Semi-arid River Basin Research Articles

Health hazards from perchlorate enriched groundwater of a semi-arid river basin of south India and suggesting in-situ remediation through Managed Aquifer Recharge

The present study was conducted to assess the groundwater quality and perchlorate contents in the pre- and post-monsoon groundwater samples along with its associated health concerns with suggesting in-situ remediation in semi-arid Arjunanadi River basin of south India. Most of the samples (86 in pre-monsoon and 84 in post-monsoon out of total 94) showed secondary salinity and secondary alkalinity, and the perchlorate showed positive relations with Na+, K+, SO42-, Cl-, and NO3- contents. The main source of perchlorate could be fireworks manufacturing industries with 23 % of pre-monsoon (246.5 km2) and 33 % of post-monsoon samples (360 km2) showing perchlorate above the World Health Organization (WHO) standard (>0.07 mg/l). Perchlorate health risk assessment (PHRA) and total hazard index (THI) indicated more effect from oral pathway compared to the dermal pathway with about 80 %, 79 %, 65 %, and 60 % of samples causing health complications for infants, children, women, and men during the pre-monsoon. The post-monsoon groundwater showed increased health risks with 90 %, 82 %, 74 %, and 69 % of samples remaining hazardous for infants, children, women, and men. Artificial recharge through Managed Aquifer Recharge (MAR) techniques in the high-risk area could be useful to minimize the perchlorate contamination in groundwater and associated health risks under the United Nations Development Programme (UNDP) Sustainable Development Goals 3 and 6 (SDGs) for a healthy society.

Optimizing sustainable development in arid river basins: A multi-objective approach to balancing water, energy, economy, carbon and ecology nexus

The ongoing water crisis poses significant threats to the socioeconomic sustainability and ecological security of arid and semi-arid river basins. Achieving Sustainable Development Goals (SDGs) within a complex socio-ecological nexus requires effective and balanced resource management. However, due to the intricate interactions between human societies and environmental systems, the tradeoffs and synergies of different SDGs remain unclear, posing a substantial challenge for collaborative management of natural resources. Here we introduce a gray fractional multi-objective optimization (GFMOP) model to balance multi-dimensional SDGs through a novel water–energy–economy–carbon–ecology nexus perspective. The model was applied to a typical arid river basin in Northwest China, where thirty-two scenarios were explored, considering factors such as shared socioeconomic pathways, carbon removal rates, water conveyance efficiencies, and ecological requirements. The results reveal a strong tradeoff between marginal benefit and carbon emission intensity, indicating that improving the economic efficiency of water use can simultaneously reduce emissions and protect the environment. Given the immense power generation potential, wind power development should be prioritized in the future, with its share in the energy structure projected to increase to 23.3% by 2060. Furthermore, promoting carbon capture technologies and expanding grassland coverage are recommended to achieve regional carbon neutrality, contributing 39.5% and 49.1% to carbon absorption during 2021–2060, respectively. Compared with traditional single-objective models, GFMOP demonstrates a superiority in uncovering interrelationships among multiple SDGs and identifying compromised alternatives within the compound socio-ecological nexus. The model also provides detailed strategies for resource allocation and pollutant control, offering valuable guidance to policymakers and stakeholders in pursuing sustainable and harmonious watershed management.

Semi-arid rather than arid regions of China deserve the priority in drought mitigation efforts

The integration of drought assessment, mitigation priority analysis and mitigation measures development is a forward-looking strategy to achieve water resources allocation, implement anti-drought techniques and formulate corresponding mitigation measures strategies. However, since most drought indices cannot be based on surface water-balance to estimate water demand for drought recovery, there is a gap between drought assessment and proactive drought mitigation. Here, we established the Standardized Water Availability Index (taking water yield as surface water deficit/surplus) to identify hydrological drought, and further use it to determine the water demand for hydrological drought mitigation. On that basis, a comprehensive framework, integrating with drought assessment-resilience-recovery and water scarcity stress, was proposed to investigate the hydrological drought mitigation priority for basins in different climate regions in China. The results show that non-humid river basins have greater water scarcity stress, lower resilience to hydrological drought, but less water demand for hydrological drought mitigation (3 mm ∼ 7 mm in mild drought, 5 mm ∼ 14 mm in moderate drought, 7 mm ∼ 21 mm in severe drought). In contrast, humid river basins have greater water demand for hydrological drought mitigation (15 mm ∼ 49 mm in mild drought, 27 mm ∼ 93 mm in moderate drought, 32 mm ∼ 119 mm in severe drought), but higher resilience to hydrological drought. The densely populated semi-arid river basins in China should be given priority attention in mitigating hydrological drought on account of their greatest water scarcity stress, lower drought resilience, and less water demand for drought mitigation. This work highlights the complexity of the hydrological drought mitigation, and our findings can help stakeholders to make precise drought mitigation measures and adapt drought-relative water management.

Drought evaluation using various evapotranspiration models over semi-arid river basins

ABSTRACT Multivariate drought indices including various hydrological processes into account can be more valuable under climatic and anthropogenic changes. Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized precipitation Actual Evapotranspiration Index (SPAEI) are the drought indices used to estimate drought index, considering precipitation, and evapotranspiration (ET) into account. Many studies used empirical, machine learning, and process-based model estimates of ET for the calculation of drought indices of SPEI and SPAEI. However, the sensitivity of ET estimates on drought characteristics at the catchment scale is highly complex. The present study aimed to include and analyze the sensitivity of various approaches of empirical (Budyko, Penman–Monteith, Hargreaves, and Turc), modeled (SWAT), and remote sensing (MODIS) in the drought characterization using SPEI and SPAEI. The present methodology was tested on a dry-sub-humid river catchment of India, the Tunga-Bhadra River catchment for the period of 2000–2012. The performance of statistical indicators (Nash–Sutcliffe Efficiency and R2) for SPEI values by various empirical methods of Potential Evapotranspiration (PET) (i) Penman–Monteith (ii) Hargreaves against remote sensing PET were 0.93 and 0.95, respectively, which are high in comparison with SWAT simulated PET-based SPEI values, which shows NSE values of 0.85 against remote sensing PET-based SPEI.

Comparative evaluation of meteorological and hydrological drought using stationary and non-stationary indices in a semi-arid river basin in India

Comparative evaluation of meteorological and hydrological drought using stationary and non-stationary indices in a semi-arid river basin in India

Evaluation of the impact of anthropogenic storage on the hydrological drought propagation in two contrasting semi-arid river basins

ABSTRACT This study quantitatively investigated reservoir-effects on drought propagation in two semi-arid river basins: India’s Tapi basin with the Ukai reservoir and Uzbekistan’s Chirchik basin with the Charvak reservoir. Meteorological drought (MD) is analyzed using the Standardized Precipitation Index (SPI) and hydrological drought (HD) using the Standardized Streamflow Index (SSI) for the duration from 1980 to 2004. Both the river basins, especially in upstream reservoir areas, exhibited a notable correlation between HD and MD. Reservoir operation was observed to reduce the downstream MD–HD correlation at shorter SPI timescales. Hit-score-based evaluations indicated that reservoir operation has induced changes in the drought propagation patterns for both river basins. Due to the contrasting characteristics, the river basins showed a significant variation in the drought propagation time (DPT), with distinct influences from monsoon (Tapi) and snow-melting (Chirchik). The average DPT (average DPT over 12 months) for the reservoir-influenced part of the Tapi (∼ six months) and Chirchik (∼ nine months) basins is higher than that of the natural parts of both basins (Tapi: ∼ four months; Chirchik: ∼ six months) as a result of the natural and anthropogenic storage influence.

Hydrological response to vegetation restoration and urban sprawl in typical hydrologic years within a semiarid river basin in China

Hydrological response to vegetation restoration and urban sprawl in typical hydrologic years within a semiarid river basin in China

Vegetation greening accelerated hydrological drought in two-thirds of river basins over China

Although the vegetation-greening-induced water supply reduction has been widely recognized, little is known about the impacts of vegetation greening on hydrological drought. Here Standardized Water Availability Index (SWAI, based on surface water-balance), driven by evapotranspiration (ET, with vegetation dynamics), was developed to quantify the impacts of vegetation greening on hydrological drought at multiple timescales over China from 1982 to 2015. The ET with vegetation dynamics was modeled by the improved PT-JPL model, and was validated with in-situ observed data from 8 flux tower sites and 4 on-site field experiments (covered with 12 different land-cover types in China). SWAI was also validated with monthly runoff records (from 59 gauging stations over different climatic regimes in China), and proved to effectively capture the response of water surplus/deficit to vegetation dynamics. Results reveal that percentage drought-affected areas increased (increased by 2 % to 9 %) and drought intensity enhanced in two-thirds of Chinese river basins due to vegetation greening. Moreover, in nearly half of the river basins in China, drought duration increased by 0.035–0.131 months, and drought frequency increased by 0.016–0.085 months/34-year. Hydrological drought accelerated by vegetation greening mainly occurred in arid and semi-arid river basins (water-limited areas), while it was not obvious in humid and sub-humid river basins due to limited energy for ET in these areas. Our work and findings provide new insights for understanding the vegetation-induced water resource shortage and have potential applications for government and water managers to timely monitor and assess the balance between ecological restoration and water resources.

BHARAT: a MADM approach to prioritizing the best performing EPS in a semi-arid river basin

BHARAT: a MADM approach to prioritizing the best performing EPS in a semi-arid river basin

Assessment of climate change impact and comparison of downscaling approaches: a case study in a semi-arid river basin

Assessment of climate change impact and comparison of downscaling approaches: a case study in a semi-arid river basin

Optimizing performance assessment of multi-reservoir operations for sustainable water management in a semi-arid region

Abstract Global challenges, such as population growth, rapid urbanization, and the impacts of climate change, are creating unprecedented demands on water resources in semi-arid regions. Meeting the surging needs for irrigation and water supply requires a departure from the limitations of single reservoir systems. Instead, the construction of multi-reservoir systems within semi-arid river basins is imperative. The research employs an integrated reservoir operation approach that facilitates the controlled release of surplus water from upstream reservoirs to downstream ones. The novel Teaching-Learning-Based Optimization (TLBO) model is utilized to determine optimal irrigation releases, subsequently forming the basis for evaluating reservoir operation performance through the lenses of reliability, resilience, and vulnerability. The findings of this study shed light on the performance of these reservoirs under different models. Notably, the Aji-2 reservoir operation exhibits higher levels of reliability and resilience when the TLBO model is employed, surpassing the outcomes of the Linear Programming (LP) model. Conversely, the vulnerability of the Aji-3 reservoir operation is more pronounced with the TLBO model, albeit reduced when compared to actual release years 2005, 2009, and 2013. This study adds to the development of reservoir operation policies that favor reduced vulnerability and increased reliability.

Identification of pollution source and prediction of water quality based on deep learning techniques

Semi-arid rivers are particularly vulnerable and responsive to the impacts of industrial contamination. Prompt identification and projection of pollutant dynamics are crucial in the accidental pollution incidents, therefore required the timely informed and effective management strategies. In this study, we collected water quality monitoring data from a typical semi-arid river. By water quality inter-correlation mapping, we identified the regularity and abnormal fluctuations of pollutant discharges. Combining the association rule method (Apriori) and characterized pollutants of different industries, we tracked major industrial pollution sources in the Dahei River Basin. Meanwhile, we deployed the integrated multivariate long and short-term memory network (LSTM) to forecast principal contaminants. Our findings revealed that (1) biological oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen, total phosphorus, and ammonia nitrogen exhibited high inter-correlations in water quality mapping, with lead and cadmium also demonstrating a strong association; (2) The main point sources of contaminant were coking, metal mining, and smelting industries. The government should strengthen the regulation and control of these industries and prevent further pollution of the river; (3) We confirmed 4 key pollutants: COD, ammonia nitrogen, total nitrogen, and total phosphorus. Our study accurately predicted the future changes in this water quality index. The best results were obtained when the prediction period was 1 day. The prediction accuracies reached 85.85%, 47.15%, 85.66%, and 89.07%, respectively. In essence, this research developed effective water quality traceability and predictive analysis methods in semi-arid river basins. It provided an effective tool for water quality surveillance in semi-arid river basins and imparts a scientific scaffold for the environmental stewardship endeavors of pertinent authorities.

Spatially distributed bivariate meteorological drought analysis using copula technique in a semi-arid river basin of West Bengal, India

Spatially distributed bivariate meteorological drought analysis using copula technique in a semi-arid river basin of West Bengal, India

Climate change impact on crop stress and food security in a semi-arid river basin

Abstract This investigation explores the spatio-temporal variations of aridity across the Sabarmati River basin (SRB), India, using rainfall and temperature datasets for the baseline (1951–2019) and future (2020–2100) periods. The projected changes are analysed using a multi-model ensemble of five general circulation models under two representative concentration pathways (RCPs). The long-term variation and dependency between the aridity index (AI) and other climate indices are explored. Further, the sensitivity of Kharif and Rabi crops to atmospheric warming is investigated using anthesis heat stress (AHS) at the district level. The results project increased rainfall and temperature at the end of the 21st century. The projected rise in AI denotes a transition from semi-arid to sub-humid conditions in parts of the SRB, particularly the southern SRB. However, AI shows a stronger positive association with rainfall compared to temperature, which drives the basin towards moisture-sufficient conditions. High to very high AHS levels are noted for the Kharif and Rabi crops in all the districts. The escalating severe temperature episodes during RCP8.5 may significantly impact crop stress and food security in the SRB. Thus, there is a need to adopt resilient agricultural practices to overcome the negative impact of increasing temperatures in the future.

Groundwater quality and its implications for domestic and agricultural water supplies in a semi-arid river basin of Niger

Groundwater quality and its implications for domestic and agricultural water supplies in a semi-arid river basin of Niger

Groundwater vulnerability assessment for drinking water suitability using Fuzzy Shannon Entropy model in a semi-arid river basin

Groundwater protection against geogenic and anthropogenic diffuse pollutants are of preeminent importance for convoying groundwater-dependent hydro-aquatic ecosystems and safeguarding human health by securing a safe and sustainable water security plan. Mapping groundwater vulnerability to pollution represents a topical area of research where traditional models suffer from inherent prejudices. A novel approach to identify groundwater vulnerable zones is thus presented in this study by combining Fuzzy Shannon Entropy (FSE) with a decision support algorithm to replace DRASTIC, GOD and other related methods. We proposed a contemporary “FSE-GVI″ framework for assessing aquifer vulnerability, which for the first time expands and redesigns the seven original geological and hydrogeological parameters with geochemical and anthropogenic factors. Applying such technique weights of 13 geo-environmental and hydrogeological factors (slope, soil, pH, recharge), and anthropogenic factors (land use land cover, population density, groundwater based schemes for irrigation) has been optimized. The computed map has been categorized into very high (10.82%), high (23.20%), moderate (29.29%), low (25.02%) and very low (11.64%).The groundwater of the river basin is rated on a scale of excellent, good, poor, very poor and unfit for consumption. The model is compared to 74 groundwater quality data, and the findings demonstrate an excellent correlation between water quality index (r = 0.84), Total dissolve solids (70%), iron (72%), hardness (85%) and alkalinity levels (75%).The findings of the research reveals 27.3 % of the sampling sites (villages) under poor water quality and 23.21% of very high vulnerable zone which requires competent planning, development, managerial technique to safeguard groundwater resources.

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT (Australia-wide Machine Learning ET for Trees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R2 of 0.94 (RMSE 6.63 mm period−1) and 0.92 (RMSE 6.89 mm period−1), respectively. In comparison, correlation between in-situ ET and a national ET product returned R2 of 0.44 (RMSE 34.08 mm period−1) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

Assessment of vulnerability to water shortage in semi-arid river basins: The value of demand reduction and storage capacity

Interest in securing reliable water supplies has increased due to climate change and rapid population growth. This challenge is significant in growing areas with limited water supplies. To meet water demands, water managers are considering new storage infrastructure to increase the reliability of water supplies while also identifying opportunities to reduce water use per person. Although these strategies change water consumption patterns, their success at reducing shortages across space and time for different climate change scenarios remains unclear. In this paper, population- and climate-dependent future water supply and demand models are developed and integrated into a water allocation model calibrated for the South Platte River Basin of Colorado. Eight future climate scenarios are simulated using four statistically downscaled models from the Coupled Model Inter-Comparison Project Phase 5 (CMIP5) with two Representative Concentration Pathways (RCP). Lastly, findings from the water allocation model simulations are generalized beyond the study area using a novel approach by introducing dimensionless indices to characterize water shortage and basin conditions. Results reveal a threshold ratio of total storage capacity to mean water supply with a value of 0.64 above which additional storage has no effect on total water shortages. This threshold communicates the limitation of building storage infrastructure as a strategy to adapt to decreasing average water supplies for basins considering increasing storage capacity. However, basins with low current capacity are likely to fall below the threshold and could invest in reservoirs to mitigate future shortages.

Groundwater Variability in a Semi-Arid River Basin, Central India

The Betwa River basin, a semi-arid catchment that has been classified as a major hotspot of groundwater depletion in Central India. The rainfall and streamflow intermittency have affected agricultural practices due to the variability of groundwater availability for irrigation. This study evaluates the spatial and temporal variations of groundwater level (GWL) in the last 25 years (1993–2018) in the catchment. We applied a nonparametric Seasonal Trend decomposition based on the Loess (STL) method to decompose the GWL time series into the seasonal, trend, and remainder components. We observed that the GWL in the northeastern regions of the basin has depleted about 3–5 mbgl in the last two decades. During the same period, the basin has experienced a reduction in the rainfall magnitude (2.07 mm/yr). We observed that the overexploitation of groundwater for irrigation and rainfall variability have greatly impacted the GWL condition in the study area. Further, if the groundwater extraction continues at present rates, the Betwa River basin may experience severe depletion in the future.

A proposal of an Irrigation Sustainability Index for agricultural basins: application in a semi-arid river basin

A proposal of an Irrigation Sustainability Index for agricultural basins: application in a semi-arid river basin