Surface Water Availability Research Articles

Unlocking the mysteries of drought: integrating snowmelt dynamics into drought analysis at the Narayani River Basin, Nepal

AbstractDrought is among the most impactful natural hazards, undermining water security, agriculture, and livelihoods worldwide. Analysing droughts in large catchments presents several unique challenges, primarily related to the complexity of land surface characteristics and data availability limitations. Conducting drought analysis in the Narayani River Basin, which encompasses a vast area within the Himalayan region of Nepal, is extremely challenging but crucial for maintaining the river basin's social, economic, and environmental balance. In response, this study develops a new combined drought index (CDI), integrating satellite-based reanalysis parameters [i.e., Land Surface Temperature (LST), Snow Cover (SC), and Normalised Difference Vegetation Index (NDVI)] with a meteorological parameter [i.e., Standardised Precipitation (std_prec)]. The novel CDI was applied at the Narayani Basin to assess the droughts over the 2004–2013 period, and the results were independently evaluated using streamflow observations to validate the accuracy of the novel drought index. The principal component analysis (PCA) technique was used to determine the contribution of input parameters to the multivariate drought index. The PCA results show a strong positive correlation (0.78) between the CDI and standardised streamflow, indicating the effectiveness of the novel index in monitoring drought conditions. Accordingly, it can be concluded that surface water availability is interdependent on landscape characteristics, such as LST, SC, and NDVI, in addition to the effects of precipitation. Also, the novel CDI can identify the specific drought-affected areas in the Narayani River Basin, offering insights into its drought characteristics beyond traditional drought assessment techniques.

Species distribution modeling of North American beavers from the late Pliocene into the future

Abstract Beavers have occurred in North America since at least 7 Ma, but relatively little is known about their distribution across the continent. We modeled distributions of beavers in the late Pliocene (3.3 Ma), Pleistocene (130 ka and 21 ka), and recent Holocene (1970 to 2000) to understand their dispersal across North America, predict future distributions and predict their possible response to future climate and habitat changes. Occurrence data for Castor canadensis were derived from the Global Biodiversity Information Facility. Those data were used with both modern (1970 to 2000) and modeled future (EC-Earth-Veg 2081 to 2100) bioclimatic variables from WorldClim as well as past (Pliocene Marine Isotope Stage M2, Pleistocene Last Interglacial, and Pleistocene Last Glacial Maximum) bioclimatic variables from PaleoClim to model beaver distributions through time. Fossil locality points for Castor extracted from the New and Old Worlds Database of Fossil Mammals (NOW), NEOTOMA Paleoecology Database, and Paleobiology Database were overlain on past projection models to use as validation points. Models were run using MaxEnt with post-processing in ArcGIS. Accuracy for the 5 models ranged between 59.6% and 60.2%. Results for the present model (1970 to 2000) showed habitat suitability in areas beavers inhabit today. During the Pliocene MIS M2 cooling event (3.3 Ma) and Pleistocene Last Glacial Maximum (21 ka), habitat suitability shifted further south into Mexico and peninsular Florida and away from more periglacial northern regions. During the Last Interglacial period (130 ka) and modeled future (2081 to 2100) EC-Earth-Veg 2081 to 2100, habitat suitability was higher in coastal and central regions in North America and lower in southern regions compared to their present distribution. Distributions were most affected by precipitation seasonality, isothermality, and mean annual temperature. High variability in seasonal precipitation and temperatures is likely to influence surface water availability, vegetation type, and riparian vegetation composition, which consequently may reduce available food resources and habitat for beavers. Observed shifts during warmer periods may indicate areas in the late Miocene that facilitated dispersal into North America. Future models using other predicted climatic scenarios and shared socioeconomic pathways may provide better resolution of potential future shifts in beaver distribution with best- and worst-case climate scenarios, thereby permitting at-risk areas to be prioritized for conservation in the face of climate change.

Regional-scale seasonal forecast of surface water availability in a semi-arid environment: The case of Ceará State in Northeast of Brazil

Study region:Ceará (Brazil). Study focus:Considerable intra- and inter-annual variability of rainfall in this semi-arid region lead to strong temporal variations in water availability. To store and supply water in times of water scarcity, tens of thousands of freshwater reservoirs have been built over time, most of which are unmonitored. Here, we develop a hydrological forecasting system for the entire state of Ceará which integrates satellite-based monitoring of reservoir water storage, bias-corrected seasonal weather forecasts and hydrological modeling of freshwater availability. We test and demonstrate the applicability of this system by conducting experiments with historic data, hindcasts and forecasts. New hydrological insights for the region:The assimilation of in-situ and Sentinel-1 based observations of reservoir fillings into the hydrological model WASA-SED proved to be feasible and an important step in the modeling of available water resources dynamics. Hydrological simulations for January to June from 1990–2019 based on meteorological observations resulted in a median average NRMSE between observed and modeled reservoir fillings of strategic reservoirs of 29.51%. The comparison of observed and predicted precipitation from two different seasonal forecasting systems were in the same order of magnitude (i.e. 19.51% and 24.52%). Hindcast experiments suggested the superposition of uncertainties of different model components. Efforts are currently being made to further test and improve the developed integrated framework as part of the operational service.

GIS-based multi-criteria approach for ranking suitable areas for the implementation of PV-Powered MCDI desalination plants in the Rheris Watershed, Southeast Morocco

In Morocco's oases, which rely heavily on surface water from mountain sources, the threat of decreasing rainfall presents a significant challenge, leading to a decline in surface water availability. This study focuses on the Rheris Watershed in Southeast Morocco, where brackish water desalination emerges as a viable alternative to ensure sustainable water supply for agriculture. Prior to the deployment of a pilot plant integrating a desalination unit, selecting an optimal site for PV-powered MCDI desalination plants was critical. This selection was based on a range of criteria, including Groundwater Quantity, Global Horizontal Irradiation, Temperature, Evaporation, Water Salinity, Water Quantity, Well Density and Slope. These criteria were evaluated using a combination of the Analytical Hierarchy Process (AHP), and geospatial data obtained from Remote Sensing (RS) and Geographic Information System (GIS) techniques.This case study in the Rheris watershed identified potential sites for future Membrane Capacitive Deionization (MCDI) desalination projects, High suitability areas encompass 280.45 km² (30.91 %), located west of Tinejdad, Khettarat Moulay Hachem, north of Goulmima, and south of Tinghir. Low suitability areas cover 63.75 km² (7.02 % of the study area), including regions south of Tadighoust and Tinejdad. Moderate suitability areas span 562.86 km² (62.05 %), involving central regions of Goulmima, Tadighoust, Tinejdad, and Tinghir. Based on the results of the study, the recommendations include focusing on areas identified as highly suitable for MCDI technology for sustainable agriculture, refining selection criteria based on local data, exploring brine management strategies, and adopting integrated water management approaches to ensure sustainable resource use.

Spatiotemporal evolution and driving mechanism of Dongting Lake based on 2005–2020 multi-source remote sensing data

As one of the largest inland lakes in China, Dongting Lake has attracted widespread attention owing to its rich natural resources, unique geographical landscape, and important ecological functions. Recently, Dongting Lake has experienced phenomena such as an early dry season and backflow during the flood season. Multi-source remote sensing data and the normalised difference water index (NDWI) threshold method were used to systematically analyse the water area of the lake from 2005 to 2020. Additionally, it employed a centre of gravity migration model and a geographic detector model to investigate the lake's evolution patterns and driving mechanisms. The research identified notable fluctuations in Dongting Lake's water area during this period, with a particularly sharp decline in 2006—from 1509.74 km2 to 815 km2, marking a decrease of 694.74 km2 and a shrinkage rate of 46.01 %. Spatial analysis indicated that the centre of gravity of these water areas changed primarily between Nandashan Town, the Dongting Lake Management Committee, Wanzihu Township, and Qingtan Township, underscoring their significant influence on lake dynamics, including runoff, surface water availability, sediment deposition, and precipitation, all of which displayed strong positive correlations (Pearson coefficients of 0.57, 0.68, and 0.63, respectively), whereas population density showed a negative correlation (Pearson coefficient of −0.56). Furthermore, the study highlighted the substantial impact of the Digital Elevation Model (DEM) and its interaction with slope and aspect on Dongting Lake's evolution, with Q values of 0.537 and 0.543, respectively, emphasising their critical roles in shaping lake area changes and providing a crucial scientific basis for enhancing the understanding and effective management of water resources in the Dongting Lake Basin through comprehensive analysis of its spatiotemporal evolution and driving mechanisms.

Application of machine learning and fuzzy AHP for identification of suitable groundwater potential zones using field based hydrogeophysical and soil hydraulic factors in a complex hydrogeological terrain

The eastern section of West Bengal grapples with limited surface water availability in its hard rock terrain, compounded by a semi-arid climate, variable rainfall, and a plateau topography, prompting communities to adapt groundwater water-use practices, leading to unsustainable extraction and misuse. Thus, the novel objective of the present research was to produce groundwater potential maps by comparing machine learning techniques with a Fuzzy MCDM model using specific field-based conditioning factors. In the first step, 285 wells were identified, of which 70 percent were used for training and 30 percent for the validation of the models. Secondly, field-based conditioning factors including, longitudinal conductance (SC), longitudinal resistance (ρl), transverse resistance (TR), coefficient of electrical anisotropy (λ), resistivity of formation (ρm), fracture porosity (φf), reflection coefficients (r), hydraulic conductivity (K), transmissivity(Tr), bulk density, porosity, permeability, soil moisture content and water holding capacity were used to analyze the association between these conditioning factors and groundwater occurrences. In the following steps, the XGBoost, Random Forest, and Naïve Bayes models were executed using the training dataset, and factor weights were calculated using Fuzzy Analytical Hierarchy Process of Extent analysis method. To validate and compare the performance of four models, ROC curves, AUCs, MCAs, and correlation plots were used. In general, all four models were successful in evaluating the potential of groundwater occurrences. The predictive capability of the XGBoost techniques with the highest AUC values (0.79) and the highest correlation value (0.78) is superior to those of other machine learning and MCDM models. Geophysical survey revealed that transmissivity and hydraulic conductivity of the aquifer of the river basin range from 1.55 to 440.11 m/day and 10.15–2253 m2/day, indicating a moderate to good hydrodynamic potential. Planners and engineers can use such groundwater potential maps to manage water resources effectively.

Climate Regimes across the Habitable Zone: A Comparison of Synchronous Rocky M and K Dwarf Planets

M and K dwarf stars make up 86% of the stellar population and host many promising astronomical targets for detecting habitable climates in the near future. Of the two, M dwarfs currently offer greater observational advantages and are home to many of the most exciting observational discoveries in the last decade. But K dwarfs could offer even better prospects for detecting habitability by combining the advantages of a relatively dim stellar flux with a more stable stellar environment. Here we explore the climate regimes that are possible on Earth-like synchronous planets in M and K dwarf systems, and how they vary across the habitable zone. We focus on surface temperature patterns, water availability, and implications for habitability. We find that the risk of nightside cold trapping decreases with increased orbital radius and is overall lower for K dwarf planets. With reduced atmospheric shortwave absorption, K dwarf planets have higher dayside precipitation rates and less day-to-night moisture transport, resulting in lower nightside snow rates. These results imply a higher likelihood of detecting a planet with a moist dayside climate in a habitable “eyeball” climate regime orbiting a K dwarf star. We also show that “terminator habitability” can occur for both M and K dwarf land planets, but would likely be more prevalent in M dwarf systems. Planets in a terminator habitability regime tend to have slightly lower fractional habitability, but offer alternative advantages including instellation rates more comparable to Earth in regions that have temperatures amenable to life.

Impacts of forest canopy heterogeneity on plot-scale hydrometeorological variables - Insights from an experiment in the humid boreal forest with the Canadian Land Surface Scheme

High latitude regions, including the circumpolar boreal biome, are experiencing important changes in the availability of usable surface water because of climate change. In this context, an adequate representation of the land-atmosphere interaction is critical to ensure optimal management of current and future water resources, forest management, and climate prediction. However, the task is particularly intricate in high-latitude boreal forest, as land surface model faces several challenges due to the unique environmental conditions and ecological characteristics. The objective of this study is to quantify the impact of forest landscape heterogeneity, specifically stand leaf-area index (LAI), soil texture, and drainage regime, on surface water and energy balance in a small boreal high-latitude sub-catchment. To this end, hydrometeorological conditions at seventeen 20×20 m plots in a 1-km2 boreal forest sub-basin are simulated using the Canadian Land Surface Scheme (CLASS), a land surface model, at the point scale. The subplot-scale soil texture, drainage regime, and vegetation characteristics and type are based as closely as possible on field measurements and observations for the 17 plots. The model-driven experiment comprises two sets of simulations using CLASS, each employing the same model setup and run for the 17 experimental plots. The main set employs meteorological forcing from a local micrometeorological tower within the sub-basin to investigate the plot-to-plot variability of albedo, energy fluxes, and soil state variables. A second set of simulations is conducted using meteorological forcing from the ERA5-Land reanalysis, which spans from 1986 to 2022. This data provides a longer time series, enabling a more accurate representation of the interannual climatic variability in the sub-basin. The results of the main and secondary sets of CLASS simulations are used to assess the plot-to-plot and temporal variability of several key hydrometeorological variables by calculating a monthly spread. In brief, the following conclusions and broader implications can be drawn from the findings: i) The simulated total annual evapotranspiration remains relatively uniform between plots despite notable variation in its partitioning from plot to plot. ii) In the presence of a full snowpack, the albedo exhibits substantial heterogeneity at the subplot scale, linked to the canopy's LAI. iii) Local soil properties, drainage regime, and vegetation structure and type exhibit substantial influence on the plot-to-plot variability in soil water content. iv) When parameterized with localized observations and measurements, CLASS can represent and be responsive to the complex dynamics of energy and water fluxes at the plot scale within the heterogeneous surface of boreal forests.

Long-term trends in human-induced water storage changes for China detected from GRACE data

Terrestrial Water Storage (TWS) plays a pivotal role in water resource management by providing a comprehensive measure of both surface water and groundwater availability. This study investigates changes in TWS driven by human activities from 2003 to 2023, and forecasts future TWS trends under various climate change and development scenarios. Our findings reveal a continuous decline in China's TWS since 2003, with an average annual decrease of approximately 1.36 mm. This reduction is primarily attributed to the combined effects of climate change and human activities, including irrigation, industrial water use, and domestic water consumption. Notably, TWS exhibits significant seasonal and annual fluctuations, with variations ranging ±10 mm. For the future period (2024–2030), we project greater disparities between water resource supply and demand in specific years for the Songliao, Southwest, and Yangtze basins. Consequently, future water resource management must prioritize water conservation during wet seasons, particularly in years when supply-demand conflicts for limited water resources intensify. This study is valuable for effective planning and sustainable utilization of water resources.

Water-suitable reclamation can mitigate the amplified agricultural water stress driven by climate change in arid inland basin

The escalation of water scarcity poses a significant challenge to the sustainability of irrigated agriculture in arid regions, with climate change further amplifying the unpredictability of water resources for agricultural purposes. Despite the critical nature of this issue, there is a lack of research identifying effective adaptation strategies and establishing water-suitable thresholds for agricultural development. This study modified a conventional approach for estimating irrigation water use (IWU) in the Heihe agricultural area of Northwest China, integrating the distributed hydrological components of the Soil and Water Assessment Tool (SWAT) model. It modeled IWU and surface water availability across three representative concentration pathways (RCPs) and conducted an extensive analysis of agricultural water scarcity for the period 2021–2050. The study established threshold levels for water-suitable agricultural development based on predicted local water resource conditions. Findings suggested a trend towards warmer and wetter conditions in the Heihe agricultural area over the next three decades. The anticipated average IWU, predicted by five general circulation models (GCMs), was expected to reach 26.785 × 108 m3 (RCP2.6), 26.827 × 108 m3 (RCP4.5), and 26.865 × 108 m3 (RCP8.5). These projections indicated an increase of 0.815 × 108 m3, 0.857 × 108 m3, and 0.895 × 108 m3, respectively, in comparison to the historical period spanning from 1985 to 2014. Streamflow was anticipated to diminish by 0.28 × 108 m3 (RCP2.6), 0.46 × 108 m3 (RCP4.5), and 0.23 × 108 m3 (RCP8.5). The predicted agricultural water scarcity index (WSI) was 1.764 (RCP2.6), 1.789 (RCP4.5), and 1.763 (RCP8.5), indicating a worsening of agricultural water use shortages due to climate change. The study identified controlling the scale of cultivation as the most effective adaptation strategy, recommending that water-suitable agricultural reclamation in the Heihe agricultural area be confined to 25 × 104 ha. This research offers a comprehensive assessment of future water security in an arid inland basin, providing valuable insights into the sustainable development of global irrigated agriculture and adaptation strategies in response to climate change.

Assesement of Surface Water Availability of Kathmandu Valley Using SWAT Model

The study used the Soil and Water Assessment Tool (SWAT) model to analyse the surface water availability in the Kathmandu Valley. The model was calibrated and validated at Khokana station of basin area 592 km2 for the period from 2000 to 2015. To test the model’s performance for smaller subbasins, it was validated at Sundarijal station of basin area 16 km2. The daily runoff simulation statistics indicated that the model’s performance was satisfactory and the model effectively captured the runoff trend for the entire basin and subbasin catchment areas. This study demonstrates that the model can be adopted for assessing stream flow within the basin by selecting appropriate parameter values. The calibrated and validated model was subsequently applied to determine the surface water availability in surrounding mountainous, forested regions less affected by urbanisation, by setting up the model at 66 watersheds. The results indicate that the upper reaches of the Bagmati River basin and its tributary, the Nakkhu River, possess substantial surface water resources that can be utilised to alleviate water stress in the valley.

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

Spatial patterns of valley network erosion on early Mars

Fluvial valley networks are a key record of the geomorphic effects of past liquid water on the surface of Mars. Most valley networks formed early in Mars history (>3.5 Ga) during a period of increased surface water availability, and these landforms may preserve information on the nature and spatial heterogeneity of the ancient martian hydroclimate. Here we present work to constrain patterns of valley network geometry (length, depth, and volume), and assess how these factors are related to topography and landscape position. We find that valley depth is most strongly controlled by regional slope and landscape relief, with deeper valleys on steeper/higher relief terrains, likely driven by a slope control on the rate of fluvial erosion. In contrast, total valley length and volume are most controlled by slope orientation, with larger values on north-draining slopes, which we suggest is related to more efficient fluvial integration (i.e., inter-connection of valleys) on such slopes. At lower elevations and towards terminal basins (northern plains and Hellas), valley depth increases, while total valley length and volume decrease, consistent with the geometry expected as a branching valley system converges downstream into fewer, larger valleys. Finally, we show that patterns of total valley length and eroded volume peak about a previously proposed paleo-latitude band on a pre-Tharsis-driven true polar wander Mars. Valley depth increases from paleo-south to paleo-north in this pre-true polar wander framework, consistent with valley network development in a paleo-north direction. This is potentially consistent with syn/pre-Tharsis growth and true polar wander valley network incision; however, this signal is not unique and may be amplified by patterns of post-valley network incision resurfacing.

Techno-Economic Analysis of Atmospheric Water Harvesting Across Climates.

Drinking water scarcity is a global challenge as groundwater and surface water availability diminishes. The atmosphere is an alternative freshwater reservoir that has universal availability and could be harvested as drinking water. In order to effectively perform atmospheric water harvesting (AWH), we need to (1) understand how different climate regions (e.g., arid, temperate, and tropical) drive the amount of water that can be harvested and (2) determine the cost to purchase, operate, and power AWH. This research pairs thermodynamics with techno-economic analysis to calculate the water productivity and cost breakdown of a representative condensation-based AWH unit with water treatment. We calculate the monthly and annual levelized cost of water from AWH as a function of climate and power source (grid electricity vs renewable energy from solar photovoltaics (PV)). In our modeled unit, AWH can provide 1744-2710 L/month in a tropical climate, 394-1983 L/month in a temperate climate, and 37-1470 L/month in an arid climate. The levelized cost of water of AWH powered by the electrical grid is $0.06/L in a tropical climate, $0.09/L in a temperate climate, and $0.17/L in an arid climate. If off-grid solar PV was purchased at the time of purchasing the AWH unit to power the AWH, the costs increase to $0.40/L in an arid climate, $0.17/L in a temperate climate, and $0.10/L in a tropical climate. However, if using existing solar PV there are potential cost reductions of 4.25-5-fold between purchasing and using existing solar PV, and 2-3-fold between using the electrical grid and existing solar PV, with the highest cost reductions occurring in the tropical climate. Using existing solar PV, the levelized cost of AWH is $0.09/L in an arid climate, $0.04/L in a temperate climate, and $0.02/L in a tropical climate.

Устойчивое использование водных ресурсов в междуречье Нура-Есиль (Казахстан) для развития сельских районов

Research is related to need to assess the availability of agricultural production with water resources and their rational use. These issues are considered on the example of assessing the water supply of rural areas of the flat interfluve of the Nura-Yesil rivers, located within the suburban area of Astana. In accordance with regional programs, the suburban area should provide a significant part of the needs of the capital with agricultural products. These plans have not been implemented in recent years due to a number of reasons, the main of which is the increased risk of flooding of the territory between the rivers by spring flood waters. In accordance with the above, the purpose of the research was to assess the resources and water availability of surface water in the interfluve of the Nura-Yesil rivers, as a determining factor in land use and the security of rural development. The object of the study was the surface waters of the interfluve with the channels of the Sarkyrama, Mukkyr and Kozgosh, through which during the spring flood the waters of the Nura River are discharged into the Yesil River.

Role of Surface Energy Fluxes in Urban Overheating Under Buoyancy‐Driven Atmospheric Conditions

AbstractUrbanization alters land surface properties in absorbing, reflecting and emitting radiation as well as infiltrating, evaporating and storing water. This consequently modifies surface energy and water fluxes and, thus, urban climates. Weak synoptic flow, clear sky conditions and higher surface temperatures in cities compared to their rural surroundings create a buoyancy‐driven atmospheric circulation, in which surface energy fluxes become the main determinants of urban daytime overheating. Here, we demonstrate the role of surface energy fluxes for warming and cooling processes in the urban canopy layer under buoyancy‐driven atmospheric conditions. We improve and apply an integrated CFD‐GIS modeling approach to provide a detailed analysis of fine‐scale land‐atmosphere interactions and assess the surfaces' profound implications on energy and water exchange. We show that variations in the ratios of the surface energy fluxes to the net radiation can be separated from meteorological conditions (wind speed, air temperature and incoming solar radiation) and emissivity values, varying explicitly with changes in land surface type and water availability for vegetated areas. Based on the energy flux ratios, we introduce an approach to assess the surface‐induced warming and cooling effect and its contribution to urban overheating in the urban canopy layer, under buoyancy‐driven atmospheric conditions, directly applicable to strategic urban planning for climate change adaptation. Independent of meteorological conditions, this approach can be used to evaluate different surface materials (both natural and artificial) and climate adaptation measures, such as urban nature‐based solutions and blue‐green infrastructures, and to monitor changes in the energy and water balance.

Reducing Sedimentation in Catchment Areas as Part of the Revitalization Efforts at Batujai Reservoir in Central Lombok

This research discusses efforts to revitalize the Batujai Reservoir in Central Lombok with a focus on sedimentation problems. Batujai Reservoir has a strategic role in meeting water needs in the surrounding area, but faces serious challenges due to significant sedimentation. In addition to assessing the effects of these changes on the reservoir's benefits�such as irrigation, flood control, and electricity production�this study intends to examine the effects of land use changes in the Dodokan Sub-Watershed Catchment Area (DTA) on the features and volume of sedimentation entering the reservoir. In addition, this study attempts to develop suggestions for efficient sedimentation management plans in order to increase the Batujai Reservoir's service life. Research methods include primary and secondary data collection, sedimentation modeling using the Water and Tillage/Sediment Delivery Model (WATEM/SEDEM), to evaluate the impact of sediment control structures such as check dams. Research variables include catchment area, population, annual rainfall, average daily evaporation, mainstay surface water availability, land surface erosion rate, sediment volume deposited in the reservoir, effective age of the Batujai Reservoir, and changes in land use in the Dodokan Sub-watershed. The results of this research will provide a better understanding of the main sources of sedimentation in the Batujai Reservoir and the impact of land use changes on the reservoir. It is hoped that the recommendations for sedimentation management strategies resulting from this research will help maintain reservoir storage capacity, which is important for meeting various water needs in the region.

Investigation and Evaluation of Aquiferous Zones Within Orlu and Its Environs, Using a Geo-electrical and Physiochemical Approach

This study investigated the suitability of drinking water in Orlu, Nigeria, facing challenges due to limited surface water availability and environmental deterioration. To solve the problem of the availability of portable water, electrical resistivity surveys using a Schlumberger array were conducted to identify potential groundwater resources. Twelve locations were assessed, revealing resistivity values indicative of potential aquifers. Following the geophysical survey, the physicochemical properties of water samples collected from various locations were analyzed. Parameters including pH, dissolved oxygen (DO), total dissolved solids (TDS), and minerals were evaluated against WHO and Nigerian drinking water standards. The analysis indicated generally good water quality across the sampling sites. pH levels were within the recommended range, and DO concentrations met the minimum requirements. Similarly, TDS and BOD values suggested low levels of organic matter and dissolved solids. Mineral content also remained below WHO-permissible limits. A Water Quality Index further confirmed that the water quality within the study area can be graded from good to excellent in quality. These findings suggest that the groundwater resources identified in the study hold promise for providing safe drinking water in Orlu and its environs.

Characterizing streamflow regimes using a distributed model for sustainable resource management in the humid tropics

Estimating streamflow regimes on small tropical islands is challenging due to limited observational data, poor accuracy of remote sensing, and the limitations of coarse-scale climate models, restricting our understanding of hydrological processes and the management of water resources. The inadequacy of data has also affected the development of instream flow standards (i.e., environmental flows, e-flows) needed to protect ecological and cultural values central to island communities. Estimates of water availability for agriculture, hydropower, and drinking water supply are also critical for informed investments in water resource planning. We utilized high-resolution (250 m) gridded daily rainfall data to parameterize the Soil and Water Assessment Tool (SWAT) to characterize streamflow regimes at ungauged locations in a watershed on Kaua‘i Island. The resultant flow statistics were then used to describe the daily, seasonal, and annual availability of surface water to evaluate the implications of potential e-flow scenarios on water available for run-of-river hydropower. Compared to rainfall data derived from a single station within the watershed, the gridded daily rainfall product increased the accuracy of model output from not satisfactory to good. Model techniques using high resolution rainfall data may substitute for long-term hydrological data collection across complex tropical environments and provide data for making sustainable management decisions at ungauged locations.

Future malaria environmental suitability in Africa is sensitive to hydrology.

Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths.