Implications For Water Resources Research Articles

Flash Drought Intensification due to Enhanced Land–Atmospheric Coupling in India

Abstract Land–atmospheric feedback influences the occurrence and severity of flash droughts. However, the observed and projected changes in flash droughts and associated land–atmospheric coupling have not been examined over India. Moreover, the causes of the rapid depletion of soil moisture during flash droughts are not well known. We identify major flash droughts and associated soil moisture–vapor pressure deficit (SM–VPD) coupling in India using ERA5 and simulations from global climate models (CMIP6-GCMs). The summer monsoon season (June–September) witnesses more than 60% of the flash drought events and a relatively higher rate of flash drought development. The flash drought frequency has mainly decreased during India’s observed climate (1980–2019), which is projected to decline further in the future warming climate. On the other hand, the flash drought development rate has significantly increased during the observed period, which is projected to enhance further under the warming climate. SM–VPD coupling during the flash drought onset-development phase is considerably higher (threefold to fivefold) than during the normal condition (in the absence of flash drought). The high (low) SM–VPD coupling explains the faster (slower) flash drought development rate in the observed and future warming climate. The strength of SM–VPD coupling has increased in the recent period and is projected to increase further in the future warming climate. The increased SM–VPD coupling can intensify future flash droughts in India, especially during the summer monsoon season, with considerable implications for agriculture, water resources, and ecosystems. Significance Statement This study aims to understand better the role of land–atmospheric coupling in explaining flash drought characteristics (frequency and development rate) in India. Strong land–atmospheric (SM–VPD) feedback might influence the regional weather patterns during flash drought, which often negatively impacts humans and the ecosystem. We explain the causes and drivers of increasing (decreasing) flash drought development rate (frequency) in India. The long-term change in SM–VPD coupling drives the frequency of flash drought, whereas an anomalous instantaneous change in coupling controls the flash drought development rate. More intense flash droughts contributed by the increased land–atmospheric coupling are projected in the future. Predicting the SM–VPD coupling metric can facilitate more time for preparedness, resulting in minimizing the flash drought impacts.

Hydrogeological Characteristics and Geophysical Study of Base Aquifers in the Island of Grande Comore: Implications for Water Resources and Saline Intrusion

Hydrogeological Characteristics and Geophysical Study of Base Aquifers in the Island of Grande Comore: Implications for Water Resources and Saline Intrusion

Long‐term trends in mountain groundwater levels across Canada and the United States

AbstractMountains have a critical role in freshwater supply for downstream populations. As the climate changes, groundwater stored in mountains may help buffer the impacts to declining water resources caused by decreased snowpack and glacier recession. However, given the scarcity of groundwater observation wells in mountain regions, it remains unclear how mountain groundwater is being impacted by climate change across ecoregions. This study quantifies temporal trends in mountain groundwater levels and explores how various climatic, physiographic and anthropogenic factors affect these trends. We compiled data from 171 public groundwater observation wells within mountain regions across Canada and the United States, for which at least 20 years of monthly data is available. The Mann‐Kendall test for monotonic trend revealed that 54% of these wells have statistically significant temporal trends (p < 0.05) over the period of record, of which 69% were negative and therefore indicating overall declining groundwater storage. Wells in the western mountain ranges showed stronger trends (both positive and negative) than the eastern mountain ranges, and higher elevation wells showed fewer negative trends than the low elevation (<400 m asl) wells (p < 0.05). Correlation, Kruskal‐Wallis tests, stepwise multiple linear regression and random forest regression were used to identify factors controlling groundwater trends. Statistical analysis revealed that lower‐elevation mountain regions with higher average annual temperatures and lower average annual precipitation have the greatest declines in groundwater storage under climate change. Trends in temperature and precipitation, and ecoregion were also important predictors on groundwater level trends, highlighting geographic differences in how mountain wells are responding to climate change. Furthermore, sedimentary bedrock aquifers showed markedly more negative trends than crystalline bedrock aquifers. The findings demonstrate that the impact of climate change on mountain water resources extends to the subsurface, with important implications for global water resources.

Changes in evaporation patterns and their impact on Climatic Water Balance and river discharges in central Poland, 1961–2020

This study investigates the changes in precipitation and evaporation patterns and their impact on Climatic Water Balance and river discharges in central Poland from 1961 to 2020. The analysis focuses on two “normal” periods, 1961–1990 and 1991–2020 (according to the World Meteorological Organization). Bartlett’s test and the Kruskal–Wallis rank sum test were used to assess the homogeneity of variances and compare distributions of analyzed variables over two “normal” periods. The probability density functions were estimated using a kernel density estimator with a Gaussian kernel function. Significant findings indicate alterations in evaporation rates and shifts in water balance dynamics. Mean evaporation increased from 530.8 to 637.9 mm, leading to a notable decrease in the mean Climatic Water Balance from 1.1 to − 107.5 mm (in the periods 1961–1990 and 1991–2020, respectively). Additionally, rivers showed reduced mean annual discharges (from 4.28 to 3.01 m3·s−1 and 1.25 to 0.87 m3·s−1, for the Zgłowiączka and Skrwa Lewa rivers, respectively). These climatic changes in central Poland have substantial implications for regional water resources, especially in spring and summer and particularly in agricultural areas, potentially exacerbating drought conditions and impacting agricultural productivity mainly in the warm half-year.

Offshore freshened groundwater reservoirs controlled by submarine faults with a complex dependency on antecedent hydrogeological conditions

Offshore Freshened Groundwater (OFG) reservoirs are gaining attention, as evidence suggests they are more prevalent worldwide than previously thought. OFG systems are generally classified as either passive, a relic of ancient, lower sea levels, or as active, with an onshore-offshore hydrogeologic connection and associated discharge offshore. Previous studies on the mechanisms of OFG were conducted in various hydrogeologic settings, but the role of faults remains understudied. Based on geologic data, we apply hydrogeologic modeling of a faulted submarine confined aquifer in the Levant basin (eastern Mediterranean), to study the impact of faults on OFG. We find that faults that are close to the coastline and within the brackish zone that would have developed without a fault control the offshore salinities regardless of initial conditions. The influence of distal faults, in contrast, depends on antecedent conditions. When initial salinities are such that the distal fault lies in the fresh part of the aquifer, the saline wedge migrates landward toward the fault with sea-level rise, and the fault dictates the steady-state salinity distribution. If the fault is initially within the saline part of the aquifer, freshwater never reaches the fault, likely due to the density-driven flow barrier that the underlying saline wedge generates. These findings suggest a new mode of OFG in which the same geologic system can be either active or passive depending on the hydrologic history. This should be considered in future studies of OFG systems, the functioning of which has implications for marine ecosystems, seafloor geomorphology, and coastal water resources.

Analysis of the Spatiotemporal Variability of Hydrological Drought Regimes in the Lowland Rivers of Kazakhstan

Hydrological droughts occur as a result of various hydrometeorological conditions, such as precipitation deficits, reduced snow cover, and high evapotranspiration. Droughts caused by precipitation deficits and occurring during warm seasons are usually longer in duration. This important observation raises the question that climate change associated with global warming may increase drought conditions. Consequently, it is important to understand changes in the processes leading to dry periods in order to predict potential changes in the future. This study is a scientific analysis of the impact of climate change on drought conditions in the Zhaiyk–Caspian, Tobyl–Torgai, Yesil, and Nura–Sarysu water management basins using the standardized precipitation index (SPI) and streamflow drought index (SDI). The analysis methods include the collection of hydrometeorological data for the entire observation period up to and including 2021 and the calculation of drought indices to assess their intensity and duration. The results of this study indicate an increase in the intensity and frequency of drought periods in the areas under consideration, which is associated with changes in climatic conditions. The identified trends have serious implications for agriculture, ecological balance, and water resources. The conclusions of this scientific study can be useful for the development of climate change adaptation strategies and the sustainable management of natural resources in the regions under consideration.

Biomimetic Leaf-Shaped Wedge Structure with Mixed Wettability for Fog Harvesting.

Water scarcity is a pressing issue in arid and semi-arid regions, making fog harvesting a promising method for water collection. However, enhancing the rate of fog harvesting remains a challenge. Controlling the movement of droplets on functional surfaces is crucial for the development of effective water-harvesting devices. In this study, a three-dimensional (3D) fog-harvesting device with mixed wettability is fabricated using a combination of physical and chemical techniques. With inspiration drawn from natural organisms, such as the desert beetle and Nephrolepis cordifolia, which can both live in low humidity, a copper substrate with a leaf-shaped wedge superhydrophilic structure and flat superhydrophobic regions is fabricated for fog harvesting. The modified surface results in a maximum 49.89% improvement in fog-harvesting efficiency compared to the original copper substrate. The synergistic effect of the 3D structure and mixed wettability of this study offers an idea for improving fog collection efficiency, with potential implications for energy sustainability water resources.

Improving hydrological modeling to close the gap between elevated CO2 concentration and crop response: Implications for water resources

Rising atmospheric carbon dioxide concentrations ([CO2]) affect crop growth and the associated hydrological cycle through physiological forcing, which is mainly regulated by reducing stomatal conductance (gs) and increasing leaf area index (LAI). However, reduced gs and increased LAI can affect crop water consumption, and the overall effects need to be quantified under elevated [CO2]. Here we develop a SWAT-gs-LAI model by incorporating a nonlinear gs-CO2 equation and a missing LAI-CO2 relationship to investigate the responses of water consumption of grain maize, maize yield, and losses of water and soil to elevated [CO2] in the Upper Mississippi River Basin (UMRB; 492,000 km2). Results exhibited enhanced maize yield with decreased water consumption for increases in [CO2] from 495 ppm to 825 ppm during the historical period (1985–2014). Elevated [CO2] promoted surface runoff but suppressed sediment loss as the predominant impact of LAI-CO2 leading to enhanced surface cover. A comprehensive analysis of future climate change showed increased maize water consumption in comparison to the historical period, driven by the more pronounced effects of overall climate change rather than solely elevated [CO2]. Generally, future climate change promoted maize yield in most regions of the UMRB for three Shared Socioeconomic Pathway (SSP) scenarios. Surface runoff was shown to increase generally in the future with sediment loss increasing by an average of 0.39, 0.42, and 0.66 ton ha-1 for SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. This was due to negative climatic change effects largely surpassing the positive effect of elevated [CO2], particularly in zones near the middle and lower stream. Our results underscore the crucial role of employing a physically-based model to represent crop physiological processes under elevated [CO2] conditions, improving the reliability of predictions related to crop growth and the hydrological cycle.

Recent and near‐term future changes in impacts‐relevant seasonal hydroclimate in the world's Mediterranean climate regions

AbstractChange over recent decades in the world's five Mediterranean Climate Regions (MCRs) of quantities of relevance to water resources, ecosystems and fire are examined for all seasons and placed in the context of changes in large‐scale circulation. Near‐term future projections are also presented. It is concluded that, based upon agreement between observational data sets and modelling frameworks, there is strong evidence of radiatively‐driven drying of the Chilean MCR in all seasons and southwest Australia in winter. Observed drying trends in California in fall, southwest southern Africa in fall, the Pacific Northwest in summer and the Mediterranean in summer agree with radiatively‐forced models but are not reproduced in a model that also includes historical sea surface temperature (SST) forcing, raising doubt about the human‐origin of these trends. Observed drying in the Mediterranean in winter is stronger than can be accounted for by radiative forcing alone and is also outside the range of the SST‐forced ensemble. It is shown that near surface vapour pressure deficit (VPD) is increasing almost everywhere but that, surprisingly, this is contributed to in the Southern Hemisphere subtropics to mid‐latitudes by a decline in low‐level specific humidity. The Southern Hemisphere drying, in terms of precipitation and specific humidity, is related to a poleward shift and strengthening of the westerlies with eddy‐driven subsidence on the equatorward side. Model projections indicate continued drying of Southern Hemisphere MCRs in winter and spring, despite ozone recovery and year‐round drying in the Mediterranean. Projections for the North American MCR are uncertain, with a large contribution from internal variability, with the exception of drying in the Pacific Northwest in summer. Overall the results indicate continued aridification of MCRs other than in North America with important implications for water resources, agriculture and ecosystems.

Chemical Perspectives on the Impact of Climate Change in Afghanistan: A Comprehensive Review

: Climate change is a global phenomenon that has significant impacts on various aspects of human life, including the environment, economy, and social well-being. Afghanistan, one of the least developed and most vulnerable countries to climate change, is facing alarming effects due to its high dependence on agricultural livelihoods, fragile environment, poor socio-economic development, high frequency of natural hazards, and over four decades of conflict. This comprehensive review aims to provide an overview of the current state of knowledge on the impact of climate change on Afghanistan's environment, economy, and society, and to highlight the vulnerability of Afghanistan to climate change. The review also explores the chemical composition of air pollutants in Afghan cities, the impact of air and water pollution on human health and the environment, the influence of climate change on soil composition and nutrient availability, and the implications for water resources, including groundwater quality and availability. Finally, the review discusses the chemical aspects of climate change adaptation and mitigation efforts in Afghanistan, focusing on innovative technologies and practices to address climate-related challenges in the country.

Nano-Food Farming Approaches to Mitigate Heat Stress under Ongoing Climate Change: A Review

Increased heat stress is a common feature of global climate change and can cause adverse impacts on crops from germination through maturation and harvest. This review focuses on the impacts of extreme heat (>35 °C) on plants and their physiology and how they affect food and water security. The emphasis is on what can be done to minimize the negative effects of heat stress, which includes the application of various materials and approaches. Nano-farming is highlighted as one promising approach. Heat is often combined with drought, salinity, and other stresses, which together affect the whole agroecosystem, including soil, plants, water, and farm animals, leading to serious implications for food and water resources. Indeed, there is no single remedy or approach that can overcome such grand issues. However, nano-farming can be part of an adaptation strategy. More studies are needed to verify the potential benefits of nanomaterials but also to investigate any negative side-effects, particularly under the intensive application of nanomaterials, and what problems this might create, including potential nanotoxicity.

Multi-criteria decision analysis framework for engaging stakeholders in river pollution risk management

Water pollution presents a substantial environmental challenge with extensive implications for water resources, ecosystem sustainability, and human health. Using a South African catchment, this study aimed to provide watershed managers with a framework for selecting best management practices (BMPs) to reduce pollution and the related risk to river users, while also including the perspectives of key catchment stakeholders. The framework encompassed the identification of and consultation with key stakeholders within the catchment. A Multi-Criteria Decision Analysis (MCDA) methodology using the Simple Multi-Attribute Rating Technique for Enhanced Stakeholder Take-up (SMARTEST) was used to identify and prioritise suitable BMPs in a case study. Decision alternatives and assessment criteria as well as their weights were derived based on stakeholder responses to a two-stage survey. Stakeholders included those utilising the river for domestic and recreational purposes, municipal representatives, scientists, NGOs, and engineers. The assessment of decision alternatives considered environmental, economic, and social criteria. The aggregated scores for decision alternatives highlighted the significance of involving stakeholders throughout the decision process. This study recommends the pairing of structural and non-structural BMPs. The findings provide valuable insights for catchment managers, policymakers, and environmental stakeholders seeking inclusive and effective pollution mitigation strategies in a catchment.

Comparative analysis of geothermal binary ORC systems: performance and environmental considerations for CO2 andwater as geofluids

This study considers the process simulation of geothermal binary Organic Rankine Cycle (ORC) systems which utilizes CO2 and water as geofluids for electricity generation. The simulation was performed using Hysys v11 software by using Peng Robinson’s fluid property package. Two dry working fluids including isopentane and n-pentane, were used. The effects of geofluid temperature and working fluid mass flowrate on power generation, as well as the maximum pressure of working fluids were evaluated. The result showed that power generation increases with higher geofluid temperature due to enhanced heat transfer. Isopentane outperformed n-pentane, attributed to its superior thermodynamic properties. CO2 showed better performance as geofluid than water highlighting its superiority, observed in the increased power generation. The unique characteristics of CO2 enable efficient heat transfer at lower temperatures, making it an environmentally friendly and effective choice. Contrarily, the use of water as a geofluid poses some implications for local ecosystems and water resources. From an environmental perspective, CO2 shows greater potential for reduced environmental impact, which aligns with the transition to cleaner energy sources. However, the economic considerations suggest a trade-off, as CO2 projects may entail higher upfront costs compared to water-based systems. Regulatory factors and economic feasibility, therefore, play a crucial role in the choice of geofluid for geothermal power generation.

Atmospheric and Land Drivers of Streamflow Flash Droughts in India

AbstractStreamflow flash droughts (SFDs), characterized by a rapid decline in streamflow over a relatively short period, affect water availability, hydropower generation, and the ecosystem. However, atmospheric and land processes that drive SFDs in the monsoonal climate of India remain unexplored. Using observations, reanalysis data sets, and model simulations, we examined the critical drivers of SFDs in 64 catchments in India during the 1971–2018 period. We identified meteorological flash droughts (MFDs) using precipitation and SFDs using in situ observations and model simulations of streamflow. We show that precipitation deficit and anomalous high temperature, driven mainly by the summer monsoon breaks, lead to the development of MFDs. Antecedent baseflow conditions play a major role in the propagation of MFDs to SFDs. Favorable atmospheric conditions (driven by the monsoon breaks) cause MFDs, which translate to SFDs. High and low baseflow conditions limit the rapid decline in streamflow, which controls the occurrence of streamflow flash drought. On the other hand, favorable atmospheric conditions combined with moderate baseflow can trigger SFDs in India during the summer monsoon season. Moreover, humid catchments are more prone to propagation from MFDs to SFDs during the monsoon season in India. Understanding the crucial role of atmospheric and land drivers can assist in examining the occurrence of streamflow flash drought with implications for water resources planning and management.

Impacts of recent rainfall changes on agricultural productivity and water resources within the Southern Western Ghats of Kerala, India.

Significant changes in rainfall patterns are critical to agriculture, and the dependency of cropping systems on rainfall variability would engender appropriate farming practices and agriculture policies for a climate-resilient agriculture system. This study analyses the significance of rainfall variability on agriculture productivity in the Wayanad district of Kerala (India) using time series data on rainfall (1989-2019) and crop yield (2000-2019). The spatial variability of rainfall patterns reveals a dichotomy between the rain gauge stations in the northern and southern parts of the region. Despite the absence of statistically significant trends in the monthly, seasonal and annual rainfall, based on the Mann-Kendall trend analysis, an increase in the yield of many crops (e.g., winter paddy, banana) is evident, which emphasises the critical role of irrigation in driving the crop productivity. As an adaptation strategy to changing rainfall patterns, irrigation would meet the additional crop water requirement for sustainable agricultural production under the varying rainfall distributions. However, the increase in the area under irrigation in recent years has had significant implications for both surface water and groundwater resources. The conclusive findings suggest that the region requires climate-resilient agriculture, focusing on optimising irrigation and developing sustainable agriculture and water conservation strategies.

Climate Variability over Southern Africa and Implications for Water Resources: A Review

Climate Variability over Southern Africa and Implications for Water Resources: A Review

Impact of land use/land cover changes on evapotranspiration and model accuracy using Google Earth engine and classification and regression tree modeling

This research uses a Classification and Regression Tree (CART) model with Google Earth Engine (GEE) to assess the winter season’s land cover and change detection mapping impact on the evapotranspiration (crop water requirement) parameters. Winter seasons, crucial for agricultural planning, and irrigation water requirement challenges in accurately mapping land cover and detecting changes due to the dynamic nature of farming practices during this period. In this study, Landsat-8 OLI images have been combined to map Land use and Land cover (LULC) and other change detection mapping in Akola Block, Maharashtra, India, during the 2018–2022 winter season. As an discoverer researcher that found detailed information of LULC classes during last 2018 to 2022 winter seasons, the use of the CART model in combination with a cloud-computing GEE demonstrates to be a practical approach for accurate land cover classification and change detection maps to create a pixel-based winter seasons information of study area. The novelty of this study lies in its innovative use of GEE, a powerful platform for remote sensing and geospatial analysis, to create LULC maps with remarkable accuracy. Achieving a 100% training accuracy across the four years under consideration is an exceptional feat, highlighting the reliability and stability of the methodology. Furthermore, the validation accuracy values, ranging from 89 to 94% for the winter seasons of 2018 to 2022, underscore the robustness of this approach. Such consistently high accuracy in mapping LULC over time is a groundbreaking achievement and offers a new dimension to the field of hydrology. For the hydrological community, the implications of this study are profound. Accurate LULC mapping and change detection provide critical data for modeling and analyzing the effects of land use changes on water resources, watershed management, and water quality. The User, Kappa, and Producer accuracy metrics used in this research highlight the model’s performance and its suitability for hydrological applications. These accurate LULC maps can aid in the development of hydrological models, forecasting, and decision-making processes, ultimately contributing to more effective water resource management and environmental conservation. In summary, this study’s innovative use of GEE, its remarkable accuracy in LULC mapping, and its relevance to the hydrological community demonstrate the potential for advanced remote sensing and geospatial tools to significantly improve our understanding of land use changes and their implications for water resources and environmental management.

Predicting River Discharge in the Niger River Basin: A Deep Learning Approach

Across West Africa, the River Niger is a major source of freshwater. In addition, the river system also provides services such as aquaculture, transportation, and hydropower. The river network plays a critical role in the hydropolitics and hydroeconomics of the region. Therefore, River Niger is integral to the development of West Africa, hence, there is a need to ensure that the river’s ecosystem is a healthy one. In light of the changing climate and its associated threats such as droughts and floods, constant monitoring and measurements of the the river’s flow system cannot be overemphasized. This study investigates temporal variations in annual river discharge characteristics at eight stations (Koulikoro, Dioila, Kirango, Douna, Mopti, Dire, Ansongo, and Niamey) in the Niger River basin, presenting detailed quantitative findings. Analyzing discharge data of River Niger from 1950 to 1990, the minimum discharge measures (minimum and 10th percentile) exhibit a consistent decreasing trend post-1960, persisting into the 1990s at several stations. Central tendency measures (mean and 50th percentile) also consistently reduced since 1950, with near-zero median values observed in Diola and Douna. Recovery in mean discharge is evident in Ansongo after 1980. Extreme values (maximum and 90th percentile) show decreasing trends across all stations, with some locations exhibiting a slight recovery after 1980. The decreasing trend in annual minimum, mean, and maximum values has implications for water resources, affecting hydroelectric generation, fish farming, and dry season irrigation. Machine learning algorithms (MLAs) are deployed to predict the prediction of monthly river discharge, with LSTM identified as the best-performing model overall. However, model performance varies across locations, with TCN excelling in Diola but underperforming in Koulikoro. This study emphasizes the chaotic nature of time series data and external drivers limiting the long-term predictive capabilities of MLAs. Quantitative evaluation of MLA performance reveals specific strengths and weaknesses at each station. This study underscores the importance of predicting the 10th percentile of annual river discharge for water resource planning. Models exhibit diverse performance across basins, emphasizing the need for tailored approaches. Further analysis considers measures of central tendencies, predicting the 50th percentile (Q50) and mean discharge values. TCN emerges as the best model for Q50 prediction, showcasing superior performance over other models. Additionally, the study delves into predicting high and low extreme discharges, crucial for understanding potential flood events and preparing for meteorological and hydrological droughts. This study concludes by emphasizing the necessity for location-specific studies in the River Niger basin to facilitate an enhanced integrated river management system.

Analyzing the Impact of Rainfall Patterns on Agriculture, Economy and Tourism in India: A Statistical Approach

The current study examines rainfall trends in India, encompassing its effect on various economic aspects and forecasting for 2023-2030. The Mann-Kendall test and Sen’s slope estimator are utilized to analyze annual and seasonal rainfall patterns. Results reveal a pronounced winter decline (2001-2022) alongside significant pre- monsoon, monsoon, and post-monsoon increases. Annual rainfall consistently de- creases, contrasting with rising pre-monsoon, monsoon, and post-monsoon trends. Annual rainfall exhibits the steepest decline (-1.0891 mm/year), while the monsoon season displays the highest increase (3.2538 mm/year). Further, the present study explores relationships between rainfall and economic growth, tourism, and agriculture. A statistically insignificant yet positive correlation is found between annual rainfall and per-capita GDP, indicating other economic drivers. Tourism shows a weak, statistically insignificant link with annual rainfall. In contrast, a robust statistically significant correlation emerges between annual rainfall and food- grain production, highlighting its role in agriculture. Finally, the present research forecasts annual rainfall (2023-2030) using the ARIMA (1,0,0) model, predicting a continued decline. This has profound implications for water resources, agriculture, and the economy, necessitating proactive measures such as water conservation, drought-resistant farming, and alternative energy investments.

Characterising the regional growth of on-farm storages and their implications for water resources under a changing climate

Water demand for agricultural activities has caused a growth in small on-farm storages (i.e., ≥ 0.1 ha to ≤ 10 ha) in many areas worldwide, thereby increasing the capture of landscape runoff which otherwise would enter the catchment drainage system. The cumulative effects of these on-farm storages (colloquially known as farm ponds or farm dams) can result in reduced mean annual flows, particularly during dry years. Climate change, which will very likely exacerbate extreme weather conditions including droughts, may accelerate the growth of farm dams in semi-arid agricultural areas with limited access to surface water. The aim of this study is to evaluate farm dam development and total farm dam water volumes at regional scales using Landsat water indices (WIs). The Murray-Darling Basin (MDB, 1.061 million km2) in south and eastern Australia, which has experienced a sustained growth in farm dams in the 1990s and early 2000s, is used as a case study. Using a pixel validation dataset, four WIs were trialled for their capabilities to detect the presence of water in farm dams. Of the WIs tested here, AWEIshadow showed the best performance. As a result, AWEIshadow was used to establish the year in which water was first observed (i.e., its year of commission) in 727,081 farm dams across the MDB and to calculate the total farm dam volume in the region. Farm dams’ volume in the MDB increased more than twofold between 1990 and 2020, from 1241.0 MCM (million cubic meters) to 2,629.5 MCM. The growth differed across MDB regions, generally accelerating during the ‘Millennium Drought’ (2001–2009). In the entire MDB, there was rapid development in the 1990s with 3.1% growth. Growth was 2.5% from 2000 to 2010, tapering off to 0.6% from 2010 to 2020.In Robertson et al. (this issue), the year-by-year growth in farm dams’ volume were used in a rainfall-runoff model thereby incorporating the time-varying effects of farm dams. Robertson et al. (this issue) show that explicitly modelling farm dams improves the model’s performance relative to a traditional rainfall-runoff model that ignores the effects of farm dams. Hence, this improves the capability of assessing the direct impacts of farm dams and their potential growth in climate change studies.