Assessment Tool (SWAT) and MODFLOW to simulate various surface and groundwater processes under historical (1980–2013) and future (2040–2073) warming scenarios in western Canada. We calibrated, validated, and verified our models using streamflow, GW heads, and snow depth data from multiple hydrometric stations, observation wells, and a grid product. Using simulated data, we analyzed snow and GW drought characteristics, their dominant physical processes, and GW response time across eco-hydro(geo)logical regions like Mountains, Foothills, and Plains. Historical data show that Mountains are experiencing more snow droughts while Plains are facing greater GW droughts. However, future scenarios suggest increased snow droughts in all regions and a shift towards more severe GW droughts in Plains. Historical response time of GW to changes in snow processes spans 4–6 months from Mountains to Plains, with projected reductions in Mountains and Foothills, and a slight increase in Plains in the future. The dominant physical processes controlling GW response across all regions are soil moisture and percolation, with curve number displaying more significance in Mountains, and water yield exerts more control in Foothills and Plains. During cold seasons, SWE and snowmelt had minimal impact on GW response in Plains, while they presented a major role in Mountains. This study lays the basis for further research on snow-groundwater interactions in cold watersheds, aiding water resource management in mid-to-high latitude regions and providing a unified framework for analyzing snow and GW drought relationships.

Deep Learning Integrating Scale Conversion and Pedo‐Transfer Function to Avoid Potential Errors in Cross‐Scale Transfer

AbstractPedo‐transfer functions (PTFs) relate soil/landscape static properties to a wide range of model inputs (e.g., soil hydraulic parameters) that are essential to soil hydrological modeling. Combining PTFs and hydrological models is a powerful strategy allowing the use of soil/landscape static properties for the generalization of large‐scale modeling. However, since the spatial scales of soil hydraulic parameters required for model inputs and soil/landscape static properties are often not identical, cross‐scale transfer is required, which can be a significant source of errors. Here, we investigate uncertainties in cross‐scale transfer and develop an approach that avoids them. The proposed method uses the convolutional neural network (CNN) as a cross‐scale transfer approach to directly map soil/landscape static properties to soil hydraulic parameters across different spatial scales. The proposed CNN approach is applied under two different estimation strategies to invert the hydraulic parameters of a soil‐water balance model and subsequently the quality of the parameters is assessed. Both synthetical and real‐world results around the conterminous United States indicate that in general the employed end‐to‐end strategy is superior to the two‐step strategy. The CNN‐based integrated model successfully reduces potential errors in cross‐scale transfer and can be applied to other areas lacking information on hydraulic parameters or observations. The proposed method can be extended to improve parameter estimation in earth system models and enhance our understanding of key hydrological processes.

Effect of vegetation treatment and water stress on evapotranspiration in bioretention systems

Evapotranspiration is a key hydrological process for reducing stormwater runoff in bioretention systems, regardless of their physical configuration. Understanding the volumes of stormwater that can be returned to the atmosphere via evapotranspiration is, therefore, a key consideration in the design of any bioretention system. This study establishes the evapotranspiration dynamics of three common, structurally different, bioretention vegetation treatments (an Amenity Grass mix, and mono-cultures of Deschampsia cespitosa and Iris sibirica) compared with an un-vegetated control using lab-scale column experiments. Via continuous mass and moisture loss data, observed evapotranspiration rates were compared with those predicted by the FAO-56 Penman–Monteith model for five 14-day dry periods during Spring 2021, Summer 2021, and Spring 2022. Soil moisture reductions over the 14-day trials led to reduced rates of evapotranspiration. This necessitated the use of a soil moisture extraction function alongside a crop coefficient to represent actual evapotranspiration from FAO-56 Penman–Monteith reference evapotranspiration estimates. Crop coefficients (Kc) varied between 0.65 and 2.91, with a value of 1.0 identified as a recommended default value in the absence of treatment-specific empirical data. A continuous hydrological model with Kc=1.0 and a loading ratio of 10:1 showed that evapotranspiration could account for between 1 and 12% of the annual water budget for a bioretention system located in the UK and Ireland, increasing to a maximum of 35% when using the highest Kc observed (2.91).

Simulation of Hydrological Processes in the Jing River Basin Based on the WEP Model

Inappropriate vegetation reconstruction in the Loess Plateau region has led to a significant increase in regional evapotranspiration and water consumption, further aggravating the shortage of soil water resources in the Loess Plateau region. The Jing River basin is a typical area for vegetation reconstruction in the Loess Plateau region. A thorough understanding of changes in hydrological processes in the Jing River basin is of significant scientific importance for efficient utilization of soil water resources and sustainable vegetation restoration in the region. In this study, the physically based Water and Energy Transfer Processes (WEP) distributed hydrological model was used to simulate key hydrological processes in the Jing River Basin during different periods before and after the implementation of cropland conversion to forest and grassland from 1980 to 2019. The results showed that after the implementation of cropland conversion to forest and grassland from 2000 to 2019, the average runoff volume in the Jing River Basin decreased by 20.91%. The most significant decrease in average runoff occurred in the central and northern parts of the basin, with a maximum reduction of 48.6%. The decrease in runoff in flood season is more obvious. The peak discharge decreased by 24.91%, and the most significant decrease occurred in the northern and central parts of the basin, ranging from 10.3% to 50.2%. The spatial distribution pattern of average soil moisture in the 0–0.8 m soil layer showed more moisture in the south and less in the north, with the minimum value occurring in certain areas in the eastern part of the basin. Overall, the implementation of cropland conversion to forest and grassland led to a certain degree of decrease in soil moisture in the basin. After the implementation of cropland conversion to forest and grassland, reference evapotranspiration fluctuated only in specific areas of the basin with no significant overall change.

JAMES BUTTLE REVIEW: A resilience framework for physical hydrology

AbstractHydrological systems across the globe are increasingly subjected to pressures from a warming climate and anthropogenic disturbance. Responses to stress can be nonlinear and variable; therefore, it is imperative to improve understanding of resilience and tipping points of these systems. Previous applications of resilience concepts to physical hydrology have been disconnected, and an increasing range of definitions and approaches has often led to improper applications. Here, upon synthesizing relevant literature, we define physical hydrological resilience as the ability of a watershed to maintain hydrological function while exposed to a stressor or perturbation, thus remaining within the same regime. From this definition a new framework for physical hydrological resilience is forwarded which includes four key traits that must be part of a robust application of resilience for physical hydrology. Any evaluation of resilience should (1) identify and justify a baseline regime; (2) evaluate hydrological function, one or more of collection, storage and release; (3); assess physical hydrological systems for both resistance and latitude and (4) evaluate important perturbations and processes and how they interact to manifest into resistance, latitude, and tipping points. The framework is applied to the example of the Elbow River in Alberta, Canada, using baseline (1979–2015) and future (2050–2080) conditions. Two key hydrological processes, snow accumulation and streamflow, are found to have low resistance to winter duration and late spring precipitation, respectively. The collection function is resilient to a warmer, wetter climate due to a large latitude in relation to air temperatures, while the release function is not resilient, shifting from a streamflow‐ towards an evapotranspiration‐dominated regime in the future. The successful application of the concepts of resilience to this complex catchment demonstrates how the framework could be applied across a diversity of catchments. Results of resilience studies can improve environmental monitoring and evaluation programs and complement social‐ecological resilience frameworks and water management strategies.

Balanced Functional Herbivore Composition Stabilizes Tree-Grass Coexistence and Productivity in a Simulated Savanna Rangeland Ecosystem

Savanna ecosystems provide resources supporting the livelihoods of millions of people globally. Ongoing exploitation through high livestock densities, among other factors, however, threatens these ecosystems. Shrub encroachment, a consequence of this exploitation, causes severe declines in fodder biomass for cattle. For example, in Namibia, this leads to losses of land productivity of up to 100%. Consequently, we must rethink land-use options to ensure sustainable utilization of savanna resources. In southern Africa, many landowners and custodians have switched to or included wildlife in their management systems, making it an excellent model region to study how changing herbivory affects ecosystems. The diversity of indigenous wildlife species is expected to promote efficient herbaceous layer utilization with browsing herbivores counteracting nondesirable woody plant encroachment. Nevertheless, surprisingly little research has been conducted on the ecological consequences of altering grazer-to-browser ratios.We developed a large-scale spatially explicit dynamic vegetation model including key hydrological and ecological processes, fire, and an herbivore algorithm that accounts for aggregated animal herds in a heterogeneous savanna landscape. We find that different ratios of wild herbivore feeding types greatly influence vegetation composition and dynamics. By dynamically computing plant biomass as a resource, our model estimates the occurrence of fodder biomass shortages, providing a valuable tool for land users. The model also reports the number of patches with low to medium tree functional cover (10–25%), indicating structural diversity with its implications for species richness, and is thus essential for nature conservation. We find that a herbivore species composition of approximately 40% browsers and 60% grazers is beneficial for plant structural and species diversity. Theoretically, therefore, the browse-graze ratio achieved through wildlife-based land-use can lead to more sustainability and resilience. The interplay between diverse herbivory, vegetation, rain, and fire complicates but also stabilizes the savanna rangeland ecosystem and may contribute to its long-term persistence.

Understanding the Silala River—Scientific insights from the dispute over the status and use of the waters of the Silala (Chile v. Bolivia)

AbstractThe flows of surface water and groundwater from the Andes to the Atacama Desert are a vital source of freshwater, supporting ecosystems and human activities, but few substantive studies have addressed the hydrological and hydrogeological functioning of these systems. A dispute between Chile and Bolivia concerning the transboundary Silala River, recently heard before the International Court of Justice, The Hague, provided a unique opportunity for new scientific studies, reviewed in this Special Issue. First, findings from field studies that address the geological and geomorphological evolution of the Silala River basin and its current status, the key hydrological processes (including infiltration, actual evaporation from wetlands and alluvial plains, and surface water‐groundwater interactions), and the hydrogeological characterization of the major aquifers are reviewed. The dispute arose because Bolivia disagreed that the Silala was a transboundary river, subject to international law. As the Court proceedings evolved, this was accepted by Bolivia, but effects on surface flows of historical channelization in the Bolivian headwater wetlands remained a point of legal and technical disagreement. Bolivia asserted large increases in surface flow, based on modeling by their consultants, DHI. Chile held that these effects are small. In the second part of this paper, we summarize the modeling evidence. Chile's use of DHI's models, and its own hydrological and groundwater modeling of the basin, fully support Chile's position. We conclude with discussion of the Court's judgment, the challenges of physically‐based modeling of small changes in complex systems, and associated implications for judicial practice.This article is categorized under: Human Water > Water Governance Science of Water > Hydrological Processes Science of Water > Water and Environmental Change

Towards the development of an isotope‐enabled rainfall‐runoff model: Improving the ability to capture hydrological and anthropogenic change

AbstractGlobal hydrological alterations are being driven by climate change. However, while modelling tools have been instrumental in identifying these changes, their calibration is often dependent solely on streamflow data, which limits the ability to simulate important hydrological processes with the required level of certainty. Constraining hydrological process simulations is required to identify robust model parameters, reducing model uncertainty and providing a baseline model for climate‐related risk assessments. In this study, stable isotope measurements of rainwater, groundwater and stream water (δ2H and δ18O), together with an end member mixing analysis (EMMA) (as a post‐processing step) were integrated with the Jena adaptative modelling system (JAMS)/J2000 rainfall‐runoff model, named J2000iso. The J2000iso models of δ2H and δ18O were able to achieve a streamflow Nash–Sutcliffe efficiency (NSE) of 0.75 and 0.72 and an isotope mixing Kling–Gupta efficiency (KGE) of 0.51 and 0.60, respectively. Compared with the base version, the J2000iso had a much smaller variability with 56% less ensemble variance in the NSE, 13% more simulated interflow which resulted in a better soil‐moisture simulation at an observation point, and lower simulated flow component uncertainty. The J2000iso δ2H model was more robust than the base version during a subsequent validation in terms of KGE and Bias with 0.60 and 0.002 compared with 0.51 and −0.14 for the base version. The EMMA provided a means to improve the hydrograph separation ability of the JAMS/J2000. As many catchments around the world are still ungauged and are affected by anthropogenic activities, the development and enhancement of isotope‐enabled modelling provides a means to improve the simulation of key hydrological processes.

Reconfiguration of ecohydrology as a sustainability tool for Himalayan waterways

AbstractTwenty first century faces unprecedented challenges for the management of global waterways. The Himalayan waterways in Asia are exposed to unpredictable climatic warming together with anthropogenic perturbations caused by population growth, land use change and socio‐economic development. Given the increased public concerns on the Himalayan Mountain development programmes including the hydropower and tourism, there has been a growing need of the use of interdisciplinary scientific approaches to address water resources challenges that the Himalayan region has faced during the 21st century. Ecohydrology is an emerging scientific tool that explores key hydrological processes regulating structure and function of ecosystems, as well as assessing the impact of biological processes on water cycle variables under rapidly changing environment. The International Geosphere‐Biosphere Programme and the International Hydrological Programme hosted by the United Nations Educational, Scientific and Cultural Organization have adopted ecohydrology as a sustainable development tool by linking water resources and poverty eradication and ecosystem restoration, irrigation, energy and sanitation. However, ecohydrology tool needs to be reconfigured for sustainable development of rapidly changing Himalayan waterways. Here we propose the advancement of ecohydrology by developing various integrated frameworks of ecology, hydrology, hydraulics and sociology for resilient waterways in the Asian Himalayas.

Key hydrological process of a multiple aquifer flow system in the mining area of Huaibei plain, Eastern China

Groundwater resource protection and use are major challenges for the development of the coal industry in the long term. It is therefore crucial to investigate hydrogeochemical processes for sustainable groundwater resource use. A complex multi-layered groundwater system in a coal mine area was investigated and hierarchical cluster analysis, hydrochemical correlation analysis, and stable isotope analysis were applied to identify the water-rock interactions in the six reaction zones. Mineral dissolution and precipitation, cation exchange, sulfate reduction, and evaporation were the potential reactions. Three hydrogeochemical transport paths were derived using inverse simulation. The study found a connection between river water, pit lake water, and the Quaternary loose aquifer (QLA), indicating a contamination threat. Cross contamination between the Ordovician fracture limestone aquifer (OFA) water and QLA water, the Carboniferous fracture limestone aquifer (CFA) water, and Xie River water is possible, and after pit closure, mine water could contaminate QLA water. Therefore, measures to prevent cross-contamination due to these connections should be taken. The results provide a scientific basis for groundwater quality management in the study area and in other coal mines within the Huabei coalfield.

Comparisons of three scaling up methods to estimate stand transpiration of a xerophytic shrub (Salix psammophila) in northern China

Transpiration (T) is a key hydrological process, delivering water essential for plant metabolism and thus affecting productivity. A major challenge in estimating stand T is how to accurately scale sap flow data from individual trees to the stand. In shrub ecosystems, various scaling up methods have been used to extrapolate tree-level sap flow measurements to stand-level T, these include leaf area, cross-sectional area and number of branches. However, the performances of different scaling up methods have not been fully explored for shrubs. In this study, we measured sap flow of a xerophytic shrub (Salix psammophila) and scaled up using measures of leaf area, cross-sectional area and numbers of branches in order to estimate stand T during the rainy seasons in 2019 and 2020 on the northern Loess Plateau, China. In addition, we measured precipitation, throughfall, stemflow, soil evaporation, surface runoff and 0–200 cm soil water content to calculate actual stand T on the basis of soil water balance method. The results revealed that daily stand T differed according to the scaling up methods used for the estimation. Daily estimated stand T based on measures of leaf area (0.1–13.1 mm d−1) was consistently higher than those based on cross-sectional area (0.2–8.6 mm d−1) and number of branches (0.4–8.9 mm d−1) (p < 0.05). During the two rainy seasons, the actual daily mean stand T (2.5 ± 1.6 mm d−1) was significantly lower than the estimation by the three scaling up methods (p < 0.05). The method based on cross-sectional area appeared to be most suitable for scaling up because it had the lowest root mean square error and bias values (0.939 mm d−1 and 0.633 mm d−1, respectively). This study highlights the wide variations of stand T upon which scaling up method was chosen, and these differences need to be considered when converting tree-level sap flow to stand-level T in shrub and other ecosystems.

Surface Flooding as a Key Driver of Groundwater Arsenic Contamination in Southeast Asia.

Chronic exposure to groundwater contaminated with geogenic arsenic (As) poses a significant threat to human health worldwide, especially for those living on floodplains in South and Southeast (S-SE) Asia. In the alluvial and deltaic aquifers of S-SE Asia, aqueous As concentrations vary sharply over small spatial scales (10-100 m), making it challenging to identify where As contamination is present and mitigate exposure. Improved mechanistic understanding of the factors that control groundwater As levels is essential to develop models that accurately predict spatially variable groundwater As concentrations. Here we demonstrate that surface flooding duration and interannual frequency are master variables that integrate key hydrologic and biogeochemical processes that affect groundwater As levels in S-SE Asia. A machine-learning model based on high-resolution, satellite-derived, long-term measures of surface flooding duration and frequency effectively predicts heterogeneous groundwater As concentrations at fine spatial scales in Cambodia, Vietnam, and Bangladesh. Our approach can be reliably applied to identify locations of safe and unsafe groundwater sources with sufficient accuracy for making management decisions by solely using remotely sensed information. This work is important to evaluate levels of As exposure, impacts to public health, and to shed light on the underlying hydrogeochemical processes that drive As mobilization into groundwater.

Storage in South‐Eastern Australian Catchments

AbstractStorage and subsequent release of water is a key function of catchments that moderates the impact of meteorological and climate extremes. Despite the fact that many key hydrological processes depend upon storage, there are relatively few studies that focus on storage itself. Storage is difficult to quantify due to catchment heterogeneity and the paucity of data on key catchment characteristics that largely determine storage, such as soil, hydrogeology, and topography. We adopt a multi‐method approach to estimate the dynamic and extended dynamic storages using hydrometric data in 69 catchments in the Murray‐Darling Basin in south‐eastern Australia. We test relationships between the derived catchment storages and hydrological and physical characteristics that potentially control storage. The study catchments tended to have small dynamic storages relative to the extended dynamic storage; proportionally the dynamic storages were all less than 10% of the extended dynamic storage. While storage estimates produced by the different methods and study catchments varied, the order in which they ranked was consistent. Correlations between catchment characteristics and estimates of storage were inconsistent; however, the results indicated that greater storage is strongly associated with steeper catchments and smoother hydrographs. This study highlights limitations in the current methodology to derive storage and the quality of widely applied hydrometric data. We reinforce the need to collect data that can validate storage estimates and call for new approaches that can broadly estimate storage at the catchment scale.

Advances in the simulation of nutrient dynamics in cold climate agricultural basins: Developing new nitrogen and phosphorus modules for the Cold Regions Hydrological Modelling Platform

Excess nutrients in aquatic ecosystems is a major water quality problem globally. Worsening eutrophication issues are notable in cold temperate areas, with pervasive problems in many agriculturally dominated catchments. Predicting nutrient export to rivers and lakes is particularly difficult in cold agricultural environments because of challenges in modelling snow, soil, frozen ground, climate, and anthropogenic controls. Previous research has shown that the use of many popular small basin nutrient models can be problematic in cold regions due to poor representation of cold region hydrology. In this study, the Cold Regions Hydrological Modelling Platform (CRHM), a modular modelling system, which has been widely deployed across Canada and cold regions worldwide, was used to address this problem. CRHM was extended to simulate biogeochemical and transport processes for nitrogen and phosphorus through a complex of new process-based modules that represent physicochemical processes in snow, soil and freshwater. Agricultural practices such as tillage and fertilizer application, which strongly impact the availability and release of soil nutrients, can be explicitly represented in the model. A test case in an agricultural basin draining towards Lake Winnipeg shows that the model can capture the extreme hydrology and nutrient load variability of small agricultural basins at hourly time steps. It was demonstrated that fine temporal resolutions are an essential modelling requisite to capture strong concentration changes in agricultural tributaries in cold agricultural environments. Within these ephemeral and intermittent streams, on average, 30%, 31%, 20%, and 16% of the total annual load of nitrate (NO3), ammonium (NH4), soluble reactive phosphorus (SRP), and particulate phosphorous (partP)NO3, NH4, SRP and partP occurred during the episodic snowmelt freshet (∼9 days, accounting for 21% of the annual flow), but shows extreme temporal variation. The new nutrient modules are critical tools for predicting nutrient export from small agricultural drainage basins in cold climates via better representation of key hydrological processes, and a temporal resolution more suited to capture dynamics of ephemeral and intermittent streams.

Does Catchment Nestedness Enhance Hydrological Similarity?

AbstractThe topology of river networks defines the hierarchical organization of the landscape and controls the drainage pathways triggered by precipitation. This study investigates how the structure of channel networks influences spatial patterns of flow regimes by focusing on the hydrograph observed at the outlet of nested and non‐nested basins. An extensive data set spanning diverse geomorphoclimatic conditions is used to show that – when inter‐catchment distance increases – nested catchments exhibit a more pronounced decrease of streamflow correlation as compared to non‐nested sites. Thus, non‐nested basins have more correlated hydrologic responses at large distances. This unexpected behavior is explained by a geometrical model, which reveals that inter‐catchment differences in size and elevation are larger in nested sites, thereby increasing the spatial heterogeneity of key hydrological processes that shape the hydrograph. This study provides clues to critically reinterpret the hydrological response on nested versus non‐nested catchments, with relevant implications for hydrology and ecology.

A hydropedological approach to simulate streamflow and soil water contents with SWAT+

AbstractReflecting internal catchment hydrological processes in hydrological models is important for accurate predictions of the impact of climate and land‐use change on water resources. Characterizing these processes is however difficult and expensive due to their dynamic nature and spatio‐temporal variability. Hydropedology is a relatively new discipline focusing on the synergistic integration of hydrology, soil physics and pedology. Hydropedological interpretations of soils and soil distribution can be used to characterize key hydrological processes, especially in areas with no or limited hydrometric measurements. Here we applied a hydropedological approach to reflect flowpaths through detailed routing in SWAT+ for a 157 ha catchment (Weatherley) in South Africa. We compared the hydropedological approach and a standard (no routing) approach against measured streamflow (two weirs) and soil water contents (13 locations). The catchment was treated as ‘ungauged’ and the model was not calibrated against hydrometric measurements in order to determine the direct contribution of hydropedology on modelling efficiency. Streamflow was predicted well without calibration (NSE &gt; 0.8; R2 &gt; 0.82) for both approaches at both weirs. The standard approach yielded slightly better streamflow predictions. The hydropedological approach resulted in considerable improvements in the simulation of soil water contents (R2 increased from 0.40 to 0.49 and PBIAS decreased from 40% to 20%). The routing capacity of SWAT+ as employed in the hydropedological approach reduced the underestimation of wetland water regimes drastically and resulted in a more accurate representation of the dominant hydrological processes in this catchment. We concluded that hydropedology can be a valuable source of ‘soft data’ to reflect internal catchment structure and processes and, potentially, for realistic calibrations in other studies, especially those conducted in areas with limited hydrometric measurements.

Rainfall forecasting in upper Indus basin using various artificial intelligence techniques

Accurate forecasting of key hydrological processes, such as rainfall, generally requires the use of auxiliary predictive hydrological variables. Data requirements can be reduced by using artificial intelligence models that are able to successfully capture the information contained in the historic observations of the target variable of interest. In this study, a novel Wavelet-coupled Multi-order Time Lagged Neural Network (WMTLNN) model is developed to accurately forecast rainfall by using previous rainfall records only. The study is conducted using daily rainfall data recorded in the period 2015–2017 at three meteorological stations (Astore, Chillas, and Gilgit) located in Upper Indus Basin (UIB), Pakistan. WMTLNN models are developed by introducing time lags up to ten days, Symlets 4 (sym4) wavelets and Daubechies wavelets with three vanishing moments (db3), and Maximal Overlap Discrete Wavelet Transformation (MODWT) to account for boundary effects in the forecasting mode. The performance of WMTLNN models is compared with that of Time Lagged Neural Network (TLNN) models, Wavelet-coupled Time Lagged Neural Network (WTLNN), and deep learning Long Short-Term Memory (LSTM) models. Comparative analysis indicates that WMTLNN models overcome the other models, with more than 80% forecasting accuracy for most of the cases, and a typical range of 0.85–0.95 accuracy in terms of NSE. The highest NSE value is 0.97 at Astore with LSTM model, 0.96 at Chillas with WMTLNN model, and 0.95 at Gilgit with WMTLNN model. Overall, wavelet transformation of time series data enhances efficiency and accuracy of rainfall forecast.

Quantitative impacts of climate change and human activities on the runoff evolution process in the Yanhe River Basin

Since 1999, the surface vegetation coverage in the Yanhe River Basin has undergone constant change. The ecological environment in the basin has improved partially; however, water scarcity remains a critical issue for the Loess Plateau. The current quantitative analysis of runoff evolution affected by climatic and anthropogenic elements in the study area is insufficient. To evaluate the influence of anthropogenic elements and climatic variation on runoff evolution, we used the SWAT hydrological model to study key hydrological processes under different simulation scenarios along the river basin in this study. Overall, the runoff volume of the Yanhe River Basin showed a significant downward trend, although different trends were observed over different periods. Runoff declined from 1981 to 1998 and increased after 1998. A comparative analysis of three different scenarios shows that climate change contributes approximately twice as much to runoff evolution as land use changes. Climate change causes runoff to decrease by 65.64%, whereas land use change causes runoff to increase by 34.36%. The decrease in runoff in small watersheds is primarily due to climatic factors, whereas vegetation restoration is beneficial to the increase in runoff in small watersheds. The research results will be valuable in comprehending the quantitative influence of climatic and anthropogenic factors on the hydrological evolution of the Yellow River Valley.