Hydrological Impact Research Articles

Climate or land cover variations: what is driving observed changes in river peak flows? A data-based attribution study

Abstract. Climate change and land cover changes are influencing the hydrological regime of rivers worldwide. In Flanders (Belgium), the intensification of the hydrological cycle caused by climate change is projected to cause more flooding in winters, and land use and land cover changes could amplify these effects by, for example, making runoff on paved surfaces faster. The relative importance of both drivers, however, is still uncertain, and interaction effects between both drivers are not yet well understood. In order to better understand the hydrological impact of climate variations and land cover changes, including their interaction effects, we fitted a statistical model for historical data over 3 decades for 29 catchments in Flanders. The model is able to explain 60 % of the changes in river peak flows over time. It was found that catchment characteristics explain up to 18 % of changes in river peak flows, 6 % of changes in climate variability and 8 % of land cover changes. Steep catchments and catchments with a high proportion of loamic soils are subject to higher peak flows, and an increase in urban area of 1 % might cause increases in river peak flows up to 5 %. Interactions between catchment characteristics, climate variations and land cover changes explain up to 32 % of the peak-flow changes, where flat catchments with a low loamic soil content are more sensitive to land cover changes with respect to peak-flow anomalies. This shows the importance of including such interaction terms in data-based attribution studies.

Hillslope Hydrology in Global Change Research and Earth System Modeling

AbstractEarth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.

Evaluation of the effectiveness of green infrastructure on hydrology and water quality in a combined sewer overflow community

Evaluation of the effectiveness of green infrastructure (GI) practices on improving site hydrology and water quality and their associated cost could provide valuable information for decision makers when creating development/re-development strategies. In this study, a watershed scale rainfall-runoff model (the Long-Term Hydrologic Impact Analysis - Low Impact Development model, the L-THIA-LID 2.1 model) was enhanced to improve its simulation of urban water management practices including GI practices. The enhanced model (L-THIA-LID 2.2) is capable of: simulating in more detail impervious surfaces including sidewalks, roads, driveways, and parking lots; conducting cost calculations for converting these impervious surfaces to porous pavements; and, selecting suitable areas for bioretention in the study area. The effectiveness of GI practices on improving hydrology and water quality in a combined sewer overflow urban watershed—the Darst Sewershed in the City of Peoria, IL—was examined in eleven simulation scenarios using 8 practices. The total cost and the cost effectiveness for each scenario considering a 20-year practice lifetime were calculated. Results showed: combined implementation of GI practices performed better than applying individual practices alone; adoption levels and combinations of GI practices could potentially reduce runoff volume by 0.2–23.5%, TSS by 0.18–30.8%, TN by 0.2–27.9%, and TP by 0.2 to 28.1%; adding more practices did not necessarily achieve substantial runoff and pollutant reductions based on site characteristics; the most cost-effective scenario out of eleven considered had an associated cost of $9.21 to achieve 1 m3 runoff reduction per year and $119 to achieve 1 kg TSS reduction per year assuming residents' cooperation in implementing GI practices on their properties; adoption of GI practices on all possible areas could potentially achieve the greatest runoff and pollutant reduction, but would not be the most cost-effective option. This enhanced model can be applied to different locations to support assessing the beneficial uses of GI practices.

Analysis of Hydrologic Response Units and Impact of Flooding in Kuala Terengganu Sub-basins River Catchment in Malaysia

One of the issue of environmental disasters occurring in a wet tropical environment is flood influenced by the climatic factor of rainfall with high intensity. Flood is the most frequent catastrophe in Kuala Terengganu, Malaysia. The flood occurs during the monsoon season inundating riverbank and displacing the inhabitant rendering them homeless. The application of the Soil Water Assessment Tool (SWAT) is employed to identify the Hydrologic Response Units (HRUs). The flood vulnerability simulation in the Terengganu sub-basins river catchment was done using the most affected sub-basins. In this study, the impacts of five out of the 25 sub-basins have been affected by high flooding risk. The sub-basin with the highest impact of Hydrologic Response Unit is the sub-basin Three and the lowest is found in sub-basin Five.

Using a Hydrologic Model to Assess the Performance of Regional Climate Models in a Semi-Arid Watershed in Brazil

This study assessed the impact of climate change on the hydrological regime of the Paraguaçu river basin, northeastern Brazil. Hydrological impact simulations were conducted using the Soil and Water Assessment Tool (SWAT) for 2020–2040. Precipitation and surface air temperature projections from two Regional Climate Models (Eta-HadGEM2-ES and Eta-MIROC5) based on IPCC5—RCP 4.5 and 8.5 scenarios were used as inputs after first applying two bias correction methods (linear scaling—LS and distribution mapping—DM). The analysis of the impact of climate change on streamflow was done by comparing the maximum, average and reference (Q90) flows of the simulated and observed streamflow records. This study found that both methods were able to correct the climate projection bias, but the DM method showed larger distortion when applied to future scenarios. Climate projections from the Eta-HadGEM2-ES (LS) model showed significant reductions of mean monthly streamflow for all time periods under both RCP 4.5 and 8.5. The Eta-MIROC5 (LS) model showed a lower reduction of the simulated mean monthly streamflow under RCP 4.5 and a decrease of streamflow under RCP 8.5, similar to the Eta-HadGEM2-ES model results. The results of this study provide information for guiding future water resource management in the Paraguaçu River Basin and show that the bias correction algorithm also plays a significant role when assessing climate model estimates and their applicability to hydrological modelling.

Hydrological and geochemical responses of fire in a shallow cave system

The influence of wildfire on surface soil and hydrology has been widely investigated, while its impact on the karst vadose zone is still poorly understood. A moderate to severe experimental fire was conducted on a plot (10 m × 10 m) above the shallow Wildman's Cave at Wombeyan Caves, New South Wales, Australia in May 2016. Continuous sampling of water stable isotopes, inorganic geochemistry and drip rates were conducted from Dec 2014 to May 2017. After the fire, drip discharge patterns were significantly altered, which is interpreted as the result of increased preferential flows and decreased diffuse flows in the soil. Post-fire drip water δ18O decreased by 6.3‰ in the first month relative to the average pre-fire isotopic composition. Post-fire monitoring showed an increase in drip water δ18O in the following six months. Bedrock related solutes (calcium, magnesium, strontium) decreased rapidly after the fire due to reduced limestone dissolution time and potentially reduced soil CO2. Soil- and ash-derived solutes (boron, lead, potassium, sodium, silicon, iodine and iron) all decreased after the fire due to volatilisation at high temperatures, except for SO42−. This is the first study to understand the hydrological impact from severe fires conducted on a karst system. It provides new insights on the cave recharge process, with a potential explanation for the decreased d18O in speleothem-based fire study, and also utilise the decreased bedrock solutes to assess the wildfire impacts both in short and long time scales.

Attributing the hydrological impact of different land use types and their long-term dynamics through combining parsimonious hydrological modelling, alteration analysis and PLSR analysis

Understanding the relationship between hydrological processes and environmental changes is important for improved water management. The Geba catchment in Ethiopia, forming the headwaters of Tekeze-Atbara basin, was known for its severe land degradation before the recent success in integrated watershed management. This study analyses the hydrological response attributed to land management change using an integrated approach composed of (i) simulating the hydrological response of Land Use/Cover (LULC) changes; (ii) assessing the alteration of streamflow using Alteration of Hydrological Indicators (IHA); and (iii) quantifying the contribution of individual LULC types to the hydrology using Partial Least Square Regression model (PLSR).The results show that the expansion of agricultural and grazing land at the expense of natural vegetation has increased the surface runoff 77% and decreased dry season flow by 30% in the 1990s compared to 1970s. However, natural vegetation started to recover from the late 1990s and dry season flows increased by 16%, while surface runoff declined by 19%. More pronounced changes of the streamflow were noticed at sub-catchment level, mainly associated with the uneven spatial distribution of land degradation and rehabilitation. However, the rate of increase of low-flow halted in the 2010s, most probably due to an increase of water withdrawals for irrigation. Fluctuations in hydrological alteration parameters are in agreement with the observed LULC change. The PLSR analysis demonstrates that most LULC types showed a strong association with all hydrological components.These findings demonstrate that changing water conditions are attributed to the observed LULC change dynamics. The combined analysis of rainfall-runoff modelling, alteration indicators and PLSR is able to assess the impact of environmental change on the hydrology of complex catchments. The IHA tool is robust to assess the magnitude of streamflow alterations obtained from the hydrological model while the PLSR method is useful to zoom into which LULC is responsible for this alteration.

SSII-Evap: Simplified scheme to incorporate improved evapotranspiration estimates into the streamflow elasticity framework

The streamflow elasticity concept based on the Budyko framework is widely used in hydrological impact assessment studies. However, in landscapes transformed by human activities, identification of climate contributions to runoff change is difficult due to changing surface properties of river basins. Here, a method is proposed to quantify the effects of changing vegetation cover and included them in the calculus. The simplified scheme to incorporate improved evapotranspiration estimates into the streamflow elasticity framework is introduced and named as “SSII-Evap” method. SSII-Evap allows for calculating runoff changes induced by climate taking into account: 1) changes in two climatic variables (precipitation and potential evapotranspiration) and 2) changes in land surface conditions responsible for varying actual evapotranspiration. The six-step procedure provides a focused guide for enhancing the original method.•The SSII-Evap method introduces a bias correction to the original bivariate framework of streamflow elasticity to climate change.•In contrast to the original method, SSII-Evap accounts for the influence of vegetation changes on actual evapotranspiration that is estimated from satellite-derived data.•The elaborated customization is helpful for discriminating between climatic and human induced changes in mean annual runoff and is applicable to heavily modified river basins.

Green infrastructure practices simulation of the impacts of land use on surface runoff: Case study in Ecorse River watershed, Michigan

As an urban fringe district, the Ecorse River watershed is faced with increased impervious area caused by urban expansion. Effects of Green Infrastructure (GI) practice implementation were simulated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 model (L-THIA-LID 2.1). Suitable locations of each GI practice were identified, based on construction condition requirements and demand on GI practices in the study area. Using the data of 2011, various GI practice combination scenarios were explored according to the cost-efficiency of each GI practice. GI practice implementation scenarios in 2050 were also simulated based on projected land use and rainfall data. Results show that grassed swales, rain barrels (residential areas) and dry ponds were the top three most cost-efficient GI practices, with the cost at $1.5/m³/yr, $3.0/m³/yr and $3.4/m³/yr, respectively. Green roofs with rain cisterns (industrial and commercial area) were the most expensive GI practices, with the cost at $92.9/m³/yr. With the increase of investment in GI practices, the changing curves of the annual runoff volume, Total Nitrogen (TN) load and Total Phosphorus (TP) load reduction ratios match the law of diminishing marginal utility. The scenario with grassed swales, rain barrels, dry ponds and porous pavement would be the most cost-efficient scenario for runoff water quantity reduction. In addition, the scenario with additional wet ponds would be the most cost-efficient one for TN load and TP load reduction. GI practices in each scenario for expected 2050 conditions show better effectiveness on water quantity and quality management.

An approach to the implementation of Low Impact Development measures towards an EcoCampus classification

Impervious cover has important hydrologic impacts, namely the increased runoff volume and peak discharges in the rainwater network, which can lead to significant consequences like rapid urban floods with social, environmental and economic implications. LID (Low Impact Development) consist of distributed runoff management measures, like green roofs, pervious pavements, waterways covered with vegetation and filter trails, among others, that seek to control stormwater in the origin, reducing imperviousness. These solutions avoid increased runoff rate and volume, increase infiltration and groundwater recharge.The main goal of the research work here presented is to study the hydrological impact of LID's in UTAD (University of Trás-os-Montes e Alto Douro) campus, which is an institution focused on sustainability, since it has defined in its Strategic Plan to achieve, in a near future, an EcoCampus classification. To achieve the proposed goal, the campus area was studied in detail in order to evaluate the technical possibility of LID's implementation. A peak discharge comparison was made between the current situation and the one with LID's implementation, using the rational method.The results showed that peak discharges reduction between 68 and 95% may be achieved with LID solutions in UTAD campus.

Hydrologic Impacts of Ensemble-RCM-Projected Climate Changes in the Athabasca River Basin, Canada

Abstract In this study, the Providing Regional Climates for Impacts Studies (PRECIS) and the Regional Climate Model (RegCM) system as well as the Variable Infiltration Capacity (VIC) macroscale hydrologic model were integrated into a general framework to investigate impacts of future climates on the hydrologic regime of the Athabasca River basin. Regional climate models (RCMs) including PRECIS and RegCM were used to develop ensemble high-resolution climate projections for 1979–2099. RCMs were driven by the boundary conditions from the Hadley Centre Global Environment Model, version 2 with Earth system configurations (HadGEM2-ES); the Second Generation Canadian Earth System Model (CanESM2); and the Geophysical Fluid Dynamics Laboratory Earth System Model with MOM (GFDL-ESM2M) under the representative concentration pathways (RCPs). The ensemble climate simulations were validated through comparison with observations for 1984–2003. The RCMs project increases in temperature, precipitation, and wind speed under RCPs across most of the Athabasca River basin. Meanwhile, VIC was calibrated using the University of Arizona Shuffled Complex Evolution method (SCE-UA). The performance of the VIC model in replicating the characteristics of the observed streamflow was validated for 1994–2003. Changes in runoff and streamflow under RCPs were then simulated by the validated VIC model. The validation results demonstrate that the ensemble-RCM-driven VIC model can effectively reproduce historical climatological and hydrological patterns in the Athabasca River basin. The ensemble-RCM-driven VIC model shows that monthly streamflow is projected to increase in the 2050s and 2080s under RCPs, with notably higher flows expected in the spring for the 2080s. This will have substantial impacts on water balance on the Athabasca River basin, thus affecting the surrounding industry and ecosystems. The developed framework can be applied to other regions for exploration of hydrologic impacts under climate change.

Uncertainty assessment of streamflow projection under the impact of climate change in the Lower Mekong Basin: a case study of the Srepok River Basin, Vietnam

AbstractUncertainty assessment of future projection of streamflow is of the essence for an effective formulation of water resources management and planning adaptive to climate change. The aim of this study is to investigate the uncertainty in streamflow projection under the climate change impact in the Srepok River Basin. Uncertainty associated with emission scenarios (RCP2.6, RCP4.5 and RCP8.5), General Circulation Models (GCMs) (CanESM2, CNMR‐CM5 and HadGEM2‐AO), statistical downscaling methods (delta change method, quantile mapping and SDSM), and hydrological models (ANN, HEC‐HMS and SWAT) is examined. The results showed the largest uncertainty source of the streamflow projection is the GCM simulations, followed by the statistical downscaling methods, hydrological models and emission scenarios. In addition, the use of hydrological models has a considerable impact on uncertainty in the simulations of dry seasonal streamflow. Generally, the present study highlighted the importance of using multi‐GCMs in the studies on hydrological impact of climate change.

The Hydrological Impact of Extreme Weather-Induced Forest Disturbances in a Tropical Experimental Watershed in South China

Tropical forests are frequently disturbed by extreme weather events including tropical cyclones and cold waves, which can not only yield direct impact on hydrological processes but also produce indirect effect on hydrology by disturbing growth and structures of tropical forests. However, the hydrological response to extreme weather-induced forest disturbances especially in tropical forested watersheds has been less evaluated. In this study, a tropical experimental watershed in Hainan Province, China, was selected to investigate the hydrological responses to extreme weather-induced forest disturbances by use of a single watershed approach and the paired-year approach. Key results are: (1) extreme weather-induced forest disturbances (e.g., typhoon and cold wave) generally had a positive effect on streamflow in the study watershed, while climate variability either yielded a negative effect or a positive effect in different periods; (2) the response of low flows to forest discussion was more pronounced; (3) the relative contribution of forest disturbances to annual streamflow (48.6%) was higher than that of climate variability (43.0%) from 1995 to 2005. Given the increasing extreme weather with climate change and their possible catastrophic effects on tropical forests and hydrology in recent decades, these findings are essential for future adaptive water resources and forest management in the tropical forested watersheds.

Hydrologic impact of aspen harvesting within the subhumid Boreal Plains of Alberta

AbstractThis study examined the hydrological impact of harvesting aspen (Populus tremuloides) within the subhumid Boreal Plains of Alberta, Canada, following clear‐cutting of two stands in successive winters within a small catchment situated in glacial moraine. Impacts were evaluated using a combination of observational data collected from within the harvested catchment and an adjacent reference catchment and numerical simulations conducted with HydroGeoSphere. Sensitivity simulations evaluated the influence of post‐harvest evapotranspiration rates and variability in atmospheric conditions on the range of hydrologic response. Study results indicate that aspen harvesting had limited impact on groundwater levels and streamflows within these hydrologic systems because of the subhumid climate with low frequency of large storms, large soil‐moisture storage capacity of heterogeneous glacial materials, and high evapotranspiration rates of regenerating aspen. Despite an estimated increase in hillslope groundwater levels of up to 3 m, pond and peatland water levels increased by less than 0.3 m and were accompanied by increased streamflows of less than 10 mm. However, predicted increases in groundwater levels and streamflows were sensitive to regenerating aspen evapotranspiration rates, which can be enhanced by appropriate harvesting techniques but may be reduced by climate change. These results are consistent with previous results from within the Boreal Plains but differ from aspen harvesting studies conducted in other settings where appreciable increases in streamflows have been reported. This disparity highlights the need to consider the integrated response of the hydrologic system when evaluating impacts from disturbance and making comparisons between settings.

Application of Machine Learning Methodologies for Predicting Corn Economic Optimal Nitrogen Rate

Core Ideas A Machine Learning approach was innovatively used to predict corn EONR. Two features were created to approximate hydrological conditions for modeling EONR. Soil hydrology conditions were found essential in successful modeling in‐season EONR. Determination of in‐season N requirement for corn (Zea mays L.) is challenging due to interactions of genotype, environment, and management. Machine learning (ML), with its predictive power to tackle complex systems, may solve this barrier in the development of locally based N recommendations. The objective of this study was to explore application of ML methodologies to predict economic optimum nitrogen rate (EONR) for corn using data from 47 experiments across the US Corn Belt. Two features, a water table adjusted available water capacity (AWCwt) and a ratio of in‐season rainfall to AWCwt (RAWCwt), were created to capture the impact of soil hydrology on N dynamics. Four ML models—linear regression (LR), ridge regression (RR), least absolute shrinkage and selection operator (LASSO) regression, and gradient boost regression trees (GBRT)—were assessed and validated using “leave‐one‐location‐out” (LOLO) and “leave‐one‐year‐out” (LOYO) approaches. Generally, RR outperformed other models in predicting both at planting and split EONR times. Among the 47 tested sites, for 33 sites the predicted split EONR using RR fell within the 95% confidence interval, suggesting the chance of using the RR model to make an acceptable prediction of split EONR is ∼70%. When RR was used to test split EONR prediction with input weather features surrogated with 10 yr of historical weather data, the model demonstrated robustness (MAE, 33.6 kg ha−1; R2 = 0.46). Incorporating mechanistically derived hydrological features significantly enhanced the ability of the ML procedures to model EONR. Improvement in estimating in‐season soil hydrological status seems essential for success in modeling N demand.

Groundwater Is Key to Salmonid Persistence and Recruitment in Intermittent Mediterranean‐Climate Streams

AbstractJuvenile coho salmon thrive in intermittent streams of the Pacific Northwest yet are in danger of increased mortality from drought and rising temperatures. With warmer temperatures and more frequent climate extremes projected, the need to understand how intermittent stream hydrology and biogeochemistry impact juvenile salmonid habitat and behavior is imperative. Previous investigations indicated that dissolved oxygen limits the persistence of coho salmon in intermittent streams, leading to the hypothesis that groundwater inflow would ultimately control patterns of salmon recruitment and persistence. Here we tested that hypothesis in paired tributaries of Salmon Creek, Sonoma County, CA during California's extreme drought of 2011–2017. We used the fluorescent fingerprint of dissolved organic carbon, together with a parallel factor analysis, to estimate groundwater influence in individual stream pools, corroborating those estimates with stable isotope and radon analyses. Repeat snorkel surveys provided fish counts in those pools at the beginning and end of the period of surface‐water disconnection. Results suggested that coho salmon fry preferentially selected pools with a groundwater inflow signal and persisted in pools maintaining that signal through the dry season. This groundwater inflow signal was distinct from hyporheic influence, which exhibited little correlation with fish distribution. Groundwater within pools was young, and spot measurements suggested that it was relatively oxygenated. Proportional groundwater contributions to pools increased as drought deepened. Results suggest that maintaining relatively high groundwater levels in coastal aquifers may be imperative to the persistence of vulnerable salmonid populations in a changing climate.

Stima della Vulnerabilità intrinseca di un acquifero: automazione del metodo SINTACS con strumenti software GIS

Groundwater protection is always a prior environmental concern about water management; for this reason, several evaluation methods can be used to identify areas where an aquifer could be damaged by pollution. In this paper, the assessment of groundwater pollution vulnerability is realized using SINTACS method that was automated with the aid of ESRI Model Builder in ArcGIS software. SINTACS Method evaluates the intrinsic vulnerability using seven parameters:depth to groundwater (S), recharge action (I), attenuation capacity of the vadose zone (N), attenuation capacity of the soil (T), hydrogeologic characteristics of the aquifer media (A), hydraulic conductivity (C), and topographic slope (S). These parameters are adapted to five different weight classes depending on the hydrogeological features (porous, fissured or karstified media) and on impact condition (uncontaminated or urbanized environment). Actually, the real purpose of this project was to accelerate the application of the SINTACS method by creatingan automatic model, which every user can set according to his own needs. Model Builder is an application for building workflows, that are sequences of geoprocessing tools, feeding the output of one tool into another tool as input. In details, two tools are developed: a main model called SINTACS Model, realized with ESRI Model Builder (version 10.3.1) and an optional script tool called SINTACS Model – Scenari, created by using Python language and the ArcPy site-package. SINTACSModel produces all the outputs required from SINTACS method, while SINTACS Model – Scenari is able to identify the hydrological features and impact conditions in a specific area. The alluvial plan in Laterina (AR), an italian small country in Tuscany land, was selected as testsite: the results show that data has been correctly processed, filling in a reliable way all the information gaps.

Assessing the Hydrologic Impacts of Land Use Change in the Taihu Lake Basin of China from 1985 to 2010

In recent decades, the land use patterns in the Taihu Lake Basin (TLB) have undergone tremendous change. Assessing the response of land surface hydrological processes caused by land use change is conducive to basin water resource management and the prevention of urban flooding. The water yield under different land use scenarios in 1985, 1995, 2000, 2005, and 2010 were calculated by the STREAM model. During the study period of 1985–2010, the contribution of farmland to the total water yield decreased from 47.20% to 35.2%. The contribution of construction land to the total water yield increased from 10.50% to 25.82%. There was a significant spatial difference in the growth of the water yield in 1985–2010. The Pudong sub-region, Puxi sub-region, Yangchengdianmao sub-region, and the Wuchengxiyu sub-region, with relatively faster urban development, also had higher water yield growth rates. During the study period, the growth rate of water yields in towns showed a spatial clustering feature. MI increased from 0.22 to 0.38, indicating that this spatial clustering feature had an increasing trend. The results of an LISA analysis showed that there was a significant spatial difference in the growth rate of water yield in the TLB. The high growth centers are mainly located in the north of the basin, while the low growth centers are mainly located in the southwest of the basin. At the same time, the center of the high growth rate of water yield showed a certain trend of expansion and transfer. Regression analysis showed that urban development had a significant impact on water yield; for every increase of 1 km2 of construction land in the TLB, there was an increase of water yield of more than 300,000 m3. Further study indicated that the growth of local water production in TLB was much higher than the average value of the basin, and it was significantly related to the gross domestic product (GDP) per capita.

Modeling the hydrological impact of land use change in a dolomite-dominated karst system

Hydrological models represent valuable tools to investigate the impacts of land use changes on water resources. Most commonly, distributed, physically-based models are applied for land use change impact studies in hydrology. However, providing a physically-based and detailed description of subsurface flows in karst systems is challenging. Lumped models, in contrast, are easy to implement and widely used in karst hydrological research, albeit not applicable for land use change impact studies. To overcome these limitations, we developed a new semi-distributed model LuKARS (Land use change modeling in KARSt systems) that lumps the predominant hydrotopes (i.e. distinct landscape units characterized by homogeneous hydrological properties as a result of similar land use and soil types) present in a catchment as independent, non-linear units. Flows from each hydrotope represent a specific response of the vadose zone (soil-epikarst-infiltration zone) in a defined recharge area. The saturated zone consists of a single linear storage unit recharged by each hydrotope independently. The main goal of this approach was to investigate land use change impacts in a dolomite karst system exploited for the water supply of the city of Waidhofen a.d. Ybbs (Austria) by changing the area covered by each hydrotope. Here, land use changes occured in the form of increasing spaces used for dolomite mining and at the expense of existing forest sites. With our parametrized model, we were able to reproduce the measured discharge in the largest spring of the Waidhofen karst system (Kerschbaum spring). Moreover, we succeeded in transferring the parametrized hydrotopes to other recharge areas (Hinterlug and Mitterlug) and validated the transferability of the modeling approach. Finally, we successfully showed the model’s applicability for land use change impact studies by validating the calibrated model in a period in which the space of the dolomite quarries in the Kerschbaum recharge area almost doubled. The results of our study show that an increase of the dolomite quarries negatively affects the water supply of the city of Waidhofen a.d. Ybbs.

Multi-site multivariate downscaling of global climate model outputs: an integrated framework combining quantile mapping, stochastic weather generator and Empirical Copula approaches

A distributed modeling of hydrological impact under climate change relies on climate scenarios for multiple climate variables at multiple locations across the catchment. The site-specific or variable-specific downscaling methods only produce climate change scenarios for a specific site or specific variable, which is inadequate to drive distributed hydrological models to investigate the spatio-temporal variability of climate change impacts at the catchment scale. This study proposes an integrated framework combining quantile mapping (QM), stochastic weather generator (WG) and Empirical Copula (EC) approaches for multi-site multivariate downscaling of global climate model outputs from monthly, grid-scale to daily, station-specific scale. In this hybrid scheme, the QM method is used to spatially downscale the monthly large-scale climate model outputs; then a stochastic WG is used to temporally downscale the monthly data to daily data by adjusting the WG parameters according to the predicted changes from large-scale climate models; at last, the observed inter-site and inter-variable dependencies, the temporal persistence, as well as the inter-annual variability are restored using the EC approach. An application of the proposed methodology is presented for statistical downscaling of the monthly precipitation, maximum and minimum temperatures from historical simulations of two Earth System Models (ESMs) to eleven weather stations over Daqing river basin in north China. The proposed methodologies are calibrated during the period 1957–1986 and evaluated in the period 1987–2016. The results show that the proposed downscaling approach is able to reconstruct the marginally distributional statistics, inter-site and inter-variable dependencies, and temporal persistence in the downscaled data for the validation period. A Limitation is also noted, such as a possible misrepresentation of the dependence structure and inter-annual variability under a non-stationary climate condition. The proposed methodologies are useful for downscaling ensembles of large-scale climate model simulations and projections for distributed hydrological impact studies.