Water

Research

22 pages, 7692 KiB

Open AccessArticle

Micro-Catchments, Macro Effects: Natural Water Retention Measures in the Kylldal Catchment, Germany

by Silke M. Nauta, Maarten J. Waterloo, Anouk I. Gevaert, Jos de Bijl and Paul Brotherton

Water 2024, 16(5), 733; https://doi.org/10.3390/w16050733 - 29 Feb 2024

Viewed by 1536

Floods are among the most devastating and financially burdensome natural disasters in Europe. The combined impact of climate change and land use change is expected to exacerbate and intensify the destructive consequences of river floods. In this study, we analysed the effects of [...] Read more.

Floods are among the most devastating and financially burdensome natural disasters in Europe. The combined impact of climate change and land use change is expected to exacerbate and intensify the destructive consequences of river floods. In this study, we analysed the effects of wetland restoration on peak and base flows and on water quality in the Kylldal catchment of the Kyll River in the German Middle Mountains using the Soil and Water Assessment Tool+ (SWAT+). Monthly median daily discharge increases varied between 3% and 33% in the studied (micro)catchments. The higher median flow rates show that discharge peaks were attenuated and distributed over a longer period, making both extreme peak flows and low flows less common. Peak flows tended to decrease, with the largest effects between late fall and early spring when peak flow values decreased by up to 18%. The annual maximum peak flows in each of the three micro-catchments decreased by 12–24% on average. The occurrence of daily average flow rates larger than 1 m³ s⁻¹ was up to 45% lower after wetland restoration. Low flows increased by up to 21% and 13% in the summer and fall, respectively, which suggests that drought risk also decreases after wetland restoration. Average nitrogen exports decreased by 38–50% in the project areas and by 20% at the catchment level. Average phosphorus exports decreased by 52–67% in the project areas and by 25% at the catchment level. The study highlights the potential of wetland restoration for improving hydrological services, mitigating flood risks, and enhancing water quality. Restoring and maintaining freshwater ecosystems and their natural sponge functions is crucial for effectively managing water resources and addressing the challenges posed by climate change and land use changes. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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24 pages, 12683 KiB

Open AccessArticle

Estimating Climate Change’s Impacts on the Recharge of an Ungauged Tropical Aquifer (Togolese Coastal Sedimentary Basin)

by Rachid Barry, Florent Barbecot, Manuel Rodriguez, Alexandra Mattéi and Aime Djongon

Water 2024, 16(5), 731; https://doi.org/10.3390/w16050731 - 29 Feb 2024

Cited by 1 | Viewed by 1284

Abstract

The aquifers of the Togolese coastal sedimentary basin are the principal sources of water for almost half of the country’s population. These aquifers’ features have not been adequately monitored and studied. The resource is threatened by human activities, notably agriculture, industry, and withdrawals [...] Read more.

The aquifers of the Togolese coastal sedimentary basin are the principal sources of water for almost half of the country’s population. These aquifers’ features have not been adequately monitored and studied. The resource is threatened by human activities, notably agriculture, industry, and withdrawals for drinking water supplies. This situation is exacerbated by the potential effects of climate change. For this research, a basin-scale study was conducted to estimate current groundwater recharge and its future evolution in response to climate change. A recharge model based on Thornthwaite–Mather balance equations using runoff coefficients characterizing land use was fed with current and future climate data from an optimistic scenario (RCP 4.5) and a pessimistic scenario (RCP 8.4). Despite the associated uncertainties, the soil–water balance model at monthly time steps predicts a recharge of 3 to 455 mm per year from 2020 to 2039, and 40 to 420 mm per year from 2040 to 2059 under the optimistic RCP 4.5 scenario. According to the pessimistic RCP 8.5 scenario, the recharge will range between 16 and 515 mm per year from 2020 to 2049 and from 1 to 467 mm per year between 2040 and 2059. As a result, the basin’s groundwater recharge range, which is currently 47 to 225 mm, will significantly increase. This study provides a scientific basis for the sustainable management of groundwater in the Togolese coastal sedimentary basin. The recharge of the groundwater in the basin will increase regardless of the climate scenario and will support future development in the Togolese coastal sedimentary basin. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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20 pages, 6540 KiB

Open AccessArticle

Future Changes in Hydro-Climatic Extremes across Vietnam: Evidence from a Semi-Distributed Hydrological Model Forced by Downscaled CMIP6 Climate Data

by Hong Xuan Do, Tu Hoang Le, Manh-Hung Le, Dat Le Tan Nguyen and Nhu Cuong Do

Water 2024, 16(5), 674; https://doi.org/10.3390/w16050674 - 25 Feb 2024

Viewed by 1518

Abstract

Flood hazards have led to substantial fatalities and economic loss in the last five decades, making it essential to understand flood dynamics in a warming climate. This study reports the first comprehensive assessment of projected flood hazards across Vietnam. We used downscaled climate [...] Read more.

Flood hazards have led to substantial fatalities and economic loss in the last five decades, making it essential to understand flood dynamics in a warming climate. This study reports the first comprehensive assessment of projected flood hazards across Vietnam. We used downscaled climate data from the CMIP6 initiative, involving a total of 20 climate models, and streamflow projection simulated using a semi-distributed hydrological model. The assessment covers seven near-natural catchments, each representing a climate zone of the country. To evaluate climate change impacts on floods, the study simultaneously analyzes changes in three indices: (i) the annual hottest day temperature, to represent temperature extremes; (ii) the maximum daily rainfall amount, to represent rainfall extremes; and (iii) the discharge value exceeding 5% in a year, to assess streamflow extremes. Changes in the selected indices (relative to the reference period from 1985 to 2014) are assessed under four emission scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) and two future time slices (2036–2065 and 2070–2099). Although the robustness (as indicated by multi-model agreement) and significance (identified through the statistical test) of the changes vary substantially, depending on the selected indices and assessed time slices, an overall increase is consistently identified across all of the assessed hydro-climatic extremes (up to 4.8 °C for temperature extremes, 43 mm for rainfall extremes, and 31% for streamflow extremes). The findings suggest a potential increase in flood risk across Vietnam in a warming climate, highlighting the urgent need for improved flood preparedness and investment to reduce economic loss and mortality in an uncertain future. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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19 pages, 7468 KiB

Open AccessArticle

Simulation and Evaluation of Runoff in Tributary of Weihe River Basin in Western China

by Yinge Liu, Yang Su, Lingang Wang and Yaqian Zhao

Water 2024, 16(2), 221; https://doi.org/10.3390/w16020221 - 9 Jan 2024

Cited by 1 | Viewed by 1097

Abstract

Model simulation plays a significant role in the water resources cycle, and the simulation accuracy of models is the key to predicting regional water resources. In this research, the Qianhe tributary at the Weihe River basin in Western China was selected as the [...] Read more.

Model simulation plays a significant role in the water resources cycle, and the simulation accuracy of models is the key to predicting regional water resources. In this research, the Qianhe tributary at the Weihe River basin in Western China was selected as the study area. The tributary was divided into 29 sub-basins and 308 hydrological response units according to the spatial raster data and attribute data of the hydrology, meteorology, topography, land use, and soil types. On this basis, a soil and water assessment tool (SWAT) model for runoff simulation and evaluation of this region was established. A sensitivity test and parameter calibration were then executed on 15 parameters involved with surface runoff, soil flow, and shallow underground runoff. The simulation results demonstrate a calibration and verification error of 3.06–10.08%, with very small uncertainties throughout the simulation, whereas they exhibit relatively large errors in the simulation of the dry period (winter) but, in contrast, quite small errors in the rainy period (summer). In addition, the simulated runoff with a low value is overestimated. When the annual, monthly, and daily runoff are 4–13.5 m³/s, 4–69.8 m³/s, and 40–189.3 m³/s, respectively, the relative error is smaller, and the simulation results are more accurate. The sensitive parameters predominantly affecting the runoff simulation of the basin include soil evaporation compensation, runoff curve coefficient, vegetation transpiration compensation, and saturated hydraulic conductivity in this region. In the case of hypothetical land use change scenarios, we observe a great reduction in simulated runoff in arable land, woodland, and grassland, while we observe an increment in construction and residential land and wasteland. The annual and monthly runoff are increased by above 54.5%. With the increase in cultivated land and forestland, the annual and monthly runoff decrease by 24.6% and 6.8%, respectively. In the case of hypothetical scenarios under 24 climate combinations, if the precipitation remains unchanged, the increase and decrease in temperature by 1 °C leads to a decline and increment of runoff by −0.72% and 5.91%, respectively. With regard to the simulation for the future under the RCP2.6 and RCP8.5 climate scenarios, downscaling was employed to predict the runoff trend of the future. In short, this study provides a method for runoff inversion and water resources prediction in small mountainous watersheds lacking hydrological and meteorological observation stations. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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23 pages, 7110 KiB

Open AccessArticle

Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India

by Pradip Debnath, Stabak Roy, Satarupa Bharadwaj, Samrat Hore, Harjeet Nath, Saptarshi Mitra and Ana-Maria Ciobotaru

Water 2023, 15(23), 4109; https://doi.org/10.3390/w15234109 - 27 Nov 2023

Cited by 3 | Viewed by 1720

Abstract

The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of [...] Read more.

The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of the study area, an esteemed Ramsar site in North Eastern India, using a combined application of multivariable statistical and geospatial techniques. In this study, 24 water samples were designed based on their use and collected along the periphery and the inner areas of the lake employing the Latin Square Matrix. This research also examines the spatial variations of water quality involving quartile-based water quality categorization of parameters, with Pearson’s Correlation analysis, Principal Component Analysis (PCA), and Hierarchy Cluster Analysis (HCA) applied for dimension reduction. The analysis involved quartile-based water quality categorization of parameters, with PCA and HCA applied for dimension reduction. Meanwhile, the Inverse distance weighted (IDW) approach was used to interpolate the spatial distribution of the quartile score using the ArcGIS platform. The Bureau of Indian Standards (BIS) was followed for water quality assessment. The results revealed significant spatial variation, providing valuable insights for future water management strategies. PCA indicates 57.26% of the variance in the dataset, whereas samples were classified into three subgroups and two groups in a dendrogram representing the result of the HCA. This study demonstrates the utility of PCA, HCA, and IDW interpolation in water quality assessment, highlighting the effect of human-induced activities in the lake’s vicinity. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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24 pages, 17475 KiB

Open AccessArticle

Evaluation of Legacy Forest Harvesting Impacts on Dominant Stream Water Sources and Implications for Water Quality Using End Member Mixing Analysis

by Robert W. Fines, Micheal Stone, Kara L. Webster, Jason A. Leach, James M. Buttle, Monica B. Emelko and Adrian L. Collins

Water 2023, 15(15), 2825; https://doi.org/10.3390/w15152825 - 4 Aug 2023

Viewed by 1800

Abstract

Forests are critical water supply regions that are increasingly threatened by natural and anthropogenic disturbance. Evaluation of runoff-generating processes within harvested and undisturbed headwater catchments provides insight into disturbance impacts on water quality and drinking water treatability. In this study, an extensive hydrologic [...] Read more.

Forests are critical water supply regions that are increasingly threatened by natural and anthropogenic disturbance. Evaluation of runoff-generating processes within harvested and undisturbed headwater catchments provides insight into disturbance impacts on water quality and drinking water treatability. In this study, an extensive hydrologic dataset collected at the experimental Turkey Lakes Watershed (TLW) located on the Canadian Shield was used to quantify sources of stormflow in legacy clear-cut (24-years post harvesting) and forested (control) headwater catchments using an end member mixing analysis (EMMA) model. Stream water, groundwater, soil water, and throughfall water quality were evaluated during spring snowmelt, stormflow, and fall wet-up. Groundwater chemistry was similar to stream water chemistry in both catchments, suggesting that groundwater is a major contributor to stream flow. The water chemistry in small wetlands within the study catchments was comparable to stream water chemistry, suggesting that wetlands are also important contributors to stream flow. Differences in wetland position between the legacy clear-cut and control catchments appeared to have a greater influence on source contributions than legacy harvesting. Results from this study provide insight into runoff-generation processes that reflect event/seasonal flow dynamics and the impacts on water quality. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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13 pages, 2437 KiB

Open AccessArticle

Changes in Water-Use Efficiency of Eucalyptus Plantations and Its Driving Factors in a Small County in South China

by Yuefeng Yao, Jinjun Huang, Wen He, Jiafu Zhu and Yanyu Li

Water 2023, 15(15), 2754; https://doi.org/10.3390/w15152754 - 29 Jul 2023

Cited by 3 | Viewed by 1634

Abstract

Ecosystem water-use efficiency (

W U E

) has been central in revealing the variability in terrestrial carbon and water cycles. Short-rotation plantations such as Eucalyptus plantations can simultaneously impact net primary production (

N P P

) and actual evapotranspiration ( [...] Read more.

Ecosystem water-use efficiency (

W U E

) has been central in revealing the variability in terrestrial carbon and water cycles. Short-rotation plantations such as Eucalyptus plantations can simultaneously impact net primary production (

N P P

) and actual evapotranspiration (

{E T}_{a}

), components of

W U E

, resulting in changes in terrestrial carbon and water cycles. However, there are few detailed studies on the changes in the

W U E

of Eucalyptus plantations at the catchment scale with high spatial remote sensing imagery. Here, we present the changes in the

W U E

of Eucalyptus plantations and its driving factors (i.e.,

N P P

and

{E T}_{a}

) using satellite-based models combined with 5-m spatial resolution RapidEye imagery in a small county in South China. The increases in

{E T}_{a}

of Eucalyptus plantations are primarily the result of climate warming and result in low

W U E

of Eucalyptus plantations. The management practice used (short rotation in this study) can enhance the effect of climate warming on

W U E

by varying the

N P P

of Eucalyptus plantations. A high value of

N P P

leads to a high

W U E

of Eucalyptus plantations at the end of a short rotation, while a low value of

N P P

results in a low

W U E

at the beginning of another short rotation. Changes in the

W U E

of Eucalyptus plantations indicated large spatial and temporal variability, associated with climate warming and short-rotation practices. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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17 pages, 3148 KiB

Open AccessArticle

Climate Change Impacts on the Côa Basin (Portugal) and Potential Impacts on Agricultural Irrigation

by Diogo Rodrigues, André Fonseca, Oiliam Stolarski, Teresa R. Freitas, Nathalie Guimarães, João A. Santos and Helder Fraga

Water 2023, 15(15), 2739; https://doi.org/10.3390/w15152739 - 28 Jul 2023

Cited by 3 | Viewed by 1802

Abstract

The increasing gap between water demands and availability is a significant challenge for sustainable water management, particularly in the context of growing irrigation needs driven by climate change. In the Côa region (inner-north Portugal), agriculture plays a vital role in the local economy, [...] Read more.

The increasing gap between water demands and availability is a significant challenge for sustainable water management, particularly in the context of growing irrigation needs driven by climate change. In the Côa region (inner-north Portugal), agriculture plays a vital role in the local economy, ensuring food security and contributing to the conservation of natural resources, though also threatened by climate change. The present study assesses how streamflow in the Côa River can be affected by climate change. The HSPF (Hydrological Simulation Program-FORTRAN) hydrological model was coupled with three global–regional climate model chains to simulate historical monthly and annual streamflow (1986–2015), and to predict future (2040–2099) streamflow under RCP8.5. Irrigation scenarios were subsequently developed considering a potential future increase from 10% to 50% per decade. The evaluation of HSPF performance during the historical period revealed good agreement (R² > 0.79) between simulated and observed flows. A general decrease in streamflow is found in the future, particularly in 2070–2099, with annual mean streamflow projected to decrease by −30% until 2099. Interannual variability is also expected to increase. Generally, the simulations indicated higher future flows in winter/early spring, whilst they are expected to decrease over the rest of the year, suggesting drought intensification. An increase in water demands for irrigation, potentially rising from 46 hm³·yr⁻¹ (baseline scenario) up to 184 hm³·yr⁻¹ (50% increase per decade) may lead to unsustainable irrigation. Managing these opposite trends poses significant challenges, requiring a comprehensive and integrated approach from stakeholders and policymakers. Strategies should focus on both demand-side and supply-side measures to optimize water use, improve water efficiency, and preserve water availability. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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17 pages, 3492 KiB

Open AccessArticle

Attribution Analysis of Runoff Variation in the Second Songhua River Based on the Non-Steady Budyko Framework

by Zan Li, Yao Wu, Ji Li, Peng Qi, Jiaxin Sun and Yingna Sun

Water 2023, 15(3), 451; https://doi.org/10.3390/w15030451 - 23 Jan 2023

Cited by 2 | Viewed by 2402

Abstract

Understanding the role of climate change and catchment characteristics in hydrological activity is important for the efficient use of water resources. In this study, a Budyko framework suitable for non-steady conditions was used to assess the impacts of climate change and catchment characteristics [...] Read more.

Understanding the role of climate change and catchment characteristics in hydrological activity is important for the efficient use of water resources. In this study, a Budyko framework suitable for non-steady conditions was used to assess the impacts of climate change and catchment characteristics on the long-term changes in annual and seasonal runoff in the Second Songhua River (SSR) basin during the last 30 years. Based on the analysis of the hydro-meteorological series of the SSR, the runoff in the SSR basin showed a non-significant increasing trend. The hydro-meteorological elements changed abruptly in 2009, and the study period was divided into a baseline period (1989–2009) and a disturbed period (2010–2018). Runoff increased during the disturbed period compared to the baseline period, with a significant increase in spring runoff in the upstream area and summer runoff in the downstream area. The attribution analysis results indicated that the annual runoff was mainly affected by climatic factors, and 66.8–99.6% of yearly runoff changes were caused by climate change. Catchment characteristics had little effect on yearly runoff but significantly affected seasonal runoff. The catchment characteristics affecting runoff were mainly increased water withdrawal, changes in snowfall, degradation of permafrost, and changes in reservoir operation. This study provides a basis for further understanding the intra-annual runoff variability for SSR and other similar rivers. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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20 pages, 8932 KiB

Open AccessArticle

Possible Factors Driving Groundwater Quality and Its Vulnerability to Land Use, Floods, and Droughts Using Hydrochemical Analysis and GIS Approaches

by Sherif Ahmed Abu El-Magd, Hanaa Ahmed, Quoc Bao Pham, Nguyen Thi Thuy Linh, Duong Tran Anh, Ismail Elkhrachy and Ahmed M. Masoud

Water 2022, 14(24), 4073; https://doi.org/10.3390/w14244073 - 13 Dec 2022

Cited by 8 | Viewed by 2505

Abstract

Land use and climate change always induce significant changes in various parameters of the hydrologic cycle (e.g., surface runoff, infiltration, evapotranspiration). The Wadi El-Assiuti downstream area in the Eastern Desert of Egypt is one of the most promising areas for development that is [...] Read more.

Land use and climate change always induce significant changes in various parameters of the hydrologic cycle (e.g., surface runoff, infiltration, evapotranspiration). The Wadi El-Assiuti downstream area in the Eastern Desert of Egypt is one of the most promising areas for development that is suffering from insufficient water availability and inadequate water quality for different purposes. The main goal of this research is to evaluate the changes in groundwater quality, land use, and climate in association with geology and flooding during three periods within the years 1997–2019 in the downstream portion of Wadi El-Assiuti in the Eastern Desert of Egypt, using spatiotemporal variation associated with groundwater hydrochemical analysis and GIS techniques. About 133 groundwater samples were collected to examine groundwater quality changes over time. Different groundwater quality indices were calculated, and the results show that TDS levels of groundwater in the study area ranged between 1080–2780 mg/L, 672–4564 mg/L, and 811–6084 mg/L, while SAR levels varied within 6.15–15.34, 1.83–28.87, and 1.43–30.57 for the years 1997, 2007, and 2019, respectively. Both RSBC and SSP values exhibited significantly increasing trends over time. KR values were within 1.36–4.06 in 1997, 0.58–14.09 in 2007, and 0.35–14.92 in 2019; MAR values were within 6.9–45.2 in 1997, 20.79–71.5 in 2007, and 17.71–75.81 in 2019; and PI values were within 60.16–83 in 1997, 45.56–101.03 in 2007, and 42.51–148.88 in 2019. Across the entire study area, ongoing land use changes increased from 1.1% in 1997 to 4.1% in 2019. Findings pointed to the significant contribution of the deep Nubian Sandstone Aquifer to the groundwater aquifer at Wadi El-Assiuti through fractures and deep faults. Given the climatic conditions from 1997–2019, these changes may have affected water quality in shallow aquifers, especially with increasing evaporation. Realizing the spatiotemporal variation of the aquifer recharge system, land use development, and climate change clearly would help in water resource management. This study revealed that flooding events, deep-seated geologic structures, and land use development associated with human activities have the highest impact on groundwater quality. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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45 pages, 49213 KiB

Open AccessArticle

Assessment of Implementing Land Use/Land Cover LULC 2020-ESRI Global Maps in 2D Flood Modeling Application

by Mohamed Soliman, Mohamed M. Morsy and Hany G. Radwan

Water 2022, 14(23), 3963; https://doi.org/10.3390/w14233963 - 5 Dec 2022

Cited by 4 | Viewed by 4592

Abstract

Floods are one of the most dangerous water-related risks. Numerous sources of uncertainty affect flood modeling. High-resolution land-cover maps along with appropriate Manning’s roughness values are the most significant parameters for building an accurate 2D flood model. Two land-cover datasets are available: the [...] Read more.

Floods are one of the most dangerous water-related risks. Numerous sources of uncertainty affect flood modeling. High-resolution land-cover maps along with appropriate Manning’s roughness values are the most significant parameters for building an accurate 2D flood model. Two land-cover datasets are available: the National Land Cover Database (NLCD 2019) and the Land Use/Land Cover for Environmental Systems Research Institute (LULC 2020-ESRI). The NLCD 2019 dataset has national coverage but includes references to Manning’s roughness values for each class obtained from earlier studies, in contrast to the LULC 2020-ESRI dataset, which has global coverage but without an identified reference to Manning’s roughness values yet. The main objectives of this study are to assess the accuracy of using the LULC 2020-ESRI dataset compared with the NLCD 2019 dataset and propose a standard reference to Manning’s roughness values for the classes in the LULC 2020-ESRI dataset. To achieve the research objectives, a confusion matrix using 548,117 test points in the conterminous United States was prepared to assess the accuracy by quantifying the cross-correspondence between the two datasets. Then statistical analyses were applied to the global maps to detect the appropriate Manning’s roughness values associated with the LULC 2020-ESRI map. Compared to the NLCD 2019 dataset, the proposed Manning’s roughness values for the LULC 2020-ESRI dataset were calibrated and validated using 2D flood modeling software (HEC-RAS V6.2) on nine randomly chosen catchments in the conterminous United States. This research’s main results show that the LULC 2020-ESRI dataset achieves an overall accuracy of 72% compared to the NLCD 2019 dataset. The findings demonstrate that, when determining the appropriate Manning’s roughness values for the LULC 2020-ESRI dataset, the weighted average technique performs better than the average method. The calibration and validation results of the proposed Manning’s roughness values show that the overall Root Mean Square Error (RMSE) in depth was 2.7 cm, and the Mean Absolute Error (MAE) in depth was 5.32 cm. The accuracy of the computed peak flow value using LULC 2020-ESRI was with an average error of 5.22% (2.0% min. to 8.8% max.) compared to the computed peak flow values using the NLCD 2019 dataset. Finally, a reference to Manning’s roughness values for the LULC 2020-ESRI dataset was developed to help use the globally available land-use/land-cover dataset to build 2D flood models with an acceptable accuracy worldwide. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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15 pages, 6880 KiB

Open AccessArticle

Machine Learning Assessment of the Impact of Global Warming on the Climate Drivers of Water Supply to Australia’s Northern Murray-Darling Basin

by Milton Speer, Joshua Hartigan and Lance Leslie

Water 2022, 14(19), 3073; https://doi.org/10.3390/w14193073 - 29 Sep 2022

Cited by 6 | Viewed by 2729

Abstract

Droughts and long dry spells, interspersed with intense rainfall events, have been characteristic of the northern Murray-Darling Basin (NMDB), a major Australian agricultural region. The NMDB precipitation results from weather systems ranging from thunderstorms to larger scale events. The larger scale events exhibit [...] Read more.

Droughts and long dry spells, interspersed with intense rainfall events, have been characteristic of the northern Murray-Darling Basin (NMDB), a major Australian agricultural region. The NMDB precipitation results from weather systems ranging from thunderstorms to larger scale events. The larger scale events exhibit high seasonal and annual rainfall variability. To detect attributes shaping the NMDB precipitation patterns, and hence net water inflows to the vast Darling River catchment area, numerous (45) possible attributes were assessed for their influence on rainfall trends. Four periods were assessed: annual, April–May (early cool-season), June–September (remaining cool-season), and October–March (warm-season). Linear and non-linear regression machine learning (ML) methods were used to identify the dominant attributes. We show the impact of climate drivers on the increasingly dry April–May months on annual precipitation and warmer temperatures since the early 1990s. The NMDB water supply was further reduced during 1992–2018 by the lack of compensating rainfall trends for the April–May decline. The identified attributes include ENSO, the Southern Annular Mode, the Indian Ocean Dipole, and both local and global sea surface temperatures. A key finding is the prominence of global warming as an attribute, both individually and in combination with other climate drivers. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources)

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