Water Conservation Research Articles

Controlling soil erosion and landslides through ecosystem-based adaptation interventions in the hilly landscape of western Rwanda

Ecosystem-based Adaptation interventions such as protective vegetation, soil and water conservation measures and re-vegetation of degraded land have shown promise in reducing soil erosion and landslides occurrence. The western province of Rwanda has experienced destructive natural hazards especially soil erosions, floods and landslides. This study aimed to assess the contribution of Ecosystem-based Adaptation interventions on the reduction of soil erosion and landslides in the hilly landscape of Western Rwanda with a case study of Rubyiro sub-catchment in Rusizi District. Methods used in data collection comprised remote sensing techniques combined with a questionnaire survey to collect perceptions of farmers conducting agricultural activities in the catchment where Rusizi District has implemented Ecosystem-based Adaptation (EbA) interventions. The Revised Universal Soil Loss Equation (RUSLE) model combined with Geographic Information System (GIS) and remote sensing tools were used to assess soil loss pre- and post-EbA interventions. The results of the survey indicated that after four years of EbA interventions, the number of landslide occurrences was reduced at a rate of 62.6 %. The respondents who appreciated forest restoration to minimize landslides were 72.4 %, progressive terraces 26.1 % and bench terraces 1.5 %. The estimated average annual soil losses were 11.9 tons/ha/year, 17.6 tons/ha/year, 10.1 tons/ha/year, 9.3 tons/ha/year in 2017, 2018, 2021 and 2022, respectively. This indicates a reduction of 8.3 tons/ha/year from 2018 to 2022 as opposed to an increase of 5.7 tons/ha/year recorded from 2017 to 2018. Thus, EbA interventions made a great contribution to the reduction of soil erosion and landslides in the Rubyiro sub-catchment, and they can be recommended in other similar hilly landscapes.

The Influence of Microalgae Fertilizer on Soil Water Conservation and Soil Improvement: Yield and Quality of Potted Tomatoes

We aim to study the impact of microalgae fertilizer on soil nutrients, water conservation and crop yield and quality while also determining the optimal ratio of microalgae fertilizer to chemical fertilizer. Using “Xinoufen No.9” tomatoes as the test subject, we conducted pot experiments with four different treatments: control with 100% chemical fertilizer (CK), T1 (25% microalgae fertilizer + 75% regular chemical fertilizer), T2 (75% microalgae fertilizer + 25% regular chemical fertilizer) and T3 (100% microalgae fertilizer). The results show that an increased application of microalgae fertilizer enhanced the soil organic matter, ammonium nitrogen, available phosphorus and potassium content. T3 showed the most improvement followed by T2. The co-application of microalgae fertilizer with chemical fertilizer can significantly increase the stem girth, plant height and yield of tomatoes. At the same time, microalgae fertilizer effectively regulates leaf stomatal conductance, promoting tomato leaf respiration. As the stomatal conductance increases, the transpiration rate and net photosynthesis rate of all treatments improve, followed by a decline in intercellular CO2 concentration, with T2 exhibiting the best performance. Among all treatments, T2 treatment yielded the highest per-plant production (0.630 kg), followed by T3 (0.521 kg). This is because the microalgae fertilizer promotes the distribution of photosynthetic products to the fruit, enhancing the yield and quality of tomatoes. Additionally, the microalgae fertilizer also increases the content of soluble sugars, soluble protein, vitamin C and lycopene in the fruit while reducing the nitrate content. Compared to the control group CK, T2 increases the content of soluble sugars, vitamins and lycopene by 26.74%, 39.29% and 158.31%, respectively. Microalgae fertilizer also helps to improve soil water and thermal conditions, enhancing the water-use efficiency of tomatoes. Compared to CK, the water-use efficiency of T2 treatment increased by 54.05%. Correlation analysis indicates that water and fertilizer factors significantly affect tomato yield, with a correlation exceeding 70%. The net photosynthesis and transpiration rates significantly influence fruit quality, with correlations above 80%. By applying microalgae fertilizer, the efficiency of water and fertilizer use can be effectively improved, thus achieving the goal of water conservation and quality enhancement. Therefore, through comprehensive analysis, using the membership function method of indicators such as soil environment, crop yield, fruit quality and water-use efficiency, it is concluded that T2 is the optimal fertilization treatment. This study provides theoretical support for the application of microalgae biofertilizer technology in the cultivation of tomatoes and other vegetables in the northern, cold and arid regions.

Eco-friendly dentistry: Understanding the environmental impact in dental practice

Dental practices, akin to other branches of the healthcare industry, are vital for public health. However, they also play a part in environmental detriment via waste production, energy consumption, and the management of hazardous substances. This review endeavors to conduct a thorough analysis of the environmental impact stemming from dental facilities, precisely identifying main contributors to pollution and waste and will explore pragmatic approaches and remedies for fostering a greener, more sustainable dental sector focusing on waste reduction, energy efficiency, water conservation, and sustainable procurement. This article also underscores the significance of societal principles, community welfare, involving stakeholders, financial advantages, crafting policies, and demonstrating leadership to translate the idea of eco-friendly dentistry into tangible action. Green dentistry advocates for the utilization of biodegradable, non-toxic, and mercury-free materials and products to reduce both the quantity and harmfulness of dental waste. Concurrently, bio-dentistry embraces a holistic patient care approach while prioritizing environmentally conscious practices

County-Level Cultivated Land Quality Evaluation Using Multi-Temporal Remote Sensing and Machine Learning Models: From the Perspective of National Standard

Scientific evaluation of cultivated land quality (CLQ) is necessary for promoting rational utilization of cultivated land and achieving one of the Sustainable Development Goals (SDGs): Zero Hunger. However, the CLQ evaluation system proposed in previous studies was diversified, and the methods were inefficient. In this study, based on China’s first national standard “Cultivated Land Quality Grade” (GB/T 33469-2016), we constructed a unified county-level CLQ evaluation system by selecting 15 indicators from five aspects—site condition, environmental condition, physicochemical property, nutrient status and field management—and used the Delphi method to calculate the membership degree of the indicators. Taking Jimo district of Shandong Province, China, as a case study, we compared the performance of three machine learning models, including random forest, AdaBoost, and support vector regression, to evaluate CLQ using multi-temporal remote sensing data. The comprehensive index method was used to reveal the spatial distribution of CLQ. The results showed that the CLQ evaluation based on multi-temporal remote sensing data and machine learning model was efficient and reliable, and the evaluation results had a significant positive correlation with crop yield (r was 0.44, p < 0.001). The proportions of cultivated land of high-, medium- and poor-quality were 27.43%, 59.37% and 13.20%, respectively. The CLQ in the western part of the study area was better, while it was worse in the eastern and central parts. The main limiting factors include irrigation capacity and texture configuration. Accordingly, a series of targeted measures and policies were suggested, such as strengthening the construction of farmland water conservancy facilities, deep tillage of soil and continuing to construct well-facilitated farmland. This study proposed a fast and reliable method for evaluating CLQ, and the results are helpful to promote the protection of cultivated land and ensure food security.

Recycled Jute Non-Woven Material Coated with Polyaniline/TiO2 Nanocomposite for Removal of Heavy Metal Ions from Water.

Growing volumes of textile waste and heavy metal pollution of water are emerging environmental challenges. In an attempt to tackle these issues, a non-woven sorbent based on jute fibers was fabricated by recycling the textile waste from the carpet industry. The influence of contact time, concentration, pH and temperature on the sorption of lead and copper ions from aqueous solutions was studied. In order to enhance the sorption capacity of the non-woven material, in situ synthesis of polyaniline (PANI) in the presence of TiO2 nanostructures was performed. The contribution of TiO2 nanoparticles and TiO2 nanotubes to the uniformity of PANI coating and overall sorption behavior was compared. Electrokinetic measurements indicated increased swelling of modified fibers. FTIR and Raman spectroscopy revealed the formation of the emeraldine base form of PANI. FESEM confirmed the creation of the uniform nanocomposite coating over jute fibers. The modification with PANI/TiO2 nanocomposite resulted in a more than 3-fold greater sorption capacity of the material for lead ions, and a 2-fold greater absorption capacity for copper ions independently of applied TiO2 nanostructure. The participation of both TiO2 nanostructures in PANI synthesis resulted in excellent cover of jute fibers, but the form of TiO2 had a negligible effect on metal ion uptake.

Using Artificial Neural Networks to Predict Leakage Location in Water Distribution Networks

One of the major types of water wastage in a distribution network is the leakage that occurs in pipes or other network components such as connections. Leaks in urban water supply networks impose many costs and workforce on governments and related organizations annually. If the cause of leakage is traced to the cracks and slits on various parts of a network, the amount of leakage from the location of the crack is said to be directly associated with the amount of pressure at that point. To trace leakage in water distribution networks, this study introduced a method based on hydraulics modeling and the inverse solution of flow equations to predict the location and amount of leakage in water distribution networks, by considering the values of the measured pressure in some network nodes. For this, a hydraulic model of the network under study was provided in the EPANET Hydraulic Analysis software, and the network analysis of various values and states of hypothetical leaks led to obtaining pressure values in the different nodes of the network via modeling water modeling under a steady state. Then, the artificial neural network, having been trained, was used to provide measured pressures in some network nodes at the testing hour as input data to the neural network to locate possible leaks in the water distribution network and to predict their approximate values. The findings were found to enjoy desirable accuracy. DOI: https://doi.org/10.52783/pst.835

Soil erodibility and hillslope erosion processes affected by vegetation restoration duration

Restoring vegetation is an effective way to control regional erosion as well as reduce soil erodibility. However, it is not clear how the vegetation restoration duration affects soil erodibility and how it further influences soil erosion processes. Therefore, the soil physicochemical properties and comprehensive soil erodibility index (CSEI) at five sampling sites with 3, 20, 55, 80 and 100 years of vegetation restoration were investigated in this study. A simulated rainfall with intensities of 60, 90, and 120 mm h−1 was conducted on three slopes with gradients of 10°, 20°, and 30° by using rare earth element oxides (Ho2O3 and Sm2O3) as tracers to quantify interrill and rill erosion. The results revealed a decreasing trend in both the CSEI and sediment concentration with increasing vegetation restoration duration. Compared to that at the site with 3 years of vegetation restoration, the CSEI at the sites with 20, 55, 80, and 100 years of restoration was reduced by 35.2 %, 39.7 %, 92.8 %, and 67.1 %, respectively. Interrill erosion dominated the hillslope erosion processes and contributed more than 76.9 % to the total erosion amount. By comparing the measured and estimated erosion rates using the equations provided by the Water Erosion Prediction Project (WEPP), significant prediction errors were found. Therefore, relationships among the CSEI, slope gradient and rainfall intensity were established for interrill and rill erosion rate estimation in vegetation restoration areas. This study provides a theoretical basis for evaluating the soil and water conservation benefits of vegetation restoration and for improving soil erosion prediction models within the context of vegetation restoration.

Combining price and non-price interventions for water conservation

Abstract Marginal pricing has long been the instrument of choice to address water conservation challenges. More recently, non-price behavioral interventions have emerged as an alternative. However, there is limited data on the relative efficacies of price and non-price interventions. We report results from long-term field experiments studying unit-level water conservation responses to both price and non-price interventions in the same group of households (n = 64 186 household-days). Conservation habits, attitude-action gaps, principal-agent incongruities, and billing cycles help account for the heterogeneity in response between households, and across time. A non-price behavior modification intervention before the introduction of marginal pricing resulted in a large and significant effect on treated households (33%). The subsequent introduction of marginal volumetric pricing also reduced water use (8%, for previously untreated households). However, this average price effect masks how a large share (21%) of households increased water use, or how a mere 12% of the households accounted for all the aggregate reduction in water use. We investigated such heterogeneous responses as a systematic conservation maximization design question beyond statistical variance in individual responses. We used daily water consumption measurements across three years alongside a household survey to delineate structural and agentic barriers to conservation behavior. Our analysis reveals how combining price and non-price behavioral interventions could hold the key to achieving conservation effects that are both large and persistent.

Global effects of livestock grazing on ecosystem functions vary with grazing management and environment

Grasslands support multiple ecosystem functions and services, and diverse biota, and are critical for human well-being. Grazing is the most pervasive land use in grasslands, but can have damaging effects when poorly managed. How grazing management and the environment interact to affect ecosystem functions globally is less well understood. Addressing this knowledge gap is important if we are to evaluate where (climate region, soil texture, and grassland type), what (livestock type), and how (grazing intensity, grazing regime, and duration) grazing might minimize grassland degradation and sustain healthy grassland functions. We used a systematic meta-analysis to explore the effects of grazing on ecosystem functions (primary production, carbon sequestration, water conservation, nutrient cycle, and decomposition) based on 3917 paired data from 148 studies across the globe. We found that grazing substantially reduced plant productivity (-26%), followed by water conservation (-18%) and carbon sequestration (-19%). The value of most ecosystem functions declined with increasing grazing intensity, and more pronounced negative effects of grazing with mixed-herbivore than single species grazing. Grazing impacts also varied with environmental conditions, with light grazing increasing carbon sequestration in arid regions, but reducing it in semi-arid regions. Further, increasing aridity indirectly weakened the positive impacts of light grazing on ecosystem functions by suppressing grazing effects. Our study suggests that the interactions between grazing management and environmental conditions are critical when assessing the effects of grazing on grassland functions, and this will likely be more important as climates become hotter and drier.

Diffusion of radioactive waste elements from underground water and leachates of phosphate waste forms in pore solution of clay materials

Using through diffusion method at room temperature, migration of RW element simulators (P, Se, Br, Mo, Cs, U) in compacted samples of clay materials of various mineral compositions was studied during porous diffusion from model solutions: underground water and leachates of phosphate waste forms having a total salt content of up to 500 mg/L. Based on the results of experiments, effective diffusion coefficients and sorption distribution coefficients of elements in barrier materials were determined. Numerical models are proposed to describe diffusion transfer of selenium, cesium and uranium depending on porosity, mineral composition of materials, and concentration of elements in pore solution. Patterns of diffusion of elements from solutions of different salt composition were revealed.

Automatic extraction of geological discontinuities of a tunnel surface by integrating multiple features

In water conservancy, transportation, and mining projects, the timely acquisition of geological structural information from tunnels is critical in the analysis of engineering geological problems during the investigation and construction stages. The acquisition of comprehensive and accurate geological information from a tunnel surface remains challenging. This study provides an automatic extraction method for geological discontinuities on a tunnel surface by integrating 2D textural semantic features and 3D geological semantic features. A dense point cloud is generated using multiline parallel sequence images, after which the 3D geological semantic features, including the local geological attitude, are calculated. Through a virtual projection from 3D to 2D, the red, green, and blue (RGB) images and geological semantic images based on views of the interior umbrella arch and the sidewalls of the tunnel surface are obtained. The feature mapping between the 2D textural semantic features and the 3D geological semantic features is determined accordingly. The virtual RGB images and geological semantic images serve as dual inputs for ensemble learning for pixel block segmentation, and the output is a similarity probability tensor that describes the probability that each pixel will belong to its surrounding pixel blocks. The pixel blocks are clustered on the basis of pole and contour plots of their geological attitudes to extract geological discontinuities. Experiments were conducted to confirm and evaluate the feasibility and veracity of the proposed method. The developed method automatically extracts geological discontinuities of a tunnel surface and extends the scope of surveying and mapping through geological remote sensing.

Climate Change Contributions to Water Conservation Capacity in the Upper Mekong River Basin

Climate Change Contributions to Water Conservation Capacity in the Upper Mekong River Basin

Spatio-temporal evolution of water erosion in the western Songnen Plain: Analysis of its response to land use dynamics and climate change

Preventing water erosion is crucial for maintaining ecosystems and ensuring food security, necessitating a comprehensive understanding of the spatial and temporal patterns of water erosion and its underlying drivers. In the context of global warming, analyzing the impacts of land use dynamics and climate change on water erosion contributes to effective land management and sustainability of both industry and agriculture. This study aims to analyze the spatial distribution of water erosion in the western Songnen Plain from 1990 to 2020 using the Revised Universal Soil Loss Equation (RUSLE), with a focus on assessing the impacts of land use and climate on water erosion. The results revealed a 7.1 % increase in the area experiencing water erosion above light levels in the western Songnen Plain. The hotspots for water erosion were located in the southeast and northwest of the study area. The rapid expansion of farmland and land salinization, leading to reduced vegetation cover and soil property deterioration, were the main causes of intensified water erosion in the region before 2000. Although water erosion was slightly alleviated after 2000, the further expansion of farmland, the worsened water erosion intensity in alkaline land and frequent extreme weather still posed serious threats to water erosion in the study area. Water erosion was positively correlated with temperature and dry/wet alternation events, including frequency, duration, and severity. In addition, land use type was the main factor influencing the heterogeneous distribution of water erosion in the western Songnen Plain, whose interaction with dry/wet alternation events had the strongest explanatory power. Therefore, this study calls for the implementation of soil and water conservation measures to mitigate the impacts of land cultivation, salinization, and climate change on water erosion.

Global Supply Chains are Becoming Conducive to Water Saving in India

Global Supply Chains are Becoming Conducive to Water Saving in India

Runoff and erosion reduction benefits of vegetation during natural succession on fallow grassland slopes

Vegetation restoration is an effective and important measure for controlling soil erosion in arid and -arid regions. Both its aboveground and underground parts play a crucial role in controlling surface runoff and soil detachment on slopes. But how much the parts of vegetation contribute to the runoff and sediment reducing benefits of rill erosion on slopes is unclear. We used grassland slopes at four successional stages for simulated scouring experiments to observe how successional vegetation community structures, root characteristics, and soil structures contribute to erosion and sand production. Initial flow production time increased, and total runoff decreased. Under the scour intensities, the 11-year slope had the lowest flood peak and volume and the greatest runoff reduction benefit. The 25-year slope had the lowest sand peak and volume and the greatest sediment reduction benefit. As scour intensity increased, runoff reduction effect of vegetation at the successional stages decreased; the sediment reduction benefit remained high. PLS-PM analysis showed that the indirect effects of the aboveground and underground parts of vegetation on sand production were −0.364 and −0.439, respectively. Aboveground parts mainly embodied the regulation of runoff, in which stem count, humus mass, and biomass were the main factors affecting runoff and sand production. Underground parts mainly reflected their soil structure improvement, in which root volume density, root surface area density, and root mass density are the main explanatory variables. The direct effects of runoff and soil structure on slope rill erosion were 0.330 and −0.616, respectively, suggesting the stability of soil structure is the primary factor affecting the sand production, not erosion energy. The results provide a reference for scientific assessment of the key role of natural vegetation restoration in regional soil erosion control and the development of biological measures for soil and water conservation on the slopes of the Loess Plateau.

Research constituent, intellectual structure and current trends in environmental sustainability-an analytical retrospective

Climate change is a paramount problem for humanity, representing a substantial danger to all living organisms. Industrialization, a vital factor for economic progress, has resulted in global warming, posing a threat to the long-term viability of our ecosystem. Currently, a wide range of techniques and technologies are being used to guarantee the preservation of the environment for future generations. This study employed data from the Scopus database to do topic modeling. Authors used latent Dirichlet allocation to extract research themes related to environmental sustainability from a corpus of 4023 research articles published between 1976 and 2022. By utilizing clustering methodologies to analyze the collection of words, Authors successfully forecasted two, five, and ten study subjects, emphasizing specific domains that necessitate additional investigation by scholars. Based on coherence ratings, five subjects have been identified as prospective study areas requiring further scientific exploration. The results of our research emphasize the significance of incorporating environmentally-friendly technologies in different industries to promote a long-lasting and eco-friendly ecosystem. In addition, authors recommend prioritizing implementing sustainable and environmentally friendly technologies, improving the management of ecosystems, encouraging water conservation, promoting agricultural advancements, and advancing renewable energy resources as crucial strategies for protecting the environment and enhancing ecological conditions. This analysis illuminates current research trends in environmental sustainability and potential pathways for future investigation and intervention.

The influence of operational factors on the photocatalytic degradation of methylene blue dye in aqueous Sr-Au-ZnO suspensions under UV-A light

Any of several processes that break down dyes, ideally into harmless chemicals, is referred to as industrial dye degradation. Water waste discharges various colors, particularly those used in the textile industry like methyl red and methylene blue, into ecosystems, leading to significant pollution of the water supply. Under UV-A irradiation, the photocatalytic degradation of a commercial heterocyclic aromatic chemical molecule called methylene blue (MB) has been investigated using an aqueous solution of Sr-Au-ZnO as a photocatalyst. Research has been done on how different process characteristics affect the degradation process. For the mineralization of MB dye under UV-A light, it was found that the optimized Sr-Au-ZnO was more effective than commercial catalysts (ZnO and benchmark photocatalyst Degussa P25), single metal dopants (Sr-ZnO, Au-ZnO), and prepared ZnO. The effects of operational parameters, such as the quantity of photocatalyst, dye concentration, and starting pH, on the photo-mineralization of MB are analyzed before optimal values are given. Chemical oxygen demand (COD) measurements have confirmed that MB is mineralized. Using GC–MS analysis, the intermediates produced during photodegradation were predicted, and an appropriate degradation pathway was suggested. This procedure can be used for treating wastewater from sewage since optimized Sr-Au-ZnO is reusable.

Experimental performance of smart irrigation systems using IoT

In agriculture field soil is a crucial determinant of plant development, primarily in irrigated environments. Nowadays there are several ways for assessing soil quality on a density or suspense basis. To develop, all plants need a specific amount of moisture level. PI involves cutting-edge technologies such as the Internet of Things (IoT), Wireless Sensor Networks (WSN), and cloud computing. In this method presents an overview of the soft computing methods based on the PI concept and architecture, including the most common wireless technologies. Then, a real-time IoT-based intelligent irrigation system is designed as a proof of concept. Several wireless sensor nodes are deployed to monitor both soil moisture and temperature. Sensed data are transmitted to the gateway through the Messaging Queuing Telemetry Transport (MQTT) communication protocol. Root based findings depict that the proposed work increases crop growth and productivity and decreases water wastage more than other state-of-the-art strategies. ANFIS method to predict the plant growth level based on the fuzzy rule. Wireless communication technology allows for the automation of different devices and real-time analysis of data collected by these sensors. The IoT (Internet of Things) system demonstrates improved plant growth. Furthermore, the application used in the plant's worst conditions and situations has provided the best sources for appropriate plant growth..

Exploring the role of microtopography in the spatial pattern of soil water at the hillslope scale based on high-resolution observation

Terraces have consistently been regarded as crucial measures for water conservation and vegetation restoration, particularly in mountainous environments. However, the hydrological effects of terraces in artificial forests have been rarely studied. In this study, detailed topography, soil properties and high-resolution (30 sites) soil water data (0–70 cm) observed from March 2015 to March 2016 were collected at hillslope scale (0.2 ha). The effects of static (soil properties and topography) and dynamic factors (precipitation) on the dynamics and variability of soil water content (SWC) were studied based on statistical methods, temporal stability and variance decomposition methods. The results showed that slope, topographic wetness index (TWI) and microtopography were the main control factors of different soil layers (shallow, middle and deep layer), which explained 37.2 %, 48.6 % and 47.3 % of the total variance of corresponding soil layers, respectively. Microtopography primarily affects deep layer soil water (40–70 cm). Level terraces show significantly higher soil water content (SWC) (30.89 ± 5.28 %) compared to gentle slopes (25.40 ± 5.33 %), steep slopes (27.05 ± 5.74 %), and scarps (19.71 ± 4.43 %) (P<0.05). Temporal stability of soil water varied across different depths, with shallow layer soil water exhibiting significantly weaker stability compared to other depths, the most representative point of different soil layers was located on relatively flat terraces. Decomposition of spatial variance revealed that the time-invariant component was the primary contributor to the total spatial variance, with a mean value over 70 %. These results highlight that microtopography could weaken the influence of soil-terrain factors on soil water, and the implementation of level terraces can enhance hillslope hydrological conditions in the Rocky Mountain area.

Adoption of Black Plastic Mulch as a Coping Strategy to Water Conservation Among Vegetable Farmers in Kisoro Municipality, Kisoro District

The study was about the adoption of black plastic mulches as a copying strategy to water conservation among smallholder vegetable farmers in Kisoro Municipality, Kisoro district. Farmers in Kisoro District have increasingly adopted black plastic mulch to address these agricultural challenges. The use of black plastic mulch in this region helps in conserving soil moisture, controlling weeds, and enhancing crop yields. It was guided by three specific objectives which were to; establish the socio-economic characteristics of smallholder vegetable farmers, establish the knowledge level on the benefits of black plastic mulch among smallholder vegetable farmers and examine the factors influencing farmer’s decision to adopt black plastic mulch as a coping strategy to water conservation. The study employed a cross-sectional study design that used both quantitative and qualitative approaches. The study used a sample size of 300. The study used questionnaires and interview guide to collect data. The data collected was analysed using Statistical Package for Social Scientists (SPSS). The results revealed that land ownership was a positive and significant factor at (sig. 0.000**), source of income at (sig.0.001*), credit accessibility at (sig.0.002**) and knowledge on use of black plastic mulches at (sig. 0.000**) The study concluded that vegetable farmers were characterized in terms of gender, age, farm size, marital status and level of education. The study also concluded that there was adequate knowledge level on the benefits of black plastic mulch among smallholder vegetable farmers. Such as; leads to higher yields and improved quality of vegetables, increase the growth rate of vegetables, reduce the risk of root damage, weed suppression, moisture conservation and contribute to soil health and protect the soil from wind and water erosion. The study finally concluded that there were significant and non-significant factors influencing farmer’s decision to adopt black plastic mulch as a coping strategy to water conservation among smallholder vegetable farmers which included; land ownership, limited extension training, source of income, knowledge on use of black plastic mulches and credit accessibility and non-significant ones were; un-availability of labour, infrastructure development, level of education, price of black plastic mulch and farm size.